AGRICULTURE INVENTORY ELABORATION PART 2 SIMULATION 3B.1 STATE-OF-ART OF NAI PARTIES Until September/2003, 70 NCs from NAI Parties were compiled and assessed by the UNFCCC-Secretariat From the Compilation & Synthesis Report, the problems encountered by NAI Parties for the elaboration of the national inventory elaboration: activity data emission factors methods 93 per cent 64 per cent 11 per cent 3B.2 INVENTORY ELABORATION Previous activities: Key source category determination Sub-category importance determination Methods to be applied per category (T1 for non-KS; T2/3 for KS) Mass balance for shared items (crop residues, animal manure) Single livestock characterization (basic linked to T1; enhaced linked to T2) 3B.3 INVENTORY ELABORATION. PREVIOUS ACTIVITIES Preliminary key source determination Two ways: Using last/previous year GHG inventory data, and/or Applying Tier 1 to all sectors for the year to be inventoried 3B.4 PRELIMINARY KEY SOURCE DETERMINATION. STEPS List of categories, according to IPCC disaggregation (excluding LUCF categories) Decreasing ranking, according to their individual contribution to CO2-equiv. emissions Estimating relative contribution of each category to the total national emissions Calculating the cumulative contribution of the categories to the total national emissions, Key sources should gather the upper 95% of GHG emissions 3B.5 PRELIMINARY KEY SOURCE DETERMINATION CHILE, 1994 GHG-Inventory (Gg CO2-equivalent) (1) SECTOR/sub-sector CO2 CH4 N2O Gg/year Gg/year Gg/year 36227.0 1575.2 499.1 38301.3 - ENERGY INDUSTRIES 9439.8 21.2 31.0 9492.0 - MANUFACTURING INDUSTRIES AND CONSTRUCTION 9255.2 33.6 31.0 9319.8 - ROAD TRANSPORT 12695.3 44.1 310.0 13049.4 - RESIDENTIAL, COMMERCIAL, INSTITUTIONAL 4049.6 606.9 124.0 4780.5 787.1 14.7 3.1 804.9 ENERGY - AGRICULTURE, FORESTRY, FISHING TOTALS - C MINING 195.3 195.3 - OIL AND NATURAL GAS 659.4 659.4 - OIL REFINING, FUEL STORAGE AND DISTRIBUTION 0.0 INDUSTRIAL PROCESSES 1870.0 - CEMENT 1021.1 44.1 248.0 2162.1 1021.1 - ASPHALT 0.0 - COPPER 0.0 - GLASS 0.0 - CHEMICAL PRODUCTS 44.1 248.0 292.1 - IRON AND STEEL 812.2 812.2 - FERROALLEYS 36.7 36.7 - PULP/ PAPER; FOODS/DRINKS; REFRIGERATION/OTHERS SOLVENT USE 0.0 0.0 0.0 0.0 0.0 3B.6 PRELIMINARY KEY SOURCE DETERMINATION 1994 GHG-Inventory of Chile (Gg in CO2-equivalent) (Non-energy sectors) AGRICULTURE: 0.0 6760.3 8661.3 15421.6 - RICE CULTIVATION 134.4 134.4 - ENTERIC FERMENTATION 5564.8 5564.8 - MANURE MANAGEMENT 1009.1 - RICE CULTIVATION 134.4 1304.8 2313.9 134.4 - AGRICULTURAL SOILS: DIRECT EMISSIONS 4693.9 4693.9 - AGRICULTURAL SOILS: INDIRECT EMISSIONS 1495.9 1495.9 - AGRICULTURAL SOILS: PASTURE RANGE/PADDOCK 559.2 559.2 52.0 607.5 659.5 1560.3 206.7 1767.0 - AGRICULTURAL RESIDUE BURNING WASTE: 0.0 - WASTEWATER TREATMENT: - SOILD WASTE DISPOSAL LANDS 3.2 3.2 1557.1 1557.1 - INDUSTRIAL SOLID WASTE DISPOSAL 0.0 - UNTREATED WASTE WATER RUNOFF 206.7 - INDUSTRIAL LIQUID WASTES TOTAL NATIONAL 202.9 38097.0 10142.8 206.7 202.9 9615.2 57854.9 3B.7 KEY SOURCES FOR THE 1994 GHG-Inventory of Chile Contribution Gg/yr CO2equiv. Ind. Cumul. - Road transport 13049,4 22,6% 22,6% Energy - Energy industries 9492,0 16,4% 39,0% Energy - Processing industries and construction 9319,8 16,1% 55,1% Energy - Enteric fermentation 5564,8 9,6% 64,7% Agriculture - Residential, commercial, institutional 4780,5 8,3% 73,0% Energy - Agricultural soils, direct N2O 4693,9 8,1% 81,1% Agriculture - Solid waste disposal lands 1557,1 2,7% 83,8% Waste - Agricultural soils, indirect N2O 1495,9 2,6% 86,3% Agriculture - Manure management-N2O 1304,8 2,3% 88,6% Agriculture - Cement 1021,1 1,8% 90,4% Energy - Manure management-CH4 1009,1 1,7% 92,1% Agriculture - Iron and ferroalloys 812,2 1,4% 93,5% Industrial Processes - Agriculture, Forestry, Fishing 804,9 1,4% 94,9% Energy - Agricultural residue burning 659,5 1,1% 96,0% Agriculture - Oil and natural gas 659,4 1,1% 97,2% Industrial Processes - Agricultural soils, pasture range and paddock 559,2 1,0% 98,1% Agriculture - Chemical products 292,1 0,5% 98,7% Industrial Processes - Waste water runoff 206,7 0,4% 99,0% Agric./Waste - Industrial liquid residues 202,9 0,4% 99,4% Waste - C mining 195,3 0,3% 99,7% Energy - Rice cultivation 134,4 0,2% 99,9% Agriculture 3,2 0,0% 100,0% Energy SECTOR/sub-sector - Sewage waters Sector KS NKS 3B.8 INVENTORY ELABORATION. SIGNIFICANCE OF SUBSOURCES Significance of animal species: Example for CH4 emissions from Enteric Fermentation and Manure Management Emissions estimated by Tier 1 To simplify: country with no division into agroecological units 3B.9 INVENTORY ELABORATION. SIGNIFICANCE OF SUBSOURCES Steps: Collection of animal species population If no national AD are available, the use of FAOSTAT is appropriate Disaggregation between dairy and non-dairy cattle, following expert’s judgment Filling in of IPCC software Table 4-1s1 with the population data and default emission factors Estimation of individual contribution to the total emissions of the source category 3B.10 Determination of Significant SubSource Categories For significant species = enhanced characterization and Tier-2, if possible Perform a rough estimation of CH4 emissions from enteric fermentation applying Tier-1 one way of screening species for their contribution to emissions estimation has the only purpose of identifying categories requiring a Tier-2 estimation use IPCC Software, sheet ‘4-1s1’: fill in animal population data, and collect default EF from Tables 4-3 and 4-4 of IPCC Guidelines Vol. 3 (also taken from the EFDB) 3B.11 Low Level of Data Availability MODULE AGRICULTURE SUBMODULE METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC ANIMALS AND MANURE MANAGEMENT WORKSHEET 4-1 SHEET 1 of 2 METHANE EMISSIONS FROM ENTERIC FERMENTATION COUNTRY YEAR ANYWHERE 2003 STEP 1 Animal Species A B Nº of animals EF for Enteric Fermenta tion (1000s) (kg/head/year ) STEP 2 C Emissions from Enteric Fermentation (ton/year) STEP 3 D E F EF for Manure Manage ment Emissions due to Manure Management Total emissions from domestic animals (kg/head/year ) (ton/year) (Gg/year) E = (A x D) F =(C + E)/1000 C = (A x B) Dairy cattle 1.000,0 57,0 57000,0 2,0 2000,0 59,00 Non-dairy cattle 5.000,0 49,0 245000,0 1,0 5000,0 250,00 Buffalo NO 55,0 Sheep 3.000,0 5,0 15000,0 0,16 480,0 15,48 Goats 50,0 5,0 250,0 0,17 8,5 0,26 Camels NO 46,0 Horses 10,0 18,0 16,0 0,20 NO 10,0 1.500,0 1,5 3,0 4500,0 6,00 4.000,0 NE 0,018 72,0 0,07 12076,50 331,01 Mules & Assess Swine Poultry 1 5,0 1,9 180,0 1,6 0,9 2250,0 Disaggregation between dairy and non-dairy cattle, based on expert`s judgment Totals 318930,0 3B.12 Determining significant animal species Worksheet 4-1s1 MODULE SUBMODULE METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT WORKSHEET 4-1 SHEET COUNTRY YEAR Livestock Type A Number of Animals (1000s) Dairy Cattle Non-dairy Cattle Buffalo Sheep Goats Camels Horses Mules & Asses Swine Poultry Totals AGRICULTURE 1000 5000 0 3000 50 0 10 0 1500 4000 1 OF 2 METHANE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT Hypothetical 2003 STEP 1 B Emissions Factor for Enteric Fermentation (kg/head/yr) 57 49 55 5 5 46 18 10 1.5 0 STEP 2 C Emissions from Enteric Fermentation (t/yr) C = (A x B) 57,000.00 245,000.00 0.00 15,000.00 250.00 0.00 180.00 0.00 2,250.00 0.00 319,680.00 STEP 3 D E F Emissions Emissions from Total Annual Factor for Manure Emissions from Manure Management Domestic Management Livestock (kg/head/yr) (t/yr) (Gg) E = (A x D) F =(C + E)/1000 0.00 57.00 0.00 245.00 0.00 0.00 0.00 15.00 >25% 0.00 0.25 0.00 0.00 0.00 0.18 0.00 species0.00 No other significant 0.00 2.25 0.00 0.00 0.00 319.68 Conclusion: Tier 2 method, supported by an enhanced characterization, for the non-dairy cattle 3B.13 Enhanced Characterization Non-Dairy Cattle Enhanced characterization requires information additional to that provided by FAO Statistics. Consultation with local experts/industry is a valuable source Assume that, using these sources, the inventory team determines that non-dairy cattle population is composed by: Cows : 40% Steers : 40% Young growing animals : 20% No information available to divide the animal population into climatic zones and production systems Each of these homogenous groups of animals must have an estimate of feed intake and an EF to convert intake to CH4 emissions Procedure is described in IPCC-GPG (pages 4.10-4.20) 3B.14 Enhanced Characterization Non-Dairy Cattle Parameter Cows Steer Young W 400 450 230 Table A-2, IPCC-GL V3 Weight Gain (kg/day) WG 0 0 0.3 Table A-2, IPCC-GL V3 Mature Weight (kg) MW 400 450 425 Table A-2, IPCC-GL V3 Ca 0.28 0.23 0.25 Table 4-5 IPCC-GPG, and expert’s judgment - 67 - - Table A-2, IPCC-GL V3 Feed Digestibility (%) DE 60 60 60 Table A-2, IPCC-GL V3 Maintenance coefficient Cfi 0.335 0.322 0.322 Table 4-4 IPCC-GPG Net Energy Maintenance (MJ/day) NEm 30.0 31.5 19.0 Calculated using equation 4.1, IPCC-GPG Net Energy Activity (MJ/day) NEa 8.4 7.2 4.8 Calculated using equation 4.2a, IPCC-GPG Weight (kg) Feeding Situation Females giving birth (%) Symbol Source 3B.15 Enhanced Characterization Non-Dairy Cattle Parameter Symbol Cows Steer Young Comments Growth coefficient C - - 0.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NEg - - 4.0 Calculated using equation 4.3a, IPCC-GPG CP 0.1 - - Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NEP 3.0 - - Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NEma/D E 0.49 0.49 0.49 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth NEga/DE 0.28 0.28 0.28 Calculated using equation 4.10, IPCC-GPG GE 139.3 130.4 117.7 Pregnancy coefficient Gross Energy Intake (MJ/day) Calculated using equation 4.11, IPCCGPG To check the estimates of GE, convert to kg/day of feed intake (by dividing GE by 18.45) and divide by live weight. The result must be between 1 and 3 % of live weight 3B.16 Tier-2 Estimation of CH4 emissions from Enteric Fermentation by Non-Dairy Cattle Enhanced characterization yielded CS-AD (average daily gross energy intake) per group of non-dairy cattle (cows, steers, growing animals) These AD must be combined with specific EFs for animal group to obtain emission estimates Determination of EFs requires selection of a suitable value for CH4 conversion rate (Ym) In this example of country with no CS-data, a default value for Ym (MCF) can be obtained from the IPCC-GPG 3B.17 Tier-2 Estimation of CH4 emissions Enteric Fermentation - Non-Dairy Cattle Parameter Symb ol Cows Steer Young Comments Gross Energy Intake (MJ/day) (from the GE 139.3 130.4 117.7 Calculated using equation 4.11, IPCCGPG CH4 conversion factor Ym 0.06 0.06 0.06 Table 4.8, IPCC-GPG, and EFDB Emission Factor (kg CH4/head/yr) EF 54.8 51.3 46.3 Calculated using equation 4.14, IPCCGPG Portion of group in total population (%) - 40 40 20 Population of group (thousand heads) - 2,000 2,000 1,000 CH4 Emissions (Gg CH4/yr - 110 103 46 enhanced characterization) Expert judgment, industry data Weighed EF= 52 3B.18 Tier-2 Estimation of CH4 emissions Enteric Fermentation by Non-Dairy Cattle Tier-2 estimation for non-dairy cattle: 259 Gg CH4 (245 Gg CH4 by Tier 1) Weighed EF: 52 kg CH4/head/yr (49 kg CH4/head/yr, as default value) This value should be used in the worksheet to report emissions by non-dairy cattle Another chance: to modify worksheet to recognize T2 and incorporate new Efs directly 3B.19 Medium Level of AD Availability For AD1, the country has reliable statistics on livestock population Applying the same procedure as above, the country determines that non-dairy cattle requires enhanced characterization National statistics + expert judgment allow disaggregation of non-dairy cattle population into: 2 climate regions (some of previous example) 3 animal categories (cows, sterrs, young animals) 3 production systems It means 18 estimation units 3B.20 Medium Level of AD Availability Climate Region Warm Temperate Total Production System Population (1,000 hd) Cows Steers Young Extensive Grazing 1,473 828 610 Intensive Grazing 228 414 120 Feedlot 40 92 96 Extensive Grazing 348 201 161 Intensive Grazing 150 275 75 Feedlot 15 31 32 2,254 1,841 1,094 5,153 New Total: 5,153·103 heads (against FAO: 5,000·103 heads ) 3B.21 Tier-2 Estimation of CH4 emissions Enteric Fermentation - Non-Dairy Cattle Enhanced characterization yielded CS-AD (average daily GE intake) for 18 classes of animals This AD must be combined with EFs for each animal class to obtain 18 emission estimates Next slides will show detailed calculations to estimate GE intake only for 6 of the 18 classes (three types of animals for ‘Warm-Extensive Grazing’ and for ‘Temperate-Intensive Grazing’ 3B.22 Enhanced characterization, Non-Dairy Cattle Warm Climate - Extensive Grazing Parameter Symbol Cow s Stee r Youn g Weight (kg) W 420 380 210 Country-specific data Weight Gain (kg/day) WG 0 0.2 0.2 Country-specific data Mature Weight (kg) MW 420 440 430 Country-specific data Ca 0.33 0.33 0.33 Table 4-5 IPCC-GPG, and expert judgment - 60 - - Country-specific data Feed Digestibility (%) DE 57 57 57 Country-specific data Maintenance coefficient Cfi Net Energy Maintenance (MJ/day) NEm 31.1 27.7 17.8 Calculated using equation 4.1, IPCC-GPG Net Energy Activity (MJ/day) NEa 10.3 9.2 5.9 Calculated using equation 4.2a, IPCC-GPG Feeding Situation Females giving birth (%) 0.335 0.322 0.322 Comments Table 4-4 IPCC-GPG Comments in green indicate improvements over previous example 3B.23 Enhanced characterization, Non-Dairy Cattle Warm Climate - Extensive Grazing Symbol Cows Steer Young Growth coefficient C - 1.0 0.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NEg - 3.4 2.4 Calculated using equation 4.3a, IPCC-GPG Pregnancy coefficient CP 0.1 - - Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NEP 3.1 - - Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NEma/DE 0.48 0.48 0.48 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth NEga/DE 0.26 0.26 0.26 Calculated using equation 4.10, IPCC-GPG GE 162.2 170.0 111.2 Parameter Gross Energy Intake (MJ/day) Comments Calculated using equation 4.11, IPCCGPG To check estimates of GE, convert to kg/day of feed intake (by dividing GE by 18.45) and divide by live weight. The result must be between 1 and 3 % of live weight 3B.24 Enhanced characterization, Non-Dairy Cattle Temperate Climate - Intensive Grazing Parameter Symbol Cow s Stee r Weight (kg) W 405 390 240 Country-specific data Weight Gain (kg/day) WG 0.15 0.33 0.65 Country-specific data Mature Weight (kg) MW 445 470 452 Country-specific data Feeding Situation Ca 0.17 0.17 0.17 Table 4-5 IPCC-GPG, and expert judgment Females giving birth (%) - 81 - - Country-specific data Feed Digestibility (%) DE 72 72 72 Country-specific data Maintenance coefficient Cfi 0.335 0.322 0.322 Table 4-4 IPCC-GPG NEm 30.2 28.3 19.6 Calculated using equation 4.1, IPCC-GPG Net Energy Maintenance (MJ/day) Young Comments Net Energy Activity NEa 5.1 4.8 3.3 Calculated using equation (MJ/day) 4.2a, IPCC-GPG Comments in green indicate improvements over previous example 3B.25 Enhanced characterization, Non-Dairy Cattle Temperate Climate, Intensive Grazing Parameter Symbol Cows Steer Young Comments Growth coefficient C 0.8 1.0 0.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NEg 3.0 5.7 9.2 Calculated using equation 4.3a, IPCC-GPG Pregnancy coefficient CP 0.1 - - Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NEP 3.0 - - Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NEma/DE 0.53 0.53 0.53 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth. NEga/DE 0.34 0.34 0.34 Calculated using equation 4.10, IPCC-GPG GE 120.1 123.9 121.5 Gross Energy Intake (MJ/day) Calculated using equation 4.11, IPCCGPG To check estimates of GE, convert to kg/day of feed intake (by dividing GE by 18.45) and divide by live weight. The result must be between 1 and 3 % of live weight 3B.26 Medium Level of Data Availability Estimated GE values are used for calculation of EF (using equation 4.14, IPCC-GPG). Calculation of EF requires to select a value for methane conversion rate (Ym), this is, the fraction of energy in feed in take that is converted to energy in methane. In this example we assume the country uses a default value (Ym =0.06, from Table 4.8, IPCCGPG). 18 estimates of EF were obtained (next slide) 3B.27 Medium Level of Data Availability Climate Region Warm Temperate Productio n System EF (kg CH4/head/yr) Cows Steers Young Extensive Grazing 63.8 66.9 max 43.8 Intensive Grazing 47.7 51.5 48.4 Feedlot 41.5 min 49.3 52.8 Extensive Grazing 61.5 66.7 49.5 Intensive Grazing 47.3 48.8 47.8 Feedlot 41.5 min 49.3 52.8 Range from 41.5 to 66.9 3B.28 Medium Level of Data Availability Weighed EF (Tier 2, CS-AD): 57 kg CH4/head/yr (range: 42-67 kg CH4/head/yr) EF for Tier 2 (with default and aggregated AD): 52 kg CH4/head/yr EF for Tier 1: 49 kg CH4/head/yr Multiplication of EF with cattle population in each class yielded 18 estimates of annual emission of methane from enteric fermentation, with a total of 294 Gg CH4/year Total for Tier 2 (with default and aggregated AD): 259 Gg CH4/year Total for Tier 1: 245 Gg CH4/year 3B.29 Medium Level of Data Availability MODULE WORKSHEET 4-1 COUNTRY YEAR A Number of Animals (1000s) Dairy Cattle Non-dairy Cattle Buffalo Sheep Goats Camels Horses Mules & Asses Swine Poultry Totals Worksheet 4-1s1 METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT SHEET Livestock Type AGRICULTURE SUBMODULE 1 OF 2 METHANE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT Hypothetical 2003 STEP 1 B Emissions Factor for Enteric Fermentation (kg/head/yr) 1000 57 5153 0 3000 50 0 10 0 1500 4000 57 55 5 5 46 18 10 1.5 0 C Emissions from Enteric Fermentation (t/yr) C = (A x B) 57,000.00 293,721.00 0.00 15,000.00 250.00 0.00 180.00 0.00 2,250.00 0.00 368,401.00 STEP 2 STEP 3 D E F Emissions Emissions from Total Annual Factor for Manure Emissions from Manure Management Domestic Management Livestock (kg/head/yr) (t/yr) (Gg) E = (A x D) F =(C + E)/1000 0.00 57.00 0.00 293.72 0.00 0.00 0.00 15.00 0.00 0.25 0.00 0.00 0.00 0.18 0.00 0.00 0.00 2.25 0.00 0.00 0.00 368.40 3B.30 Highest Level of Data Availability Activity data could be improved by: more accurate national statistics on livestock population lowest uncertainties further disaggregation of cattle population (e.g., by race or age, subdividing climate region by administrative units, soil type, forage quality, others) implementation of geographically-explicit AD and cattle traceability systems development of local research to obtain CS estimates of parameters used for livestock characterization (e.g., coefficients for maintenance, growth, activity or pregnancy) 3B.31 Highest Level of Data Availability Emission factors could be improved by: developing local capacities for measuring CH4 emissions by individuals characterising diverse feeds used by their CH4 conversion factors for different animal types development of local research to improve understanding of locally-relevant factors affecting methane emissions adapting international information (scientific literature, EFDB, etc.) from conditions similar to those of the country 3B.32 Highest Level of Data Availability Numerical example not developed here Very few -if any- developing countries are in position of having this level of information With high level of data availability, countries would be able to implement Tier-3 methods (CS methods) 3B.33 Estimation of Uncertainties It is good practice to estimate and report uncertainties of emission estimates, which implies estimating uncertainties of AD and EF According to IPCC, EF used in Tier-1 may have an uncertainty in the order of 30-50%, and default AD may have even higher values Application of Tier-2 method with country-specific AD may substantially reduce uncertainty levels with respect to Tier1 with default AD/EF Priority should be given to improve the quality of AD estimates 3B.34 Direct N2O Emissions from Agricultural Soils NAI GHG Inventory Training Workshop Agriculture Sector 3B.35 Mineral fertilizers Animal manures Anthropogenic N inputs to soils Crop residues Fraction of … (from the mass balance) Sewage sludges N-fixing crops Other practices dealing with soil N Histosols cultivation 3B.36 AGRICULTURAL SOILS Assess individual contribution of different N sources to determine ones (sub-categories) which are significant for the source category (25% or more of source category N2O emissions) For this, apply Tier 1a method and default values, to get a preliminary emission estimate For the significant sub-categories, the best efforts should be invested to apply Tier 1b along with country-specific AD1, AD2 and emission factors For non-significant sub-categories, Tier 1a along with country-specific AD1 and default AD2 and emission factors is acceptable It is also acceptable to mix Tiers 1a and 1b for different N sources, which will depend on the activity data availability 3B.37 Direct N2O – Agricultural Soils Assumption of the same country It will be assumed that the country has the following AD: usage of synthetic N fertilizers: FAO database usage of synthetic N fertilizers for barley crop: Industry source estimate of EF1 for N applied to barley crops: local research, which due to improved practices in this crop (e.g., fractioning of N applications), is lower than the IPCC default EF N excretion from different animal categories under pasture/range/paddock AWMS: data from previous example on N2O from manure management area devoted to N-fixing crops: FAO database The country has no organic soils (histosols) and no sewage sludge application to soils Direct N2O emissions are estimated using a combination of Tier 1a (for most of the sources) and Tier 1b (for use of N fertilizers in barley and N in crop residues applied to soils) 3B.38 Use of N-Fertilizers From the FAO database: Crop Area (1,000 ha) Crop Yield (kg dm/ha) Use of N Fertilizer (1000 t N) Wheat 824 1,545 n/a 356 (371) 1,488 (1400) 19.1 1,225 2,233 n/a Rice 98 4,800 n/a Soybeans 231 1,982 n/a Potatoes 25 18,000 n/a 2,779 -- 130 Barley 1 Maize Total 1 Barley data from industry sources, shown in parentheses 3B.39 Direct N2O – Agricultural Soils From FAO database, only total country data for fertilizer use is available. Therefore, only Tier-1a method could be used unless further disaggregation can be done with the support of national sources Data from barley industry/research can be used to apply Tier-1b method: to ensure consistency, it is recommended to compare crop area and crop yield data between FAO and the local industry in this case, both sources reasonably matched for area and yield, and it can be assumed that industry estimation of N fertilizer usage is compatible with the FAO N fertilizer data from previous table, it can be derived that 19,000 t N fertilizer were applied to barley crops, and 111,000 t N fertilizer to the rest (130 minus 19) from local research, EF1 was estimated to be 0.9% for fertilizer applied to barley crops in the country Since there are no organic soils in the country, EF2 is not needed 3B.40 Synthetic Fertilisers: Determination of FSN and EF1 FSN: annual amount of fertiliser N applied to soils, adjusted by amount of N that volatilises as NH3 and NOx To adjust for volatilisation, use IPCC default value from Table 4-17, IPCC Guidelines, V2: 0.1 kg (NOx+NH3)-N/kg fertiliser-N It is determined that: FSN= 19,000 (1-0.1) = 17,100 t fertiliser-N (barley) FSN= 111,000 (1-0.1) = 99,900 t fertiliser-N (all other crops) Total fertiliser-N = 117,000 t fertiliser-N EF1 is 0.9 % for barley (country-specific) and 1.25 % for the other crops (Table 4.17, IPCC-GPG) For the purpose of filling the IPCC Software sheet 4-5s1, a weighted EF1 is calculated as follows: EF1 = weighed average= 17.1/117 (0.9) + 99.9/117 (1.25) = 1.20 % From worksheet 4-5s1, the annual emission of N2O-N from use of synthetic fertilizer was estimated as 1.40 Gg N2O-N 3B.41 Emissions of N2O from Synthetic Fertilisers MODULE AGRICULTURE SUBMODULE AGRICULTURAL SOILS WORKSHEET 4-5 SHEET COUNTRY YEAR Type of N input to soil Combined EF and defaultt) 1 OF 5 DIRECT NITROUS OXIDE EMISSIONS FROM AGRICULTURAL FIELDS, EXCLUDING CULTIVATION OF(CS HISTOSOLS Hypothetical 2003 STEP 1 A Amount of N Input STEP 2 (kg N/yr) Synthetic fertiliser (FSN) Animal waste (FAW) C Direct Soil Emissions (kg N2O–N/kg N) (Gg N2O-N/yr) C = (A x B)/1 000 000 117,000,000.00 0.012 1.40 65,793,280.00 0.0125 0.82 0.0125 0.00 0.0125 0.00 Total 2.23 N-fixing crops (FBN) Crop residue (FCR) B Factor for Direct Emissions EF1 0.00 3B.42 Indirect N2O Emissions from Agricultural Soils NAI GHG Inventory Training Workshop Agriculture Sector 3B.43 Indirect N2O – Agricultural Soils We will assume that the country only covers the following sources: N2O(G): from volatilisation of applied synthetic fertiliser and animal manure N, and its subsequent deposition as NOx and NH4. N2O(L): from leaching and runoff of applied fertiliser and animal manure Indirect N2O emissions are estimated using Tier 1a method and IPCC default emission factors Next slides show calculations as performed by IPCC Software 3B.44 Indirect N2O Emissions from Atmospheric Depositions MODULE AGRICULTURE SUBMODULE AGRICULTURAL SOILS WORKSHEET 4-5 SHEET 4 OF 5 INDIRECT NITROUS OXIDE EMISSIONS FROM ATMOSPHERIC DEPOSITION OF NH 3 AND NOX COUNTRY Hypothetical YEAR 2003 Type of Deposition A Synthetic Fertiliser N B Fraction of Synthetic C Amount of Synthetic N D Total N Excretion by STEP 6 E Fraction of Total Manure N Applied to Soil, NFERT Fertiliser N Applied that Volatilizes FracGASFS (kg N/kg N) Applied to Soil that Volatilizes Livestock NEX Excreted that Volatilizes (kg N/yr) 130000000 Default value 0.1 G Emission Factor EF4 H Nitrous Oxide Emissions (kg N2O–N/kg N) (Gg N2O–N/yr) Volatilizes FracGASM (kg N/kg N) (kg N/yr) (kg N/kg N) (kg N/kg N) C = (A x B) Total F Total N Excretion by Livestock that 13,000,000.00 249,240,080.00 From Table 4-17 IPCC Guidelines V2 F = (D x E) 0.2 49,848,016.00 H = (C + F) x G /1 000 000 0.01 0.63 From Table 4.18 IPCC-GPG 3B.45 Indirect N2O Emissions from Leaching & Runoff MODULE AGRICULTURE SUBMODULE AGRICULTURAL SOILS WORKSHEET 4-5 SHEET COUNTRY YEAR I Synthetic Fertiliser Use NFERT 5 OF 5 INDIRECT NITROUS OXIDE EMISSIONS FROM LEACHING Hypothetical 2003 J Livestock N Excretion NEX STEP 7 K Fraction of N That Leaches L Emission Factor EF5 M Nitrous Oxide Emissions From Leaching STEP 8 N Total Indirect Nitrous Oxide Emissions (Gg N2O–N/yr) M = (I + J) x K x L/1 000 000 (Gg N2O/yr) N = (H + M)[44/28] FracLEACH (kg N/yr) (kg N/yr) 130,000,000.00 249,240,080.00 From Table 4-17 IPCC Guidelines V2 (kg N/kg N) 0.3 0.025 2.84 5.46 From Table 4.18 IPCC-GPG 3B.46 Field Burning of Crop Residues NAI GHG Inventory Training Workshop Agriculture Sector 3B.47 CROP RESIDUES BURNING Main issues derived from the Decision-Tree • If not occurring, then emission estimates are “NO” • If occurring, then emissions must be are estimated using Worksheet 4-4 sheets 1-2-3 (IPCC software) • Only one method is available to estimate emissions from this source category • If key source, then CS-values for non-collectable AD and emission factors must be preferred (default values for key source are possible if the country cannot provide the required AD or financial resources are jeopardised) • If CS values are used, they must be reported in a transparent manner 3B.48 CROP RESIDUES BURNING • Activity data required to estimate emissions: • collected by statistics agencies: annual crop productions (alternative way = FAO database) • not collected by statistics agencies: • residue to crop ratio • • • • • dry matter fraction of biomass fraction of crop residues burned in field fraction of crop residues oxidised C fraction in dry matter Nitrogen/Carbon ratio • Emision factors: C-N emission ratios as CH4, CO, N2O, NOX • Other constants (conversion ratios): • C to CH4 or CO (16/12; 28/12, respectively) • N to N2O or NOX (44/28; 46/14, respectively); 3B.49 1. OPEN THE IPCC SOFTWARE AND CHOOSE THE YEAR OF THE INVENTORY 2. CLICK IN “SECTORS” IN THE MENU BAR, AND THEN CLICK IN AGRICULTURE 3. OPEN SHEET 4-4s2 MODULE AGRICULTURE SUBMODUL E FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEE T 4-4 SHEET COUNTRY YEAR 1 OF 3 Main residue-producing crops: Cereals (wheat, barley, oat, rye, rice, maize, sorghum, sugar cane) Pulses (peas, bean, STEP lentils) STEP 2 3 Potatoes, peanut, others FICTICIOUS LAND 2002 STEP 1 Crops A B C D E F G H (specify locally Annual Residue to Quantity of Dry Matter Quantity of Fraction Fraction Total Biomass important Production Crop Ratio Residue Fraction Dry Residue Burned in Oxidised Burned crops) Fields (Gg crop) (Gg biomass) (Gg dm) (Gg dm) C = (A x B) E = (C x D) H = (E x F xG) 0,00 0,00 0,00 Wheat 15750 1,3 20.475,00 0,85 17.403,75 0,75 0,9 11.747,53 Maize 5200 1 5.200,00 0,5 2.600,00 0,5 0,9 1.170,00 Rice 1050 1,4 1.470,00 0,85 1.249,50 0,85 0,9 955,87 Identify the . existing residueproducing crops 0,00 0,00 0,00 3B.50 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop Priority order for non-collectable AD2: 1. CS values-research 2. CS values-expert judgment 3. Values from countries with similar conditions 4. Default values (search EFDB) A. Annual crop Production (Gg) B. Residue/crop Ratio Priority order for collectable AD1: 1. Values collected from published statistics 2. If not available, values can be derived from: a) crop area (in kha) b) crop yield (in ton ha-1) 3. From FAO DB C. Quantity of residues (Gg biomass) 3B.51 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop C. Quantity of residue (Gg biomass) from previous slide D. Dry matter Fraction Priority order for non-collectable AD: 1. CS values-research 2. CS values-expert judgment 3. Values from countries with similar conditions 4. IPCC default values (search EFDB) E. Total quantity of dry residue (Gg dm) 3B.52 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop Priority order for non-collectable AD: 1. CS values-research 2. CS values-expert judgment 3. Values from countries with similar conditions (No default values) To avoid double counting, a mass balance of crop residue biomass must be internally performed: Fburned= Total biomass – (Fremoved from the field+ Featen by animals+ Fother uses) E. Quantity of dry residue (Gg dm) from previous slide F. Fraction burned in fields For default values, search EFDB as combustion efficiency G. Fraction oxidised H. Total biomass burned (Gg dm burned) 3B.53 4. OPEN THE SHEET 4-4s2 OF “AGRICULTURE” UNDER “SECTORS” MODULE AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 2 OF 3 FICTICIOUS LAND 2002 STEP 4 Crops STEP 5 I J K L Carbon Total Carbon Nitrogen- Total Nitrogen Fraction of Released Carbon Ratio Released Residue (Gg C) (Gg N) J = (H x I) L = (J x K) 0,00 0,00 Wheat 0,48 5.638,82 0,012 67,67 Maize 0,47 549,90 0,02 11,00 Rice 0,41 391,91 0,014 5,49 . 0,00 0,00 3B.54 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 2 Flowchart to be applied to each crop H. Biomass burned (Gg dm burned) from previous slide J. C released (Gg C) Total C and N released are obtained by addding the values obtained per each individual crop I. C fraction in residue K. N/C ratio Priority order for non-collectable AD: 1. CS values-research 2. CS values-expert judgment 3. Values from countries with similar conditions 4. Default values (search EFDB) L. N released (Gg N) 3B.55 5. OPEN THE SHEET 4-4s3 OF “AGRICULTURE” UNDER “SECTORS” Worksheet 4-4, sheet 3 MODULE Total emission estimates AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 3 OF 3 FICTICIOUS LAND 2002 STEP 6 M N O P Emission Ratio Emissions Conversion Ratio Emissions from Field Burning of Agricultural Residues (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH4 0,005 32,90 16/12 43,87 CO 0,06 394,84 28/12 921,29 N = (L x M) P = (N x O) N2O 0,007 0,59 44/28 0,93 NOx 0,121 10,18 46/14 33,46 3B.56 6. GO TO THE “OVERVIEW” MODULE 7. OPEN THE WORHSHEET 4-S2 TABLE 4 SECTORAL REPORT FOR AGRICULTURE Total emission estimates (Sheet 2 of 2) SECTORAL REPORT FOR NATIONAL GREENHOUSE GAS INVENTORIES (Gg) GREENHOUSE GAS SOURCE AND SINK CATEGORIES CH4 N2O NOx CO NMVOC B Manure Management (cont...) 10 Anaerobic 0 11 Liquid Systems 0 12 Solid Storage and Dry Lot 0 13 Other (please specify) 0 C Rice Cultivation 0 1 Irrigated 0 2 Rainfed 0 3 Deep Water 0 4 Other (please specify) D Agricultural Soils E Prescribed Burning of Savannas F Field Burning of Agricultural Residues (1) 0 1 0 2 36 44 1 33 921 1 Cereals 2 Pulse 3 Tuber and Root 4 Sugar Cane 5 Other (please specify) G Other (please specify) 3B.57 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 3 Flowchart to be applied to aggregated figures Total C released (Gg C from all crops) from previous slide M Non-CO2 emission rates (search EFDB) Total N released (Gg N from all crops) from previous slide EFs: If no CS values, use defaults (Table 4-16, Reference Manual, 1996 Revised Guidelines) P1 CH4 emited (Gg CH4) P2 CO emited (Gg CO) C-N emitted (Gg C emitted as CH4 or CO; Gg N emitted as N2O or NOX) O Conversion ratios P3 N2O emited (Gg N2O) P4 NOX emited (Gg NOX) 3B.58 FIELD BURNING OF CROP RESIDUES Emission factors 3B.59 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (1 of 3) MODULE AD from national statistics AGRICULTURE SUBMODUL E FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEE T 4-4 SHEET COUNTRY YEAR CS activity data, from research and monitoring 1 OF 3 FICTICIOUS 2002 STEP 1 STEP 2 STEP 3 Crops A B C D E F G H (specify locally Annual Residue to Quantity of Dry Matter Quantity of Fraction Fraction Total Biomass important Production Crop Ratio Residue Fraction Dry Residue Burned in Oxidised Burned crops) Fields (Gg crop) Wheat 18.350,50 1,50 (Gg biomass) (Gg dm) (Gg dm) C = (A x B) E = (C x D) H = (E x F xG) 27.525,8 0,90 24.773,2 0,12 0,96 2.735,0 3B.60 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (2 of 3) MODULE AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 2 OF 3 FICTICIOUS 2002 STEP 4 Crops Wheat STEP 5 I J K L Carbon Total Carbon Nitrogen- Total Nitrogen Fraction of Released Carbon Ratio Released Residue 0,45 (Gg C) (Gg N) J = (H x I) L = (J x K) 1.230,7 CS activity data, from research and monitoring 0,0032 3,94 3B.61 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (3 of 3) MODULE AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 3 OF 3 FICTICIOUS 2002 STEP 6 Gas M N O P Emission Ratio Emissions Conversion Ratio Emissions (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH4 0,00311 3,83 16/12 5,10 CO 0,06 73,84 28/12 172,30 N = (L x M) P = (N x O) N2 O 0,018 0,07 44/28 0,11 NOx 0,121 0,48 46/14 1,57 CS values for CH4/N2O D for CO/NOX 3B.62 FIELD BURNING OF CROP RESIDUES Emission estimates using default values Wheat residues (1 of 3) MODULE SUBMODULE WORKSHEET AD: SHEET 1. from national statistics, or COUNTRY 2. from FAO database: (www.fao.org, then “FAOSTATYEAR Agriculture” and “Crops primary”) AGRICULTURE FIELD BURNING OF AGRICULTURAL RESIDUES 4-4 1 OF 3 FICTICIOU S 2002 STEP 1 STEP 3 STEP 2 Crops A B C D E F G H (specify locally Annual Residue to Quantity of Dry Matter Quantity of Fractio n Fraction Total Biomass importan t Productio n Crop Ratio Residue Fraction Dry Residue Burned in Oxidised Burned crops) Fields (Gg crop) Wheat 18.350,5 (Gg biomass) EF ID= 43555 C = (A x B) 1,30 23.855, 7 (Gg dm) EF ID= 43636 0,83 Activity data, taken from EFDB (Gg dm) EF ID= 45941 E = (C x D) 19.800, 2 0,12 0,94 CS value, from monitoring or expert judgment H = (E x F xG) 2.140,4 3B.63 FIELD BURNING OF CROP RESIDUES Emission estimates using default values Wheat residues (2 of 3) MODULE AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 2 OF 3 FICTICIOUS 2002 STEP 4 Crops Wheat STEP 5 I J K L Carbon Total Carbon Nitrogen- Total Nitrogen Fraction of Released Carbon Ratio Released Residue 0,48 (Gg C) (Gg N) J = (H x I) L = (J x K) 1.027,4 EF ID= 43716 0,012 12,33 EF ID= 43796 Default activity data, from EFDB 3B.64 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (3 of 3) MODULE AGRICULTURE SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET 4-4 SHEET COUNTRY YEAR 3 OF 3 FICTICIOUS 2002 STEP 6 M N O P Emission Ratio Emissions Conversion Ratio Emissions (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH4 0,005 5,14 16/12 6,85 CO 0,06 61,64 28/12 143,83 N = (L x M) P = (N x O) N2 O 0,007 0,09 44/28 0,14 NOx 0,121 1,49 46/14 4,90 EF ID= 43583, 43548, 43543, 43549 Default values, from EFDB 3B.65 FIELD BURNING OF CROP RESIDUES Differences in emission estimates If CS or D values are used Emissions Emissions Per cent Gg gas Gg gas of using using difference CS values Defaults CH4 5,10 6,85 -25% CO 172,30 143,83 20% N2O 0,11 0,14 -18% NOx 1,57 4,90 -68% Gas emitted 3B.66 Prescribed Burning of Savannas NAI GHG Inventory Training Workshop Agriculture Sector 3B.67 PRESCRIBED BURNING OF SAVANNAS Main issues derived from the Decision-tree • If not occurring, then no emission estimates • If occurring, then emissions must be are estimated using Worksheet 4-3, sheets 1-2-3 (IPCC software) • Only one methods is available to estimate emissions from this source category • If key source, country-specific non-collectable activity data and emission factors must be preferred to be used (use of default values for key source is possible, if the country cannot provide the required AD or resources are jeopardised) • If CS values are used, they must be reported in a transparent manner 3B.68 PRESCRIBED BURNING OF SAVANNAS • Activity data required to estimate emissions: • collected by statistics agencies: • division of savannas into categories • area per savanna category • not collected by statistics agencies: • biomass density (kha) (column A in worksheets) • • • • • • dry matter fraction of biomass (ton DM/ha) (column B) fraction of biomass actually burned (column D) fraction of living biomass actually burned (column F) fraction oxidised of living and dead biomass (column I) C fraction of living and dead biomass (column K) Nitrogen/carbon ratio • Emision factors: C-N emission ratios as CH4, CO, N2O, NOX • Other constants (conversion ratios): • C to CH4 or CO (16/12; 28/12, respectively) • N to N2O or NOX (44/28; 46/14, respectively) 3B.69 1. 2. 3. 4. OPEN THE IPCC SOFTWARE AND CHOOSE THE YEAR OF THE INVENTORY GO TO THE MENU BAR AND CLICK IN “SECTORS” AND THEN IN “AGRICULTURE” OPEN THE SHEET 4-3s1 FILL IN WITH THE DATA MODULE AGRICULTURE SUBMODULE PRESCRIBED BURNING OF SAVANNAS WORKSHEET 4-3 SHEET COUNTRY YEAR 1 OF 3 FICTICIOUS LAND 2002 STEP 1 STEP 2 A B C D E F G H Area Burned by Category (specify) Biomass Density of Savanna Total Biomass Exposed to Burning Fraction Actually Burned Quantity Actually Burned Fraction of Living Biomass Burned Quantity of Living Biomass Burned Quantity of Dead Biomass Burned (k ha) (t dm/ha) (Gg dm) The first 3 steps is to determine: 15,5 1. the categories of savannas existing per ecological unit 2. the area burned per category 3. the biomass density per category C = (A x B) 7 108,50 Sources for AD on categories of savannas and (Gg dm) (Gg dm) (Gg dm) area covered by category: E =1. (C National x D) G = (E x F) H = (E - G) statistics 0,85 2. National 92,23 mapping 0,45 systems 41,50 50,72 Sources for AD on biomass density: 0,00 0,00 1. National statistics 0,00 2. National vegetation surveys and mapping 0,00 3. National expert judgment 4. Data provided by third countries with similar features 5. IPCC defaults (Table 4-14, Reference Manual, 1996 Revised Guidelines) 3B.70 PRESCRIBED BURNING OF SAVANNAS Flow chart to estimate non-CO2 emissions To be applied to each savanna category B Biomass density (ton dm/ha) A Area burned (k ha) F F of living biomass burned C Total biomass exposed to burning (Gg dm) D F actually burned E Biomass actually Burned (Gg dm) G Living biomass actually burned (Gg dm) Ideally, CS values based on measurements. If not, CS values based on expert judgment. If not, default values (search EFDB) H Dead biomass actually burned (Gg dm) 3B.71 5. GO SHEET 4-3s2 IN “SECTORS/AGRICULTURE” OF THE IPCC SOFTWARE 6. FILL IT WITH THE DATA MODULE AGRICULTURE SUBMODULE PRESCRIBED BURNING OF SAVANNAS WORKSHEET 4-3 SHEET COUNTRY YEAR 2 OF 3 FICTICIOUS LAND 2002 STEP 3 I J K L Fraction Oxidised of living and dead biomass Total Biomass Oxidised Carbon Fraction of Living & Dead Biomass Total Carbon Released (Gg dm) (Gg C) Living: J = (G x I) Dead: J = (H x I) L = (J x K) Living 0,9 37,35 0,45 16,81 Dead 0,95 48,19 5 240,94 Living 0,00 0,00 Dead 0,00 0,00 3B.72 PRESCRIBED BURNING OF SAVANNAS Flow chart to estimate non-CO2 emissions Applicable per each savanna category G Living biomass actually burned (Gg dm) If no CS values, defaults in EFDB, as combustion efficiency I1 Fraction of living biomass oxidised (Gg dm) from previous slide J1 Oxidised living biomass (Gg dm) H Dead biomass actually burned (Gg dm) from previous slide I2 Fraction of dead biomass oxidised (Gg dm) K1 C fraction of living biomass J2 Oxidised dead biomass (Gg dm) K2 C fraction of dead biomass N Total N released (Gg N) M N/C ratio L1 C released from living biomass (Gg C) L Total C released (Gg C) L2 C released from dead biomass (Gg C) 3B.73 7. GO TO SHEET 4.3s3 IN “SECTORS/AGRICULTURE” 8. FILL IT GO THE DATA MODULE AGRICULTURE SUBMODULE PRESCRIBED BURNING OF SAVANNAS WORKSHEET 4-3 SHEET COUNTRY YEAR TOTAL EMISSION ESTIMATES 3 OF 3 FICTICIOUS LAND 2002 STEP 4 STEP 5 L M N O P Q R Total Carbon Released NitrogenCarbon Ratio Total Nitrogen Content Emissions Ratio Emissions Conversion Ratio Emissions from Savanna Burning (Gg C) 257,75 0,015 (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,004 1,03 16/12 CH4 1,37 0,06 15,46 28/12 CO 36,08 3,87 P = (N x O) R = (P x Q) 0,007 0,03 44/28 N2O 0,04 0,121 0,47 46/14 NOx 1,54 3B.74 9. GO TO “OVERVIEW” MODULE 8. OPEN THE WORKSHEET 4S2 TABLE 4 SECTORAL REPORT FOR AGRICULTURE (Sheet 2 of 2) SECTORAL REPORT FOR NATIONAL GREENHOUSE GAS INVENTORIES (Gg) GREENHOUSE GAS SOURCE AND SINK CATEGORIES CH4 N2O NOx CO NMVOC B Manure Management (cont...) 10 Anaerobic 0 Total emission estimates 11 Liquid Systems From Savanna Burning 12 Solid Storage and Dry Lot 0 0 13 Other (please specify) C Rice Cultivation 0 0 1 Irrigated 0 2 Rainfed 0 3 Deep Water 0 4 Other (please specify) D Agricultural Soils E Prescribed Burning of Savannas F Field Burning of Agricultural Residues (1) 0 1 0 2 36 44 1 33 921 1 Cereals 2 Pulse 3 Tuber and Root 4 Sugar Cane 5 Other (please specify) G Other (please specify) 3B.75 PRESCRIBED BURNING OF SAVANNAS Applicable to aggregated figures O N2O & NOx emission rates N Total N released (Gg N) from previous slide If no CS EFs, defaults in EFDB P N2O-N released (Gg N) R NOx emitted (Gg NOX) P NOx-N released (Gg N) Q N2O & NOx conversion rates O CH4 & CO emission rates L Total C released (Gg C) R N2O emitted (Gg N2O) P CH4-C released (Gg C) R CO emitted (Gg CO) from previous slide P CO-C released (Gg C) R CH4 emitted (Gg CH4) Q CH4 & CO conversion rates 3B.76 PRESCRIBED BURNING OF SAVANNAS Examples of default emission factors 3B.77 PRESCRIBED BURNING OF SAVANNAS Example based in a ficticious country having three ecological regions: north, centre, south Northern zone: shortest drought period Southern zone: longest drought period Central zone: intermediate situation Two scenarios: use of country-specific values for the majority of the ADs and EFs use of default values for all the ADs and EFs 3B.78 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values STEP 1 Savan na catego ry A B C D E F G H Area Burned by Category (specify) Biomass Density of Savanna Total Biomass Exposed to Burning Fraction Actually Burned Quantity Actually Burned Fraction of Living Biomass Burned Quantity of Living Biomass Burned Quantity of Dead Biomass Burned (t dm/ha) (Gg dm) (Gg dm) (Gg dm) (Gg dm) C = (A x B) E = (C x D) G = (E x F) H = (E G) (k ha) North Centre South STEP 2 15,5 7,00 108,50 0,85 92,23 0,55 50,72 41,50 145,8 5,00 729,00 0,95 692,55 0,50 346,28 346,28 22,0 4,00 88,00 Total s AD from national statistics (census, surveys, mapping) 1,00 88,00 0,45 39,60 48,40 436,60 CS values (field measurements, expert’s judgment) 436,18 3B.79 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values STEP 3 Savanna category Biomass type I J K L Fraction Oxidised of living and dead biomass Total Biomass Oxidised Carbon Fraction of Living & Dead Biomass Total Carbon Released (Gg dm) (Gg C) Living: J = (G x I) Dead: J = (H x I) North Centre South Totals L = (J x K) Living 0,9 37,35 0,4 14,94 Dead 0,95 48,19 0,45 21,68 Living 0,9 324,77 0,4 129,91 Dead 0,95 280,48 0,45 126,22 Living 0,9 41,38 0,4 16,55 Dead 0,95 35,74 0,45 16,08 Living 403,50 Dead 364,41 325,39 CS values (field measurements, lab analysis, expert’s judgment) 3B.80 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values CS values for CH4 & N2O D values for CO & NOx SUBMODULE PRESCRIBED BURNING OF SAVANNAS WORKSHEET 4-3 SHEET 3 OF 3 COUNTRY CHILE YEAR 2002 STEP 4 STEP 5 M N O P Q R NitrogenCarbon Ratio Total Nitrogen Content Emissions Ratio Emissions Conversi on Ratio Emissions from Savanna Burning 0,0142 (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,006 2,06 16/12 CH4 2,75 0,06 20,62 28/12 CO 48,11 P = (N x O) 4,88 R = (P x Q) 0,006 0,03 44/28 N2 O 0,05 0,121 0,59 46/14 NOx 1,94 3B.81 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values STEP 1 STEP 2 A B C D E F G H Area Burned by Category (specify) Biomass Density of Savanna Total Biomass Exposed to Burning Fraction Actually Burned Quantity Actually Burned Fraction of Living Biomass Burned Quantity of Living Biomass Burned Quantity of Dead Biomass Burned (k ha) (t dm/ha) (Gg dm) (Gg dm) (Gg dm) (Gg dm) C = (A x B) E = (C x D) G = (E x F) H = (E - G) 15,50 7,00 108,50 EF ID= 43475 145,80 6,00 4,00 EF ID= 43480 103,08 EF ID= 43485 874,80 EF ID= 43445 22,00 0,95 0,95 0,95 56,69 EF ID= 43518 831,06 EF ID= 43485 88,00 0,55 0,55 46,38 457,08 EF ID= 43518 83,60 EF ID= 43485 0,45 373,98 37,62 EF ID= 43515 45,98 551,39 AD from national statisitcs Default values taken from EFDB 466,34 3B.82 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values STEP 3 Savanna category I J K L Fraction Oxidised of living and dead biomass Total Biomass Oxidised Carbon Fraction of Living & Dead Biomass Total Carbon Released Default values taken from EFDB North Centre South Totals (Gg dm) (Gg C) Living: J = (G x I) Dead: J = (H x I) L = (J x K) Living 0,94 53,29 0,4 21,32 Dead 0,94 43,60 0,45 19,62 Living 0,94 429,66 0,4 171,86 Dead 0,94 351,54 0,45 158,19 Living 0,94 35,36 0,4 14,15 Dead 0,94 43,22 0,45 19,45 Living 518,31 Dead 438,36 EF ID= 45949 404,59 Experts CS values taken from expert’s judgment 3B.83 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values SUBMODULE PRESCRIBED BURNING OF SAVANNAS WORKSHEET 4-3 SHEET 3 OF 3 COUNTRY CHILE YEAR 2002 STEP 4 STEP 5 M N O P Q R NitrogenCarbon Ratio Total Nitrogen Content Emissions Ratio Emissions Conversion Ratio Emissions from Savanna Burning 0,0095 (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,005 2,02 16/12 CH4 2,70 0,06 24,29 28/12 CO 56,64 3,84 R = (P x Q) P = (N x O) EF ID= 45998 0,007 0,03 44/28 N2 O 0,04 Default values taken from EFDB 0,121 0,47 46/14 NOx 1,53 defaults 3B.84 PRESCRIBED BURNING OF SAVANNAS Difference of estimates PRESCRIBED BURNING OF SAVANNAS Emissions Emissions Per cent Gg gas Gg gas of using using difference CS values Defaults CH4 2,75 2,70 2% CO 48,11 56,64 -15% N2O 0,05 0,04 9% NOx 1,94 1,53 27% Gas emitted 3B.85 RICE CULTIVATION NAI GHG Inventory Training Workshop Agriculture Sector 3B.86 RICE CULTIVATION Anaerobic decomposition of organic material in flooded rice fields produces CH4 The gas escapes to the atmosphere primarily by transport through the rice plants Amount emitted: function of rice species, harvests nº/duration, soil type, tº, irrigation practices, and fertiliser use Three processes of CH4 release into the atmosphere: Diffusion loss across the water surface (least important process) CH4 loss as bubbles (ebullition) (common and significant mechanism, especially if soil texture is not clayey) CH4 transport through rice plants (most important phenomenon) 3B.87 RICE CULTIVATION Methodological issues 1996 IPCC Guidelines outline one method, that uses annual harvested areas and area-based seasonally integrated emission factors (Fc = EF x A x 10-12) In its most simple form, the method can be implemented using national total area harvested and a single EF High variability in growing conditions (water management practices, organic fertiliser use, soil type) will significantly affect seasonal CH4 emissions Method can be modified by disaggregating national total harvested area into sub-units (e.g. areas under different water management regimes or soil types), and multiplying the harvested area for each sub-unit by an specific EF With this disaggregated approach, total annual emissions are equal to the sum of emissions from each sub-unit of harvested area 3B.88 RICE CULTIVATION Activity data total harvested area excluding upland rice (national statistics or international databases FAO (www.fao.org/ag/agp/agpc/doc) or IRRI (www.irri.org/science/ricestat/pdfs) harvested area differs from cultivated area according the number of cropping within the year (multiple cropping) regional units, recognising similarities in climatic conditions, water management regimes, organic amendments, soil types, and others (national statistics or mapping agencies or expert judgment) harvested area per regional unit (national statistics or mapping agencies) cropping practices per regional unit (research agencies or expert judgment) amount/type of organic amendments applied per regional unit, to allow the use of scaling factors (national statistics or international databases or expert judgment) 3B.89 RICE CULTIVATION Main features from decision-tree If no rice is produced, then reported as “NO” If not key source: If keysource: and cropped area is homogeneous, then emissions can be estimated using total harvested area (Box 1) but cropped area in heterogeneous, then total harvested area muts be disaggregated into homogeneous regional units applying default EF and scaling factors, if available and the cropped area is homogeneous, then emissions must be estimated using total harvested area and CS EFs (Box 2) but cropped area variable, then the total harvested area must be divided into homogeneous regional units and emissions estimated using CS EFs and scaling factors for organic ammendements (if available) (Box 3) The country is encouraged to produce seasonally-integrated EFs for each regional unit (excluding organic ammendements) through a good practice measurement programme The EFs must include the multiple cropping effect 3B.90 RICE CULTIVATION Numerical example Assumptions: Hypothetical country located in Asia Key source condition Total harvested area: 38,5 kha, disaggregated into: 28,5 kha as irrigated and continously flooded 10,0 kha as irrigated, intermitently flooded and single aireated 3B.91 RICE CULTIVATION Regional units, from national estatistics or mapping agencies or MODULE expert judgment SUBMODULE WORKSHEET SHEET COUNTRY YEAR AD from national statistics Water Management Regime or international databases (FAO, IRRI) EF: local research or other country’s use or from EFDB AGRICULTURE METHANE EMISSIONS FROM FLOODED RICE FIELDS Scaling factor for water management: local research or other country’s use or EFDB 4-2 1 OF 1 FICTICIOUS LAND (Agriculture, Rice Production, 2002 Intermitently Flooded, Single aeration) A B C D E Harvested Area Scaling Factor for Methane Emissions Correction Factor for Organic Amendment Seasonally Integrated Emission Factor for Continuously Flooded Rice without Organic Amendment CH4 Emissions (g/m2) (Gg) (m2 /1 000 000 000) E = (A x B x C x D) Irrigated Continuously Flooded Intermittently Flooded Single Aeration 0,285 1 2 20 11,40 0,1 0,5 2 20 2,00 Multiple Aeration Rainfed 0,00 Flood Prone 0,00 Enhancement factor for organic ammendements: local research or taken from the EFDB (Agriculture, Rice Production) Drought Prone Deep Water Water Depth 50-100 cm Water Depth > 100 cm Totals 0,385 0,00 0,00 0,00 3B.92 13,40 THANK YOU SERGIO GONZALEZ sgonzale@inia.cl 3B.93