ࡱ> u999rt99999999999999999999999999999999999999999999999999999999999` N&bjbj &N 1*E*E*ER|E<iiiZ jch%*U @Tj P f f {/!4#0S!%%%%%%%$l%h%pѼ%Qi=" N ="="Ѽ%ggf f @"%V"V"V"=" gf if %V"="%V"V"A"*h^i##f U *\G"k"#8%0h%" D%NM"" D%,##D%i##d!Nv!08V"!,"%d!d!d!Ѽ%Ѽ%pV"jd!d!d!h%="="="="$ ui  u*l8 VEZ gggg Annexes  TOC \o "1-3" \h \z  HYPERLINK \l "_Toc226519617" A1 ANNEX 1: Key Categories  PAGEREF _Toc226519617 \h 258  HYPERLINK \l "_Toc226519618" A1.1 Key Category Analysis  PAGEREF _Toc226519618 \h 258  HYPERLINK \l "_Toc226519619" A2 ANNEX 2: Detailed Discussion of Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion  PAGEREF _Toc226519619 \h 274  HYPERLINK \l "_Toc226519620" A3 ANNEX 3: Other Detailed Methodological Descriptions  PAGEREF _Toc226519620 \h 275  HYPERLINK \l "_Toc226519621" A3.1 FUELS DATA  PAGEREF _Toc226519621 \h 275  HYPERLINK \l "_Toc226519622" A3.2 NAEI Source Categories and IPCC Equivalents  PAGEREF _Toc226519622 \h 278  HYPERLINK \l "_Toc226519623" A3.3 Energy (CRF sector 1)  PAGEREF _Toc226519623 \h 285  HYPERLINK \l "_Toc226519624" A3.3.1 Basic Combustion Module  PAGEREF _Toc226519624 \h 285  HYPERLINK \l "_Toc226519625" A3.3.2 Conversion of Energy Activity Data and Emission Factors  PAGEREF _Toc226519625 \h 296  HYPERLINK \l "_Toc226519626" A3.3.3 Energy Industries (1A1)  PAGEREF _Toc226519626 \h 297  HYPERLINK \l "_Toc226519627" A3.3.4 Manufacturing Industries and Construction (1A2)  PAGEREF _Toc226519627 \h 302  HYPERLINK \l "_Toc226519628" A3.3.5 Transport (1A3)  PAGEREF _Toc226519628 \h 303  HYPERLINK \l "_Toc226519629" A3.3.6 Other Sectors (1A4)  PAGEREF _Toc226519629 \h 339  HYPERLINK \l "_Toc226519630" A3.3.7 Other (1A5)  PAGEREF _Toc226519630 \h 339  HYPERLINK \l "_Toc226519631" A3.3.8 Fugitive Emissions From fuels (1B)  PAGEREF _Toc226519631 \h 341  HYPERLINK \l "_Toc226519632" A3.3.9 Stored Carbon  PAGEREF _Toc226519632 \h 356  HYPERLINK \l "_Toc226519633" A3.4 Industrial Processes (crf sector 2)  PAGEREF _Toc226519633 \h 358  HYPERLINK \l "_Toc226519634" A3.4.1 Mineral Processes (2A)  PAGEREF _Toc226519634 \h 358  HYPERLINK \l "_Toc226519635" A3.4.2 Chemical Industry (2B)  PAGEREF _Toc226519635 \h 360  HYPERLINK \l "_Toc226519636" A3.4.3 Metal Production (2C)  PAGEREF _Toc226519636 \h 361  HYPERLINK \l "_Toc226519637" A3.4.4 Production of Halocarbons and SF6 (2E)  PAGEREF _Toc226519637 \h 364  HYPERLINK \l "_Toc226519638" A3.4.5 Consumption of Halocarbons and SF6 (2F)  PAGEREF _Toc226519638 \h 364  HYPERLINK \l "_Toc226519639" A3.5 SOLVENT AND OTHER PRODUCT USE (CRF SECTOR 3)  PAGEREF _Toc226519639 \h 364  HYPERLINK \l "_Toc226519640" A3.6 AGRICULTURE (CRF SECTOR 4)  PAGEREF _Toc226519640 \h 365  HYPERLINK \l "_Toc226519641" A3.6.1 Enteric Fermentation (4A)  PAGEREF _Toc226519641 \h 365  HYPERLINK \l "_Toc226519642" A3.6.2 Manure Management (4B)  PAGEREF _Toc226519642 \h 368  HYPERLINK \l "_Toc226519643" A3.6.3 Agricultural Soils (4D)  PAGEREF _Toc226519643 \h 374  HYPERLINK \l "_Toc226519644" A3.6.4 Field Burning of Agricultural Residues (4F)  PAGEREF _Toc226519644 \h 380  HYPERLINK \l "_Toc226519645" A3.7 Land Use, land use Change and Forestry (CRF Sector 5)  PAGEREF _Toc226519645 \h 381  HYPERLINK \l "_Toc226519646" A3.7.1 Land Converted to Forest Land (5A2)  PAGEREF _Toc226519646 \h 381  HYPERLINK \l "_Toc226519647" A3.7.2 Land Use Change and Soils (5B2, 5C2, 5E2)  PAGEREF _Toc226519647 \h 385  HYPERLINK \l "_Toc226519648" A3.7.3 Changes in stocks of carbon in non-forest biomass due to land use change (5B2, 5C2, 5E2)  PAGEREF _Toc226519648 \h 391  HYPERLINK \l "_Toc226519649" A3.7.4 Biomass Burning due to De-forestation (5C2, 5E2)  PAGEREF _Toc226519649 \h 393  HYPERLINK \l "_Toc226519650" A3.7.5 Biomass Burning Forest Wildfires (5A2)  PAGEREF _Toc226519650 \h 394  HYPERLINK \l "_Toc226519651" A3.7.6 Liming of Agricultural Soils (5B1, 5C1)  PAGEREF _Toc226519651 \h 395  HYPERLINK \l "_Toc226519652" A3.7.7 Lowland Drainage (5B1)  PAGEREF _Toc226519652 \h 396  HYPERLINK \l "_Toc226519653" A3.7.8 Changes in Stocks of Carbon in Non-Forest Biomass due to Yield Improvements (5B1)  PAGEREF _Toc226519653 \h 396  HYPERLINK \l "_Toc226519654" A3.7.9 Peat Extraction (5C1)  PAGEREF _Toc226519654 \h 396  HYPERLINK \l "_Toc226519655" A3.7.10 Harvested Wood Products (5G)  PAGEREF _Toc226519655 \h 397  HYPERLINK \l "_Toc226519656" A3.7.11 Emissions of Non-CO2 Gases from Disturbance Associated with Land use Conversion  PAGEREF _Toc226519656 \h 398  HYPERLINK \l "_Toc226519657" A3.7.12 Emissions of N2O due Disturbance Associated with Land Use Conversion  PAGEREF _Toc226519657 \h 398  HYPERLINK \l "_Toc226519658" A3.7.13 Methods for the Overseas Territories and Crown Dependencies  PAGEREF _Toc226519658 \h 400  HYPERLINK \l "_Toc226519659" A3.8 Waste (CRF sector 6)  PAGEREF _Toc226519659 \h 401  HYPERLINK \l "_Toc226519660" A3.8.1 Solid Waste Disposal on Land (6A)  PAGEREF _Toc226519660 \h 401  HYPERLINK \l "_Toc226519661" A3.8.2 Flaring and Energy Recovery  PAGEREF _Toc226519661 \h 404  HYPERLINK \l "_Toc226519662" A3.8.3 Wastewater Handling (6B)  PAGEREF _Toc226519662 \h 407  HYPERLINK \l "_Toc226519663" A3.8.4 Waste Incineration (6C)  PAGEREF _Toc226519663 \h 410  HYPERLINK \l "_Toc226519664" A3.9 Emissions From the UKs Crown Dependencies and Overseas Territories  PAGEREF _Toc226519664 \h 411  HYPERLINK \l "_Toc226519665" A3.9.1 Crown Dependencies: the Channel Islands and the Isle of Man  PAGEREF _Toc226519665 \h 416  HYPERLINK \l "_Toc226519666" A3.9.2 Overseas Territories: Bermuda, Falklands Islands, Montserrat, the Cayman Islands and Gibraltar  PAGEREF _Toc226519666 \h 420  HYPERLINK \l "_Toc226519667" A4 ANNEX 4: Comparison of CO2 Reference and Sectoral Approaches  PAGEREF _Toc226519667 \h 428  HYPERLINK \l "_Toc226519668" A4.1 Estimation of CO2 from the Reference Approach  PAGEREF _Toc226519668 \h 428  HYPERLINK \l "_Toc226519669" A4.2 Discrepancies between the IPCC Reference and Sectoral Approach  PAGEREF _Toc226519669 \h 428  HYPERLINK \l "_Toc226519670" A4.3 Time series of differences in the IPCC Reference and Sectoral Inventories  PAGEREF _Toc226519670 \h 429  HYPERLINK \l "_Toc226519671" A5 ANNEX 5: Assessment of Completeness  PAGEREF _Toc226519671 \h 430  HYPERLINK \l "_Toc226519672" A5.1 Assessment of completeness  PAGEREF _Toc226519672 \h 430  HYPERLINK \l "_Toc226519673" A6 ANNEX 6: Additional Information Quantitative Discussion of 2007 Inventory  PAGEREF _Toc226519673 \h 432  HYPERLINK \l "_Toc226519674" A6.1 Energy Sector (1)  PAGEREF _Toc226519674 \h 432  HYPERLINK \l "_Toc226519675" A6.1.1 Carbon Dioxide  PAGEREF _Toc226519675 \h 432  HYPERLINK \l "_Toc226519676" A6.1.2 Methane  PAGEREF _Toc226519676 \h 433  HYPERLINK \l "_Toc226519677" A6.1.3 Nitrous Oxide  PAGEREF _Toc226519677 \h 433  HYPERLINK \l "_Toc226519678" A6.1.4 Nitrogen Oxides  PAGEREF _Toc226519678 \h 434  HYPERLINK \l "_Toc226519679" A6.1.5 Carbon Monoxide  PAGEREF _Toc226519679 \h 434  HYPERLINK \l "_Toc226519680" A6.1.6 Non Methane Volatile Organic Compounds  PAGEREF _Toc226519680 \h 434  HYPERLINK \l "_Toc226519681" A6.1.7 Sulphur Dioxide  PAGEREF _Toc226519681 \h 435  HYPERLINK \l "_Toc226519682" A6.2 Industrial Processes sector (2)  PAGEREF _Toc226519682 \h 438  HYPERLINK \l "_Toc226519683" A6.2.1 Carbon Dioxide  PAGEREF _Toc226519683 \h 438  HYPERLINK \l "_Toc226519684" A6.2.2 Methane  PAGEREF _Toc226519684 \h 438  HYPERLINK \l "_Toc226519685" A6.2.3 Nitrous Oxide  PAGEREF _Toc226519685 \h 438  HYPERLINK \l "_Toc226519686" A6.2.4 Hydrofluorocarbons  PAGEREF _Toc226519686 \h 438  HYPERLINK \l "_Toc226519687" A6.2.5 Perfluorocarbons  PAGEREF _Toc226519687 \h 438  HYPERLINK \l "_Toc226519688" A6.2.6 Sulphur Hexaflouride  PAGEREF _Toc226519688 \h 439  HYPERLINK \l "_Toc226519689" A6.2.7 Nitrogen Oxides  PAGEREF _Toc226519689 \h 439  HYPERLINK \l "_Toc226519690" A6.2.8 Carbon Monoxide  PAGEREF _Toc226519690 \h 439  HYPERLINK \l "_Toc226519691" A6.2.9 Non Methane Volatile Organic Compounds  PAGEREF _Toc226519691 \h 439  HYPERLINK \l "_Toc226519692" A6.2.10 Sulphur Dioxide  PAGEREF _Toc226519692 \h 439  HYPERLINK \l "_Toc226519693" A6.3 Solvents and Other Product Use sector (3)  PAGEREF _Toc226519693 \h 445  HYPERLINK \l "_Toc226519694" A6.4 Agriculture Sector (4)  PAGEREF _Toc226519694 \h 447  HYPERLINK \l "_Toc226519695" A6.4.1 Methane  PAGEREF _Toc226519695 \h 447  HYPERLINK \l "_Toc226519696" A6.4.2 Nitrous Oxide  PAGEREF _Toc226519696 \h 447  HYPERLINK \l "_Toc226519697" A6.4.3 Nitrogen Oxides  PAGEREF _Toc226519697 \h 447  HYPERLINK \l "_Toc226519698" A6.4.4 Carbon Monoxide  PAGEREF _Toc226519698 \h 447  HYPERLINK \l "_Toc226519699" A6.4.5 Non-Methane Volatile Organic Compounds  PAGEREF _Toc226519699 \h 447  HYPERLINK \l "_Toc226519700" A6.5 Land Use, land use Change and forestry (5)  PAGEREF _Toc226519700 \h 453  HYPERLINK \l "_Toc226519701" A6.5.1 Carbon Dioxide  PAGEREF _Toc226519701 \h 453  HYPERLINK \l "_Toc226519702" A6.5.2 Methane  PAGEREF _Toc226519702 \h 453  HYPERLINK \l "_Toc226519703" A6.5.3 Nitrous Oxide  PAGEREF _Toc226519703 \h 453  HYPERLINK \l "_Toc226519704" A6.5.4 Nitrogen Oxides  PAGEREF _Toc226519704 \h 453  HYPERLINK \l "_Toc226519705" A6.5.5 Carbon Monoxide  PAGEREF _Toc226519705 \h 453  HYPERLINK \l "_Toc226519706" A6.6 Waste (6)  PAGEREF _Toc226519706 \h 456  HYPERLINK \l "_Toc226519707" A6.6.1 Carbon Dioxide  PAGEREF _Toc226519707 \h 456  HYPERLINK \l "_Toc226519708" A6.6.2 Methane  PAGEREF _Toc226519708 \h 456  HYPERLINK \l "_Toc226519709" A6.6.3 Nitrous Oxide  PAGEREF _Toc226519709 \h 456  HYPERLINK \l "_Toc226519710" A6.6.4 Nitrogen Oxides  PAGEREF _Toc226519710 \h 456  HYPERLINK \l "_Toc226519711" A6.6.5 Carbon Monoxide  PAGEREF _Toc226519711 \h 456  HYPERLINK \l "_Toc226519712" A6.6.6 Non-Methane Volatile Organic Compounds  PAGEREF _Toc226519712 \h 457  HYPERLINK \l "_Toc226519713" A6.6.7 Sulphur Dioxide  PAGEREF _Toc226519713 \h 457  HYPERLINK \l "_Toc226519714" A7 ANNEX 7: Uncertainties  PAGEREF _Toc226519714 \h 459  HYPERLINK \l "_Toc226519715" A7.1 Estimation of Uncertainty by Simulation (Approach2)  PAGEREF _Toc226519715 \h 459  HYPERLINK \l "_Toc226519716" A7.1.1 Overview of the Method  PAGEREF _Toc226519716 \h 459  HYPERLINK \l "_Toc226519717" A7.1.2 Review of Recent Improvements to the Monte Carlo Model  PAGEREF _Toc226519717 \h 461  HYPERLINK \l "_Toc226519718" A7.1.3 Review of changes made to the Monte Carlo model since the last NIR  PAGEREF _Toc226519718 \h 462  HYPERLINK \l "_Toc226519719" A7.1.4 Quality Control Checks on the Monte Carlo Model Output  PAGEREF _Toc226519719 \h 462  HYPERLINK \l "_Toc226519720" A7.2 Uncertainties according to gas  PAGEREF _Toc226519720 \h 463  HYPERLINK \l "_Toc226519721" A7.2.1 Carbon Dioxide Emission Uncertainties  PAGEREF _Toc226519721 \h 463  HYPERLINK \l "_Toc226519722" A7.2.2 Methane Emission Uncertainties  PAGEREF _Toc226519722 \h 467  HYPERLINK \l "_Toc226519723" A7.2.3 Nitrous Oxide Emission Uncertainties  PAGEREF _Toc226519723 \h 471  HYPERLINK \l "_Toc226519724" A7.2.4 Halocarbons and SF6  PAGEREF _Toc226519724 \h 473  HYPERLINK \l "_Toc226519725" A7.3 Uncertainties in GWP weighted emissions  PAGEREF _Toc226519725 \h 474  HYPERLINK \l "_Toc226519726" A7.3.1 Uncertainty in the emissions  PAGEREF _Toc226519726 \h 474  HYPERLINK \l "_Toc226519727" A7.3.2 Uncertainty in the Trend  PAGEREF _Toc226519727 \h 474  HYPERLINK \l "_Toc226519728" A7.4 Comparison of uncertainties from the error propagation and Monte Carlo analyses  PAGEREF _Toc226519728 \h 476  HYPERLINK \l "_Toc226519729" A7.5 Sectoral uncertainties  PAGEREF _Toc226519729 \h 477  HYPERLINK \l "_Toc226519730" A7.5.1 Overview of the Method  PAGEREF _Toc226519730 \h 477  HYPERLINK \l "_Toc226519731" A7.5.2 Review of Changes made to the Monte Carlo Model since the last NIR  PAGEREF _Toc226519731 \h 477  HYPERLINK \l "_Toc226519732" A7.6 Estimation of uncertainties using an error propagation APPROACH (Approach1)  PAGEREF _Toc226519732 \h 481  HYPERLINK \l "_Toc226519733" A7.6.1 Review of Recent Improvements to the Error Propagation Model  PAGEREF _Toc226519733 \h 481  HYPERLINK \l "_Toc226519734" A7.6.2 Review of Changes Made to the Error Propagation Model since the last NIR  PAGEREF _Toc226519734 \h 483  HYPERLINK \l "_Toc226519735" A7.6.3 Uncertainty in the Emissions  PAGEREF _Toc226519735 \h 483  HYPERLINK \l "_Toc226519736" A7.6.4 Uncertainty in the Trend  PAGEREF _Toc226519736 \h 483  HYPERLINK \l "_Toc226519737" A7.6.5 Key Categories  PAGEREF _Toc226519737 \h 484  HYPERLINK \l "_Toc226519738" A7.6.6 Tables of uncertainty estimates from the error propagation approach  PAGEREF _Toc226519738 \h 484  HYPERLINK \l "_Toc226519739" A8 ANNEX 8: Verification  PAGEREF _Toc226519739 \h 489  HYPERLINK \l "_Toc226519740" A8.1 Modelling approach used for the verification of the UK GHGI  PAGEREF _Toc226519740 \h 489  HYPERLINK \l "_Toc226519741" A8.2 Methane  PAGEREF _Toc226519741 \h 489  HYPERLINK \l "_Toc226519742" A8.3 Nitrous Oxide  PAGEREF _Toc226519742 \h 491  HYPERLINK \l "_Toc226519743" A8.4 Hydrofluorocarbons  PAGEREF _Toc226519743 \h 492  HYPERLINK \l "_Toc226519744" A8.4.1 HFC-134a  PAGEREF _Toc226519744 \h 492  HYPERLINK \l "_Toc226519745" A8.4.2 HFC-152a  PAGEREF _Toc226519745 \h 492  HYPERLINK \l "_Toc226519746" A8.4.3 HFC-125  PAGEREF _Toc226519746 \h 493  HYPERLINK \l "_Toc226519747" A8.4.4 HFC-365mfc  PAGEREF _Toc226519747 \h 493  HYPERLINK \l "_Toc226519748" A8.4.5 HFC-143a  PAGEREF _Toc226519748 \h 494  HYPERLINK \l "_Toc226519749" A8.4.6 HFC-23  PAGEREF _Toc226519749 \h 494  HYPERLINK \l "_Toc226519750" A9 ANNEX 9: IPCC Sectoral Tables of GHG Emissions  PAGEREF _Toc226519750 \h 495  HYPERLINK \l "_Toc226519751" A10 Annex 10: Supplementary information for estimates of greenhouse gas emissions by sources and removals by sinks resulting from activities under Article 3.3 and 3.4 of the Kyoto Protocol  PAGEREF _Toc226519751 \h 514  HYPERLINK \l "_Toc226519752" A10.1 General Information  PAGEREF _Toc226519752 \h 514  HYPERLINK \l "_Toc226519753" A10.1.1 Definition of forest  PAGEREF _Toc226519753 \h 514  HYPERLINK \l "_Toc226519754" A10.1.2 Elected activities under Article 3.4  PAGEREF _Toc226519754 \h 514  HYPERLINK \l "_Toc226519755" A10.1.3 Description of how the definitions of each activity under Article 3.3 and 3.4 have been implemented and applied consistently over time  PAGEREF _Toc226519755 \h 515  HYPERLINK \l "_Toc226519756" A10.1.4 Precedence conditions and hierarchy among Art. 3.4 activities  PAGEREF _Toc226519756 \h 515  HYPERLINK \l "_Toc226519757" A10.2 Land-related information  PAGEREF _Toc226519757 \h 515  HYPERLINK \l "_Toc226519758" A10.2.1 Spatial assessment unit used  PAGEREF _Toc226519758 \h 515  HYPERLINK \l "_Toc226519759" A10.2.2 Methodology used to develop the land transition matrix  PAGEREF _Toc226519759 \h 515  HYPERLINK \l "_Toc226519760" A10.2.3 Identification of geographical locations  PAGEREF _Toc226519760 \h 518  HYPERLINK \l "_Toc226519761" A10.3 Activity-specific information  PAGEREF _Toc226519761 \h 519  HYPERLINK \l "_Toc226519762" A10.3.1 Methods for carbon stock change and GHG emission and removal estimates  PAGEREF _Toc226519762 \h 519  HYPERLINK \l "_Toc226519763" A10.3.2 Article 3.3  PAGEREF _Toc226519763 \h 524  HYPERLINK \l "_Toc226519764" A10.3.3 Article 3.4  PAGEREF _Toc226519764 \h 525  HYPERLINK \l "_Toc226519765" A10.4 Other information  PAGEREF _Toc226519765 \h 526  HYPERLINK \l "_Toc226519766" A10.4.1 Key category analysis  PAGEREF _Toc226519766 \h 526  HYPERLINK \l "_Toc226519767" A10.5 Information relating to Article 6  PAGEREF _Toc226519767 \h 526  HYPERLINK \l "_Toc226519768" A11 Annex 11: End User Emissions  PAGEREF _Toc226519768 \h 527  HYPERLINK \l "_Toc226519769" A11.1 Introduction  PAGEREF _Toc226519769 \h 527  HYPERLINK \l "_Toc226519770" A11.2 Definition of final users  PAGEREF _Toc226519770 \h 527  HYPERLINK \l "_Toc226519771" A11.3 Overview of the final users calculations  PAGEREF _Toc226519771 \h 528  HYPERLINK \l "_Toc226519772" A11.4 Example final user calculation  PAGEREF _Toc226519772 \h 530  HYPERLINK \l "_Toc226519773" A11.5 Final user calculation methodology for the UK greenhouse gas inventory  PAGEREF _Toc226519773 \h 533  HYPERLINK \l "_Toc226519774" A11.6 Methodological Changes  PAGEREF _Toc226519774 \h 545  HYPERLINK \l "_Toc226519775" A11.7 Detailed emissions according to final user categories  PAGEREF _Toc226519775 \h 545  HYPERLINK \l "_Toc226519776" A12 ANNEX 12: Analysis of EU ETS Data  PAGEREF _Toc226519776 \h 561  HYPERLINK \l "_Toc226519777" A12.1 Introduction  PAGEREF _Toc226519777 \h 561  HYPERLINK \l "_Toc226519778" A12.2 Processing of EU ETS Data  PAGEREF _Toc226519778 \h 562  HYPERLINK \l "_Toc226519779" A12.3 Analysis of EU ETS data for power stations  PAGEREF _Toc226519779 \h 563  HYPERLINK \l "_Toc226519780" A12.4 Analysis of EU ETS data for refineries  PAGEREF _Toc226519780 \h 564  HYPERLINK \l "_Toc226519781" A12.5 analysis of EUETS data for industrial combustion Sources  PAGEREF _Toc226519781 \h 565  HYPERLINK \l "_Toc226519782" A13 ANNEX 13: Standard Electronic Format Tables of GHG Emissions  PAGEREF _Toc226519782 \h 566  HYPERLINK \l "_Toc226519783" A13.1 SEF Tables  PAGEREF _Toc226519783 \h 567  HYPERLINK \l "_Toc226519784" A14 ANNEX 14: Additional Reporting Requirements  PAGEREF _Toc226519784 \h 575  HYPERLINK \l "_Toc226519785" A14.1 Consideration of new requirements  PAGEREF _Toc226519785 \h 575  List of Tables  TOC \h \z \c "Table A"  HYPERLINK \l "_Toc224623127" Table A 1.1.1: Key Category Analysis for the base year based on level of emissions (including LULCUF)  PAGEREF _Toc224623127 \h 254  HYPERLINK \l "_Toc224623128" Table A 1.1.2: Key Category Analysis for the base year based on level of emissions (excluding LULCUF)  PAGEREF _Toc224623128 \h 255  HYPERLINK \l "_Toc224623129" Table A 1.1.3: Key Category Analysis for 1990 based on level of emissions (including LULCUF)  PAGEREF _Toc224623129 \h 256  HYPERLINK \l "_Toc224623130" Table A 1.1.4: Key Category Analysis for 1990 based on level of emissions (excluding LULCUF)  PAGEREF _Toc224623130 \h 257  HYPERLINK \l "_Toc224623131" Table A 1.1.5: Key Category Analysis for the latest reported year based on level of emissions (including LULCUF)  PAGEREF _Toc224623131 \h 258  HYPERLINK \l "_Toc224623132" Table A 1.1.6: Key Category Analysis for the latest reported year based on level of emissions (excluding LULCUF)  PAGEREF _Toc224623132 \h 259  HYPERLINK \l "_Toc224623133" Table A 1.1.7: Key Category Analysis based on trend in emissions (from base year to latest reported year, including LULCUF)  PAGEREF _Toc224623133 \h 260  HYPERLINK \l "_Toc224623134" Table A 1.1.8: Key Category Analysis based on the trend in emissions (from base year to latest reported year, excluding LULCUF)  PAGEREF _Toc224623134 \h 261  HYPERLINK \l "_Toc224623135" Table A 1.1.9: Key Category Analysis based on trend in emissions (from 1990 to latest reported year, including LULCUF)  PAGEREF _Toc224623135 \h 262  HYPERLINK \l "_Toc224623136" Table A 1.1.10: Key Category Analysis based on trend in emissions (from 1990 to latest reported year, excluding LULCUF)  PAGEREF _Toc224623136 \h 263  HYPERLINK \l "_Toc224623137" Table A 1.1.11: Key Source Category Analysis summary for the base year (including LULUCF)  PAGEREF _Toc224623137 \h 264  HYPERLINK \l "_Toc224623138" Table A 1.1.12: Key Source Category Analysis summary for the base year (excluding LULUCF)  PAGEREF _Toc224623138 \h 265  HYPERLINK \l "_Toc224623139" Table A 1.1.13: Key Source Category Analysis summary for the latest reported year (including LULUCF)  PAGEREF _Toc224623139 \h 266  HYPERLINK \l "_Toc224623140" Table A 1.1.14: Key Source Category Analysis summary for the latest reported year (excluding LULUCF)  PAGEREF _Toc224623140 \h 267  HYPERLINK \l "_Toc224623141" Table A 3.1.1: Mapping of fuels used in the GHGI and the NAEI  PAGEREF _Toc224623141 \h 271  HYPERLINK \l "_Toc224623142" Table A 3.2.1: Mapping of IPCC Source Categories to NAEI Source Categories fuel combustion  PAGEREF _Toc224623142 \h 273  HYPERLINK \l "_Toc224623143" Table A 3.2.2: Mapping of IPCC Source Categories to NAEI Source Categories (Fugitive emissions from fuels)  PAGEREF _Toc224623143 \h 274  HYPERLINK \l "_Toc224623144" Table A 3.2.3: Mapping of IPCC Source Categories to NAEI Source Categories (Industrial Processes)  PAGEREF _Toc224623144 \h 274  HYPERLINK \l "_Toc224623145" Table A 3.2.4: Mapping of IPCC Source Categories to NAEI Source Categories  PAGEREF _Toc224623145 \h 276  HYPERLINK \l "_Toc224623146" Table A 3.2.5: Mapping of IPCC Source Categories to NAEI Source Categories (Agriculture)  PAGEREF _Toc224623146 \h 277  HYPERLINK \l "_Toc224623147" Table A 3.2.6: Mapping of IPCC Source Categories to NAEI Source Categories (Land Use, Land Use Change and Forestry)  PAGEREF _Toc224623147 \h 278  HYPERLINK \l "_Toc224623148" Table A 3.2.7: Mapping of IPCC Source Categories to NAEI Source Categories (Waste)  PAGEREF _Toc224623148 \h 278  HYPERLINK \l "_Toc224623149" Table A 3.3.1: Emission Factors for the Combustion of Liquid Fuels for 20071 (kg/t)  PAGEREF _Toc224623149 \h 284  HYPERLINK \l "_Toc224623150" Table A 3.3.2: Emission Factors for the Combustion of Coal for 20071 (kg/t)  PAGEREF _Toc224623150 \h 285  HYPERLINK \l "_Toc224623151" Table A 3.3.3: Emission Factors for the Combustion of Solid Fuels 20071 (kg/t)  PAGEREF _Toc224623151 \h 286  HYPERLINK \l "_Toc224623152" Table A 3.3.4: Emission Factors for the Combustion of Gaseous Fuels 20071 (g/GJ gross)  PAGEREF _Toc224623152 \h 287  HYPERLINK \l "_Toc224623153" Table A 3.3.5: Conversion Factors for Gross to Net Energy Consumption  PAGEREF _Toc224623153 \h 290  HYPERLINK \l "_Toc224623154" Table A 3.3.6: Emission Factors for Power Stations in 2007 [A time series of carbon emission factors can be found in the background energy tables on the accompanying CD]  PAGEREF _Toc224623154 \h 292  HYPERLINK \l "_Toc224623155" Table A 3.3.7: Components of Emissions Included in Reported Emissions from Civil Aviation  PAGEREF _Toc224623155 \h 298  HYPERLINK \l "_Toc224623156" Table A 3.3.8: Aircraft Movement Data  PAGEREF _Toc224623156 \h 299  HYPERLINK \l "_Toc224623157" Table A 3.3.9: Carbon Dioxide and Sulphur Dioxide Emission Factors for Civil and Military Aviation for 2007 (kg/t)  PAGEREF _Toc224623157 \h 300  HYPERLINK \l "_Toc224623158" Table A 3.3.10: Non-CO2 Emission Factors for Civil and Military Aviation  PAGEREF _Toc224623158 \h 300  HYPERLINK \l "_Toc224623159" Table A 3.3.11: Railway Emission Factors (kt/Mt)  PAGEREF _Toc224623159 \h 305  HYPERLINK \l "_Toc224623160" Table A 3.3.12: Fuel-Based Emission Factors for Road Transport (kg/tonne fuel)  PAGEREF _Toc224623160 \h 306  HYPERLINK \l "_Toc224623161" Table A 3.3.13: Fuel Consumption Factors for Road Transport  PAGEREF _Toc224623161 \h 309  HYPERLINK \l "_Toc224623162" Table A 3.3.14: Fuel Consumption Factors for HGVs (in g fuel/km) based on DfTs road freight statistics  PAGEREF _Toc224623162 \h 310  HYPERLINK \l "_Toc224623163" Table A 3.3.15: UK vehicle km by road vehicles  PAGEREF _Toc224623163 \h 313  HYPERLINK \l "_Toc224623164" Table A 3.3.16: Average Traffic Speeds in Great Britain  PAGEREF _Toc224623164 \h 314  HYPERLINK \l "_Toc224623165" Table A 3.3.17: Vehicles types and regulation classes  PAGEREF _Toc224623165 \h 316  HYPERLINK \l "_Toc224623166" Table A 3.3.18: Emission Degradation rates permitted for Euro 3 and 4 Light-Duty Vehicles by Directive 98/69/EC  PAGEREF _Toc224623166 \h 320  HYPERLINK \l "_Toc224623167" Table A 3.3.19: Scale Factors for Emissions from a Euro II Bus Running on Fitted with an Oxidation Catalyst or DPF  PAGEREF _Toc224623167 \h 321  HYPERLINK \l "_Toc224623168" Table A 3.3.20: Scale Factors for Emissions from a Euro II HGV Fitted with a DPF  PAGEREF _Toc224623168 \h 321  HYPERLINK \l "_Toc224623169" Table A 3.3.21: Cold Start Emission Factors for N2O (in mg/km)  PAGEREF _Toc224623169 \h 323  HYPERLINK \l "_Toc224623170" Table A 3.3.22: N2O Emission Factors for Road Transport (in mg/km)  PAGEREF _Toc224623170 \h 326  HYPERLINK \l "_Toc224623171" Table A 3.3.23: Methane Emission Factors for Road Transport (in mg/km)  PAGEREF _Toc224623171 \h 327  HYPERLINK \l "_Toc224623172" Table A 3.3.24: NOx Emission Factors for Road Transport (in g/km)  PAGEREF _Toc224623172 \h 328  HYPERLINK \l "_Toc224623173" Table A 3.3.25: CO Emission Factors for Road Transport (in g/km)  PAGEREF _Toc224623173 \h 329  HYPERLINK \l "_Toc224623174" Table A 3.3.26: NMVOC Emission Factors for Road Transport (in g/km)  PAGEREF _Toc224623174 \h 330  HYPERLINK \l "_Toc224623175" Table A 3.3.27: Equations for diurnal, hot soak and running loss evaporative emissions from vehicles with and without control systems fitted  PAGEREF _Toc224623175 \h 331  HYPERLINK \l "_Toc224623176" Table A 3.3.28 Aggregate Emission Factors for Off-Road Source Categories in 2007 (t/kt fuel)  PAGEREF _Toc224623176 \h 335  HYPERLINK \l "_Toc224623177" Table A 3.3.29: Methane Emission Factors for Coal Mining (kg/t coal)  PAGEREF _Toc224623177 \h 336  HYPERLINK \l "_Toc224623178" Table A 3.3.30: Emission Factors Used for Coke and Solid Smokeless Fuel Production  PAGEREF _Toc224623178 \h 339  HYPERLINK \l "_Toc224623179" Table A 3.3.31: Activity Data & Implied Emission Factors: Offshore Flaring  PAGEREF _Toc224623179 \h 342  HYPERLINK \l "_Toc224623180" Table A 3.3.32: Activity Data & Implied Emission Factors: Offshore Own Gas Use  PAGEREF _Toc224623180 \h 343  HYPERLINK \l "_Toc224623181" Table A 3.3.33: Activity Data and Implied Emission Factors: Well Testing  PAGEREF _Toc224623181 \h 344  HYPERLINK \l "_Toc224623182" Table A 3.3.34: Aggregate Emission Factors used for Emissions from Platforms and Terminals  PAGEREF _Toc224623182 \h 346  HYPERLINK \l "_Toc224623183" Table A 3.3.35: Activity Data and Implied Emission Factors: Crude Oil Loading, Onshore and Offshore  PAGEREF _Toc224623183 \h 346  HYPERLINK \l "_Toc224623184" Table A 3.3.36: Methane and NMVOC Composition of Natural Gas  PAGEREF _Toc224623184 \h 348  HYPERLINK \l "_Toc224623185" Table A 3.4.1: Emission Factors for Cement Kilns based on Fuel Consumption, 2007  PAGEREF _Toc224623185 \h 353  HYPERLINK \l "_Toc224623186" Table A 3.4.2: Emission Factors for Cement Kilns based on Clinker Production, 1990-2007  PAGEREF _Toc224623186 \h 353  HYPERLINK \l "_Toc224623187" Table A 3.4.3: Emission Factors for Lime Kilns based on Fuel Consumption, 2007  PAGEREF _Toc224623187 \h 353  HYPERLINK \l "_Toc224623188" Table A 3.4.4 Emission Factors for Lime Kilns, 2007: Indirect GHGs  PAGEREF _Toc224623188 \h 354  HYPERLINK \l "_Toc224623189" Table A 3.4.5 Summary of Nitric Acid Production in the UK, 1990-2007  PAGEREF _Toc224623189 \h 354  HYPERLINK \l "_Toc224623190" Table A 3.4.6: Emission Factors for Blast Furnaces (BF), Electric Arc Furnaces (EAF) and Basic Oxygen Furnaces (BOF), 2007  PAGEREF _Toc224623190 \h 356  HYPERLINK \l "_Toc224623191" Table A 3.4.7: Emission Factors for Aluminium Production, 2007  PAGEREF _Toc224623191 \h 357  HYPERLINK \l "_Toc224623192" Table A 3.4.8: NMVOC Emission Factors for Food and Drink Processing, 2007  PAGEREF _Toc224623192 \h 357  HYPERLINK \l "_Toc224623193" Table A 3.6.1 Livestock Population Data for 2007 by Animal Type  PAGEREF _Toc224623193 \h 360  HYPERLINK \l "_Toc224623194" Table A 3.6.2 Methane Emission Factors for Livestock Emissions  PAGEREF _Toc224623194 \h 360  HYPERLINK \l "_Toc224623195" Table A 3.6.3 Dairy Cattle Methane Emission Factorsa  PAGEREF _Toc224623195 \h 361  HYPERLINK \l "_Toc224623196" Table A 3.6.4 Parameters used in the calculation of the Methane Emission Factorsa for Beef and Other Cattle  PAGEREF _Toc224623196 \h 362  HYPERLINK \l "_Toc224623197" Table A 3.6.51 Dry Mass Content and Residue Fraction of UK Crops  PAGEREF _Toc224623197 \h 370  HYPERLINK \l "_Toc224623198" Table A 3.6.63 Emission Factors for Field Burning (kg/t)  PAGEREF _Toc224623198 \h 374  HYPERLINK \l "_Toc224623199" Table A 3.7.1: Afforestation rate and age distribution of conifers and broadleaves in the United Kingdom since 1921  PAGEREF _Toc224623199 \h 376  HYPERLINK \l "_Toc224623200" Table A 3.7.2; Main parameters for forest carbon flow model used to estimate carbon uptake by planting of forests of Sitka spruce (P. sitchensis and beech (F. sylvatica) in the United Kingdom (Dewar & Cannell 1992)  PAGEREF _Toc224623200 \h 378  HYPERLINK \l "_Toc224623201" Table A 3.7.3: Grouping of MLC land cover types for soil carbon change modelling  PAGEREF _Toc224623201 \h 380  HYPERLINK \l "_Toc224623202" Table A 3.7.4: Grouping of Countryside Survey Broad Habitat types for soil carbon change modelling  PAGEREF _Toc224623202 \h 380  HYPERLINK \l "_Toc224623203" Table A 3.7.5: Sources of land use change data in Great Britain for different periods in estimation of changes in soil carbon  PAGEREF _Toc224623203 \h 381  HYPERLINK \l "_Toc224623204" Table A 3.7.6: Sources of land use change data in Northern Ireland for different periods in estimation of changes in soil carbon. NICS = Northern Ireland Countryside Survey  PAGEREF _Toc224623204 \h 381  HYPERLINK \l "_Toc224623205" Table A 3.7.7: Annual changes (000 ha) in land use in England in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys (Haines-Young et al. 2000). Data have been rounded to 100 ha  PAGEREF _Toc224623205 \h 381  HYPERLINK \l "_Toc224623206" Table A 3.7.8: Annual changes (000 ha) in land use in Scotland in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys (Haines-Young et al. 2000). Data have been rounded to 100 ha  PAGEREF _Toc224623206 \h 381  HYPERLINK \l "_Toc224623207" Table A 3.7.9: Annual changes (000 ha) in land use in Wales in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys (Haines-Young et al. 2000). Data have been rounded to 100 ha  PAGEREF _Toc224623207 \h 382  HYPERLINK \l "_Toc224623208" Table A 3.7.10: Annual changes (000 ha) in land use in Northern Ireland in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Northern Ireland Countryside Surveys (Cooper & McCann 2002). Data have been rounded to 100 ha  PAGEREF _Toc224623208 \h 382  HYPERLINK \l "_Toc224623209" Table A 3.7.11: Soil carbon stock (TgC = MtC) for depths to 1 m in different land types in the UK  PAGEREF _Toc224623209 \h 382  HYPERLINK \l "_Toc224623210" Table A 3.7.12: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in England  PAGEREF _Toc224623210 \h 384  HYPERLINK \l "_Toc224623211" Table A 3.7.13: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Scotland  PAGEREF _Toc224623211 \h 384  HYPERLINK \l "_Toc224623212" Table A 3.7.14: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Wales  PAGEREF _Toc224623212 \h 384  HYPERLINK \l "_Toc224623213" Table A 3.7.15: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Northern Ireland  PAGEREF _Toc224623213 \h 384  HYPERLINK \l "_Toc224623214" Table A 3.7.16: Rates of change of soil carbon for land use change transitions. (Fast & Slow refer to 99% of change occurring in times shown in Table A3.7.17)  PAGEREF _Toc224623214 \h 385  HYPERLINK \l "_Toc224623215" Table A 3.7.17: Range of times for soil carbon to reach 99% of a new value after a change in land use in England (E), Scotland (S) and Wales (W)  PAGEREF _Toc224623215 \h 385  HYPERLINK \l "_Toc224623216" Table A 3.7.18: Equilibrium biomass carbon density (kg m-2) for different land types  PAGEREF _Toc224623216 \h 386  HYPERLINK \l "_Toc224623217" Table A 3.7.19: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in England (Transitions to and from Forestland are considered elsewhere)  PAGEREF _Toc224623217 \h 386  HYPERLINK \l "_Toc224623218" Table A 3.7.20: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in Scotland. (Transitions to and from Forestland are considered elsewhere)  PAGEREF _Toc224623218 \h 386  HYPERLINK \l "_Toc224623219" Table A 3.7.21: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in Wales. (Transitions to and from Forestland are considered elsewhere)  PAGEREF _Toc224623219 \h 386  HYPERLINK \l "_Toc224623220" Table A 3.7.22: Weighted average change in equilibrium biomass carbon density (kgm2) to 1m deep for changes between different land types in Northern Ireland. (Transitions to and from Forestland are considered elsewhere)  PAGEREF _Toc224623220 \h 387  HYPERLINK \l "_Toc224623221" Table A 3.7.23: Area burnt in wildfires in state (Forestry Commission) forests 19902007 (* indicates an estimated area)  PAGEREF _Toc224623221 \h 388  HYPERLINK \l "_Toc224623222" Table A 3.7.24: Biomass densities, tonnes DM ha-1, used to estimate mass of available fuel for wildfires  PAGEREF _Toc224623222 \h 389  HYPERLINK \l "_Toc224623223" Table A 3.7.25: Area and carbon loss rates of UK fen wetland in 1990  PAGEREF _Toc224623223 \h 390  HYPERLINK \l "_Toc224623224" Table A 3.7.26: Emission Factors for Peat Extraction  PAGEREF _Toc224623224 \h 391  HYPERLINK \l "_Toc224623225" Table A 3.7.27: Emissions of N2O in the UK due to disturbance of soils after land use change estimated by the method of the LULUCF GPG  PAGEREF _Toc224623225 \h 393  HYPERLINK \l "_Toc224623226" Table A 3.8.1 Waste degradable carbon model parameters for MSW waste  PAGEREF _Toc224623226 \h 396  HYPERLINK \l "_Toc224623227" Table A 3.8.2 Waste degradable carbon model parameters for C & I waste  PAGEREF _Toc224623227 \h 397  HYPERLINK \l "_Toc224623228" Table A 3.8.3 Amount of methane generated, captured, utilised, flared, oxidised and emitted.  PAGEREF _Toc224623228 \h 400  HYPERLINK \l "_Toc224623229" Table A 3.8.4: Specific Methane Emission Factors for Sludge Handling (kg CH4/Mg dry solids, Hobson et al (1996))  PAGEREF _Toc224623229 \h 402  HYPERLINK \l "_Toc224623230" Table A 3.8.5: Time-Series of Methane Emission Factors for Emissions from Wastewater Handling, based on Population (kt CH4 / million people)  PAGEREF _Toc224623230 \h 403  HYPERLINK \l "_Toc224623231" Table A 3.8.6: Time-series of per capita protein consumptions (kg/person/yr)  PAGEREF _Toc224623231 \h 403  HYPERLINK \l "_Toc224623232" Table A 3.9.1: Summary of category allocations in the CRF tables and the NIR  PAGEREF _Toc224623232 \h 407  HYPERLINK \l "_Toc224623233" Table A 3.9.2: Isle of Man, Guernsey and Jersey Summary of Methodologies  PAGEREF _Toc224623233 \h 412  HYPERLINK \l "_Toc224623234" Table A 3.9.3: Isle of Man, Guernsey and Jersey Emissions of Direct GHGs (Mt CO2 equivalent)  PAGEREF _Toc224623234 \h 413  HYPERLINK \l "_Toc224623235" Table A 3.9.4: Cayman Islands, Falklands Islands and Montserrat Methodology (for estimates of carbon, CH4 and N2O)  PAGEREF _Toc224623235 \h 416  HYPERLINK \l "_Toc224623236" Table A 3.9.5: Cayman Islands, Falklands Islands, Bermuda and Montserrat Emissions of Direct GHGs (Mt CO2 equivalent)  PAGEREF _Toc224623236 \h 417  HYPERLINK \l "_Toc224623237" Table A 3.9.6: Summary of methodologies used to estimate emissions from Gibraltar  PAGEREF _Toc224623237 \h 420  HYPERLINK \l "_Toc224623238" Table A 3.9.7: Emissions of Direct GHGs (Mt CO2 equivalent) from Gibraltar  PAGEREF _Toc224623238 \h 421  HYPERLINK \l "_Toc224623239" Table A 4.3.1: Modified comparison of the IPCC Reference Approach and the National Approach  PAGEREF _Toc224623239 \h 423  HYPERLINK \l "_Toc224623240" Table A 5.1.1: GHGs and sources not considered in the UK GHG inventory  PAGEREF _Toc224623240 \h 424  HYPERLINK \l "_Toc224623241" Table A 6.1.1: % Changes from 1990 to 2007 in Sector 1  PAGEREF _Toc224623241 \h 431  HYPERLINK \l "_Toc224623242" Table A 6.1.2: % Changes from 2006 to 2007 in Sector 1  PAGEREF _Toc224623242 \h 431  HYPERLINK \l "_Toc224623243" Table A 6.1.3: % Contribution to Sector 1  PAGEREF _Toc224623243 \h 431  HYPERLINK \l "_Toc224623244" Table A 6.1.4: % Contribution to Overall Pollutant Emissions  PAGEREF _Toc224623244 \h 431  HYPERLINK \l "_Toc224623245" Table A 6.2.1: % Changes from 1990 to 2007 in Sector 2  PAGEREF _Toc224623245 \h 435  HYPERLINK \l "_Toc224623246" Table A 6.2.2: % Changes from 2006 to 2007 in Sector 2  PAGEREF _Toc224623246 \h 436  HYPERLINK \l "_Toc224623247" Table A 6.2.3: % Contribution to Sector 2  PAGEREF _Toc224623247 \h 437  HYPERLINK \l "_Toc224623248" Table A 6.2.4: % Contribution to Overall Pollutant Emissions  PAGEREF _Toc224623248 \h 438  HYPERLINK \l "_Toc224623249" Table A 6.3.1: % Changes 1990-2007 within Sector 3  PAGEREF _Toc224623249 \h 440  HYPERLINK \l "_Toc224623250" Table A 6.3.2: % Changes 2006-2007 within Sector 3  PAGEREF _Toc224623250 \h 440  HYPERLINK \l "_Toc224623251" Table A 6.3.3: % Contribution to Sector 3  PAGEREF _Toc224623251 \h 440  HYPERLINK \l "_Toc224623252" Table A 6.3.4: % Contribution to Overall Pollutant Emissions  PAGEREF _Toc224623252 \h 440  HYPERLINK \l "_Toc224623253" Table A 6.4.1: % Changes 1990-2007 within Sector 4  PAGEREF _Toc224623253 \h 443  HYPERLINK \l "_Toc224623254" Table A 6.4.2: % Changes 2006-2007 within Sector 4  PAGEREF _Toc224623254 \h 444  HYPERLINK \l "_Toc224623255" Table A 6.4.3: % Contribution to Sector 4  PAGEREF _Toc224623255 \h 445  HYPERLINK \l "_Toc224623256" Table A 6.4.4: % Contribution to Overall Pollutant Emissions  PAGEREF _Toc224623256 \h 446  HYPERLINK \l "_Toc224623257" Table A 6.5.1: % Changes 1990-2007 within Sector 5  PAGEREF _Toc224623257 \h 449  HYPERLINK \l "_Toc224623258" Table A 6.5.2: % Changes 2006-2007 within Sector 5  PAGEREF _Toc224623258 \h 449  HYPERLINK \l "_Toc224623259" Table A 6.6.1: % Changes 1990-2007 within Sector 6  PAGEREF _Toc224623259 \h 452  HYPERLINK \l "_Toc224623260" Table A 6.6.2: % Changes 2006-2007 within Sector 6  PAGEREF _Toc224623260 \h 452  HYPERLINK \l "_Toc224623261" Table A 6.6.3: % Contribution to Sector 6  PAGEREF _Toc224623261 \h 452  HYPERLINK \l "_Toc224623262" Table A 6.6.4: % Contribution to Overall Pollutant Emissions  PAGEREF _Toc224623262 \h 452  HYPERLINK \l "_Toc224623263" Table A 7.2.1: Uncertainties in the activity data and emission factors for fuels used in the carbon dioxide inventory  PAGEREF _Toc224623263 \h 459  HYPERLINK \l "_Toc224623264" Table A 7.2.2: Uncertainties in the activity data and emission factors for non-fuels used in the carbon dioxide inventory  PAGEREF _Toc224623264 \h 460  HYPERLINK \l "_Toc224623265" Table A 7.2.3: Estimated uncertainties in the activity data and emission factors used in the methane inventory  PAGEREF _Toc224623265 \h 462  HYPERLINK \l "_Toc224623266" Table A 7.2.4: Estimated uncertainties in the activity data and emission factors used in the N2O inventory  PAGEREF _Toc224623266 \h 466  HYPERLINK \l "_Toc224623267" Table A 7.3.1: Summary of Monte Carlo Uncertainty Estimates 1990 - 2007  PAGEREF _Toc224623267 \h 469  HYPERLINK \l "_Toc224623268" Table A 7.4.1: Comparison of the central estimates and trends in emissions from the error propagation (Approach1) and Monte Carlo (Approach2) uncertainty analyses  PAGEREF _Toc224623268 \h 471  HYPERLINK \l "_Toc224623269" Table A 7.5.1: Sectoral Uncertainty Estimates  PAGEREF _Toc224623269 \h 472  HYPERLINK \l "_Toc224623270" Table A 7.6.1: Summary of error propagation uncertainty estimates including LULUCF, base year to the latest reported year  PAGEREF _Toc224623270 \h 479  HYPERLINK \l "_Toc224623271" Table A 7.6.2: Summary of error propagation uncertainty estimates including LULUCF, base year to the latest reported year (continued)  PAGEREF _Toc224623271 \h 480  HYPERLINK \l "_Toc224623272" Table A 7.6.3: Summary of error propagation uncertainty estimates excluding LULUCF, base year to the latest reported year  PAGEREF _Toc224623272 \h 481  HYPERLINK \l "_Toc224623273" Table A 7.6.4: Summary of error propagation uncertainty estimates excluding LULUCF, base year to the latest reported year (continued)  PAGEREF _Toc224623273 \h 482  HYPERLINK \l "_Toc224623274" Table A 8.2.1: Verification of the UK emission inventory estimates for methane in Ggyr-1 for 1995-2007. NAME uncertainty (500 Gg yr-1. NAME1 use Mace Head observations only, NAME2 use observations from 11 sites across Europe including Mace Head.  PAGEREF _Toc224623274 \h 484  HYPERLINK \l "_Toc224623275" Table A 8.3.1 Verification of the UK emission inventory estimates for nitrous oxide in Ggyr-1 for 1995-2007. NAME uncertainty varies but is approximately (30 Gg yr-1.  PAGEREF _Toc224623275 \h 485  HYPERLINK \l "_Toc224623276" Table A 8.4.1 Verification of the UK emission inventory estimates for HFC-134a in Gg yr-1 for 1995-2007. The NAME estimates have a calculated error of 0.4 Gg yr-1.  PAGEREF _Toc224623276 \h 486  HYPERLINK \l "_Toc224623277" Table A 8.4.2: Verification of the UK emission inventory estimates for HFC-152a in Ggyr-1 for 1995-2007. The NAME estimates have a calculated error of up to 0.06 Gg yr-1  PAGEREF _Toc224623277 \h 487  HYPERLINK \l "_Toc224623278" Table A 8.4.3: Verification of the UK emission inventory estimates for HFC-125 in Gg yr-1 for 1998-2007. The NAME estimates have a calculated error of 0.10 Gg yr-1.  PAGEREF _Toc224623278 \h 487  HYPERLINK \l "_Toc224623279" Table A 8.4.4: Verification of the UK emission inventory estimates for HFC-365mfc in Gg yr-1 for 2003-2007. The NAME estimates have a calculated error of 0.07 Gg yr-1.  PAGEREF _Toc224623279 \h 487  HYPERLINK \l "_Toc224623280" Table A 8.4.5: Verification of the UK emission inventory estimates for HFC-143a in Gg yr-1 for 2004-2007. The NAME estimates have a calculated error of 0.1 Gg yr-1.  PAGEREF _Toc224623280 \h 488  HYPERLINK \l "_Toc224623281" Table A 8.4.6: Verification of the UK emission inventory estimates for HFC-23 in Gg yr-1 for 2007. The NAME estimates have a calculated error of 0.02 Gg yr-1.  PAGEREF _Toc224623281 \h 488  HYPERLINK \l "_Toc224623282" Table A 10.2.1 Data sources on ARD and FM activities (additional data sources may become available in the future)  PAGEREF _Toc224623282 \h 493  HYPERLINK \l "_Toc224623283" Table A 10.2.2 Land transition matrix using national datasets  PAGEREF _Toc224623283 \h 494  HYPERLINK \l "_Toc224623284" Table A 10.2.3 Proposed land transition matrix with the 20km grid for end of commitment period accounting  PAGEREF _Toc224623284 \h 494  HYPERLINK \l "_Toc224623285" Table A 11.4.1 Example of the outputs during a final user calculation  PAGEREF _Toc224623285 \h 508  HYPERLINK \l "_Toc224623286" Table A 11.5.1: Sources reallocated to final users and the fuels used  PAGEREF _Toc224623286 \h 510  HYPERLINK \l "_Toc224623287" Table A 11.5.2: Final user category, IPCC sectors, and NAEI source names and activity names used in the emission calculation  PAGEREF _Toc224623287 \h 512  HYPERLINK \l "_Toc224623288" Table A 11.7.1: Final user emissions from Agriculture, by gas, MtCO2 equivalent  PAGEREF _Toc224623288 \h 522  HYPERLINK \l "_Toc224623289" Table A 11.7.2: Final user emissions from Business, by gas, MtCO2 equivalent  PAGEREF _Toc224623289 \h 523  HYPERLINK \l "_Toc224623290" Table A 11.7.3: Final user emissions from Industrial Processes, by gas, MtCO2 equivalent  PAGEREF _Toc224623290 \h 524  HYPERLINK \l "_Toc224623291" Table A 11.7.4: Final user emissions from Land Use Land Use Change and Forestry, by gas, MtCO2 equivalent  PAGEREF _Toc224623291 \h 525  HYPERLINK \l "_Toc224623292" Table A 11.7.5: Final user emissions from Public Sector, by gas, MtCO2 equivalent  PAGEREF _Toc224623292 \h 526  HYPERLINK \l "_Toc224623293" Table A 11.7.6: Final user emissions from Residential, by gas, MtCO2 equivalent  PAGEREF _Toc224623293 \h 527  HYPERLINK \l "_Toc224623294" Table A 11.7.7: Final user emissions from Transport, by gas, MtCO2 equivalent  PAGEREF _Toc224623294 \h 528  HYPERLINK \l "_Toc224623295" Table A 11.7.8: Final user emissions from Waste Management, by gas, MtCO2 equivalent  PAGEREF _Toc224623295 \h 529  HYPERLINK \l "_Toc224623296" Table A 11.7.9: Final user emissions from all National Communication categories, MtCO2 equivalent  PAGEREF _Toc224623296 \h 530  HYPERLINK \l "_Toc224623297" Table A 11.7.10: Final user emissions, Carbon, MtCO2 equivalent  PAGEREF _Toc224623297 \h 531  HYPERLINK \l "_Toc224623298" Table A 11.7.11: Final user emissions, Methane, MtCO2 equivalent  PAGEREF _Toc224623298 \h 532  HYPERLINK \l "_Toc224623299" Table A 11.7.12: Final user emissions, Nitrous Oxide, MtCO2 equivalent  PAGEREF _Toc224623299 \h 533  HYPERLINK \l "_Toc224623300" Table A 11.7.13: Final user emissions, HFC, MtCO2 equivalent  PAGEREF _Toc224623300 \h 534  HYPERLINK \l "_Toc224623301" Table A 11.7.14: Final user emissions, PFC, MtCO2 equivalent  PAGEREF _Toc224623301 \h 535  HYPERLINK \l "_Toc224623302" Table A 11.7.15: Final user emissions, SF6, MtCO2 equivalent  PAGEREF _Toc224623302 \h 536  HYPERLINK \l "_Toc224623303" Table A 12.2.1: Numbers of installations included in the EU ETS datasets  PAGEREF _Toc224623303 \h 538  HYPERLINK \l "_Toc224623304" Table A 12.3.1 EU ETS data for Coal, Fuel Oil and Natural Gas burnt at Power Stations and Autogenerators (Emission Factors in ktonne / Mtonne for Coal & Fuel Oil and ktonne / Mtherm for Natural Gas)  PAGEREF _Toc224623304 \h 539  HYPERLINK \l "_Toc224623305" Table A 12.4.1: EU ETS Data for Fuel Oil, OPG and Petroleum Coke burnt at Refineries (Emission Factors in ktonne / Mtonne for Fuel Oil & Petroleum Coke and ktonne / Mtherm for OPG)  PAGEREF _Toc224623305 \h 540  HYPERLINK \l "_Toc224623306" Table A 12.5.1 EU ETS data for Coal, Fuel Oil and Natural Gas burnt by Industrial Combustion Plant (Emission Factors in ktonne / Mtonne for Coal & Fuel Oil and ktonne / Mtherm for Natural Gas)  PAGEREF _Toc224623306 \h 541  HYPERLINK \l "_Toc224623307" Table A 13.1.1 Total quantities of Kyoto Protocol units by account type at beginning of reported year  PAGEREF _Toc224623307 \h 543  HYPERLINK \l "_Toc224623308" Table A 13.1.2 Annual internal transactions  PAGEREF _Toc224623308 \h 544  HYPERLINK \l "_Toc224623309" Table A 13.1.3 Annual external transactions  PAGEREF _Toc224623309 \h 545  HYPERLINK \l "_Toc224623310" Table A 13.1.4 Total annual transactions  PAGEREF _Toc224623310 \h 546  HYPERLINK \l "_Toc224623311" Table A 13.1.5 Expiry, cancellation and replacement  PAGEREF _Toc224623311 \h 546  HYPERLINK \l "_Toc224623312" Table A 13.1.6 Total quantities of Kyoto Protocol units by account type at end of reported year  PAGEREF _Toc224623312 \h 547  HYPERLINK \l "_Toc224623313" Table A 13.1.7 Summary information on additions and subtractions  PAGEREF _Toc224623313 \h 548  HYPERLINK \l "_Toc224623314" Table A 13.1.8 Summary information on replacement  PAGEREF _Toc224623314 \h 549  HYPERLINK \l "_Toc224623315" Table A 13.1.9 Summary information on retirement  PAGEREF _Toc224623315 \h 549  HYPERLINK \l "_Toc224623316" Table A 13.1.10 Memo item: Corrective transactions relating to additions and subtractions  PAGEREF _Toc224623316 \h 550  HYPERLINK \l "_Toc224623317" Table A 13.1.11 Memo item: Corrective transactions relating to replacement  PAGEREF _Toc224623317 \h 550  HYPERLINK \l "_Toc224623318" Table A 13.1.12 Memo item: Corrective transactions relating to retirement  PAGEREF _Toc224623318 \h 550  List of Figures FigureTitleAnnexSectionA6.1UK emissions of direct Greenhouse Gases from IPCC sector 1 1990-2006Annex 6A6.1.7A6.2UK emissions of indirect Greenhouse Gases from IPCC sector 1 1990-2006Annex 6A6.1.7A6.3UK emissions of direct Greenhouse Gases from IPCC sector 2 1990-2006Annex 6A6.2.10A6.4UK emissions of indirect Greenhouse Gases from IPCC sector 2 1990-2006Annex 6A6.2.10A6.5UK emissions of NMVOC from IPCC sector 3 1990-2006Annex 6A6.3A6.6UK emissions of direct Greenhouse Gases from IPCC sector 4 1990-2006Annex 6A6.4.5 A6.7UK emissions of indirect Greenhouse Gases from IPCC sector 4 1990-2006Annex 6A6.4.5 A6.8UK emissions and removals of direct Greenhouse Gases from IPCC sector 5 1990-2006Annex 6A6.5.5A6.9UK emissions of indirect Greenhouse Gases from IPCC sector 5 1990-2006Annex 6A6.5.5A6.10UK emissions of direct Greenhouse Gases from IPCC sector 6 1990-2006Annex 6A6.6.7A6.11UK emissions of indirect Greenhouse Gases from IPCC sector 6 1990-2006Annex 6A6.6.7A8.1Verification of the UK emission inventory estimates for nitrous oxide in Gg yr-1 for 1995-2006Annex 8A8.3A10.1Spatial units used for reporting Kyoto protocol LULUCF activities: (left) the four countries of the UK, (right) 20 x 20km grid cells covering the UKAnnex 10A10.2.3A11.1Extremely simplified fuel flows for a final user calculation.Annex 11A11.5A11.2Fuel use in the example calculationAnnex 11A11.6A11.3Comparison of direct and final user emissions of sulphur dioxide according the sectors considered in the final user exampleAnnex 11A11.6 ANNEX 1: Key Categories Key Category Analysis Up to and including the 2007NIR this Annex referred to key sources. The NIR now refers to key categories, or key source categories, rather than key sources. Key categories is the terminology used in the IPCCs Good Practice Guidance (2000) and the word category is used, rather than source, to avoid any potential confusion with sources and corresponding sinks of carbon. In the UK inventory, certain source categories are particularly significant in terms of their contribution to the overall uncertainty of the inventory. These key source categories have been identified so that the resources available for inventory preparation may be prioritised, and the best possible estimates prepared for the most significant source categories. We have used the method set out in Section7.2 of the IPCC Good Practice Guidance (2000) (Determining national key source categories) to determine the key source categories. The results of the key source category analysis with and without LULUCF, for the base year and the latest reported year, are summarised by sector and gas in TableA1.1.11 to TableA1.1.14. A trend cannot be calculated for the base year alone, and so TableA1.1.11 and TableA1.1.12 only contain key source categories identified by level. The key category analysis is based on the level analysis and trend analysis which are part of the Approach1 uncertainty analysis. The Approach1 uncertainty analysis is an error propagation approach, as described in Section3.2.3.1 of the IPCC 2006 Guidelines. This analysis has been performed using the data shown in TablesA7.6.1 toA7.6.4 using the same categorisation and the same estimates of uncertainty. The table indicates whether a key category arises from the level assessment or the trend assessment. The factors that make a source a key category are: A high contribution to the total; A high contribution to the trend; and High uncertainty. For example, transport fuel (1A3b) is a key category for carbon dioxide because it is large; landfill methane (6A) is key because it is large, has a high uncertainty and shows a significant trend. Both the level and the trend assessments have been completed, following the procedure set out in the IPCC Good Practice Guidance (2000). A qualitative assessment was not conducted, but we do not anticipate that additional source categories would have been identified using such an assessment. The emission estimates were taken from the current inventory. The results of the level assessment with and without LULUCF the base year, 1990, and the latest reported year are shown in TableA1.1.1 to TableA1.1.6. The key source categories are highlighted by the shaded cells in the table. The source categories (i.e. rows of the table) were sorted in descending order of magnitude based on the results of the Level Parameter, and then the cumulative total was included in the final column of the table. The key source categories are those whose contributions add up to 95% of the total uncertainty in the final column after this sorting process. The results of the trend assessment with and without LULUCF the base year, 1990 and the latest reported year are shown in TableA1.1.7 and TableA1.1.10. The key source categories are highlighted by the shaded cells in the table. The trend parameter was calculated using absolute value of the result; an absolute function is used since Land Use, Land Use Change and Forestry contains negative sources (sinks) and the absolute function is necessary to produce positive uncertainty contributions for these sinks. The source categories (i.e. rows of the table) were sorted in descending order of magnitude based on the results of the trend parameter, and then the cumulative total was included in the final column of the table. The key source categories are those whose contributions add up to 95% of the total uncertainty in the final column after this sorting process. The emissions of nitric and adipic acid are both key categories in the UK inventory and the emissions from nitric acid production are associated with a very high uncertainty. The uncertainties assigned to the AD and EFs are: 2B2 Nitric acid production, AD 10%, EF 230%; 2B3 Adipic acid production, AD 0.5%, EF 15%. The uncertainty associated with N2O emissions released from nitric acid production dominate the overall uncertainty of N2O emissions in sector 2B. The uncertainty assigned to the EF of nitric acid production was taken from a study commissioned by UK Defra (Salway et al., 1998). The uncertainty in the emission factor from nitric acid production was estimated from a range of values in the available literature - the reference in the report indicates the main source was the 1996 IPCC guidelines. The UK has not reviewed the uncertainties associated with nitric and adipic acid for some time. A review of the uncertainties was planned with the manufacturers during the compilation of the 2009NIR but this has been deferred until the 2010NIR. Any improvements methodological improvements to the uncertainty analysis are discussed in Annex7. Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 1: Key Category Analysis for the base year based on level of emissions (including LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 2: Key Category Analysis for the base year based on level of emissions (excluding LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 3: Key Category Analysis for 1990 based on level of emissions (including LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 4: Key Category Analysis for 1990 based on level of emissions (excluding LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 5: Key Category Analysis for the latest reported year based on level of emissions (including LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 6: Key Category Analysis for the latest reported year based on level of emissions (excluding LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 7: Key Category Analysis based on trend in emissions (from base year to latest reported year, including LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 8: Key Category Analysis based on the trend in emissions (from base year to latest reported year, excluding LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 9: Key Category Analysis based on trend in emissions (from 1990 to latest reported year, including LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 10: Key Category Analysis based on trend in emissions (from 1990 to latest reported year, excluding LULCUF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 11: Key Source Category Analysis summary for the base year (including LULUCF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 12: Key Source Category Analysis summary for the base year (excluding LULUCF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 13: Key Source Category Analysis summary for the latest reported year (including LULUCF)  Table A  STYLEREF 2 \s 1.1. SEQ Table_A \* ARABIC \s 2 14: Key Source Category Analysis summary for the latest reported year (excluding LULUCF)  ANNEX 2: Detailed Discussion of Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion Methodology for estimating CO2 emissions from fossil fuel combustion is discussed together with the methodologies for other emissions in Annex3. This is because the underlying methodology for such estimates applies to a range of pollutants and not just CO2. ANNEX 3: Other Detailed Methodological Descriptions This Annex contains background information about methods used to estimate emissions in the UK GHG inventory. This information has not been incorporated in the main body of the report because of the level of detail, and because the methods used to estimate emissions cut across sectors. This Annex provides: Background information on the fuels used in the UK GHG inventory. Mapping between IPCC and NAEI source categories. Detailed description of methods used to estimate GHG emissions, and emission factors used in those methods presented in Section A3.3 onwards. FUELS DATA The fuels data are taken from DUKES - the Digest of UK Energy Statistics (BERR, 2008), so the fuel definitions and the source categories used in the NAEI reflect those in DUKES. Categories used in the inventory for non-combustion sources generally reflect the availability of data on emissions from these sources. IPCC Guidelines (IPCC, 1997a) lists fuels that should be considered when reporting emissions. Table A3.1.1 lists the fuels that are used in the GHGI and indicates how they relate to the fuels reported in the NAEI. In most cases the mapping is obvious but there are a few cases where some explanation is required. Aviation Fuels UK energy statistics report consumption of aviation turbine fuel and this is mapped onto jet kerosene in the GHGI. Aviation turbine fuel includes fuel that is described as jet gasoline using IPCC terminology. Coal The IPCC Guidelines (IPCC, 1997a) classify coal as anthracite, coking coal, other bituminous coal and sub-bituminous coal. In mapping the UK fuel statistics to these categories it is assumed that only the coal used in coke ovens is coking coal; and the rest is reported as either coal or anthracite. Most coal used in the UK is bituminous coal; anthracite is reported separately in UK energy statistics. Coke Oven Coke Gas works coke is no longer manufactured in the UK so all coke and coke breeze consumption is reported as coke oven coke. Colliery Methane The IPCC Guidelines do not refer to colliery methane but significant use is made of it as a fuel in the UK so emissions are included in the GHGI. Orimulsion Orimulsion is an emulsion of bitumen and water and was burnt in some power stations in the UK, however its use has now been discontinued Slurry This is a slurry of coal and water used in some power stations. Sour Gas Unrefined natural gas is used as a fuel on offshore platforms and in some power stations. It has a higher carbon and sulphur content than mains gas. Wastes used as fuel The following wastes are used for power generation: municipal solid waste, scrap tyres, poultry litter, meat and bone meal, landfill gas, sewage gas, and waste oils. Some waste oils and scrap tyres are burnt in cement kilns. Further waste oils are burnt by other industrial sectors, and it is assumed that some lubricants consumed in the UK are destroyed (burnt) in engines. Table A  STYLEREF 2 \s 3.1. SEQ Table_A \* ARABIC \s 2 1: Mapping of fuels used in the GHGI and the NAEI GHGINAEICategorySubcategorySubcategoryLiquidMotor Gasoline Aviation Gasoline Jet Kerosene Other Kerosene Gas/Diesel Oil Residual Fuel Oil Orimulsion Liquefied Petroleum Gas Naphtha Petroleum Coke Refinery Gas Other Oil: Other Other Oil: Other Lubricants Petrol Aviation Spirit Aviation Turbine Fuel1 (ATF) Burning Oil Gas Oil/ DERV Fuel Oil Orimulsion Liquefied Petroleum Gas (LPG) Naphtha Petroleum Coke Other Petroleum Gas (OPG) Refinery Miscellaneous Waste Oils LubricantsSolidAnthracite Coking Coal Coal Coal Coke Oven Coke Patent Fuel Coke Oven Gas Blast Furnace Gas Anthracite Coal2 Coal Slurry3 Coke Solid Smokeless Fuel (SSF) Coke Oven Gas Blast Furnace GasGasNatural Gas Natural Gas Colliery Methane5 Natural Gas Sour Gas4 Colliery MethaneOther FuelsMunicipal Solid Waste Industrial Waste: Scrap Tyres Municipal Solid Waste Scrap TyresBiomassWood/Wood Waste Other Solid Biomass: Straw Other Solid Biomass: Poultry Litter, Meat & Bone Meal Landfill Gas Sludge Gas Wood Straw Poultry Litter, Meat & bone meal Landfill Gas Sewage Gas 1 Includes fuel that is correctly termed jet gasoline. 2 Used in coke ovens. 3 Coal-water slurry used in some power stations 4 Unrefined natural gas used on offshore platforms and some power stations 5 Not referred to in IPCC Guidelines (IPCC, 1997a) but included in GHGI. NAEI Source Categories and IPCC Equivalents Tables A3.2.1 to A3.2.7 relate the IPCC source categories to the equivalent NAEI base categories. In most cases it is possible to obtain a precise mapping of an NAEI source category to a specific IPCC source category. In some cases the relevant NAEI source category does not correspond exactly to the IPCC source category and in a few cases an equivalent NAEI source category is not estimated or is defined quite differently. As a result, total annual emissions given in the NAEI and GHGI differ slightly. The source categories responsible for the differences between the GHGI and the NAEI are Land Use, Land Use Change and Forestry sources. Tables A3.2.1 to A3.2.7 refer to NAEI base categories. Normally the NAEI is not reported in such a detailed form but in the summary UNECE/CORINAIR SNAP97, eleven-sector format or the new NFR (Nomenclature For Reporting) system used for submission to CORINAIR. Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 1: Mapping of IPCC Source Categories to NAEI Source Categories fuel combustion IPCC Source CategoryNAEI Source Category1A1a Public Electricity and Heat ProductionPower Stations1A1b Petroleum RefiningRefineries (Combustion)1A1ci Manufacture of Solid FuelsSSF Production Coke Production 1A1cii Other Energy IndustriesCollieries Gas Production Gas Separation Plant (Combustion) Offshore Own Gas Use Production of Nuclear Fuel Town Gas Production1A2a Iron and SteelIron and Steel (Combustion) Iron and Steel (Sinter Plant) Iron and Steel (Blast Furnaces)1A2b Non-Ferrous Metals 1A2c Chemicals 1A2d Pulp, Paper and Print 1A2e Food Processing, Beverages, TobaccoIncluded under Other Industry (Combustion)1A2fi OtherOther Industry (Combustion) Cement (Fuel Combustion) Cement (Non-decarbonising) Lime Production (Combustion) Autogenerators Ammonia (Combustion)1A2fii Other (Off-road Vehicles and Other Machinery)Other Industry Off-road1A3a Civil AviationNo comparable category1A3b Road TransportationRoad Transport1A3c RailwaysRailways (Freight) Railways (Intercity) Railways (Regional)1A3di International MarineInternational Marine1A3dii Internal NavigationCoastal Shipping1A3e Other TransportAircraft Support1A4a Commercial/InstitutionalMiscellaneous Public Services Railways (Stationary Sources)1A4bi ResidentialDomestic1A4bii Residential Off-roadDomestic, House & Garden1A4ci Agriculture/Forestry/Fishing (Stationary)Agriculture1A4cii Agriculture/Forestry/Fishing (Off-road Vehicles and Other Machinery)Agriculture Power Units1A4ciii Agriculture/Forestry/Fishing (Fishing)Fishing1A5a Other: StationaryNo comparable category-included in 1A4a1A5b Other: mobileAircraft Military Shipping Naval  Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 2: Mapping of IPCC Source Categories to NAEI Source Categories (Fugitive emissions from fuels) IPCC Source CategoryNAEI Source Category1B1a Coal Mining i Mining activitiesDeep-Mined Coal1B1a Coal Mining ii Post mining activitiesCoal Storage & Transport1B1a Coal Mining ii Surface MinesOpen-Cast Coal1B1b Solid Fuel TransformationCoke Production (Fugitive) SSF Production (Fugitive) Flaring (Coke Oven Gas)1B1c OtherNot Estimated1B2a Oil i ExplorationOffshore Oil and Gas (Well Testing) 1B2a Oil ii ProductionOffshore Oil and Gas1B2a Oil iii TransportOffshore Loading Onshore Loading1B2a Oil iv Refining/Storage Refineries (drainage) Refineries (tankage) Refineries (Process) Oil Terminal Storage Petroleum Processes1B2a Oil vi Other Not Estimated1B2a Oil v Distribution of oil productsPetrol Stations (Petrol Delivery) Petrol Stations (Vehicle Refuelling) Petrol Stations (Storage Tanks) Petrol Stations (Spillages) Petrol Terminals (Storage) Petrol Terminals (Tanker Loading) Refineries (Road/Rail Loading)1B2b i Natural Gas ProductionGasification Processes1B2b ii Natural Gas. Transmission/DistributionGas Leakage1B2ciii Venting: CombinedOffshore Oil and Gas (Venting)1B2ciii Flaring: CombinedOffshore Flaring Refineries (Flares) Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 3: Mapping of IPCC Source Categories to NAEI Source Categories (Industrial Processes) IPCC Source CategoryNAEI Source Category2A1 Cement ProductionCement (Decarbonising)2A2 Lime ProductionLime Production (Decarbonising)2A3 Limestone and Dolomite UseGlass Production: Limestone and Dolomite Iron and Steel (Blast Furnace): Limestone and Dolomite Power Stations (FGD)2A4 Soda Ash Production and UseGlass Production: Soda Ash2A5 Asphalt RoofingNot Estimated2A6 Road Paving with AsphaltRoad Construction2A7 OtherBrick Manufacture (Fletton) Glass (continuous filament glass fibre) Glass (glass wool)2B1 Ammonia ProductionAmmonia Feedstock2B2 Nitric Acid ProductionNitric Acid Production2B3 Adipic Acid ProductionAdipic Acid Production2B4 Carbide Production2B5 OtherSulphuric Acid Production Chemical Industry Chemical Industry (Carbon Black) Chemical Industry (Ethylene) Chemical Industry (Methanol) Chemical Industry (Nitric Acid Use) Chemical Industry (Pigment Manufacture) Chemical Industry (Reforming) Chemical Industry (Sulphuric Acid Use) Coal, tar and bitumen processes Solvent and Oil recovery Ship purging2C1 Iron and Steel Iron and Steel (other) Iron and Steel (Basic Oxygen Furnace) Iron and Steel (Electric Arc Furnace) Iron and Steel Flaring (Blast Furnace Gas) Rolling Mills (Hot & Cold Rolling)2C2 Ferroalloys ProductionsNo Comparable Source Category2C3 Aluminium ProductionNon-Ferrous Metals (Aluminium Production)2C4 SF6 Used in Aluminium and Magnesium FoundriesSF6 Cover Gas2C5 OtherNon-Ferrous Metals (other non-ferrous metals) Non-Ferrous Metals (primary lead/zinc) Non-Ferrous Metals (secondary Copper) Non-Ferrous Metals (secondary lead)2D1 Pulp and PaperWood Products Manufacture2D2 Food and DrinkBrewing (barley malting, fermentation, wort boiling) Bread Baking Cider Manufacture Other Food (animal feed; cakes, biscuits, cereals; coffee, malting, margarine and other solid fats; meat, fish and poultry; sugar) Spirit Manufacture (barley malting, casking distillation, fermentation, maturation, spent grain drying) Wine Manufacture2E1 Halocarbon & SF6 By-Product Emissions 2E2 Halocarbon & SF6 Fugitive EmissionsHalocarbons Production (By-Product and Fugitive)2E3 Halocarbon & SF6 OtherNot Estimated2F1 Refrigeration & Air Conditioning EquipmentRefrigeration Supermarket Refrigeration Mobile Air Conditioning2F2 Foam BlowingFoams2F3 Fire ExtinguishersFire Fighting2F2 AerosolsMetered Dose Inhalers Aerosols (Halocarbons)2F5 SolventsNot Occurring2F8a One Component Foams2F8 Semiconductors, Electrical and Production of TrainersElectronics Training Shoes Electrical Insulation Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 4: Mapping of IPCC Source Categories to NAEI Source Categories IPCC Source CategoryNAEI Source Category3A Paint ApplicationDecorative paint (retail decorative) Decorative paint (trade decorative) Industrial Coatings (automotive) Industrial Coatings (agriculture & construction) Industrial Coatings (aircraft) Industrial Coatings (Drum) Industrial Coatings (coil coating) Industrial Coatings (commercial vehicles) Industrial Coatings (high performance) Industrial Coatings (marine) Industrial Coatings (metal and plastic) Industrial Coatings (metal packaging) Industrial Coatings (vehicle refinishing) Industrial Coatings (wood)3B Degreasing & Dry CleaningDry Cleaning Surface Cleaning Leather Degreasing3C Chemical Products, Manufacture & ProcessingCoating Manufacture (paint) Coating Manufacture (ink) Coating Manufacture (glue) Film Coating Leather coating Other Rubber Products Tyre Manufacture Textile Coating3D OtherAerosols (Car care, Cosmetics & toiletries, household products) Agrochemicals Use Industrial Adhesives Paper Coating Printing Other Solvent Use Non Aerosol Products (household, automotive, cosmetics & toiletries, domestic adhesives, paint thinner) Seed Oil Extraction Wood Impregnation Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 5: Mapping of IPCC Source Categories to NAEI Source Categories (Agriculture) IPCC Source CategoryNAEI Source Category4A1 Enteric Fermentation: CattleDairy Cattle Enteric Other Cattle Enteric4A2 Enteric Fermentation: BuffaloNot Occurring4A3 Enteric Fermentation: SheepSheep Enteric4A4 Enteric Fermentation: GoatsGoats Enteric4A5 Enteric Fermentation: Camels & LlamasNot Occurring4A6 Enteric Fermentation: HorsesHorses Enteric4A7 Enteric Fermentation: Mules & Asses Not Occurring4A8 Enteric Fermentation: SwinePigs Enteric4A9 Enteric Fermentation: PoultryNot Occurring4A10 Enteric Fermentation: Other: DeerDeer Enteric4B1 Manure Management: CattleDairy Cattle Wastes Other Cattle Wastes4B2 Manure Management: BuffaloNot Occurring4B3 Manure Management: SheepSheep Wastes4B4 Manure Management: GoatsGoats Wastes4B5 Manure Management: Camels & LlamasNot Occurring4B6 Manure Management: HorsesHorses Wastes4B7 Manure Management: Mules & AssesNot Occurring4B8 Manure Management: SwinePigs Wastes4B9 Manure Management: PoultryBroilers Wastes Laying Hens Wastes Other Poultry4B9a Manure Management: Other: DeerDeer Wastes4B10 Anaerobic LagoonsNot Occurring4B11 Liquid SystemsManure Liquid Systems4B12 Solid Storage and Dry LotManure Solid Storage and Dry Lot4B13 OtherManure Other4C Rice CultivationNot Occurring4D 1 Agricultural Soils: Direct Soil Emissions 4D 2 Agricultural Soils: Animal Emissions 4D 4 Agricultural Soils: Indirect EmissionsAgricultural Soils Fertiliser Agricultural Soils Crops4E Prescribed Burning of SavannahsNot Occurring4F1 Field Burning of Agricultural Residues: CerealsBarley Residue Wheat Residue Oats Residue4F5 Field Burning of Agricultural Residues: Other: LinseedLinseed Residue4G OtherNot Estimated Emissions in this NIR are reported used the reporting nomenclature specified in the LULUCF Good Practice Guidance and agreed at the 9th Conference of Parties for reporting to the UNFCCC. These reporting categories are very different to those previously used, and to the NAEI source categories, which are based on NFR codes. Table A 3.2.6 summarises the categories used, and which NAEI categories they correspond to. Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 6: Mapping of IPCC Source Categories to NAEI Source Categories (Land Use, Land Use Change and Forestry) IPCC Source CategoryNAEI Source Category5A Forest Land (Biomass Burning - wildfires)Not Reported5A Forest Land (Drainage of soils)Not Reported5A1 Forest Land Remaining Forest LandNot Reported5A2 Forest Land (N fertilisation)Not Reported5A2 Land Converted to Forest LandNot Reported5B Cropland (Biomass Burning - controlled)Not Reported5B Liming4D1 Liming of Agricultural Soils5B1 Cropland Remaining CroplandNot Reported5B2 Land Converted to CroplandNot Reported5C Grassland (Biomass burning - controlled)Not Reported5C Liming4D1 Liming of Agricultural Soils5C1 Grassland Remaining GrasslandNot Reported5C2 Land converted to grasslandNot Reported5D Wetlands (Biomass burning - controlled)Not Reported5D1 Wetlands remaining wetlandsNot Reported5D2 Land converted to wetlandsNot Reported5E Settlements (Biomass burning - controlled)Not Reported5E1 Settlements remaining settlementsNot Reported5E2 Land converted to settlementsNot Reported5F Other land (Biomass burning - controlled)Not Reported5F1 Other land remaining other landNot Reported5F2 Land converted to other landNot Reported5G Other (Harvested wood)Not ReportedNo relevant category5B Deforestation Table A  STYLEREF 2 \s 3.2. SEQ Table_A \* ARABIC \s 2 7: Mapping of IPCC Source Categories to NAEI Source Categories (Waste) IPCC Source CategoryNAEI Source Category6A1 Managed Waste Disposal on LandLandfill6A2 Unmanaged Waste Disposal on LandNot Occurring6A3 OtherNot Occurring6B1 Industrial Wastewater 6B2 Domestic and Commercial Wastewater 6B3 OtherSewage Sludge Disposal6C Waste IncinerationIncineration: MSW Incineration: Sewage Sludge Incineration: Clinical Incineration: Cremation6D Other WasteNot estimated Energy (CRF sector 1) The previous two sections defined the fuels and source categories used in the NAEI and the GHGI. This section describes the methodology used to estimate the emissions arising from fuel combustion for energy. These sources correspond to IPCC Table 1A. There is little continuous monitoring of emissions performed in the UK; hence information is rarely available on actual emissions over a specific period of time from an individual emission source. In any case, emissions of CO2 from fuel are probably estimated more accurately from fuel consumption data. The majority of emissions are estimated from other information such as fuel consumption, distance travelled or some other statistical data related to the emissions. Estimates for a particular source sector are calculated by applying an emission factor to an appropriate statistic. This is as follows: Total Emission = Emission Factor ( Activity Statistic Emission factors are typically derived from measurements on a number of representative sources and the resulting factor applied to the UK environment. For the indirect gases, emissions data are sometimes available for individual sites from databases such as the Environment Agencys Pollution Inventory (PI). Hence the emission for a particular sector can be calculated as the sum of the emissions from these point sources. That is: Emission = ( Point Source Emissions However it is still necessary to make an estimate of the fuel consumption associated with these point sources, so that the emissions from non-point sources can be estimated from fuel consumption data without double counting. In general the point source approach is only applied to emissions of indirect greenhouse gases for well-defined point sources (e.g. power stations, cement kilns, coke ovens, refineries). Direct greenhouse gas emissions and most non-industrial sources are estimated using emission factors. Basic Combustion Module For the pollutants and sources discussed in this section the emission results from the combustion of fuel. The activity statistics used to calculate the emission are fuel consumption statistics taken from BERR (2008). A file of the fuel combustion data used in the inventory is provided on a CD ROM attached to this report. Emissions are calculated according to the following equation: E(p,s,f) = A(s,f) ( e(p,s,f) where E(p,s,f) = Emission of pollutant p from source s from fuel f (kg); A(s,f) = Consumption of fuel f by source s (kg or kJ); and e(p,s,f) = Emission factor of pollutant p from source s from fuel f (kg/kg or kg/kJ). The pollutants estimated in this way are as follows: Carbon dioxide as carbon; Methane; Nitrous oxide; NOx as nitrogen dioxide (some source/fuel combinations only); NMVOC; Carbon monoxide (some source/fuel combinations only); and Sulphur dioxide (some source/fuel combinations only). The sources covered by this module are: Domestic; Miscellaneous; Public Service; Refineries (Combustion); Iron & Steel (Combustion); Iron & Steel (Blast Furnaces); Iron & Steel (Sinter Plant); Other Industry (Combustion); Autogenerators; Gas Production; Collieries; Production of Nuclear Fuel; Coastal Shipping; Fishing; Agriculture; Ammonia (Combustion); Railways (Stationary Sources); Aircraft Military; and Shipping Naval. The fuels covered are listed in Annex 3, Section 3.1, though not all fuels occur in all sources. For the estimation of CO and NOx emissions from industrial, commercial/institutional and domestic sources the methodology allows for source/fuel combinations to be further broken down by a) thermal input of combustion devices; b) type of combustion process e.g. boilers, furnaces, turbines etc. Different emission factors are applied to these subdivisions of the source/fuel combination. Most of these emission factors are taken from literature sources, predominantly from US EPA, (2005), EMEP/CORINAIR (2003), and Walker et al, (1985). Some emissions data reported in the Pollution Inventory (Environment Agency, 2008) are also used to generate emission factors. Tables A3.3.1 to A3.3.4 list the emission factors used in this module. Emission factors are expressed in terms of kg pollutant/tonne for solid and liquid fuels, and g/TJ gross for gases. This differs from the IPCC approach, which expresses emission factors as tonnes pollutant/TJ based on the net calorific value of the fuel. For gases the NAEI factors are based on the gross calorific value of the fuel. This approach is used because the gas consumption data in BERR (2008) are reported in terms of energy content on a gross basis. For most of the combustion source categories, the emission is estimated from fuel consumption data reported in DUKES and an emission factor appropriate to the type of combustion e.g. commercial gas fired boiler. However the DUKES category Other Industries covers a range of sources and types, so the Inventory disaggregates this category into a number of sub-categories, namely: Other Industry; Other Industry Off-road; Ammonia Feedstock (natural gas only); Ammonia (Combustion) (natural gas only); Cement (Combustion); and Lime Production (non-decarbonising). Thus the GHGI category Other Industry refers to stationary combustion in boilers and heaters by industries not covered elsewhere (including the chemicals, food & drink, non-ferrous metal, glass, ceramics & bricks, textiles & engineering sectors). The other categories are estimated by more complex methods discussed in the sections indicated. For certain industrial processes (e.g. Lime production, cement production and ammonia production), the methodology is discussed in Section A3.4 as the estimation of the fuel consumption is closely related to the details of the process. However, for these processes, where emissions arise from fuel combustion for energy production, these are reported under IPCC Table 1A. The fuel consumption of Other Industry is estimated so that the total fuel consumption of these sources is consistent with DUKES (BERR, 2008). According to IPCC 1996 Revised Guidelines, electricity generation by companies primarily for their own use is autogeneration, and the emissions produced should be reported under the industry concerned. However, most National Energy Statistics (including the UK) report emissions from electricity generation as a separate category. The UK inventory attempts to report as far as possible according to the IPCC methodology. Hence autogenerators would be reported in the relevant sector where they can be identified e.g. iron and steel (combustion), refineries (combustion). In some cases the autogenerator cannot be identified from the energy statistics so it would be classified as other industry (combustion). This means that the split between iron and steel (combustion) and other industry (combustion) may be uncertain. Also, for certain sectors, data on fuel deliveries are used in preference to data on fuel consumption because deliveries will include autogeneration whereas consumption does not. In 2004, an extensive review of carbon factors in the UK GHG inventory was carried out (Baggottet al., 2004). This review covered over 90% of carbon emissions in the UK and focused on obtaining up-to-date carbon factors and oxidation factors for use in the inventory. The methods used to derive the carbon factors are described below. In the UK, power stations and the cement industry are important users of coal. Power station emissions account for approximately 85% of UK carbon emissions. The carbon contents of coal used by these two industries are obtained directly from industry representatives and this ensures that the inventory contains emissions of CO2 that are estimated as accurately as possible. Normally, the carbon contents of power station coal are updated annually. The cement industry imports most of the coal it uses from abroad, and the coal burnt is considered to be 100% oxidised due to the high operating temperatures of cement kilns. The carbon contents of fuels used by other industry sectors are not requested annually, but a time series is updated each year by scaling the carbon contents to the GCVs presented in the latest version of the Digest of UK Energy Statistics (BERR, 2008). The carbon content of a fuel is closely correlated with the calorific value and so using calorific values as a proxy provides a good estimate of the changing carbon contents. The major liquid fuel carbon factors in the inventory have been from the UK Petroleum Institute Association (UKPIA). During the review in 2004, UKPIA undertook fuel analysis and provided carbon emission factors for the following fuels: Petrol; Burning oil; ATF; Aviation spirit; Diesel; Fuel oil; Gas oil; Petroleum coke; Naphtha; OPG; Propane; and Butane. UKPIA advise whether these factors are still valid each year. For the cement sector, industry specific petroleum coke carbon factors are used as like coal, the sector uses different types of petroleum coke to other industries. Natural gas factors are provided by the UK gas network distributors. These data are derived from extensive measurements which are carried out by the various network distributors and data are provided to us each year. In the 2009 GHGI, carbon factors from the EUETS were introduced for certain sector and fuel combinations. These sectors are listed below, along with the years for which EUETS data was introduced. Power Stations coal for 2005, 2006, 2007 Power Stations fuel oil for 2005, 2006, 2007 Power Stations natural gas for 2005, (interpolated 2006, 2007) Autogenerators coal 2005, 2006, 2007 Refineries fuel oil - 2005, (interpolated 2006, 2007) Refineries Petroleum coke 2005, 2006, 2007 For years and sectors not listed, carbon factors remained the same as in previous inventories and as described in the carbon factors review from 2004. Implied emission factors (IEFs) for carbon are partly driven by the carbon emission factors and so there is some variability across the time series due to changes in UK factors. Updating carbon emission factors each year can cause large inter-annual changes in carbon implied emission factors (IEFs). One approach to avoid this, which has been suggested by an UNFCCC Expert Review Team, is to use regression analysis and derive the CEFs from the best fit line. We have considered this approach and discussed with UK DECC. For the moment, the UK continues to update CEFs on an annual basis because it considers that this approach provides the most accurate estimates of carbon emissions in a given year. For gas in sector 1A1, the carbon IEFs for gas are high in relation to other Member States of the European Union. This is because sour gas has been used in the UK ESI sector from 1992 onwards, and sour gas has a much greater IEF than natural gas. The increase in the CO2 IEF between 1991 and 1992 is explained by the commissioning of Peterhead power station in Scotland. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 1: Emission Factors for the Combustion of Liquid Fuels for 20071 (kg/t) FuelSourceCajCH4N2ONOxCONMVOCSO2ATFAircraft Military859a0.103ad0.1g8.5ad8.2ad1.1ad10.9zBurning OilDomestic859a0.462g0.0277g3.23l1.85l0.047f0.59zBurning OilOther Industry859a0.0924g0.0277g3.32l0.19l0.028e0.59zBurning OilPublic Service, Railways (Stationary)859a0.462g0.0277g2.05l0.16l0.047f0.59zBurning OilMiscellaneous859a0.462g0.0277g2.70l0.16l0.047f0.59zGas OilAgriculture870a0.455g0.0273g0ap0ap0.048f2.9zGas OilDomestic870a0.455g0.0273g3.19l1.82l0.047f2.7zGas OilFishing, Coastal Shipping, Naval, International Marine870a0.05ap0.08 ap72.3 aq7.4ap3.5 aq19.6 arGas Oil Iron&Steel870a0.0910g0.0273g20.17l7.95l0.028f2.7zGas OilRefineries870a0.136g0.0273g4.55k0.24i0.028f2.7zGas OilOther Industry870a0.0910g0.0273g5.08l0.90l0.028f2.7zGas OilPublic Service870a0.455g0.0273g2.44l0.38l0.047f2.7zGas OilMiscellaneous870a0.455g0.0273g1.34l0.17l0.047f2.7zFuel OilAgriculture879a0.433g0.026g7.69l0.31l0.14f16.8zFuel OilPublic Service879a0.433g0.026g7.62l0.81l0.14f17.0zFuel OilMiscellaneous879a0.433g0.026g0.85l0.034l0.14f17.0zFuel OilFishing; Coastal Shipping, International Marine879a0.05ap0.08 ap72.3 aq7.4ap3.5 aq52.9 arFuel OilDomestic879a0.433g0.026g0ap0ap0.14f17.0zFuel OilIron&Steel879a0.087g0.026g7.340.86l0.035f17.06zFuel OilRailways (Stationary)879a0.433g0.026g7.62l0.81l0.14f17.0zFuel OilOther Industry879a0.087g0.026g8.84l1.15l0.035f17.0zFuel OilRefineries (Combustion)877.4at0.130g0.026g3.90ag0.74ag0.035f24.7agLubricantsOther Industry865x0.091e0.027e4.55k0.25f0.13f11.4xPetrolRefineries855a0.141an0.028g4.62k0.24e0.028e0.061z Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 2: Emission Factors for the Combustion of Coal for 20071 (kg/t) SourceCajCH4N2ONOxCONMVOCSO2Agriculture639.1ao0.011o0.147w4.75l8.25l0.05o17.7aaCollieries687.3ao0.011o0.148w4.75l8.25l0.05o22.8aaDomestic683.5ao15.7o0.122w2.34l160.0l14o24.8aaIron and Steel (Combustion)693.8a0.011o0.237wIEIE0.05o17.68aaLime Production (Combustion)645.4ao0.011o0.214w60.44v15.73v0.05o17.68aaMiscellaneous702.8ao0.011o0.148w4.72l7.75l0.05o17.7aaPublic Service702.8ao0.011o0.148w4.78l5.99l0.05o17.7aaOther Industry645.4ao0.011o0.214w4.38l1.69l0.05o17.7aaRailways702.8ao0.011o0.148w4.78l5.99l0.05o17.68aaAutogenerators594.5at0.02o0.0660w5.55l1.60l0.03o17.68aa Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 3: Emission Factors for the Combustion of Solid Fuels 20071 (kg/t) FuelSourceCajCH4N2ONOxCONMVOCSO2AnthraciteDomestic820.7ap2o0.14w3.38k202.8k1.7o16.3aaCokeAgriculture799.5r0.011p0.150w5.15l1.17l0.05p19abCokeSSF Production799.5r0.011p0.230wIEIE0.05p19abCokeDomestic799.5r5.8o0.117w3.04l118.6l4.9o16.3aaCokeI&Sak (Sinter Plant)799.5r1.27ae0.230w11.6ae278ae0.41ae12.2aeCokeI&Sak (Combustion) 799.5r0.011p0.230w0.87l226l0.05p19abCokeOther Industry799.5r0.011p0.230w5.15l1.17l0.05p19abCokeRailways799.5r0.011p0.150w5.15l1.17l 0.05p19abCokeMiscellaneous; Public Service799.5r0.011p0.150w5.15l1.17l 0.05p19abMSWMiscellaneous75ah2.85g0.038g0.88v0.10v0.0050v0.028vPetroleum CokeDomestic930aNENE3.95k158k4.9am142.4asPetroleum CokeRefineries1000at0.107ai0.281w8.51ag1.97ag0.054ai45.2agPetroleum CokeCement Production Combustion8130.1070.1434.67k46.7k0.05p19abSSFMiscellaneous; Public Service766.3n0.011p0.151w3.11k124.4k4.9o16abSSFDomestic774.2n5.8o0.118w4.67k46.7k0.05p19abSSFOther Industry766.3n0.011p0.232w1.5g75g9g0StrawAgriculture418g4.5g0.06g0.7k70g24k0.108fWoodDomestic387g4.17g0.06g3.38k202.8k1.7o16.3aa Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 4: Emission Factors for the Combustion of Gaseous Fuels 20071 (g/GJ gross) FuelSourceCajCH4N2ONOxCONMVOCSO2Blast Furnace GasCoke Production75402r112k2.0k79k39.5k5.6k0Blast Furnace GasI&Sak (Combustion), I&Sak (Flaring)75402r112k2.0k79k39.5k5.6k0Blast Furnace GasBlast Furnaces75402r112k2.0k35.1v39.5k5.6k0Coke Oven GasOther Sources11089r57.25k2.0k80.5k40.0k4.35k280vCoke Oven GasI&Sak Blast Furnaces11089r57.25k2.0k35.1v40.0k4.35k280vCoke Oven GasCoke Production11089r57.25k2.0k374v 40.0k4.35k280vLPGDomestic16227a0.889f0.10g64.3f8.9f1.55f0LPGI&Sak, Other Industry, Refineries, Gas Production16227a0.889f0.10g88.7f15.1f1.55f0Natural GasAgriculture14003r5.0g0.10g39.2l2.13l2.22f0Natural GasMiscellaneous14003r5.0g0.10g53.15l10.6l2.22f0Natural GasPublic Service14003r5.0g0.10g56.0l12.85l2.22f0Natural GasCoke Production, SSF Prodnal, 14003r1.0g0.10g175.0k2.37l2.22f0Natural GasRefineries14003r1.0g0.10g70.0k2.37l2.22f0Natural GasBlast Furnaces14003r5.0g0.10g35.1v2.37l2.22f0Natural GasDomestic14003r5.0g0.10g69.2l30.8l2.22f0Natural GasGas Prodnal, 14003r1.0g0.10g92.87l17.4l2.22f0Natural GasI&Sak14003r5.0g0.10g178.56l177.2l2.22f0Natural GasRailways14003r5.0g0.10g92.87l33.8l2.22f0Natural GasOther Industry14003r5.0g0.10g142.95l62.6l2.22f0Natural GasNuclear Fuel Prodnal, Collieries1.0g0.10g142.95l62.6l2.22f0Natural GasAutogenerators14003r5.0g0.10g80.1l19.95l2.22f0Natural GasAmmonia (Combustion)14003r5.0g0.10g203.97dNE2.22f0OPGGas production15582a1.0gNE70.0k2.37i1.54f0OPGRefineries (Combustion)15582a1.0gNE96.3ag13.5z1.54f0OPGOther Industry15582a5.0gNE70.0k2.37i1.54f0Colliery MethaneOther Industry13930a5.0s0.10g70.0k2.37i2.21f0Colliery MethaneCoke Production, Gas Production13930a1.0s0.10g70.0k2.37i2.21f0Sewage GasPublic Services27405g5.0g0.10g66.78f7.1f2.42f0Landfill GasMiscellaneous27405g5.0g0.10g39.0f122.4f3.62f0 Footnotes to Tables A3.3.1 to A3.3.4: aCarbon Factor Review (2004), Review of Carbon Emission Factors in the UK Greenhouse Gas Inventory. Report to UK Defra. Baggott, SL, Lelland, A, Passant and Watterson, JW, and selected recent updates to the factors presented in this report.bCORINAIR (1992)b+Derived from CORINAIR(1992) assuming 30% of total VOC is methanecMethane facto r estimated as 12% of total hydrocarbon emission factor taken from EMEP/CORINAIR(1996) based on speciation in IPCC (1997c)dBased on operator data: Terra Nitrogen (2008), Invista (2008), BP Chemicals (2008) eAs for gas oilfUSEPA (2005)gIPCC (1997c)hEMEP (1990)iWalker et al (1985)jAs for fuel oil.kEMEP/CORINAIR (2003)lAEA Energy & Environment estimate based on application of literature emission factors at a greater level of detail than the sector listed (see Section A.3.3.1).mUSEPA (1997)nBritish Coal (1989)oBrain et al, (1994)pAs for coalqEMEP/CORINAIR (2003)rAEA Energy & Environment estimate based on carbon balancesAs for natural gastEMEP/CORINAIR (1996)uIPCC (2000)vEmission factor derived from emissions reported in the Pollution Inventory (Environment Agency, 2008)wFynes et al (1994)xPassant (2005)yUKPIA (1989)zEmission factor derived from data supplied by UKPIA (2006, 2007, 2008)aaEmission factor for 2005 based on data provided by UK Coal (2005), Scottish Coal (2006), Celtic Energy (2006), Tower (2006), Betwys (2000)abMunday (1990)acEstimated from THC data in CRI (Environment Agency, 1997) assuming 3.% methane split given in EMEP/CORINAIR (1996)adEMEP/CORINAIR (1999)aeAEA Energy & Environment estimate based on data from Environment Agency (2005) and Corus (2005)afUKPIA (2004)agAEA Energy & Environment estimate based on data from Environment Agency (2005), UKPIA, DUKES, and other sourcesahRoyal Commission on Environmental Pollution (1993)aiDTI (1994)ajEmission factor as mass carbon per unit fuel consumptionakI&S = Iron and SteelalProdn = ProductionamAs for SSFanAs for burning oilaoAEA Energy & Environment estimate based on carbon factors reviewapEMEP/CORINAIRaqAEA Energy & Environment estimatearDirectly from annual fuel sulphur concentration dataasBased on sulphur content of pet coke used in Drax trials (Drax Power Ltd, 2008)atBased on factors presented in EU-ETS returnsNENot estimatedNANot availableIEIncluded elsewhere1These are the factors used the latest inventory year. The corresponding time series of emission factors and calorific values may are available electronically [on the CD accompanying this report]. Note that all carbon emission factors used for Natural Gas include the CO2 already present in the gas prior to combustion.Conversion of Energy Activity Data and Emission Factors The NAEI databases store activity data in Mtonnes for solid and liquid fuels and Mtherms (gross) for gaseous fuels. Emission factors are in consistent units namely: ktonnes/Mtonne for solid and liquid fuels and ktonnes/Mtherm (gross) for gaseous fuels. For some sources emission factors are taken from IPCC and CORINAIR sources and it is necessary to convert them from a net energy basis to a gross energy basis. For solid and liquid fuels: Hn = m hg f and for gaseous fuels: Hn = Hg f where: Hn Equivalent energy consumption on net basis (kJ) m Fuel consumption (kg) hg Gross calorific value of fuel (kJ/kg) f Conversion factor from gross to net energy consumption (-) Hg Energy Consumption on gross basis (kJ) In terms of emission factors: em = en hg f or eg = en f where: em Emission factor on mass basis (kg/kg) en Emission factor on net energy basis (kg/kJ net) eg Emission factor on gross energy basis (kg/kJ gross) The gross calorific values of fuels used in the UK are tabulated in BERR, (2008). The values of the conversion factors used in the calculations are given in Table A3.3.5. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 5: Conversion Factors for Gross to Net Energy Consumption FuelConversion FactorOther Gaseous Fuels0.9Solid and Liquid Fuels0.95LPG and OPG0.92Blast Furnace Gas1.0 The values given for solid, liquid and other gaseous fuels are taken from IPCC Guidelines (IPCC, 1997c). The value used for LPG is based on the calorific value for butane, the major constituent of LPG (Perry et al, 1973). Blast furnace gas consists mainly of carbon monoxide and carbon dioxide. Since little hydrogen is present, the gross calorific value and the net calorific values will be the same. Energy Industries (1A1) Electricity Generation The NAEI category Power Stations is mapped onto 1A1 Electricity and Heat Production, and this category reports emissions from electricity generation by companies whose main business is producing electricity (Major Power Producers) and hence excludes autogenerators. Activity data for this category are taken from fuel consumption data in the annual publication The Digest of UK Energy Statistics (BERR, 2008) in conjunction with site-specific fuel use data obtained directly from plant operators. Coal and natural gas data from DUKES are very close to the category definition (i.e. exclude autogenerators) but fuel oil data does contain a small contribution from transport undertakings and groups of factories. From 1999 onwards, the fuel oil consumption reported within DUKES has been significantly lower than that estimated from returns from the power generators. In the inventory, the fuel oil use data from the power station operators are used; if the DUKES data was to be used, the emission factors implied by the data reported to UK environmental regulators (EA, SEPA, NIDoE) would be impossibly high. A correction is applied to the Other Industry (Combustion) category in the NAEI to ensure that total UK fuel oil consumption corresponds to that reported in DUKES. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 6: Emission Factors for Power Stations in 2007 [A time series of carbon emission factors can be found in the background energy tables on the accompanying CD] SourceUnitCO21CH4N2ONOxCONMVOCSO2CoalKt/Mt615.4s0.02e0.063l5.86n0.865n0.0227n5.34nPetroleum CokeKt/Mt615.9 a0.107q0.087r 4.30n21.3n0.032n7.80nFuel OilKt/Mt871.2s0.130h0.0260h13.23n1.17n0.0161n7.95nGas OilKt/Mt870a0.136h0.0273h14.11n0.64n0.075n7.95nBurning OilKt/Mt3.74n2.70n0.032n0.00039nNatural gasKt/Mth1.463s0.000106h1.06E-05h0.00393n0.00134n0.000170n3.19E-05nMSWKt/Mt75d0.285h0.038h0.877o0.101o0.00495o0.0276oSour gasKt/Mth1.916c0.000106h1.06E-05h0.00360n0.00137o9.85 E-05n0.0013nPoultry LitterKt/MtNE0.278h0.0370j1.093n0.646o1.292o0.299nSewage GasKt/MthNE0.000106h1.06E-05h0.00704k0.000749k0.000255kNEWaste OilsKt/Mt864.8bNENE13.23n1.17n0.0161n13.24nLandfill gasKt/MthNE0.000106h1.06E-05h0.00411k0.0129k0.000382kNE Footnotes to A3.3.6: (Emission Factors for Power Stations) 1Emission factor as mass carbon/ unit fuel consumptionaBaggott et al (2004) - Review of Carbon Emission Factors in the UK Greenhouse Gas Inventory. Report to UK Defra. Baggott, SL, Lelland, A, Passant and Watterson, JW Plus selected updates. (UKPIA (2004)-Liquid Fuels, Transco (2008) Natural Gas, Quick (2004) and AEP(2004) Power Station Coal). Note that all carbon emission factors used for Natural Gas include the CO2 already present in the gas prior to combustion. bPassant, N.R., Emission factors programme Task 1 Summary of simple desk studies (2003/4), AEA Technology Plc, Report No AEAT/ENV/R/1715/Issue 1, March 2004cStewart et al (1996) Emissions to Atmosphere from Fossil Fuel Power Generation in the UK, AEAT-0746, ISBN 0-7058-1753-3dRCEP (Royal Commission on Environmental Protection) 17th Report - Incineration of Waste, 1993. Recently photosynthesised carbon is excluded from the carbon EF for MSW used in the GHG inventory, and is assumed to be 75% of total carbon. This indicates a total carbon EF of 300 kg/t.eBrain (1994)fStewart et al (1996) estimated from total VOC factor assuming 27.2% is methane after USEPA(1997)gCORINAIR (1992)hIPCC (1997c)iEMEP/CORINAIR (1996)jIPCC (1997)kUSEPA (2004)lFynes et al (1994)mStewart (1997)nBased on reported emissions data from the EA Pollution Inventory (Environment Agency, 2008), SEPAs Scottish Pollutant Release inventory (SEPA, 2008), NI DoEs Inventory of Sources and Releases list (NI DoE, 2008) and direct communications with plant operators (Pers. Comms., 2008)oEnvironment Agency (2008)pUSEPA (1997)qIPCC (2006)rBased on Fynes, G. & Sage, P.W (1994)sBased on EU-ETS dataNENot Estimated The emission factors used for Power Stations are shown in Table A3.3.6. National emission estimates for SO2, NOx, CO and NMVOC are based on estimates for each power station provided by the process operators to UK regulators (EA, SEPA, NIDoE, all 2008). These emission estimates are reported on a power station basis and comprise emissions from more than one fuel in many cases (for example, those from coal fired plant will include emissions from oil used to light up the boilers). It is necessary to estimate emissions by fuel in order to fulfil IPCC and UNECE reporting requirements. Therefore, the reported emissions are allocated across the different fuels burnt at each station. Plant-specific fuel use data are obtained directly from operators, or obtained from EU ETS data held by UK regulators, or estimated from carbon emissions in a few cases where no other data are available. The allocation of reported emissions of a given pollutant across fuels is achieved as follows: Emissions from the use of each fuel at each power station are calculated using the reported fuel use data and a set of literature-based emission factors to give default emission estimates; For each power station, the default emission estimates for the various fuels are summed, and the percentage contribution that each fuel makes to this total is calculated; and The reported emission for each power station is then allocated across fuels by assuming each fuel contributes the same percentage of emissions as in the case of the default emission estimates. From 1991 to 1997 some UK power stations burnt orimulsion, an emulsion of bitumen and water. DTI (1998) gives the UK consumption of orimulsion. This fuel was only used by the electricity supply industry so these data were used in the category power stations. The carbon content of the fuel was taken from the manufacturers specification (BITOR, 1995). The emissions of NOx, SO2, NMVOC and CO were taken from Environment Agency (1998) but emission factors for methane and N2O were derived from those of heavy fuel oil but adjusted on the basis of the gross calorific value. The CO emission factor is based on measured data. This fuel is no longer used. Electricity has been generated from the incineration of municipal solid waste (MSW) to some extent from before 1990, though generation capacity increased markedly in the mid 1990s owing to construction and upgrading of incinerators to meet regulations which came into force at the end of 1996. Data are available (BERR, 2008) on the amount of waste used in heat and electricity generation and the emissions from the incinerators (Environment Agency, 2008). Since 1997, all MSW incinerators have generated electricity so emissions are no longer reported under the waste incineration category. In addition to MSW combustion, the inventory reports emissions from the combustion of scrap tyres. The carbon emissions are based on estimates compiled by DTI (2000) and a carbon emission factor based on the carbon content of tyres (Ogilvie, 1995). IPCC default factors based on oil are used. In 2000, the tyre-burning plant closed down. Also included are emissions from four plants that were designed to burn poultry litter, a plant burning wood, and a plant burning straw. In 2000 one of the poultry litter plants was converted to burn meat and bone meal. A number of large coal-fired power stations co-fire small quantities of biofuels. Most co-firing is with solid fuels such as short-rotation coppice (SRC), and these fuels were included in the GHGI for the first time for the 2008 version of the inventory. Quantities of liquid biofuels are very much lower and have not been included to date since the impact on emission estimates would be trivial. This will be reviewed annually, in case the quantities being consumed increase. Carbon emissions for poultry litter, straw and wood/SRC are not included in the UK total since these derive from biomass, but emissions are reported for information in the CRF. Emissions of CH4, N2O, CO, NOx, SO2, and NMVOC are also estimated. Emission factors are based on Environment Agency (2008) data and IPCC (1997) defaults for biomass. Fuel use data are provided directly by the operators of three poultry litter plant and have been estimated for the fourth poultry litter plant and the wood and straw-burning plant either by using EU ETS data or, where that is not available, based on information published on the internet by the operators of the power stations. There is considerable variation in emission factors for different sites due to the variability of fuel composition. Emission estimates are made from the generation of electricity from landfill gas and sewage gas (BERR, 2008). It is assumed that the electricity from this source is fed into the public supply or sold into non-waste sectors and hence classified as public power generation. The gases are normally used to power reciprocating gas (or dual-fuel engines), which may be part of combined heat and power schemes. Emission factors for landfill gas and sewage gas burnt in reciprocating engines have not been found so those for these gases burnt in gas turbines have been used instead (USEPA, 2008). BERR (2008) reports the energy for electricity production and for heat production separately. The emissions for electricity generation are allocated to Public Power whilst those for heat production are reported under Miscellaneous for landfill gas and Public Services for sewage gas. The carbon emissions are not included in the UK total as they are derived from biomass, but emissions are reported for information in the CRF. Petroleum Refining The NAEI category refinery (combustion) is mapped onto the IPCC category 1A1b Petroleum Refining. The emission factors used are shown in Table A3.3.1. Included in this category is an emission from the combustion of petroleum coke. This emission arises from the operation of fluidized bed catalytic crackers. During the cracking processes coke is deposited on the catalyst degrading its performance. The catalyst must be continuously regenerated by burning off the coke. The hot flue gases from the regeneration stage are used as a source of heat for the process. Since the combustion provides useful energy and the estimated amount of coke consumed is reported (BERR, 2008), the emissions are reported under 1A1b Petroleum Refining rather than as a fugitive emission under 1B2. Emission factors are either based on operators' data (UKPIA, 2008) or IPCC (1997) defaults for oil. The NAEI definition of Refinery (Combustion) includes all combustion sources: refinery fuels, electricity generation in refineries and fuel oils burnt in the petroleum industry. Manufacture of Solid Fuels The mappings used for these categories are given in Sections A3.1-3.2 and emission factors for energy consumption in these industries are given in Tables A3.3.1-3.3.4. The fuel consumption for these categories are taken from BERR (2008). The emissions from these sources (where it is clear that the fuel is being burnt for energy production) are calculated as in the base combustion module and reported in IPCC Table 1A Energy. Where the fuel is used as a feedstock resulting in it being transformed into another fuel, which may be burnt elsewhere, a more complex treatment is needed. The approach used by the NAEI is to perform a carbon balance over solid smokeless fuel (SSF) production and a separate carbon balance over coke production, sinter production, blast furnaces and basic oxygen furnaces. This procedure ensures that there is no double counting of carbon and is consistent with IPCC guidelines. No town gas was manufactured in the UK over the period covered by these estimates so this is not considered. The transformation processes involved are: Solid Smokeless Fuel Production coal ( SSF + carbon emission Coke Production/Sinter production/Blast furnaces/Basic oxygen furnaces (simplified) coal ( coke + coke oven gas + benzoles & tars + fugitive carbon emission coke + limestone + iron ore ( sinter + carbon emission sinter + coke + other reducing agents ( pig iron + blast furnace gas pig iron + oxygen ( steel + basic oxygen furnace gas Carbon emissions from each process can be estimated by comparing the carbon inputs and outputs of each stage of the transformation. The carbon content of the primary fuels are fixed based on the findings of the 2004 UK carbon factor review, as is the carbon content of coke oven gas, blast furnace gas, pig iron, and steel. The carbon contents of coke, coke breeze, and basic oxygen furnace gas are allowed to vary in order to enable the carbon inputs and outputs to be balanced. The calculations are so arranged that the total carbon emission corresponds to the carbon content of the input fuels in accordance with IPCC Guidelines. In the case of SSF production, the carbon content of both input (coal) and output (SSF) are held constant with the difference being treated as an emission of carbon from the process (since the carbon content of the input is always greater than the output). This procedure has been adopted because it has been assumed that some carbon would be emitted in the form of gases, evolved during the production process, and possibly used as a fuel for the transformation process. In reporting emissions from coke ovens and SSF manufacturing processes, emissions arising from fuel combustion for energy are reported under 1A1ci Manufacture of Solid Fuels, whilst emissions arising from the transformation process are reported under 1B1b Solid Fuel Transformation. In the case of blast furnaces, energy emissions are reported under 1A2a Iron and Steel and process emissions under 2C1 Iron and Steel Production. Other Energy Industries Section A3.2 shows the NAEI source categories mapped onto 1A1cii Other Energy Industries. All these emissions are treated according to the base combustion module using emission factors given in Tables A3.3.1 to A3.3.4. However, the treatment of gas oil use on offshore installations is anomalous: this is accounted for within the NAEI category Coastal Shipping and is mapped to 1A3dii National Navigation, based on the reporting of gas oil use in DUKES and the absence of any detailed data to split gas oil used in coastal vessels and that used to service offshore installations. There are no double counts in these emissions. The estimation of emissions from natural gas, LPG and OPG used as a fuel in offshore installations and onshore terminals is discussed in Section A3.3.8. These emissions are reported in category 1A1cii, but the methodology used in their estimation is closely linked to the estimation of offshore fugitive emissions. Manufacturing Industries and Construction (1A2) Other Industry In the NAEI, the autogenerators category reports emissions from electricity generation by companies primarily for their own consumption. The Inventory makes no distinction between electricity generation and combined heat and power or heat plants. Hence CHP systems where the electricity is fed into the public supply are classified as power stations and CHP systems where the electricity is used by the generator are classified as autogeneration. The autogenerators category is mapped onto the IPCC category 1A2f Other Industry. The IPCC 1A1 category also refers to CHP plant and heat plant. Transport (1A3) Aviation Overview of method to estimate emissions from civil aviation In accordance with the agreed guidelines, the UK inventory contains estimates for both domestic and international civil aviation. Emissions from international aviation are recorded as a memo item, and are not included in national totals. Emissions from both the Landing and Take Off (LTO) phase and the Cruise phase are estimated. The method used to estimate emissions from military aviation can be found towards the end of this section on aviation. In2004, the simple method previously used to estimate emissions from aviation overestimated fuel use and emissions from domestic aircraft because only two aircraft types were considered and the default emission factors used applied to older aircraft. It is clear that more smaller modern aircraft are used on domestic and international routes. Emissions from international aviation were correspondingly underestimated. A summary of the more detailed approach now used is given below, and a full description is given in Wattersonetal.(2004). The current method estimates emissions from the number of aircraft movements broken down by aircraft type at each UK airport, and so complies with the IPCC Tier3 specification. Emissions of a range of pollutants are estimated in addition to the reported greenhouse gases. In comparison with earlier methods used to estimate emissions from aviation, the current approach is much more detailed and reflects differences between airports and the aircraft that use them. Emissions from additional sources (such as aircraft auxiliary power units) are also now included. This method utilises data from a range of airport emission inventories compiled in the last few years by AEA. This work includes the RASCO study (23 regional airports, with a 1999 case calculated from CAA movement data) carried out for the Department for Transport (DfT), and the published inventories for Heathrow, Gatwick and Stansted airports, commissioned by BAA and representative of the fleets at those airports. Emissions of NOx and fuel use from the Heathrow inventory have been used to verify the results of this study. In 2006, the Department for Transport (DfT) published its report Project for the Sustainable Development of Heathrow (PSHD). This laid out recommendations for the improvement of emission inventories at Heathrow and lead to a revised inventory for Heathrow for 2002. For departures, the PSDH made recommendations for revised thrust setting at take-off and climb-out as well as revised cut-back heights. For landing, the PSDH made recommendations for revised reverse thrust setting and durations along with revised landing-roll times. In 2007, these recommendations for Heathrow were incorporated into the UK inventory. Since publication of the PSDH report, inventories at Gatwick and Stansted have been updated. These inventories incorporated many of the recommendations of the PSDH and have been used as a basis for the current UK inventory. Separate estimates have been made for emissions from the LTO cycle and the cruise phase for both domestic and international aviation. For the LTO phase, fuel consumed and emissions per LTO cycle are based on detailed airport studies and engine-specific emission factors (from the ICAO database). For the cruise phase, fuel use and emissions are estimated using distances (based on great circles) travelled from each airport for a set of representative aircraft. In the current UK inventory there is a noticeable reduction in emissions from 2005 to 2006 despite a modest increase in aircraft movements and kilometres flown. This is attributable to the propagation of more modern aircraft into the fleet. From 2006 to 2007 there is a further reduction in emissions, which is attributable to both a modest decrease in aircraft movements and kilometres flown and the propagation of more modern aircraft into the fleet. Emission Reporting Categories for Civil Aviation Table A3.3.7 below shows the emissions included in the emission totals for the domestic and international civil aviation categories currently under the UNFCCC, the EU NECD and the LRTAP Convention. Note the reporting requirements to the LRTAP Convention have altered recently the table contains the most recent reporting requirements Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 7: Components of Emissions Included in Reported Emissions from Civil Aviation EU NECDLRTAP Convention EU-MM/UNFCCC Domestic aviation (landing and take-off cycle [LTO])Included in national totalIncluded in national totalIncluded in national totalDomestic aviation (cruise)Not included in national totalNot included in national totalIncluded in national totalInternational aviation (LTO)Included in national totalIncluded in national totalNot included in national totalInternational aviation (cruise)Not included in national totalNot included in national totalNot included in national total Notes Emissions from the LTO cycle include emissions within a 1000m ceiling of landing. Aircraft Movement Data (Activity Data) The methods used to estimate emissions from aviation require the following activity data: Aircraft movements and distances travelled Detailed activity data has been provided by the UK Civil Aviation Authority (CAA). These data include aircraft movements broken down by: airport; aircraft type; whether the flight is international or domestic; and, the next/last POC (port of call) from which sector lengths (great circle) have been calculated. A summary of aircraft movement data is given in TableA3.3.8. Inland Deliveries of Aviation Spirit and Aviation Turbine Fuel Total inland deliveries of aviation spirit and aviation turbine fuel to air transport are given in BERR (2008). This is the best approximation of aviation bunker fuel consumption available and is assumed to cover international, domestic and military use. Consumption of Aviation Turbine Fuel by the Military Total consumption by military aviation is given in ONS (1995) and MOD (2005a) and is assumed to be aviation turbine fuel. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 8: Aircraft Movement Data International LTOs (000s)Domestic LTOs (000s)International Aircraft, Gm flownDomestic Aircraft, Gm flown1990410.1318.1635.498.81991397.4312.6623.997.01992432.8331.0705.9102.81993443.6338.0717.3106.51994461.9316.3792.6102.21995480.9329.6831.9107.41996507.2341.2871.5113.11997537.7346.0948.9118.31998576.4360.01034.6124.31999610.1368.11101.4129.12000646.8378.81171.3134.12001653.8393.11186.4142.52002650.2391.61178.7141.92003669.3401.71230.7145.22004700.6434.21335.1155.42005739.4458.01427.3165.32006762.4458.41492.6165.92007788.4450.91547.6163.0Notes Gm Giga metres, or 109 metres Estimated emissions from aviation are based on data provided by the CAA / International aircraft, Gm flown, calculated from total flight distances for departures from UK airports Emission factors used The following emission factors were used to estimate emissions from aviation. The emissions of CO2, SO2 and metals depend on the carbon, sulphur and metal contents of the aviation fuels. Emissions factors for CO2, SO2 and metals have been derived from the contents of carbon, sulphur and metals in aviation fuels. These contents are reviewed, and revised as necessary, each year. Full details of the emission factors used are given in Wattersonetal. (2004). Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 9: Carbon Dioxide and Sulphur Dioxide Emission Factors for Civil and Military Aviation for 2007 (kg/t) FuelCO2SO2Aviation Turbine Fuel8590.87Aviation Spirit8530.87Notes Carbon and sulphur contents of fuels provided by UKPIA (2008) Carbon emission factor as kg carbon/tonne Military aviation only uses ATF For the LTO-cycle calculations, emissions per LTO cycle are required for each of a number of representative aircraft types. Emission factors for the LTO cycle of aircraft operation have been taken from the International Civil Aviation Organization (ICAO) database. The cruise emissions have been taken from CORINAIR data (which are themselves developed from the same original ICAO dataset). Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 10: Non-CO2 Emission Factors for Civil and Military Aviation FuelUnitsCH4N2ONOxCONMVOCCivil aviationDomestic LTOASkt/Mt1.490.105.17956.2513.56Domestic CruiseASkt/Mt-0.106.753.620.24Domestic LTOATFkt/Mt0.150.1010.679.301.52Domestic CruiseATFkt/Mt-0.1013.702.510.55International LTOASkt/Mt1.920.102.971157.7817.54International CruiseASkt/Mt-0.106.90--International LTOATFkt/Mt0.110.1012.928.461.15International CruiseATFkt/Mt-0.1014.161.150.52Military aviationATFkt/Mt0.100.108.58.21.10Notes AS Aviation Spirit ATF Aviation Turbine Fuel Use of all aviation spirit assigned to the LTO cycle Method used to estimate emissions from the LTO cycle civil aviation domestic and international The basic approach to estimating emissions from the LTO cycle is as follows. The contribution to aircraft exhaust emissions (in kg) arising from a given mode of aircraft operation (see list below) is given by the product of the duration (seconds) of the operation, the engine fuel flow rate at the appropriate thrust setting (kg fuel per second) and the emission factor for the pollutant of interest (kg pollutant per kg fuel). The annual emissions total for the mode (kg per year) is obtained by summing contributions over all engines for all aircraft movements in the year. The time in each mode of operation for each type of airport and aircraft has been taken from individual airport studies. The time in mode is multiplied by an emission rate (the product of fuel flow rate and emission factor) at the appropriate engine thrust setting in order to estimate emissions for phase of the aircraft flight. The sum of the emissions from all the modes provides the total emissions for a particular aircraft journey. The modes considered are: Taxi-out; Hold; Take-off Roll (start of roll to wheels-off); Initial-climb (wheels-off to 450 m altitude); Climb-out (450 m to 1000 m altitude); Approach (from 1000 m altitude); Landing-roll; Taxi-in; APU use after arrival; and Auxiliary Power Unit (APU) use prior to departure. Departure movements comprise the following LTO modes: taxi-out, hold, take-off roll, initial-climb, climb-out and APU use prior to departure. Arrivals comprise: approach, landing-roll, taxi-in and APU use after arrival. Method used to estimate emissions in the cruise civil aviation - domestic and international The approaches to estimating emissions in the cruise are summarised below. Cruise emissions are only calculated for aircraft departures from UK airports (emissions therefore associated with the departure airport), which gives a total fuel consumption compatible with recorded deliveries of aviation fuel to the UK. This procedure prevents double counting of emissions allocated to international aviation. Estimating emissions of the indirect and nongreenhouse gases The EMEP/CORINAIR Emission Inventory Guidebook (EMEP/CORINAIR, 1996) provides fuel consumption and emissions of non-GHGs (NOx, HC and CO) for a number of aircraft modes in the cruise. The data are given for a selection of generic aircraft type and for a number of standard flight distances. The breakdown of the CAA movement by aircraft type contains a more detailed list of aircraft types than in the EMEP/CORINAIR Emission Inventory Guidebook. Therefore, each specific aircraft type in the CAA data has been assigned to a generic type in the Guidebook. Details of this mapping are given in Wattersonetal.(2004). A linear regression has been applied to these data to give emissions (and fuel consumption) as a function of distance:  EMBED Equation.3  Where:  EMBED Equation.3  is the emissions in cruise of pollutant  EMBED Equation.3  for generic aircraft type  EMBED Equation.3  and flight distance  EMBED Equation.3  (kg)  EMBED Equation.3  is the flight distance  EMBED Equation.3  is the generic aircraft type  EMBED Equation.3  is the pollutant (or fuel consumption)  EMBED Equation.3  is the slope of regression for generic aircraft type  EMBED Equation.3  and pollutant  EMBED Equation.3  (kg/km)  EMBED Equation.3  is the intercept of regression for generic aircraft type  EMBED Equation.3  and pollutant  EMBED Equation.3  (kg) Emissions of SO2 and metals are derived from estimates of fuels consumed in the cruise (see equation above) multiplied by the sulphur and metals contents of the aviation fuels for a given year. Estimating emissions of the direct greenhouse gases Estimates of CO2 were derived from estimates of fuel consumed in the cruise (see equation above) and the carbon contents of the aviation fuels. Methane emissions are believed to be negligible at cruise altitudes, and the emission factors listed in EMEP/CORINAIR guidance are zero (EMEP/CORINAIR, 1996); we have also assumed them to be zero. This was the assumption in the previous aviation calculation method also. Estimates of N2O have been derived from an emission factor recommended by the IPCC (IPCC, 1997c) and the estimates of fuel consumed in the cruise (see equation above). Classification of domestic and international flights The UK CAA has provided the aircraft movement data used to estimate emissions from civil aviation. The definitions the CAA use to categorise whether a movement is international or domestic are (CAA, per. comm.) Domestic A flight is domestic if the initial point on the service is a domestic and the final point is a domestic airport; and International A flight is international if either the initial point or the final point on the service is an international airport. Take, for example, a flight (service) that travels the following route: Glasgow (within the UK) Birmingham (within the UK) Paris (outside the UK). The airport reporting the aircraft movement in this example is Glasgow, and the final airport on the service is Paris. The CAA categorises this flight as international, as the final point on the service is outside the UK. Flights to the Channel Islands and the Isle of Man are considered to be within the UK in the CAA aircraft movement data. By following the IPCC Good Practice Guidance (IPCC, 2000), it is necessary to know whether passengers or freight are put down before deciding whether the whole journey is considered as an international flight or consisting of a (or several) domestic flight(s) and an international flight. We feel the consequence of the difference between CAA and IPCC definitions will have a small impact on total emissions. The CAA definitions above are also used by the CAA to generate national statistics of international and domestic aircraft movements. Therefore, the aircraft movement data used in this updated aviation methodology are consistent with national statistical datasets on aircraft movements. Overview of method to estimate emission from military aviation LTO data are not available for military aircraft movements, so a simple approach is used to estimate emissions from military aviation. A first estimate of military emissions is made using military fuel consumption data and IPCC (1997) and EMEP/CORINAIR (1999) cruise defaults shown in Table1 of EMEP/CORINAIR (1999) (see Table A3.3.10). The EMEP/CORINAIR (1999) factors used are appropriate for military aircraft. The military fuel data include fuel consumption by all military services in the UK. It also includes fuel shipped to overseas garrisons, casual uplift at civilian airports, but not fuel uplifted at foreign military airfields or ad hoc uplift from civilian airfields. Emissions from military aircraft are reported under IPCC category 1A5Other. Fuel reconciliation The estimates of aviation fuels consumed in the commodity balance table in the BERR publication DUKES are the national statistics on fuel consumption, and IPCC guidance states that national total emissions must be on the basis of fuel sales. Therefore, the estimates of emissions have been re-normalised based on the results of the comparison between the fuel consumption data in DUKES and the estimate of fuel consumed produced from the civil aviation emissions model. The ATF fuel consumptions presented in BERR DUKES include the use of both civil and military ATF, and the military ATF use must be subtracted from the DUKES total to provide an estimate of the civil aviation consumption. This estimate of civil ATF consumption has been used in the fuel reconciliation. Emissions will be re-normalised each time the aircraft movement data is modified or data for another year added. Geographical coverage of aviation emission estimates According to the IPCC Guidelines, "inventories should include greenhouse gas emissions and removals taking place within national (including administered) territories and offshore areas over which the country has jurisdiction." IPCC, (1997c); (IPPC Reference Manual, Overview, Page5). The national estimates of aviation fuels consumed in the UK are taken from BERR DUKES. The current (and future) methods used to estimate emissions from aviation rely on these data, and so the geographical coverage of the estimates of emissions will be determined by the geographical coverage of DUKES. UK BERR has confirmed that the coverage of the energy statistics in DUKES is England, Wales, Scotland and Northern Ireland plus any oil supplied from the UK to the Channel Islands and the Isle of Man. This clarification was necessary since this information cannot be gained from UK trade statistics. BERR have confirmed estimates in DUKES exclude Gibraltar and the other UK overseas territories. The BERR definition accords with that of the "economic territory of the United Kingdom" used by the UK Office for National Statistics (ONS), which in turn accords with the definition required to be used under the European System of Accounts (ESA95). Railways The UK GHGI reports emissions from both stationary and mobile sources. The inventory source railways (stationary) comprises emissions from the combustion of burning oil, fuel oil and natural gas by the railway sector. The natural gas emission derives from generation plant used for the London Underground. These stationary emissions are reported under 1A4a Commercial/Institutional in the IPCC reporting system. Most of the electricity used by the railways for electric traction is supplied from the public distribution system, so the emissions arising from its generation are reported under 1A1a Public Electricity. These emissions are based on fuel consumption data from BERR (2008). Emission factors are reported in Tables A3.3.1 to A3.3.3. The UK GHGI reports emissions from diesel trains in three categories: freight, intercity and regional. Emission estimates are based on train kilometres travelled and gas oil consumption by the railway sector. Gas oil consumption by passenger trains was calculated utilising data provided by the Association of Train Operating Companies (ATOC). As a result of issues regarding the availability of gas oil consumption data by passenger trains, fuel consumption was estimated on the basis of reported train kilometres travelled. Following compilation of the inventory, new fuel consumption data for 2007 was received from ATOC. However, due to concerns regarding the completeness of the latest data, the data will need to be quality checked before use in the Inventory. This data will be reviewed with the rail industry in the next round of the Inventory. For freight trains, the data is estimated by combining fuel consumption factors with train kilometre data from the UKs national rail trends yearbook. Emissions from diesel trains are reported under the IPCC category 1A3c Railways. As a consequence of increased train km travelled, the estimated fuel consumption in passenger and freight rail showed an increase in 2007 in comparison to 2006. Carbon dioxide, sulphur dioxide and nitrous oxide emissions are calculated using fuel-based emission factors and fuel consumption data. The fuel consumption is distributed according to: Train km data taken from the National rail trends yearbook (2008)  HYPERLINK "http://www.rail-reg.gov.uk/upload/pdf/375.pdf" http://www.rail-reg.gov.uk/upload/pdf/375.pdf for the three categories; Assumed mix of locomotives for each category; and Fuel consumption factors for different types of locomotive (LRC (1998), BR (1994) and Hawkins & Coad (2004)). Emissions of CO, NMVOC, NOx and methane are based on the train km estimates and emission factors for different train types. The emission factors shown in Table A3.3.11 are aggregate implied factors so that all factors are reported on the common basis of fuel consumption. Compared with the last version of the inventory, very minor changes to implied emission factors are noted for regional and intercity passenger rail with respect to NOx, CO and NMVOC, with the emission factors for regional trains increasing slightly and intercity showing a minor decrease from values used in 2006. These changes to the implied factors are a net result in minor changes in estimated km travel and fuel consumed. The emission factor for SO2 has declined from 3.0 kt/ Mt in 2006 to 2.67 kt/ Mt in 2007 in line with UKPIAs Table of the S-content in fuels in 2007 (UKPIA, 2008). Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 11: Railway Emission Factors (kt/Mt) C1CH4N2ONOxCONMVOCSO2Freight8700.171.280.18.94.52.67Intercity8700.221.242.113.25.72.67Regional8700.381.233.036.66.42.67Emission factors expressed as ktonnes carbon per Mtonne fuel Road Transport Emissions from road transport are calculated either from a combination of total fuel consumption data and fuel properties or from a combination of drive related emission factors and road traffic data. Improvements in the 2007 inventory There have been a number of significant improvements made to the road transport inventory including the use of new sets of emission factor-speed relationships for some pollutants (N2O and NOx), changes to vehicle speed data (affecting emission factors) and use for the first time of more detailed activity data showing annual variations in car fleet by engine size and travel survey information indicating variations in mileage done by cars of different engine size and fuel type on different types of road. A major change has been the adoption of new N2O emission factors and functions given by the COPERT 4 methodology for the Emissions Inventory Guidebook (EEA, 2007). These indicate a trend of decreasing emissions with higher Euro standards of petrol cars after the initial increase that occurred with the introduction of three-way catalyst technology at Euro 1 standards. A new set of emission factor-speed relationships for NOx has been adopted from the new database of factors developed by TRL on behalf of DfT (Boulter et al, 2008). Another major change has resulted from the update of vehicle speed data for different road and area types. This was done following a review of more up-to-date speed data from various DfT sources. The methodology of allocating vehicle-kilometres between petrol and diesel cars has also been changed. The new method has taken account of the fact that diesel cars do more annual mileage than petrol cars and lead to a different fuel mix on different road types. This is based on information collected from the National Travel Survey and the effect is applied from 1990 to 2007. In addition, the proportion of cars by engine size are taken to be variable from each year from 2000 reflecting a growing trend of bigger engine-sized cars purchased in recent years. These ratios have further been adjusted to take account of fact that bigger engine-sized cars do more annual mileage than smaller cars. This is again based on information collected from the National Travel Survey and is applied across the time series. Car fleet specific data for Northern Ireland are also incorporated into the 2007 inventory as Northern Ireland has seen a greater penetration of diesel cars than in Great Britain. DfT has revised their average miles per gallon fuel efficiency for HGVs between 1993 and 2007. These changes have only affected the distribution of fuel consumption and hence CO2 emissions between vehicle types, but the total CO2 emissions for road transport in all years remains unchanged, because these are based on the total fuel consumption figures reported in DUKES. Estimates of fuel consumption calculated for individual types of vehicles are normalised so the total adds up to the DUKES figures for petrol and diesel consumption (corrected for off-road consumption). However, for other pollutants where emissions are not directly related to fuel consumption, the changes in activity data and emission factors alter the total emissions for road transport reported in each year. Fuel-based emissions Emissions of carbon dioxide and sulphur dioxide from road transport are calculated from the consumption of petrol and diesel fuels and the sulphur content of the fuels consumed. Data on petrol and diesel fuels consumed by road transport in the UK are taken from the Digest of UK Energy Statistics published by the BERR and corrected for consumption by off-road vehicles. In 2007, 17.59 Mtonnes of petrol and 21.04 Mtonnes of diesel fuel (DERV) were consumed in the UK (a very small proportion of this was used in the Crown Dependencies). It was estimated that of this, around 1.5% of petrol was consumed by off-road vehicles and machinery, leaving 17.32 Mtonnes of petrol consumed by road vehicles in 2007. According to figures in DUKES (BERR, 2008), 0.119 Mtonnes of LPG were used for transport in 2007, down from 0.126 Mtonnes the previous year. Since 2005, there has been a rapid growth in consumption of biofuels in the UK. These are not included in the totals presented above for petrol and diesel which according to BERR refer only to mineral-based fuels (fossil fuels). According to statistics in DUKES and from HMRC (2008), an additional 0.11 Mtonnes bioethanol and 0.30 Mtonnes biodiesel were consumed in the UK in 2007, representing around 0.6% and 1.4% of fossil-fuel based petrol and diesel consumed, respectively. The CO2 emissions arising from consumption of these fuels are not included in the national totals. Emissions of CO2, expressed as kg carbon per tonne of fuel, are based on the carbon content (by mass) of the fuel; emissions of SO2 are based on the sulphur content of the fuel. Values of the fuel-based emission factors for CO2 and SO2 from consumption of petrol and diesel fuels are shown in Table A3.3.12. Values for SO2 vary annually as the sulphur-content of fuels change, and are shown in Table A3.3.12 for 2007 fuels based on data from UKPIA (2008). Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 12: Fuel-Based Emission Factors for Road Transport (kg/tonne fuel) FuelCaSO2bPetrol8550.061Diesel8630.030 a Emission factor in kg carbon/tonne, based on UKPIA (2005) b 2007 emission factor calculated from UKPIA (2008) figures on the weighted average sulphur-content of fuels delivered in the UK in 2007 Emissions of CO2 and SO2 can be broken down by vehicle type based on estimated fuel consumption factors and traffic data in a manner similar to the traffic-based emissions described below for other pollutants. In the 2007 inventory, the same procedure was used as in the 2006 inventory in the way that factors based on drive cycle test data, relating fuel consumption and speed, were combined with fleet-averaged fuel efficiency and vehicle CO2 factors from other sources. Depending on available sources of data, slightly different approaches were used for different vehicle classes, but the aim was to reconcile as much available information as possible. The important equations relating fuel consumption to average speed are based on the set of tailpipe CO2, CO and total hydrocarbon (THC) emission-speed equations developed by TRL (Barlow et al, 2001). The TRL equations were derived from their large database of emission measurements compiled from different sources covering different vehicle types and drive cycles. A substantial part of the emission measurements for Euro 1/I and 2/II standard vehicles come from test programmes funded by DfT and Defra and carried out in UK test laboratories between 1999 and 2001. The measurements were made on dynamometer test facilities under simulated real-world drive cycles. For cars, average fuel consumption factors were calculated from UK fleet-averaged CO2 emission factors for different car vintages (years of production) provided by DfT (2004a) following consultation with the Society of Motor Manufacturers and Traders (SMMT). Their dependence on speed used the TRL-based speed relations for vehicles categorised into each Euro emission class described in a later section. Each year of car production and entry into service was associated with different Euro emission standards. In this case then, the average fuel consumption factors for each petrol and diesel car Euro standard are linked directly to the average CO2 factors of cars entering new into the fleet from the information provided by DfT/SMMT and the TRL speed-related functions are used to define the variation, relative to the averaged value, in fuel consumption with speed and hence road type. For HGVs, the DfT provide statistics from a survey of haulage companies on the average miles per gallon fuel efficiency of different sizes of lorries (DfT, 2008a). A time-series of mpg figures from 1989 to the current year is provided by the road freight statistics and these can be converted to g fuel per kilometre fuel consumption factors. The figures will reflect the operations of haulage companies in the UK in terms of vehicle load factor and typical driving cycles, e.g. distances travelled at different speeds on urban, rural and motorway roads. The TRL speed-related functions based on test cycle measurements of more limited samples of vehicles are then used to define the variation, relative to the averaged value, in fuel consumption with speed and hence road type in a similar way to the method used for cars. For LGVs, buses and motorcycles, there are no additional statistics or datasets to use in conjunction with the research-based TRL speed-related functions. For these vehicles the inventory uses fuel consumption factors expressed as g fuel per kilometre for each vehicle type and road type calculated directly from the TRL equations grouped into Euro standards. Average fuel consumption factors are shown in TableA3.3.13 for cars, LGVs, buses and motorcycles, and respective Euro emission standard and road type in the UK. The different emission standards are described in a later section. TableA3.3.14 presents the fleet-averaged fuel consumption factors for rigid and articulated HGVs from 1990-2007 for urban, rural and motorway conditions based on the road freight statistics for HGVs up to 2007 published in DfT (2008a); for 1993 onwards HGV fuel consumption figures have been revised in DfT (2008a) as a result of data quality improvements and methodological changes, leading to a change in the factors presented in this table compared with the corresponding figures in last years version of the inventory. Using a model to calculate total petrol and diesel consumption by combining these factors with relevant traffic data (discussed in Section A3.3.5.3.1.1), the figures are compared with BERR figures for total fuel consumption in the UK published in DUKES (adjusted for off-road consumption). A normalisation procedure is used to correct the figures for each vehicle class so that the total calculated fuel consumption adds up to the DUKES figures. This normalisation process introduces uncertainties into the fuel consumption and hence CO2 emission estimates for individual vehicle classes even though the totals for road transport are known with high accuracy. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 13: Fuel Consumption Factors for Road Transport (in g fuel/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 14: Fuel Consumption Factors for HGVs (in g fuel/km) based on DfTs road freight statistics  For petrol, cars consume the vast majority of this fuel, so the DUKES figures provide a relatively accurate description of the trends in fuel consumption and CO2 emissions by petrol cars. A small residual is consumed by petrol LGVs and motorcycles, so their estimates are susceptible to fairly high levels of uncertainty introduced by the normalisation process. In order to provide a consistent comparison in the fuel consumption figures for petrol and diesel cars, the same normalisation factor (the relative adjustment necessary to bring the calculated petrol consumption in line with DUKES totals) derived for petrol cars was applied to diesel cars. The calculated fuel consumption for HGVs is also taken directly as implied by DfTs fuel efficiency statistics and are excluded from the normalisation process, so it is the calculated residual diesel consumption by LGVs and buses that are adjusted to bring the total diesel consumed to the same amount as reported in DUKES. This inevitably introduces uncertainties to the reported fuel consumption figures for these vehicle types. Total CO2 emissions from vehicles running on LPG are estimated on the basis of national figures (from BERR) on the consumption of this fuel by road transport. The CO2 emissions from LPG consumption cannot be broken down by vehicle type because there are no figures available on the total number of vehicles or types of vehicles running on this fuel. This is unlike vehicles running on petrol and diesel where the DfT has statistics on the numbers and types of vehicles registered as running on these fuels. It is believed that many vehicles running on LPG are cars and vans converted by their owners and that these conversions are not necessarily reported to vehicle licensing agencies. It is for this same reason that LPG vehicle emission estimates are not possible for other pollutant types, because these would need to be based on traffic data and emission factors for different vehicle types rather than on fuel consumption. The LPG consumption figures from BERR suggest that in comparison with petrol and diesel, relatively small numbers of vehicles run on LPG. Emissions from vehicles running on natural gas are not estimated at present, although the number of such vehicles in the UK is very small. Estimates are not made as there are no separate figures from BERR on the amount of natural gas used by road transport, nor are there useable data on the total numbers and types of vehicles equipped to run on natural gas. Traffic-based emissions Emissions of the pollutants NMVOCs, NOx, CO, CH4 and N2O are calculated from measured emission factors expressed in grammes per kilometre and road traffic statistics from the Department for Transport. The emission factors are based on experimental measurements of emissions from in-service vehicles of different types driven under test cycles with different average speeds. The road traffic data used are vehicle kilometre estimates for the different vehicle types and different road classifications in the UK road network. These data have to be further broken down by composition of each vehicle fleet in terms of the fraction of diesel- and petrol-fuelled vehicles on the road and in terms of the fraction of vehicles on the road made to the different emission regulations which applied when the vehicle was first registered. These are related to the age profile of the vehicle fleet in each year. Emissions from motor vehicles fall into three different types, which are each calculated in a different manner. These are hot exhaust emissions, cold-start emissions and, for NMVOCs, evaporative emissions. Hot exhaust emissions Hot exhaust emissions are emissions from the vehicle exhaust when the engine has warmed up to its normal operating temperature. Emissions depend on the type of vehicle, the type of fuel its engine runs on, the driving profile of the vehicle on a journey and the emission regulations which applied when the vehicle was first registered as this defines the type of technology the vehicle is equipped with that affects emissions For a particular vehicle, the drive cycle over a journey is the key factor that determines the amount of pollutant emitted. Key parameters affecting emissions are the acceleration, deceleration, steady speed and idling characteristics of the journey, as well as other factors affecting load on the engine such as road gradient and vehicle weight. However, work has shown that for modelling vehicle emissions for an inventory covering a road network on a national scale, it is sufficient to calculate emissions from emission factors in g/km related to the average speed of the vehicle in the drive cycle (Zachariadis and Samaras, 1997). Emission factors for average speeds on the road network are then combined with the national road traffic data. Vehicle and fuel type Emissions are calculated for vehicles of the following types: Petrol cars; Diesel cars; Petrol Light Goods Vehicles (Gross Vehicle Weight (GVW) d" 3.5 tonnes); Diesel Light Goods Vehicles (Gross Vehicle Weight (GVW) d" 3.5 tonnes); Rigid-axle Heavy Goods Vehicles (GVW ( 3.5 tonnes); Articulated Heavy Goods Vehicles (GVW ( 3.5 tonnes); Buses and coaches; and Motorcycles. Total emission rates are calculated by multiplying emission factors in g/km with annual vehicle kilometre figures for each of these vehicle types on different types of roads. Vehicle kilometres by road type Hot exhaust emission factors are dependent on average vehicle speed and therefore the type of road the vehicle is travelling on. Average emission factors are combined with the number of vehicle kilometres travelled by each type of vehicle on rural roads and higher speed motorways/dual carriageways and many different types of urban roads with different average speeds and the emission results combined to yield emissions on each of these main road types: Urban; Rural single carriageway; and Motorway/dual carriageway. DfT estimates annual vehicle kilometres for the road network in Great Britain by vehicle type on roads classified as trunk, principal and minor roads in built-up areas (urban) and non-built-up areas (rural) and motorways (DfT, 2008b). The DfT Report Transport Statistics Great Britain (DfT, 2008b) provides vehicle kilometres data up to 2007. Slight changes were made by DfT to the vehicle kilometres data for 2006 in the 2007 publication, but data for other years were not changed. Vehicle kilometre data for Northern Ireland by vehicle type and road class were provided by the Department for Regional Development (DRD), Northern Ireland, Road Services (DRDNI, 2002, 2003, 2006, 2007, 2008a). These provided a consistent time-series of vehicle km data for all years up to 2007. The Northern Ireland data have been combined with the DfT data for Great Britain to produce a time-series of total UK vehicle kilometres by vehicle and road type from 1970 to 2007. The vehicle kilometre data were grouped into the three road types mentioned above for combination with the associated hot exhaust emission factors. Table A  STYLEREF 2 \s 3.3.15 shows the time series in the UK vehicle kilometre data by vehicle and road type from 1990-2007. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 15: UK vehicle km by road vehicles billion vkm1990199520002001200220032004200520062007Petrol carsurban143.0139.7139.2138.7140.1136.2133.8129.8127.6124.9rural138.5128.3127.4127.4127.2124.6122.7118.6117.1113.4m-way47.846.048.448.848.246.445.944.043.141.5Diesel carsurban4.813.921.323.025.928.331.233.937.039.9rural8.123.035.338.242.646.951.755.961.065.1m-way4.211.919.120.823.024.927.729.832.334.3Petrol LGVsurban11.17.74.33.73.02.62.31.91.91.7rural11.48.34.74.13.63.12.72.32.32.2m-way4.03.02.01.81.41.21.10.91.00.9Diesel LGVsurban5.910.616.417.517.819.621.122.022.623.8rural6.411.818.419.822.223.925.527.028.030.5m-way2.04.17.68.38.59.110.010.511.111.7Rigid HGVsurban4.74.44.24.24.14.34.44.34.24.0rural7.57.07.67.68.18.38.28.28.38.5m-way3.73.54.34.34.34.34.44.34.34.3Artic HGVsurban1.11.11.11.11.01.01.11.01.01.0rural4.35.15.65.65.35.35.35.35.55.6m-way4.75.67.07.07.57.48.07.98.08.3Busesurban2.43.03.03.03.03.23.23.23.33.4rural1.71.51.61.61.81.81.61.51.61.8m-way0.60.50.60.60.50.50.50.50.60.6M/cycleurban3.31.92.22.42.63.12.83.02.73.2rural2.01.62.02.12.12.22.12.22.12.2m-way0.30.30.50.50.40.40.40.40.40.4 Vehicle speeds by road type The vehicle speed data used to calculate emission factors from the emission factor-speed relationships available for different pollutants were updated and applied to all previous years. Average speed data for traffic in a number of different areas were taken from the following main sources: Transport Statistics Great Britain (DfT, 2008b) provided averages of speeds in Central, Inner and Outer London surveyed at different times of day during 1990 to 2007. Speeds data from other DfTs publications such as Road Statistics 2006: Traffic, Speeds and Congestion (DfT, 2007a) and 2008 national road traffic and speed forecasts (DfT, 2008c) were used to define speeds in other urban areas, rural roads and motorways. Where new information is not available, previous NAEI assumptions were maintained or road speed limits used for the vehicles expected to observe these on the type of road concerned. TableA3.3.16 shows the speeds used in the 2007 inventory for light duty vehicles, HGVs and buses. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 16: Average Traffic Speeds in Great Britain  Vehicle fleet composition: by age, technology and fuel type Vehicle kilometre data based on traffic surveys do not distinguish between the type of fuels the vehicles are being run on (petrol and diesel) nor on their age. DfT Vehicle Licensing Statistics (DfT, 2008d) provide number of vehicles licensed on the road by fuel type; this data has traditionally been used to split the vehicle kilometres data by fuel type. However, in the 2007 inventory, this information is combined with data on the relative mileage done by petrol and diesel cars (DfT, 2008e, pers comm). This indicates that diesel cars do on average 60% more annual mileage than petrol cars. The information originated from the National Travel Survey (DfT, 2007b). It has been assumed that the additional mileage done by diesel cars is mainly done on motorways and rural roads. On this basis, the petrol car/diesel car mix on urban roads is assumed to be that indicated by the population mix according to vehicle licensing data (i.e. that there is no preferential use of diesel or petrol cars on urban roads) and the mix on rural and motorways adjusted to give an overall mileage pattern over all roads in the UK that leads to an average 60% higher annual mileage by diesel cars compared with petrol cars. This leads to the vehicle km data for petrol and diesel cars on different road types shown in Table A  STYLEREF 2 \s 3.3.15. In previous inventories, the same proportion of cars by engine size was used in the time series; however, the vehicle licensing statistics have shown that there has been a growing trend in the sales of bigger engine-sized cars in recent years, in particular for diesel cars. In the 2007 inventory, the proportion of cars by engine size varies from 2000 onwards based on the vehicle licensing data (DfT, 2008d). In addition, the relative mileage done by different size of vehicles was factored into the ratios, this is to take account of the fact that larger cars do more annual mileage than smaller cars (DfT, 2008e). The age of a vehicle determines the type of emission regulation that applied when it was first registered. These have successively entailed the introduction of tighter emission control technologies, for example three-way catalysts and better fuel injection and engine management systems. TableA3.3.17 shows the regulations that have come into force up to 2007 for each vehicle type. The average age profile and the fraction of petrol and diesel cars and LGVs in the fleet each year are based on the composition of the UK vehicle fleet using DfT Vehicle Licensing Statistics. The Transport Statistics Bulletin Vehicle Licensing Statistics: 2007 (DfT, 2008d) either gives historic trends in the composition of the UK fleet by age directly or provides sufficient information for this to be calculated from new vehicle registrations and average vehicle survival rates. Thus, year-of-first registration data for vehicles licensed in each year from 1990 to 2007 have been taken to reflect the age distribution of the fleet in these years. Statistics are also available on the number of new registrations in each year up to 2007, reflecting the number of new vehicles entering into service in previous years. The two sets of data combined allow an average survival rate to be determined for each type of vehicle. Particularly detailed information is available on the composition of the HGV stock by age and size. The age composition data are combined with data on the change in annual vehicle mileage with age to take account of the fact that newer vehicles on average travel a greater number of kilometres in a year than older vehicles. For cars and LGVs, such mileage by age data are from the National Travel Survey (DETR, 1998a); data for HGVs of different weights are taken from the Continuous Survey of Road Goods Transport (DETR, 1996a). Separate vehicle licensing statistics for private and light goods vehicles (PLG) in Northern Ireland are available from the Central Statistics and Research Branch of the Department of Regional Development in Northern Ireland (DRDNI, 2008b). These show a higher proportion of diesel cars here than in Great Britain. Unlike other regional licensing statistics, it is more likely that these statistics reflect the actual fuel mix of cars on the road in Northern Ireland and so this information was used in the inventory. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 17: Vehicles types and regulation classes Vehicle TypeFuelRegulationApprox. date into service in UK CarsPetrolPre ECE-15.00ECE-15.001/1/1971ECE-15.011/7/1975ECE-15.021/7/1976ECE-15.031/7/1979ECE-15.041/7/198391/441/EEC (Euro 1) 1/7/199294/12/EC (Euro 2)1/1/199798/69/EC (Euro 3)1/1/200198/69/EC (Euro 4)1/1/2006DieselPre-Euro 191/441/EEC (Euro 1) 1/1/199394/12/EC (Euro 2)1/1/199798/69/EC (Euro 3)1/1/200198/69/EC (Euro 4)1/1/2006LGVsPetrolPre-Euro 193/59/EEC (Euro 1)1/7/199496/69/EEC (Euro 2)1/7/199798/69/EC (Euro 3)1/1/2001 (<1.3t) 1/1/2002 (>1.3t)98/69/EC (Euro 4)1/1/2006DieselPre-Euro 193/59/EEC (Euro 1)1/7/199496/69/EEC (Euro 2)1/7/199798/69/EC (Euro 3)1/1/2001 (<1.3t) 1/1/2002 (>1.3t)98/69/EC (Euro 4)1/1/2006HGVs and Diesel (All types)Pre-1988buses88/77/EEC (Pre-Euro I)1/10/198891/542/EEC (Euro I)1/10/199391/542/EEC (Euro II)1/10/199699/96/EC (Euro III)1/10/200199/96/EC (Euro IV)1/10/2006MotorcyclesPetrolPre-2000: < 50cc, >50cc (2 st, 4st)97/24/EC: all sizes (Euro 1)1/1/20002002/51/EC (Euro 2)1/7/20042002/51/EC (Euro 3)1/1/2007 Assumptions are made about the proportion of failing catalysts in the petrol car fleet. For first-generation catalyst cars (Euro 1), it is assumed that the catalysts fail in 5% of cars fitted with them each year (for example due to mechanical damage of the catalyst unit) and that 95% of failed catalysts are repaired each year, but only for cars more than three years in age, when they first reach the age for MOT testing. Following discussions with DfT, a review of information from the Vehicle Inspectorate, TRL, the Cleaner Vehicles Task Force, industry experts and other considerations concerning durability and emission conformity requirements in in-service tests, lower failure rates are assigned to Euro 2, 3 and 4 petrol cars manufactured since 1996. The following failure rates are assumed in the inventory: Euro 1 5% Euro 2 1.5% Euro 3, 4 0.5% The inventory takes account of the early introduction of certain emission and fuel quality standards and additional voluntary measures to reduce emissions from road vehicles in the UK fleet. The Euro 3 emission standards for passenger cars (98/69/EC) came into effect from January 2001 (new registrations). However, some makes of cars sold in the UK already met the Euro 3 standards prior to this (DfT, 2001). Figures from the Society of Motor Manufacturers and Traders suggested that 3.7% of new cars sold in 1998 met Euro 3 standards (SMMT, 1999). Figures were not available for 1999 and 2000, but it was assumed that 5% of new car sales met Euro 3 standards in 1999 increasing to 10% in 2000. In 2001, an assumption was made that 15% of all new petrol cars sold in the UK met Euro 4 standards, increasing to 81% in 2004 even though the mandatory date of introduction of this standard is not until 2006 (DfT, 2004b). The remaining new petrol car registrations in 2001 - 2005 would meet Euro 3 standards. From 2006, all new cars must fully comply with Euro 4 standards. In January 2000, European Council Directive 98/70/EC came into effect relating to the quality of petrol and diesel fuels. This introduced tighter standards on a number of fuel properties affecting emissions. The principal changes in UK market fuels were the sulphur content and density of diesel and the sulphur and benzene content of petrol. The volatility of summer blends of petrol was also reduced, affecting evaporative losses. During 2000-2004, virtually all the diesel sold in the UK was of ultra-low sulphur grade (<50 ppmS), even though this low level sulphur content was not required by the Directive until 2005. Similarly, ultra-low sulphur petrol (ULSP) became on-line in filling stations in 2000, with around one-third of sales being of ULSP quality during 2000, the remainder being of the quality specified by the Directive. In 2001-2004, virtually all unleaded petrol sold was of ULSP grade (UKPIA, 2004). These factors and their effect on emissions were taken into account in the inventory. It is assumed that prior to 2000, only buses had made a significant switch to ULSD, as this fuel was not widely available in UK filling stations. Freight haulage operators have used incentives to upgrade the engines in their HGVs or retrofit them with particle traps. DETR estimated that around 4,000 HGVs and buses were retrofitted with particulate traps in 2000, and this would rise to 14,000 vehicles by the end of 2005 (DETR, 2000). This was accounted for in the inventory for its effects on NOx, CO and VOC emissions. Detailed information from DVLA was used on the composition of the motorcycle fleet in terms of engine capacity (DfT, 2008d). The information was used to calculate the proportion of motorcycles on the road less than 50cc (i.e. mopeds), >50cc, 2-stroke and >50cc, 4-stroke. Hot Emission Factors The emission factors for all pollutants are currently in the process of being reviewed and updated. For the direct Greenhouse Gases, the emission factors for N2O for all vehicle types have been updated with the latest recommendation of the Emissions Inventory Guidebook (EEA, 2007) derived from the COPERT 4 methodology Computer Programme to Calculate Emissions from Road Transport. For petrol cars and LGVs, emission factors are provided for different Euro standards and driving conditions (urban, rural, highway) with adjustment factors that take into account the vehicles accumulated mileage and the fuel sulphur content; both of these tend to increase emission factors. For diesel cars and LGVs, bulk emission factors are provided for different Euro standards and road types, with no fuel and mileage effects. The factors for HGVs, buses and motorcycles are unchanged and make no distinction between different Euro standards and road types. Table A  STYLEREF 2 \s 3.3.22 summarises the N2O emission factor for all vehicle types and road conditions in mg/km; the factors for petrol cars and LGVs are shown for zero accumulated mileage, but the inventory takes account of the increase in emissions with mileage. For the latest Euro 3 and 4 cars, emission factors in urban areas increase by around 15% over 50,000km, while for rural and motorway conditions, emission factors increase by as much as 38% over this distance, though starting from a smaller base. N2O emissions were considered to be a problem mainly with petrol cars fitted with three-way catalysts, being formed as a by-product on the catalyst surface during the NOx reduction process. Previously, the inventory assumed that petrol car emission factors for all Euro standards from Euro 1-4 were the same and larger than those for pre-Euro 1 cars, leading to an increase in the N2O inventory since the introduction of three-way catalysts in the 1990s. The latest compilation of emission factors now shows that emission factors have been declining with successive Euro standards since the first generation of catalysts for Euro 1, presumably due to better catalyst formulations as well as reductions in fuel sulphur content. Road transport is a relatively unimportant emitter of methane, being only produced as a consequence of incomplete combustion, but largely controlled by catalysts on petrol vehicles. Emission factors were unchanged in the inventory this year and are shown in Table A  STYLEREF 2 \s 3.3.20 in mg/km. Factors for pre-Euro I and/or Euro I standards for each vehicle type were taken from COPERT III (EEA, 2000) which provided either full emission factor-speed relationships or single average factors for urban, rural and highway roads. Methane emission factors for other Euro standards were scaled according to the ratio in the total hydrocarbon emission factors between the corresponding Euro standards (described below for NMVOC emissions). This assumes that methane emissions are changed between each successive Euro standard to the same extent as total hydrocarbons so that the methane fraction remains constant. The uncertainties in the CH4 and N2O factors can be expected to be quite large. However, the emission factors used for different technologies, Euro standards and fuels are likely to reflect realistic trends. Emission factors for NOx were updated in this years inventory following a major review and release of a new compilation of emission factors by TRL in a research programme for DfT (Boulter et al, 2008). This review considered a wide range of pollutants, but the factors released by DfT were for consultation and have yet to be finalised in light of responses from this consultation. The emission factors for NOx were, however, adopted for the 2007 inventory because of the urgent need to undertake some emissions mapping, forecasting and air quality modelling for this important air pollutant, even though there is a possibility the finalised figures may be altered slightly. Emission factors for NOx were provided for a more extensive range of vehicle types, sizes and Euro standards than had previously been available and were based on more up-to-date emission test data for in-service vehicles. The factors were presented as a series of emission factor-speed relationships for vehicles normalised to an accumulated mileage of 50,000 kilometres. Scaling factors were provided to take account of degradation in emissions with accumulated mileage for some vehicle classes, emission factors actually improved with mileage, but most deteriorated. Scaling factors were also provided to take into account the effects of fuel quality since some of the measurements would have been made during times when available fuels were of inferior quality than they are now, particularly in terms of sulphur content. Table A  STYLEREF 2 \s 3.3.24 summarises the NOx emission factors for all vehicle types and road conditions in g/km normalised to zero accumulated mileage (i.e. corresponding to new vehicles) and current fuels. The inventory takes into account the change in emissions with mileage using the TRL functions and change in mileage with age data and uses the fuel scaling factors to take into account the prevailing fuel quality in different years. Note that the new TRL compilation lumps together emission factors for all the pre-Euro 1 classes of petrol cars that were previously separated. This would only affect the time-series trends in the 1970s and 1980s. The emission factors used for CO and NMVOCs are the same as those used in last years inventory. Factors used for pre-Euro I vehicles are based on data from TRL (Hickman, 1998) and COPERT II, Computer Programme to Calculate Emissions from Road Transport produced by the European Topic Centre on Air Emissions for the European Environment Agency (EEA, 1997). Both these sources provide emission functions and coefficients relating emission factor (in g/km) to average speed for each vehicle type and Euro emission standard derived by fitting experimental measurements to some polynomial functional form. Emission factors for Euro 1/I and Euro 2/II vehicles are based on speed-emission factor relationships derived by TRL from emission test programmes carried out in the UK (Barlow et al, 2001). The tests were carried out on in-service vehicles on dynamometer facilities under simulated real-world drive cycles. The factors for NMVOCs are actually based on emission equations for total hydrocarbons (THC), the group of species that are measured in the emission tests. To derive factors for non-methane VOCS, the calculated g/km factors for methane were subtracted from the corresponding THC emission factors. The older in-service vehicles in the test surveys that were manufactured to a particular emission standard would have covered a range of different ages. Therefore, an emission factor calculated for a particular emission standard (e.g. ECE 15.04) from the emission functions and coefficients from TRL and COPERT II is effectively an average value for vehicles of different ages which inherently takes account of possible degradation in emissions with vehicle age. However, for the Euro 1 and 2 emission standards, the vehicles would have been fairly new when the emissions were measured. Therefore, based on data from the European Auto-Oil study, the deterioration in emissions with age or mileage was taken into account for catalyst cars. It was assumed that emissions of CO increase by 60% over 80,000 km, while emissions of NMVOCs increase by 30% over the same mileage (DETR, 1996b). Based on the average annual mileage of cars, 80,000 km corresponds to a time period of 6.15 years. Due to lack of measured data, emission factors for Euro 3/III and 4/IV vehicles had been estimated by applying scaling factors to the Euro 2/II factors. The scale factors for light duty vehicles take into consideration the requirement for new vehicles to meet certain durability standards set in the Directives. Scaling factors were first estimated by considering how much emissions from Euro 2/II vehicles would need to be reduced to meet the Euro 3/III and 4/IV limit values taking account of the characteristics and average speed of the regulatory test cycles used for type-approval of the vehicle. It was then assumed that emissions from new vehicles would be a certain percentage lower than the limit value-derived figure when new so that the vehicle would not have emissions that degrade to levels higher than the limit value over the durability period of the vehicle set in the Directives. The emission degradation rates permitted for Euro 3 and 4 light duty vehicles by Directive 98/69/EC are as follows: Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 18: Emission Degradation rates permitted for Euro 3 and 4 Light-Duty Vehicles by Directive 98/69/EC Degradation ratePetrol vehiclesHC and COEuro 3x1.2 over 80,000kmEuro 4x1.2 over 100,000kmDiesel vehiclesCOEuro 3x1.1 over 80,000kmEuro 4x1.1 over 100,000km For heavy-duty vehicles, the emission scaling factors were taken from COPERT III (EEA, 2000). The speed-emission factor equations were used to calculate emission factor values for each vehicle type and Euro emission standard at each of the average speeds of the road and area types shown in TableA1.3.16. The calculated values were averaged to produce single emission factors for the three main road classes described earlier (urban, rural single carriageway and motorway/dual carriageway), weighted by the estimated vehicle kilometres on each of the detailed road types taken from DfT. Table A  STYLEREF 2 \s 3.3.25 to 26 summarises the CO and NMVOC emission factor for all vehicle types and road conditions in g/km. For many pollutant and vehicle types, both TRL and COPERT provide separate equations for different ranges of vehicle engine capacity or vehicle weight. Emission factors calculated from these equations were therefore averaged, weighted according to the proportion of the different vehicle sizes in the UK fleet according to vehicle licensing statistics, to produce a single average emission factor for each main vehicle type and road type. This is the basis of the emission factors seen in these tables. Various other assumptions were applied to the emission factors, as follows. The emission factors used for NMVOCs, NOx and CO are already adjusted to take account of improvements in fuel quality for conventional petrol and diesel, mainly due to reductions in the fuel sulphur content of refinery fuels. An additional correction was also made to take account of the presence of biofuels blended into conventional fossil fuel. Uptake rates of biofuels were based on the figures from HMRC (2008) and it was assumed that all fuels were consumed as weak (typically 5%) blends with fossil fuel. The effect of biofuel (bioethanol and biodiesel) on exhaust emissions was represented by a set of scaling factors given by Murrells and Li (2008). A combined scaling factor was applied to the emission factors according to both the emission effects of the biofuel and its uptake rates each year. The effects are generally rather small for these weak blends. For CO and NMVOC emissions from motorcycles, speed-dependent functions provided by TRL (Hickman, 1998) for different engine sizes were used. Prior to 2000, all motorcycles are assumed to be uncontrolled. It was also assumed that mopeds (<50cc) operate only in urban areas, while the only motorcycles on motorways are the type more than 50cc, 4-stroke. Otherwise, the number of vehicle kilometres driven on each road type was disaggregated by motorcycle type according to the proportions in the fleet. Motorcycles sold since the beginning of 2000 were assumed to meet the Directive 97/24/EC and their emission factors were reduced according to the factors given in COPERT III (EEA, 2000). Further stages in emission reductions occur for >50cc motorcycles first registered from July 2004 and January 2007 and are referred to as Euro 2 and Euro 3. Account was taken of some heavy duty vehicles in the fleet being fitted with pollution abatement devices, perhaps to control particulate matter emissions (PM), or that otherwise lead to reductions in NOx, CO and NMVOC emissions beyond that required by Directives. Emissions from buses were scaled down according to the proportion fitted with oxidation catalysts or diesel particulate filters (DPFs) and the effectiveness of these measures in reducing emissions from the vehicles. The effectiveness of these measures in reducing emissions from a Euro II bus varies for each pollutant and is shown in TableA3.3.19. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 19: Scale Factors for Emissions from a Euro II Bus Running on Fitted with an Oxidation Catalyst or DPF NOxCONMVOCsOxidation catalystUrban0.970.200.39Rural0.950.220.55DPFUrban0.900.170.19Rural0.880.190.27 These scale factors based on data from LT Buses (1998). Euro II HGVs equipped with DPFs have their emissions reduced by the amounts shown in Table A3.3.20. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 20: Scale Factors for Emissions from a Euro II HGV Fitted with a DPF NOxCONMVOCsDPFUrban0.810.100.12Rural0.850.100.12Cold-Start Emissions When a vehicles engine is cold it emits at a higher rate than when it has warmed up to its designed operating temperature. This is particularly true for petrol engines and the effect is even more severe for cars fitted with three-way catalysts, as the catalyst does not function properly until the catalyst is also warmed up. Emission factors have been derived for cars and LGVs from tests performed with the engine starting cold and warmed up. The difference between the two measurements can be regarded as an additional cold-start penalty paid on each trip a vehicle is started with the engine (and catalyst) cold. The procedure for estimating cold-start emissions is taken from COPERT II (EEA, 1997), taking account of the effects of ambient temperature on emission factors for different vehicle technologies and its effect on the distance travelled with the engine cold. A factor, the ratio of cold to hot emissions, is used and applied to the fraction of kilometres driven with cold engines to estimate the cold start emissions from a particular vehicle type using the following formula: Ecold = ( . Ehot . (ecold/ehot - 1) where Ehot = hot exhaust emissions from the vehicle type ( = fraction of kilometres driven with cold engines ecold/ehot = ratio of cold to hot emissions for the particular pollutant and vehicle type The parameters ( and ecold/ehot are both dependent on ambient temperature and ( is also dependent on driving behaviour in, particular the average trip length, as this determines the time available for the engine and catalyst to warm up. The equations relating ecold/ehot to ambient temperature for each pollutant and vehicle type were taken from COPERT II and were used with an annual mean temperature for the UK of 11oC. This is based on historic trends in Met Office data for ambient temperatures over different parts of the UK. The factor ( is related to ambient temperature and average trip length by the following equation taken from COPERT II: ( = 0.698 - 0.051 . ltrip - (0.01051 - 0.000770 . ltrip) . ta where ltrip = average trip length ta = average temperature An average trip length for the UK of 8.4 km was used, taken from Andre et al (1993). This gives a value for ( of 0.23. This methodology was used to estimate annual UK cold start emissions of NOx, CO and NMVOCs from petrol and diesel cars and LGVs. Emissions were calculated separately for catalyst and non-catalyst petrol vehicles. Cold start emissions data are not available for heavy-duty vehicles, but these are thought to be negligible (Boulter, 1996). All the cold start emissions are assumed to apply to urban driving. Cold start emissions of N2O have been estimated for the first time using a method provided by the COPERT 4 methodology for the Emissions Inventory Guidebook (EEA, 2007). The method is simpler in the sense that it uses a mg/km emission factor to be used in combination with the distances travelled with the vehicle not fully warmed up., i.e. under cold urban conditions. For petrol cars and LGVs, a correction is made to the cold start factor that takes into account the vehicles accumulated mileage and the fuel sulphur content, in the same way as for the hot exhaust emission. The cold start factors in mg/km for N2O emissions from light duty vehicles are shown in Table A  STYLEREF 2 \s 3.3.21. There are no cold start factors for HGVs and buses. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 21: Cold Start Emission Factors for N2O (in mg/km) mg/kmPetrol carsPetrol LGVsPre-Euro 110.010.0Euro 134.043.4Euro 223.755.0Euro 311.620.9Euro 46.115.6 Data for estimating cold start effects on methane emissions are not available and are probably within the noise of uncertainty in the hot exhaust emission factors. Cold start effects are mostly an issue during the warm up of three-way catalyst on petrol cars when the catalyst is not at its optimum efficiency in reducing hydrocarbon, NOx and CO emissions, but without measured data, it would be difficult to estimate the effects on methane emissions. During this warm-up phase, one might expect higher methane emissions to occur, but as the catalyst is less effective in reducing methane emissions when fully warmed up compared with other, more reactive hydrocarbons on the catalyst surface, the cold start effect and the excess emissions occurring during the catalyst warm up phase is probably smaller for methane emissions than it is for the NMVOCs. As petrol cars contribute only 0.2% of all UK methane emissions, the effect of excluding potential and unquantifiable cold start emissions will be very small. Evaporative Emission Evaporative emissions of petrol fuel vapour from the tank and fuel delivery system in vehicles constitute a significant fraction of total NMVOC emissions from road transport. The procedure for estimating evaporative emissions of NMVOCs takes account of changes in ambient temperature and fuel volatility. There are three different mechanisms by which gasoline fuel evaporates from vehicles: i) Diurnal Loss This arises from the increase in the volatility of the fuel and expansion of the vapour in the fuel tank due to the diurnal rise in ambient temperature. Evaporation through tank breathing will occur each day for all vehicles with gasoline fuel in the tank, even when stationary. ii) Hot Soak Loss This represents evaporation from the fuel delivery system when a hot engine is turned off and the vehicle is stationary. It arises from transfer of heat from the engine and hot exhaust to the fuel system where fuel is no longer flowing. Carburettor float bowls contribute significantly to hot soak losses. iii) Running Loss These are evaporative losses that occur while the vehicle is in motion. Evaporative emissions are dependent on ambient temperature and the volatility of the fuel and, in the case of diurnal losses, on the daily rise in ambient temperature. Fuel volatility is usually expressed by the empirical fuel parameter known as Reid vapour pressure (RVP). For each of these mechanisms, equations relating evaporative emissions to ambient temperature and RVP were developed by analysis of empirically based formulae derived in a series of CONCAWE research studies in combination with UK measurements data reported by TRL. Separate equations were developed for vehicles with and without evaporative control systems fitted such as carbon canister devices. The overall methodology is similar to that reported by COPERT II (EEA, 1997), but the data are considered to be more UK-biased. Evaporative emissions are calculated using monthly average temperature and RVP data. Using this information, evaporative emissions are calculated from the car fleet for each month of the year and the values summed to derive the annual emission rates. Calculating emissions on a monthly basis enables subtle differences in the seasonal fuel volatility trends and differences in monthly temperatures to be better accounted for. Monthly mean temperatures from 1970-2007 were used for the calculations based on Met Office for Central England (CET data). The monthly average, monthly average daily maximum and monthly average diurnal rise in temperatures were required. The monthly average RVP of petrol sold in the UK used historic trends data on RVP and information from UKPIA on the RVP of summer and winter blends of fuels supplied in recent years and their turnover patterns at filling stations (Watson, 2001, 2003). The average RVP of summer blends of petrol in the UK in 2007 was 68 kPa, 2kPa below the limit set by European Council Directive 98/70/EC for Member States with arctic summer conditions (UKPIA, 2008). All the equations for diurnal, hot soak and running loss evaporative emissions from vehicles with and without control systems fitted developed for the inventory are shown in TableA3.3.27. The inventory uses equations for Euro 1 cars with first generation canister technology, based on early measurements, but equations taken from COPERT III leading to lower emissions were used for Euro 2-4 cars as these better reflected the fact that modern cars must meet the 2g per test limit on evaporative emissions by the diurnal loss and hot soak cycles under Directive 98/69/EC. For diurnal losses, the equations for pre-Euro 1 (non-canister) and Euro 1 cars were developed from data and formulae reported by CONCAWE (1987), TRL (1993) and ACEA (1995). Equations for Euro 2-4 cars were taken from COPERT III. The equations specified in TableA3.3.27 give diurnal loss emissions in g/vehicle.day for uncontrolled (DLuncontrolled) and Euro 1 and Euro 2-4 canister controlled vehicles (DLEU1, DLEUII-IV). Total annual diurnal losses were calculated from the equation: Ediurnal = 365 . N . (DLuncontrolled . Funcontrolled + DLEU1 . FEUI + DLEUII-IV . FEUII-IV) where: N = number of petrol vehicles (cars and LGVs) in the UK parc Funcontrolled = fraction of vehicles not fitted with carbon canisters, assumed to be the same as the fraction of pre-Euro 1 vehicles FEUI = fraction of Euro 1 vehicles in the fleet FEUII-IV = fraction of Euro 2-4 vehicles in the fleet For hot soak losses, the equations were developed from data and formulae reported by CONCAWE (1990), TRL (1993) and COPERT II. The equations specified in TableA3.3.27 give hot soak loss emissions in g/vehicle.trip for uncontrolled (HSuncontrolled) and Euro 1 and Euro 2-4 canister controlled (HSEUI, HSEUII-IV) vehicles. Total annual hot soak losses were calculated from the equation: Ehot soak = (VKM/ ltrip) . (HSuncontrolled . Funcontrolled + HSEU1 . FEUI + HSEUII-IV . FEUII-IV) where VKM = total number of vehicle kilometres driven in the UK by the petrol vehicles (cars and LGVs) ltrip = average trip length (8.4 km in the UK) For running losses, the equations were developed from data and formulae reported by CONCAWE (1990) and COPERT II. The equations specified in TableA3.3.27 give running loss emissions in g/vehicle.km for uncontrolled (RLuncontrolled) and canister controlled (RLcontrolled) vehicles with no distinction made between Euro 1 and Euro 2-4 canister cars. Total annual running losses were calculated from the equation: Erunning loss = VKM. (RLuncontrolled . Funcontrolled + RLcontrolled . Fcontrolled) where Fcontrolled = FEUI + FEUII-IV Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 22: N2O Emission Factors for Road Transport (in mg/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 23: Methane Emission Factors for Road Transport (in mg/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 24: NOx Emission Factors for Road Transport (in g/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 25: CO Emission Factors for Road Transport (in g/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 26: NMVOC Emission Factors for Road Transport (in g/km)  Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 27: Equations for diurnal, hot soak and running loss evaporative emissions from vehicles with and without control systems fitted Emission factorUnitsUncontrolled vehicle (pre-Euro I)Diurnal loss (DLuncontrolled)g/vehicle.day1.54 * (0.51*Trise + 0.62*Tmax + 0.22*RVP - 24.89)Hot soak (HSuncontrolled)g/vehicle.tripexp(-1.644 + 0.02*RVP + 0.0752*Tmean)Running loss (RLuncontrolled)g/vehicle.km0.022 * exp(-5.967 + 0.04259*RVP + 0.1773*Tmean) Emission factorUnitsCarbon canister controlled vehicle (Euro I)Diurnal loss (DLEUI)g/vehicle.day0.3 * (DLuncontrolled)Hot soak (HSEUI)g/vehicle.trip0.3 * exp(-2.41 + 0.02302*RVP + 0.09408*Tmean)Running loss (RLcontrolled)g/vehicle.km0.1 * (RLuncontrolled) Emission factorUnitsCarbon canister controlled vehicle (Euro II-IV)Diurnal loss (DLEUII-IV)g/vehicle.day0.2 * 9.1 * exp(0.0158*(RVP-61.2) + 0.0574*(Tmax-Trise-22.5) + 0.0614*(Trise-11.7))Hot soak (HSEUII-IV)g/vehicle.trip0Running loss (RLcontrolled)g/vehicle.km0.1 * (RLuncontrolled) Where: Trise = diurnal rise in temperature in oC Tmax = maximum daily temperature in oC Tmean = annual mean temperature in oC RVP = Reid Vapour Pressure of petrol in kPa Navigation The UK GHGI provides emission estimates for coastal shipping, naval shipping and international marine. Coastal shipping is reported within IPCC category 1A3dii National Navigation and includes emissions from diesel use at offshore oil & gas installations. A proportion of this diesel use will be for marine transport associated with the offshore industry but some will be for use in turbines, motors and heaters on offshore installations. Detailed fuel use data is no longer available to determine emissions from diesel use in fishing vessels, as the DTI gas oil dataset was revised in the 2004 inventory cycle. All emissions from fishing are now included within the coastal shipping sector, 1A3dii National Navigation. The emissions reported under coastal shipping and naval shipping are estimated according to the base combustion module using the emission factors given in Table A3.3.1. The NAEI category International Marine is the same as the IPCC category 1A3i International Marine. The estimate used is based on the following information and assumptions: (i) Total deliveries of fuel oil, gas oil and marine diesel oil to marine bunkers are given in BERR (2008); (ii) Naval fuel consumption is assumed to be marine diesel oil (MOD, 2008). Emissions from this source are not included here but are reported under 1A5 Other; and (iii) The fuel consumption associated with international marine is the marine bunkers total minus the naval consumption. The emissions were estimated using the emission factors shown in Table A3.3.1. Emissions from 1A3i International Marine are reported for information only and are not included in national totals. Bunker fuels data for shipping are provided to the BERR by UKPIA, and are based on sale of fuels to UK operators going abroad and overseas operators (assumed to be heading abroad) (DTI 2004, per. comm.). Emissions from navigation are based on emission factors for different types of shipping and a detailed examination of their activities in UK waters. In particular, detailed information on shipping emission factors has been used from the study done by Entec UK Ltd for the European Commissions (Entec, 2005) and from the more recent EMEP/CORINAIR Handbook (EMEP/CORINAIR, 2003). Lloyds Marine Intelligence Unit (LMIU) publishes ship arrivals at UK ports by type and dead weight for four different vessel types: tankers, Ro-Ro ferry vessels, fully cellular container vessels and other dry cargo vessels. Fuel use between different vessel types has been apportioned on the basis of the vessels main engine power as well as number of port arrivals. The main engine power for the Gross Registered Tonnage (GRT) groups used in the LMIU table was estimated. Then the product of vessel (type, GRT) port visits multiplied by the estimated main engine power was calculated and summed for each of the four vessel types. The distribution of total engine power summed over a year was then used to distribute the DUKES fuel consumption among the four vessel types. Different engine types when fuelled with fuel oil, marine gas oil or marine diesel oil have different emission factors (kg pollutant emitted /tonne of fuel used). For NOx and NMVOCs, it was possible to use data from the Entec study to produce a weighted mean emission factor for each of the four LMIU vessel types based on their average engine size and fuel type. Aggregated emission factors for the whole UK shipping activity were then calculated by weighting each vessel types factor with the proportion of fuel consumed by each vessel type. Emissions of CH4, CO and N2O are not covered in the Entec report, so emission factors quoted in the Corinair handbook were used. Emissions of SO2 are based on the fuel sulphur content and amount of each type of fuel used. Other Sectors (1A4) The mapping of NAEI categories to 1A4 Other Sectors is shown in Section A3.2. For most sources, the estimation procedure follows that of the base combustion module using BERR reported fuel use data and emission factors from Table A3.3.1. The NAEI category public service is mapped onto 1A4a Commercial and Institutional. This contains emissions from stationary combustion at military installations, which should be reported under 1A5a Stationary. Also included are stationary combustion emissions from the railway sector, including generating plant dedicated to railways. Also included in 1A4 are emissions from the miscellaneous sector, which includes emissions from the commercial sector and some service industries. Emissions from 1A4b Residential and 1A4c Agriculture/Forestry/Fishing are disaggregated into those arising from stationary combustion and those from off-road vehicles and other machinery. The estimation of emissions from off-road sources is discussed in Section A3.3.7.1 below. Emissions from fishing vessels are now included within the coastal shipping sector, due to the withdrawal of more detailed fuel use datasets that have historically been provided by BERR but are now determined to be of questionable accuracy. Other (1A5) Emissions from military aircraft and naval vessels are reported under 1A5b Mobile. The method of estimation is discussed in Sections A3.3.5.1 and A3.3.5.4 with emission factors given Table A3.3.1. Note that military stationary combustion is included under 1A4a Commercial and Institutional due to a lack of more detailed data. Emissions from off-road sources are estimated and are reported under the relevant sectors, i.e. Other Industry, Residential, Agriculture and Other Transport. The methodology of these estimates is discussed in Section A3.3.7.1. Estimation of Other Off-Road Sources Emissions are estimated for 77 different types of portable or mobile equipment powered by diesel or petrol driven engines. These range from machinery used in agriculture such as tractors and combine harvesters; industry such as portable generators, forklift trucks and air compressors; construction such as cranes, bulldozers and excavators; domestic lawn mowers; aircraft support equipment. In the NAEI they are grouped into four main categories: domestic house & garden agricultural power units (includes forestry) industrial off-road (includes construction and quarrying) aircraft support machinery. The mapping of these categories to the appropriate IPCC classes is shown in Section 3.2. Aircraft support is mapped to Other Transport and the other categories map to the off-road vehicle subcategories of Residential, Agriculture and Manufacturing Industries and Construction. Emissions are calculated from a bottom-up approach using machinery- or engine-specific emission factors in g/kWh based on the power of the engine and estimates of the UK population and annual hours of use of each type of machinery. The emission estimates are calculated using a modification of the methodology given in EMEP/ CORINAIR (1996). Emissions are calculated using the following equation for each machinery class: Ej = Nj . Hj . Pj . Lj . Wj.(1 + Yj . aj /2). ej where Ej = Emission of pollutant from class j (kg/y) Nj = Population of class j. Hj = Annual usage of class j (hours/year) Pj = Average power rating of class j (kW) Lj = Load factor of class j (-) Yj = Lifetime of class j (years) Wj = Engine design factor of class j (-) aj = Age factor of class j (y-1 ) ej = Emission factor of class j (kg/kWh) For petrol-engined sources, evaporative NMVOC emissions are also estimated as: Evj = Nj . Hj . evj where Evj = Evaporative emission from class j kg evj = Evaporative emission factor for class j kg/h The population, usage and lifetime of different types of off-road machinery were updated following a study carried out by AEA Energy & Environment on behalf of the Department for Transport (Netcen, 2004a). This study researched the current UK population, annual usage rates, lifetime and average engine power for a range of different types of diesel-powered non-road mobile machinery. Additional information including data for earlier years were based on research by Off Highway Research (2000) and market research polls amongst equipment suppliers and trade associations by Precision Research International on behalf of the former DoE (Department of the Environment) (PRI, 1995, 1998). Usage rates from data published by Samaras et al (1993, 1994) were also used. The population and usage surveys and assessments were only able to provide estimates on activity of off-road machinery for years up to 2004. These are one-off studies requiring intensive resources and are not updated on an annual basis. There are no reliable national statistics on population and usage of off-road machinery nor figures from the BERR on how these fuels, once they are delivered to fuel distribution centres around the country, are ultimately used. Therefore, other activity drivers were used to estimate activity rates for the four main off-road categories from 2005-2007. For industrial machinery, manufacturing output statistics were used to scale 2005-2007 activity rates relative to 2004; for domestic house and garden machinery, trends in number of households were used; for airport machinery, statistics on number of take-off and landings at UK airports were used. The emission factors used came mostly from EMEP/CORINAIR (1996) though a few of the more obscure classes were taken from Samaras & Zierock (1993). The load factors were taken from Samaras (1996). Emission factors for garden machinery, such as lawnmowers and chainsaws were updated following a review by Netcen (2004b), considering the impact of Directive 2002/88/EC on emissions from these types of machinery. Aggregated emission factors for the four main off-road machinery categories in 2007 are shown in Table A3.3.28 by fuel type. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 28 Aggregate Emission Factors for Off-Road Source Categories in 2007 (t/kt fuel) SourceFuelC2CH4N2ONOxCONMVOCSO23Domestic House&GardenDERV8630.1651.35849.874.52.70.030Domestic House&GardenPetrol8551.4770.0324.11698.397.40.061Agricultural Power UnitsGas Oil8700.1561.27133.9416.05.92.67Agricultural Power UnitsPetrol8552.1750.0151.45716.3248.60.061Industrial Off-roadGas Oil8700.1611.36035.2617.06.12.67Industrial Off-roadPetrol8553.6240.0496.00994.838.00.061Aircraft SupportGas Oil8700.1651.29333.3512.54.82.67 Emission factors reported are for 2007 Emission factor as kg carbon/t, UKPIA (2004) Based on sulphur content of fuels in 2007 from UKPIA (2008). The emission factors used for carbon were the standard emission factors for DERV, gas oil and petrol given in Table A3.3.1. Fugitive Emissions From fuels (1B) Solid Fuels (1B1) Coal Mining Emissions for IPCC categories 1B1ai Underground Mines-mining, 1B1ai Underground Mines-post-mining and 1B1aii Surface Mines are calculated from saleable coal production statistics reported by BERR (2008). Licensed mines referred to privately owned mines and were generally smaller and shallower than previously nationalised mines. The distinction was sufficiently marked to allow the use of a separate emission factor. Data on the shallower licensed mines are supplied by Barty (1995) up to 1994. Following privatisation, the distinction between licensed mines and deep mines no longer exists and all domestically produced coal that is not open-cast is assumed to be deep mined. For 1995, data from 1994 were used but in subsequent years the distinction has been abandoned. The emission factors used are shown in Table A3.3.29. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 29: Methane Emission Factors for Coal Mining (kg/t coal) YearDeep MinedCoal Storage & TransportaLicensed MinecOpen Castc199010.0a1.161.360.34199110.2a1.161.360.34199211.0a1.161.360.34199313.1b,d1.161.360.34199413.0b,d1.161.360.34199513.0b,d1.161.360.34199613.4b,d1.161.360.34199713.4b,d1.161.360.34199813.4b1.16-0.34199913.5b1.16-0.34200014.0b1.16-0.34200112.6b1.16-0.34200213.5b1.16-0.34200311.7b1.16-0.34200413.7b1.16-0.34200512.6b1.16-0.34200610.6b1.16-0.3420077.45b1.16-0.34 a Bennet et al (1995) b Factor based on UK Coal Mining Ltd data c Williams (1993) d Based on 1998 factor from UK Coal Mining Ltd. (in m3/tonne) extrapolated back from 1998 to 1993 as no other data are available The licensed and open cast factors are taken from Williams (1993). The deep mined factors for 1990 -1992 and the coal storage factor are taken from Bennet et al (1995). This was a study on deep mines which produced estimates of emissions for the period 1990-93. This was a period over which significant numbers of mines were being closed, hence the variation in emission factors. The emission factors for 1998-2004 are based on operator's measurements of the methane extracted by the mine ventilation systems. The mines surveyed cover around 90% of deep mined production. No time series data are available for 1993-97, so the 1998 factor was used. Methane extracted is either emitted to atmosphere or utilised for energy production. Methane is not flared for safety reasons. The factors reported in Table A3.3.26 refer to emissions and exclude the methane utilised. The coal storage and transport factor is only applied to deep mined coal production. The activity data for the coal mining emissions are reported in the CRF tables attached as a CD to this report. The number of active deep mines reported is defined as the number of mines producing at any one time during the period (Coal Authority, 2005). Hence, this would include large mines as well as small ones or those that only produced for part of the year. The colliery methane utilisation data are taken from BERR (2008). Methane emissions from closed coal mines are accounted for within Sector 1B1a of the UK inventory, with estimates based on consultation with the author of a recent study funded by Defra (Kershaw, UK Coal, 2007). The original study into closed coal mine emissions was conducted during 2005. The estimation method for both historic and projected methane emissions from UK coal mines comprised two separate sets of calculations to estimate emissions from (1) coal mines that had been closed for some years, and (2) methane emissions from mines that had recently closed or were forecast to close over 2005 to 2009. The 2005 study derived emission estimates for the years 1990 to 2050 using a relationship between emissions and the quantity of the underlying methane gas within the abandoned mine workings, including site-specific considerations of the most appropriate decay model for the recently closed mines. Consultation with the author has confirmed the actual mine closure programme in the UK and has thus provided updated estimates for 2005 and 2006. The emission calculations include estimates for the methane utilised or burned at collieries and other mitigating factors such as flooding of closed coal mines which reduces the source of methane gas over time. Methane emissions from closed mines reach the surface through many possible flow paths: vents, old mine entries, diffuse emission through fractured and permeable strata. Direct measurement of the total quantity of gas released from abandoned mines is not practical. Emission estimates for 1990 to 2050 have been calculated using a relationship between emission and the quantity of the underlying methane gas within the abandoned mine workings. Methane reserves have been calculated for all UK coalfields that are not totally flooded from 1990 with projections to 2050. The gas reserves are calculated by totalling all the gas quantities in individual seams likely to have been disturbed by mining activity. To enable calculation of the reserves over time, it has been necessary to calculate the rises in water levels in the abandoned mines due to water inflow. As workings become flooded they cease to release significant amounts of methane to the surface. Monitoring has been carried out to measure methane emission from vents and more diffuse sources. Monitoring of vents involved measurement of the flows and concentrations of the gas flowing out of the mine. Monitoring of more diffuse sources required collection of long-term gas samples to measure any increases in background atmospheric methane level in the locality. Methane flows measured by both methods showed a general increase with the size of the underlying gas reserve. The data indicated an emission of 0.74% of the reserve per year as a suitable factor to apply to the methane reserve data in order to derive methane emission estimates for abandoned UK coalfields for 1990 to 2050. Solid Fuel Transformation Fugitive emissions from solid fuel transformation processes are reported in IPCC category 1B1b. The IPCC Revised 1996 Guidelines do not provide any methodology for such estimates, hence emissions are largely based on default emission factors. Combustion emissions from these processes have already been discussed in Section A3.3.3. In a coke oven, coal is transformed into coke and coke oven gas. The coke oven gas is used as a fuel to heat the coke oven or elsewhere on the site. The coke may be used elsewhere as a fuel or as a reducing agent in metallurgical processes. A carbon balance is performed over the coke oven on the fuels input and the fuels produced as described in Section A.3.3.1. Process emissions of other pollutants from coke ovens are estimated either on the basis of total production of coke or the coal consumed. Emission factors are given in Table A3.3.30. Emissions of carbon from solid smokeless fuel production are calculated using a mass balance approach, described previously in Section A.3.3.1. A similar mass balance is carried out for SO2. For emissions of other pollutants, a mass balance approach is not used. It is likely that emissions will arise from the combustion of the gases produced by some SSF retorts but this combustion is not identified in the energy statistics. Process emissions from SSF plant are estimated on the basis of total production of SSF. The emission factors used are given in Table A3.3.30 and are based on US EPA (2008) factors for coke ovens. There are a number of processes used in the UK ranging from processes similar to coking to briquetting of anthracite dust and other smokeless fuels. Given the number of processes in use these estimates will be very uncertain. Data are available on the production of SSF and the fuels used (BERR, 2008). It is clear that in recent years both coke and imported petroleum coke have been used in the production of smokeless fuels. Data on the total UK imports and exports of petroleum coke are available but little information is available on its consumption. In the GHGI, it is assumed that 245 kt per annum of petroleum coke were used in SSF production from 1990 to 1998 based on data provided within DUKES (DTI, 1999). For 1999-2006 approximate estimates based on data provided in later versions of DUKES are used, with petroleum coke known to be burnt by other sectors subtracted from the DUKES figures. The data for 1999 onwards are believed to be more accurate than the earlier data, and are considerably lower as well. Further development of the petroleum coke activity data would be desirable. The carbon content of the petroleum coke consumed is not included in the SSF carbon balance instead it is allocated to the domestic sector as a separate fuel. Coke used by SSF manufacturers is assumed to be burnt as a fuel and is also not included in the carbon balance. The model used is not entirely satisfactory but further information would be required before a more accurate carbon balance could be developed. Emissions from the combustion of fuels to heat the smokeless fuel retorts are reported under 1A1ci Manufacture of Solid Fuels, however process emissions and the residual carbon emission discussed above are considered to be fugitives and are reported under 1B1b Solid Fuel Transformation. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 30: Emission Factors Used for Coke and Solid Smokeless Fuel Production UnitsCH4CONOxSO2NMVOCCokekt/Mt coke made0.0802a2.22c-1.77c0.0261eCokekt/Mt coal consumed--0.02b-SSFkt/Mt SSF made0.0802a0.0156c0.0236c-0.0178aSSFkt/Mt coal consumed---5.957d- a EIPPCB, (2000) b USEPA (2004) c Factor for 2006 based on Environment Agency (2007) d Based on mass balance but zero for 2002 (because calculated sulphur content of SSF produced was higher than the sulphur content of coal used to make the SSF). e Derived from benzene emission factor assuming a VOC/benzene ratio of 3.9:2.195, which is based on emission factors suggested by Corus, 2000 Oil and Natural Gas (1B2) The emissions reported in this sector pertain to the offshore platforms and onshore terminals on the UK Continental Shelf Area and represented by the Oil and Gas UK trade association (formerly UKOOA). Data Source: The EEMS Reporting System, (1995 onwards) Emission estimates for the offshore oil & gas industry are based on data provided by the UK regulatory agency (the Department of Energy & Climate Change), called the Environmental Emissions Monitoring System (EEMS). The EEMS system has been developed by DECC and the trade organisation, Oil and Gas UK (formerly UKOOA). This system provides a detailed inventory of point source emissions estimates, based on operator returns for the years 1995-2007. Additional data on CO2 emissions from some offshore combustion processes has become available via the National Allocation Plan and annual operator emission estimates for sites participating in the EU Emission Trading Scheme. In recent years these EU ETS data have been used by operators to update their EEMS emission estimates for combustion processes, ensuring consistency between EEMS and EU ETS, and by the Inventory Agency as a useful Quality Check on time-series consistency of carbon emission factors. Development of the EEMS Quality Assurance System The EEMS dataset continues to develop in quality; the quality system in place, developed by the regulatory body (DECC) in conjunction with the trade association (UK Oil & Gas), is now based on an online reporting system with controls over data entry, together with guidance notes provided to operators to provide estimation methodology options and emission factors for specific processes. The online reporting system was introduced for the 2006 data submission, and several glitches in the system were evident during the compilation of the 1990-2006 GHGI. Many of these issues have now been resolved by the DECC oil & gas team of regulators, although in the latest dataset from plant operators there remain some gaps in reported emissions for 2006 and 2007. This indicates that the EEMS reporting quality system requires further development to ensure that operators report a consistent and comprehensive series of emissions data, with time-series consistency a key factor. Where a site intermittently reports emissions from a specific process source, these gaps ought to be identified and rectified at source. The inventory agency has worked through many of the data inconsistencies in the EEMS dataset with the DECC team, to identify where gaps in data provision require provisional estimates to be used for the UK GHGI reporting system. Reference Sources for Emission Estimates, 1990-1995 For years prior to 1995 (i.e. pre-EEMS), emission totals are based on an internal Oil and Gas UK summary report produced in 1998. The 1990-1994 detailed estimates are based on (1) total emission estimates and limited activity data (for 1990-1994) from the 1998 UKOOA summary report, and (2) the detailed split of emissions from the 1997 EEMS dataset. The 1998 UKOOA report presents data from detailed industry studies in 1991 and 1995 to derive emission estimates for 1990 from available operator estimates. Emission estimates for 1991-1994 are then calculated using production-weighted interpolations. Only limited data are available from operators in 1990-1994, and emission totals are only presented in broadly aggregated sectors of: drilling (offshore), production (offshore), loading (offshore) and total emissions onshore. Estimates of the more detailed oil & gas processing source sectors for 1990-1994 are therefore based on applying the fraction of total emissions derived from the 1997 data from EEMS (as gaps and inconsistencies within the 1995 and 1996 datasets indicate that these early years of the EEMS dataset are somewhat unreliable). Other Data Sources: Onshore Terminal Emissions Emission estimates for onshore oil and gas terminals are also based on annual emissions data reported by process operators under the EEMS system, regulated by DECC. These onshore sites also report emissions data to the UK environmental regulatory agencies (the Environment Agency of England & Wales and the Scottish Environmental Protection Agency) under IPC/IPPC regulations. Emissions data for Scottish plant are available for 2002 and 2004 onwards, whilst in England & Wales the Pollution Inventory of the EA holds emissions data from industrial plant from around 1995 onwards. For some terminals, occasional data gaps are evident in the EEMS data, most notably for methane and NMVOC emissions from oil loading activities. In these instances, the emission estimates reported under IPC/IPPC are used to provide an indication of the level of emissions in that year, but the longer time-series of the EEMS data for Scottish sites has led the Inventory Agency to use the EEMS data as the primary data source for these terminals. UK GHGI Compilation: Method Development and Quality Control For the EEMS reporting cycle for 2006 data, a new online system of operator reporting was implemented by DECC. However, due to complications with this new system the operator emissions data provided to the Inventory Agency was incomplete for several sources including drilling and well testing (all activity data and emissions data), onshore loading (missing NMVOC emissions for several sites), onshore fugitive emission sources (missing methane data for some sites), and onshore own gas use data (CO2 emissions for some sites). In the 2007 dataset, many of these problems had been resolved, as the DECC Oil & Gas team of regulators had engaged with several operators to identify and resolve reporting gaps and inconsistencies. However, one or two non-reporting sites for some sources were still evident. To resolve these data gaps, the Inventory Agency agreed the following actions with DECC (Furneaux, 2008): Onshore loading: Two sites had omitted to report in 2007, and data were extrapolated from earlier years; Onshore Fugitive sources: Several sites had omitted to report the quite minor fugitive emissions data estimates in 2007, and all of these were estimated based on extrapolation of previous data and comparison against PI/SPRI data; Onshore Own Gas use: One site had omitted to report in 2007, and data were extrapolated from previous years. Some significant revisions to emissions data reporting have been made in the 1990-2007 data compilation, following discussion with the DECC Oil & Gas team, and the DECC Energy Statistics team. There are two reporting systems from upstream oil & gas processing in the UK; the EEMS system provides emissions data to the DECC Oil & Gas team, whilst the Petroleum Processing Reporting System (PPRS) is used to report data to the DECC Energy Statistics team as part of the wider system of regulation of oil & gas extraction and production permitting system. These data reported via the PPRS include data on gas flaring & venting volumes at offshore and onshore installations, and have previously been used as the activity data within the UK GHGI. The EEMS system meets an environmental emissions reporting requirement, whilst the PPRS meets other regulatory licensing reporting requirements. Whilst the two systems might be expected to reflect similar trends in activities, where reported activities coincide (such as gas flaring and venting), consultation with the DECC teams has indicated that the two systems are largely independent. Further to this, the development of the EEMS dataset has enabled greater access to reported activity data that have been used to calculate the emissions. These EEMS-derived activity data enable greater analysis of the oil & gas emissions and related emission factors. In the compilation of the 1990-2007 inventory data, where previously the EEMS emissions were reported alongside the PPRS activity data (e.g. in the case of gas flaring and venting), the EEMS-derived activity data are now used. In most cases, this has led to an improvement in data transparency and easier query of Implied Emission Factor trends. However, the EEMS activity data are only available back to 1997. Where necessary, therefore, the activity data back to 1990 have been extrapolated using the PPRS time-series to provide the indicative trend. Data Reconciliation with UK Energy Statistics Across Reporting Categories The data reported from the EEMS system must be reconciled with the UK Energy Statistics and integrated into the NAEI without double-counting emissions. The diesel oil consumption by offshore installations is not reported separately in the UK Energy Statistics but is included under coastal shipping. In order to avoid double counts, the Oil and Gas UK estimates have been corrected to remove diesel oil emissions. In the NAEI, offshore emissions are estimated in the following categories each with its own methodology: Offshore flaring Offshore Oil & Gas (well testing) Offshore Oil & Gas (venting) Offshore Oil & Gas Process Emissions (including fugitive emissions) Offshore Loading Onshore Loading Oil Terminal Storage Offshore own gas use (reported under 1A1c Other Energy Industries) Gas Separation Plant (Combustion) (reported under 1A1c Other Energy Industries) The mapping of these sources to IPCC categories is described in Section A3.2. Activity data are reported in the CRF Background Table 1B2, however in most cases these data are not used to calculate the emissions, but are provided for comparison with other inventories. Offshore Flaring This includes flaring from offshore platforms and onshore terminals. Flaring emission data for CO2, SO2, NOx, CO, NMVOC, and CH4 are taken from the EEMS dataset (DECC, 2008). Data from 1995-2007 are based on detailed operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1997 data splits between sources. N2O emissions are based on operator information from 1999-2007, and on emission factors and production throughput data for 1990-1998. The activity data and implied emission factors are given in Table A3.3.31. The implied emission factors for 1997-2007 are reported as kg pollutant per kg gas flared and are calculated from emissions and activity data reported annually by operators via the EEMS reporting system. The data for 1990-1996 are estimated based on reported emission totals and extrapolated activity data. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 31: Activity Data & Implied Emission Factors: Offshore Flaring Activity DataCO2CH4NOxCONMVOCSO2N2Oktonneskg/kgkg/kgkg/kgkg/kgkg/kgkg/kgkg/kg200716572.560.00950.00120.00670.00800.000110.00008200615392.540.00990.00130.00680.00720.000130.00008200517732.590.00930.00130.00670.00780.000150.00008200415562.600.00970.00130.00670.00680.000210.00008200315062.640.01020.00130.00680.00670.000160.00008200217362.640.00970.00160.00680.00700.000150.00008200118902.630.00990.00130.00660.00700.000220.00008200019282.500.01080.00120.00640.00630.000190.00008199918902.660.01070.00160.00690.00780.000280.00009199820922.690.01070.00140.00700.00900.000140.00008199720802.690.01070.00150.00730.00900.000130.00008199623082.450.01050.00140.00750.00970.000130.00008199522722.460.01030.00140.00750.00980.000140.00008199421642.180.01000.00120.00830.01170.000060.00007199320342.190.01070.00130.00850.01230.000060.00007199219052.190.01250.00130.00870.01290.000060.00007199117752.180.01330.00140.00890.01350.000060.00007199017962.180.01390.00140.00890.01290.000060.00007Flaring is reported under 1B2ciii Flaring Combined, since many of the platforms produce both oil and gas. An estimate of NMVOC emissions from refinery flares is reported in 1B2ci Venting and Flaring: Oil. This is based on estimates supplied by UKPIA (2008). Offshore Own Gas Use This refers to the use of unrefined natural gas on offshore platforms and onshore terminals as a fuel in heaters, boilers, turbines and reciprocating engines. Gas combustion emission data for CO2, SO2, NOx, CO, NMVOC, and CH4 are taken from the EEMS dataset (DECC, 2008). Data from 1995-2007 are based on detailed operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1995 data splits between sources. N2O emissions are based on operator information from 1999-2007, and on emission factors and production throughput data for 1990-1998. The activity data and implied emission factors are given in TableA3.3.32. The implied emission factors for 1990-2007 are reported as tonne pollutant per Mtherm gas used and are calculated from the emissions data reported within the EEMS dataset, and the activity data reported as Producers Own Use within the Digest of UK Energy Statistics. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 32: Activity Data & Implied Emission Factors: Offshore Own Gas Use Activity DataCO2CH4NOxCONMVOCSO2N2OMthkt/Mtht/Mtht/Mtht/Mtht/Mtht/Mtht/Mth200722286.372.5518.546.870.190.150.45200623935.652.3317.736.270.180.200.45200525316.152.9120.516.900.300.150.49200426536.213.0819.906.830.310.160.49200326226.402.8819.316.970.240.210.51200227086.503.0820.626.850.260.200.58200126776.392.8915.596.930.241.150.51200022377.263.1018.427.800.241.450.59199922057.273.4919.037.820.301.880.55199822357.153.4919.037.820.300.330.55199719898.033.4919.037.820.300.330.55199619068.033.4919.037.820.300.330.55199516808.033.4919.037.820.300.330.55199416478.033.4919.037.820.300.330.55199313888.033.4919.037.820.300.330.55199213148.033.4919.037.820.300.330.55199112358.033.4919.037.820.300.330.55199011888.033.4919.037.820.300.330.55 These emissions apply to the mixture of methane, ethane, propane and butane used. In the NAEI database they are reported in the categories: Offshore own gas use: natural gas; Gas separation plant: LPG; and Gas separation plant: OPG. Emissions are reported under 1A1cii Other Energy Industries. Well Testing This activity involves the combustion of crude oil and crude gas during well testing, and is an activity that is not recorded within the Digest UK Energy Statistics. Combustion emission data for CO2, SO2, NOx, CO, NMVOC, and CH4 are taken from the EEMS dataset (DECC, 2008). Activity data (tonnes fuel burnt) are also now available from the EEMS dataset for 1998 onwards, whilst the activity data for 1990-1997 has been estimated, based on the assumption that the Carbon emission factor remains constant back to 1990. This revised approach is more transparent for the assessment of implied emission factors for 1998 onwards, as the previous approach compared emissions against numbers of wells explored which is a poor parameter to use to represent gas and oil consumption during well testing. This new approach does create new estimated activity data for 1990-1997, but the emissions data are unchanged (as there is no new data on emissions during 1990-1997) and overall the method change is considered an improvement. This new approach has also helped to identify possible inconsistencies in emissions data within the earlier years of the time-series, most notably for emissions of SO2 during 1990-1997 and for N2O during 1990-1994. Further enquiries with DECC and Oil & Gas UK may enable further improvements to these emission trends in the next inventory cycle. Emissions data from 1995-2007 are based on operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1997 data splits between sources. N2O emissions are based on operator information from 1999-2007, and on emission factors and production throughput data for 1990-1998. The 2006 dataset has been completely revised since the previous inventory submission. The activity data and implied emission factors are given in Table A3.3.33. Well testing is reported under 1B2a Oil Production since many of the wells produce oil and gas. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 33: Activity Data and Implied Emission Factors: Well Testing Activity DataCO2SO2NOxCONMVOCCH4N2Oktonneskt/ktt/ktt/ktt/ktt/ktt/ktt/kt200725.7 2.8244.03.597.276.020.0130.075200629.2 2.8225.92.927.2719.20.0120.072200540.3 3.0034.82.4712.515.20.0130.081200443.3 2.9438.02.0710.612.00.0130.081200345.1 2.9637.22.1711.112.80.0130.081200248.3 3.0532.72.7313.617.30.0130.081200135.3 3.0731.42.9014.418.60.0130.081200044.7 3.0930.53.0114.919.50.0130.081199970.4 3.0134.42.5212.715.60.0130.0811998218.7 2.9434.42.5913.314.10.0130.0811997211.6 2.9434.82.5913.315.029.90.0811996210.3 2.9436.92.7414.115.831.60.0851995201.1 2.9434.82.5913.314.929.80.0811994554.2 2.9411.217.910.46.0914.20.0291993521.0 2.9411.919.110.66.3714.70.0291992487.9 2.9414.020.410.96.6815.20.0291991454.7 2.9414.922.067.77.0415.90.0291990459.9 2.9415.722.011.26.7315.90.029 Other Emissions from Offshore Platforms and Onshore Terminals These include emissions from offshore platforms and onshore terminals, including the following sources: Gas Venting (CO2 CH4, NMVOC estimates only); Fugitive emissions (CO2 CH4, NMVOC estimates only); Direct process emissions, such as acid gas stripping plant at terminals (CO2, NOx, SO2, CO, CH4, NMVOC); Storage vessel emissions from the storage of crude oil at terminals (CH4, NMVOC estimates only). Emissions data are taken from the EEMS dataset (DECC, 2008) and previous industry studies by Oil & Gas UK (1998). Data from 1995-2007 are based on detailed operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1997 data splits between sources. Note that there are no activity data for these activities available from DECC or UK Oil & Gas, and hence the method used in the compilation of the UK GHGI is merely to compile the sum of the operator emissions reported via the EEMS system, and report the emissions against an activity data of 1. Gaps in reported fugitive & storage tank emissions by certain operators and sites are evident in recent years, and where possible, data have been extrapolated from previous years to provide estimates to fill these gaps. There have also been some significant changes in activities at some sites that have led to notable emission reductions in recent years, including: Reductions in direct process emissions of SO2 have been achieved at the Elgin PUQ platform, due to a change to venting acid gases rather than flaring them. In 2007, large reductions in NOx emissions from the acid gas removal system have been achieved at the SAGE St Fergus terminal. These other emissions from platforms and terminals are reported in the following NAEI categories, all mapped to 1B2a Oil ii Production: offshore oil & gas (fugitive and process emissions), offshore venting and oil terminal storage. It is not possible to split oil and gas production emissions since oil and gas are frequently produced on the same platform. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 34: Aggregate Emission Factors used for Emissions from Platforms and Terminals PeriodUnitsCH4NMVOCGas Platforms Oil Platforms Oil/Gas Platforms1970-92 1970-92 1970-92kt/installation kt/installation kt/installation0.589 0.327 0.7630.0754 0.393 0.686Gas Terminals Oil Terminals1970-92 1970-92kt/installation kt/installation3.0 0.0760.425 0.315Oil Loading Emissions This sector includes emissions of CH4 and NMVOCs from tanker loading and unloading based on data from the EEMS dataset (DECC, 2008). Data from 1995-2007 are based on detailed operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1997 data splits between sources. In 2006 and 2007, the methane and NMVOC data from operators appear to be incomplete in the EEMS dataset, most notably from ship emissions at two BP terminals at Sullom Voe and Hound Point. Hence estimates have been made for emissions from these sources, extrapolating emission estimates from earlier years. These emission totals for methane and NMVOCs are therefore subject to quite considerable uncertainty, and the clarification of actual emissions from these sources is a priority for the next inventory cycle. This source is another example of where new activity data have now been made available to the Inventory Agency, following improvements to the EEMS reporting system. Activity data (tonnes oil loaded / unloaded) are also now available from the EEMS dataset for 1998 onwards, whilst the activity data for 1990-1997 has been estimated, based on the assumption that the methane emission factor remains constant back to 1990. This revised approach is more transparent for the assessment of implied emission factors for 1998 onwards, as the previous approach compared emissions against oil production data from a separate data source. This new approach does create new estimated activity data for 1990-1997, but the emissions data are unchanged (as there is no new data on emissions during 1990-1997) and overall the method change is considered an improvement. Emissions data from 1995-2007 are based on operator returns, whilst 1990-1994 data are calculated from extrapolation of total emissions data and the use of 1997 data splits between sources. The activity data and implied emission factors are given in TableA3.3.35. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 35: Activity Data and Implied Emission Factors: Crude Oil Loading, Onshore and Offshore ONSHORE LOADINGOFFSHORE LOADINGActivityCH4NMVOCActivityCH4NMVOCktt/ktt/ktktt/ktt/kt200760,291 0.0120.6719,948 0.1141.43200659,676 0.0110.6724,699 0.0721.25200566,447 0.0120.7021,721 0.0971.30200464,387 0.0120.6832,784 0.0841.12200374,824 0.0130.7936,547 0.0801.38200282,464 0.0120.8641,171 0.1151.64200186,663 0.0120.8542,277 0.1131.54200093,192 0.0120.8730,644 0.1181.671999102,395 0.0110.8335,484 0.0741.341998104,354 0.0130.9430,639 0.0431.441997104,776 0.0130.9424,013 0.0432.391996114,031 0.0130.9419,640 0.0432.401995125,628 0.0130.9417,163 0.0432.401994177,194 0.0130.9415,676 0.0432.761993176,810 0.0130.9415,642 0.0432.721992193,646 0.0130.9417,132 0.0432.441991193,224 0.0130.9417,094 0.0432.401990204,684 0.0130.9418,108 0.0432.19Leakage from the Gas Transmission System The NAEI category Gas Leakage covers emissions of CH4 and NMVOC from the UK gas transmission and distribution system. This is accounted for within the IPCC category 1B2b Natural Gas ii Transmission/Distribution. Data on gas leakage and the methane & NMVOC content of natural gas are provided by UK Transco and four companies (newly formed in 2005) that operate the low-pressure gas distribution networks. The leakage estimates are determined in three parts: Losses from High Pressure Mains (UK Transco); Losses from Low Pressure Distribution Network (UKD, Scotia Gas, Northern Gas Networks, Wales & West); and Other losses, from Above Ground Installations and other sources (UK Transco). Estimates are derived from specific leakage rates measured on the various types of gas mains and installations, together with data on the infrastructure of the UK supply system (such as length and type of pipelines and other units). Historic data for the leakage from the low-pressure distribution network and other losses (Above Ground Installations (AGIs) etc.) is based on studies from British Gas in the early 1990s (British Gas, 1993; Williams, 1993). Emission estimates for 1997 to 2007 are derived from an industry leakage model (data provided by the four network operator companies independently due to commercial confidentiality concerns), whilst emission estimates from 1990-96 are based on an older British Gas model that provided historical data for 1991-94 but projected estimates for 1995-96. The methane and NMVOC content of natural gas is shown in TableA3.3.36. These data were provided by contacts within British Gas Research for 1990-1996 and by UK Transco from 1997 to 2005 (Personal Communication: Dave Lander, 2008), and from the gas network operators from 2006 onwards (UKD, Scotia Gas, Northern Gas Networks, Wales & West). Data on NMVOC content for 2001-2003 has been estimated by interpolation due to a lack of data. Table A  STYLEREF 2 \s 3.3. SEQ Table_A \* ARABIC \s 2 36: Methane and NMVOC Composition of Natural Gas PeriodCH4 weight %NMVOC weight %1990-96184.38.91997-99277.114.72000277.614.72001277.114.832002277.315.032003277.415.232004277.415.32005477.915.3200678.415.0200778.214.8 British Gas (1994) UK Transco (2005) AEA Energy & Environment estimate (2005), based on data provided for other years National Grid UK (2006) Petrol Distribution The NAEI reports emissions from the storage, distribution and sale of petrol in the following categories each of which is further divided into emissions of leaded and unleaded petrol: Refineries (Road/Rail Loading). Emissions during loading of petrol on to road and rail tankers at refineries; Petrol Terminals (Storage). Emissions from storage tanks at petrol distribution terminals; Petrol Terminals (Tanker Loading). Emissions during loading of petrol on to road and rail tankers at petrol terminals; Petrol Stations (Petrol Delivery). Emissions during loading of petrol from road tankers into storage tanks at petrol stations; Petrol Stations (Storage Tanks). Emissions from storage tanks at petrol stations; Petrol Stations (Vehicle Refuelling). Emissions due to displacement of vapour during the refuelling of motor vehicle at petrol stations; and Petrol Stations (Spillages). Emissions due to spillages during refuelling of motor vehicles at petrol stations. Emissions also occur from storage tanks at refineries. This source is included together with emissions from the storage of crude oil and other volatile materials in the NAEI source category, refineries (tankage). The emission estimates from road and rail tanker loading at refineries are supplied by UKPIA (2008). The remaining estimates are based on methodologies published by the Institute of Petroleum (2000) or, in the case of petrol terminal storage, based on methods given by CONCAWE (1986). The calculations require information on petrol density, given in DECC (2008), and petrol Reid Vapour Pressure (RVP), data for which have been obtained from a series of surveys carried out by Associated Octel between 1970 and 1994. More recent, detailed RVP data are not available, but UKPIA have suggested values for 1999 onwards. Central England Temperature (CET) data (Met Office, 2008) are used for ambient UK temperatures. The methodology also includes assumptions regarding the level of vapour recovery in place at terminals and petrol stations. These assumptions draw upon annual account surveys carried out by the Petroleum Review (2000 onwards) that include questions on petrol station controls, and the timescales recommended in Secretary of States Guidance for petrol terminals (PG 1/13 (97)). The activity data are the sales of leaded and unleaded petrol from BERR (2008). Refineries and Petroleum Processes The IPCC category 1B2aiv Refining and Storage reports estimates of NMVOC emissions from oil refineries. In the NAEI these are split into: Refineries (drainage); Refineries (tankage); and Refineries (process). All are based on UKPIA (2008) estimates for 1994-2007. The UKPIA data refer to the following installations: Texaco, Milford Haven; Elf, Milford Haven; BP, Coryton; Shell, Shell Haven (closed during 1999); Conoco, South Killingholme; Lindsey, Killingholme; Shell, Stanlow; PIP, North Tees; Esso, Fawley; BP, Grangemouth; and Gulf, Milford Haven (closed during 1997). UKPIA also supply estimates for loading of petrol into road and rail tankers at refineries see Section A3.3.8.2.7 Prior to 1994, process emissions are estimated by extrapolation from the 1994 figure on the basis of refinery throughput, whereas emissions from tankage, flares and drainage systems are assumed to be constant. Also included under 1B2aiv Refining and Storage are NMVOC emissions from the NAEI category petroleum processes. This reports NMVOC emissions from specialist refineries (Llandarcy, Eastham, Dundee, & Harwich), onshore oil production facilities, and miscellaneous petroleum processes not covered elsewhere in the inventory (most significant of which are the Tetney Lock and Tranmere oil terminals). Emissions are taken from the Pollution Inventory (Environment Agency, 2008). No emissions data have been found for the Dundee refinery. Gasification Processes The NAEI also reports NMVOC emissions from on shore gas production facilities, refining and odourisation of natural gas, natural gas storage facilities, and processes involving reforming of natural gas and other feedstocks to produce carbon monoxide and hydrogen gases. Emissions are taken from the Pollution Inventory (Environment Agency, 2008). For the years prior to 1994, they are extrapolated based on gas throughput. Care is taken to avoid double counting with the offshore emissions. Stored Carbon As part of our review of the base year GHG inventory estimates, the UK reviewed the treatment of stored carbon in the UK GHG inventory and the fate of carbon from the non-energy use (NEU) of fuels and other fossil carbon products. This appraisal included a review of the National Inventory Reports (NIRs) of other countries. The US NIR contained a detailed methodology of the approach used in the US inventory to estimate emissions of stored carbon, and the US NIR presents storage factors for a range of products. Some of these factors have been used in the new UK method. The UK Inventory Agency has conducted a series of calculations to estimate the fate of carbon contained in those petroleum products shown in the NEU line of the UK commodity balance tables. The analysis indicates that most of the carbon is stored, although a significant quantity does appear to be emitted. Some of the emitted carbon has been included in previous versions of the GHG inventory, e.g. carbon from chemical waste incinerators; most has not. A summary of the estimates of emitted/stored carbon has been produced and these have been presented in a separate technical report. The study also provides subjective, qualitative commentary regarding the quality of the estimates. Following the review of stored carbon, the procedure adopted is to assume that emissions from the non-energy use of fuels are zero (i.e. the carbon is assumed to be sequestered as products), except for cases where emissions could be identified and included in the inventory: Catalytic crackers regeneration of catalysts; Ammonia production; Aluminium production consumption of anodes; Combustion of waste lubricants and waste solvents; Burning of lubricants during use in engines; Use of waste products from chemical production as fuels; Emissions of carbon due to use and/or disposal of chemical products; Incineration of fossil carbon in products disposed of as waste. Methodology for some of these sources has been described in detail elsewhere and so is not repeated here. Carbon deposits build up with time on catalysts used in refinery processes such as catalytic cracking. These deposits need to be burnt off to ensure continued effectiveness of the catalyst and emissions from this process are treated as use of a fuel (since heat from the process is used) and reported under IA1a. Details are given in Chapter 3 of the report. Natural gas is used as a feedstock in the manufacture of ammonia and emissions from this process are reported under 2B1. Coal tar pitch and petroleum coke are used in the manufacture of carbon anodes used by the aluminium industry and CO2 is emitted during use of the anodes. Details of methodology for both sources are given in Chapter 4. AEA estimates of the quantities of lubricants burnt are based on data from Recycling Advisory Unit, 1999; BLF/UKPIA/CORA, 1994; Oakdene Hollins Ltd, 2001 &ERM, 2008.. Separate estimates are produced for the following sources: Power stations; Cement kilns; and Other industry. The figures for power station and other industrial use of waste lubricants were revised for this version of the GHGI. This was partly due to new information being generally available, and partly due to the recognisation that the Waste Incineration Directive (WID) was likely to have had a profound impact on the market for waste oil, used as a fuel. After WID was introduced in 2006, it is assumed that no waste oil is burnt either in power stations or by roadstone coating plant. One repercussion of these changes is that it is assumed that, since 2006, a large quantity (> 200 ktonnes/annum) of waste oil is recovered but not used. In reality new markets for waste oil as a fuel may have developed or the waste oil may have been sent for incineration (in both cases this would have resulted in CO2 emissions which are not reflected in the GHGI), or the excess oil might have been stockpiled or exported. Further investigation is needed to ascertain the fate of this oil. Emissions from use of waste oils as fuels are reported under 1A1a and 1A2f. In addition, an estimate is made of lubricants burnt in vehicle engines. Carbon emissions from these sources are calculated using a carbon factor derived from analysis of eight samples of waste oil (Passant, 2004). In 2005, the combustion of lubricating oils within engines was reviewed. Analysis by UK experts in transport emissions and oil combustion have lead to a revision to the assumptions regarding re-use or combustion of lubricating oils from vehicle and industrial machinery. The fate of the unrecovered oil has now been allocated across several IPCC source sectors including road, rail, marine, off-road and air transport. Emissions from these sources are reported under 1A3b, 1A3d & 1A4c. Some of the unrecovered oil is now allocated to non-oxidising fates such as coating on products, leaks and disposal to landfill. Emissions can occur from products from the chemical industry. Sources of emissions include burning of waste products and final products (e.g. flaring and use of wastes as fuels, or burning of candles, firelighters and other products etc.) or degradation of products after disposal resulting in CO2 emissions (including breakdown of consumer products such as detergents etc.). After considering the magnitude of the sources in relation to the national totals, the uncertainty associated with emissions, and the likely forthcoming IPCC reporting requirements in the 2006 Guidelines, emissions of carbon from the following sources were included in the 2004 GHG inventory (2006NIR) and subsequent NIRs: Petroleum waxes; Carbon emitted during energy recovery - chemical industry; Carbon in products - soaps, shampoos, detergents etc; and Carbon in products pesticides. A full time series of emissions is included in the inventory, and details of the methodology for these sectors are given in Passant, Watterson & Jackson, 2007. Emissions are reported under 2B5. Fossil carbon destroyed in MSW incinerators and clinical waste incinerators is included in the GHG inventory, as is carbon emitted by chemical waste incinerators. These emissions are reported under 1A1a & 6C, and methodology is detailed in Chapters 3 and 8 of the report. The analysis also included an assessment of the fate of carbon from the use of coal tars and benzoles. Benzoles and coal tars are shown as an energy use in the BERR DUKES and up until the 2002 version of the GHG inventory, the carbon was included in the coke ovens carbon balance as an emission of carbon from the coke ovens. When the carbon balance methodology was improved for the 2003 GHG inventory, the UK inventory treated the carbon in these benzoles and coal tars as a non-emissive output from the coke ovens. However, we were not sure what the ultimate fate of the carbon was but were unable to research this in time for the 2003 GHG inventory. It was therefore treated as an emission from the waste disposal sector - thus ensuring that total UK carbon emissions were not altered until we had sufficient new information to judge what the fate of the carbon was. New information from Corus UK Ltd (the sole UK operator of coke ovens) indicates that the benzoles & coal tars are recovered and sold on for other industrial uses, the emissions from which are already covered elsewhere within the inventory. Hence the carbon content from these coke oven by-products is now considered as stored and the carbon emissions included in previous inventories has been removed from the new version of the GHG inventory. The analysis estimates emissions from: The energy uses of coal tars and benzoles; and NEU of petroleum products. Since emissions of carbon are estimated, carbon which is not emitted (i.e. stored) can be calculated from the BERR DUKES consumption data by difference. Industrial Processes (crf sector 2) Mineral Processes (2A) Cement Production (2A1) Emission factors for the production of cement, as described in Chapter 4, are as follows: Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 1: Emission Factors for Cement Kilns based on Fuel Consumption, 2007 FuelC aCH4N2OUnitsCoal647.1j0.3e0.109hKt / Mt fuelFuel Oil879b0.0866f0.0262fKt / Mt fuelGas Oil870b0.0910f0.0273fKt / Mt fuelNatural Gas1.48b0.000528fNEKt / MthermPetroleum Coke813.0j0.1071g0.143hKt / Mt fuelScrap Tyres455.11j0.96fNEKt / Mt fuelWaste Oils825.2j0.0910iNEKt / Mt fuelWaste Solvent439.8 jNENEKt / Mt fuelOther Waste204.1jNENEKt / Mt fuel a Emission factor as mass carbon per unit fuel consumed b Derived using the methods given in Baggott et al (2004) c Emission factor derived from emissions reported in the PI d Passant, N.R., 2004 e Brain, SA et al. British Coal Corp, CRE (1994) f IPCC 1997c g IPCC (2006) h Fynes et al (1994) i As for gas oil j Data supplied by British Cement Association/Lafarge Cement, 2007 Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 2: Emission Factors for Cement Kilns based on Clinker Production, 1990-2007 YearCONOxNMVOCSO2Units1990-942.965.700.1463.19kt/Mt Clinker19952.865.200.1463.38kt/Mt Clinker19964.393.630.1462.24kt/Mt Clinker19971.903.910.1462.56kt/Mt Clinker19982.274.110.1462.34kt/Mt Clinker19992.583.610.1252.27kt/Mt Clinker20002.493.420.1231.88kt/Mt Clinker20012.323.070.1571.94kt/Mt Clinker20022.402.890.1172.06kt/Mt Clinker2003NRNRNRNRkt/Mt Clinker20042.573.200.0641.74kt/Mt Clinker20052.863.070.0641.58kt/Mt Clinker20062.842.670.0651.24kt/Mt Clinker20072.872.540.0861.00kt/Mt Clinker NR 2003 emission factor data are not reported due to issues of commercial confidentiality raised by the BCA. Lime Production (2A2) Emission factors for the production of lime, as discussed in Chapter 4, Section 4.3: Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 3: Emission Factors for Lime Kilns based on Fuel Consumption, 2007 FuelC aCH4N2OUnitsCoal645.4b0.011c0.214eKt / Mt fuelNatural Gas1.48b0.00053f1.055E-05fKt / MthermCoke799.5d0.011c0.230eKt / Mt fuel a Emission factor as mass carbon per unit fuel consumed b Derived using the method given in Baggott et al (2004) c Brain, SA et al. British Coal Corp, CRE (1994) d AEA estimate based on carbon balance e Fynes et al (1994) f IPCC(1997) IPCC Revised 1996 Guidelines Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 4 Emission Factors for Lime Kilns, 2007: Indirect GHGs FuelCONOxNMVOCUnitsCoal15.760.440.05Kt / Mt fuelNatural Gas0.05660.03110.00023Kt / MthermCoke9.920.3240.05Kt / Mt fuel Chemical Industry (2B) Nitric Acid Production (2B2) Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 5 Summary of Nitric Acid Production in the UK, 1990-2007 YearNo of sitesProduction (Mt 100% Nitric Acid)Aggregate EF (kt N2O / Mt Acid)Aggregate EF (kt NOX / Mt Acid)199082.415.233.36199462.493.891.93199562.403.820.81199662.443.830.74199762.353.780.90199862.613.990.73199962.446.290.91200062.036.940.99200151.656.620.66200241.644.200.39200341.714.380.43200441.715.000.44200541.713.800.37200641.473.870.42200741.613.540.38 Adipic Acid Production (2B3) There is only one company manufacturing adipic acid in the UK. Production data are not provided in the NIR because of commercial confidentiality concerns. Emissions have been estimated based on information from the process operator (Invista, 2008). These emission estimates are based on the use of plant-specific emission factors for unabated flue gases, which were determined through a series of measurements on the plant, combined with plant production data and data on the proportion of flue gases that are unabated. In 1998 an N2O abatement system was fitted to the plant. The abatement system is a thermal oxidation unit and is reported by the operators to be 99.99% efficient at N2O destruction. The abatement unit is not available 100% of the time, and typically achieves 90-95% availability during AA production. The abatement plant availability has a very significant impact upon the annual emissions of N2O, and leads to somewhat variable trends in IEFs over the time-series. A small nitric acid (NA) plant is associated with the adipic acid plant. This NA plant also emits nitrous oxide but has no abatement fitted. Operator emission estimates from the NA plant are based on emission factors; there is no online measurement of N2O in the stack from the NA plant. From 1994 onwards this emission is reported as nitric acid production but prior to 1994 it is included under adipic acid production. This will cause a variation in reported effective emission factor for these years. This allocation reflects the availability of data. The level of uncertainty associated with reported emissions of N2O is not known, but the data are considered to be reliable as they are subject to QA/QC checks by the operator, by the Environment Agency (before being reported in the Pollution Inventory) and by the regulators of the UK Emission Trading Scheme (DEFRA NCCP). Metal Production (2C) Iron and Steel (2C1) The following emissions are reported under 2C1 Iron and Steel Production: Blast furnaces: process emissions of CO, NOX, and SO2; Flaring of blast furnace gas/basic oxygen furnace gas; Electric arc furnace emissions; Basic oxygen furnaces: process emissions of CO and NOX.; Rolling mill process emissions of VOC; and Slag processing: process emissions of SO2. Emissions arising from the combustion of blast furnace gas and other fuels used for heating the blast furnace are reported under 1A2a Iron and Steel. Emissions of CO, NOX, and SO2 from integrated steelworks, and the flaring of blast furnace gas and basic oxygen furnace gas are reported under 2C1 Iron & Steel Production. CO2 emissions from limestone and dolomite use in iron and steel production are reported under 2A3 Limestone and Dolomite use. Carbon Dioxide Emissions Carbon emissions from flaring of blast furnace gas (BFG) and basic oxygen furnace gas (BOFG) are calculated using emission factors which are calculated as part of the carbon balance used to estimate emissions from CRF category 1A2a. The figure for 2007 was 75.4 ktonnes C/PJ. Emissions from electric arc furnaces are 2.2 kt C/Mt steel in 1990, falling to 2 kt C/Mt steel in 2000 and constant thereafter (Briggs, 2005). Other Pollutants Emissions from blast furnaces of other pollutants are partly based on the methodology described in IPCC (1997) for blast furnace charging and pig iron tapping and partly on emissions data reported by the process operators. The emission factors are expressed in terms of the emission per Mt of pig iron produced and are given in Table A3.4.6. Data on iron production are reported in ISSB (2006). Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 6: Emission Factors for Blast Furnaces (BF), Electric Arc Furnaces (EAF) and Basic Oxygen Furnaces (BOF), 2007 C aCH4N2ONOx SO2NMVOCCOUnitsBlast furnacesIENENENE0.1179b0.12c2.25ckt/Mt pig ironElectric arc furnaces2d0.01e0.005e0.1e0.154b0.09e0.71bkt/Mt SteelBasic oxygen furnacesIENENE0.012fIENE7.33bkt/Mt SteelLosses of BFG/BOFG7.96gNENENENENENEkt/Mtherm gasSlag processingNENENENE7.3E-6bNENEkt/Mt Pig iron a Emission factor as kt carbon/unit activity b Emission factor for 2006 based on data from Corus (2007) and data for non-Corus plant from EA (2007) c IPCC (1997) d Briggs (2005) e EMEP/CORINAIR(1999) f EIPPCB(2000), Corus (2001, 2000) g AEA estimate based on carbon balance NE Not estimated IE Emission included elsewhere. Emissions from electric arc furnaces are calculated mainly using default emission factors taken from EMEP/CORINAIR (1999). The CO2 emission arises from the consumption of a graphite anode and the emission factor has been suggested by Briggs (2005). Emissions of CO from basic oxygen furnaces are based on data supplied by Corus (2007) while the NOx emission is based on an EIPPCB default. Emissions of NMVOC are estimated from the hot rolling and cold rolling of steel using emission factors of 1 g/tonne product and 25g/tonne product respectively (EMEP/CORINAIR, 1996). Activity data were taken from ISSB (2007). There is insufficient activity or emission factor data to make an estimate for emissions from ferroalloys. Emissions of CO2 will be included in 1A2a, since the fuels used as reducing agents are included in the energy statistics. Aluminium Production (2C3) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Emission factors for aluminium production, as discussed in Chapter 4, Section 4.16, are shown in Table A3.4.7. Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 7: Emission Factors for Aluminium Production, 2007 C aSO2 bNOx bCO bUnitsPrebake42013.40.75496.6Kt / Mt Al Anode BakingIE1.440.423.89Kt / Mt anode a Emission factor as kt carbon per unit activity, Walker, 1997. b Environment Agency Pollution Inventory (2008) and SEPA (2008) IE Emission included elsewhere. SF6 used in Aluminium and Magnesium Foundries (2C4) The method used to estimate emissions of SF6 from this source is described in AEA(2008). Food and Drink (2D2) NMVOC emission factors for food and drink, as discussed in Chapter 4, Section 4.20. Table A  STYLEREF 2 \s 3.4. SEQ Table_A \* ARABIC \s 2 8: NMVOC Emission Factors for Food and Drink Processing, 2007 Food/DrinkProcessEmission FactorUnitsBeerBarley Malting Wort Boiling Fermentation0.6c 0.0048c 0.02cg/L beerCiderFermentation0.02cg/L ciderWineFermentation0.2ckg/m3SpiritsFermentation Distillation Casking Spent grain drying Barley Malting Maturation1.58d 0.79g 0.40h 1.31i 4.8c 15.78dg/ L alcohol g/ L alcohol g/ L whiskey kg/ t grain kg/ t grain g/ L alcoholBread Baking1akg/tonneMeat, Fish & Poultry0.3fkg/tonneSugar0.020bkg/tonneMargarine and solid cooking fat10fkg/tonneCakes, biscuits, breakfast cereal, animal feed1fkg/tonneMalt production (exports) 4.8ckg/ t grainCoffee Roasting0.55fkg/tonne a Federation of Bakers (2000) b Environment Agency (2007) c Gibson et al (1995) d Passant et al (1993) e Assumes 0.1% loss of alcohol based on advice from distiller f EMEP/CORINAIR, 2006 g Unpublished figure provided by industry h Based on loss rate allowed by HMCE during casking operations i US EPA, 2007 Production of Halocarbons and SF6 (2E) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Consumption of Halocarbons and SF6 (2F) Refrigeration and Air Conditioning Equipment (2F1) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Foam Blowing (2F2) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Fire Extinguishers (2F3) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Aerosols/ Metered Dose Inhalers (2F4) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Solvents (2F5) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Semiconductor Manufacture (2F6) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Electrical Equipment (2F7) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). One Component Foams (2F8A) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). Semiconductors, Electrical and Production of Trainers (2F8B) Details of the method used to estimate emissions of Fgases from this source are given in AEA(2008). SOLVENT AND OTHER PRODUCT USE (CRF SECTOR 3) There is currently no additional information for this sector in this Annex. AGRICULTURE (CRF SECTOR 4) Enteric Fermentation (4A) Methane is produced in herbivores as a by-product of enteric fermentation, a digestive process by which carbohydrates are broken down by microorganisms. Emissions are calculated from animal population data (Table A3.6.1) collected in the June Agricultural Census and published in Defra (2008a) and the appropriate emission factors. Data for earlier years are often revised so information was taken from the Defra agricultural statistics database. Table A3.6.2 shows the emission factors used. Apart from cattle, lambs and deer, the methane emission factors are IPCC Tier 1 defaults (IPCC, 1997) and do not change from year to year. The dairy cattle emission factors are estimated following the IPCC Tier 2 procedure (IPCC, 1997) and vary from year to year. For dairy cattle, the calculations are based on the population of the dairy breeding herd rather than dairy cattle in milk. The former definition includes cows in calf but not in milk. The emission factors for beef and other cattle were also calculated using the IPCC Tier 2 procedure (Table A3.6.4), but do not vary from year to year. The enteric emission factors for beef cattle were almost identical to the IPCC Tier 1 default so the default was used in the estimates. The base data and emission factors for cattle for 1990-2007 are given in Table A3.6.3 and Table A3.6.4. The emission factor for lambs is assumed to be 40% of that for adult sheep (Sneath et al. 1997). In using the animal population data, it is assumed that the reported numbers of animals are alive for that whole year. The exception is the treatment of sheep where it is normal practice to slaughter lambs and other non-breeding sheep after 6 to 9 months. Hence it is assumed that breeding sheep are alive the whole year but that lambs and other non-breeding sheep are only alive 6 months of a given year (based on Smith and Frost, 2000). The sheep emission factors in Table A3.6.2 are reported on the basis that the animals are alive the whole year. The main parameters involved in the calculation of the emissions factors for beef are shown in Table A3.6.5. Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 1 Livestock Population Data for 2007 by Animal Type Animal TypeNumberCattle:Dairy Breeding Herd1,953,980Beef Herda1,698,196Beef and others >1 year oldb5,492,919Others < 1 year old2,735,801Pigs:All breeding pigs537,138Other pigs > 50 kg1,836,736Other pigs 20-50 kg1,207,779Pigs <20 kg1,252,721Sheep:Breeding sheep16,063,634Other sheep1,026,744Lambs < 1 year16,855,428Goats95,478Horses383,748Deer30,933Poultry (000 head):Broilers108,753,182Breeders12,502,480Layers27,320,752Growing Pullets8,936,348Ducks, geese and guinea fowl2,510,166Turkeys3,848,330 aBeef herd refers to mature beef cows bBeef and others >1 year old include dairy heifers, beef heifers, others>2 and others 1-2 years old. Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 2 Methane Emission Factors for Livestock Emissions Animal TypeEnteric methanea kg CH4/head/yearMethane from manuresa kg CH4/head/yearDairy Breeding Herd105.0b25.8bBeef Herd482.74Other Cattle >1 year, Dairy Heifers48 6Other Cattle <1 year32.8 2.96Pigs1.5 7.06fBreeding Sheep8 0.19Other Sheep8e 0.19eLambs < 1 year3.2ce 0.076ceGoats5 0.12Horses18 1.4Deer: Stags & Hinds10.4c 0.26cDeer: Calves5.2c0.13cPoultrydNE0.078 a IPCC (1997) b Emission factor for year 2007 c Sneath et al. (1997) d Chickens, turkeys, geese, ducks and guinea fowl e Factor quoted assumes animal lives for a year; emission calculation assumes animal lives for 6 months f Factor changed according to 2000 GPG Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 3 Dairy Cattle Methane Emission Factorsa Average Weight of cow (kg) bAverage Rate of Milk Production (litre/d)Average Fat Content (%)Enteric Emission Factor (kg CH4/head/y)Manure Emission Factor (kg CH4/head/y)199055014.34.0188.121.6199154914.24.0488.421.7199256414.54.0690.122.1199356414.74.0790.822.3199455914.74.0590.922.3199555915.04.0592.322.7199656315.14.0893.222.8199756615.94.0796.023.6199855816.14.0796.823.8199955516.44.0397.824.0200056316.64.0398.724.2200157516.74.0199.424.4200257917.93.97102.725.2200357618.33.96103.825.5200457918.14.00101.824.9200557718.84.02103.525.4200657718.54.04102.825.2200757719.14.06105.025.8 a In 2003, 46% of animals graze on good quality pasture, rest confined Gestation period 281 days Digestible energy 74% (Bruce Cottrill, ADAS, pers. comm.) Methane conversion rate 6% Ash content of manure 8% Methane producing capacity of manure 0.24 m3/kg VS b Weights according to Steve Walton, Defra, pers. comm., from 1990 to 2004, Helen Mason, 2005, 2006, 2007 was the average of the weight of the previous 5 years Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 4 Parameters used in the calculation of the Methane Emission Factorsa for Beef and Other Cattle Beef herdbOthers>1cOthers<1Average Weight of Animal (kg)500400-500180Time Spent Grazing50%43-50%d46%GE (MJ/d)123.3123.383.4eDaily weight gain (kg day-1)00.30f0.60Enteric Emission Factor (kg CH4/head/y)48.5g4832.8Manure Emission Factor (kg CH4/head/y)2.7462.96 a Digestible Energy 65%, Ash content of manure 8%, Methane producing capacity of manure 0.17 m3/kg VS b Beef herd refers to mature cows c Includes dairy heifers, beef heifers, others>2, others 1-2 d Time spent grazing is 43% and 50% for dairy and beef cattle respectively e Calculated following IPCC guidelines f Only for animals less than 2 years old g IPCC (1997) default (48 kg/head/y) used since calculated factor is very close to default and the difference under the Tier 2 method will not affect the accuracy of the emission factor at the required level of precision Table A  STYLEREF 2 \s 3.6.5 Parameters in calculation of Beef herd Emission Factorsa FactorEquationaAverage Weight of Animal (kg)500NEm (Maintenance energy), MJ/d135.42NEfeed (Energy for obtaining food), MJ/db23.01NEg (Energy required for growth), MJ/d30NE (Lactation energy), MJ/d40NEpregnancy (Daily energy for pregnancy), MJ/d62.89GE (Gross energy intake), MJ/d13123.3EF enteric, kg CH4/head/y48.5cEF manure, kg CH4/head/y2.74 aFrom IPCC Revised guidelines 1996 bBased on 17% of NEm, grazing factor of 0.085 introduced to account for proportion of time spent grazing/housed cMethane conversion rate is 6% Manure Management (4B) Methane emissions from animal manures Methane is produced from the decomposition of manure under anaerobic conditions. When manure is stored or treated as a liquid in a lagoon, pond or tank it tends to decompose anaerobically and produce a significant quantity of methane. When manure is handled as a solid or when it is deposited on pastures, it tends to decompose aerobically and little or no methane is produced. Hence the system of manure management used affects emission rates. Emissions of methane from animal manures are calculated from animal population data (Defra, 2008a) in the same way as the enteric emissions. The emission factors are listed in Table A3.6.2. Apart from cattle, lambs and deer, these are all IPCC Tier 1 defaults (IPCC, 1997) and do not change from year to year. The emission factors for lambs are assumed to be 40% of that for adult sheep. Emission factors for dairy cattle were calculated from the IPCC Tier 2 procedure using data shown in Table A3.6.3 and Table A3.6.6 (Defra, 2002). There was a revision (in 2002) of the allocation of manure to the different management systems based on new data. This is detailed in Section 6.3.2.2. For dairy cattle, the calculations are based on the population of the dairy breeding herd rather than dairy cattle in milk used in earlier inventories. The former definition includes cows in calf but not in milk. The waste factors used for beef and other cattle are now calculated from the IPCC Tier 2 procedure but do not vary from year to year. Emission factors and base data for beef and other cattle are given in Table A3.6.4. Table A  STYLEREF 2 \s 3.6.6 Cattle Manure Management Systems in the UK Manure Handling SystemMethane Conversion Factor %aFraction of manure handled using manure system %Fraction of manure handled using manure system %DairyBeef and OtherPasture Range 1 45.5 50.5Liquid System3930.66Solid Storage19.820.7Daily Spread0.114.123 a IPCC (2000) Nitrous Oxide emissions from Animal Waste Management Systems Animals are assumed not to give rise to nitrous oxide emissions directly, but emissions from their manures during storage are calculated for a number of animal waste management systems (AWMS) defined by IPCC. Emissions from the following AWMS are reported under the Manure Management IPCC category: Flushing anaerobic lagoons. These are assumed not to be in use in the UK. Liquid systems Solid storage and dry lot (including farm-yard manure) Other systems (including poultry litter, stables) According to IPCC (1997) guidelines, the following AWMS are reported in the Agricultural Soils category: All applied animal manures and slurries Pasture range and paddock Emissions from the combustion of poultry litter for electricity generation are reported under power stations. The IPCC (1997) method for calculating emissions of N2O from animal waste management systems can be expressed as: N2O(AWMS) = 44/28 . ( N(T) . Nex(T) . AWMS(W) . EF(AWMS) where N2O(AWMS) = N2O emissions from animal waste management systems (kg N2O/yr) N(T) = Number of animals of type T Nex(T) = N excretion of animals of type T (kg N/animal/yr) AWMS(W) = Fraction of Nex that is managed in one of the different waste management systems of type W EF(AWMS) = N2O emission factor for an AWMS (kg N2O-N/kg of Nex in AWMS) The summation takes place over all animal types and the AWMS of interest. Animal population data are taken from Agricultural Statistics (Defra, 2008a). Table A3.6.7 shows emission factors for nitrogen excretion per head for domestic livestock in the UK (Nex) from Ken Smith and Bruce Cottrill (ADAS). Table A  STYLEREF 2 \s 3.6.7 Nitrogen Excretion Factors, kg N hd-1 year-1 for livestock in the UKa (1990-2000)b Animal Type199019911992199319941995199619971998199920002001200220032004200520062007Dairy Cows9797989899100101104104106106110112113114115.1116.2117.3Dairy heifers in calf676767676767676767676767676767676767Beef cows and heifers797979797979797979797979797979797979Other Cattle > 2 year565656565656565656565656565656565656Other Cattle 1-2 year565656565656565656565656565656565656Other Cattle <1 year383838383838383838383838383838383838Pigs < 20kg4.64.64.54.54.44.44.34.34.34.24.24.14.14.043.93.83.7Other Pigs 20-50 kg11.711.611.511.411.311.211.111.010.910.710.610.510.410.310.210.09.89.6Fattening & Other Pigs > 50 kg18.2618.0917.9417.7717.6417.5217.4417.2217.0316.8816.7316.5916.4616.3616.1615.8615.5015.16Breeding Pigs > 50 kg23.0622.8522.6322.3622.2021.9921.721.4821.3421.1220.9420.8720.5520.3519.5719.7219.3318.55Breeding Sheep10.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.2Other Sheep <1 year10.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.210.2Lambs0.650.650.650.650.650.650.650.650.650.650.650.650.650.650.650.650.650.65Goats20.620.620.620.620.620.620.620.620.620.620.620.620.620.620.620.620.620.6Broilers0.640.630.620.610.600.590.580.570.560.550.550.540.530.520.510.490.470.46Broiler Breeders1.161.161.151.151.141.131.131.121.121.111.101.101.091.091.081.071.061.05Layers0.860.850.850.840.830.820.820.810.800.800.790.790.780.780.770.760.760.74Ducks,1.301.331.351.371.391.411.431.451.471.491.521.541.561.581.601.621.641.66Turkeys1.51.521.541.551.571.591.611.621.641.661.681.701.711.731.751.761.771.79Growing Pullets0.420.410.410.400.390.390.380.380.370.370.360.360.350.350.340.340.340.34Horses505050505050505050505050505050505050Deer: Stags, hinds and calves131313131313131313131313131313131313 a Ken Smith, Bruce Cottrill, ADAS b Nex factors do not exclude 20% N volatilising as NOx and NH3 The UK methodology assumes that 20% of the total N emitted by livestock volatilises as NOx and NH3 and therefore does not contribute to N2O emissions from AWMS. This is because in the absence of a more detailed split of NH3 losses at the different stages of the manure handling process it has been assumed that NH3 loss occurs prior to major N2O losses. Thus, the Nex factors used in the AWMS estimates exclude the fraction of N volatilising and are 20% less than if they were reported on the same basis as the total Nex factors reported in the IPCC Guidelines. Values of total N excreted shown in the Common Reporting Format are not corrected in this way and are estimates of total N excreted from livestock. The conversion of excreted N into N2O emissions is determined by the type of manure management system used. The distribution of waste management systems for each animal type (AWMS(T)) is given in Table A3.6.8. The distributions used were revised for cattle and poultry in the 2000 Inventory. The change related to the way that data on no significant storage capacity of farmyard manure (FYM) were allocated. This could have a large effect on emissions because it amounted to around 50% of manure and the Daily spread (DS) category has an emission factor of zero, compared to 0.02 for the Solid storage and dry lot (SSD) category. However, we are advised (Smith, 2002) that: In terms of slurry, it seems likely that where a proportion of the estimated slurry production is attributed with nil or little storage (<1 month capacity), as above, it can be assumed that such units will rely on a significant amount of daily weekly spreading activity, according to land availability and trafficability, throughout. With FYM and poultry manure, however, significant storage capacity exists within the house and so, no storage generally implies that manure is cleared from the house/straw littered yard and spread direct on land. Storage capacity within the house or yard might comprise between 7 weeks 12 months (poultry) or several months (cattle) and is unlikely to require daily spreading activity. Therefore, assigning this stored in house manure to daily spread is acceptable only if emissions from the housing phase are thought to be very small. Calculations were performed with the N2O Inventory of Farmed Livestock to compare housing and storage phases (Sneath et al. 1997). For pigs and poultry, the emission factor for housing is the same as or greater than that of storage. It would therefore lead to significant underestimation to use the daily spread emission factor. A proportion of the pig waste (as FYM) is therefore allocated to SSD. Poultry waste is allocated to other except for that dropped outside by free-range poultry (PRP) and that exported for incineration in power stations (fuel). For dairy and non-dairy cattle, the emission factor for the housing phase is around 10% of the storage phase, so the non-stored FYM has been split between SSD and DS to account for this. Table A  STYLEREF 2 \s 3.6.8 Distribution of Animal Waste Management Systems used for Different Animal typesc Animal TypeLiquid SystemDaily SpreadSolid Storage and Dry LotaPasture Range and PaddockOtherbFuelDairy Cows30.614.19.845.5NANAOther Cattle >1 year6.023.020.450.5NANAOther Cattle <1 year22.922.354.8NANAFattening & Other Pigs > 20 kg,29.25.864.01.0NANABreeding sows35.57.12829.3NANAPigs <20 kg38.37.746.08.0NANASheepNANA2.098.0NANAGoatsNANANA96.04.0NABroilers & Table Fowl (2003)NANANA1.063.036.0BreedersNANANA1.099.0NALayerseNANANA10.090.0NAPulletseNANANA10.090.0NADucks, Geese & Guinea FowleNANANA50.050.0NATurkeyseNANANA8.092.0NAHorsesNANANA96.04.0NADeer: StagsdNANANA100NANADeer: Hinds & CalvesdNANANA75.025.0NA a Farmyard manure b Poultry litter, Stables from NH3 inventory (T. Misselbrook) c ADAS (1995a), Smith (2002) d Sneath et al. (1997) e Tucker and Canning (1997) Table A3.6.9 gives the N2O emission factor for each animal waste management system (EF(AWMS)). These are expressed as the emission of N2O-N per mass of excreted N processed by the waste management system. Emissions from grazing animals (pasture range and paddock) and daily spread are calculated in the same way as the other AWMS. However, emissions from land spreading of manure that has previously been stored in a) liquid systems, b) solid storage and dry lot and c) other systems, are treated differently. These are discussed in Section A3.6.3. Table A  STYLEREF 2 \s 3.6.9 Nitrous Oxide Emission Factors for Animal Waste Handling Systemsa Waste Handling SystemEmission Factor kg N2O-N per kg N excretedLiquid System0.001Daily Spreadb0Solid Storage and Dry Lot0.02Pasture, Range and Paddockb0.02Other (all poultry except layers)0.02cOther (layers)0.005 a IPCC (1997) b Reported under Agricultural Soils c 2000 GPG Agricultural Soils (4D) Source category description Direct emissions of nitrous oxide from agricultural soils are estimated using the IPCC recommended methodology (IPCC, 1997) but incorporating some UK specific parameters. The IPCC method involves estimating contributions from: The use of inorganic fertilizer Biological fixation of nitrogen by crops Ploughing in crop residues Cultivation of Histosols (organic soils) Spreading animal manures on land Manures dropped by animals grazing in the field In addition to these, the following indirect emission sources are estimated: Emission of N2O from atmospheric deposition of agricultural NOx and NH3 Emission of N2O from leaching of agricultural nitrate and runoff Descriptions of the methods used are described in Section6.5.2. Inorganic Fertiliser Emissions from the application of inorganic fertilizer are calculated using the IPCC (1997) methodology and IPCC default emission factors. They are given by: N2O(SN) = 44/28 . N(FERT) . (1-Frac(GASF)) . EF1 where N2O(SN) = Emission of N2O from synthetic fertiliser application (kg N2O/yr) N(FERT) = Total use of synthetic fertiliser (kg N/yr) Frac(GASF) = Fraction of synthetic fertiliser emitted as NOx + NH3 = 0.1 kg NH3-N+NOx -N / kg synthetic N applied EF1 = Emission Factor for direct soil emissions = 0.0125 kg N2O-N/kg N input Annual consumption of synthetic fertilizer is estimated based on crop areas (Defra, 2008a) and fertilizer application rates (BSFP, 2008) as shown in Table A.3.6.10. Figure 1 shows data compiled by the ONS (2008) and BSFP (used in the inventory) at UK level. The ONS data is derived from a combination of sources, including import/export statistics, BSFP and industry production data. The graph shows the BSFP is 8.8% larger in average. Table A  STYLEREF 2 \s 3.6.10 Areas of UK Crops and rates of fertiliser applied Crop TypeCrop area, haFertiliser rate, ktNWinter wheat1,815,878344.7Spring barley514,97950.47Winter barley382,93451.98Oats129,34712.3Rye, triticale & mixed corn24,5611.4Maize146,3087.6Maincrop potatoes140,15317.9Sugar beet124,99411.5Oilseed rape601,605114.0Peas (green, human cons)37,7000.0Peas (dry, human cons)7,0510.0Peas, dry, animal cons)29,9960.0Broad beans3730.0Beans (human cons)90.0Beans (animal cons)123,9730.12Rootcrops for stockfeed35,3873.43Leafy forage crops5,9820.3Other forage crops31.5410.0Vegetables (brassicae)30,5214.19Vegetables (other)37,7702.9Soft fruit9,5080.3Top fruit23,1512.5Hops1,1000.0Linseed10,9580.0Other tillage144,2448.3Grass under 5 years1,176,011117.4Permanent grass5,964,915346.8  Figure A3.6.1. Comparison of fertiliser data, sources BSFP and ONS Biological Fixation of Nitrogen by crops Emissions of nitrous oxide from the biological fixation of nitrogen by crops are calculated using the IPCC (2000) Tier 1a methodology and IPCC default emission factors. They are given by: N2O(BF) = 44/28 . 2 . Crop(BF) . FracDM . Frac(NCRBF) . EF1 where N2O(BF) = Emission of N2O from biological fixation (kg N2O/yr) Crop(BF) = Production of legumes (kg /yr) FracDM = Dry matter fraction of crop Frac(NCRBF) = Fraction of nitrogen in N fixing crop = 0.03 kg N/ kg dry mass EF1 = Emission Factor for direct soil emissions = 0.0125 kg N2O-N/kg N input The factor of 2 converts the edible portion of the crop reported in agricultural statistics to the total biomass. The fraction of dry mass for the crops considered is given in Table A3.6.11. Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 51 Dry Mass Content and Residue Fraction of UK Crops Crop TypeFraction dry massbResidue/CropBroad Beans, Green Peas0.081.1Field Beand, Peas(harvest dry)0.861.1Rye, Mixed corn, Triticale0.855a1.6Wheat, Oats0.855a1.3Barley0.855a1.2Oilseed Rape, Linseed0.91a1.2Maize0.501Hopsc0.201.2Potatoes0.200.4Roots, Onions0.071.2Brassicas0.061.2Sugar Beet0.10.2Other0.051.2Phaseolus beans0.081.2 a Defra (2002) b Burton (1982), Nix (1997) or Defra estimates c Hops dry mass from Brewers Licensed Retail Association (1998) d Field beans dry mass from PGRE (1998) The data for the ratio residue/crop are default values found under Agricultural Soils or derived from Table 4.17 in Field Burning of Agricultural Residues (IPCC, 1997). Crop production data are taken from Defra (2008a, 2008b). The total nitrous oxide emission reported also includes a contribution from improved grass calculated using a fixation rate of 4 kg N/ha/year (Lord, 1997). Crop Residues Emissions of nitrous oxide from the ploughing in of crop residues are calculated using a combination of the IPCC (2000) Tier 1b and 1a methodology, for non-N fixing and N-fixing crops, respectively, and IPCC default emission factors. They are given by: N2O(CR) = (i (CropO . Resoi/Cropoi . FracDMi . Frac(NCRO) . (1-FracB) + (j (2 . Crop(BFj) . FracDMj . Frac(NCRBFj)) . (1-FracRj) . (1-FracBj) )) . EF1 . 44/28 where N2O(CR) = Emission of N2O from crop residues (kg N2O/yr) CropOi = Production of non-N fixing crop i (kg /yr) Frac(NCRO) = Fraction of nitrogen in non-N fixing crops = 0.015 kg N/ kg dry mass FracDMi,j = dry matter fraction of crop i, j. FracR = Fraction of crop that is remove from field as crop FracB = Fraction of crop residue that is burnt rather than left on field EF1 = Emission Factor for direct soil emissions = 0.0125 kg N2O-N/kg N input Crop(BFj) = Production of legume crop j (kg /year) Frac(NCRBF) = Fraction of nitrogen in N fixing crop = 0.03 kg N/ kg dry mass Production data of crops are taken from Defra (2008a, 2008b) and are shown in Table A3.6.12. The dry mass fraction of crops and residue fraction are given in Table A3.6.11. Field burning has largely ceased in the UK since 1993. For years prior to 1993, field-burning data were taken from the annual MAFF Straw Disposal Survey (MAFF, 1995). Table A  STYLEREF 2 \s 3.6.12 Production of UK Crops Crop TypeCrop production, ktBroad beans9.6Field Beans375Peas green for market6Peas green for processing97.8All peas harvested dry17Rye, mixed corn, triticale118Wheat13138Oats712Barley5079OSR1901Linseed17Maize0Sugar beet7525Hops0Potatoes5635Total roots & onions1292Total brassicas439Total others323Phaseolus beans17 Histosols Emissions from Histosols were estimated using the IPCC (2000) default factor of 8 kg N2O-N/ha/yr. The area of cultivated Histosols is assumed to be equal to that of eutric organic soils in the UK and is based on a FAO soil map figure supplied by SSLRC (now NSRI). Grazing Animals Emissions from manure deposited by grazing animals are reported under agricultural soils by IPCC. The method of calculation is the same as that for AWMS (see SectionA3.6.2.2), using factors for pasture range and paddock. Organic Fertilizers Emissions from animal manures and slurries used as organic fertilizers are reported under agricultural soils by IPCC. The calculation involves estimating the amount of nitrogen applied to the land and applying IPCC emission factors. For daily spreading of manure, the emission is given by: N2O(DS) = 44/28 . (T (NT . Nex(T) . AWMS(DS)) . EF1 where N2O(DS) = N2O emissions from daily spreading of wastes (kg N2O/yr) NT = Number of animals of type T Nex(T) = N excretion of animals of type T (kg N/animal/yr), net of N volatilising as NOx and NH3 (values in Table A3.6.7 are without the volatilised fraction removed) AWMS(DS) = Fraction of Nex that is daily spread EF1 = Emission Factor for direct soil emissions = 0.0125 kg N2O-N/kg N input For the application of previously stored manures to land, a correction is applied to account for previous N2O losses during storage. N2O(FAW) = 44/28 . (T (NT . Nex(T) . AWMS(W) - N(AWMS) ) . EF1 where N2O(FAW) = N2O emission from organic fertiliser application NT = Number of animals of type T Nex(T) = N excretion of animals of type T (kg N/animal/yr) net of N volatilising as NOx and NH3 (values in Table A3.6.7 are without the volatilised fraction removed) AWMS(W) = Fraction of Nex that is managed in one of the different waste management systems of type W N(AWMS) = N2O emissions from animal waste management systems as nitrogen (kg N2O-N/yr) The summation is for all animal types and manure previously stored in categories defined as a) liquid, b) solid storage and dry lot and c) other. Atmospheric deposition of NOx and NH3 Indirect emissions of N2O from the atmospheric deposition of ammonia and NOx are estimated according to the IPCC (1997) methodology but with corrections to avoid double counting N. The sources of ammonia and NOx considered are synthetic fertiliser application and animal manures applied as fertiliser. The contribution from synthetic fertilisers is given by: N2O(DSN) = 44/28 . N(FERT) . Frac(GASF) . EF4 where N2O(DSN) = Atmospheric deposition emission of N2O arising from synthetic fertiliser application (kg N2O/yr) N(FERT) = Total mass of nitrogen applied as synthetic fertiliser (kg N/yr) Frac(GASF) = Fraction of total synthetic fertiliser nitrogen that is emitted as NOx + NH3 = 0.1 kg N/ kg N EF4 = N deposition emission factor = 0.01 kg N2O-N/kg NH3-N and NOx-N emitted The indirect contribution from waste management systems is given by: N2O(DWS) = 44/28. (N(EX) /(1-Frac(GASM)) -N(F) ) . Frac(GASM) . EF4 where N2O(DWS) = Atmospheric deposition emission of N2O arising from animal wastes (kg N2O/yr) N(EX) = Total N excreted by animals (kg N/yr), net of N volatilising as NOx and NH3 (values in Table A3.6.7 are without the volatilised fraction removed) Frac(GASM) = Fraction of livestock nitrogen excretion that volatilises as NH3 and NOx = 0.2 kg N/kg N N(F) = Total N content of wastes used as fuel (kg N/yr) The equation corrects for the N content of manures used as fuel. Leaching and runoff Indirect emissions of N2O from leaching and runoff are estimated according the IPCC methodology but with corrections to avoid double counting N. The sources of nitrogen considered, are synthetic fertiliser application and animal manures applied as fertiliser. The contribution from synthetic fertilisers is given by: N2O(LSN) = 44/28 . (N(FERT) . (1-Frac(GASF) )- N(SN)) . Frac(LEACH) . EF5 where N2O(LSN) = Leaching and runoff emission of N2O arising from synthetic fertiliser application (kg N2O/yr) N(FERT) = Total mass of nitrogen applied as synthetic fertiliser (kg N/yr) N(SN) = Direct emission of N2O(SN) as nitrogen (kg N2O-N/yr) Frac(GASF) = Fraction of total synthetic fertiliser nitrogen emitted as NOx + NH3 = 0.1 kg N/ kg N Frac(LEACH) = Fraction of nitrogen input to soils lost through leaching and runoff = 0.3 kg N/ kg fertiliser or manure N EF5 = Nitrogen leaching/runoff factor = 0.025 kg N2O-N /kg N leaching/runoff The estimate includes a correction to avoid double counting N2O emitted from synthetic fertiliser use. The indirect contribution from waste management systems is given by: N2O(LWS) = 44/28. ((N(EX) -N(F) -N(AWMS) ) . Frac(LEACH) . EF5 where N2O(LWS) = Leaching and runoff emission of N2O from animal wastes (kg N2O/yr) N(EX) = Total N excreted by animals (kg N/yr), net of N volatilising as NOx and NH3 (values in Table A3.6.7 are without the volatilised fraction removed) N(F) = Total N content of wastes used as fuel (kg N/yr) N(AWMS) = Total N content of N2O emissions from waste management systems including daily spread and pasture range and paddock (kg N2O-N/yr) Frac(LEACH) = Fraction of nitrogen input to soils that is lost through leaching and runoff = 0.3 kg N/ kg fertiliser or manure N EF5 = Nitrogen leaching/runoff factor = 0.025 kg N2O-N /kg N leaching/runoff The equation corrects both for the N lost in the direct emission of N2O from animal wastes and the N content of wastes used as fuel. Field Burning of Agricultural Residues (4F) The National Atmospheric Emissions Inventory reports emissions from field burning under the category agricultural incineration. The estimates are derived from emission factors calculated according to IPCC (1997) and from USEPA (1997) shown in Table A3.6.13. Table A  STYLEREF 2 \s 3.6. SEQ Table_A \* ARABIC \s 2 63 Emission Factors for Field Burning (kg/t) CH4CONOxN2ONMVOCBarley3.05a63.9a2.18a0.060a7.5bOther3.24a67.9a2.32a0.064a9.0ba IPCC (1997) b USEPA (1997) The estimates of the masses of residue burnt of barley, oats, wheat and linseed are based on crop production data (Defra, 2008b) and data on the fraction of crop residues burnt (MAFF, 1995; ADAS, 1995b). Field burning ceased in 1993 in England and Wales. Burning in Scotland and Northern Ireland is considered negligible, as is grouse moor burning, so no estimates are reported from 1993 onwards. The carbon dioxide emissions are not estimated because under the IPCC Guidelines they are considered to be part of the annual carbon cycle. Land Use, land use Change and Forestry (CRF Sector 5) The following section describes in detail the methodology used in the Land-Use Change and Forestry Sector. Further information regarding this Sector can be found in Chapter 7. Land Converted to Forest Land (5A2) The carbon uptake by the forests planted since 1920 is calculated by a carbon accounting model (Dewar and Cannell 1992; Cannell and Dewar 1995; Milne et al. 1998) as the net change in pools of carbon in standing trees, litter, soil in conifer and broadleaf forests and in products. Restocking is assumed in all forests. The method is Tier 3, as defined in the Good Practice Guidance for LULUCF (IPCC 2003). Two types of input data and two parameter sets were required for the model (Cannell and Dewar 1995). The input data are: (a) areas of new forest planted in each year in the past, and (b) the stemwood growth rate and harvesting pattern. Parameter values were required to estimate (i) stemwood, foliage, branch and root masses from the stemwood volume and (ii) the decomposition rates of litter, soil carbon and wood products. For the estimates described here we used the combined area of new private and state planting from 1921 to 2007 for England, Scotland, Wales and Northern Ireland sub-divided into conifers and broadleaves. Restocking was dealt with in the model through the second and subsequent rotations, which occur after clearfelling at the time of Maximum Area Increment (MAI). Therefore areas restocked in each year did not need to be considered separately. The key assumption is that the forests are harvested according to standard management tables. However, a comparison of forest census data over time has indicated that there are variations in the felling/replanting date during the 20th century, i.e. non-standard management. These variations in management have been incorporated into the forest model, and the methodology will be kept under review in future reporting. The carbon flow model uses Forestry Commission Yield Tables (Edwards and Christie 1981) to describe forest growth after thinning commences and an expo-linear curve for growth before first thinning. It was assumed that all new conifer plantations have the same growth characteristics as Sitka spruce (Picea sitchensis (Bong.) Carr.) under an intermediate thinning management regime. Sitka spruce is the commonest species in UK forests being about 50% by area of conifer forests. Milne et al. (1998) have shown that mean Yield Class for Sitka spruce varied across Great Britain from 10-16 m3 ha-1 a-1, but with no obvious geographical pattern, and that this variation had an effect of less than 10% on estimated carbon uptake for the country as a whole. The Inventory data has therefore been estimated by assuming all conifers in Great Britain followed the growth pattern of Yield Class 12 m3 ha-1 a-1, but in Northern Ireland Yield Class 14 m3 ha-1 a-1 was used. Milne et al. (1998) also showed that different assumptions for broadleaf species had little effect on carbon uptake. It is assumed that broadleaf forests have the characteristics of beech (Fagus sylvatica L.) of Yield Class 6 m3 ha-1 a-1. The most recent inventory of British woodlands (Forestry Commission 2002) shows that beech occupies about 8% of broadleaf forest area (all ages) and no single species occupies greater than 25%. Beech was selected to represent all broadleaves as it has characteristics intermediate between fast growing species e.g. birch, and very slow growing species e.g. oak. However, using oak or birch Yield Class data instead of beech data has been shown to have an effect of less than 10% on the overall removal of carbon to UK forests (Milne et al. 1998). The use of beech as the representative species will be kept under review. Irrespective of species assumptions, the variation in removals from 1990 to the present is determined by the afforestation rate in earlier decades and the effect this has on the age structure in the present forest estate, and hence the average growth rate. At the current (declining) rate of forest expansion removals of atmospheric carbon increased until 2004 and have now started to decrease, reflecting the reduction in afforestation rate after the 1970s. This afforestation is all on ground that has not been wooded for many decades.  REF _Ref193005110 \* MERGEFORMAT Table A 3.7.1 shows the afforestation rate since 1921 and a revised estimate of the present age structure of these forests. A comparison of historical forest census data and the historical annual planting rates has been undertaken. Forest censuses were taken in 1924, 1947, 1965, 1980 and the late 1990s. The comparison of data sources showed that discrepancies in annual planting rates and inferred planting/establishment date (from woodland age in the forest census) are due to restocking of older (pre-1920) woodland areas and variations in the harvesting rotations. However, there is also evidence of shortened conifer rotations in some decades and transfer of woodland between broadleaved categories (e.g. between coppice and high forest). As a result, the afforestation series for conifers in England and Wales were sub-divided into the standard 59 year rotation (1921-2004), a 49 year rotation (1921-1950) and a 39 year rotation (1931-1940, England only). It is difficult to incorporate non-standard management in older conifer forests and broadleaved forests into the Inventory because it is not known whether these forests are on their first rotation or subsequent rotations (which would affect carbon stock changes, particularly in soils). Further work is planned for this area. In addition to these planted forests, there are about 822,000 ha of woodland planted prior to 1921 or not of commercial importance. These forests are assumed to fall in Category 5.A.1 (Forest Land remaining Forest Land). It is evident from the comparison of historical forest censuses that some of this forest area is still actively managed, but overall this category is assumed to be carbon-neutral. The possible contribution of this category to carbon emissions and removals will be considered in more detail in future reporting. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 1: Afforestation rate and age distribution of conifers and broadleaves in the United Kingdom since 1921 PeriodPlanting rate (100 ha a-1)Age distributionConifers on all soil typesConifers on organic soilBroadleavesConifersBroadleaves1921-19305.430.542.441.4%7.8%1931-19407.460.732.132.5%8.4%1941-19507.430.822.226.1%11.8%1951-196021.663.063.0916.0%11.4%1961-197030.085.282.5522.8%8.3%1971-198031.387.611.1422.4%5.9%1981-199022.316.052.1919.1%4.9%199113.463.416.710.9%0.6%199211.562.976.480.8%0.6%199310.062.438.870.7%0.8%19947.391.7411.160.5%1.0%19959.442.3710.470.6%1.0%19967.421.798.930.5%0.8%19977.721.879.460.5%0.9%19986.981.629.670.5%0.9%19996.631.4410.120.5%0.9%20006.531.3710.910.4%1.0%20014.901.0113.450.3%1.2%20023.890.759.990.3%0.9%20033.740.729.220.3%0.8%20042.940.598.890.2%0.8%20052.100.409.190.1%0.8%20061.140.217.030.1%0.6%Afforestation rates and ages of GB forests planted later than 1989 are from planting records. The age distribution for GB forests planted before 1990 is from the National Inventory of Woodland and Trees carried out between 1995 and 1999. The age distribution for pre-1990 Northern Ireland forests is estimated from planting records. Conifer planting on organic soil is a subset of total conifer planting. All broadleaf planting is assumed to be on non-organic soil. Increases in stemwood volume were based on standard Yield Tables, as in Dewar and Cannell (1992) and Cannell and Dewar (1995). These Tables do not provide information for years prior to first thinning so a curve was developed to bridge the gap (Hargreaves et al. 2003). The pattern fitted to the stemwood volume between planting and first thinning from the Yield Tables follows a smooth curve from planting to first thinning. The formulation begins with an exponential pattern but progresses to a linear trend that merges with the pattern in forest management tables after first thinning. The mass of carbon in a forest was calculated from volume by multiplying by species-specific wood density, stem:branch and stem:root mass ratios and the fraction of carbon in wood (0.5 assumed). The values used for these parameters for conifers and broadleaves are given in  REF _Ref193005154 \* MERGEFORMAT Table A 3.7.2. The parameters controlling the transfer of carbon into the litter pools and its subsequent decay are given in  REF _Ref193005154 \* MERGEFORMAT Table A 3.7.2. Litter transfer rate from foliage and fine roots increased to a maximum at canopy closure. A fraction of the litter was assumed to decay each year, half of which was added to the soil organic matter pool, which then decayed at a slower rate. Tree species and Yield Class were assumed to control the decay of litter and soil matter. Additional litter was generated at times of thinning and felling. These carbon transfer parameters have been used to split the living biomass output from C-Flow between gains and losses. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 2; Main parameters for forest carbon flow model used to estimate carbon uptake by planting of forests of Sitka spruce (P. sitchensis and beech (F. sylvatica) in the United Kingdom (Dewar & Cannell 1992) P. sitchensisP. sitchensisF. sylvaticaYC12YC14YC6Rotation (years)595792Initial spacing (m)221.2Year of first thinning252330Stemwood density (t m-3)0.360.350.55Maximum carbon in foliage (t ha-1)5.46.31.8Maximum carbon in fine roots (t ha-1)2.72.72.7Fraction of wood in branches0.090.090.18Fraction of wood in woody roots0.190.190.16Maximum foliage litterfall (t ha-1 a-1)1.11.32Maximum fine root litter loss (t ha-1 a-1)2.72.72.7Dead foliage decay rate (a-1)113Dead wood decay rate (a-1)0.060.060.04Dead fine root decay rate (a-1)1.51.51.5Soil organic carbon decay rate (a-1)0.030.030.03Fraction of litter lost to soil organic matter0.50.50.5Lifetime of wood products575992 Estimates of carbon losses from the afforested soils are based on measurements taken at deep peat moorland locations, covering afforestation of peat from 1 to 9 years previously and at a 26 year old conifer forest (Hargreaves et al. 2003). These measurements suggest that long term losses from afforested peatlands are not as great as had been previously thought, settling to about 0.3 tC ha-1 a-1 thirty years after afforestation. In addition, a short burst of regrowth of moorland plant species occurs before forest canopy closure. Carbon incorporated into the soil under all new forests is included, and losses from pre-existing soil layers are described by the general pattern measured for afforestation of deep peat with conifers. The relative amounts of afforestation on deep peat and other soils in the decades since 1920 are considered. For planting on organo-mineral and mineral soils, it is assumed that the pattern of emissions after planting will follow that measured for peat, but the emissions from the pre-existing soil layers will broadly be in proportion to the soil carbon density of the top 30 cm relative to that same depth of deep peat. A simplified approach was taken to deciding on the proportionality factors, and it is assumed that emissions from pre-existing soil layers will be equal to those from the field measurements for all planting in Scotland and Northern Ireland and for conifer planting on peat in England and Wales. Losses from broadleaf planting in England and Wales are assumed to proceed at half the rate of those in the field measurements. These assumptions are based on consideration of mean soil carbon densities for non-forest in the fully revised UK soil carbon database. The temporary re-growth of ground vegetation before forest canopy closure is, however, assumed to occur for all planting at the same rate as for afforested peat moorland. This assumption agrees with qualitative field observations at plantings on agricultural land in England. It is assumed in the carbon accounting model that harvested material from thinning and felling is made into wood products. The net change in the carbon in this pool of wood products is reported in Category 5G. Nitrogen fertilisation of forest land is assumed to occur only when absolutely necessary, i.e. new planting on poor soils (slag heaps, impoverished brown field sites, or upland organic soils). In terms of the inventory, this means that N fertilisation is assumed for Settlement converted to Forest land and Grassland converted to Forest Land on organic soils. The areas of new planting with these conditions were taken from the same dataset used in the CFlow model for 5.A.2. Land converted to Forest land. An application rate of 150 kg N ha-1 is assumed based on Forestry Commission fertilisation guidelines  ADDIN EN.CITE Taylor199110210210227Taylor, C.M.A.Forest fertilisation in Britain. Forestry Commission Bulletin 95.nutrients, forestry1991FC Bulletin 95ISBN 0 11 710294 6(Taylor 1991). The guidelines recommend applying fertiliser on a three-year cycle until canopy closure (at c. 10 years), but this is thought to be rather high  ADDIN EN.CITE Skiba200710110110126Skiba, U.Thomson, A.N fertilisation of UK forestsWord document "Nitrogen applications to forests.doc" on I:\carb62007(Skiba 2007) and unlikely to occur in reality, so two applications are adopted as a compromise. These applications occur in year 1 and year 4 after planting. As a result, emissions from N fertilisation since 1990 include emissions from forests that were planted before 1990 but received their second dose of fertiliser after 1990. The emission factor for N2O of applied nitrogen fertiliser is the default value of 1.25%. Emissions of N2O from N fertilisation of forests have fallen since 1990 due to reduced rates of new forest planting. Land Use Change and Soils (5B2, 5C2, 5E2) The method for assessing changes in soil carbon due to land use change uses a matrix of change from land surveys linked to a dynamic model of carbon stock change. For Great Britain (England, Scotland and Wales), matrices from the Monitoring Landscape Change (MLC) data from 1947 & 1980 (MLC 1986) and the Countryside Surveys (CS) of 1984, 1990 and 1998 (Haines-Young et al. 2000) are used. In Northern Ireland, fewer data are available to build matrices of land use change, but for 1990 to 1998 a matrix for the whole of Northern Ireland was available from the Northern Ireland Countryside Survey (Cooper and McCann 2002). The only data available for Northern Ireland pre-1990 is land use areas from The Agricultural Census and The Forest Service (Cruickshank and Tomlinson 2000). Matrices of land use change were then estimated for 1970-79 and 1980-89 using area data. The basis of the method devised was to assume that the relationship between the matrix of land use transitions for 1990 to 1998 and the area data for 1990 is the same as the relationship between the matrix and area data for each of two earlier periods 1970-79 and 1980-89. The matrices developed in this approach were used to extrapolate areas of land use transition back to 1950 to match the start year in the rest of the UK. The Good Practice Guidance for Land Use, Land Use Change and Forestry (IPCC 2003) recommends use of six classes of land for descriptive purposes: Forest, Grassland, Cropland, Settlements, Wetlands and Other Land. The data presently available for the UK does not distinguish wetlands from other types, so land in the UK has been placed into the five other types. The more detailed categories for the two surveys in Great Britain were combined as shown in  REF _Ref193005216 \* MERGEFORMAT Table A 3.7.3 for MLC and  REF _Ref193005229 \* MERGEFORMAT Table A 3.7.4 for CS. The area data used between 1947 and 1998 are shown in  REF _Ref193005265 \h  \* MERGEFORMAT Table A 3.7.5 and  REF _Ref193005277 \* MERGEFORMAT Table A 3.7.6. The land use change data over the different periods were used to estimate annual changes by assuming that these were uniform across the measurement period. Examples of these annual changes (for the period 1990 to 1999) are given in  REF _Ref193005314 \* MERGEFORMAT Table A 3.7.7 to  REF _Ref193005334 \* MERGEFORMAT Table A 3.7.10. The data for afforestation and deforestation shown in the Tables are adjusted before use for estimating carbon changes to harmonise the values with those used in the calculations for Land converted to and from Forest Land. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 3: Grouping of MLC land cover types for soil carbon change modelling CROPLANDGRASSLANDFORESTLANDSETTLEMENTS (URBAN)OTHERCropsUpland heathBroadleaved woodBuilt upBare rockMarket gardenUpland smooth grassConifer woodUrban openSand/shingleUpland coarse grassMixed woodTransportInland waterBlanket bogOrchardsMineral workingsCoastal waterBrackenDerelictLowland rough grassLowland heatherGorseNeglected grasslandMarshImproved grasslandRough pasturePeat bogFresh MarshSalt Marsh Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 4: Grouping of Countryside Survey Broad Habitat types for soil carbon change modelling CROPLANDGRASSLANDFORESTLANDSETTLEMENTS (URBAN)OTHERArableImproved grasslandBroadleaved/ mixedBuilt up areasInland rockHorticultureNeutral grasslandConiferousGardensSupra littoral rockCalcareous grasslandLittoral rockAcid grasslandStanding watersBrackenRiversDwarf shrub heathSeaFen, marsh, swampBogsMontaneSupra littoral sedimentLittoral sediment Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 5: Sources of land use change data in Great Britain for different periods in estimation of changes in soil carbon Year or PeriodMethodChange matrix data1950-1979Measured LUC matrixMLC 1947->MLC19801980 - 1984InterpolatedCS1984->CS19901984 - 1989Measured LUC matrixCS1984->CS19901990 - 1998Measured LUC matrixCS1990->CS19981999-2003ExtrapolatedCS1990->CS1998 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 6: Sources of land use change data in Northern Ireland for different periods in estimation of changes in soil carbon. NICS = Northern Ireland Countryside Survey Year or PeriodMethodChange matrix data1950 1969Extrapolation and ratio methodNICS1990->NICS19981970 1989Land use areas and ratio methodNICS1990->NICS19981990 1998Measured LUC matrixNICS1990->NICS19981999-2003ExtrapolatedNICS1990->NICS1998 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 7: Annual changes (000 ha) in land use in England in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys ( ADDIN EN.CITE Haines-Young200079796Haines-Young, R.H.Barr, C.J.Black, H.I.J.Briggs, D.J.Bunce, R.G.H.Clarke, R.T.Cooper, A. Dawson, F.H.Firbank, L.G.Fuller, R.M.Furse, M.T.Gillespie, M.K.Hill, R.Hornung, M.Howard, D.C.McCann, T.Morecroft, M.D.Petit, S.Sier, A.R.J.Smart, S.M.Smith, G.M.Stott, A.P.Stuart, R.C.Watkins, J.W.Accounting for nature: assessing habitats in the UK countryside2000LondonDETR Countryside Survey 2000ISBN 1 85112 460 8Haines-Young et al. 2000). Data have been rounded to 100 ha From ToForestlandGrasslandCroplandSettlementsForestland8.93.42.1Grassland8.755.33.4Cropland0.562.90.6Settlements1.28.52.1 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 8: Annual changes (000 ha) in land use in Scotland in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys ( ADDIN EN.CITE Haines-Young200079796Haines-Young, R.H.Barr, C.J.Black, H.I.J.Briggs, D.J.Bunce, R.G.H.Clarke, R.T.Cooper, A. Dawson, F.H.Firbank, L.G.Fuller, R.M.Furse, M.T.Gillespie, M.K.Hill, R.Hornung, M.Howard, D.C.McCann, T.Morecroft, M.D.Petit, S.Sier, A.R.J.Smart, S.M.Smith, G.M.Stott, A.P.Stuart, R.C.Watkins, J.W.Accounting for nature: assessing habitats in the UK countryside2000LondonDETR Countryside Survey 2000ISBN 1 85112 460 8Haines-Young et al. 2000). Data have been rounded to 100 ha From ToForestlandGrasslandCroplandSettlementsForestland11.10.60.2Grassland5.016.80.7Cropland0.121.40.3Settlements0.32.20.1 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 9: Annual changes (000 ha) in land use in Wales in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Countryside Surveys ( ADDIN EN.CITE Haines-Young200079796Haines-Young, R.H.Barr, C.J.Black, H.I.J.Briggs, D.J.Bunce, R.G.H.Clarke, R.T.Cooper, A. Dawson, F.H.Firbank, L.G.Fuller, R.M.Furse, M.T.Gillespie, M.K.Hill, R.Hornung, M.Howard, D.C.McCann, T.Morecroft, M.D.Petit, S.Sier, A.R.J.Smart, S.M.Smith, G.M.Stott, A.P.Stuart, R.C.Watkins, J.W.Accounting for nature: assessing habitats in the UK countryside2000LondonDETR Countryside Survey 2000ISBN 1 85112 460 8Haines-Young et al. 2000). Data have been rounded to 100 ha From ToForestlandGrasslandCroplandSettlementsForestland2.40.20.2Grassland1.55.50.6Cropland0.08.00.0Settlements0.11.80.2 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 10: Annual changes (000 ha) in land use in Northern Ireland in matrix form for 1990 to 1999. Based on land use change between 1990 and 1998 from Northern Ireland Countryside Surveys ( ADDIN EN.CITE Cooper2002737327Cooper, AMcCann, TTechnical Report of the Northern Ireland Countryside Survey2002University of UlsterCooper & McCann 2002). Data have been rounded to 100 ha From ToForestlandGrasslandCroplandSettlementsForestland1.60.00.0Grassland0.35.90.0Cropland0.03.70.0Settlements0.11.00.0 A database of soil carbon density for the UK ( ADDIN EN.CITE Milne1997656517Milne, R.Brown, T. A.Carbon in the vegetation and soils of Great BritainJournal of Environmental ManagementJournal of Environmental Management413-4334941997AprISI:A1997WV10800003<Go to ISI>://A1997WV10800003 Milne & Brown 1997,  ADDIN EN.CITE Cruickshank1998666617Cruickshank, M. M.Tomlinson, R. W.Devine, P. M.Milne, R.Carbon in the vegetation and soils of Northern IrelandBiology and Environment-Proceedings of the Royal Irish AcademyBiology and Environment-Proceedings of the Royal Irish Academy9-2198B11998AugISI:000080604400002<Go to ISI>://000080604400002 Cruickshank et al. 1998,  ADDIN EN.CITE Bradley2005888817Bradley, R IMilne, RBell, JLilly, AJordan, CHiggins, AA soil carbon and land use database for the United KingdomSoil Use and ManagementSoil Use and ManagementSoil Use Manage.363-36921004Soil carbon inventory, carbon stocks, land use, United Kingdom2005December 2005DOI: 10.1079/SUM2005351Bradley et al. 2005) is used in conjunction with the land use change matrices. There are three soil survey groups covering the UK and the field data, soil classifications and laboratory methods have been harmonized to reduce uncertainty in the final joint database. The depth of soil considered was also restricted to 1 m at maximum as part of this process.  REF _Ref193005369 \* MERGEFORMAT Table A 3.7.11 shows total stock of soil carbon (1990) for different land types in the four devolved areas of the UK. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 11: Soil carbon stock (TgC = MtC) for depths to 1 m in different land types in the UK Region Type EnglandScotlandWalesN. IrelandUKForestland1082954520467Grassland9952,3492832423,870Cropland583114833738Settlements54103169Other0000-TOTAL1,7402,7683402965,144 The dynamic model of carbon stock change requires the change in equilibrium carbon density from the initial to the final land use. The core equation describing changes in soil carbon with time for any land use transition is: EMBED Equation.3 where Ct is carbon density at time t C0 is carbon density initial land use Cf is carbon density after change to new land use k is time constant of change By differentiating we obtain the equation for flux ft (emission or removal) per unit area:  EMBED Equation.3  From this equation we obtain, for any inventory year, the land use change effects from any specific year in the past. If AT is area in a particular land use transition in year T considered from 1950 onwards then total carbon lost or gained in an inventory year, e.g. 1990, is given by:  EMBED Equation.3  This equation is used with k, AT and (Cf-C0) chosen by Monte Carlo methods within ranges set by prior knowledge, e.g. literature, soil carbon database, agricultural census, LUC matrices. In the model, the change is required in equilibrium carbon density from the initial to the final land use during a transition. Here, these are calculated for each land use category as averages for Scotland, England, Wales and Northern Ireland. These averages are weighted by the area of Land Use Change occurring in four broad soil groups (organic, organo-mineral, mineral, unclassified) in order to account for the actual carbon density where change has occurred. Hence mean soil carbon density change is calculated as: EMBED Equation.3 This is the weighted mean, for each country, of change in equilibrium soil carbon when land use changes, where: i = initial land use (Forestland, Grassland, Cropland, Settlements) j = new land use (Forestland, Grassland, Cropland, Settlements) c = country (Scotland, England, N. Ireland & Wales) s = soil group (organic, organo-mineral, mineral, unclassified) Csijc is change in equilibrium soil carbon for a specific land use transition The most recent land use data (1990 to 1998) is used in the weighting. The averages calculated are presented in  REF _Ref224627108 \h  \* MERGEFORMAT Table A 3.7.12- REF _Ref224627118 \h  \* MERGEFORMAT Table A 3.7.15. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 12: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in England From ToForestlandGrasslandCroplandSettlementsForestland0253283Grassland-2102379Cropland-31-23052Settlements-87-76-540 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 13: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Scotland From ToForestlandGrasslandCroplandSettlementsForestland047158246Grassland-52088189Cropland-165-90096Settlements-253-187-670 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 14: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Wales From ToForestlandGrasslandCroplandSettlementsForestland02357114Grassland-18036101Cropland-53-38048Settlements-110-95-730 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 15: Weighted average change in equilibrium soil carbon density (kg m-2) to 1 m deep for changes between different land types in Northern Ireland From ToForestlandGrasslandCroplandSettlementsForestland094168244Grassland-94074150Cropland-168-74076Settlements-244-150-760 The rate of loss or gain of carbon is dependent on the type of land use transition ( REF _Ref224627168 \h  \* MERGEFORMAT Table A 3.7.16). For transitions where carbon is lost e.g. transition from Grassland to Cropland, a fast rate is applied whilst a transition that gains carbon occurs much more slowly. A literature search for information on measured rates of changes of soil carbon due to land use was carried out and ranges of possible times for completion of different transitions were selected, in combination with expert judgement. These are shown in  REF _Ref224627194 \h  \* MERGEFORMAT Table A 3.7.17. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 16: Rates of change of soil carbon for land use change transitions. (Fast & Slow refer to 99% of change occurring in times shown in Table A3.7.17) InitialForestlandGrasslandCroplandSettlementFinalForestlandslowslowslowGrasslandfastslowslowCroplandfastfastslowSettlementfastfastfast Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 17: Range of times for soil carbon to reach 99% of a new value after a change in land use in England (E), Scotland (S) and Wales (W) Low (years)High (years)Carbon loss (fast) E, S, W50150Carbon gain (slow) E, W100300Carbon gain (slow) S300750 Changes in soil carbon from equilibrium to equilibrium (Cf-Co) were assumed to fall within ranges based on 2005 database values for each transition and the uncertainty indicated by this source (up to 11% of mean). The areas of land use change for each transition were assumed to fall a range of uncertainty of 30% of mean. A Monte Carlo approach is used to vary the rate of change, the area activity data and the values for soil carbon equilibrium (under initial and final land use) for all countries in the UK. The model of change was run 1000 times using parameters selected from within the ranges described above. The mean carbon flux for each region resulting from this imposed random variation is reported as the estimate for the Inventory. An adjustment was made to these calculations for each country to remove increases in soil carbon due to afforestation, as the C-Flow model provides a better estimate of these fluxes in the Land Converted to Forest Land category. Variations from year to year in the reported net emissions reflect the trend in land use change as described by the matrices of change. Changes in stocks of carbon in non-forest biomass due to land use change (5B2, 5C2, 5E2) Changes in stocks of carbon in biomass due to land use change are based on the same area matrices used for estimating changes in carbon stocks in soils (see previous section). The biomass carbon density for each land type is assigned by expert judgement based on the work of Milne and Brown (1997) and these are shown in  REF _Ref224627262 \h  \* MERGEFORMAT Table A 3.7.18. Five basic land uses were assigned initial biomass carbon densities, then the relative occurrences of these land uses in the four countries of the UK were used to calculate mean densities for each of the IPCC types, Cropland, Grassland and Settlements. Biomass carbon stock changes due to conversions to and from Forest Land are dealt with elsewhere. The mean biomass carbon densities for each land type were further weighted by the relative proportions of change occurring between land types ( REF _Ref224627288 \h  \* MERGEFORMAT Table A 3.7.19- REF _Ref224627312 \h  \* MERGEFORMAT Table A 3.7.22), in the same way as the calculations for changes in soil carbon densities. Changes between these equilibrium biomass carbon densities were assumed to happen in a single year. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 18: Equilibrium biomass carbon density (kg m-2) for different land types Density (kg m-2)ScotlandEnglandWalesN. IrelandArable0.150.150.150.15Gardens0.350.350.350.35Natural0.200.200.200.20Pasture0.100.100.100.10Urban0000IPPC types weighted by occurrenceCropland0.150.150.150.15Grassland0.180.120.130.12Settlements0.290.280.280.26 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 19: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in England (Transitions to and from Forestland are considered elsewhere) From ToForestlandGrasslandCroplandSettlementsForestlandGrassland00.08-0.08Cropland-0.080-0.13Settlements0.080.130 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 20: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in Scotland. (Transitions to and from Forestland are considered elsewhere) From ToForestlandGrasslandCroplandSettlementsForestlandGrassland00.02-0.09Cropland-0.020-0.14Settlements0.090.140 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 21: Weighted average change in equilibrium biomass carbon density (kgm2) to 1 m deep for changes between different land types in Wales. (Transitions to and from Forestland are considered elsewhere) From ToForestlandGrasslandCroplandSettlementsForestlandGrassland00.07-0.08Cropland-0.070-0.13Settlements0.080.130 Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 22: Weighted average change in equilibrium biomass carbon density (kgm2) to 1m deep for changes between different land types in Northern Ireland. (Transitions to and from Forestland are considered elsewhere) From ToForestlandGrasslandCroplandSettlementsForestlandGrassland00.08-0.06Cropland-0.080-0.11Settlements0.060.110 Biomass Burning due to De-forestation (5C2, 5E2) Levy and Milne (2004) discuss methods for estimating deforestation using a number of data sources. Here we use their approach of combining Forestry Commission felling licence data for rural areas with Ordnance Survey data for non-rural areas. In Great Britain, some activities that involve tree felling require permission from the Forestry Commission, in the form of a felling licence, or a felling application within the Woodland Grant Scheme. Under the Forestry Act 1967, there is a presumption that the felled areas will be restocked, usually by replanting. Thus, in the 1990s, around 14,000 ha a 1 were felled and restocked. However, some licences are granted without the requirement to restock, where there is good reason so-called unconditional felling licences. Most of these areas are small (1-20 ha), but their summation gives some indication of areas deforested. These areas are not published, but recent figures from the Forestry Commission have been collated. These provide estimates of rural deforestation rates in England for 1990 to 2002 and for GB in 1999 to 2001. The most recent deforestation rate available for rural areas is for 2002 so rates for 2003-2007 were estimated by extrapolating forwards from the rates for 1999-2002. Only local planning authorities hold documentation for allowed felling for urban development, and the need for collation makes estimating the national total difficult. However, in England, the Ordnance Survey (national mapping agency) makes an annual assessment of land use change from the data it collects for map updating and provides this assessment the Department of Communities and Local Government. Eleven broad land-use categories are defined, with a number of sub-categories. The data for England (1990 to 2007) were available to produce a land-use change matrix, quantifying the transitions between land-use classes. Deforestation rate was calculated as the sum of transitions from all forest classes to all non-forest classes providing estimates on non-rural deforestation. The rural and non-rural values for England were each scaled up to GB scale, assuming that England accounted for 72 per cent of deforestation, based on the distribution of licensed felling between England and the rest of GB in 1999 to 2002. However, the Ordnance Survey data come from a continuous rolling survey programme, both on the ground and from aerial photography. The changes reported each year may have actually occurred in any of the preceding 1-5 years (the survey frequency varies among areas, and can be up to 10 years for moorland/mountain areas). Consequently, a five-year moving average was applied to the data to smooth out the between-year variation appropriately, to give a suitable estimate with annual resolution. Deforestation is not currently estimated for Northern Ireland. Rural deforestation is assumed to convert the land to Grassland use (reported in Category 5C2) and non-rural deforestation causes conversion to the Settlement land type (reported in 5E2). Information from land use change matrices indicates that conversion of forest to cropland is negligible. On deforestation it is assumed that 60% of the standing biomass is removed as timber products and the remainder is burnt. The annual area loss rates were used in the method described in the IPCC 1996 guidelines (IPCC 1997 a, b, c) to estimate immediate emissions of CO2, CH4 and N2O from this biomass burning. Only immediate losses are considered because sites are normally completely cleared for development, leaving no debris to decay. Changes in stocks of soil carbon after deforestation are included with those due to other land use transitions. Biomass Burning Forest Wildfires (5A2) The method for estimating emissions of CO2 and non-CO2 gases from wildfires within managed forests is that described in the GPG LULUCF (Section 3.2.1.4). Estimates of the area burnt in wildfires 1990-2004 are published in different locations (FAO/ECE 2002; Forestry Commission 2004; FAO 2005) but all originate from either the Forestry Commission (Great Britain) or the Forest Service (Northern Ireland). No data on areas burnt in wildfires has been collected or published since 2004, although this is apparently under review. Activity data for 2005 and 2007 is extrapolated using a Burg regression equation based on the trend and variability of the 1990-2004 dataset. These areas refer only to fire damage in state forests; no information is collected on fire damage in privately owned forests. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 23: Area burnt in wildfires in state (Forestry Commission) forests 19902007 (* indicates an estimated area) YearArea burnt, haGreat BritainNorthern IrelandUK% UK forest area burnt19901851273120.021%1991376*88*4640.042%199292*22*1140.010%1993157*37*1940.018%1994123*241470.014%19951023*1610390.119%1996466945600.055%19975851357200.069%1998310223320.037%1999459540.005%200016561710.020%2001181852660.023%2002141852260.018%200314711480.019%2004146912370.019%20055*75*80*0.008%2006429*3*432*0.045%2007412*97*508*0.054% The area of private-owned forest that was burnt each year was assumed to be in proportion to the percentage of the state forest that was burnt each year. An estimated 921 ha of forest was burnt on average every year (the sum of state-owned and privately-owned forests) between 1990 and 2007. There is no information on the type (conifer or broadleaf) or age of forest that is burnt in wildfires in the UK. Therefore, the amount of biomass burnt is estimated from the mean forest biomass density in each country of the UK, as estimated by the C-Flow model. These densities vary with time due to the different afforestation histories in each country ( REF _Ref224627354 \h  \* MERGEFORMAT Table A 3.7.24). Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 24: Biomass densities, tonnes DM ha-1, used to estimate mass of available fuel for wildfires YearForest biomass density, tonnes DM ha-1EnglandScotlandWalesNorthern IrelandUK199092.37259.53184.79388.15971.394199597.18469.53595.83297.72780.1892000100.93779.323101.856106.35388.0562005107.62893.177119.397116.110100.3532007110.30198.319125.671118.154104.846 A combustion efficiency of 0.5 is used with a carbon fraction of dry matter of 0.5 to estimate the total amount of carbon released, and hence emissions of CO2 and non-CO2 gases (using the IPCC emission ratios). Liming of Agricultural Soils (5B1, 5C1) The method for estimating CO2 emissions due to the application of lime and related compounds is that described in the IPCC 1996 Guidelines. For limestone and chalk, an emission factor of 120 tC/kt applied is used, and for dolomite application, 130 tC/kt. These factors are based on the stoichiometry of the reaction and assume pure limestone/chalk and dolomite. Only dolomite is subjected to calcination. However, some of this calcinated dolomite is not suitable for steel making and is returned for addition to agricultural dolomite this fraction is reported annually by the Office of National Statistics (ONS) as material for calcination under agricultural end use. Calcinated dolomite, having already had its CO2 removed, will therefore not cause the emissions of CO2 and hence is not included here. Lime (calcinated limestone) is also used for carbonation in the refining of sugar but this is not specifically dealt with in the UK LUCF GHG Inventory. Lime is applied to both grassland and cropland. The annual percentages of arable and grassland areas receiving lime in Great Britain for 1994-2006 were obtained from the Fertiliser Statistics Report (Agricultural Industries Confederation 2006), and the British Survey of Fertiliser Practice (BSFP 2007). These data are produced annually and used to update the inventory, however due to new time restrains the data were unavailable for the 2007 accounting period. The projected value for 2007 estimated in the 2006 accounting period has been used as the 2007 figure. Percentages for 1990-1993 were assumed to be equal to those for 1994. Lowland Drainage (5B1) Lowland wetlands in England were drained many years ago for agricultural purposes and continue to emit carbon from the soil. Bradley (1997) described the methods used to estimate these emissions. The baseline (1990) for the area of drained lowland wetland for the UK was taken as 150,000 ha. This represents all of the East Anglian Fen and Skirtland and limited areas in the rest of England. This total consists of 24,000 ha of land with thick peat (more than 1 m deep) and the rest with thinner peat. Different loss rates were assumed for these two thicknesses as shown in  REF _Ref224627396 \h  \* MERGEFORMAT Table A 3.7.25. The large difference between the implied emission factors is due to the observation that peats described as thick lose volume (thickness) more rapidly than peats described as thin. The thick peats are deeper than 1m, have 21% carbon by mass and in general have different texture and less humose topsoil than the thin peats, which have depths up to 1m (many areas ~0.45 m deep) and carbon content of 12% by mass. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 25: Area and carbon loss rates of UK fen wetland in 1990 AreaOrganic carbon contentBulk densityVolume loss rateCarbon mass lossImplied emission factorkg m-3m3 m-2 a-1GgC a-1gC m-2 a-1Thick peat24x107 m2 (24,000 ha)21%4800.01273071280Thin peat126x107 m2 (126,000 ha)12%4800.0019138109Total150x107 m2 (150 kha)445297 The emissions trend since1990 was estimated assuming that no more fenland has been drained since then but that existing drained areas have continued to lose carbon. The annual loss for a specific location decreases in proportion to the amount of carbon remaining. Furthermore, as the peat loses carbon it becomes more mineral in structure. The Century model of plant and soil carbon was used to average the carbon losses from these fenland soils over time (Bradley 1997): further data on how these soil structure changes proceed with time is provided in Burton (1995). Changes in Stocks of Carbon in Non-Forest Biomass due to Yield Improvements (5B1) There is an annual increase in the biomass of cropland vegetation in the UK that is due to yield improvements (from improved species strains or management, rather than fertilization or nitrogen deposition). Under category 5.B.1 an annual value is reported for changes in carbon stock, on the assumption that the annual average standing biomass of cereals has increased linearly with increase in yield between 1980 and 2000 (Sylvester-Bradley et al. 2002). Peat Extraction (5C1) Cruickshank and Tomlinson (1997) provide initial estimates of Emissions due to peat extraction. Since their work, trends in peat extraction in Scotland and England over the period 1990 to 2007 have been estimated from activity data taken from the Business Monitor of Mineral Extraction in Great Britain (Office of National Statistics 2007). In Northern Ireland, no new data on use of peat for horticultural use has been available but a recent survey of extraction for fuel use suggested that there is no significant trend for this purpose. The contribution of emissions due to peat extraction in Northern Ireland is therefore incorporated as constant from 1990 to 2007. Peat extraction is negligible in Wales. Emissions factors are from Cruickshank and Tomlinson (1997) and are shown in  REF _Ref224627475 \h  \* MERGEFORMAT Table A 3.7.26. Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 26: Emission Factors for Peat Extraction Emission Factor kg C m-3Great Britain Horticultural Peat55.7Northern Ireland Horticultural Peat44.1Harvested Wood Products (5G) The activity data used for calculating this activity is the annual forest planting rates. C-Flow assumes an intermediate thinning management regime with clear-felling and replanting at the time of Maximum Area Increment (57 or 59 years for conifers and 92 years for broadleaves). Hence, for a given forest stand, carbon enters the HWP pool when thinning is undertaken (depending on the species first thinning occurs c. 20 years after planting) and when harvesting takes place. Harvesting operations that result in deforestation and land use changes are assumed to be conversions to either Grasslands or Settlements and are report in 5C2 and 5E2 respectively. The UK has no records showing the reduction rate of Forest Land from thinning operations, therefore a nominal (822 kha y-1) is subtracted from the pre 1921 Forest records (these Forests are assumed to be C neutral), reductions are now reported in 5.A.1. A living biomass carbon stock loss of 5% is assumed to occur immediately at harvest (this carbon is transferred to the litter or soil pools). The remaining 95% is transferred to the HWP pool. The residence times of wood products in the HWP pool depend on the type and origin of the products and are based on exponential decay constants. Residence times are estimated as the time taken for 95% of the carbon stock to be lost (from a quantity of HWP entering the HWP pool at the start). Harvested wood products from thinnings are assumed to have a lifetime (residence time) of 5 years, which equates to a half-life of 0.9 years. Wood products from harvesting operations are assumed to have a residence time equal to the rotation length of the tree species. For conifers this equates to a half life of 14 years (59 years to 95% carbon loss) and for broadleaves a half life of 21 years (92 years to 95% carbon loss). This approach captures differences in wood product use: fast growing softwoods tend to be used for shorter lived products than slower growing hardwoods. These residence time values fall mid range between those tabled in the LULUCF GPG (IPCC 2003) for paper and sawn products: limited data were available for the decay of HWP in the UK when the C-Flow model was originally developed. A criticism of the current approach is that the mix of wood products in the UK may be changing and this could affect the true mean value of product lifetime. At present there is very limited accurate data on either decay rates or volume statistics for different products in the UK, although this is kept under review. The C-Flow method does not precisely fit with any of the approaches to HWP accounting described in the IPCC Guidelines (2006) but is closest to the Production Approach (see Thomson and Milne in Milne and Mobbs 2005). The UK method is a top-down approach that assumes that the decay of all conifer products and all broadleaf products can be approximated by separate single decay constants. While this produces results with high uncertainty it is arguably as fit-for-purpose as bottom-up approaches where each product is given an (uncertain) decay and combined with (uncertain) decay of other products using harvest statistics which are in themselves uncertain. According to this method the total HWP pool from UK forests is presently increasing, driven by historical expansion of the forest area and the resulting history of production harvesting (and thinning). The stock of carbon in HWP (from UK forests planted since 1921) has been increasing since 1990 but this positive stock change rate recently reversed, reflecting a severe dip in new planting during the 1940s. The net carbon stock change in the HWP pool has returned to a positive value (i.e. an increasing sink) in 2006, and is forecast to increase sharply as a result of the harvesting of the extensive conifer forests planted between 1950 and the late 1980s. Emissions of Non-CO2 Gases from Disturbance Associated with Land use Conversion Emissions of greenhouse gases other than CO2 in the Land Use Change and Forestry Sector come from four activities: (i) biomass burning as part of deforestation producing CO2, CH4 and N2O emissions; (ii) biomass burning during wildfires on forest land producing CO2, CH4 and N2O emissions; (iii) application of fertilisers to forests producing N2O; and (iv) disturbance of soils due to some types of land use change producing N2O associated with CO2 emissions, or CH4. Emissions by biomass burning are discussed elsewhere. Emissions from other activities were considered by Skiba (in Milne and Mobbs 2005) but have not yet been reported in the CRF. Here we discuss these emissions in more detail with a view to their reporting in future CRF submissions. The CRF provides two tables where emissions of non-CO2 gases associated with soil disturbance after land use change can be reported. CRF Table 5(II) is provided for reporting emissions due to drainage of forest soils or wetlands (which are not reported in the UK). Drainage of some form has often occurred when new forests are planted in the UK but there is no information readily available on the extent of this. Table 5(III) specifically provides for reporting of emissions after land use conversion to Cropland but this table is also appropriate for reporting N2O emissions from other land use change (excepting emissions from conversion to Forest Land which are already covered elsewhere). Emissions of N2O due Disturbance Associated with Land Use Conversion In the UK six land use transitions cause immediate and delayed emissions of CO2. These are as follows: Forest Land to Grassland; Forest Land to Cropland; Forest Land to Settlement; Grassland to Cropland; Grassland to Settlement; and Cropland to Settlement. The method recommended in the LULUCF GPG for calculating N2O emissions due to land use change is to take the CO2 emission due to a specific change and then use the C:N ratio for the soils being disturbed to estimate the N lost due to the mineralisation of organic matter. The default emission factor for the N2O pathway (1.25%) is then used to calculate the emitted flux of N2O-N.  REF _Ref193005745 \* MERGEFORMAT Table A 3.7.27 shows the emissions for the period from 1990 to 2007 adopting this approach with a C:N ratio of 15:1 for all land Table A  STYLEREF 2 \s 3.7. SEQ Table_A \* ARABIC \s 2 27: Emissions of N2O in the UK due to disturbance of soils after land use change estimated by the method of the LULUCF GPG Forest Land to GrasslandForest Land to CroplandForest Land to SettlementGrassland to CroplandGrassland to SettlementCropland to SettlementALL LUCGg N2OGg N2OGg N2OGg N2OGg N2OGg N2OGg N2O19900.0350.0040.0264.9952.0190.4017.48219910.0350.0040.0295.0012.0080.3907.46619920.0350.0040.0315.0061.9970.3787.45219930.0340.0040.0355.0121.9860.3687.43919940.0340.0030.0375.0181.9770.3587.42819950.0360.0030.0385.0241.9680.3497.41919960.0370.0030.0395.0311.9600.3407.41019970.0340.0030.0445.0371.9530.3327.40319980.0340.0030.0465.0441.9460.3247.39619990.0450.0030.0375.0501.9390.3177.39120000.0500.0020.0335.0571.9330.3107.38620010.0540.0020.0315.0641.9280.3037.38220020.0560.0020.0315.0711.9230.2977.37920030.0560.0020.0325.0771.9180.2927.37720040.0540.0020.0355.0841.9130.2867.37520050.0560.0020.0355.0901.9090.2817.37320060.0560.0020.0365.0961.9050.2767.37220070.0530.0020.0415.1031.9020.2727.371 The 1990 emission rate for all land use change is equivalent to an emission of 2319 Gg CO2 (using a GWP of 310) which is similar to the net uptake of CO2 equivalents by all other activities in the UK LULUCF Sector. It is therefore of considerable importance that the methodology used is scientifically sound. On further investigation this does not appear to be the case. The LULUCF GPG methodology relies on estimating gross nitrogen loss from a gross carbon loss and a C:N ratio, but several factors suggest that this approach does not lead to reliable values. There are few measurements of C:N ratios for different land use and for different environmental conditions, making it difficult to generalise values for a whole country. More importantly, understanding of the mechanisms that cause C:N ratios to vary with different land management is weak, particularly in relation to how changes in the C:N ratio of different pools in the soil affect the gross C:N ratio. For example Pineiro et al. (2006) show that it is possible to obtain gross N mineralisation changes of opposite sign depending on whether changes in whole-soil or individual pool C:N ratios are considered in a model of the effect of grazing on soil. It would therefore seem prudent to await an alternative approach to estimating N2O emissions due to land use change before including any data in the inventory. The UK National Inventory System is currently supporting research to measure change in stocks of soil carbon and nitrogen due to ploughing of an upland grassland. Emissions from Disturbance of Soils by Afforestation (drainage etc) The methodology used to estimate CO2 removals and emissions due to the establishment of forests is described in Section  REF _Ref224627566 \r \h  \* MERGEFORMAT A3.7.1. Included in these estimates are emissions relating to the loss of carbon (as CO2) as a result of disturbance of the pre-existing soil. The calculation of N2O emissions from this disturbance was discussed in the 1990-2005 NIR. In this discussion it was assumed that nitrogen in the soil was lost with the carbon in proportion to the C:N ratio as suggested by the LULUCF GPG for other types of land use change that cause carbon mineralization. The resulting N2O emissions were of the same order of magnitude as those suggested as Tier 1 Defaults in the LULUCF GPG. However, the criticisms of using gross C:N ratios to obtain N loss also apply. A further consideration of methods will therefore be needed before data can be included in the inventory. Emissions of methane due to drainage of forests are estimated to be very small (Skiba in Milne and Mobbs (2005)). Methods for the Overseas Territories and Crown Dependencies The UK includes direct GHG emissions in its GHGI from those UK Crown Dependencies (CDs) and Overseas Territories (OTs) which have joined, or are likely to join, the UKs instruments of ratification to the UNFCCC and the Kyoto Protocol. Currently, these are: Guernsey, Jersey, the Isle of Man, the Falkland Islands, the Cayman Islands, Bermuda, Montserrat and Gibraltar. The 2007 figures have been estimated from the 2006 projections, as no updated information has been made available. An MSc project to calculate LULUCF net emissions/removals for the OTs and CDs was undertaken during 2007 (Ruddock 2007). The availability of data for the different OTs and CDs is very variable, so that emission estimates can only be made for the Isle of Man, Guernsey, Jersey and the Falkland Islands. These four comprise over 95% of the area in all the OTs and CDs. Gibraltar wished to produce their own inventory: their LULUCF net emissions/removals are likely to be extremely small, given the size of the country (6km2), and will have little impact on overall numbers. A lack of suitable data for the Caribbean territories (discussed in the 1990-2006 NIR) makes it impossible to create inventories for them at the present time. Information on the area of each IPCC land category, dominant management practices, land use change, soil types and climate types were compiled for each OT/CD from statistics and personal communications from their government departments and global land/soil cover databases. This allowed Tier 1 level inventories to be constructed for the four OT/CDs already mentioned, and a Tier 3 approach for Forest Land on the Isle of Man (using the C-Flow model also used for the UK). The estimates have high uncertainty and probably do not capture all relevant activities, in particular land use change to Settlement from land uses other than Forest Land (there are no default IPCC methods for these transitions). Waste (CRF sector 6) Solid Waste Disposal on Land (6A) Degradable Organic Carbon (DOC) and Fraction Dissimilated (DOCF) UK values for DOC and DOCf are based on an emissions model developed by LQM (2003) that uses updated degradable carbon input parameters with values based on well-documented US research for the USEPAs life-cycle programme (Barlaz et al., 1997). The data taken from this report relate to those waste fractions most representative of UK municipal waste, on the basis that the biochemistry of individual fractions of waste in the US will be comparable to the same fractions in the UK. This has been adapted to UK conditions and incorporated into (1) the Environment Agencys WISARD life cycle assessment model (WS Atkins, 2000); (2) the HELGA framework model (Gregory et al., 1999) and (3) GasSim (Environment Agency, 2002). Cellulose and hemi-cellulose are known to make up approximately 91% of the degradable fraction, whilst other potential degradable fractions which may have a small contribution (such as proteins and lipids) are ignored. The amount of degradable carbon that produces landfill gas is determined using the mass (expressed on a percentage dry weight basis) and degradability (expressed as a percentage decomposition) of cellulose and hemi-cellulose using data provided by Barlaz et al. (1997). The input values for these parameters are provided in Tables A3.8.1 and A3.8.2 below for each of the waste fractions for both municipal (MSW) and commercial and industrial (C&I) waste categories, respectively. Also included are the proportions of individual waste streams that are considered to be rapidly, moderately or slowly degradable. The moisture content of the components of the waste is derived from The National Household Waste Analysis Project (1994). This detailed report provides the range of moisture contents analysed for each of the fractions of waste collected and sampled. These fractions came from a number of different waste collection rounds, across the UK, representing different types of communities. The waste is analysed in its as collected form, which is then sorted and chemically analysed as separate fractions. The report also gives the averages used in the model. More recent waste arisings data collated by the Devolved Administrations, not available at the time of LQM (2003), do not include chemical analysis data. These data are used within the model to determine the amount of degradable carbon that decays at the relevant decay rate. This process requires complete disaggregation of the waste streams into their component parts, allocation of degradability and rate of decomposition to each component and hence the application of the IPCC model approach at this disaggregated level. Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 1 Waste degradable carbon model parameters for MSW waste Waste categoryFractionMoisture contentCelluloseHemi-celluloseDOC DOC Decomposition (DOCf)Readily DegradableModerately DegradableSlowly DegradableInert(%)(% Dry waste)(% Dry waste)(% Dry waste)(% Wet waste)(% Dry waste)Paper and card0257503061.29.131.2421.8761.8Dense plastics00010050000.000Film plastics (until 1995)000100300000.000Textiles00100025202017.7813.3350Misc. combustible (plus non-inert fines from 1995)01000020252522.2217.7850Misc. non-combustible (plus inert fines from 1995)00010050000.000Putrescible1000006525.71317.206.0262Composted putrescibles050500300.70.70.620.4457Glass00010050000.000Ferrous metal00010050000.000Non-ferrous metal and Al cans000100100000.000Non-inert fines10000040252522.2213.3350Inert fines00010050000.000Notes:1. DOC is Degradable Organic Carbon. 2. DOCf is the portion of DOC that is converted to landfill gas. Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 2 Waste degradable carbon model parameters for C & I waste Waste categoryFractionMoisture contentCelluloseHemi-celluloseDOC DOC Decomposition (DOCf)Readily DegradableModerately DegradableSlowly DegradableInert(%)(% Dry waste)(% Dry waste)(% Dry waste)(% Wet waste)(% Dry waste)Commercial155715133776837.3323.5285Paper and card0257503087.48.442.5829.8098General industrial waste154320223776837.3323.5285Food solids79100116555.47.227.829.7476Food effluent5050456555.47.227.829.7476Abattoir waste78100126555.47.227.829.7476Misc processes055902010108.897.1150Other waste1535351520252522.2217.7850Power station ash0001002000000Blast furnace and steel slag0001002000000Construction/demolition05590308.58.57.565.2957Sewage sludge10000070141412.443.7375Notes:1. DOC is Degradable Organic Carbon. . 2. DOCf is the portion of DOC that is converted to landfill gas. Flaring and Energy Recovery Flaring and energy recovery constitutes the method likely to reduce methane emissions from landfills by the largest amount, and was surveyed in 2002, as described below. It is estimated that in 2005 onwards 70% (Golders (2005)) of the total landfill gas generated in the UK was flared or utilised (Table 3.8.2). Gas Utilisation The gas utilisation data are based on comparison of information from the trade association, the Renewables Energy Association, formerly Biogas Association (Gaynor Hartnell, Pers. Comm. 2002) and current DTI figures. In addition, LQM (2003) included data on utilisation prior to the first round of the Non Fossil Fuel Obligation (NFFO) contracts (Richards and Aitchison, 1990). The first four NFFO rounds (NFFO 1-4) and the Scottish Renewables Order (SRO) round are all taken to be completed and operational schemes, since there are relatively few outstanding schemes still to be implemented. It is known that not all of the proposed early schemes were found to be economic, and no NI-NFFO (Northern Ireland-NFFO) schemes have progressed, so those known schemes have not been included in the total (Gaynor Hartnell, Pers. Comm. 2002). This approach, comparing the trade association and Government data sources, provides a reasonable correlation, and so LQM is confident in the accuracy of its estimates of current installed capacity. The latest round of NFFO (NFFO 5) has been implemented in the forecasting model over the period 2000 2005, to give a reasonable lead in time for these new projects. Various industry sources have indicated in confidence that some of the proposed NFFO 5 projects are now also considered uneconomic under NFFO. Some of these have definitely been abandoned, some have been surrendered and re-started under the new renewables order, and others are likely to follow this route. These figures are likely to have only a small uncertainty, as they are directly derived from power generation figures supplied by the industry and the Department of Trade and Industry. Flaring Information on flaring capacity was obtained through consultation with flare manufacturers. LQM (2003) collected information from all but one of the UK flare companies contacted. The data collected was divided into flares supplied for routine flaring and flares supplied as back-up to generation sets. The data produced demonstrates total flare capacity as opposed to the actual volumes of gas being flared in each year. There are difficulties in ascertaining the actual volumes of LFG burnt, as detailed records, if they exist at all, are held by individual site operators. It is rare to find a flare stack with a flow measurement. The operational capacity is derived by subtracting the back-up capacity from the total. LQMs total for generation back-up capacity remains at a fairly constant percentage of the installed generation capacity (around 60%), indicating that these figures are realistic. In the model, there is a further correction factor used in arriving at the final volume of gas flared each year, to take account of maintenance downtime (15%). In addition, it is assumed that since 1984 (i.e. three years after the first flare was commissioned) 7% of capacity in any given year is treated as replacement. This effectively gives the flare an expected 15-year operational lifetime. In 1990, the methane captured equates to 11% of the total generated, rising to 70% in 2005, averaged over the UK (Table 3.8.3). The downtime and replacement figures are LQM assessments following inquiries made as part of the 2002 survey. The last input of gas utilisation data in the model is year 2005 and the last input of flare data is year 2002. Gas utilisation and flaring is assumed constant thereafter. Collection efficiency at any site is limited to 75%. Further work is still to be completed on flare and engine utilization at UK landfills, this research will be incorporated when published into the latest report and any amendments to the model will also be completed to provide a better picture for the future. Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 3 Amount of methane generated, captured, utilised, flared, oxidised and emitted. YearMass of waste landfilled (Mt)Methane generated (kt)Methane captured (kt)Methane captured (%)Methane Utilised (kt)Methane Utilised (%)Methane Flared (kt)Methane Flared (%)Residual methane oxidisedResidual methane oxidised (%)Methane emitted (kt)MSWC&ICombined waste streams(kt)MSW199018.1981.83100.02294732211491.672729.242638.912363199118.8481.77100.61302443614662.1837012.252598.562329199219.4781.72101.193098576191103.5646515.022528.142270199320.0981.66101.763170712221364.2957618.182467.752212199420.7181.61102.323240832261635.0366920.642417.432167199523.8381.56105.393294962292096.3575222.852337.082099199624.7678.17102.9333301077322557.6782224.682256.762027199726.1472.8699.00335212793837811.2990126.862076.191866199825.9474.0199.95338914474345913.5598829.151945.731748199927.0371.9999.02342516494858717.15106130.991785.191598200027.5469.9897.51346117935263918.45115533.371674.821501200126.8767.9694.82349220395873721.12130137.261454.161308200227.1865.9493.13352321956277221.90142340.411333.771195200326.4165.9492.35355123866795626.92143140.291163.281048200425.4865.9491.433577249270105429.48143740.191093.03977200524.1965.9490.133600252870115131.99137838.271072.98964200621.6965.9487.633617254570115631.96139038.431072.96965200720.0665.9486.003631256171116031.95140238.601072.95963 Wastewater Handling (6B) Use of the 1996 Hobson Model within the UK GHG Inventory The NAEI estimate is based on the work of Hobson et al (1996) who estimated emissions of methane for the years 1990-95. Subsequent years are extrapolated on the basis of population. Sewage disposed to landfill is included in landfill emissions. The basic activity data are the throughput of sewage sludge through the public system. The estimates are based on the UK population connected to the public sewers and estimates of the amount of sewage per head generated. From 1995 onwards the per capita production is a projection (Hobson et al, 1996). The main source of sewage activity data is the UK Sewage Survey (DOE, 1993). Emissions are calculated by disaggregating the throughput of sewage into 14 different routes. The routes consist of different treatment processes each with specific emission factors. The treatment routes and emission factors are shown in TableA3.8.4. Industrial Wastewater Treatment Plants There is no separate estimate made of emissions from private wastewater treatment plants operated by companies prior to discharge to the public sewage system or rivers, as there is no available activity data for this source and it has historically been assumed to be a minor source. Where an IPPC-regulated industrial process includes an on-site water treatment works, any significant emission sources (point-source or fugitive) are required to be reported within their annual submission to UK environmental regulatory agencies, including emissions from their water treatment plant. Therefore, methane emissions from industrial wastewater treatment should be included within operator returns to the pollution inventories of the EA, SEPA and NIDoE, and therefore accounted for within the Industrial Process sector of the GHG Inventory. In practice it is not straightforward to ascertain the extent to which this is the case across different industry sectors. Within sector-specific guidance to plant operators on pollution inventory data preparation, emissions of methane from wastewater treatment are not highlighted as a common source to be considered (whereas in some guidance, wastewater treatment is singled out as a potentially significant source of NH3 and N2O emissions). Sludge Applications to Agricultural Land The Hobson model includes emissions of methane from sewage sludge applications to agricultural land, and these emissions are therefore included within sector 6B2, rather than within the agricultural sector as recommended in IPCC guidance. There is no double-counting of these emissions as methane emissions from sludge application to land are excluded from the agricultural inventory compiled by IGER. Sewage Treatment Systems Outside of the National Network The model does not take account for sewage treatment systems that are not connected to the national network of treatment works. The emissions are all determined on a population basis, using factors that pertain to mainstream treatment systems. Differences in emissions from alternative systems such as septic tanks are not considered, as it is assumed that the vast majority of the UK population is connected to the public wastewater treatment system. Design of Wastewater Treatment Systems in the UK Most UK wastewater treatment works comprise the following components as a minimum: Initial screening / grit removal; Primary settlement tanks, using simple sedimentation; and Secondary treatment (usually a biological process such as activated sludge systems & sedimentation or percolating filters). Many also have a tertiary treatment unit to complete waste-water filtration, remove target nutrients (such as nitrogen or phosphorus) or specific industrial pollutants, to polish the water as required prior to outputting treated water to watercourses. In each of the treatment phases, sewage sludge is produced and may be treated in a variety of ways, each with different methane emission characteristics, and these options are accounted for within the model. Emissions from Anaerobic Digestion The Hobson model includes calculations to account for different designs of anaerobic digesters, primary and secondary digestion phases, the utilisation of digester gas flaring, CHP and venting systems, and uses emission factors derived for each design type, which include consideration of fugitive losses of methane in each case. The dataset refers to plant survey data and emission factor research from the early 1990s, and so may not be fully representative of current emissions research, plant design and practice. Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 4: Specific Methane Emission Factors for Sludge Handling (kg CH4/Mg dry solids, Hobson et al (1996)) Sludge Handling SystemGravity Thickening1Long term storageAnaerobic Digestion2Agricultural LandLandfillAnaerobic digestion to agriculture0.721435Digestion, drying, agriculture0.721435Raw sludge, dried to agriculture0.7220Raw sludge, long term storage (3m), agriculture0.723620Raw sludge, dewatered to cake, to agriculture0.7220Digestion, to incinerator0.72143Raw sludge, to incinerator0.72Digestion , to landfill0.721430Compost, to agriculture0.725Lime raw sludge, to agriculture0.7220Raw Sludge , to landfill0.720Digestion , to sea disposal0.72143Raw sludge to sea disposal0.72Digestion to beneficial use (e.g. land reclamation)0.721435An emission factor of 1 kg/tonne is used for gravity thickening. Around 72% of sludge is gravity thickened hence an aggregate factor of 0.72 kg CH4/Mg is used. The factor refers to methane production, however it is assumed that 121.5 kg CH4/Mg is recovered or flared Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 5: Time-Series of Methane Emission Factors for Emissions from Wastewater Handling, based on Population (kt CH4 / million people) YearCH4 Emission (kt)CH4 EF (kt CH4/ million people)199033.380.583199131.270.544199234.760.604199334.460.597199435.960.622199534.330.593199635.270.608199736.210.623199837.150.637199936.020.616200036.890.629200137.130.628200237.350.630200337.580.631200437.800.632200538.030.632200638.160.630200738.290.628 Nitrous oxide emissions from the treatment of human sewage are based on the IPCC (1997c) default methodology. The most recent average protein consumption per person is based on the Expenditure and Food Survey (Defra, 2008); see TableA3.8.6. Between 1996 and 1997 there is a step change in the reported data. This is because Defra revised their publication (formally National Food Survey) and in doing so revised the method used to calculate protein consumption. The new method only provides data back to 1997 and so a step change occurs. Table A  STYLEREF 2 \s 3.8. SEQ Table_A \* ARABIC \s 2 6: Time-series of per capita protein consumptions (kg/person/yr) YearProtein consumption (kg/person/yr)199023.0199122.7199222.9199322.7199424.6199523.0199623.7199726.3199826.0199925.0200025.7200126.3200226.0200326.0200425.9200527.8200626.3200726.3 Waste Incineration (6C) This source category covers the incineration of wastes, excluding waste-to-energy facilities. For the UK, this means that all MSW incineration is excluded, and is reported under CRF source category 1A instead. Emission factors for the municipal solid waste incinerated, and the treatment of biogenic emissions from MSW incineration, can be found the section Energy Industries, in this Annex. Emissions From the UKs Crown Dependencies and Overseas Territories Emissions from the UK Overseas Territories (OTs) were first included in the UK Greenhouse Gas Inventory in the 1990-2004 inventory, published in 2006. Emissions from fuel use the UK Crown Dependencies (CDs), however, have always been included in the UK inventory because their fuel use is included in the UK energy statistics, produced by BERR. Emissions from non-fuel sources were introduced into the inventory at the same time as the estimates for the OTs. This year, the database structure and method used for estimating emissions from the Overseas Territories and Crown Dependencies has been updated and improved. This has allowed the methods and emission factors used to be more consistent with those used for the UK inventory, and also allows more flexibility in reporting, for example it allows the correct coverage for the EUMM (UK and Gibraltar only) to be easily extracted from the database. A summary of the new method and improvements is as follows: All emission sources from the Overseas Territories and Crown Dependencies were identified, and where possible assigned the same Source codes and activity codes used for the UK inventory sources. Each OT and CD (and the UK) was assigned a Territory Code, which identifies where the emissions originate. For the Crown Dependencies fuel use, the UK spreadsheets were modified to include separate data for each of the Crown Dependencies. These fuel totals were then subtracted from the totals from DUKES to maintain the overall fuel balance (DUKES total = UK + CDs). Where the emissions are calculated using a simple activity multiplied by emission factor calculation, and there is no information available about the likely emission factors in the OTs or CDs, only emission factors for the UK were entered into the database. The database then derives emission factors for the OTs and CDs, where corresponding activity data exist (i.e. the emission factors from the UK are applied to the OT or CD activity data). If the emissions in the OTs or CDs are based on proxy data, or the UK emission factors are known to be not appropriate, then emission factors for the OTs and CDs are entered into the database, with the appropriate territory code. This has led to a number of recalculations of the data, since the UKs emissions factors for each year are applied to the majority of sources, whereas in previous inventory versions, a fixed emission factor for each source (taken from the 2003 UK GHGi) was applied across all years. In addition, the treatment of fuel use for the Crown Dependencies has led to a reallocation of fuels between the power stations and industrial combustion sectors. This is because the estimates of fuels used in power stations in the inventory are known to cover only power stations in the UK, whereas the DUKES final consumption also includes Crown Dependencies. Therefore, in order to maintain the fuel balance with DUKES, and to retain the accuracy of the UK power station emissions estimates, fuel used for power generation in the CDs has been reallocated from the Other Industry sector to power stations. These changes have also meant that indirect greenhouse gas emissions from the Overseas Territories are also included in the inventory. In addition, the improvements also mean that the database now includes activity data for fuels used in the OTs and CDs, which allows reporting in the CRF to be more transparent. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 1: Summary of category allocations in the CRF tables and the NIR SourceCategory in CRFCategory in NIRNotesPower stations (OTs and CDs)1A1a: Public Electricity and Heat Production (Other Fuels) 1A1aThe activity data and emissions data in the CRF for the relevant fuels now includes the component of emissions from the OTs and CDs. In previous years, the OT emissions were included as a separate estimate and the CDs were assumed to be part of the UK total (fuels used for power generation in the CDs has been reallocated from the UKs Other Industry sector, as explained above).Domestic Aviation (CDs only)1A3a: Aviation1A3aFlights between the UK and the CDs are classified as domesticIndustrial Combustion (OTs and CDs)1A2f: Other - OT Industrial Combustion 1A2fThe activity data and emissions data in the CRF for the relevant fuels now includes the component of emissions from the OTs and CDs. In previous years, the OT emissions were included as a separate estimate and the CDs were assumed to be part of the UK total.Road Transport (OTs and CDs)1A3b: Road Transport (Other Fuels)1A3bThe activity data and emissions data in the CRF for the relevant fuels now includes the component of emissions from the OTs and CDs. In previous years, the OT emissions were included as a separate estimate and the CDs were assumed to be part of the UK total. The assumption that the CDs were included as part of the UK total was only true for CO2 for other GHGs, the emissions are calculated based on vkm and therefore these emissions are additional for this inventory.Memo items: Aviation (OTs only)Footnoted1C1aIt was not possible to include emissions from aviation under 1C1a in the CRF because there was no option to create another fuel category, and adding the OT emissions to the UK figures would affect the IEFs. Emissions are therefore displayed as a footnote. This does not affect the national total.Residential and Commercial Combustion (OTs and CDs)1A4a and 1A4b1A4a and 1A4bThe activity data and emissions data in the CRF for the relevant fuels now includes the component of emissions from the OTs and CDs. In previous years, the OT emissions were included as a separate estimate and the CDs were assumed to be part of the UK total.OT and CD F gases2F9: Other - OT and CD F Gas Emissions2FThis has been included in the CRF as a separate category for all F Gas emissions from the OTs and CDs.OT and CD Enteric Fermentation4A10: Other - OTs and CDs All LivestockRelevant animal categories within 4AA separate category for all livestock in the OTs and CDs is used.OT and CD Manure Management4G: Other - OT and CD Emissions from Manure ManagementRelevant categories within 4BIt was not possible to introduce a new category in which to put emissions of N2O from manure from the OTs and CDs into Sector 4B. A separate category was therefore included in Sector 4G - Other.OT and CD LULUCF Emissions5G: Other7Total net LULUCF emissions from the OTs and CDs are included in sector 7 as it was not possible to report these emissions as a separate total within sector 5 in the CRF.OT and CD Landfill6A3: Other - OT and CD Landfill Emissions6AThis has been included in the CRF as a separate category under 6A.OT and CD Sewage Treatment6B3: Other - OT and CD Sewage Treatment (all)6BThis has been included in the CRF as a separate category under 6B.OT and CD Waste Incineration6C3: Other - OT and CD MSW Incineration6CThis has been included in the CRF as a separate category under 6C. GHG emissions are included from those UK Crown Dependencies (CDs) and Overseas Territories (OTs) which have joined the UKs instruments of ratification to the UNFCCC and the Kyoto Protocol. The relevant CDs and OTs are: Guernsey; Jersey; The Isle of Man; The Falkland Islands; The Cayman Islands; Bermuda; Montserrat; and Gibraltar. Separate CRF tables have also been submitted to the EU to include only the parts of the UK that are also members of the EU. These are the UK itself, and Gibraltar. Country specific data have been sought to estimate emissions as accurately as possible. In general the data were requested by questionnaire asking for information on fuel use, the vehicle fleet, shipping movements, aircraft, livestock numbers and waste treatment. In some cases (such as for the Channel Islands) much of the data were readily available from government statistical departments, and the inventory already included all emissions from energy use in the CDs because of the coverage of the Digest of UK Energy Statistics. In these cases it was possible make estimates of the emissions using the same methodology as used for the UK inventory. There were some difficulties obtaining information for some sectors in some of the OTs to estimate emissions using the same methods applied to the existing UK GHG inventory. Modifications were therefore made to the existing methods and surrogate data were used as necessary; this is discussed in the sections below. For sectors such as waste treatment in some of the Overseas Territories, no data were available and it was not possible to make any estimates of emissions. Emissions of GHGs from fuel combustion in IPCC Sector1 (but not waste incineration) were already included in the GHG inventory from the CDs, but emissions from other sources from these CDs were not previously estimated or included before 2004. In this inventory, the database structure has been changed to allow emissions from the CDs to be reported separately and easily removed from the UK total. A summary of the emissions of the direct GHGs from the UKs Crown Dependencies and Overseas Territories are given in TableA3.9.3 and TableA3.9.5. Crown Dependencies: the Channel Islands and the Isle of Man The methods used to estimate emissions from the Channel Islands and the Isle of Man are summarised in TableA3.9.2. These data are supplied by energy statisticians and other government officials and are thought to be of good quality. Emissions are summarised in Table A3.9.3. Although the fuel used in the Crown Dependencies is included in the total energy statistics for the UK, as published in DUKES, the estimates made of the fuel use in the individual CDs has been used to modify the UK fuel balance, to allow separate reporting of emissions from the CDs. The total fuel used in the UK plus the Crown Dependencies matches the totals published in DUKES. Jersey The largest sources of CO2 emissions for Jersey in 2007 are the commercial and domestic sectors and road transport. Emissions from power generation make up 17% of total CO2 emissions, which is an increase compared with earlier years since the proportion of electricity imported from France has decreased. Agricultural activity is the main source of methane emissions, accounting for around 75% - 80% of total methane emissions across the time series. Waste is incinerated, and so there are no methane emissions from landfill sites. These emissions were estimated using emission factors from the GHGi. N2O emissions only make up a small proportion of the total emissions in Jersey. Fgas emissions are based on UK emissions, scaled using proxy statistics such as population or GDP. There are no emissions from industrial sources and so the Fgas emissions show a similar trend to the UK emissions from non-industrial sources. Estimates of emissions from fuel combustion are based on real data supplied for fuel use and vehicle movements, and we consider the uncertainty on these emissions to be low and probably similar in magnitude to the uncertainties on UK emissions from these sources. Emissions from livestock were based on an incomplete time series, and rely on extrapolated figures, introducing greater uncertainty for this sector. Emissions from sewage treatment are based on UK per capita emission factors, which may not be an accurate representation of the technology in use for Jersey. Net emissions of CO2 from LULUCF were calculated for the 1990 to 2006 inventory. These estimates were not updated for the current inventory, and emissions in 2007 have been rolled from 2006. The Isle of Man The main sources of carbon emissions in the Isle of Man are road transport and power generation, which together contribute 55% to total CO2 emissions. Residential and commercial combustion are also significant sources, accounting for a further 29% of total emissions. Some minor industrial sources of combustion emissions also exist - the sewage treatment plant and quarries. The most significant methane source is agriculture, which accounted for 97% of methane emissions in 2007. The only other significant source was waste treatment and disposal to landfill, until the incinerator replaced the landfill sites. N2O emissions arise mainly from agricultural practices livestock manure management. No estimate has been made of N2O from agricultural soils. The emissions for fuel combustion and transportation sources for the majority of the time series are based on real data and emission factors sourced from the existing GHG inventory, and so estimates have a fairly low uncertainty. However, for later years, data has not always been obtained and therefore emissions are based on extrapolated data, which makes it much more uncertain. Further data has been received from the Isle of Man after the 1990-2007 Inventory was compiled and this will be included in the 1990 2008 Inventory. Emissions from landfill, sewage treatment, and Fgas use rely on UK data scaled to population and therefore assume similar characteristics and usage patterns to the UK. Guernsey The largest single source of CO2 in 2007 was road transport. Power stations accounted for around 19% of CO2 emissions showing a decrease from the previous year. 2006 emissions were much higher than 2005, going against the trend of decreasing emissions that had been observed reflecting changes in the amount of electricity imported from France. The largest methane source is from waste disposed to landfill. Major improvements were made to these estimates for the 2008 Greenhouse Gas Inventory. The estimates of emissions from fuel consumption for Guernsey are based on a number of assumptions. Fuel consumption figures for power generation were calculated based on electricity consumption figures, total fuel imports, and fuel consumption data for a few years taken from the power station statistical report. Domestic and commercial combustion figures also needed to be separated out from the total imports, and split into different fuel types based on data given in a previous inventory for Guernsey. Shipping and agriculture figures are based on incomplete time series and the missing data have been interpolated or extrapolated as necessary, and are therefore subject to greater uncertainty. The improvements to emissions from landfill, and also aviation (see Section 3.9.1.2) have helped to decrease the uncertainties associated with these sources. In addition to the improvements outlined above, emissions and removals from LULUCF have been estimated this year. The LULUCF sector in Guernsey is a net source when calculated using Tier 1 methods and stable over time. This is because there is very limited land use change on Guernsey and most emissions come from agricultural liming. Land cover is only available for 1999 and 2006 (a constant rate of change is assumed between these points). Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 2: Isle of Man, Guernsey and Jersey Summary of Methodologies SectorSource nameActivity dataEmission factorsNotes1Energy - power stations and small combustion sourcesFuel use data supplied1990-2007 GHGi emission factors used for all sourcesIn some cases time series were incomplete - other years were based on extrapolated/interpolated values. Fuel imports for Guernsey were not always broken down into different fuel classes - this information was derived from data in a previous report (2002).Energy - road transportTime series of vehicle numbers and fuel consumption supplied, age profile and vehicle km data calculated using UK figuresFactors for vehicle types based on UK figuresBreakdown of vehicle types not always detailed, some fuel use is based on extrapolated figures. Assumes the same vehicle age profile as the UK.Energy - other mobile sourcesAircraft and shipping movements supplied, and some data about off road machineryAircraft emissions taken from the UK aviation model, shipping from 2003/2002 NAEIIncomplete datasets were supplied in many cases - the time series were completed based on passenger number data or interpolated values. 2Industrial processesPopulation, GDPSome sources assumed zero. Per capita emission factors based on UK emissions, where appropriate.Based on the assumption that activities such as MDI use and refrigeration will be similar to the UK, whilst industrial sources will not be present. Industrial process emissions are assumed to be zero.3Solvent usePopulation, GDP, vehicle and housing numbersPer capita (or similar) emission factors based on UK emissionsAssumes that solvent use for activities such as car repair, newspaper printing, and domestic painting will follow similar patterns to the UK, whilst the more industrial uses will be zero.4AgricultureLivestock statistics suppliedAmmonia and N2O from manure management are based on a time series of UK emissions. Methane emissions based on IPCC guidelinesAmmonia and N2O emissions assume similar farm management practices as for the UK. Some of the farming statistics time series were incomplete - other years were based on interpolated values5Land use change and forestryLand use and forest planting dataEmissions and removals have been calculated using a Tier 1 method in most cases, with a Tier 3 method for forestry in the Isle of Man also being used.Differing amounts of data were supplied for each CD, which has meant that the same methodologies could not be used for all. 6Waste MSWLandfill estimates based on population or waste amounts, incineration estimates based on limited data on the amount of waste incineratedTime series of UK per capita emission factors used for land fill sites, improved emission model for GuernseyEstimates of amounts of incinerated waste are based on limited data and interpolated values. The emission model that has been implemented for Guernsey has improved estimates for this source.Waste - Sewage treatmentPopulationTime series of UK per capita emission factorsAssumes the same sewage treatment techniques as for the UK. In practice, treatment not thought to be as comprehensive as UK, but no details available. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 3: Isle of Man, Guernsey and Jersey Emissions of Direct GHGs (Mt CO2 equivalent) Sector1990199119921993199419951996199719981999200020012002200320042005200620071. Energy1.381.451.511.481.531.591.711.741.821.751.651.361.341.291.301.311.331.352. Industrial Processes0.000.000.000.000.000.010.010.020.020.020.030.030.030.030.030.030.030.033. Solvent and Other Products Use4. Agriculture0.140.140.140.130.140.140.130.140.140.140.140.130.140.100.100.100.120.105. Land Use, Land Use Change and Forestry0.010.010.010.010.010.010.010.010.010.010.010.010.010.020.010.030.030.036. Waste0.140.140.140.130.130.130.130.130.130.130.090.090.070.070.040.060.060.067. OtherNONONONONONONONONONONONONONONONONOTotal1.661.741.811.761.811.882.002.042.132.061.911.611.581.511.491.521.571.57 Overseas Territories: Bermuda, Falklands Islands, Montserrat, the Cayman Islands and Gibraltar TableA3.9.4 summarises the methods used to estimate emissions from the Falklands Islands, Montserrat and the Cayman Islands. Emissions from some sources are not estimated due to lack of data. Emissions are summarised in Table A3.9.5. The government of Bermuda has prepared its own GHG inventory estimates and methodological report, so TableA3.9.4 only refers to the methodologies used for Falkland Islands, Montserrat and the Cayman Islands. TableA3.9.7 does, however, include emissions estimates for Bermuda, and further information has been provided (after the compilation of the 1990-2007 Inventory) from Bermuda to update and improve these emission estimates. These improvements will be made in the 1990-2008 Inventory. Falklands Islands The most significant source of CO2 is domestic heating. There are no industrial combustion sources. Estimates have been made for aviation, but no data were available to calculate emissions from shipping or off road machinery. Methane emissions are mostly from agriculture there are around 500,000 sheep on the island. Agriculture is also a major source of N2O. Methane emissions from waste disposal are small, as waste is burnt. Sewage is disposed of to sea. The LULUCF sector in the Falkland Islands is a net source (stable 1990-2000 and increasing to 2005) when calculated using Tier 1 methods. This is due to the requirement to estimate emissions from organic soil under Cropland. The Cropland area in the Falklands is very small but is the only active variable in the Inventory when Tier 1 methods are used. Consistent information on land use in the Falklands is available since 1984. There is very little land use change on the islands (93% of their area is natural Grassland). The estimates of emissions from power generation are based on a complete time series of annual fuel consumptions, and can therefore be considered fairly reliable. Domestic fuel consumption statistics, however, were only provided for six years, so the time series was extrapolated back to 1990, and forwards to 2007 based on population statistics. Vehicle numbers were only provided for one year, so this time series was also generated based on population statistics. We consider the uncertainties associated with emissions from domestic fuel consumption and transport to be high, with the greatest uncertainties earlier in the time series. Montserrat Only limited activity data were supplied for Montserrat, so it was not possible to make estimates of GHG emissions from all source sectors. In addition half of the island is currently uninhabitable due to recent volcanic activity. Nevertheless a reliable time series of the islands population was supplied, and it was possible to use this to extend some of the time series of available emission estimates. Estimates have been made for power generation, residential combustion, aviation, road transport and Fgases. No information was supplied about shipping. There was also no information supplied about the disposal of waste, treatment of sewage, or livestock numbers. Since emissions from different waste disposal and sewage treatment techniques vary greatly, there is no way of calculating a reliable estimate based on any surrogate statistics. It is also difficult to predict livestock figures without any indication of the importance of agriculture to the island. It has also not been possible to calculate emissions and removals from LULUCF activities for Montserrat. Of the sectors calculated, road transport is the most important. Only fuel consumption figures were supplied for this sector and emissions of non-CO2 greenhouse gases are therefore quite uncertain. It is assumed that emissions from some off road transport and machinery will be included in the figure calculated for the road transport sector. Power generation is the other major source. Cayman Islands This year, a more detailed data set has been received from the Cayman Islands in order to calculate a more comprehensive inventory for this Overseas Territory. Fuel import data has been received, and fuel use for the power station, together with livestock statistics and more qualitative information about the likely emission sources on the Islands. The largest CO2 emission source is power generation, accounting for 41% of emissions. There are also significant industrial combustion emissions from the water desalination plant and the cement industry. Agriculture is not a large source of emissions, and therefore methane and N2O emissions are small. No data were available to estimate LULUCF emissions from the Cayman Islands. The new data provided has led to large improvements in the inventory for the Cayman Islands. However, in some cases assumptions had to be made to fill gaps in the data, or where the data were inconsistent. For example, the total fuel imports data was inclusive of the power station fuel use, however in some years the reported consumption at the power station was greater than the total fuel imports. Bermuda The Bermuda Department for Environmental Protection has produced its own greenhouse gas inventory, compiled according to the IPCC guidelines. Calculated emissions and the methodology used for Bermuda are detailed in Bermudas Greenhouse Gas Inventory Technical Report 1990-2000 (the Department of Environmental Protection, Government of Bermuda). An estimate of emissions from waste incineration (excluded from Bermudas report) has also been made based on UK emission factors, and statistics contained in Bermudas report on the amount of waste generated per person per day. This report is now becoming very out of date, and therefore information has been requested from Bermuda to update and improve this inventory. The data requested have now been received and will be incorporated into the 1990-2008 inventory. The major sources for carbon are road transport and power generation. Emissions from landfill were the main source of methane in 1990, but waste is now disposed of by incineration. N2O emissions arise mainly from sewage treatment. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 4: Cayman Islands, Falklands Islands and Montserrat Methodology (for estimates of carbon, CH4 and N2O) SectorSource nameActivity dataEmission factorsNotes1Energy - power stations and small combustion sourcesFuel use data supplied1990-2007 Emission factors from the UK GHGiFuel data in most cases was only supplied for the latter part of the time series. Extrapolated figures based on population trends have been used to calculate fuel consumption for earlier years. Energy - road transportVehicle numbers and fuel use supplied for the Falkland Islands, vehicle numbers and vehicle kilometres and fuel use for the Cayman Islands, fuel use for Montserrat.Factors for vehicle types based on UK figuresVehicle numbers have only been supplied for one year (time series are based on population), and the age profiles are based on UK figures - which may not be appropriate. Emissions for Montserrat are subject to a greater degree of uncertainty as there is no information about vehicle types or numbers.Energy - other mobile sourcesAircraft movements supplied for FI and Montserrat.EMEP/CORINAIR factorsIt has not been possible to make any estimates of emissions from shipping activities for any of these - no information was supplied, and the use of any surrogate statistics would not be suitable for this source.2Industrial processesPopulation, GDPSome sources assumed zero. Per capita emission factors based on UK/Gibraltar emissions.Assumes activities such as aerosol use and refrigeration will be similar to the UK. In practice, this is unlikely, but there is no other data available. The Cayman Island estimates were based on figures calculated for Gibraltar rather than for the UK - it was assumed that trends in the use of air conditioning etc would be similar.5Land use change and forestryLand use dataTier 1 dataData were only available to estimate emissions from the Falklands.6Waste - MSWTonnes of waste incinerated (Falkland Islands), NE for Montserrat and Cayman Islands, waste generation (Bermuda)US EPA factors for the open burning of municipal refuse, NAEI factors for clinical waste incineration and MSW incineration in BermudaInformation on the amount of waste incinerated was limited. No information about the type of waste treatment was available for Montserrat or the Cayman Islands.Waste - Sewage treatmentNO (Falkland Islands), NE (Cayman Islands ands Montserrat)Sewage from the Falkland Islands is disposed of to sea. Emissions Not Estimated (NE) for the Cayman Islands and Montserrat, as no information was available. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 5: Cayman Islands, Falklands Islands, Bermuda and Montserrat Emissions of Direct GHGs (Mt CO2 equivalent) Sector1990199119921993199419951996199719981999200020012002200320042005200620071. Energy1.121.151.171.211.251.281.281.331.421.431.461.541.541.581.651.661.741.812. Industrial Processes0.000.000.000.000.000.010.010.010.010.020.020.020.020.020.020.020.020.023. Solvent and Other Products Use0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.004. Agriculture0.170.170.170.170.170.170.160.170.160.160.170.170.160.150.150.140.140.145. Land Use, Land Use Change and Forestry0.010.010.010.010.010.010.010.010.010.010.010.010.010.020.010.030.030.036. Waste0.070.070.070.070.070.030.030.030.030.030.030.030.030.030.030.030.030.037. Other0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.00Total1.381.401.421.461.501.491.491.551.641.651.681.761.761.811.871.881.962.03 Gibraltar Emissions A greenhouse gas inventory forGibraltar has been created which contains annual emission estimates from1990 to2007 inclusive and emissions for the Base Year. The year 1995 has been chosen as the Base Year for the fluorinated gases, in agreement with the year the UK has chosen, and in accordance with Article 3(8) of the Kyoto Protocol. Gibraltar made the decision to join the UKs instrument of ratification of the Kyoto Protocol in 2006. Gibraltar already reports emissions under other international agreements. During the compilation of the Gibraltar GHG inventory, steps have been taken to ensure the existing Gibraltar inventories and the GHG inventory share common activity data where appropriate. Data specific to Gibraltar have been collected to estimate emissions as accurately as possible. In general the data were requested by questionnaire asking for information on fuel use, the vehicle fleet, shipping movements, aircraft, livestock numbers and waste treatment. Communications between the Gibraltar Environmental Agency and other companies is extremely good, allowing the acquisition of reliable data relating to the larger emission sources. The Gibraltar Environmental Agency was able to provide information from the government of Gibraltar statistics office, which holds much information relating to several source sectors. However, there are laws in Gibraltar restricting the data available from the Government statistics department. In general these were introduced to protect commercially sensitive information, which is more likely to occur in smaller administrations. For example it is not possible to obtain information on petrol sales from the eight petrol stations on Gibraltar without special dispensation. However, it is possible to obtain information on services that have no direct competitors (and hence the information is not regarded as being commercially sensitive). There were some difficulties obtaining information for some sectors to estimate emissions using the same methods applied to the existing UK GHG inventory. Modifications were therefore made to the existing methods and surrogate data were used as necessary; this is discussed in the sections below. Where possible, emissions were estimated using same methods used in the UK inventory. Emission factors for most sources are taken from the NAEI, to be consistent with the UK GHG inventory. Emissions from aircraft were calculated using default factors from the EMEP/CORINAIR guidebook, since the information available about aircraft movements from Gibraltar was limited. Whilst the data availability was regarded as good for an administrative area the size of Gibraltar, there were a number of sources for which detailed activity data was not available. In these cases expert judgement was required to enable an emission estimate to be obtained. Table A3.9.6 summarises the methodologies used to produce emission estimates for Gibraltar. In addition, no further data were provided to update the inventory to 2007. Some recalculations have occurred to the historic estimates due to the database changes, which means that the emissions are now calculated using up to date emission factors from the UK GHGI. Emissions from LULUCF have not been estimated from Gibraltar but are believed to be very small. Emissions from military activities in Gibraltar have been excluded from the totals. This is because the fuel used for these activities is likely to be sourced from the UK, and therefore to include emissions in the Gibraltar inventory would result in a double-count. All shipping and aviation emissions are currently classified as international, on the basis that Gibraltar has only one port and one airport. A summary of the emissions of the direct GHGs from Gibraltar is given in Table A3.9.7. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 6: Summary of methodologies used to estimate emissions from Gibraltar SectorSource nameActivity dataEmission factorsNotes1Energy - power stations, domestic, and small combustion sourcesFuel use data supplied for the three power stations. No activity data available for domestic, commercial and institutional combustion and so estimates made. Fuel use available for industrial combustion.Emission factors from the 1990 2007 GHGIIn some cases time series were incomplete - other years were based on extrapolated (on population)/interpolated values.Energy - road transportTime series of vehicle numbers and typical annual vehicle km per car, age profile calculated using UK figures.Factors for vehicle types based on UK figures.Breakdown of vehicle types not always detailed, some fuel use is based on extrapolated figures. Assumes the same vehicle age profile as the UK.Energy - other mobile sourcesAircraft and shipping movements suppliedAircraft factors taken from EMEP/CORINAIR, shipping from 2003/2002 NAEI.Incomplete datasets were supplied in many cases - the time series were completed based on passenger number data or interpolated values.2Industrial processesNo industrial processes identified with GHG emissions. Emissions of F-gases from air conditioning units are included in this sector.Per capita (or similar) emission factors based on UK emissions.Estimates of HFCs from air conditioning were based on percentages of homes, cars etc using the equipment, provided by the Environmental Agency.4AgricultureNo commercial agricultural activity. No emissions from this sector.5Land use change and forestryEmissions Not Estimated, as insufficient data are available. These emissions are likely to be negligible.6Waste - MSWIncineration estimates based on limited data on the amount of waste incinerated up to 2001. After2001, waste transported to Spain to be land filled.Emission factors taken from 1990-2007 GHGIEstimates of waste incinerated between 1990 and 1993 are based on extrapolated values. Data for the remainder of the time series was provide. Emissions from this source are assumed zero after the closure of the incinerator in 2000.Waste - Sewage treatmentNo emissions from this sector; all sewage is piped directly out to sea, with no processing. Table A  STYLEREF 2 \s 3.9. SEQ Table_A \* ARABIC \s 2 7: Emissions of Direct GHGs (Mt CO2 equivalent) from Gibraltar Sector1990199119921993199419951996199719981999200020012002200320042005200620071. Energy0.170.180.190.160.170.170.170.170.180.190.190.200.200.200.210.220.220.222. Industrial Processes0.000.000.000.000.000.000.000.000.000.000.010.010.010.010.010.010.010.013. Solvent and Other Products Use0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.004. Agriculture0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.005. Land Use, Land Use Change and Forestry0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.006. Waste0.010.010.010.010.010.010.010.010.010.010.010.000.000.000.000.000.000.007. Other0.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.00Total0.180.190.190.170.180.180.180.190.190.200.210.200.200.210.220.230.230.22 ANNEX 4: Comparison of CO2 Reference and Sectoral Approaches This annex presents information about the Reference Approach calculations, and its comparison with the Sectoral Approach. Estimation of CO2 from the Reference Approach The UK greenhouse gas inventory uses the bottom-up (sectoral) approach based on the combustion of fuels in different economic sectors and estimates of non-combustion emissions from other known sectors to produce detailed sectoral inventories of the 10 pollutants. In addition, estimates are also provided of carbon dioxide emissions using the IPCC Reference Approach. This is a top down inventory calculated from national statistics on production, imports, exports and stock changes of crude oil, natural gas and solid fuels. It is based on a different set of statistics and methodology and produces estimates around between 1% lower to 3 % higher than the bottom-up approach when categories not included in the reference approach are removed from the sectoral approach estimate. Discrepancies between the IPCC Reference and Sectoral Approach The UK GHGI contains a number of sources not accounted for in the IPCC Reference Approach and so gives a higher estimate of CO2 emissions. The sources not included in the reference approach are: Land use change and forestry; Offshore flaring and well testing; Waste incineration; and Non-Fuel industrial processes. In principle the IPCC Reference Total can be compared with the IPCC Table 1A Total plus the emissions arising from fuel consumption in 1B1 Solid Fuel Transformation and Table 2 Industrial Processes (Iron and Steel and Ammonia Production). The IPCC Reference totals range between 1% lower to 3 % higher than the comparable bottom up totals. The IPCC Reference Approach is based on statistics of production, imports, exports and stock changes of fuels whilst the sectoral approach uses fuel consumption data. The two sets of statistics can be related using mass balances (see the publication Digest of UK Energy Statistics BERR, 2008), but these show that some fuel is unaccounted for. This fuel is reported in DUKES as statistical differences these differences consist of measurement errors and losses. The system of energy statistics operated by BERR aims to keep UK statistical differences (without normalisation) at less than 0.5% of energy supply, and generally manages to meet this target, not only for total supply but by fuel. Nevertheless a proportion of the difference between the Reference Approach and the sectoral totals will be accounted for by statistical differences, particularly for liquid fuels. The sectoral approach only includes emissions from the non-energy use of fuel where they can be specifically identified and estimated such as with fertilizer production and iron and steel production. The IPCC Reference approach implicitly treats the non-energy use of fuel as if it were combustion. A correction is then applied by deducting an estimate of carbon stored from non-energy fuel use. The carbon stored is estimated from an approximate procedure that does not identify specific processes. The result is that the IPCC Reference approach is based on a higher estimate of non-energy use emissions. The IPCC Reference Approach uses data on primary fuels such as crude oil and natural gas liquids, which are then corrected for imports, exports and stock changes of secondary fuels. Thus the estimates obtained will be highly dependent on the default carbon contents used for the primary fuels. The sectoral approach is based wholly on the consumption of secondary fuels where the carbon contents are known with greater certainty. In particular the carbon contents of the primary liquid fuels are likely to vary more than those of secondary fuels. Time series of differences in the IPCC Reference and Sectoral Inventories TableA4.3.1 shows the percentage differences between the IPCC Reference Approach and the National Approach. These percentages include a correction for the fact that a significant proportion of fuel consumption emissions occur in the 2C Metal Production and 2B1 Ammonia Production sectors. Table A  STYLEREF 2 \s 4.3. SEQ Table_A \* ARABIC \s 2 1: Modified comparison of the IPCC Reference Approach and the National Approach Year199019911992199319941995Percentage difference-1.4-0.10.80.30.52.0 Year199619971998199920002001Percentage difference0.2-0.10.71.31.51.1 Year200220032004200520062007Percentage difference0.60.11.00.82.32.0 ANNEX 5: Assessment of Completeness Assessment of completeness TableA5.1.1 shows sources of GHGs that are not estimated in the UK GHG inventory, and the reasons for those sources being omitted. This table is taken from the CRF; Table9(a). Table A  STYLEREF 2 \s 5.1. SEQ Table_A \* ARABIC \s 2 1: GHGs and sources not considered in the UK GHG inventory GHGCRF sectorSource/sink categoryReasonCO22. Industrial Processes2A5/6 Asphalt Roofing/PavingNo methodology available but considered negligibleCO23. Solvent and Other Product UseCarbon equivalent of solvent use not included in total - provided for informationCO25. Land-Use Change and Forestry5C1 Grassland remaining Grassland - Carbon stock change in living biomassEmissions believed smallCO22. Industrial Processes2A4 soda ash productionEmissions from fuels used in soda ash production are reported elsewhere. Carbon evolved from the initial calcination stage of the process is assumed to be entirely converted into soda ash and therefore not emittedCO25. Land-Use Change and Forestry5B2/5C1/5C2/5E Biomass burning by WildfiresMethodology being developed - believed smallN2O3. Solvent and Other Product Use3D Other AnaesthesiaActivity not readily available believed smallN2O5. Land-Use Change and Forestry5A1 Direct N2O emissions from N fertilisationNow included for new forests (5A2)N2O5. Land-Use Change and Forestry5A N2O emissions from drainage of soilsMethodology under considerationN2O5. Land-Use Change and Forestry5B2 N2O emissions from disturbance associated with LUC to CroplandMethodology under considerationN2O5. Land-Use Change and Forestry5B2/5C1/5C2/5E Biomass burning by WildfiresMethodology being developed - believed smallCH42. Industrial Processes2B1 Ammonia ProductionManufacturers do not report emission - believed negligibleCH42. Industrial Processes2C1 Iron and SteelEAF emission and flaring only estimated - methodology not available for other sourcesCH42. Industrial Processes2C2 FerroalloysMethodology not available but considered negligibleCH42. Industrial Processes2C3 AluminiumMethodology not available but considered negligibleCH45. Land-Use Change and Forestry5B2/5C1/5C2/5E Biomass burning by WildfiresMethodology being developed - believed smallCH46. Waste6B1 Industrial Waste WaterActivity data unavailable - most waste water treated in public system- believed smallCH46. Waste6B1 Industrial Waste WaterActivity data unavailable - most waste water treated in public system- believed smallPFC2. Industrial processes2F1 Refrigeration and air-conditioning equipmentData not available, but assumed negligibleSF62.Industrial Processes2C4. Aluminium FoundriesData not available, but assumed negligible ANNEX 6: Additional Information Quantitative Discussion of 2007 Inventory This Annex discusses the emission estimates made in the 1990-2007 Greenhouse Gas Inventory. Each IPCC sector is described in detail with significant points noted for each pollutant where appropriate. The tables show rounded percentages only. All calculations are based on IPCC categorisation. Energy Sector (1) Figure A6.1 and A6.2 show both emissions of direct and indirect Greenhouse Gases for the Energy sector (category 1) in the UK for the years 1990-2007. Emissions from direct greenhouse gases in this sector have declined 11% since 1990, with a decrease of 1.95% between 2006 and 2007 continuing this trend. Tables A6.1.1 to A6.1.4 summarise the changes observed through the time series for each pollutant, as well as the contribution the emissions make to both sector 1 and the overall emissions in the UK during 2007. Carbon Dioxide Analysing emissions by pollutant shows that 98% of total net CO2 emissions in 2007 came from the Energy sector (Table A6.1.4), making this sector by far the most important source of CO2 emissions in the UK. Overall, CO2 emissions from sector 1 have decreased by 8% since 1990 (Table A6.1.1) and have also shown a decrease of 1.8% between 2006 and 2007 (Table A6.1.2). Energy industries (category 1A1) were responsible for 39% of the sectors CO2 emissions in 2007 (Table A6.1.3). There has been an overall decline in emissions from this sector of 11% since 1990 (Table A6.1.1). Although recently relatively high gas prices have led to more coal being burnt, in general since the privatisation of the power industry in 1990, there has been a move away from coal and oil generation towards combined cycle gas turbines (CCGT) and nuclear power, the latter through greater availability. During this time there has been an increase in the amount of electricity generated but a decrease in CO2 emissions from Power stations (1A1a). This can be attributed to several reasons. Firstly, the greater efficiency of the CCGT stations compared with conventional stations around 49% as opposed to 36%. Secondly, the calorific value of natural gas per unit mass carbon is higher than that of coal and oil. Emissions from this sector showed a 2% decrease from 2006 to 2007, due to a significant decrease in the amount of coal used for electricity generation in 2007. Emissions of from category 1A2 Manufacturing Industries and Construction contributed 15% (Table A6.1.4) to overall net CO2 emissions in the UK in 2007. Since 1990, these emissions have declined by 20%, (Table A6.1.1) mostly as a result of a decline in the emissions from the Iron and steel industry. This sector has seen a significant decrease in coke, coal and fuel oil usage, with an increase occurring in the emissions from combustion of natural gas. Emissions of CO2 from 1A3 (Transport) have increased by 12% since 1990 (Table A6.1.1). In 2007, this sector contributed 25% (Table A6.1.4) to overall CO2 emissions within the UK. Emissions from transport are dominated by road transport (1A3b), which in 2007 contributed 93% to the total emissions from transport. Since 1990, emissions from road transport have increased by 11%. Emissions from domestic aviation have almost doubled since 1990, but has shown a decrease of 10% since 2005 despite an increase in the total number of km flown. This is because of a move to use more fuel efficient aeroplanes in 2006. Emissions of CO2 from 1A4 (Other) have decreased by 8% since 1990 (Table A6.1.1). During this period, residential emissions have decreased by 3% and emissions from the commercial/institutional subsector have decreased by 19%. Fuel consumption data shows a trend away from coal, coke, fuel oil and gas oil towards burning oil and natural gas usage. Emissions of CO2 from 1A5 (Fuel Combustion; Other), 1B1 (Fugitive Emissions from Fuels; Solid fuels) and 1B2 (Fugitive Emissions from Fuels; Oil and Natural Gas) all show decreases between 1990-2007, although they only contribute a small percentage towards emissions from the energy sector. Methane In 2007, 19% (see Table A6.1.4) of total methane emissions came from the energy sector, the majority (59%, Table A6.1.3) from fugitive emissions from oil and natural gas (1B2). Emissions from this category have decreased by 47% since 1990 (Table A6.1.1). Sources include leakage from the gas transmission and distribution system and offshore emissions. Estimates of leakage from the gas distribution system are based on leakage measurements made by National Grid UK together with data on their gas main replacement programme, and have declined since 1990 as old mains are replaced. The major sources of emissions from the offshore oil and gas industry are venting, fugitive emissions and loading and flaring from offshore platforms. Nitrous Oxide The energy sector accounted for 15% of total N2O emissions in the UK during 2007. Of this, a majority (31%, Table A6.1.3) arose from the transport sector (1A3). Between 1990 and 2007, emissions increased by 12% (Table A6.1.1). This is because of the increasing numbers of petrol driven cars fitted with three-way catalysts. These are used to reduce emissions of nitrogen oxides, carbon monoxide and non-methane volatile organic compounds. However, nitrous oxide is produced as a by-product and hence emissions from this sector have increased. The other major contribution towards N2O emissions within the energy sector comes from energy industries (1A1). Within this category, emissions from public electricity production have shown a 34% decrease, whilst emissions from petroleum refining have increased by 5%. Emissions from 1A1c (Manufacture of Solid Fuels and Other Energy Industries) have increased by 33% between 1990 and 2007. N2O emissions have decreased overall by 47% since 1990. Over this period the use of coal has decreased and the use of natural gas increased. Nitrogen Oxides In 2007, over 99% of NOx emissions in the UK came from the energy sector. Since 1990 emissions from this sector have decreased by 45% (Table A6.1.1), mostly as a result of abatement measures on power stations, three-way catalysts fitted to cars and stricter emission regulations on trucks. The main source of NOx emissions is transport: in 2007, emissions from transport contributed 41% (Table 6.1.4) to the total emissions of NOx in the UK, with 17% arising from road transport (1A3b). From 1970, emissions from transport increased (especially during the 1980s) and reached a peak in 1989 before falling by 50% (Table A6.1.1) since 1990. This reduction in emissions is due to the requirement since the early 1990s for new petrol cars to be fitted with three way catalysts and the further tightening up of emission standards on these and all types of new diesel vehicles over the last decade. Emissions from the energy industries (1A1) contributed 30% (Table A6.1.4) to total NOx emissions in the UK during 2007. Between 1990 and 2007, emissions from this sector decreased by 48% (Table A6.1.1). The main reason for this was a decrease in emissions from public electricity and heat (1A1a) of 53%. Since 1998 the electricity generators adopted a programme of progressively fitting low NOx burners to their 500 MWe coal fired units. Since 1990, further changes in the electricity supply industry such as the increased use of nuclear generation and the introduction of CCGT plant have resulted in additional reduction in NOx emissions. Emissions from Manufacturing, Industry and Construction (1A2) have fallen by 37% (Table A6.1.1) since 1990. In 2007, emissions from this sector contributed 17% (Table A6.1.4) to overall emissions of NOx. Over this period, the iron and steel sector has seen a move away from the use of coal, coke and fuel oil towards natural gas and gas oil usage. Carbon Monoxide Emissions of carbon monoxide from the energy sector contributed 90% (Table A6.1.4) to overall UK CO emissions in 2007. Of this, 45% of emissions (Table A6.1.3) occur from the transport sector. Since 1990, emissions from 1A3 have declined by 86% (Table A6.1.1), which is mainly because of the increased use of three way catalysts, although a proportion is a consequence of fuel switching in moving from petrol to diesel cars. Emissions from sector 1A2 contributed 25% (Table A6.1.4) to overall emissions of CO in 2007. Emissions from within this category mostly come from the Iron and Steel industry and from petrol use in off-road vehicles within the Manufacturing, industry and combustion sector. Non Methane Volatile Organic Compounds In 2007, 43% (Table A6.1.4) of non-methane volatile organic compound emissions came from the energy sector. Of these, the largest contribution arises from the fugitive emissions of oil and natural gas (1B2), which contributed 22% (Table A6.1.4) towards the overall UK emissions of NMVOCs in 2007. This includes emissions from gas leakage, which comprise around 10% of the total for the energy sector. Remaining emissions arise from oil transportation, refining, storage and offshore. Emissions from transport (1A3) contribute 10% (Table A6.1.4) to overall emissions of NMVOC in the UK in 2007. Since 1990, emissions from this sector have decreased by 89% (Table A6.1.1) due to the increased use of three way catalysts on petrol cars. Sulphur Dioxide 95% (Table A6.1.4) of emissions of sulphur dioxide came from the energy sector in 2007. 66% (Table A6.1.3) of these emissions arose from the energy industries sector (1A1). A majority of these emissions are from the public electricity and heat production category (1A1a). Since 1990, emissions from power stations have declined by 89%. This decline has been due to the increase in the proportion of electricity generated CCGT stations and other gas fired plant. CCGTs run on natural gas and are more efficient (see Section A6.1.1.1) than conventional coal and oil stations and have negligible SO2 emissions. Emissions from Manufacturing, Industry and Construction were responsible for 16% (Table A6.1.4) of UK emissions of SO2 in 2007. Since 1990, emissions from this sector have declined by 78% (Table A6.1.1). This decline is due to the reduction in the use of coal and oil in favour of natural gas, and also some improvement in energy efficiency.   Table A  STYLEREF 2 \s 6.1. SEQ Table_A \* ARABIC \s 2 1: % Changes from 1990 to 2007 in Sector 1 CO2CH4N2ONOxCONMVOCSO21A1-11%19%-23%-48%-22%-32%-87%1A2-20%-16%-18%-37%-28%-11%-78%1A312%-78%12%-50%-86%-89%-43%1A4-8%-65%-37%-24%-67%-41%-87%1A5-34%-31%-33%-44%-34%-40%-45%1B1-84%-86%-52%-56%-74%-62%-52%1B2-12%-47%-7%-84%-48%-63%-95%Overall-8%-70%-16%-45%-76%-72%-85% Table A  STYLEREF 2 \s 6.1. SEQ Table_A \* ARABIC \s 2 2: % Changes from 2006 to 2007 in Sector 1 CO2CH4N2ONOxCONMVOCSO21A1-2%2%-8%-7%1%-5%-16%1A2-3%-2%-1%-6%-4%-2%-5%1A30%-9%-3%-8%-15%-12%-4%1A4-4%6%-3%-8%3%3%-1%1A527%32%29%7%28%16%0%1B1-1%-30%-8%-4%0%-3%27%1B24%0%4%-14%6%-3%-61%Overall-1.8%-11%-4%-7%-8%-4%-12% Table A  STYLEREF 2 \s 6.1. SEQ Table_A \* ARABIC \s 2 3: % Contribution to Sector 1 CO2CH4N2ONOxCONMVOCSO21A140%3%30%30%5%1%66%1A215%3%26%17%28%6%16%1A325%2%31%41%45%25%10%1A419%6%12%11%21%15%5%1A51%0%1%2%0%0%1%1B10%28%0%0%1%0%2%1B21%59%1%0%1%52%0% Table A  STYLEREF 2 \s 6.1. SEQ Table_A \* ARABIC \s 2 4: % Contribution to Overall Pollutant Emissions CO2CH4N2ONOxCONMVOCSO21A139%0%5%30%5%1%63%1A215%1%4%17%25%3%16%1A324%0%5%41%40%10%9%1A419%1%2%11%18%7%5%1A51%0%0%2%0%0%1%1B10%5%0%0%0%0%2%1B21%11%0%0%1%22%0%Overall98%19%15%99.7%90%43%95% Industrial Processes sector (2) Figure A6.3 and A6.4 show both emissions of direct and indirect Greenhouse Gases for the UK industrial processes sector in 1990-2007. Emissions from direct Greenhouse gases within this sector have decreased by 48% since 1990. Tables A6.2.1 to A6.2.4 summarise the changes observed through the time series for each pollutant as well as the contribution the emissions make to Sector 2 and total UK emissions during 2007. Carbon Dioxide The industrial processes sector is not a major source of emissions in the UK for carbon dioxide. In 2007, just 2.6% (Table A6.2.4) of UK emissions originated from this sector. Methane Emissions of methane from the industrial processes sector are very small and have a negligible effect on overall methane emissions in the UK. Nitrous Oxide In 2007, 6% (Table A6.2.4) of N2O emissions in the UK came from the industrial processes sector. Between 1990 and 2007, emissions from this sector declined by an estimated 89% (Table A6.2.1) due to reductions in emissions from adipic acid manufacture (a feedstock for nylon) and nitric acid production. N2O emissions from nitric acid manufacture show a fall in 1995 due to the installation of an abatement system at one of the plants. Emissions from adipic acid manufacture were reduced significantly from 1998 onwards due to the retrofitting of an emissions abatement system to the only adipic acid plant in the UK. Hydrofluorocarbons Table A6.2.4 shows that the industrial processes sector was responsible for 100% of emissions of HFCs in the UK in 2007. Since 1990, emissions of HFCs have decreased by 16% (Table A6.2.1). The largest contribution to this sector in 2007 arises from category 2F1 refrigeration and air conditioning equipment. In 2007, these contributed 59% (Table A6.2.4) to the overall emissions of HFCs. Emissions from this category arise due to leakage from refrigeration and air conditioning equipment during its manufacture and lifetime. Emissions from aerosols contribute the next largest percentage (31%, Table A6.2.4) to overall HFC emissions. In this category, it is assumed that all the fluid is emitted in the year of manufacture. This category contains mainly industrial aerosols and also metered dose inhalers (MDI). The remaining emissions arise mainly from foam blowing (4%, Table A6.2.4), by-product emissions (3%, Table A6.2.4) and fire extinguishers (2%, Table A6.2.4). A small emission also arises from the use of HFCs as a cover gas in aluminium and magnesium foundries. Perfluorocarbons In 2007, 100% (Table A6.2.4) of PFC emissions came from the industrial processes sector. Since 1990, emissions from this sector have declined by 85% (Table A6.2.1). Within this sector, the main contribution to emissions comes from aluminium production (38%, Table A6.2.4). During the process of aluminium smelting, PFC is formed as a by-product. The emissions are caused by the anode effect, which occurs when alumina concentrations become too low in the smelter. This can cause very high electrical current and decomposition of the salt fluorine bath. The fluorine released then reacts with the carbon anode to create CF4 and C2F6. Since 1990, emissions arising from aluminium production have shown a 94% decrease (Table A6.2.1) due to significant improvements in process control and an increase in the rate of aluminium recycling. The next largest source is 2F8, which includes a range of sources including the semiconductor and electronics industries. In 2007, this sector contributed 37% (Table A6.2.4) to overall PFC emissions in the UK .The remaining contribution arises from fugitive emissions from PFC manufacture. In 2007, this contributed 25% (TableA6.2.4) to overall PFC totals in the UK. Sulphur Hexaflouride In 2007, the industrial processes sector contributed 100% (Table A6.2.4) of emissions of SF6 in the UK. Emissions arise from two main sectors. The use of SF6 in magnesium foundries contributed 19% (Table A6.2.4) towards total emissions in 2007. Emissions from 2F8 Other contributed 81% (Table A6.2.4) towards emissions, which includes emissions from electrical insulation. Emissions arise during the manufacture and filling of circuit breakers and from leakage and maintenance during the equipment lifetime. It also includes emissions from applications in the electronics industry and sports shoes. Since 1990, emissions from SF6 have decreased by 23% (Table A6.2.1). Nitrogen Oxides Although emissions of NOx from this sector do occur, overall they have little impact on emissions of NOx in the UK (see Table A6.2.4). Carbon Monoxide During 2007, emissions from the industrial sector contributed 8% (Table A6.2.4) to overall CO emissions in the UK. Contributions within this sector arise mainly from the chemical industry, iron and steel production, and aluminium production. For details see Table A6.2.3. Since 1990, emissions from this sector have decreased by 36% (Table A6.2.1). Non Methane Volatile Organic Compounds In 2007, emissions from the industrial processes sector contributed 13% (Table A6.2.4) to overall UK emissions of NMVOCs. The majority of emissions within this category come from the food and drink sector. Emissions also arise from the chemical industry. Sulphur Dioxide In 2007, SO2 emissions from the industrial processes sector contributed just 5% (Table A6.2.4) to overall emissions in the UK. Emissions arise from a variety of sources including the chemical industry, metal production and mineral products (Fletton brick production). Since 1990, SO2 emissions from this sector have declined 46% (Table A6.2.1).   Table A  STYLEREF 2 \s 6.2. SEQ Table_A \* ARABIC \s 2 1: % Changes from 1990 to 2007 in Sector 2 CO2CH4N2OHFCPFCSF6NOxCONMVOCSO22A1-16%2A2-42%2A312%2A442%2A52A6-37%2A71%-22%-35%17%272%2B1-9%2B2-55%-92%2B3-95%2B42B519%-55%30%-64%-80%-86%2C113%11%-16%-74%-13%-17%-43%2C22C325%-94%-59%65%27%2C4-65%2C5-99%-33%2D1-96%2D28%2E1-98%2E2400%2E32F1868287372%-100%2F22F32F425405%2F52F837%7%2GOverall-6%-46%-89%-16%-85%-23%-81%-36%-52%-46% Table A  STYLEREF 2 \s 6.2. SEQ Table_A \* ARABIC \s 2 2: % Changes from 2006 to 2007 in Sector 2 CO2CH4N2OHFCPFCSF6NOxCONMVOCSO22A14%2A20%2A3-3%2A415%2A52A6-2%2A7-4%6%-26%18%-14%2B142%2B20%-2%2B364%2B42B50%13%35%12%0%2%2C133%30%21%11%0%4%42%2C22C31%-36%0%0%-5%2C47%-17%2C5-28%-4%2D1-36%2D22%2E1-55%2E2-40%2E32F1-3%0%2F2-3%2F31%2F40%2F521%2F83%-4%-7%2GOverall8%14%16%-4%-28%-9%10%1%1%-7% Table A  STYLEREF 2 \s 6.2. SEQ Table_A \* ARABIC \s 2 3: % Contribution to Sector 2 CO2CH4N2OHFCPFCSF6NOxCONMVOCSO22A142%2A25%2A310%2A42%2A52A65%2A71%16%2%3%53%2B18%2B264%24%2B336%2B42B513%68%20%16%27%19%2C115%16%0%42%61%1%6%2C22C34%38%14%20%17%2C40%19%2C50%4%2D10%2D264%2E12%2E225%2E32F159%0%2F24%2F32%2F431%2F51%2F81%37%81%2G Table A  STYLEREF 2 \s 6.2. SEQ Table_A \* ARABIC \s 2 4: % Contribution to Overall Pollutant Emissions CO2CH4N2OHFCPFCSF6NOxCONMVOCSO22A11%2A20%2A30%2A40%2A52A61%2A70%0%0%0%3%2B10%2B25%0%2B33%2B42B50%0%0%1%3%1%2C10%0%0%0%5%0%0%2C22C30%38%0%2%1%2C40%19%2C50%0%2D10%2D28%2E12%2E225%2E32F159%0%2F24%2F32%2F431%2F51%2F81%37%81%2GOverall3%0.23%8%100%100%100%0.17%8%13%5% Solvents and Other Product Use sector (3) Only emissions of NMVOCs occur from the solvents category. Figure A6.5 displays total NMVOC emissions for 1990-2007. Tables A6.3.1-6.3.4 summarise the changes observed through the time series as well as the contribution the emissions make to both sector 3 and the overall emissions in the UK during 2007. Emissions from this sector contribute 43% to overall emissions of NMVOC in the UK (Table A6.3.4), and since 1990 emissions have declined by 40% (Table A6.3.1). The largest source of emissions within the solvents sector is category 3D (solvent and other product use: other), contributing 59% of NMVOC emissions in this sector (Table A6.3.3).  Table A  STYLEREF 2 \s 6.3. SEQ Table_A \* ARABIC \s 2 1: % Changes 1990-2007 within Sector 3 NMVOC3A-42%3B-65%3C-69%3D-28%Overall-40% Table A  STYLEREF 2 \s 6.3. SEQ Table_A \* ARABIC \s 2 2: % Changes 2006-2007 within Sector 3 NMVOC3A-2%3B0%3C0%3D0%Overall-0.4% Table A  STYLEREF 2 \s 6.3. SEQ Table_A \* ARABIC \s 2 3: % Contribution to Sector 3 NMVOC3A30%3B8%3C4%3D59% Table A  STYLEREF 2 \s 6.3. SEQ Table_A \* ARABIC \s 2 4: % Contribution to Overall Pollutant Emissions NMVOC3A13%3B3%3C2%3D25%Overall43% Agriculture Sector (4) Figures A6.6 and A6.7 show both emissions of direct and indirect greenhouse gases for the agricultural sector (category 4) in the UK for the years 1990-2007. Emissions of direct greenhouse gases from this sector have decreased by 21% since 1990. Tables A6.4.1-A6.4.4 summarise the changes observed through the time series for each pollutant emitted from the agricultural sector, as well as the contribution emissions make to both the sector and the overall UK estimates during 2007. Methane Agriculture is the second largest source of methane in the UK, and in 2007 emissions from this sector totalled 38% (Table A6.4.4) of the UK total. Since 1990, methane emissions from agriculture have declined by 17% (Table A6.4.1). The largest single source within the agricultural sector is 4A1 enteric fermentation from cattle. This accounts for 64% of methane emissions from this sector (Table A6.4.3), and 24% of total methane emissions in 2007 (Table A6.4.4). Since 1990, emissions from this sector have declined by 13% (Table A6.4.1) and this is due to a decline in cattle numbers over this period. Nitrous Oxide In 2007, nitrous oxide emissions from agriculture contributed 73% (Table A6.4.4) to the UK total emission. Of this, 93% (Table A6.4.4) came from the agricultural soils sector, 4D. Since 1990, emissions of N2O from the agricultural sector have declined by 23% (Table A6.4.1), driven by a fall in synthetic fertiliser application and a decline in animal population over this period. Nitrogen Oxides Emissions from the agricultural sector occur for NOX until 1993 only. During 1993, agricultural stubble burning was stopped and therefore emissions of NOX became zero after this time. Carbon Monoxide Emissions from the agricultural sector occur for CO until 1993 only. During 1993, agricultural stubble burning was stopped and therefore emissions of CO became zero after this time. Non-Methane Volatile Organic Compounds Emissions from the agricultural sector occur for NMVOC until 1993 only. During 1993, agricultural stubble burning was stopped and therefore emissions of NMVOC became zero after this time.   Table A  STYLEREF 2 \s 6.4. SEQ Table_A \* ARABIC \s 2 1: % Changes 1990-2007 within Sector 4 CH4N2ONOxCONMVOC4A1-13%4A24A3-23%4A4-15%4A54A688%4A74A8-36%4A94A10-35%4B1-16%4B24B3-23%4B4-13%4B54B687%4B74B8-36%4B920%4B104B114B12-21%4B13-20%4B14-23%4C4D-23%4E4F1-100%-100%-100%-100%-100%4F24F34F44F5-100%-100%-100%-100%-100%4GOverall-17%-23%-100%-100%-100% Table A  STYLEREF 2 \s 6.4. SEQ Table_A \* ARABIC \s 2 2: % Changes 2006-2007 within Sector 4 CH4N2ONoxCONMVOC4A1-1%4A24A3-3%4A4-3%4A54A6-1%4A74A8-2%4A94A10-13%4B1-3%4B24B3-3%4B4-3%4B54B6-2%4B74B8-2%4B9-2%4B104B114B12-4%4B13-1%4B14-5%4C4D-3%4E4F14F24F34F44F54GOverall-2%-3% Table A  STYLEREF 2 \s 6.4. SEQ Table_A \* ARABIC \s 2 3: % Contribution to Sector 4 CH4N2ONOxCONMVOC4A164%4A24A319%4A40%4A54A61%4A74A81%4A94A100%4B110%4B24B30%4B40%4B54B60%4B74B84%4B91%4B104B114B120%4B135%4B142%4C4D93%4E4F14F24F34F44F54G Table A  STYLEREF 2 \s 6.4. SEQ Table_A \* ARABIC \s 2 4: % Contribution to Overall Pollutant Emissions CH4N2ONOxCONMVOC4A124%4A24A37%4A40%4A54A60%4A74A80%4A94A100%4B14%4B24B30%4B40%4B54B60%4B74B81%4B91%4B104B114B120%4B133%4B142%4D68%4E4F14F24F34F44F54GOverall38%73%0%0%0% Land Use, land use Change and forestry (5) Figures A6.8 and A6.9 show both net emissions of direct Greenhouse gases, and emissions of indirect Greenhouse gases for the land-use, land use change and forestry sector (sector 5) in the UK for the years 1990-2007. Tables A6.5.1 and A6.5.2 summarise the changes observed through the time series for each pollutant. Carbon Dioxide Figure 6.8 shows net emissions/removals of carbon dioxide. In 1990, the UK was a net source of CO2 from LULUCF activities. In 2007, the UK was a net sink, therefore showing a decrease in emissions of 159%. Methane Emissions of methane from Land Use Change and Forestry are emitted from forestry, grassland and settlements categories (5A, 5C and 5E). Emissions from this sector have increased by 2% since 2006 (Table A6.5.2), and have increased overall by 84% since 1990 (Table A6.5.1). Nitrous Oxide Emissions of nitrous oxide from Land Use Change and Forestry are emitted from forestry, grassland and settlements categories (5A, 5C and 5E). Emissions of nitrous oxide from this sector have decreased by 46% since 1990 (Table A6.5.1), and shown a decline of just 1% since 2005 (Table A6.5.2). Nitrogen Oxides Emissions of nitrogen oxides from Land Use Change and Forestry are emitted from forestry, grassland and settlements categories (5A, 5C and 5E). Emissions from this sector have increased by 2% since 2006 (Table A6.5.2), and have increased overall by 84% since 1990 (Table A6.5.1). Carbon Monoxide Emissions of carbon monoxide from Land Use Change and Forestry are emitted from forestry, grassland and settlements categories (5A, 5C and 5E), due to the burning of biomass.   Table A  STYLEREF 2 \s 6.5. SEQ Table_A \* ARABIC \s 2 1: % Changes 1990-2007 within Sector 5 CO2CH4N2ONOxCO5A17%255%-59%255%255%5B-3%5C30%195%195%195%195%5D5E-11%-31%-31%-31%-31%5F5G-26%Overall-159%84%-46%84%84% Table A  STYLEREF 2 \s 6.5. SEQ Table_A \* ARABIC \s 2 2: % Changes 2006-2007 within Sector 5 CO2CH4N2ONOxCO5A-6%14%4%14%14%5B0%5C2%-16%-16%-16%-16%5D5E0%7%7%7%7%5F5G154%Overall0%2%-1%2%2% Waste (6) Figures A6.10 and A6.11 show emissions of both direct and indirect greenhouse gases from the waste category (sector 6) in the UK for the years 1990-2007. Emissions from direct greenhouse gases in this sector have declined by 57% since 1990. This is mostly as a result of a decline in methane emissions, although emissions of nitrous oxide have shown an increase. Tables A6.6.1 to A6.6.4 summarise the changes observed through the time series for each pollutant, as well as the contribution the emissions make to both sector 6 and the overall emissions in the UK during 2007. Carbon Dioxide Emissions of carbon dioxide from the waste sector occur from waste incineration only. These emissions are small in comparison to CO2 emissions from other sectors and have a negligible effect on overall net CO2 emissions in the UK (see Table A6.6.4). Since 1990, CO2 emissions arising from the waste sector have decreased by 61% (Table A6.6.1), and have shown a small decrease since 2006 (4%, Table A6.6.2). Methane Emissions of methane from the waste sector accounted for around 43% (Table A6.6.4) of total CH4 emissions in the UK during 2007. Emissions from methane occur from landfills, waste water treatment and waste incineration. The largest single source is landfill (6A1), with emissions from wastewater treatment and incineration being small in comparison (see Table A6.6.3). Emissions estimates from landfill are derived from the amount of putrescible waste disposed of to landfill and are based on a model of the kinetics of anaerobic digestion involving four classifications of landfill site. The model accounts for the effects of methane recovery, utilisation and flaring. Since 1990, methane emissions from landfill have declined by 59% (Table 6.6.1) due to the implementation of methane recovery systems. This trend is likely to continue as all new landfill sites are required to have these systems and many existing sites may have systems retrofitted. Nitrous Oxide Nearly all nitrous oxide waste emissions in the UK occur from the wastewater handling sector (see Table A6.6.3). Since 1990, N2O emissions from this sector have increased by 22% (Table A6.6.1). Overall, this sector contributes just 4% (Table A6.6.4) to overall nitrous oxide emissions. Nitrogen Oxides Emissions of NOx from the waste category have a negligible effect on overall UK emissions. Carbon Monoxide Emissions of CO from the waste category have a negligible effect on overall UK emissions, contributing around 1% during 2007 (Table A6.6.4). Non-Methane Volatile Organic Compounds Emissions of NMVOC from the waste category have a very small influence (2%, TableA6.6.4) on overall UK emissions. Sulphur Dioxide Emissions of SO2 from the waste category have a negligible effect on overall UK emissions.   Table A  STYLEREF 2 \s 6.6. SEQ Table_A \* ARABIC \s 2 1: % Changes 1990-2007 within Sector 6 CO2CH4N2ONOxCONMVOCSO26A1-59%-59%6B215%22%6C-61%-95%2%-73%-1%0%-88%Overall-61%-58%21%-73%-1%-46%-88% Table A  STYLEREF 2 \s 6.6. SEQ Table_A \* ARABIC \s 2 2: % Changes 2006-2007 within Sector 6 CO2CH4N2ONOxCONMVOCSO26A1-0.2%-0.2%6B20.3%0.6%6C4.1%0.2%0.0%-2.5%0.0%-1.6%0.8%Overall4.1%-0.2%0.6%-2.5%0.0%-0.8%0.8% Table A  STYLEREF 2 \s 6.6. SEQ Table_A \* ARABIC \s 2 3: % Contribution to Sector 6 CO2CH4N2ONOxCONMVOCSO26A196%59%6B24%96%6C100%0%4%100%100%41%100% Table A  STYLEREF 2 \s 6.6. SEQ Table_A \* ARABIC \s 2 4: % Contribution to Overall Pollutant Emissions CO2CH4N2ONOxCONMVOCSO26A141%1%6B22%4%6C0%0%0%0%1%1%0%Overall0.1%43%4%0.1%1%2%0.2% ANNEX 7: Uncertainties Uncertainty estimates are calculated using two methods: Approach1 (error propagation) and Approach2 (Monte Carlo simulation). Our use of the terminology Approach1 and Approach2 follows that defined in the IPCCs General Guidance and Reporting (IPCC, 2006). The uncertainty assessment in this NIR continues a number of improvements that were introduced in the 2007 submission, including presenting estimates of uncertainties according to IPCC sector in addition to presenting estimates by direct greenhouse gas. The Monte Carlo method was reviewed and revised in the 2007NIR, taking into account guidance from the 2006 Guidelines (IPCC, 2006), a summary of recommendations from the EUMM Workshop on Uncertainties held in Finland in 2005, and from an internal review of the uncertainty work. In the 2008NIR, there was also a major review of the correlations used in the Monte Carlo simulation, which included discussions with the LULUCF sector experts. The overall method is described below. The work to improve the accuracy of the uncertainty analysis continues. Estimation of Uncertainty by Simulation (Approach2) Overview of the Method Quantitative estimates of the uncertainties in the emissions were calculated using a Monte Carlo simulation. This corresponds to the IPCC Approach2 method, discussed in the 2006 Guidelines (IPCC, 2006). The background to the implementation of the Monte Carlo simulation is described in detail by Eggleston et al (1998), with the estimates reported here revised to reflect changes in the latest inventory and improvements made in the model. This section gives a brief summary of the methodology, assumptions and results of the simulation. The computational procedure is detailed below. A probability distribution function (PDF) was allocated to each unique emission factor and piece of activity data. The PDFs were mostly normal or log-normal. The parameters of the PDFs were set by analysing the available data on emission factors and activity data or by expert judgement; A calculation was set up to estimate the total emissions of each gas for the years 1990 and the latest reported year; Using the software tool @RISK"!, each PDF was sampled 20,000 times and the emission calculations performed to produce a converged output distribution; It was assumed that the distribution of errors in the parameter values was normal. The quoted range of possible error of uncertainty is taken as 2s, where s is the standard deviation. If the expected value of a parameter is E and the standard deviation is s, then the uncertainty is quoted as 2s/E expressed as a percentage. For a normal distribution the probability of the parameter being less than E-2s is 0.025 and the probability of the emission being less than E+2s is 0.975. The uncertainties used for the fuel activity data were estimated from the statistical difference between the total supply and demand for each fuel. Data on the statistical difference between supply and demand for individual sectors are not available. This means that the quoted uncertainties in TableA7.1.1 refer to the total fuel consumption rather than the consumption by a particular sector, e.g. coal consumed in the residential sector. Hence, to avoid underestimating uncertainties, it was necessary to correlate the uncertainties used for the same fuel in different sectors; and The uncertainty in the trend between 1990 and the latest reported year, according to gas, was also estimated. Uncertainty Distributions Distributions With the exception of one distribution, all of the distributions of emissions from sources in the inventory are now modelled used normal or log normal distributions. Custom distributions Emissions from landfill have been modelled using a custom distribution. Aitchson et al. (cited in Eggelston et al., 1998) estimated the uncertainty for landfill emissions using Monte Carlo analysis and found it to be skewed. The distribution histogram was used to generate an empirical distribution of emissions. For this study we examined the distribution and fitted a log normal distribution to Aitchisons data. The emissions are scaled according to the mean estimate of landfill emissions for each year. Correlations The Monte Carlo model contains a number of correlations. Omitting these correlations would lead to the uncertainties being underestimated. These correlations were not included in the very early versions of the Monte Carlo model used in the UK NIR, and were introduced over the years to improve the accuracy of the predicted uncertainties. The trend uncertainty in the Monte Carlo model is particularly sensitive to some correlations, for example, the correlation across years in emissions of N2O from agricultural soils. Other correlations have only a minor influence. The type and implementation of the correlations has been examined as part of a review (Abbott et al., 2007). The sensitivity analysis that we have completed on the Monte Carlo model suggest that the uncertainties are not sensitive to the correlations between emission factors for fuel used, and for LULUCF sources. Across years In running this simulation it was necessary to make assumptions about the degree of correlation between sources in 1990 and the latest reported year. If source emission factors are correlated this will have the effect of reducing the trend uncertainty. The model has been designed to aggregate activities and emission factors where possible, and the correlations included are listed at the start of the sections presenting uncertainties according to gas. The trend estimated by the Monte Carlo model is particularly sensitive to N2O emissions from agricultural soils (lognormal, with the 97.5percentile being 100 times the 2.5percentile). Correlations are also included for N2O emissions from sewage sludge, calculated from a lognormal distribution. The LULUCF correlations are discussed below. Other correlations are listed at the start of the sections presenting uncertainties according to gas. Between Sources in the same year Where we have estimated the uncertainty on the activity data based on statistical difference produced by BERR in DUKES, it has been necessary to correlate the fuel use for all sources using the same fuel. Review of Recent Improvements to the Monte Carlo Model Abbott et al (2007) completed an internal review was of the Monte Carlo uncertainty analysis used for the UK NIR. This review was commissioned following suggestions from an FCCC Expert Review Team about improvements that the UK could make to the transparency of the uncertainty analysis. The review evaluated the Monte Carlo model, and the documentation of the model, as presented in the 2005 NIR. The review was informed by the FCCC comments from the Third Centralised Review, from recommendations made at the EU workshop on uncertainties in Greenhouse Gas Inventories, and by the IPCC 2006 Guidelines. A range of changes were made to the model to simplify its structure and review and improve the correlations used. Method Changes A number of changes have been introduced to the Monte Carlo model, and these are listed below. Change of Simulation Method Following recommendations in the 2006 IPCC Guidelines, the model now uses a true Monte Carlo sampling method as opposed to the Latin Hypercube method used previously. The revision makes very little difference to the uncertainties estimated by the model. Treatment of Zero Emissions The original Monte Carlo model contained a number of sources where the emissions were zero, but uncertainties were still allocated to the activity data and emission factors. These zero emissions existed for several reasons: Emissions occurred in 1990 but were absent in later years; The activity had been banned (for example, burning of agricultural straw residues); Emissions had been transferred to another sector (for example MSW emissions from waste to IPCC category 6C to 1A1a.); and Because data had been included in the analysis for completeness where either the emission factor or the activity data were zero thus leading to a zero emission. The estimated uncertainties were unaffected when the zero emissions were removed from the model. Aggregation For the new Monte Carlo model, the detailed data from the GHG inventory was aggregated where appropriate in order to minimise the number of sources used in the calculation. Emissions were aggregated where possible for fuels (any emission arising from combustion), by activity data type e.g. coal, petrol, natural gas, and by emission factor. In doing so, the data are also being correlated as any uncertainty in the emission factor is then applied once, to all appropriate emissions, and the same is true of the activity data. Minimising the number of calculations performed in the Monte Carlo simulation ensures that the overall uncertainty is more accurately estimated by the model. Fgas uncertainties Estimated emissions and projections of F-gases have recently been reviewed and updated (AEA, 2009). This work also included an update to the uncertainty analysis, which has been taken into account in the over all uncertainty analysis for the greenhouse gas inventory. Uncertainty Parameter Reviews As part of the ongoing inventory improvement process many of the uncertainty distributions for our emission factors and activity data have been reviewed, with expert elicitation sought where appropriate. Further information is given in Section REF _Ref191986750 \r \h  \* MERGEFORMAT A7.6.1. Review of changes made to the Monte Carlo model since the last NIR Only the uncertainty parameters for emissions of F-gases have been revised since the last NIR was published. Quality Control Checks on the Monte Carlo Model Output A number of quality control checks are completed as part of the uncertainty analysis. a) Checks against totals of the national emissions To ensure the emissions in the Monte Carlo model closely agree with the reported totals in the NIR, the emissions in the model were checked against the national totals both before the simulation was run. The central estimates from the model are expected to be similar to the emissions totals, but are not expected to match completely. b) Inter-comparison between the output of the error propagation and Monte Carlo models We have introduced a new formal check to compare the output of the error propagation and Monte Carlo model. The results of this comparison are discussed in SectionA7.4. c) Calculation of uncertainty on the total The uncertainty on the 1990 and the 2007 emissions was calculated using two different methods; Using . EMBED Equation.3  Using  EMBED Equation.3  The first method uses the standard deviation calculated by @Risk and the mean to give an overall uncertainty, while the second method averages out the implied standard deviation(s) given by the percentiles quoted. When a distribution is completely normally distributed, the two methods will give the same results as the calculated standard deviation will be equal to the implied standard deviation. When a distribution is skewed however, the first method will give a much higher overall uncertainty than the second due to the inequality in the distribution. The overall uncertainty quoted in Table A.7.3.1 is calculated using the first method in order that uncertainties should not be underestimated in sectors showing a skewed distribution such as agricultural soils and N2O as a whole. Calculating the uncertainty using both of these methods allows us to check that the Monte Carlo analysis is behaving in the way we would expect. Comparing the results using both calculations showed that the uncertainties were almost the same for gases where the distributions used were predominantly normal, but higher for N2O and the GWP weighted total, as expected. Uncertainties according to gas The following for sections present the uncertainties in emissions, and the trend in emissions according to gas. The Fgases are grouped into one section. Carbon Dioxide Emission Uncertainties General Considerations The uncertainties in the activity data for major fuels were estimated from the statistical differences data in the UK energy statistics. This is explained further in SectionA7.6.1. These are effectively the residuals when a mass balance is performed on the production, imports, exports and consumption of fuels. For solid and liquid fuels both positive and negative results are obtained indicating that these are uncertainties rather than losses. For gaseous fuels these figures include losses and tended to be negative. The uncertainties in activity data for minor fuels (colliery methane, orimulsion, SSF, petroleum coke) and non-fuels (limestone, dolomite and clinker) were estimated based on judgement comparing their relative uncertainty with that of the known fuels. The high uncertainty in the aviation fuel consumption reflects the uncertainty in the split between domestic and international aviation fuel consumption. DECC indicate the total consumption of aviation fuel is accurately known. This uncertainty was reviewed in2005. Additional uncertainty for this source is also introduced by the use of a model to estimate emissions. The uncertainties in carbon emission factors (CEFs) for natural gas, coal used in power stations, and selected liquid fuels were derived from the Carbon Factor Review (see SectionA7.6.1 for further details). The uncertainties in other factors are based on expert judgement. In the case of non-fuel sources, the uncertainty depended on the purity of limestone or the lime content of clinker so the uncertainties estimated were speculative. The uncertainties in certain sources were estimated directly. Offshore flaring uncertainties were estimated by comparing the UKOOA flaring time series data with the flaring volumes reported by DTI (2001). The uncertainty in the activity data was found to be around 16%. This uncertainty will be an over estimate since it was assumed that the flaring volume data reported by DTI should be in a fixed proportion to the mass data reported by UKOOA. The uncertainty in the carbon emission factor was estimated by the variation in the time series to be around 6%. Again this will be an over estimate since it was assumed that the carbon emission factor is constant. Uncertainties for fuel gas combustion were estimated in a similar way. Uncertainties in the land use change sources were ascribed to each sector by Milne (pers. comm., 2006). The uncertainty for Fletton bricks and peat combustion is based on expert assessment of the data used to make the estimate. The uncertainty used for cement production is based on the estimates reported in IPCC (2000). Clinical waste incineration was assumed to have the same uncertainty as MSW incineration. Uncertainty Parameters Two tables are provided in this section a table of uncertainties in the activity data and emission factors for the major fuels used to estimate emissions of carbon dioxide, and a table of the same parameters for non-fuels. These nonfuels relate to emissions from a range of sources, including the following: The release of carbon from the breakdown of pesticides and detergents; and Use of natural gas for the production of ammonia. In some cases the individual uncertainties for the activity data and the emission factor are unknown, but the uncertainty on the total emission is known. In these cases, the uncertainties are listed in the column marked uncertainty in emission. Table A  STYLEREF 2 \s 7.2. SEQ Table_A \* ARABIC \s 2 1: Uncertainties in the activity data and emission factors for fuels used in the carbon dioxide inventory 19902007FuelActivity uncertainty (%)Emission factor uncertainty (%)Uncertainty in emission (%)Activity uncertainty (%)Emission factor uncertainty (%)Uncertainty in emission (%)Anthracite1.560.26Aviation spirit203.3203.3Aviation turbine fuel203.3203.3Blast furnace gas1.560.26Burning oil621.92Chemical waste715715Clinical waste720720Clinker production12.212.2Coal1.510.21Coke330.53Coke oven gas1.560.26Colliery methane5555DERV1.82.10.62.1Dolomite1515Exploration drilling128128Energy recovery - chemical industry--20--20Fuel oil5.51.712.31.7Fletton bricks20702070Gas oil1.81.40.61.4Limestone1515LPG25.734.93Lubricants205205MSW720720Naphtha7.33not usednot usedNatural gas2.81.50.41.5OPG1.431.33Orimulsion12not usednot usedPeat25252525Petrol14.81.44.8Petroleum coke7.830.83Petroleum waxes--20--20Refinery miscellaneous11.93not usednot usedSoda ash152152Scrap tyres15101510Sour gasnot usednot used0.21SSF3.335.63Wastenot usednot used150Waste oils205205Waste solventnot usednot used110Notes Uncertainties expressed as 2s/E input parameters were uncertainties of activity data and emission factors Not used = Fuel not used Table A  STYLEREF 2 \s 7.2. SEQ Table_A \* ARABIC \s 2 2: Uncertainties in the activity data and emission factors for non-fuels used in the carbon dioxide inventory 19902007SectorSourcesActivity uncertainty (%)Emission factor uncertainty (%)Uncertainty in emission (%)Activity uncertainty (%)Emission factor uncertainty (%)Uncertainty in emission (%)1B2aOffshore oil and gas - processes--28--281B2c_FlaringOffshore oil and gas - flaring1661661B2c_VentingOffshore oil and gas - venting1661665A5A2 Forest Land - biomass burning; 5A2 Land converted to forest land--25--252B1Ammonia production - feedstock use of gas0.41.50.41.55B5B1 Cropland Liming; 5B1 Cropland remaining cropland; 5B2 Land converted to cropland--45--505C5C Grassland - biomass burning; 5C1 Grassland liming; 5C1 Grassland remaining grassland; 5C2 Land converted to grassland--70--555E5E Settlements - biomass burning; 5E2 Land converted to settlements--35--505G5G Harvested Wood Products; 5G LULUCF emissions from OTs and CDs--30--30Carbon in detergents--20--20Carbon in pesticides--20--20Gypsum producednone producednone produced-15Primary aluminium production1515Steel production (electric arc and oxygen converters)120120Notes Uncertainties expressed as 2s/E input parameters were uncertainties of activity data and emission factors Uncertainty in the Emissions The overall uncertainty was estimated as around 2% in 2007. The central estimate of total CO2 emissions in 2007 was estimated as 544,657 Gg. The Monte Carlo analysis suggested that 95% of the values were between 535,814Gg and 553,499Gg. Uncertainty in the Trend The uncertainty in the trend between 1990 and 2007 was estimated. In running this simulation it was necessary to make assumptions about the degree of correlation between sources in 1990 and 2007. If source emission factors are correlated this will have the effect of reducing the trend uncertainty. The assumptions were as follows: Activity data are uncorrelated; Emission factors of some similar fuels are correlated; Land Use Change and forestry emissions are correlated (i.e. 5A with 5A etc); Offshore emissions are not correlated since they are based on separate studies using emission factors appropriate for the time; Emission factors covered by the Carbon Factors Review (Baggott et al, 2004) are not correlated; and Process emissions from blast furnaces, coke ovens and ammonia plant were not correlated. This analysis indicates that there is a 95% probability that CO2 emissions in 2007 were between 6% and 10% below the level in 1990. Methane Emission Uncertainties General Considerations In the methane inventory, combustion sources are a minor source of emissions. The uncertainties on the quantities of fuel burnt are known, although the effect of the large uncertainty associated with the emission factors will dominate the overall uncertainty on the emissions. The uncertainties are listed in TableA7.2.3. The uncertainty on the activities for the fuels burnt are not pollutant specific, and are reported in TableA7.2.1. Uncertainty Parameters Table A  STYLEREF 2 \s 7.2. SEQ Table_A \* ARABIC \s 2 3: Estimated uncertainties in the activity data and emission factors used in the methane inventory 19902007SourceReferenceActivity %Emission Factor %Source Uncertainty %Activity %Emission Factor %Source Uncertainty %Coal5050Coke5050Petroleum coke5050SSF5050Burning oil5050Fuel oil5050Gas oil5050DERV5050Petrol5050Orimulsion5050Aviation turbine fuel5050Natural gas5050Colliery methane5050LPG5050OPG5050MSW5050Sour gas5050Naphtha5050Refinery miscellaneous5050Blast furnace gas5050Coke oven gas5050Town gas5050Lubricants5050Waste oils5050Scrap tyres5050Aviation spirit5050Anthracite5050Burning oil (premium)5050Vaporising oil5050Clinical waste5050Poultry litter5050Landfill gas5050Sewage gas5050Wood5050Straw5050Sewage sludge combustion5050Field burning*25502550LandfillBrown et al 1999--~481--~481Livestock: entericWilliams, 1993--20--20Livestock: wastesWilliams, 1993--30.5--30.5Coal MiningBennett et al, 1995 --13.3--13.3Offshore*16201620Gas LeakageWilliams, 1993--17-752--17-752Chemical industry*20202020Fletton bricks*2010020100Sewage sludgeHobson et al, 1996--50--50 Notes 1 Skewed distribution 2 Various uncertainties for different types of main and service * See text Input parameters were uncertainties of activity data and emission factors Fuel combustion uncertainties expressed as 2s/E Uncertainties in the activity data for fuels burnt are reported in Table A7.2.1. The non fuel combustion sources are mainly derived from the source documents for the estimates or from the Watt Committee Report (Williams, 1993). The uncertainty in offshore emissions was revised for the 2000 inventory using improved estimates of the activity data. The methane factors were assumed to have an uncertainty of 20% since the flaring factors are based on test measurements. The sources quoted in TableA7.2.3 are assumed to have normal distributions of uncertainties with the exception of landfills. Brown et al. (1999) estimated the uncertainty distribution for landfill emissions using Monte Carlo analysis and found it to be skewed. For normal distributions there is always a probability of negative values of the emission factors arising. For narrow distributions this probability is negligible; however with wide distributions the probability may be significant. In the original work (Eggleston et al, 1998) this problem was avoided by using truncated distributions. However, it was found that this refinement made very little difference to the final estimates. In these estimates a lognormal distribution was used rather than truncated normal distributions. Uncertainty in the Emissions The overall uncertainty was estimated as around 23% in 2007. The central estimate of total CH4 emissions in 2007 was estimated as 49,015Gg CO2 equivalent. The Monte Carlo analysis suggested that 95% of the values were between 40,987 and 59,417Gg CO2 equivalent. Uncertainty in the Trend The uncertainty in the trend between 1990 and 2007 was estimated. In running this simulation it was necessary to make assumptions about the degree of correlation between sources in 1990 and 2007. If source emission factors are correlated this will have the effect of reducing uncertainty in the emissions trend. The assumptions were: Activity data are uncorrelated between years, but activity data for major fuels were correlated in the same year in a similar manner to that described above for carbon; Landfill emissions were partly correlated across years in the simulation. It is likely that the emission factors used in the model will be correlated, and also the historical estimates of waste arisings will be correlated since they are estimated by extrapolation from the year of the study. However, the reduction in emissions is due to flaring and utilisation systems installed since 1990 and this is unlikely to be correlated. As a simple estimate it was assumed that the degree of correlation should reflect the reduction. Emissions have reduced by 59% hence the degree of correlation was 31%; Offshore emissions are not correlated across years since they are based on separate studies using emission factors that reflected the processes in use at the time; Gas leakage emissions were partially correlated across years. As a simple estimate it was assumed that the degree of correlation should reflect the reduction in emissions. Emissions have reduced by 45% hence the degree of correlation was 55%; and Emissions from deep mines were not correlated across years as they were based on different studies, and a different selection of mines. Open cast and coal storage and transport were correlated since they are based on default emission factors. This analysis indicates that there is 95% probability that methane emissions in 2007 were between 50% and 56% below the level in 1990. Nitrous Oxide Emission Uncertainties General Considerations The analysis of the uncertainties in the nitrous oxide emissions is particularly difficult because emissions sources are diverse, and few data are available to form an assessment of the uncertainties in each source. Emission factor data for the combustion sources are scarce and for some fuels are not available. The parameter uncertainties are shown in TableA7.2.4. The uncertainty for the fuels burnt are not pollutant specific and are reported in TableA7.2.1. The uncertainty assumed for agricultural soils uses a lognormal distribution since the range of possible values is so high. Here it is assumed that the 97.5 percentile is greater by a factor of 100 than the 2.5 percentile based on advice from the Land Management Improvement Division of DEFRA (pers. comm.). Uncertainty Parameters Listed in table overleaf. Table A  STYLEREF 2 \s 7.2. SEQ Table_A \* ARABIC \s 2 4: Estimated uncertainties in the activity data and emission factors used in the N2O inventory 19902007SourceActivity %Emission Factor %Source Uncertainty %Activity %Emission Factor %Source Uncertainty %Coke195195Petroleum coke118118SSF118118Burning oil118118Fuel oil140140Gas oil140140DERV140140Petrol170170Orimulsion170170Aviation turbine fuel140140Natural gas170170Colliery methane110110LPG110110OPG110110MSW110110Sour gas230230Naphtha110110Refinery miscellaneous140140Blast furnace gas140140Coke oven gas118118Town gas118118Lubricants118118Waste oils140140Scrap tyres140140Aviation spirit140140Anthracite170170Burning oil (premium)387387Vaporising oil140140Limestone140140Clinical waste230230Poultry litter230230Landfill gas230230Sewage gas110110Wood110110Straw230230Sewage sludge combustion230230Agricultural soilsLog-normal2Log-normal2Wastewater treatmentLog-normal2Log-normal2Adipic Acid0.5150.515Nitric Acid1023010230Notes Expressed as 2s/E With 97.5 percentile 100 times the 2.5 percentile and the mean the distribution factor equal to 1. The logarithm for the variable is normally distributed with standard deviation,(, equal to ln(100)/(2 x 1.96) and mean equal to (-(2)/2. Uncertainties in the activity data for fuels burnt are reported in Table A7.2.1. Input parameters were uncertainties of activity data and emission factors Uncertainty in the Emissions The overall uncertainty was estimated as around 271% in 2007. The central estimate of total N2O emissions in 2007 was estimated as 34,898Gg CO2 equivalent. The Monte Carlo analysis suggested that 95% of the values were between 10,372 and 97,083Gg CO2 equivalent. Uncertainty in the Trend The uncertainty in the trend between 1990 and 2007 was also estimated. In running this simulation it was necessary to make assumptions about the degree of correlation between sources in 1990 and 2007. If sources are correlated this will have the effect of reducing the emissions. The assumptions were as follows: Activity data are uncorrelated between years, but similar fuels are correlated in the same year; Emissions from agricultural soils were correlated; The emission factor used for sewage treatment was assumed to be correlated, though the protein consumption data used as activity data were assumed not to be correlated; Nitric acid production emission factors were assumed not to be correlated, since the mix of operating plant is very different in 2007 compared with 1990 only 4 of the original 8 sites are still operating, 2 of which now have differing levels of abatement fitted; and Adipic acid emissions were assumed not to be correlated because of the large reduction in emissions due to the installation of abatement plant in 1998. This analysis indicates that there is a 95% probability that N2O emissions in 2007 were between 32% and 71% below the level in 1990. Halocarbons and SF6 Uncertainty Parameters The uncertainties in the emissions of HFCs, PFCs and SF6 have been updated in this years NIR, based on the recent study to update emissions and projections of F-gases (AEA, 2008). The previous estimates had been taken from AEAT (2004), but had not been consistently updated to reflect the estimated uncertainty in the emissions estimates for the latest reported year. The spreadsheet model has been modified to ensure that the uncertainty estimates for these gases are consistent with the correct year from the latest F-gas study. Uncertainty in the Emissions The uncertainties were estimated as 1990 (1995) 15% (14%) for HFCs, 6% (7%) for PFCs 17% (17%) for SF6 2007 22% for HFCs 24% for PFCs 15% for SF6 Uncertainty in the Trend This analysis indicates that there is a 95% probability that emissions in 2007 differed from those in 1990 by the following percentages -33% to +4% for HFCs -88% to -82% for PFCs -36% to -7% for SF6 Uncertainties in GWP weighted emissions Uncertainty in the emissions The uncertainty in the combined GWP weighted emission of all the greenhouse gases was estimated as 15% in both 1990 and 2007. Uncertainty in the Trend This analysis indicates that there is a 95% probability that the total GWP GHG emissions in 2006 were between 16% and 20% below the level in 1990. The uncertainty estimates for all gases are summarised in TableA7.3.1. The source which makes the major contribution to the overall uncertainty is 4D Agricultural Soils. This source shows little change over the years, but other sources have fallen since 1990. In previous years, trend uncertainties from the base year to the current inventory year have also been reported here. The base year in these calculations was not the true base year as it did not included the emissions/removals in the elected LULUCF articles under the Kyoto Protocol. This table has not been included this year. Base year emissions can be found in TableES5. Table A  STYLEREF 2 \s 7.3. SEQ Table_A \* ARABIC \s 2 1: Summary of Monte Carlo Uncertainty Estimates 1990 - 2007 Gas1990 Emissions2007 EmissionsUncertainty in 1990 emissions as % of emissions in categoryUncertainty introduced on national total in 1990Uncertainty in 2007 emissions as % of emissions in categoryUncertainty introduced on national total in 2007% change in emissions between 2007 and 1990Range of likely % change between 2007 and 19902.5 percentile97.5 percentile2.5 percentile97.5 percentile2.5 percentile97.5 percentileGg CO2eGg CO2eGg CO2eGg CO2e%Gg CO2eGg CO2e%%%%CO2 (net)594,192544,657584,627603,6032.0%535,814553,4992.0%-8%-10.4%-6.2%CH4104,56949,01585,440129,68526%40,98759,41723%-53%-56%-50%N2O64,94934,89832,856146,077179%10,37297,083271%-53%-71%-32%HFC11,3909,6149,99212,79015%7,89711,31722%-15%-33%4%PFC1,4022161,3461,4575%17425724%-85%-88%-82%SF61,0307948871,17317%69289415%-22%-36%-7%All777,532639,194733,190861,31715%608,565702,23915.0%-18%-20.0%-15.6% Notes Uncertainty calculated as 2s/E where s is the standard deviation and E is the mean, calculated in the simulation. N2O quoted but distribution is highly skewed and uncertainty quoted exceeds 100%. Emissions of CO2 are net emissions (i.e. sum of emissions and removals). Important - Emissions in this table are taken from the Monte Carlo model output. The central estimates, according to gas, for 1990 and the latest inventory year are very similar but not identical to the emission estimates in the inventory. The Executive Summary of this NIR and the accompanying CRF tables present the agreed national GHG emissions reported to the UNFCCC. Comparison of uncertainties from the error propagation and Monte Carlo analyses Comparing the results of the error propagation approach, and the Monte Carlo estimation of uncertainty by simulation, is a useful quality control check on the behaviour of the Monte Carlo model. The reason that the error propagation approach is used as a reference is because the mathematical approach to the error propagation approach has been defined and checked by the IPCC, and is clearly set out in the IPCC 2000 Good Practice Guidance and the 2006 Guidelines. The UK has implemented the IPCC error propagation approach as set out in this guidance. The implementation of an uncertainty estimation by simulation cannot be prescriptive, and will depend on the Monte Carlo software a country chooses to use, how the country constructs its model, and the correlations included within that model. Therefore, there is a greater likelihood of errors being introduced in the model used to estimate uncertainty by simulation. If all the distributions in the Monte Carlo model were normal, and there were no correlations between sources, the estimated errors on the trend from the Monte Carlo model should be identical to those estimated by the error propagation approach. In reality there will be correlations between sources, and some distributions are not normal and are heavily skewed. TableA7.4.1 shows that the estimates of uncertainty on the trend provided by the two methods are almost identical, and this provides confidence in our implementation of the Monte Carlo model. The error propagation approach does not account for correlations, and so we might expect the trend uncertainty estimated by this method to be greater than that reported by the Monte Carlo model. The assumption of equivalence between the two methods relies on the fact that the distributions of individual uncertainties in the activity data and emissions factors in the two approaches are both normal. However, there are a number of log-normal distributions in the Monte Carlo model and the effects of these cannot be fully reproduced in the error propagation model. These log-normal distributions will have the effect of increasing the uncertainty on the trend as the distributions are more skewed. The central estimates of emissions generated by the Monte Carlo model in1990, and those in the latest inventory year, are also very close. Mathematically we would not expect the central estimates from the two methods to be identical. Table A  STYLEREF 2 \s 7.4. SEQ Table_A \* ARABIC \s 2 1: Comparison of the central estimates and trends in emissions from the error propagation (Approach1) and Monte Carlo (Approach2) uncertainty analyses Method of uncertainty estimationCentral estimate (Gg CO2 equivalent)bUncertainty on trend, 95%CI (1990 to 2007)19902007Error propagation776,892638,2114.9Monte Carlo777,532639,1944.4a Notes CI Confidence Interval a 2.5th percentile, -20%, 97.5th percentile, -15.6%. Difference between these values is the 95th percentile which assuming a normal distribution is equal to (2 standard deviations on the central estimate. b Net emissions, including emissions and removals from LULUCF Sectoral uncertainties Overview of the Method Sectoral uncertainties were calculated from the same base data used for the by gas analysis. The emissions and uncertainties per sector are presented in Table A7.5.1. We recommend that the estimates in the table are taken only as indicative. Review of Changes made to the Monte Carlo Model since the last NIR The estimates of uncertainty for F-gas emissions have been updated based on AEA (2008). Table A  STYLEREF 2 \s 7.5. SEQ Table_A \* ARABIC \s 2 1: Sectoral Uncertainty Estimates IPCCGas19902007Uncertainty in 2007 emissionsUncertainty% change inRange of likely % changeSourceEmissionsEmissionsas % of emissionsIntroducedemissions between 1990 and 2007Categoryin categoryon national totalbetween 19902.5 percentile97.5 percentilein 2007and 20072.5 percentile97.5 percentile1A1aGWP weighted total206,929179,440177,949181,0711%-13%-15%-12%1A1bGWP weighted total18,38815,12014,68915,5473%-18%-21%-15%1A1cGWP weighted total14,10217,82117,56418,1132%26%23%30%1A2aGWP weighted total24,45318,99918,30219,6934%-22%-26%-18%1A2fGWP weighted total76,53661,94161,11162,9712%-19%-21%-17%1A3aGWP weighted total1,2612,1641,8202,51219%73%37%114%1A3bGWP weighted total111,752123,418120,820126,0113%10%7%14%1A3cGWP weighted total1,8812,4822,3332,70710%32%18%47%1A3dGWP weighted total4,1454,9704,7755,1635%20%15%25%1A3eGWP weighted total30351848456911%71%52%92%1A4aGWP weighted total25,70320,74420,49220,9971%-19%-21%-18%1A4bGWP weighted total80,47376,88776,02777,7531%-4%-7%-2%1A4cGWP weighted total5,7404,6144,3555,0159%-19%-27%-11%1A5bGWP weighted total5,3413,5253,0563,99616%-34%-45%-21%1B1aGWP weighted total18,2702,6412,4512,8299%-85%-87%-84%1B1bGWP weighted total8781491441534%-83%-84%-82%1B2aGWP weighted total2,7841,0508721,23121%-62%-70%-53%1B2bGWP weighted total7,9554,3714,3504,3911%-45%-45%-45%1B2c_FlaringGWP weighted total4,4854,6084,0165,21416%3%-14%23%1B2c_VentingGWP weighted total88454943666726%-37%-54%-16%2A1GWP weighted total7,2956,1175,9976,2402%-16%-18%-14%2A2GWP weighted total1,1916886597175%-42%-46%-39%2A3GWP weighted total1,2851,4431,4071,4793%12%8%17%2A4GWP weighted total16723820826715%43%19%70%2A7GWP weighted total20320012529953%5%-47%79%2B1GWP weighted total1,3221,2091,1931,2242%-9%-11%-6%2B2GWP weighted total3,8991,7465483,904130%-35%-89%80%2B3GWP weighted total20,7339898671,11115%-95%-96%-94%2B5GWP weighted total1,7331,9361,6902,18716%12%-6%32%2C1GWP weighted total1,8862,1252,0222,2286%13%5%21%2C3GWP weighted total1,7836436166705%-64%-66%-62%2E1GWP weighted total11,37817616019111%-98%-99%-98%2E2GWP weighted total1155486115%404%321%498%2F1GWP weighted total05,6283,9627,25236%4498709%2535740%7495327%2F2GWP weighted total041030851330%NANANA2F3GWP weighted total019816523020%NANANA2F4GWP weighted total123,0132,5903,44217%25606%20655%31306%2F5GWP weighted total070568525%NANANA2F8GWP weighted total66284273294816%28%NANA4A1GWP weighted total13,54511,7949,84813,73220%-12%-31%10%4A10GWP weighted total965720%-34%-48%-17%4A3GWP weighted total4,5033,4642,9064,03020%-22%-39%-3%4A4GWP weighted total121081220%-15%-33%7%4A6GWP weighted total7714512116920%90%49%137%4A8GWP weighted total23815212717720%-35%-49%-19%4B1GWP weighted total2,1271,7921,3432,24431%-14%-41%21%4B3GWP weighted total109836310531%-21%-47%11%4B4GWP weighted total000030%-10%-39%25%4B6GWP weighted total61181430%92%30%170%4B8GWP weighted total1,11871753889730%-34%-56%-8%4B9GWP weighted total22426920133731%23%-17%73%4B9aGWP weighted total000030%-33%-54%-6%Agriculture - N2OGWP weighted total32,96625,6201,81788,096369%-24%-25%-22%5AGWP weighted total-12,126-14,166-17,100-11,261-25%19%-13%57%5BGWP weighted total15,81115,3118,92821,62050%3%-48%72%5CGWP weighted total-6,134-7,939-11,131-5,395-45%39%-26%132%5EGWP weighted total7,0836,3433,7228,97250%-7%-50%46%5GGWP weighted total-1,658-1,234-1,537-932-30%-24%-48%7%6A1GWP weighted total49,90420,30712,60730,44254%-59%-59%-59%6B2GWP weighted total1,7252,0617815,171203%69%-69%365%6CGWP weighted total1,38952045859316%-62%-68%-56%Grand TotalGWP weighted total777,520639,151608,555702,73115%-18%-20%-16% Important - Emissions in this table are taken from the Monte Carlo model output. The central estimates, according to gas, for 1990 and the latest inventory year are very similar but not identical to the emission estimates in the inventory. The Executive Summary of this NIR and the accompanying CRF tables present the agreed national GHG emissions reported to the UNFCCC. Estimation of uncertainties using an error propagation APPROACH (Approach1) The IPCC Good Practice Guidance (IPCC, 2000) and 2006 Guidelines defines error propagation and Monte Carlo modelling approaches to estimating uncertainties in national greenhouse gas inventories. The results of the error propagation approach are shown in TablesA7.5.2-5. In the error propagation approach the emission sources are aggregated up to a level broadly similar to the IPCC Summary Table 7A. Uncertainties are then estimated for these categories. The uncertainties used in the error propagation approach are not exactly the same as those used in the Monte Carlo Simulation since the error propagation source categorisation is far less detailed. However, the values used were chosen to agree approximately with those used in the Monte Carlo Simulation. The error propagation approach is only able to model normal distributions. This presented a problem in how to estimate a normal distribution approximation of the lognormal distribution used for agricultural soils and wastewater treatment. The approach adopted was to use a normal distribution with the same mean as the lognormal distribution. There were a number of major improvements to the key source analysis in the 2006NIR. In part, these improvements have been made following comments made in the Fourth Centralised Review and have been made to improve the transparency of the uncertainty analysis. The improvements are summarised below. Review of Recent Improvements to the Error Propagation Model An ERT commented that the key source analysis was not consistent with the IPCC GPG. The comment was in reference to the guidance where it says "The (key source) analysis should be performed at the level of IPCC source categories". Our analysis included disaggregation of 1B1 and 1B2 in the case of CH4, rather than treating each of these as a single source category. This has been revised by summing these categories; and The uncertainties associated with some of the fuel consumptions in the 2005NIR were derived from an analysis of the statistical differences between supply and demand for one year, presented in the 1996UK energy statistics. This analysis was updated for the 2008NIR, and we have now revised the uncertainty associated the consumptions of the fuels listed below this bullet point. The uncertainties were calculated from the differences between supply and demand for fuel categories presented in the1996 DTI DUKES. We have now chosen to use a 5year rolling average since this is a time period short enough to allow a satisfactory estimate of the change in the variability in the supply and demand, but avoids the sometimes large yeartoyear variability that can be a feature of the UK energy statistics. This large yeartoyear variability is in part controlled by the historical revisions to the energy statistics that the BERR (now DECC) perform each year, and in some years, by revisions to historic estimates of supply and demand which will then alter the uncertainty calculated from previous data. The uncertainty between supply and demand has been estimated for the following fuels: Coal Coke Petroleum coke Solid smokeless fuel Burning oil Fuel oil Gas oil Petrol Natural gas LPG OPG Naphtha Miscellaneous Blast furnace gas Coke oven gas In a few cases in this uncertainty analysis, types of fuels are grouped into one class: for example, oil in IPCC sector1A used in stationary combustion; this oil is a combination of burning oil (minimal quantities used), fuel oil, and gas oil. In this case, and in other instances like it, we have used expert judgement to assign an uncertainty to a fuel class from the estimated uncertainties associated with individual fuels of that class. The uncertainties in the consumption of Aviation Turbine Fuel and Aviation Spirit has been reviewed and this is discussed below; We have reviewed the uncertainties associated with the emissions of HFC, PFC and SF6 from industrial processes. The uncertainties associated with the total Fgas emissions has been assigned to the EF in the error propagation analysis since uncertainties are not known individually for the ADs and EFs as the emissions are produced from a model. The uncertainties used are weighted values, and reflect the individual uncertainties and the magnitude of emissions in each of the respective sectors; The LULUCF sectoral experts, CEH, have revised the uncertainties associated with emissions associated with Land Use Change and Forestry. The uncertainties associated with the emissions in each LULUCF category have been assigned to the EF in the error propagation analysis, since uncertainties are not known individually for the ADs and EFs as emissions are produced from a complicated model; We have reviewed the uncertainties associated with the consumptions of Aviation Turbine Fuel and Aviation Spirit For this review we contacted BERR (now DECC) for their view about the 95% CI that could be applied to the demand of Aviation Spirit and Aviation Turbine Fuel in the UK energy statistics. We then considered the additional uncertainty that would be introduced by the Tier3 aviation model, which is used to estimate emissions. The overall uncertainty in the AD has been assigned by expert judgement considering the uncertainty in the BERR fuel consumption data and the additional uncertainty introduced by the model; We have reviewed the uncertainties associated with carbon emission factors (CEFs) for natural gas, coal used in power stations, and selected liquid fuels. The CEF uncertainty for natural gas was taken from analytical data of determinations of the carbon contents presented in a TRANSCO report - this report was produced for the Carbon Factor Review. The CEF uncertainty for the coal used in power stations has been derived from expert judgement following a consultation with representatives from the UK electricity supply industry, and takes into account analytical data of determinations of the carbon contents of power station coal. Analytical data of determinations of the carbon contents of liquid fuels from UKPIA have been used to determine the CEF uncertainties associated with the following fuels: motor spirit, kerosene, diesel, gas oil, and fuel oil. Analytical data were available for naphtha and aviation spirit, but these were not used to modify the existing uncertainties, as the sample sizes were too small. The existing CEF uncertainties were retained for these fuels; and Uncertainties for the ADs and EFs for peat combustion have been assigned using expert judgement. Review of Changes Made to the Error Propagation Model since the last NIR There have been no substantial changes to error propagation model since the last NIR. Uncertainty in the Emissions The error propagation analysis, including LULUCF emissions, suggests an uncertainty of 16% in the combined GWP total emission in 2007, the latest reported inventory year in this NIR; GWP emission uncertainty of 16% in the 2006 inventory, reported in the 2008NIR. The error propagation analysis, excluding LULUCF emissions, suggests an uncertainty of 16% in the combined GWP total emission in 2007, the latest reported inventory year in this NIR; GWP emission uncertainty of 16% in the 2006 inventory, reported in the 2008NIR. Uncertainty in the Trend The analysis, including LULUCF emissions, estimates an uncertainty of 2.4% in the trend between the base year and 2007, the latest reported inventory year in this NIR; trend uncertainty of 3% (with respect to 1990) in the 2006 inventory, reported in the 2008NIR. The analysis, excluding LULUCF emissions, estimates an uncertainty of 2.5% in the trend between the base year and 2007, the latest reported inventory year in this NIR; trend uncertainty of 3% (with respect to 1990) in the 2006 inventory, reported in the 2008NIR. Key Categories In the UK inventory, certain source categories are particularly significant in terms of their contribution to the overall uncertainty of the inventory. These key source categories have been identified so that the resources available for inventory preparation may be prioritised, and the best possible estimates prepared for the most significant source categories. We have used the method set out in Section7.2 of the IPCC Good Practice Guidance (2000) (Determining national key source categories) to determine the key source categories. The results of this key source analysis can be found in Annex1. Tables of uncertainty estimates from the error propagation approach See overleaf. Table A  STYLEREF 2 \s 7.6. SEQ Table_A \* ARABIC \s 2 1: Summary of error propagation uncertainty estimates including LULUCF, base year to the latest reported year  Table A  STYLEREF 2 \s 7.6. SEQ Table_A \* ARABIC \s 2 2: Summary of error propagation uncertainty estimates including LULUCF, base year to the latest reported year (continued)  Table A  STYLEREF 2 \s 7.6. SEQ Table_A \* ARABIC \s 2 3: Summary of error propagation uncertainty estimates excluding LULUCF, base year to the latest reported year  Table A  STYLEREF 2 \s 7.6. SEQ Table_A \* ARABIC \s 2 4: Summary of error propagation uncertainty estimates excluding LULUCF, base year to the latest reported year (continued)  ANNEX 8: Verification This Annex discusses the verification of the UK estimates of the Kyoto Gases. Modelling approach used for the verification of the UK GHGI In order to provide some verification of the UK Greenhouse Gas Inventory (GHGI) DECC (formerly Defra) have established and maintained a high-quality observation station at Mace Head on the west coast of Ireland. The station reports high-frequency concentrations of the key greenhouse gases and is under the supervision of Dr. Simon ODoherty of the University of Bristol (Simmonds et al. 1996). The Met Office, under contract to DECC, employs the Lagrangian dispersion model NAME (Numerical Atmospheric dispersion Modelling Environment) (Ryall et al. 1998) (Jones et al. 2004) driven by 3D synoptic meteorology from the Met Officess numerical weather prediction model, the Unified Model, to generate so called air-history maps. The air-history maps represent the recent 10-day history of the air before it arrives at the observing station, Mace Head, and estimate the dilution in concentration that surface sources would undergo during this transport. These maps have been generated for each 3-hour period from 1995 to current day and enable the observations made at Mace Head to be sorted into those that represent Northern Hemisphere baseline air masses and those that represent regionally-polluted air masses arriving from Europe. From the sorted data an estimate of the time-varying Northern Hemisphere mid-latitude baseline concentration is made. The Mace Head observations, with the baseline removed, and the 3-hourly air-history maps are applied in an inversion algorithm to estimate the magnitude and spatial distribution of the European emissions that best support the observations (Manning et al. 2003). The technique has been applied to methane, nitrous oxide and a range of HFCs where data are available. The inversion (best-fit) technique, simulated annealing, is used to fit the model emissions to the observations. It assumes that the emissions from each grid box are uniform in both time and space over the duration of the fitting period. This implies that the release is independent of meteorological factors such as temperature and diurnal cycles, and that in its production and use there are no definite cycles or intermittency. The geographical area defined as UK within the NAME estimates includes the coastal waters around the UK. A best fit solution has been determined for each two-year period (Jan95-Dec96, Feb95-Jan97, Jan07-Dec08). The uncertainty ranges have been estimated by solving multiple times with a random noise perturbation applied to the observations. The annual estimates have been calculated by taking the mean of all of the solutions with the full year represented in the solution period. Methane In Table A8.2.1 the emission estimates made for the UK with the NAME-inversion methodology are compared to the GHGI emission estimates for the period 1995-2007 inclusive. Methane has a natural (biogenic) component and it is estimated that 22% of the annual global emission is released from wetlands (Nilsson et al. 2001). Usually natural emissions are strongly dependent on a range of meteorological factors such as temperature and diurnal, annual, growth and decay cycles. Such non-uniform emissions will add to the uncertainties in the modelling, although in North West Europe the natural emissions are thought to be small compared to the anthropogenic emissions. Due to the relatively strong local (within 20km) influence of biogenic emissions at Mace Head, a peat bog area, observations taken when local emissions will be significant (low wind speeds and low boundary layer heights) have been removed from the data set prior to applying the inversion technique. The GHGI trend is monotonically downwards whereas the NAME estimates show no clear trend (Figure A8.1). The agreement from 2001 onwards is good. It must be remembered however that the GHGI totals only include anthropogenic emissions whereas the NAME estimates are total emissions combining both anthropogenic and biogenic releases however biogenic emissions in the UK are thought to be low. For 2006 the NAME-inversion method has been applied using data from 11 stations, including Mace Head, across Europe as part of the FP6 European project NitroEurope. The agreement between the Mace Head only results and the GHGI estimates are excellent for this year. Table A  STYLEREF 2 \s 8.2. SEQ Table_A \* ARABIC \s 2 1: Verification of the UK emission inventory estimates for methane in Ggyr-1 for 1995-2007. NAME uncertainty (500 Gg yr-1. NAME1 use Mace Head observations only, NAME2 use observations from 11 sites across Europe including Mace Head. Gas1995199619971998199920002001200220032004200520062007CH4 NAME12070211020001920209024602400216022502230258023201960CH4 NAME22510CH4 GHGI4334421939903782353233193034289126062520243023982326  Figure A8.1: Verification of the UK emission inventory estimates for methane in Ggyr-1 for 1995-2007. GHGI estimates are shown in red with crosses. NAME1 (blue squares) use Mace Head observations only, NAME2 (green square) use observations from 11 sites across Europe including Mace Head. NAME uncertainty is shown with the thin blue lines. Note 1 kt yr-1 is equivalent to 1 Gg yr-1. Nitrous Oxide The main activities in Europe resulting in the release of nitrous oxide are agricultural soils (~60%), chemical industry (~20%) and combustion (~15%) (UNFCCC 1998 figures). The amount emitted from soils has significant uncertainty and has a diurnal and seasonal release cycle. It is driven by the availability of nitrogen, temperature and the soil moisture content. Late in 1998, DuPont introduced technology at its adipic acid plant in Wilton, north east England. It has been estimated that this has cut its emissions of N2O by 90%, from 46 thousand tonne yr-1 to around 6 thousand tonne yr-1 (DEFRA, 2000). Table A8.3.1 shows the NAME-inversion and GHGI emission estimates for the UK for nitrous oxide for the period 1995-2007. The NAME estimates are in excellent agreement with the GHGI estimates throughout the whole time period. Both show declining UK totals (Figure A8.2). The GHGI estimates show a sharp decline (40 Gg) between 1998 and 1999 in line with the introduction of the clean technology at the DuPont plant. The nature of the nitrous oxide emissions challenges the NAME technique assumption of uniformity of release both in time and space. The uncertainty of the NAME estimates is calculated to be (30 Gg yr-1. Also the point of release to the atmosphere may not be coincident with the activity generating the nitrous oxide e.g. the nitrous oxide may be transported from its source, for example by rivers to an ocean, prior to its release to the atmosphere. Table A  STYLEREF 2 \s 8.3. SEQ Table_A \* ARABIC \s 2 1 Verification of the UK emission inventory estimates for nitrous oxide in Ggyr-1 for 1995-2007. NAME uncertainty varies but is approximately (30 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007N2O -NAME1671621401451561401351221071221239486N2O- GHGI173171175173138135127122120121118113111  Figure A8.2 Verification of the UK emission inventory estimates for nitrous oxide in Ggyr-1 for 1995-2007. The blue line with solid square points are the NAME-inversion results and the red line with crosses are the GHGI estimates. The thin lines with no points are the min-max uncertainty of the NAME-inversion results. Hydrofluorocarbons HFC-134a Table A8.4.1 shows the NAME-inversion and GHGI emission estimates for the UK for HFC-134a for the period 1995-2007. The GHGI shows an earlier increase in emission compared to the NAME estimates, the NAME estimates begin their rise in 1999-2000 whereas the GHGI estimates began to rise from 1995 (Figure A8.3). Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 1 Verification of the UK emission inventory estimates for HFC-134a in Gg yr-1 for 1995-2007. The NAME estimates have a calculated error of 0.4 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007HFC-134a NAME1.00.91.01.01.11.61.82.32.42.32.22.73.0HFC-134a GHGI 20070.71.11.62.32.22.62.93.23.53.63.7  Figure A8.3: Verification of the UK emission inventory estimates for HFC-134a in Gg yr-1 for 1995-2007. The NAME estimates are in blue with squares and the GHGI are shown in red with crosses. The thin lines with no points are the min-max uncertainty of the NAME-inversion results. HFC-152a Table A8.4.2 and Figure 8.4 show the NAME and the GHGI emission estimates for the UK for HFC-152a for the period 1995-2007. The agreement between the two datasets is poor. The GHGI shows a steep rise in 1997 whereas the NAME-inversion results show a rise in 2000 but then a fall in 2002 and then a later rise in 2006-2007. Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 2: Verification of the UK emission inventory estimates for HFC-152a in Ggyr-1 for 1995-2007. The NAME estimates have a calculated error of up to 0.06 Gg yr-1 Gas1995199619971998199920002001200220032004200520062007HFC-152a NAME0.030.030.020.020.030.090.100.070.050.040.050.080.11HFC-152a GHGI 20070.030.060.120.160.140.160.170.160.170.160.16  Figure A8.4: Verification of the UK emission inventory estimates for HFC-152a in Ggyr-1 for 1995-2007. The NAME estimates are in blue with squares and the GHGI are shown in red with crosses. The thin lines with no points are the min-max uncertainty of the NAME-inversion results. HFC-125 NAME emission estimates for the UK for HFC-125 for the period 1998-2007 are shown below in Table A8.4.3. The estimates suggest that the emissions of HFC-125 from the UK have been increasing. Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 3: Verification of the UK emission inventory estimates for HFC-125 in Gg yr-1 for 1998-2007. The NAME estimates have a calculated error of 0.10 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007HFC-125 NAME0.280.310.360.380.380.420.490.640.71HFC-365mfc NAME emission estimates for the UK for HFC-365mfc for the period 2004-2007 are shown below in Table A8.4.4. The estimates show a rise and then a fall in the emissions. Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 4: Verification of the UK emission inventory estimates for HFC-365mfc in Gg yr-1 for 2003-2007. The NAME estimates have a calculated error of 0.07 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007HFC-365mfc NAME0.280.510.470.20HFC-143a NAME emission estimates for the UK for HFC-143a for the period 2004-2007 are shown below in Table A8.4.5. The estimates suggest that the emissions of HFC-125 from the UK have been increasing. Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 5: Verification of the UK emission inventory estimates for HFC-143a in Gg yr-1 for 2004-2007. The NAME estimates have a calculated error of 0.1 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007HFC-143a NAME0.500.520.640.66HFC-23 NAME emission estimates for the UK for HFC-23 for 2007 are shown below in Table A8.4.6. Table A  STYLEREF 2 \s 8.4. SEQ Table_A \* ARABIC \s 2 6: Verification of the UK emission inventory estimates for HFC-23 in Gg yr-1 for 2007. The NAME estimates have a calculated error of 0.02 Gg yr-1. Gas1995199619971998199920002001200220032004200520062007HFC-23 NAME0.02 ANNEX 9: IPCC Sectoral Tables of GHG Emissions The tables in this Annex present summary data for UK greenhouse gas emissions for the years 1990-2007, inclusive. The data are given in IPCC reporting format. These data are updated annually to reflect revisions in the methodology and the availability of new information. These adjustments are applied retrospectively to earlier years, which accounts for any differences in data published in previous reports, to ensure a consistent time series. These tables are taken directly from the CRF. Summary Tables Tables A9.1.1 to A9.1.17 present UK GHG emissions as summary reports for national greenhouse gas inventories (IPCC Table 7A).                   Annex 10: Supplementary information for estimates of greenhouse gas emissions by sources and removals by sinks resulting from activities under Article 3.3 and 3.4 of the Kyoto Protocol The supplementary information in this Annex was first provided in the 1990-2005 NIR in accordance with Decisions 15/CP.10 (FCCC/CP/2004/10/Add.2). The UK will use entire commitment period accounting for activities under Article 3.3 and 3.4, reporting in 2014. Progress in the development of methodologies for estimating emissions and removals from such activities are described here. General Information Definition of forest Article 3.3 of the Kyoto Protocol requires Parties to account for Afforestation, Reforestation and Deforestation (ARD) since 1990 in meeting their emissions reduction commitments. The UK has chosen the following definition of forest and single minimum values: A definition of forest as agreed with the Forestry Commission comprising: a minimum area of 0.1 hectares; a minimum width of 20 metres; tree crown cover of at least 20 per cent, or the potential to achieve it; a minimum height of 2 metres, or the potential to achieve it. These single minimum values are used for reporting UK forestry statistics  ADDIN EN.CITE Forestry Commission2006371637Forestry Commission,2006Forestry Statistics 200622/03/2007http://www.forestry.gov.uk/website/ForestStats2006.nsf/(Forestry Commission, 2006) and the UKs greenhouse gas inventory submitted under the UNFCCC. The definitions are consistent with information provided by the UK to the FAO. However, if an international enquiry uses a different minimum definition, for example 0.5 ha in the Global Forest Resource Assessment 2005, the UK areas are adjusted (explicitly or implicitly) to this different definition  ADDIN EN.CITE FAO2005351035FAO2005Global Forest Resources Assessment 2005. United Kingdom of Great Britain and Northern Ireland. Country report.Global Forest Resources Assessment 2005RomeForestry Department, Food and Agriculture Organization of the United Nations64(FAO, 2005). Elected activities under Article 3.4 The UK has chosen to elect Forest Management (FM) as an activity under Article 3.4. In accordance with the Annex to Decision 16/CMP.1, credits from Forest Management are capped in the first commitment period. For the UK the cap is a relatively modest 0.37 MtC (1.36 MtCO2) per year, or 6.78 MtCO2 for the whole commitment period. Description of how the definitions of each activity under Article 3.3 and 3.4 have been implemented and applied consistently over time The areas of forest land reported for AR and FM under the Kyoto protocol equal the area reported under 5A2 (Land converted to Forest Land) in the UNFCCC greenhouse gas inventory. The Afforestation/Reforestation area is land that has been converted to forested land since 1990 (inclusive), while the Forest Management area is the area converted to forest land between 1921 and 1989. In the UK Land converted to Forest Land is considered to stay in that category beyond the 20 year default period in order to take account of the long term soil carbon dynamics. Deforestation since 1990 is taken to be the land area permanently converted from forest land to either grassland or settlement (conversion to cropland is estimated to be negligible based on land use surveys). All ARD and FM definitions are consistent with those used in the UNFCCC inventory and updates to methodologies over time have been back-calculated to 1990 to ensure consistency over time. The afforestation and reforestation datasets are provided by the Forestry Commission and the Forest Service of Northern Ireland (the national forestry agencies) and are consistent with the definition of forest given above. There is an assumption of restocking after harvesting on the national estate, although open habitat can make up 13-20% of stand area on restocking. Therefore, Afforestation and Reforestation under Article 3.3 can be considered together. A felling license is required for felling outside the national forest estate; there is a legal requirement to restock under such a license unless an unconditional felling license is granted (in which case this would be formally reported as deforestation). Information on deforestation activities is assembled from data provided by the Forestry Commission and by the Ordnance Survey (the national cartographic agency) through the UK government. To the best of knowledge, these definitions have been applied consistently over time, although larger uncertainties are associated with deforestation estimates compared with afforestation estimates. Precedence conditions and hierarchy among Art. 3.4 activities Not applicable, as only Forest Management has been elected as an Article 3.4 activity. Land-related information Spatial assessment unit used The spatial assessment units used for the provisional Kyoto Protocol LULUCF tables in 2008 are the four countries of the UK: England, Scotland, Wales and Northern Ireland. A methodology for reporting using units of 20x20km grid cells is in development, where the location of ARD and FM land will be statistically determined for the 853 grid cells covering the UK (GPG LULUCF Reporting Method 1). Each 20x20km cell has a unique identification code produced from the coordinates of the lower left corner of the cell (using the Ordnance Survey British National Grid projection). Methodology used to develop the land transition matrix Several datasets are either available, or will become available, for the assessment of ARD and FM activities in the UK (Table A10.2.1). The UK GHGI currently uses the national planting statistics from 1921 to the present, which are provided by the Forestry Commission and the Northern Ireland Forest Service for each of the countries in the UK. This data is used for the estimation of AR and FM in the submitted LULUCF tables. Estimates of Deforestation are made using the Unconditional Felling Licences and the Land Use Change Statistics (LUCS), a survey of land converted to developed use. The relationship between the national datasets and the land transition matrix is shown in Table A10.2.2. With current methods it is not possible to assess the split in the Deforestation area between areas under Afforestation/ Reforestation and Forest Management although it is reasonable to assume that there will be little Deforestation on areas afforested since 1990. We are in the process of progressing from the situation shown in Table A10.22 to that shown in Table A10.2.3 (using 20km grid scale datasets). Table A  STYLEREF 2 \s 10.2. SEQ Table_A \* ARABIC \s 2 1 Data sources on ARD and FM activities (additional data sources may become available in the future) ActivityDatasetAvailable scaleTime periodDetailsAR & FMAnnual planting statistics Country (England, Scotland, Wales, Northern Ireland) 1921-presentNew planting on previously non-forested land. Updated annually. Categorized into conifer and broadleaved woodland. ARGrant-aided woodland databaseLocal administrative unit/NI counties 1995-presentPrivate woodland planted with grant aid since 1995. Categorized into conifer and broadleaved planting.AR & FMForestry Commission management database20km grid cells1995-presentDatabase of state woodland planting since 1995, indicating the rotation (1st rotation will be Afforestation, 2nd or greater rotations are restocking). Categorised by species.AR & FMNational Inventory of Woodland and Trees (NIWT)20km grid cells (sample statistics)1995Grid cell database includes the area and planting decade of each species within the grid cell. A digital map of woodland over 2ha is also available.ARD, FMNIWT220km grid cells (sample statistics)Planned for 2009-2017Update of the 1995 NIWT. A partial repeat of the grid cell analysis should be available by 2013. An update of the digital map will be available, initially from 2009, which can be used to asses deforestation since NIWT1.DForestry Commission Unconditional Felling Licence dataEngland only (data from other countries should become available)1990-2002Unconditional Felling Licences are issued for felling without restocking. Used to estimate deforestation in rural areas (primarily for heathland restoration). English data is extrapolated to GB scale and to current reporting year. Omits felling for development purposes, e.g. construction of wind turbines.DLand Use Change Statistics (survey of land converted to developed uses)England only (data from other countries should become available)1990-2003 (updated in 2007)Estimates of the conversion of forest to urban/developed land use. Based on Ordnance Survey map updates, identifying changes through aerial surveys and other reporting, expected to capture most changes within five years. English data is extrapolated to GB scale and to current reporting year. Table A  STYLEREF 2 \s 10.2. SEQ Table_A \* ARABIC \s 2 2 Land transition matrix using national datasets To FromArticle 3.3Article 3.4Afforestation/ ReforestationDeforestationForest ManagementAfforestation/Reforest-ationNew planting since 1990 (national planting statistics).Not estimated at present.DeforestationUnconditional felling licences/LUCSForest ManagementUnconditional felling licences/LUCSForest planted 1921-1989 (national planting statistics) and NIWT. Table A  STYLEREF 2 \s 10.2. SEQ Table_A \* ARABIC \s 2 3 Proposed land transition matrix with the 20km grid for end of commitment period accounting To FromArticle 3.3Article 3.4Afforestation/ ReforestationDeforestationForest ManagementAfforestation/Reforest-ation1990-1995: national planting statistics, spatially distributed in proportion to NIWT data on planting in 1990s. 1995-2012: FC management database and grant-aided woodland database.Comparison between NIWT and NIWT2 forest cover map. Unconditional felling licences. DeforestationNIWT vs. NIWT2 forest cover map.Forest ManagementNIWT vs. NIWT2 forest cover map. Unconditional felling licencesUse NIWT and NIWT2. Identification of geographical locations National spatial units have been used for the 2008 voluntary submission (Figure A10.1): the proposed units for future submissions (when a suitable electronic submission format is made available) are also shown.  SHAPE \* MERGEFORMAT  SHAPE \* MERGEFORMAT Figure A10-  SEQ Figure_A10- \* ARABIC 1: Spatial units used for reporting Kyoto protocol LULUCF activities: (left) the four countries of the UK, (right) 20 x 20km grid cells covering the UK. Activity-specific information Methods for carbon stock change and GHG emission and removal estimates Description of methodologies and assumptions Carbon uptake by UK forests is estimated by a carbon accounting model, C-Flow ( ADDIN EN.CITE Dewar19923103149-71<Go to ISI>://A1992JF38800004Dewar, R. C.Cannell, M. G. R.Carbon Sequestration in the Trees, Products and Soils of Forest Plantations - an Analysis Using Uk ExamplesTree PhysiologyTree Physiol.1992Jul111INST TERR ECOL,BUSH ESTATE,PENICUIK EH26 0QB,MIDLOTHIAN,SCOTLAND DEWAR RC INST TERR ECOL,BUSH ESTATE,PENICUIK EH26 0QB,MIDLOTHIAN,SCOTLANDISI:A1992JF38800004Cannell19951201235-48<Go to ISI>://A1995QH54500004Cannell, M. G. R.Dewar, R. C.The Carbon Sink Provided by Plantation Forests and Their Products in BritainForestrystorage; trees; soils; co2Forestry1995681INST TERR ECOL,BUSH ESTATE,PENICUIK EH26 0QB,MIDLOTHIAN,SCOTLAND CANNELL MGR INST TERR ECOL,BUSH ESTATE,PENICUIK EH26 0QB,MIDLOTHIAN,SCOTLANDISI:A1995QH54500004Milne199858058Milne, RBrown, T. A. W.Murray, T. D.1998The effect of geographical variation in planting rate on the uptake of carbon by new forests of Great BritainForestry71298-309Cannell and Dewar, 1995; Dewar and Cannell, 1992; Milne et al., 1998). The model estimates the net change in pools of carbon in standing trees, litter and soil in conifer and broadleaf forests. The methodologies and assumptions are described in the UKs National Inventory Report, Annex 3.7. The C-Flow model was originally set up in Microsoft Excel to run at the national scale. The model has now been moved to the Matlab programming environment and modified to run with spatially disaggregated input data (20km grid cells in this instance). C-Flow is used to estimate carbon stock changes from Article 3.3 Afforestation/Reforestation and Article 3.4 Forest Management. The next stage is the construction of the activity dataset on an annual basis from the various spatially disaggregated data sources. This has initially been done for Article 3.3 Afforestation/Reforestation. The ArcMap geographical information system was used for this work. There are still some issues to resolve between national and regional annual planting totals, so at present the spatially disaggregated data is used to weight the distribution of the national planting totals across the 20km cells, rather than using the spatially disaggregated data directly. Great Britain state and private planting 1990-1995. Records of state/private planting in the decade since April 1990 were extracted from the National Inventory of Woodland and Trees (NIWT) for each 20km cell. These records include large areas of restocking as well as new planting, so the area of new planting per cell was estimated using ratios of new planting to restocking for broadleaf/conifer and state/private woodland. These ratios were obtained from published forest statistics reports and the Forestry Commission planting database (1995 onwards). The areas of planting were used to assign a weight to each cell for each country (England, Scotland and Wales): these weights were then used to distribute the national annual planting area (1990-1995) across all cells. Northern Ireland state and private planting 1990-1996. The NIWT does not cover Northern Ireland so the only planting areas are available are the national ones. Forest cover is not evenly distributed in Northern Ireland, with the dominant conifer plantations concentrated in the western uplands. The national planting areas were distributed across the country using a 20 km cell weighted distribution based on the size and location of state-owned forests (Forest Service Facts & Figures 2001/02 and the Forest Service website  HYPERLINK "http://www.forestserviceni.gov.uk/" http://www.forestserviceni.gov.uk/). This approach is not ideal, because the forest distribution only reflects that of state forests in 2001, and more appropriate data will be sought. Great Britain state planting 1995- present. The Forestry Commission Sub-Compartment Database (SCDB) was used to estimate state afforestation from 1995 onwards. The SCDB is the stand management database for state-owned and managed forest, containing information on species, age, yield class and management, and spatially referenced by 20km cells. Records of annual new planting areas were extracted for conifer and broadleaf planting. The areas of planting were used to assign a weight to each cell for each country (England, Scotland and Wales): these weights were then used to distribute the national annual planting area across all cells. Great Britain private planting 1995- present. Woodland Grant Schemes (WGS) is the schemes by which the government (i.e. the Forestry Commission) encourages planting and management of private woodland. They covers almost all private woodland planting since 1995: there is a small amount of non-grant aided woodland (mostly in England) which is assumed to be broadleaved natural regeneration but we have no further information on the management or permanence of this area. Information on planting under the WGS is available for each country in Great Britain, split by new planting and restocking. The information provided is the area for which new planting grants have been paid and the planting has actually been completed. The FC will not pay grants prior to the planting taking place so we know that the areas are therefore all stocked. Conifer and broadleaf planting is split by NUTS4 administrative regions (local authority areas). The planting areas were re-assigned in proportion to the appropriate co-incident 20km cells. The areas of planting were used to assign a weight to each cell for each country (England, Scotland and Wales): these weights were then used to distribute the national annual planting area across all cells. Northern Ireland state and private planting 1996-2006. New data was not available for reporting the 2007 values, and has therefore not been updated. Northern Ireland will be making the data available annually for the whole commitment period of the Kyoto Protocol reporting period. Information is available on the areas planted annually under the Northern Ireland Woodland Grant Scheme since 1996. These are reported by the old county districts for 1996-2006 (Antrim, Armagh, Down, Fermanagh, Derry and Tyrone) and by NUTS4 district for 2006. The planting areas were re-assigned in proportion to the appropriate co-incident 20km cells. Information on the relative distribution of conifer and broadleaf planting was only available in 2006, otherwise the same distribution is assumed for both forest types. No specific information was available on the distribution of state planting. The 20km cell weighting for private woodland planting was used to distribute the national annual planting area across all cells. The methods and data sources for Northern Ireland will be kept under review. These separate activity datasets were combined into spatial annual planting series for conifer and broadleaf woodland from 1990 to 2006. The maps of cumulative planting to 2006 are shown in  REF _Ref199756387 \h  \* MERGEFORMAT Figure A10- 2. The differences in afforestation distribution between conifer and broadleaf woodland and between countries can be seen clearly. Figure A10-  SEQ Figure_A10- \* ARABIC 2: Cumulative planting 1990-2007 of broadleaf and conifer woodland, ha The combined spatial planting series were run in the new Matlab version of the CFlow accounting model. This produces preliminary estimates of carbon stock changes due to Article 3.3 Afforestation ( REF _Ref199758390 \h  \* MERGEFORMAT Figure A10- 3). It should be noted that this methodology still needs further development. The initial results are interesting, with most of the carbon sink located in Scotland although the National Forest (in the English Midlands), where there has been extensive planting in the past decade, also shows up on the map. The small carbon source in the Shetland Islands (in the far north of the UK) is probably due to planting disturbance of organic soils, although this requires further investigation. The methods currently used for the reporting of Article 3.3 Deforestation and Article 3.4 Forest Management are those reported in the NIR. Progress in method development for these activities will be described in future annexes.  Figure A10-  SEQ Figure_A10- \* ARABIC 3: Carbon stock changes due to Article 3.3 Afforestation in the UK 1990-2007, Gg CO2 Justification for omitting pools or fluxes The below-ground biomass and dead wood carbon pools are currently not reported separately but included in the soil and litter carbon pools respectively. It may be possible to modify the C-Flow model so that it produces estimates for these carbon pools for future reporting. The area included in Forest Management only includes those areas of forest that were newly planted between 1921 and 1990 (1394 kha or c.50% of the UK forest area). The area of forest established before 1920 (c. 820 kha) is reported in the CRF for the national greenhouse gas inventory but is assumed to be in carbon balance, i.e. zero flux. Uncertainty as to the management and date of first establishment of pre-1921 woodlands (which are predominantly broadleaf) makes it difficult to estimate appropriate model parameters. The omission of pre-1920 forests will have no effect on the number of credits that the UK can claim under Article 3.4, as these are capped for the first commitment period. Nitrous oxide emissions from N fertilization of newly planted forest land on poor soils are now included (see the NIR for further details). The Forestry Commission has estimated liming of forests and N fertilisation of established forest land to be negligible due to economic factors, so emissions from these activities are not currently estimated. Emissions of N2O from areas in Forest Management due to the drainage of soils are not currently estimated, although a methodology is under consideration (NIR Annex 3.7). Emissions of greenhouse gases due to biomass burning are estimated for Deforestation. Hopefully, biomass burning will diminish as the use of woodfuel as a source of bioenergy becomes more commonplace. Emissions due to forest wildfires are now included (see the NIR for further details). At present, it is assumed that all wildfires occur on Forest Management land. Assessing the impact of wildfires on AR forests is methodologically complex under the UKs current approach and wildfires would only affect a very small area of AR land area (less than 1% since 1990) if the burnt areas are distributed in proportion to forest. It can be assumed that wildfires will not result in permanent deforestation. This area will be kept under review. Factoring out The CFlow model in principle assumes constant weather and management conditions and therefore factoring out of such influences is not required. Recalculations since last submission Emissions from N fertilisation of newly planted forests and emissions from forest wildfires have been included. Carbon stock changes in afforested soils are now calculated differently as a result of the disaggregation of the C-Flow model from national to 20km scale. At the national scale a simple country-specific model is used to split new planting between organic and mineral soils. The disaggregated version of C-Flow uses the Defra soil carbon database (Bradley et al. 2005) to estimate the proportion of planting on organic or mineral soils in each 20km square. As a result the model assigns less planting to organic soils (particularly in Scotland), which results in a small reduction in the soil carbon stock change compared with previous estimates (3-10 Gg CO2 in 2000-2006). Uncertainty estimates To be decided. A full uncertainty analysis of the LULUCF sector in the UNFCCC greenhouse gas inventory will be completed by 2009: improved uncertainty estimates for Article 3.3 and 3.4 activities will be derived from this work. Information on other methodological issues Measurement intervals. Emissions and removals are reported annually but compiled from data sources with different measurement intervals. For Afforestation/ Reforestation land the national planting statistics are produced annually and disaggregated to the 20km scale using regional datasets. The regional datasets are also produced annually but there are discrepancies between the national and regional planting totals that have yet to be resolved, hence the continued use of the more reliable national dataset. The statistics are reported by planting year, which runs from the 1st April of the previous year to the 31st March of the reported year, i.e. the 2001 planting year was 1st April 2000 to 31st March 2001. These statistics are adjusted to calendar years in order to be compliant with the Kyoto Protocol regulations. This adjustment has the effect of slightly smoothing the planting series and has no effect on the area of forest planted overall. The annual planting series drives the model C-Flow, which produces outputs at the annual scale (see NIR Annex 3.7. for more detail). The Deforestation activity data is estimated using a five year running mean. The Forest Management areas come from the annual national planting statistics. The estimated numbers will be verified using the NIWT (1995-1998) and preliminary results from NIWT2 (2009-2017). Choice of methods. The methods used to estimate emissions and removals from Deforestation and Forest Management activities are the same as those used in the UNFCCC inventory. Developments in the methods used for Kyoto Protocol reporting will be incorporated into the UNFCCC inventory reporting in due course. Disturbances. Emissions from forest wildfires were included in the UNFCCC inventory for the first time in 2008. Data is available on fire damage to state-managed forests and extrapolated to privately-managed forests (see the NIR for further details on the method and assumptions). There is no data available on the type of forest burnt by wildfires (species or age) or wildfire locations within each country of the UK. Wildfires are not assumed to result in a permanent change in land use. Damage from windblow is not reported in the UNFCCC inventory, although it does occur in the UK  ADDIN EN.CITE Forestry Commission2002361036Forestry Commission,2002UK Indicators of Sustainable ForestryEconomics and Statistics Unit, Forestry Commission/Forest ServiceFAO2005351035FAO2005Global Forest Resources Assessment 2005. United Kingdom of Great Britain and Northern Ireland. Country report.Global Forest Resources Assessment 2005RomeForestry Department, Food and Agriculture Organization of the United Nations64(FAO, 2005; Forestry Commission, 2002). There are currently insufficient data to include the effects of these disturbances in the inventory although this is being kept under review and a methodology will be developed in time. Inter-annual variability. The method used to estimate emissions and removals from AR and FM is based on the C-Flow model. This model is not sensitive to inter-annual variation in environmental conditions so these will not affect the annual growth and decay rates. There is an ongoing research project to look at the variation in management conditions across the UK forest estate and over time. The area burnt in wildfires does show inter-annual variation and this is included in the emissions methodology. Where data is missing from the annual time series a Burg regression equation is used to extrapolate the trend over the previous ten years. Accounting issues Not applicable for this submission. Article 3.3 Information that demonstrates that activities began after 1990 and before 2012 and are directly human-induced Under the current methodology, the Forestry Commission and the Forest Service of Northern Ireland provide annual data on new planting (on land that has not previously been forested). This information is provided for each country in the UK and the time series extends back before 1990. Data are provided for both state and private woodlands: the private woodland planting is divided between grant-aided and non-grant-aided. Estimates of non-grant-aided woodland planting and restocking are reported annually, for inclusion in planting statistics, although the Forestry Commission have doubts about their completeness and accuracy Their assessment is that non-grant-aided new woodland has arisen by natural regeneration and is all broadleaved. This assumption can be verified against the NIWT2 at a later date. Only state and grant-aided woodland areas are currently included in the assessment of Article 3.3 activities as these are directly human-induced. Information on how harvesting or forest disturbance followed by re establishment is distinguished from deforestation The data sources used for estimating Deforestation do not allow for confusion between harvesting or forest disturbance and deforestation. The unconditional felling licences used for the estimation of rural deforestation are only given when no restocking will occur, and the survey of land converted to developed use describes the conversion of forest land to the settlement category, which precludes re-establishment. The NIWT2, which will be partially completed by the end of the first commitment period, will be used to verify deforestation estimates made using these data sources. Information on the size and location of forest areas that have lost forest cover but are not yet classified as deforested Restocking is assumed for forest areas that have lost forest cover through harvesting or forest disturbance, unless there is deforestation as described above. As such, information on the size and location of forest areas that have lost forest cover is not explicitly collected. However, it should be possible to assess such areas through the comparison of the NIWT and NIWT2 at the end of the first commitment period. Article 3.4 Information that demonstrates that activities have occurred since 1990 and are human-induced All managed forests (planted between 1921 and 1989) are included in this category. The C-Flow model is used to calculate emissions from this forest area after 1990 that have arisen from thinning, harvesting and restocking. A current research project is examining the impact of management upon carbon stock changes in UK forests in more detail. Information relating to Forest Management: (i) that the forest definition is consistent; and (ii) that forest management is a system of practices for stewardship and use of forest land aimed at fulfilling relevant ecological, economic and social functions of the forest in a sustainable manner Data used for estimating emissions from Forest Management is supplied by the Forestry Commission and complies with their definition of forest land, which is the one used for Article 3.3 and 3.4 activities. The UK has a system of certification for sustainable woodland management under the Forest Stewardship Council (FSC). Forest statistics published in 2006 by the Forestry Commission record that 73% of softwood removals in 2005 were from certified sources. Such removals will almost entirely come from post-1920 conifer woodland reported under Forest Management. The management practices in certified woodlands are reviewed annually. All state-owned forests are certified and an increasing proportion of non-state-owned woodlands are becoming certified. The total certified area in March 2007 was 1276 kha  ADDIN EN.CITE Forestry Commission2006371637Forestry Commission,2006Forestry Statistics 200622/03/2007http://www.forestry.gov.uk/website/ForestStats2006.nsf/(Forestry Commission, 2007). This does not include all woodland that is managed in a sustainable manner, such as smaller or non-timber producing woodlands where certification is not considered worthwhile. In particular, it may omit many broadleaved woodlands even though they are managed for their social and environmental benefits  ADDIN EN.CITE Forestry Commission2002361036Forestry Commission,2002UK Indicators of Sustainable ForestryEconomics and Statistics Unit, Forestry Commission/Forest Service(Forestry Commission, 2002). In the UKs country report to the Global Forest Resource Assessment 2005  ADDIN EN.CITE FAO2005351035FAO2005Global Forest Resources Assessment 2005. United Kingdom of Great Britain and Northern Ireland. Country report.Global Forest Resources Assessment 2005RomeForestry Department, Food and Agriculture Organization of the United Nations64(FAO, 2005) 83% of UK forests are managed for production, 18% are managed for conservation of biodiversity (these have protected status) and 55% have a social service function (public access). Other information Key category analysis At present all categories relating to Article 3.3 and Forest Management under Article 3.4 are considered to be key categories. Afforestation and Reforestation activities are a component of the key UNFCCC category 5A2 and removals from this category are also likely to increase over time as a result of tree planting schemes partially focussed on climate change mitigation. Deforestation is the only significant net source in the Kyoto Protocol inventory and the data used in the reporting of deforestation are probably the most uncertain of the data sources used. Forest Management is the majority component of the key UNFCCC category 5A2 and is therefore a key category based on contribution alone. Information relating to Article 6 Not applicable to UK forests. Annex 11: End User Emissions Introduction This Annex explains the concept of a final user or end user, summarises the final user calculation methodology with examples, and contains tables of greenhouse gas emissions according to final user from 1990 to 2007. The final user sectoral categories used are consistent with those used in the National Communications (NC) to the FCCC. The sectoral categories in the NC are derived from the UNFCCC reporting guidelines on national communications. The purpose of the final user calculations is to allocate emissions from fuel and electricity producers to the energy users - this allows the emission estimates for a consumer of energy to include the emissions from the production of the fuel or electricity they use. The UNFCCC does not require final user data to be included in the UKs National Inventory Report. These data have been included to provide DECC with information for their policy support needs. The tables in this Annex present summary data for UK greenhouse gas emissions for the years 1990-2007, inclusive. These data are updated annually to reflect revisions in the methods used to estimate emissions, and the availability of new information. These recalculations are applied retrospectively to earlier years to ensure a consistent time series and this accounts for any differences in data published in previous reports. Emissions from the UK Overseas Territories have been included in the totals as a separate row. There is not enough information available to reallocate emissions from energy supply in the Overseas Territories. Definition of final users The final user or end user calculations allocate emissions from fuel producers to fuel users. The final user calculation therefore allows estimates to be made of emissions for a consumer of fuel, which also include the emissions from producing the fuel the consumer has used The emissions included in the final user categories can be illustrated with an example of two final users - the residential sector and road transport: Emissions in the residential final user category include: Direct emissions from domestic premises, for example, from burning gas, coal or oil for space heating. Emissions from power stations generating the electricity used by domestic consumers; emissions from refineries including refining, storage, flaring and extraction; emissions from coal mines (including emissions due to fuel use in the mining industry itself and fugitive emissions of methane from the mines); and emissions from the extraction, storage and distribution of mains gas. Emissions in the road transport final user category include: Direct emissions from motor vehicle exhausts. Emissions refineries producing motor fuels, including refining, storage, flaring and extraction of oil; and from the distribution and supply of motor fuels. Overview of the final users calculations As fuel and electricity producers use energy from other producers, they are allocated emissions from each other and these have to then be reallocated to final users. This circularity results in an iterative approach being used to estimate emissions from categories of final users. FigureA11.1 shows a simplified view of the energy flows in the UK (the fuels used in the greenhouse gas inventory have hundreds of uses). This figure shows that while final users consuming electricity are responsible for a proportion of the emissions from power stations they are also responsible for emissions from collieries, and some of these emissions in turn come from electricity generated in power stations and from refineries. Figure A11.1: Simplified fuel flows for a final user calculation.  EMBED Visio.Drawing.6  The approach for estimating end user emissions is summarised in the three steps below: Emissions are calculated for each sector for each fuel. Emissions from fuel and electricity producers are then distributed to those sectors that use the fuel according to the energy content of the fuel they use (these sectors can include other fuel producers). By this stage in the calculation, emissions from final users will have increased and those from fuel and electricity producers will have decreased. The sum of emissions from fuel producers and power stations in a particular year as a percentage of the total emissions is then calculated. If this percentage, for any year, exceeds a predetermined value (e.g. 1% or 0.01%) the process continues at Step2. If this percentage matches or is less than the predetermined value, the calculation is finished. Convergence of this iterative approach is likely, as the fuel flows to the final users are much greater than fuel flows amongst the fuel producers. While a direct solution could possibly be used (for example, after defining a system of linear equations and solving by an inverse matrix or Gaussian elimination) it was decided to base the calculation on an iterative approach because: This can be implemented in the database structures already in existence for the UK greenhouse gas inventory; It can handle a wide range of flows and loops that occur without any of the limits that other approaches may incur; and The same code will cover all likely situations and will be driven by tabular data stored in the database. Example final user calculation The following example illustrates the methodology used to calculate emissions according to final users. The units in this example are arbitrary and sulphur dioxide has been used in the example. The example in FigureA11.2 has two fuel producers, power stations and collieries, and three final users, residential, industry and commercial. The following assumptions have been made for simplicity: The only fuels used are coal and electricity; Coal is the only source of sulphur dioxide emissions (released from burning coal in power stations to produce electricity and from burning coal in the home for space heating); and Commerce uses no coal and so has zero direct emissions. Figure A11.2: Fuel use in the example calculation  EMBED Visio.Drawing.5  In FigureA11.2, the tonnes refer to tonnes of coal burnt (black arrows), and the units refer to units of electricity consumed (blue arrows). In this example the coal extracted by the colliery is burnt in the power station to produce electricity for the final users. Industrial and residential users also directly burn coal. Although the colliery uses electricity produced by the power station, it is not considered to be a final user. The colliery is a fuel producer as it is part of the chain that extracts, processes and converts fuels for the final users. TableA11.4.1 summarises the outputs during this example final user calculation. Table A  STYLEREF 2 \s 11.4. SEQ Table_A \* ARABIC \s 2 1 Example of the outputs during a final user calculation SectorCollieryPower StationResidentialIndustrialCommercialUnallocated emissions as percentage of total emissionTotal emission of SO2 (tonnes)Coal use (tonnes)Mass100100,00050,000100,0000Energy content25,00025,000,00012,500,00025,000,0000Electricity use (arbitrary units)Energy units10,00050,000100,000100,000Emissions of SO2 (tonnes)Initial1.001000.00500.001000.000.0040.022501.00Emissions after Iteration step138.460.40692.511385.02384.621.552501.0020.0215.38700.281400.55384.770.622501.0030.590.01703.241406.48390.690.022501.0040.000.24703.361406.72390.690.012501.0050.010.00703.401406.81390.780.002501.0060.000.00703.411406.81390.780.002501.00 The initial sulphur dioxide emissions are 1% of the mass of coal burnt. The emissions from the power stations are distributed to the other sectors by using the factor: (Electricity used by that sector)/(total electricity used minus own use by power stations); Similarly for the colliery emissions the following factor is used; and (Energy of coal used by that sector)/(total energy of coal consumed used minus own use by collieries). At the end of iteration step one, the commerce sector has 384.62 tonnes of sulphur dioxide emissions allocated to it, mainly from derived from power stations. Emissions allocated to the residential and industry sectors have also increased over their initial allocations. However collieries and power stations still have some emissions allocated to them (these come from each other) and so the reallocation process is repeated to reduce these allocations to zero these two sectors are not final users. The total unallocated (in this example, equal to the total emissions from collieries and power stations) falls in each iteration until the emissions are consistently allocated across the sectors. In this example, six iterations are needed to achieve a consistent allocation across the sectors. The sum of emissions allocated to the sectors (2501.00tonnes of sulphur dioxide) remains unchanged from the initial allocation to the allocation in the sixth iteration. This check is an important quality control measure to ensure all emissions are accounted for during the final user calculations. Figure A11.3: Comparison of direct and final user emissions of sulphur dioxide according the sectors considered in the final user example  FigureA11.3 compares the quantities of direct and final user sulphur dioxide emitted from each sector at the end of the final user calculation. The direct emissions of sulphur dioxide are from the combustion of coal in the sectors. The direct and final user emissions are from two distinct calculations and must be considered independently in other words, the direct and final user emissions in each sector must not be summed. The sum of all the direct emissions and the sum of the final user emissions, are identical. There are relatively large direct emissions of sulphur dioxide from power stations, residential and industry sectors. The final user emissions from the power stations and the colliery are zero because these two sectors are not final users. The sulphur dioxide emissions from these two sectors have been reallocated to the residential, industrial and commercial sectors. This reallocation means the final user emissions for the residential and industrial sectors are greater than their direct emissions. Final user calculation methodology for the UK greenhouse gas inventory The approach divides fuel user emissions into 7 categories (see column 1 of TableA11.5.1). For each of these groups, source categories are distributed by the total energy consumption of a group of fuels. For example, for the coal group, the emissions of four source categories are distributed to final users according to the energy use of anthracite and coal combined. Table A  STYLEREF 2 \s 11.5. SEQ Table_A \* ARABIC \s 2 1: Sources reallocated to final users and the fuels used Final user groupEmission sources to be reallocated to final usersFuels used for redistribution1. CokeGasification processesCokeCoke production2. CoalCoal storage & transportCoalCollieriesAnthraciteDeep-mined coalOpen-cast coal3. Natural gasGas separation plant (combustion)Natural gasGas leakageGas production4. ElectricityNuclear fuel productionElectricityPower stations5. PetroleumOff shore flaringNaphthaOffshore loadingBurning oil (premium)Offshore oil & gas (venting)Burning oilOffshore oil & gas (well testing)Aviation turbine fuelOffshore oil and gasAviation spiritOffshore own gas useDervOil terminal storageFuel oilOnshore loadingGas oilPetroleum processesOPGRefineries (Combustion)Refinery misc.Refineries (drainage)PetrolRefineries (flares)Petroleum cokeRefineries (process)Wide-cut gasolineRefineries (road/rail loading)Vaporizing oilRefineries (tankage)LPGRefinery (process)Ship purging6. Solid Smokeless FuelsSolid Smokeless fuel productionSolid Smokeless Fuels7. Town gasTown gas manufactureTown gas Comments on the calculation methodology used to allocate emissions according final users are listed below: Emissions are allocated to final users on the basis of the proportion of the total energy produced used by a given sector. This approach is followed to allow for sectors such as petroleum where different products are made in a refinery; Some emissions are allocated to an exports category. This is for emissions within the UK from producing fuels, (for example from a refinery or coal mine), which are subsequently exported or sent to bunkers for use outside the UK. Therefore these emissions are part of the UK inventory even if the use of the fuel produces emissions that cannot be included in the UK inventory because it takes place outside the UK; No allowance is made for the emission from the production of fuels or electricity outside the UK that are subsequently imported; Some of the output of a refinery is not used as a fuel but used as feedstock or lubricants. This is not currently treated separately and the emissions from their production (which are small) are allocated to users of petroleum fuels. This is partly due to lack of data in the database used to calculate the inventory, and partly due to the lack of a clear, transparent way of separating emissions from the production of fuels and from the production of non-fuel petroleum products; and Final user emissions are estimated for aviation in four categories: domestic take off and landing, international take off and landing, domestic cruise and international cruise. This enables both IPCC and UNECE categories to be estimated from the same final user calculation. Our exact mapping of final user emissions to IPCC categories is shown in the following table. The NAEI source sectors and activity names are also shown, as it is necessary to subdivide some IPCC categories. This classification has been used to generate the final user tables for the greenhouse gases given in this section. As this table is for final users, no fuel producers are included in the table. Table A  STYLEREF 2 \s 11.5. SEQ Table_A \* ARABIC \s 2 2: Final user category, IPCC sectors, and NAEI source names and activity names used in the emission calculation NCFormatIPCCSourceNameActivityNameAgriculture1A4ci_Agriculture/Forestry/Fishing:StationaryAgriculture - stationary combustionCoalFuel oilNatural gasStraw1A4cii_Agriculture/Forestry/Fishing:Off-roadAgricultural enginesLubricantsAgriculture - mobile machineryGas oilPetrol2B5_Chemical_Industry_OtherAgriculture - agrochemicals useCarbon in pesticides4A10_Enteric_Fermentation_DeerAgriculture livestock - deer entericNon-fuel combustion4A1a_Enteric_Fermentation_DairyAgriculture livestock - dairy cattle entericNon-fuel combustion4A1b_Enteric_Fermentation_Non-DairyAgriculture livestock - other cattle entericNon-fuel combustion4A3_Enteric_Fermentation_SheepAgriculture livestock - sheep entericNon-fuel combustion4A4_Enteric_Fermentation_GoatsAgriculture livestock - goats entericNon-fuel combustion4A6_Enteric_Fermentation_HorsesAgriculture livestock - horses entericNon-fuel combustion4A8_Enteric_Fermentation_SwineAgriculture livestock - pigs entericNon-fuel combustion4B12_Liquid_SystemsAgriculture livestock - manure liquid systemsNon-fuel combustion4B13_Solid_Storage_and_DrylotAgriculture livestock - manure solid storage and dry lotNon-fuel combustion4B14_OtherAgriculture livestock - manure otherNon-fuel combustion4B1a_Manure_Management_DairyAgriculture livestock - dairy cattle wastesNon-fuel combustion4B1b_Manure_Management_Non-DairyAgriculture livestock - other cattle wastesNon-fuel combustion4B3_Manure_Management_SheepAgriculture livestock - sheep goats and deer wastesNon-fuel combustion4B4_Manure_Management_GoatsAgriculture livestock - goats wastesNon-fuel combustion4B6_Manure_Management_HorsesAgriculture livestock - horses wastesNon-fuel combustion4B8_Manure_Management_SwineAgriculture livestock - pigs wastesNon-fuel combustion4B9_Manure_Management_PoultryAgriculture livestock - broilers wastesNon-fuel combustionAgriculture livestock - laying hens wastesNon-fuel combustionAgriculture livestock - other poultry wastesNon-fuel combustion4B9a_Manure_Management_DeerAgriculture livestock - deer wastesNon-fuel combustion4D_Agricultural_SoilsAgricultural soilsNon-fuel cropsNon-fuel fertilizer4F1_Field_Burning_of_Agricultural_ResiduesField burningBarley residueOats residueWheat residue4F5_Field_Burning_of_Agricultural_ResiduesField burningLinseed residuenon-IPCCAgriculture - stationary combustionElectricityBusiness1A2a_Manufacturing_Industry&Construction:I&SBlast furnacesBlast furnace gasCoke oven gasLPGNatural gasIron and steel - combustion plantBlast furnace gasCoalCokeCoke oven gasFuel oilGas oilLPGNatural gas1A2f_Manufacturing_Industry&Construction:OtherAmmonia production - combustionNatural gasAutogeneratorsCoalNatural gasCement production - combustionCoalFuel oilGas oilNatural gasPetroleum cokeScrap tyresWasteWaste oilsWaste solventLime production - non decarbonisingCoalCokeNatural gasOther industrial combustionBurning oilCoalCokeCoke oven gasColliery methaneFuel oilGas oilLPGLubricantsNatural gasOPGSSFWood1A2fii_Manufacturing_Industry&Construction:Off-roadIndustrial enginesLubricantsIndustrial off-road mobile machineryGas oilPetrol1A4a_Commercial/InstitutionalMiscellaneous industrial/commercial combustionCoalFuel oilGas oilLandfill gasMSWNatural gas1A4ci_Agriculture/Forestry/Fishing:StationaryMiscellaneous industrial/commercial combustionBurning oil2B5_Carbon from NEU of productsOther industrial combustionEnergy recovery - chemical industry2C1_Iron&SteelBlast furnacesCoal2F1_Refrigeration_and_Air_Conditioning_EquipmentCommercial RefrigerationRefrigeration and Air Conditioning - DisposalRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - ManufactureDomestic RefrigerationRefrigeration and Air Conditioning - DisposalRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - ManufactureIndustrial RefrigerationRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - ManufactureMobile Air ConditioningRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - ManufactureRefrigerated TransportRefrigeration and Air Conditioning - DisposalRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - ManufactureStationary Air ConditioningRefrigeration and Air Conditioning - DisposalRefrigeration and Air Conditioning - LifetimeRefrigeration and Air Conditioning - Manufacture2F2_Foam_BlowingFoamsNon-fuel combustion2F3_Fire_ExtinguishersFirefightingNon-fuel combustion2F5_SolventsPrecision cleaning - HFCNon-fuel combustion2F8_Other_(one_component_foams)One Component FoamsNon-fuel combustion2F8_Other_(semiconductors_electrical_sporting_goods)Electrical insulationNon-fuel combustionElectronics - PFCNon-fuel combustionElectronics - SF6Non-fuel combustionSporting goodsNon-fuel combustionnon-IPCCIron and steel - combustion plantElectricityMiscellaneous industrial/commercial combustionElectricityOther industrial combustionElectricityEnergy Supply1A1a_Public_Electricity&Heat_ProductionPower stationsCoalFuel oilGas oilNatural gasPetroleum coke1A1b_Petroleum_RefiningRefineries - combustionNatural gas1A1ci_Manufacture_of_Solid_Fuels-cokeCoke productionNatural gasSolid smokeless fuel productionCoke1A1cii_Other_Energy_IndustriesCollieries - combustionNatural gasGas productionLPGGas separation plant - combustionLPGOPGNuclear fuel productionNatural gasOffshore oil and gas - own gas combustionNatural gas1B1b_Solid_Fuel_TransformationCoke productionCoalSolid smokeless fuel productionCoalnon-IPCCCollieries - combustionElectricityGas productionElectricityRefineries - combustionElectricityExports1A3di_International_MarineShipping - international IPCC definitionFuel oilGas oilAviation_BunkersAircraft - international cruiseAviation spiritAviation turbine fuelAircraft - international take off and landingAviation spiritAviation turbine fuelnon-IPCCExportsAviation turbine fuelBurning oilCokeDERVElectricityFuel oilPetrolSSFIndustrial Process1A2a_Manufacturing_Industry&Construction:I&SSinter productionCoke2A1_Cement_ProductionCement - decarbonisingClinker production2A2_Lime_ProductionLime production - decarbonisingLimestone2A3_Limestone_&_Dolomite_UseBasic oxygen furnacesDolomiteGlass - generalDolomiteLimestoneSinter productionDolomiteLimestone2A4_Soda_Ash_Production_&_UseGlass - generalSoda ash2A7_(Fletton_Bricks)Brick manufacture - FlettonFletton bricks2B1_Ammonia_ProductionAmmonia production - feedstock use of gasNatural gas2B2_Nitric_Acid_ProductionNitric acid productionAcid production2B3_Adipic_Acid_ProductionAdipic acid productionAdipic acid produced2B5_Chemical_Industry_OtherChemical industry - ethyleneEthyleneChemical industry - generalProcess emissionChemical industry - methanolMethanol2C1_Iron&SteelBlast furnacesCokeFuel oilElectric arc furnacesSteel production (electric arc)Ladle arc furnacesSteel production (electric arc)Steel production (oxygen converters)2C3_Aluminium_ProductionPrimary aluminium production - generalPrimary aluminium productionPrimary aluminium production - PFC emissionsPrimary aluminium production2C4_Cover_gas_used_in_Al_and_Mg_foundriesMagnesium cover gasNon-fuel combustion2E1_Production_of_Halocarbons_and_Sulphur_HexafluorideHalocarbons production - by-productNon-fuel combustion2E2_Production_of_Halocarbons_and_Sulphur_HexafluorideHalocarbons production - fugitiveNon-fuel combustionnon-IPCCBlast furnacesElectricityLand Use Change5A_Forest Land (Biomass Burning - wildfires)Forest Land - Biomass burningBiomass5A2_Forest Land (N fertilisation)Direct N2O emission from N fertilisation of forest landNon-fuel combustion5A2_Land Converted to Forest LandLand converted to Forest LandNon-fuel combustion5B_LimingCropland - LimingDolomiteLimestone5B1_Cropland Remaining CroplandCropland remaining CroplandNon-fuel combustion5B2_Land Converted to CroplandLand converted to CroplandNon-fuel combustion5C_Grassland (Biomass burning - controlled)Grassland - Biomass BurningBiomass5C_LimingGrassland - LimingDolomiteLimestone5C1_Grassland Remaining GrasslandGrassland remaining GrasslandNon-fuel combustion5C2_Land converted to grasslandLand converted to GrasslandNon-fuel combustion5E_Settlements (Biomass burning - controlled)Settlements - Biomass BurningBiomass5E2_Land converted to settlementsLand converted to SettlementsNon-fuel combustion5G_Other (Harvested wood)Harvested Wood ProductsNon-fuel combustionPublic1A4a_Commercial/InstitutionalPublic sector combustionBurning oilCoalCokeFuel oilGas oilNatural gasSewage gasnon-IPCCPublic sector combustionElectricityResidential1A4b_ResidentialDomestic combustionAnthraciteBurning oilCoalCokeFuel oilGas oilLPGNatural gasPeatPetroleum cokeSSFWood1A4bii_Residential:Off-roadHouse and garden machineryDERVPetrol2B5_Chemical_Industry_OtherNon-aerosol products - household productsCarbon in detergentsPetroleum waxes2F4_AerosolsAerosols - halocarbonsNon-fuel combustionMetered dose inhalersNon-fuel combustion6C_Waste_IncinerationAccidental fires - vehiclesMass burntnon-IPCCDomestic combustionElectricityTransport1A3aii_Civil_Aviation_DomesticAircraft - domestic cruiseAviation spiritAviation turbine fuelAircraft - domestic take off and landingAviation spiritAviation turbine fuel1A3b_Road_TransportationRoad transport - all vehicles LPG useLPGRoad transport - buses and coaches - motorway drivingDERVRoad transport - buses and coaches - rural drivingDERVRoad transport - buses and coaches - urban drivingDERVRoad transport - cars - motorway drivingDERVRoad transport - cars - rural drivingDERVRoad transport - cars - urban drivingDERVRoad transport - cars non catalyst - motorway drivingPetrolRoad transport - cars non catalyst - rural drivingPetrolRoad transport - cars non catalyst - urban drivingPetrolRoad transport - cars with catalysts - motorway drivingPetrolRoad transport - cars with catalysts - rural drivingPetrolRoad transport - cars with catalysts - urban drivingPetrolRoad transport - HGV articulated - motorway drivingDERVRoad transport - HGV articulated - rural drivingDERVRoad transport - HGV articulated - urban drivingDERVRoad transport - HGV rigid - motorway drivingDERVRoad transport - HGV rigid - rural drivingDERVRoad transport - HGV rigid - urban drivingDERVRoad transport - LGVs - motorway drivingDERVRoad transport - LGVs - rural drivingDERVRoad transport - LGVs - urban drivingDERVRoad transport - LGVs non catalyst - motorway drivingPetrolRoad transport - LGVs non catalyst - rural drivingPetrolRoad transport - LGVs non catalyst - urban drivingPetrolRoad transport - LGVs with catalysts - motorway drivingPetrolRoad transport - LGVs with catalysts - rural drivingPetrolRoad transport - LGVs with catalysts - urban drivingPetrolRoad transport - mopeds (<50cc 2st) - urban drivingPetrolRoad transport - motorcycle (>50cc 2st) - rural drivingPetrolRoad transport - motorcycle (>50cc 2st) - urban drivingPetrolRoad transport - motorcycle (>50cc 4st) - motorway drivingPetrolRoad transport - motorcycle (>50cc 4st) - rural drivingPetrolRoad transport - motorcycle (>50cc 4st) - urban drivingPetrolRoad vehicle enginesLubricants1A3c_RailwaysRailways - freightGas oilRailways - intercityGas oilRailways - regionalGas oil1A3dii_National_NavigationMarine enginesLubricantsShipping - coastalFuel oilGas oil1A3e_Other_TransportationAircraft - support vehiclesGas oil1A4a_Commercial/InstitutionalRailways - stationary combustionBurning oilCoalFuel oilNatural gas1A5b_Other:MobileAircraft - militaryAviation turbine fuelShipping - navalGas oilnon-IPCCRailways - regionalElectricityWaste Management6A1_Managed_Waste_Disposal_on_LandLandfillNon-fuel combustion6B2_Wastewater_HandlingSewage sludge decompositionNon-fuel domestic6C_Waste_IncinerationIncinerationMSWIncineration - chemical wasteChemical wasteIncineration - clinical wasteClinical wasteIncineration - sewage sludgeSewage sludge combustion Methodological Changes Two improvements have been made to the Final User calculation this year. The first is that all emissions from the Overseas Territories have been removed from the calculation. These emissions are added in as a separate row to balance the totals. This means that there are no significant emissions remaining in the Energy Supply sector (emissions from power stations in the OTs were not reallocated, since sufficient data were not available). The second improvement has been to correct an over-allocation that had previously been made to road transport emissions. This had occurred where fuel use data is held in the database for the calculation of emissions from cold starts or dioxins, which is not additional to the fuel used to calculate emissions of greenhouse gases. By setting the GCV for the fuels used for these sources to zero, no emissions from refineries can be reallocated to these sources. The effect of this is that Energy Supply emissions allocated to road transport have been reduced, which means that more of these will be allocated to other oil users, for example in the residential and exports sectors. Detailed emissions according to final user categories The final user categories in the data tables in this summary are those used in National Communications. The final user reallocation includes all emissions from the UK and Crown Dependencies. Emissions from the Overseas Territories are included in the totals, but not in the individual sectors. The base year for hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride is 1995. For carbon dioxide, methane and nitrous oxide, the base year is 1990. Notes LULUCF Land Use Land Use Change and Forestry Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 1: Final user emissions from Agriculture, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide8.778.778.808.628.388.408.308.327.947.827.647.32Methane22.4022.4022.0722.1321.9522.0121.7521.9021.6821.6221.4820.70Nitrous oxide33.2833.2833.1131.3030.7431.4931.6131.7632.7331.8131.2229.96HFCsPFCsSF6Total greenhouse gas emissions64.4564.4563.9762.0561.0761.8961.6561.9862.3561.2660.3457.99 Greenhouse Gas2001200220032004200520062007Carbon dioxide7.667.627.557.457.237.046.66Methane19.4919.3019.2919.3318.8418.8118.42Nitrous oxide28.2328.7328.0527.9027.4826.3725.47HFCsPFCsSF6Total greenhouse gas emissions55.3955.6454.8954.6853.5552.2250.55 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 2: Final user emissions from Business, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide227.49227.49224.75211.07203.96200.96197.58199.00191.86191.76188.93196.33Methane13.0613.0612.8312.4411.939.159.949.239.078.147.386.87Nitrous oxide2.582.582.502.432.262.232.172.081.961.931.851.89HFCs1.200.000.000.000.200.671.201.842.563.364.245.11PFCs0.110.060.060.070.080.100.110.130.160.160.190.22SF60.810.600.650.700.740.760.810.840.800.790.740.71Total greenhouse gas emissions245.25243.79240.79226.71219.17213.87211.82213.13206.40206.15203.33211.13 Greenhouse Gas2001200220032004200520062007Carbon dioxide201.59188.46194.87192.51192.40194.69190.52Methane6.536.495.275.014.564.293.65Nitrous oxide1.961.891.921.911.942.011.95HFCs5.886.646.746.836.686.556.39PFCs0.150.110.100.090.090.080.08SF60.670.660.650.740.860.690.64Total greenhouse gas emissions216.77204.26209.55207.10206.51208.32203.23 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 3: Final user emissions from Industrial Processes, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide17.2517.2515.0914.3814.2915.4515.8316.4816.6816.5916.4215.59Methane1.691.691.641.641.611.321.411.451.481.251.140.98Nitrous oxide24.7224.7224.8720.2416.3316.5214.9514.8615.0415.325.445.62HFCs13.9811.3711.8412.3112.7813.2613.9814.3215.6212.124.882.62PFCs0.361.341.110.500.410.390.360.360.260.250.210.28SF60.430.430.430.430.430.430.430.430.430.470.691.09Total greenhouse gas emissions58.4256.8054.9849.5045.8447.3746.9647.8949.5246.0028.7826.18 Greenhouse Gas2001200220032004200520062007Carbon dioxide14.1213.0913.8914.2014.1913.6714.87Methane0.760.670.610.570.490.450.40Nitrous oxide4.882.732.893.642.872.432.82HFCs2.392.031.980.450.440.390.18PFCs0.270.210.170.240.170.220.14SF60.760.850.670.390.250.180.15Total greenhouse gas emissions23.1719.5720.2019.4818.4217.3418.56 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 4: Final user emissions from Land Use Land Use Change and Forestry, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide2.942.942.852.301.140.931.251.010.700.09-0.19-0.33Methane0.020.020.020.010.010.010.030.020.030.020.020.02Nitrous oxide0.010.010.010.010.010.010.010.010.010.010.000.01HFCsPFCsSF6Total greenhouse gas emissions2.972.972.882.321.150.941.291.040.740.11-0.17-0.30 Greenhouse Gas2001200220032004200520062007Carbon dioxide-0.45-0.97-1.01-1.76-1.90-1.79-1.79Methane0.030.030.030.020.020.030.03Nitrous oxide0.010.000.000.000.000.000.00HFCsPFCsSF6Total greenhouse gas emissions-0.42-0.94-0.98-1.73-1.88-1.75-1.75 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 5: Final user emissions from Public Sector, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide29.2429.2432.3233.8927.8427.5526.7427.6125.1824.0123.1922.39Methane1.741.741.932.101.661.291.371.291.201.040.940.83Nitrous oxide0.200.200.210.210.160.150.130.130.110.100.090.09HFCsPFCsSF6Total greenhouse gas emissions31.1831.1834.4636.2029.6628.9928.2429.0326.4825.1524.2223.31 Greenhouse Gas2001200220032004200520062007Carbon dioxide23.1220.7020.8121.6021.4621.4220.34Methane0.800.760.590.600.560.530.44Nitrous oxide0.090.080.080.080.080.090.08HFCsPFCsSF6Total greenhouse gas emissions24.0121.5421.4822.2822.1022.0320.86 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 6: Final user emissions from Residential, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide155.86155.86165.62159.44155.62150.40143.91156.00141.37147.13142.53147.07Methane11.6411.6412.1711.9211.398.748.458.287.437.026.495.79Nitrous oxide0.920.920.960.900.830.780.700.680.580.600.550.57HFCs0.010.010.010.010.030.120.400.781.362.111.952.24PFCsSF6Total greenhouse gas emissions168.43168.43178.76172.27167.86160.04153.46165.74150.74156.87151.52155.67 Greenhouse Gas2001200220032004200520062007Carbon dioxide153.83148.33151.83153.01148.72148.27142.25Methane5.645.554.354.273.923.723.28Nitrous oxide0.610.550.560.550.540.580.54HFCs2.432.352.652.683.023.013.01PFCsSF6Total greenhouse gas emissions162.50156.79159.39160.51156.21155.58149.07 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 7: Final user emissions from Transport, by gas, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000Carbon dioxide140.81140.81139.15140.83142.91144.11144.38150.14150.46149.21149.21148.04Methane2.272.272.152.152.021.992.051.921.791.701.481.38Nitrous oxide1.691.691.681.731.952.362.902.232.262.312.322.32HFCsPFCsSF6Total greenhouse gas emissions144.76144.76142.98144.71146.89148.45149.33154.29154.51153.23153.01151.74 Greenhouse Gas2001200220032004200520062007Carbon dioxide148.22151.34151.41150.95152.70151.82153.20Methane1.401.251.091.050.920.830.90Nitrous oxide2.242.222.132.062.001.961.89HFCsPFCsSF6Total greenhouse gas emissions151.86154.82154.64154.06155.62154.61155.99 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 8: Final user emissions from Waste Management, by gas, MtCO2 equivalent Greenhouse GasBase Year19901991199219931994199519961997199819992000Carbon dioxide1.201.201.201.151.070.920.870.880.500.500.460.46Methane50.5950.5949.8248.6647.4046.4845.0043.5240.0837.6134.4532.37Nitrous oxide1.081.081.071.081.071.151.081.121.221.231.191.23HFCsPFCsSF6Total greenhouse gas emissions52.8752.8752.0850.8949.5548.5446.9445.5241.7939.3436.1134.06 Greenhouse Gas2001200220032004200520062007Carbon dioxide0.490.490.470.470.470.430.45Methane28.3425.9422.8621.3421.1021.1221.08Nitrous oxide1.261.261.261.261.261.291.30HFCsPFCsSF6Total greenhouse gas emissions30.0927.6924.5923.0722.8422.8422.83 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 9: Final user emissions from all National Communication categories, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000Agriculture64.4564.4563.9762.0561.0761.8961.6561.9862.3561.2660.3457.99Business245.3243.8240.8226.7219.2213.9211.8213.1206.4206.1203.3211.1Energy Supply0.000.000.000.000.000.000.000.000.000.000.000.00Exports10.3110.3111.4112.3413.9014.3215.4417.0618.1717.7215.8015.17Industrial Process58.456.855.049.545.847.447.047.949.546.028.826.2Public31.1831.1834.4636.2029.6628.9928.2429.0326.4825.1524.2223.31Residential168.43168.43178.76172.27167.86160.04153.46165.74150.74156.87151.52155.67Transport144.76144.76142.98144.71146.89148.45149.33154.29154.51153.23153.01151.74Waste Management52.8752.8752.0850.8949.5548.5446.9445.5241.7939.3436.1134.06LULUCF2.972.972.882.321.150.941.291.040.740.11-0.17-0.30Overseas Territories1.561.551.591.611.631.681.671.671.731.831.851.89Total greenhouse gas emissions780.21777.12783.90758.61736.72726.10716.80737.35712.43707.65674.79676.83 Final user category2001200220032004200520062007Agriculture55.455.654.954.753.652.250.6Business216.8204.3209.5207.1206.5208.3203.2Energy Supply0.000.000.000.000.000.000.00Exports14.8816.8417.2718.4818.7616.2816.90Industrial Process23.219.620.219.518.417.318.6Public24.0121.5421.4822.2822.1022.0320.86Residential162.50156.79159.39160.51156.21155.58149.07Transport151.86154.82154.64154.06155.62154.61155.99Waste Management30.0927.6924.5923.0722.8422.8422.83LULUCF-0.42-0.94-0.98-1.73-1.88-1.75-1.75Overseas Territories1.971.962.022.092.112.192.25Total greenhouse gas emissions680.23658.17663.05660.01654.23649.66638.49 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 10: Final user emissions, Carbon, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000Agriculture8.778.778.808.628.388.408.308.327.947.827.647.32Business227.49227.49224.75211.07203.96200.96197.58199.00191.86191.76188.93196.33Energy Supply0.000.000.000.000.000.000.000.000.000.000.000.00Exports9.349.3410.4011.2912.8213.2314.2615.8916.9216.5114.8214.22Industrial Process17.2517.2515.0914.3814.2915.4515.8316.4816.6816.5916.4215.59Public29.2429.2432.3233.8927.8427.5526.7427.6125.1824.0123.1922.39Residential155.86155.86165.62159.44155.62150.40143.91156.00141.37147.13142.53147.07Transport140.81140.81139.15140.83142.91144.11144.38150.14150.46149.21149.21148.04Waste Management1.201.201.201.151.070.920.870.880.500.500.460.46LULUCF2.942.942.852.301.140.931.251.010.700.09-0.19-0.33Overseas Territories1.301.301.341.361.381.431.471.471.531.621.641.67Total greenhouse gas emissions594.19594.19601.51584.33569.40563.36554.59576.80553.12555.24544.64552.77 Final user category2001200220032004200520062007Agriculture7.667.627.557.457.237.046.66Business201.59188.46194.87192.51192.40194.69190.52Energy Supply0.000.000.000.000.000.000.00Exports13.9515.8816.4117.5017.8915.5016.05Industrial Process14.1213.0913.8914.2014.1913.6714.87Public23.1220.7020.8121.6021.4621.4220.34Residential153.83148.33151.83153.01148.72148.27142.25Transport148.22151.34151.41150.95152.70151.82153.20Waste Management0.490.490.470.470.470.430.45LULUCF-0.45-0.97-1.01-1.76-1.90-1.79-1.79Overseas Territories1.751.751.811.881.911.992.06Total greenhouse gas emissions564.27546.69558.04557.83555.08553.06544.61 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 11: Final user emissions, Methane, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000Agriculture22.4022.4022.0722.1321.9522.0121.7521.9021.6821.6221.4820.70Business13.0613.0612.8312.4411.939.159.949.239.078.147.386.87Energy Supply0.000.000.000.000.000.000.000.000.000.000.000.00Exports0.880.880.900.940.950.951.031.001.051.000.790.74Industrial Process1.691.691.641.641.611.321.411.451.481.251.140.98Public1.741.741.932.101.661.291.371.291.201.040.940.83Residential11.6411.6412.1711.9211.398.748.458.287.437.026.495.79Transport2.272.272.152.152.021.992.051.921.791.701.481.38Waste Management50.5950.5949.8248.6647.4046.4845.0043.5240.0837.6134.4532.37LULUCF0.020.020.020.010.010.010.030.020.030.020.020.02Overseas Territories0.210.210.210.200.200.200.140.140.140.140.140.14Total greenhouse gas emissions104.49104.49103.72102.2099.1392.1491.1688.7583.9479.5674.3269.84 Final user category2001200220032004200520062007Agriculture19.4919.3019.2919.3318.8418.8118.42Business6.536.495.275.014.564.293.65Energy Supply0.000.000.000.000.000.000.00Exports0.740.720.650.740.640.570.65Industrial Process0.760.670.610.570.490.450.40Public0.800.760.590.600.560.530.44Residential5.645.554.354.273.923.723.28Transport1.401.251.091.050.920.830.90Waste Management28.3425.9422.8621.3421.1021.1221.08LULUCF0.030.030.030.020.020.030.03Overseas Territories0.140.130.120.130.120.120.11Total greenhouse gas emissions63.8560.8454.8653.0551.1550.4748.97 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 12: Final user emissions, Nitrous Oxide, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000Agriculture33.2833.2833.1131.3030.7431.4931.6131.7632.7331.8131.2229.96Business2.582.582.502.432.262.232.172.081.961.931.851.89Energy Supply0.000.000.000.000.000.000.000.000.000.000.000.00Exports0.100.100.110.120.130.140.160.180.200.210.200.21Industrial Process24.7224.7224.8720.2416.3316.5214.9514.8615.0415.325.445.62Public0.200.200.210.210.160.150.130.130.110.100.090.09Residential0.920.920.960.900.830.780.700.680.580.600.550.57Transport1.691.691.681.731.952.362.902.232.262.312.322.32Waste Management1.081.081.071.081.071.151.081.121.221.231.191.23LULUCF0.010.010.010.010.010.010.010.010.010.010.000.01Overseas Territories0.050.050.050.050.050.050.050.050.050.050.050.05Total greenhouse gas emissions64.6164.6164.5758.0653.5254.8753.7553.0854.1653.5842.9241.94 Final user category2001200220032004200520062007Agriculture28.2328.7328.0527.9027.4826.3725.47Business1.961.891.921.911.942.011.95Energy Supply0.000.000.000.000.000.000.00Exports0.190.240.220.230.230.210.20Industrial Process4.882.732.893.642.872.432.82Public0.090.080.080.080.080.090.08Residential0.610.550.560.550.540.580.54Transport2.242.222.132.062.001.961.89Waste Management1.261.261.261.261.261.291.30LULUCF0.010.000.000.000.000.000.00Overseas Territories0.060.050.050.050.050.050.05Total greenhouse gas emissions39.5337.7637.1737.6836.4634.9834.29 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 13: Final user emissions, HFC, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000AgricultureBusiness1.200.000.000.000.200.671.201.842.563.364.245.11Energy SupplyExportsIndustrial Process13.9811.3711.8412.3112.7813.2613.9814.3215.6212.124.882.62PublicResidential0.400.010.010.010.030.120.400.781.362.111.952.24TransportWaste ManagementLULUCFOverseas Territories0.010.000.000.000.000.000.010.010.010.020.020.02Total greenhouse gas emissions15.5911.3911.8512.3213.0114.0615.5916.9619.5617.6011.099.99 Final user category2001200220032004200520062007AgricultureBusiness5.886.646.746.836.686.556.39Energy SupplyExportsIndustrial Process2.392.031.980.450.440.390.18PublicResidential2.432.352.652.683.023.013.01TransportWaste ManagementLULUCFOverseas Territories0.030.030.030.030.030.030.03Total greenhouse gas emissions10.7311.0511.409.9910.189.989.61 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 14: Final user emissions, PFC, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000AgricultureBusiness0.110.060.060.070.080.100.110.130.160.160.190.22Energy SupplyExportsIndustrial Process0.361.341.110.500.410.390.360.360.260.250.210.28PublicResidentialTransportWaste ManagementLULUCFOverseas Territories0.000.000.000.000.000.000.000.000.000.000.000.00Total greenhouse gas emissions0.471.401.170.570.490.490.470.490.420.410.400.50 Final user category2001200220032004200520062007AgricultureBusiness0.150.110.100.090.090.080.08Energy SupplyExportsIndustrial Process0.270.210.170.240.170.220.14PublicResidentialTransportWaste ManagementLULUCFOverseas Territories0.000.000.000.000.000.000.00Total greenhouse gas emissions0.420.310.260.330.250.31.3 Table A  STYLEREF 2 \s 11.7. SEQ Table_A \* ARABIC \s 2 15: Final user emissions, SF6, MtCO2 equivalent Final user categoryBase Year19901991199219931994199519961997199819992000AgricultureBusiness0.810.600.650.700.740.760.810.840.800.790.740.71Energy SupplyExportsIndustrial Process0.430.430.430.430.430.430.430.430.430.470.691.09PublicResidentialTransportWaste ManagementLULUCFOverseas Territories0.000.000.000.000.000.000.000.000.000.000.000.00Total greenhouse gas emissions1.241.031.081.121.171.181.241.271.231.261.431.80 Final user category2001200220032004200520062007AgricultureBusiness0.670.660.650.740.860.690.64Energy SupplyExportsIndustrial Process0.760.850.670.390.250.180.15PublicResidentialTransportWaste ManagementLULUCFOverseas Territories0.000.000.000.000.000.000.00Total greenhouse gas emissions1.431.511.321.131.110.870.79 ANNEX 12: Analysis of EU ETS Data Introduction The EU Emission Trading Scheme (EU ETS) provides a source of data that can be used to cross-check data held in the UK Greenhouse Gas Inventory (GHGI), and to inform the carbon contents of current UK fuels. The EU ETS has operated since 2005, and there are now 3 years worth of data on fuel use and emissions across major UK industrial plant, for 2005, 2006 and 2007. These processes are collectively responsible for a major proportion of UK emissions of carbon dioxide and so the EU ETS data has the potential to be an extremely important source of information to support the UK GHG inventory. However, operators of processes which are included in the UK Emission Trading Scheme (UK ETS), or which have a Climate Change Agreement (CCA) can choose to be exempt from the EU ETS. The UK ETS exemptions were valid until the end of 2006, whilst the CCA exemptions were valid until the end of 2007. These exemptions mean that the 2005 to 2007 EU ETS data gives an incomplete picture of total UK fuels consumed and carbon dioxide emitted by several major industrial sectors. From the 2008 EU ETS dataset onwards, all of the major plant opt-outs will have ceased, and a more complete picture of fuel use and emissions across heavy industry in the UK will be available. The 2008 data are due to become available during Spring 2009. Note however, that emissions from smaller combustion devices in the industrial, commercial and public sectors will not be reported within EU ETS, due to the limited scope of EU ETS reporting. This limitation will continue to restrict how much of the EU ETS data can be used to cross-check and directly inform the GHGI. However, from the 2008 dataset onwards, 100% of sector emissions will be covered for several major industrial sectors: Power stations; Oil refineries; Coke ovens; Integrated steelworks; Cement kilns; and Lime kilns. This annex examines what data are already available in 2005 to 2007 EU ETS datasets, and the use of EU ETS fuel quality data (i.e. CO2 emission factors) within the GHGI. The data reported under the EU ETS includes quantities of fuels consumed, carbon contents, calorific values and emissions of CO2. Data for individual installations are treated as commercially confidential by the UK regulatory authorities and so only aggregated emissions data are presented here. Processing of EU ETS Data In order to be able to compare EU ETS data with GHGI data it was necessary to: allocate each of the installations named in the EU ETS dataset to one of the emission sectors reported in the GHGI; and allocate each fuel used by each installation to one of the fuel types used in the GHGI. Task 1 was straightforward, while the allocation of fuels to GHGI categories was, occasionally, quite uncertain. The uncertainties largely centred on the allocation of fuels to GHGI fuel categories such as LPG, OPG, gas oil and fuel oil, and were due to the use of abbreviations or other ambiguous names for fuels within the EU ETS reporting system. There were also some instances where gas oil was specified as the fuel, but where it was possible that fuel oil was actually used, and vice versa. The level of coverage of the EU ETS data can be seen in  REF _Ref193007974 \* MERGEFORMAT Table A 12.2.1. The number of sites in each sector which are included in the ETS dataset for 2005 is given, together with AEAs estimate of the total number of installations in that sector throughout the UK. Table A  STYLEREF 2 \s 12.2. SEQ Table_A \* ARABIC \s 2 1: Numbers of installations included in the EU ETS datasets SectorNumber of installationsEU ETS dataUK totalPower stations (fossil fuel, > 75MWe)6161Power stations (fossil fuel, < 75MWe)2130Power stations (nuclear)1212Coke ovens44Sinter plant33Blast furnaces33Cement kilns415Lime kilns815Refineries1212Combustion iron & steel industry12200aCombustion other industry2375000aCombustion commercial sector231000aCombustion public sector1671000a a These estimates are not intended to be particularly accurate but are order of magnitude figures, offered in order to show that the number of installations in the UK is likely to be considerably higher than the number of installations reporting in the EU ETS at present. Data were included for all coke ovens, refineries, sinter plant and blast furnaces. Power stations are divided into three categories in the table in order to show that, although 9 stations are not included in the EU ETS data, these are all small (in most cases, very small diesel-fired plant supplying electricity to Scottish islands). In comparison, coverage is quite poor for cement and lime kilns (presumably due to CCA participants opting out) and for combustion processes (due to CCA/UKETS opt-outs and the fact that numerous combustion plant are too small to be required to join the EU ETS). Analysis of EU ETS data for power stations  REF _Ref193008163 \* MERGEFORMAT Table A 12.3.1 summarises data given in the EU ETS datasets for the major fuels burnt by major power stations and coal burnt by autogenerators. The percentage of emissions that were based on use of Tier 3 emission factors is given (tier 3 factors are based on fuel analysis, and are therefore more reliable than emission factors based on default values). The table then gives the average emission factor for all EUETS emissions that were based on use of the Tier 3 factors. Finally, the carbon factor using the methodology used in the previous version of the GHGI is given for comparison. Table A  STYLEREF 2 \s 12.3. SEQ Table_A \* ARABIC \s 2 1 EU ETS data for Coal, Fuel Oil and Natural Gas burnt at Power Stations and Autogenerators (Emission Factors in ktonne / Mtonne for Coal & Fuel Oil and ktonne / Mtherm for Natural Gas) YearFuel% Tier 3Average Carbon Emission Factor (Tier 3 sites only)2006 GHGI Carbon Emission Factor2005 Coal 100615.6627.22006100615.6627.22007100615.4627.22005 Fuel oil / Waste oila68860.2879.0200666873.3879.0200768871.2879.02005 Natural gas521.4431.4782006761.4621.4782007951.4631.4772005 Coal - autogenerators100594.3631.12006100596.3631.12007100594.5645.4 a It is not possible to distinguish between fuel oil and waste oil in the EU ETS data, so all emissions have been reported under fuel oil. The main point of note from the data presented in  REF _Ref193008163 \* MERGEFORMAT Table A 12.3.1 is that the emission factors generated using the 2006 GHGI methodology are higher than those generated from the EU ETS dataset. The EU ETS data are generally very consistent across the three years for which data are available, with the exception of the 2005 data for fuel oil and natural gas. The data used in the 2006 GHGI were based on extrapolated information from operator-supplied data from a study that focussed on carbon emission factors in the power sector 2004. The EU ETS data shown are regarded as good quality data, and are assumed to be representative of the sector as a whole, since a high proportion of emissions are based on Tier 3 emission factors (i.e. verified emissions based on fuel analysis to ISO17025). The EU ETS based emission factors presented above have therefore been used directly as the emission factors in the GHGI, with the exception of the 2005 figure for gas, where Tier 3 factors were only used for about half of the sectors emissions. Analysis of EU ETS data for refineries Similar data to that shown in Table A 1.3.1 for power stations are shown for oil refineries in  REF _Ref193008570 \* MERGEFORMAT Table A 12.4.1. The main fuels in refineries are fuel oil and OPG and emissions also occur due to the burning off of petroleum coke deposits on catalysts used in processes such as catalytic cracking. In the latter case, emissions in the EU ETS are not generally based on activity data and emission factors but are instead based on direct measurement of carbon emitted. This is due to the technical difficulty in measuring the quantity of petroleum coke burnt and the carbon content. Table A  STYLEREF 2 \s 12.4. SEQ Table_A \* ARABIC \s 2 1: EU ETS Data for Fuel Oil, OPG and Petroleum Coke burnt at Refineries (Emission Factors in ktonne / Mtonne for Fuel Oil & Petroleum Coke and ktonne / Mtherm for OPG) YearFuel% Tier 3Average Carbon Emission Factor (Tier 3 sites only)2006 GHGI Carbon Emission Factor2005 Fuel Oil 26861.0879.0200668873.7879.0200779877.4879.02005 OPG691.5261.6442006481.5071.6442007601.5191.6442005 Petroleum Coke-a1054.2930.02006-a985.8930.02007-a1189.8930.0 a It was unclear from the data received how much of the emission was based on a Tier 3 approach. As with power stations, the emission factors generated from EU ETS data were generally lower than those obtained using the 2006 GHGI methodology. Only in the case of petroleum coke is this reversed, but here the EU ETS factors are significantly higher. The factors given in Table 1.14.1 are based on EU ETS carbon emissions and DUKES activity data (since no activity data can be given in EU ETS for this fuel). The emission factors generated for 2005 and 2007 are impossibly high, suggesting that petroleum coke is more than 100% carbon. At the time of inventory compilation, it was not certain whether this was more likely to be due to inaccuracies in DUKES or EUETS. However, due to the large difference in the numbers, a compromise approach was adopted of using the 2006 EU ETS figure in the GHGI and an emission factor of 1000 ktonnes/Mtonne for 2005 and 2007. Consultation with the industry and energy statisticians should allow full resolution of this issue for the next version of the inventory. The emission factors for fuel oil are very similar to those generated using the previous GHGI methodology. Because of the high percentage of Tier 3 data in 2006 and 2007, the EU ETS data have been used in the GHGI, while the 2005 figure has not been used as only 26% Tier 3 coverage was not considered high enough to be representative for the sector. Emission factors for OPG are significantly lower than those generated using the GHGI method. However, Tier 3 emission factors are not always used for the majority of emissions, and there was in addition considerable uncertainly regarding the allocation of EU ETS fuels to the OPG fuel category. The data have therefore not been used in the GHGI, but it is hoped that Tier 3 emission factors will be used for a much higher percentage of emissions in future EU ETS data sets, thereby improving confidence in the data and enabling their future use in the derivation of the GHGI estimates. analysis of EUETS data for industrial combustion Sources Table A.12.5.1 gives data for industrial combustion of coal, fuel oil and natural gas. Table A  STYLEREF 2 \s 12.5. SEQ Table_A \* ARABIC \s 2 1 EU ETS data for Coal, Fuel Oil and Natural Gas burnt by Industrial Combustion Plant (Emission Factors in ktonne / Mtonne for Coal & Fuel Oil and ktonne / Mtherm for Natural Gas) YearFuel% Tier 3Average Carbon Emission Factor (Tier 3 sites only)2006 GHGI Carbon Emission Factor2005 Coal 98607.1631.1200698603.0631.1200799613.5645.42005 Fuel oil14864.7879.0200614865.3879.0200717865.7879.02005 Natural gas161.3761.4782006301.4701.4782007391.4651.477 At first sight, the data for coal looks like it should be reliable enough to be used in the GHGI with 98% or more of emissions based on Tier 3 factors. However, it must be recalled that numerous smaller industrial consumers will not be represented in EU ETS and that the EU ETS data are not fully representative of UK fuels as a whole. This is also true for EU ETS data for fuel oil and natural gas but here, in addition, very little of the EU ETS data are based on Tier 3 factors. Therefore, none of the above data have been used directly in the compilation of the GHGI estimates, and the emission factors from the 2006 GHGI have been retained. Within the iron & steel sector, the EU ETS reporting format does not provide a breakdown of emissions for the sectors reported within the GHGI; estimates of emissions from coke ovens, blast furnaces and sinter plants are not provided explicitly within the EU ETS. In addition, the scope of reporting of EU ETS does not cover 100% of iron & steel sites or activities, as some secondary steel processes are excluded from the scope of EU ETS reporting. These two factors make the analysis and comparison of the EU ETS and the GHGI estimates much more uncertain. The EU ETS data has, however, been useful as a quality check for the use of fuels within the iron and steel sector. ANNEX 13: Standard Electronic Format Tables of GHG Emissions 2008 was the first year the UK Registry was operating under the Kyoto Protocol rules. Connection was established during October 2008 and the reporting year ended on the 31st December 2008. The UK issued 3,412,080,630 AAUs under the Kyoto Protocol following agreement with the UNFCCC. After establishing the connection to the ITL, the UK Registry was made available to EU ETS operators and market participants from late October 2008. During the remainder of the year, units were exchanged with 27 other Registries operating within the Kyoto rules as confirmed by the UNFCCC. In total, the UK Registry received 195,468,637 AAUs and 128,774,640 CERs. Conversely, 154,160,461 AAUs and 103,671,234 CERs were externally transferred to other national registries. Account holders voluntarily cancelled 80 AAUs and 345,826 CERS. There were no transactions of any kind involving RMUs, ERUs tCERs or lCERs. All of these additions and subtractions were undertaken by account holders of person and operator holding accounts, i.e. the UK Government did not initiate any transactions or receive any units into Party Holding Accounts. The UK did not carry out any transactions in response to notifications, as none were received from the ITL. The tables in this Annex present summary data for UK greenhouse gas emissions for the years 1990-2007, inclusive. The data are given in standard electronic format (SEF). SEF Tables Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 1 Total quantities of Kyoto Protocol units by account type at beginning of reported year  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 2 Annual internal transactions  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 3 Annual external transactions  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 4 Total annual transactions  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 5 Expiry, cancellation and replacement  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 6 Total quantities of Kyoto Protocol units by account type at end of reported year  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 7 Summary information on additions and subtractions  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 8 Summary information on replacement  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 9 Summary information on retirement  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 10 Memo item: Corrective transactions relating to additions and subtractions  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 11 Memo item: Corrective transactions relating to replacement  Table A  STYLEREF 2 \s 13.1. SEQ Table_A \* ARABIC \s 2 12 Memo item: Corrective transactions relating to retirement  ANNEX 14: Additional Reporting Requirements For reporting during the Kyoto Commitment Period, additional information will be required in the NIR, specifically regarding KP-LULUCF activities, and registry information. The UNFCCC have provided a draft annotated outline to specify how the NIR should be structured to include this information. Consideration of new requirements Reporting under this new structure is not a requirement until the 2010 submission. However, the UK have considered and included some of the new data requirements, and the table below details which of the additional requirements are already included, and where they can be found. The NIR will be restructured in line with the new annotated outline for the 2010 submission. Table A14.1 is based on the annotated outline supplied by the UNFCCC, and additional requirements are highlighted in italics. Table A  STYLEREF 2 \s 14.1. SEQ Table_A \* ARABIC \s 2 1 Consideration of additional reporting requirements UNFCCC Annotated OutlineUK CommentsES.1. Background information on greenhouse gas inventories, climate change and supplementary information required under Article 7, paragraph 1, of the Kyoto Protocol (e.g., as it pertains to the national context, to provide information to the general public)The Executive Summaries will be re-ordered in the 2010 NIR to follow the structure outlined here. The emissions and removals from KP-LULUCF activities are currently included in table ES.5.ES.2. Summary of national emission and removal related trends, and emission and removals from KP-LULUCF activitiesES.3. Overview of source and sink category emission estimates and trends, including KP-LULUCF activitiesES.4. Supplementary information required under Article 7, paragraph 1, of the Kyoto ProtocolES.5. Other information (e.g., indirect greenhouse gases)PART 1: ANNUAL INVENTORY SUBMISSIONChapter 1: IntroductionBackground information on greenhouse gas inventories, climate change and supplementary information required under Article 7, paragraph 1, of the Kyoto Protocol (e.g., as it pertains to the national context, to provide information to the general public)The additional requirements are already included in Chapter 1 of the UK NIR.A description of the institutional arrangements for inventory preparation, including the legal and procedural arrangements for inventory planning, preparation and managementThe additional requirements are already included in Chapter 1 of the UK NIR.Inventory preparation Brief general description of methodologies and data sources used Brief description of key categories, including for KP-LULUCFA Key Category Analysis including KP-LULUCF will be carried out for the 2010 inventory submissionInformation on the QA/QC plan including verification and treatment of confidentiality issues where relevantGeneral uncertainty evaluation, including data on the overall uncertainty for the inventory totalsGeneral assessment of the completeness (with reference to annex 5 of the structure of the national inventory report (NIR))Chapter 2: Trends in greenhouse gas emissions2.1. Description and interpretation of emission trends for aggregated greenhouse gas emissions Description and interpretation of emission trends by gasDescription and interpretation of emission trends by categoryDescription and interpretation of emission trends for indirect greenhouse gases and SO2Description and interpretation of emission trends for KP-LULUCF inventory in aggregate and by activity, and by gasEmissions trends including KP-LULUCF will be considered in the 2010 NIR.Chapters 39: (e.g. SECTOR NAME (CRF sector number))X.1. Overview of sector (e.g., quantitative overview and description)X.2. Source category (CRF source category number)X.2.1. Source category description (e.g., characteristics of sources)X.2.2. Methodological issues (e.g., choice of methods/activity data/emission factors, assumptions, parameters and conventions underlying the emission and removal estimates the rationale for their selection, any specific methodological issues (e.g. description of national methods))X.2.3. Uncertainties and time-series consistencyX.2.4. Source-specific QA/QC and verification, if applicableX.2.5. Source-specific recalculations, if applicable, including changes made in response to the review process X.2.6. Source-specific planned improvements, if applicable (e.g., methodologies, activity data, emission factors, etc.), including those in response to the review processChapter 9: Other (CRF sector 7) (if applicable)Chapter 10: Recalculations and improvementsExplanations and justifications for recalculations, including for KP-LULUCF inventoryThere have been no recalculations to the KP-LULUCF inventory this yearImplications for emission levels, including on KP-LULUCF emission levelsImplications for emission trends, including time series consistency, and also for the KP-LULUCF inventoryRecalculations, including in response to the review process, and planned improvements to the inventory (e.g., institutional arrangements, inventory preparation), including for KP-LULUCF inventoryPART II: SUPPLEMENTARY INFORMATION REQUIRED UNDER ARTICLE 7, PARAGRAPH 1Chapter 11: KP-LULUCFGeneral informationAll of this information is currently presented in Annex10. This will be moved to Chapter 11 of the main text in the 2010 NIR.Land-related informationActivity-specific informationArticle 3.3Article 3.4Other informationInformation relating to Article 6Chapter 12: Information on accounting of Kyoto unitsBackground informationInformation about the registry and accounting of Kyoto units is currently included in Chapter1. Chapter 12 as outlined here will be included in the 2010 submission.Summary of information reported in the SEF tablesDiscrepancies and notificationsPublicly accessible informationCalculation of the commitment period reserve (CPR)KP-LULUCF accountingChapter 13: Information on changes in national systemThis information is currently contained in Chapter1. Chapter 13 will be included in the 2010 NIR.Chapter 14: Information on changes in national registryAny relevant information will be presented in the 2010 NIR.Chapter 15: Information on minimization of adverse impacts in accordance with Article 3, paragraph 14Included in Section 1.11Chapter 16: Other information REFERENCESANNEXES TO THE NATIONAL INVENTORY REPORTAnnex 1: Key categoriesDescription of methodology used for identifying key categories, including for KP-LULUCF.As discussed with reference to section 1.5.Reference to the key category tables in the CRF, including in the KP-LULUCF CRF tables).Information on the level of disaggregationTables 7.A1 - 7.A3 of the IPCC good practice guidanceTable NIR.3, as contained in the annex to decision 6/CMP.3.$$$$$$?Annex 2: Detailed discussion of methodology and data for estimating CO2 emissions from fossil fuel combustionAnnex 3: Other detailed methodological descriptions for individual source or sink categories, including for KP-LULUCF activitiesCurrently, Annex 10 contains all methods for KP-LULUCF activities. This will be moved to Chapter 11 in 2010 and it is unlikely that there will be any additional information to include in this Annex.Annex 4: CO2 reference approach and comparison with sectoral approach, and relevant information on the national energy balanceAnnex 5: Assessment of completeness and (potential) sources and sinks of greenhouse gas emissions and removals excluded for the annual inventory submission and also for the KP-LULUCF inventoryThis will be considered in the 2010 submissionAnnex 6: Additional information to be considered as part of the annual inventory submission and the supplementary information required under Article 7, paragraph 1, of the Kyoto Protocol or other useful reference informationA.6.1: Annual inventory submissionA.6.2: Supplementary information under Article 7, paragraph 1SEF tables are currently presented in Annex 13. These can be moved to Annex 6 for the 2010 NIR. All other requirements will be considered in the 2010 NIR.A.6.2.1 KP-LULUCF (accounting table, CRF and/or NIR tables)A.6.2.2 Standard electronic format (i.e. SEF tables)A.6.2.3 National system, including changesA.6.2.4 National registryChanges to national registryReports:(i) list of discrepancies; (ii) notifications from EB of CDM (reversal of storage and failure of certification)(iii) non-replacements(iv) invalid unitsPublicly available informationA.6.2.5 Adverse impacts under Article 3, paragraph 14 of the Kyoto ProtocolAnnex 7: Tables 6.1 and 6.2 of the IPCC good practice guidanceAnnex 8: Other annexes - (Any other relevant information optional).  13% in 2007 for lubricants burnt in all types of engines - this is made up of 8% burnt in road vehicle engines, 4% burnt in marine engines and the remaining 1% split between agricultural, industrial and aircraft engines.  Making use, from 2000 onwards, of supplementary data from BERR because of a revision to the DUKES reporting format.  For TOC where train km data was not available for 2007, the data was assumed to be unchanged from the previous year (2006).  DTI (2004) Personal communication from Martin Young, DTI.  Passant, Watterson and Jackson. (2007) Review of the Treatment of Stored Carbon and the NonEnergy Uses of Fuel in the UK Greenhouse Gas Inventory. AEA Energy and Environment, The Gemini Building, Fermi Avenue, Harwell, Didcot, Oxfordshire, OX11 0QR, UK. Report to Defra CESA for contract RMP/2106.  Emissions from the UK military bases in Cyprus are assumed to be included elsewhere emissions from onbase activities are included within the military section of the UK greenhouse gas inventory, whereas any offbase activities will be included within the inventory submitted for Cyprus. Plant loads, demand and efficiency, Table 5.10, BERR (2008)  EU workshop on uncertainties in Greenhouse Gas Inventories Work 5-6 September, Helsinki, Finland. Ministry of the Environment, Finland. Arranged by the VTT Technical Research Centre of Finland (Jaakko Ojala, Sanna Luhtala and Suvi Monni).  We have assumed that the distribution of errors in the parameter values was normal. The quoted range of possible error of uncertainty is taken as 2s, where s is the standard deviation. If the expected value of a parameter is E and the standard deviation is s, then the uncertainty is quoted as 2s/E expressed as a percentage. For a normal distribution the probability of the parameter being less than E-2s is 0.025 and the probability of the emission being less than E+2s is 0.975.  See page 84 of UNFCCC Guidelines contained in FCCC/CP/1999/7 available at:  HYPERLINK "http://unfccc.int/resource/docs/cop5/07.pdf" http://unfccc.int/resource/docs/cop5/07.pdf  A final user is a consumer of fuel for useful energy. A fuel producer is someone who extracts, processes and converts fuels for the end use of final users. Clearly there can be some overlap of these categories but here the fuel uses categories of the UK DECC publication DUKES are used, which enable a distinction to be made.  If calorific data for the fuels is not available then the mass of fuel is used instead. This is the case for years prior to 1990.  In the model used to determine emissions from final users, the value of this percentage cane be adjusted. The tables presented later in this Appendix were calculated for a convergence at 0.001%.     UK NIR 2009 (Issue 1) AEA Page  PAGE 245  Key Sources A1 CO2 Emissions from Fossil Fuel Combustion A2 Other Detailed Methodological Descriptions A3 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  PAGE 294 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 297 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 298 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 370 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 371 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 401 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 403 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 405 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 406 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 412 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 414 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 415 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 417 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 419 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 421 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 423 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 425 Other Detailed Methodological Descriptions A3 UK NIR 2009 (Issue 1) AEA Page  page 427 Comparison of CO2 Reference and Sectoral Approaches A4 UK NIR 2009 (Issue 1) AEA Page  page 458 Assessment of Completeness A5 Quantitative Discussion of 2007 Inventory A6 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 465 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 466 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 467 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 469 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 474 Uncertainty A7 UK NIR 2009 (Issue 1) AEA Page  PAGE 475 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 477 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  PAGE 480 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  page 484 Uncertainties A7 UK NIR 2009 (Issue 1) AEA Page  PAGE 488 Verification A8 UK NIR 2009 (Issue 1) AEA Page  page 495 IPCC Sectoral Tables of GHG Emissions A9 IPCC Sectoral Tables of GHG Emissions A9 UK NIR 2009 (Issue 1) AEA Page  page 513 LULUCF: Supplementary Reporting A10 UK NIR 2009 (Issue 1) AEA Page  page 516 LULUCF: Supplementary Reporting A10 UK NIR 2009 (Issue 1) AEA Page  page 517 LULUCF: Supplementary Reporting A10 UK NIR 2009 (Issue 1) AEA Page  page 535    !=>?@BCZ[\vwx{|}~ȿȿzuȔȿaȿVh*B*Uph hj}h*B*UphhcH":91 & Fm : &M&  G H n o p  ԕl'jh*B*Uphjqh*B*Uphh ? 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4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd4" $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kdY' $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd~, $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd1 $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd6 $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd; $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kdA $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd7F $$If s #}!`',816 Z(66,,      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4ap$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 5 5555Z5555 (5 5 / / / /  / / / /  / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd\K $$If s #}!`',816 Z(66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4a$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 55Z5555 (5 5 9 / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kdP $$If s #}!`',816""""&Z&&&&(&66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4a$$If!v h5 5555Z5555 (5 5 #v #v#v#v#vZ#v#v#v#v (#v #v :V 66, 55Z5555 (5 5 9 / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 4 kd$U $$If s #}!`',816""""&Z&&&&(&"66,,,,2 22 22 22 22 22 22 22 22 2 2 2 2 2 4a$$If!v h5 555Z5555(5 5 #v #v#v#vZ#v#v#v#v(#v #v :V 66, 55Z5555(5 5 9 / 2 22 22 22 22 22 22 22 22 2 2 2 4 ykdY $$If #}!`',816"""&Z&&&&(&"66((((2 22 22 22 22 22 22 22 22 2 2 2 4a$$If!vh525Z5555(55#v2#vZ#v#v#v#v(#v#v:V 66,55Z5555(559/ 2 22 22 22 22 22 22 22 24  kd^ $$Ifִ#}!`',816"&Z&&&&(&"66    2 22 22 22 22 22 22 22 24a$$If!v h55@ 555555p5 5 5 5 #v#v@ #v#vp#v :V 4  x046+++++++++ , 55@ 55p5 9/ / / / / / /  /  / / / / / / / 2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 4 f4pxkda $$If4  q1!!%(,a0!4&@ p  x04600002 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 4af4pxl$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 4  ֌046+++++++ + + ,555 5 5 5 / / / / / /  /  / / / / / /  2 22 22 22 2 2  2 4 f4p֌kd{i $$If48q1 q1!!%(,a0!4  ֌04688882 22 22 22 2 2  2 4af4p֌$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okdp $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd,v $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd}{ $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd΀ $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okdp $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okdc $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 OkdV $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 OkdI $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4a$$If!vh555555555 5 p5 5 5 5 #v #v p#v :V 046,59/ / / /  2 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4 Okd< $$If8q1 q1!!%(,a0!4""""""""""""""04688882 22 22 22 22 22 22 22 22 2 2 2 2 2 2 2 2 2 2  2 4ac$$Ifl!vh5 55n5n55n#v #v#vn#v#vn:V 44 <,5 55n55n/ 44 alf4p<$$Ifl!vh5 55n5n55n#v #v#vn#v#vn:V 4,5 55n55n/ 44 alf4$$Ifl!vh5 55n5n55n#v #v#vn#v#vn:V 4,5 55n55n/ 44 alf4$$Ifl!vh5 55n5n55n#v #v#vn#v#vn:V 4,5 55n55n/ 44 alf4$$Ifl!vh5 55n5n55n#v #v#vn#v#vn:V 4,5 55n55n/ 44 alf4$$Ifl!vh5 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a$$If!vh5l5555555#vl#v#v:V L"65l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"65l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 564444$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%4a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd' $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdT $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd5 $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdb $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 /  /  / / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 $$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kd/ $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kdN $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd{ $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd $$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd/!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd\ !$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd !$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 /  /  / / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 $$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kd$!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd'!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd*!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd-!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd)1!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdV4!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd7!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd:!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd=!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd A!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd7D!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 /  /  / / /  4 )kddG!$$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 $$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kdT!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kdW!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 / /  / /  4 )kd#[!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdP^!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd}a!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdg!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdk!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd1n!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd^q!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdt!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56,5l55 /  /  / / /  4 )kdw!$$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V 4L"6,5l55/ /  / 4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,5l55/ / / /  4 f4$$If!vh5l5555555#vl#v#v:V 4L"6,5l55/  / / / / 4 f4$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdC!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdp!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdʛ!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd$!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdQ!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 /  /  / / /  4 )kd~!$$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 $$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd=!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdj!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$%%%%%%%% % % % % %%%%%%%%%%%%%%%%%%% %!%"%#%$%%%&%'%(%)%*%+%,%-%.%/%0%1%2%3%4%5%6%7%8%9%:%;%<%=%>%?%@%A%B%C%D%E%F%G%H%I%J%K%L%M%N%O%P%Q%R%S%T%U%V%W%X%Y%Z%[%\%]%^%_%`%a%b%c%d%e%f%g%h%i%j%k%l%m%n%o%p%q%r%s%t%v%w%x%y%z%{%|%}%~%%%If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdK!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kdx!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 /  /  / / /  4 )kd!$$If" gw GG"&)-G15l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 $$If!vh5l5555555#vl#v#v:V L"6,5l55/  / / / / 4 $$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  /  4 a)kdE!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kdi!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd1!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kdc!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd!$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd"$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd+"$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd] "$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd "$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd"$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 / /  / /  4 a)kd"$$If" ]m }=}="%)}-=14l 5644444a$$If!v h5l55555555 5 5 5 5 #vl#v#v :V  56, 5l55 /  /  / / /  4 a)kd%"$$If" ]m }=}="%)}-=14l 5644444a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ /  / 4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 a$$If!vh5l5555555#vl#v#v:V L"6,5l55/ / / /  4 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