1. 3B.1 AGRICULTURE INVENTORY ELABORATION PART 2 SIMULATION

2. 3B.2 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 data93 per cent emission factors64 per cent methods11 per cent STATE-OF-ART OF NAI PARTIES

3. 3B.3 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)

4. 3B.4 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

5. 3B.5 PRELIMINARY KEY SOURCE DETERMINATION. STEPS List of categories, according to IPCC disaggregation (excluding LUCF categories) Decreasing ranking, according to their individual contribution to CO 2 -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

6. 3B.6 PRELIMINARY KEY SOURCE DETERMINATION CHILE, 1994 GHG-Inventory (Gg CO 2 -equivalent) (1) SECTOR/sub-sectorCO 2 CH 4 N2ON2O TOTALS Gg/year ENERGY36227.01575.2499.138301.3 - ENERGY INDUSTRIES9439.821.231.09492.0 - MANUFACTURING INDUSTRIES AND CONSTRUCTION9255.233.631.09319.8 - ROAD TRANSPORT12695.344.1310.013049.4 - RESIDENTIAL, COMMERCIAL, INSTITUTIONAL4049.6606.9124.04780.5 - AGRICULTURE, FORESTRY, FISHING787.114.73.1804.9 - C MINING 195.3 - OIL AND NATURAL GAS 659.4 - OIL REFINING, FUEL STORAGE AND DISTRIBUTION 0.0 INDUSTRIAL PROCESSES1870.044.1248.02162.1 - CEMENT1021.1 - ASPHALT 0.0 - COPPER 0.0 - GLASS 0.0 - CHEMICAL PRODUCTS 44.1248.0292.1 - IRON AND STEEL812.2 - FERROALLEYS36.7 - PULP/ PAPER; FOODS/DRINKS; REFRIGERATION/OTHERS 0.0 SOLVENT USE0.0

7. 3B.7 PRELIMINARY KEY SOURCE DETERMINATION AGRICULTURE:0.06760.38661.315421.6 - RICE CULTIVATION 134.4 - ENTERIC FERMENTATION 5564.8 - MANURE MANAGEMENT 1009.11304.82313.9 - RICE CULTIVATION 134.4 - AGRICULTURAL SOILS: DIRECT EMISSIONS 4693.9 - AGRICULTURAL SOILS: INDIRECT EMISSIONS 1495.9 - AGRICULTURAL SOILS: PASTURE RANGE/PADDOCK 559.2 - AGRICULTURAL RESIDUE BURNING 52.0607.5659.5 WASTE:0.01560.3206.71767.0 - WASTEWATER TREATMENT: 3.2 - SOILD WASTE DISPOSAL LANDS 1557.1 - INDUSTRIAL SOLID WASTE DISPOSAL 0.0 - UNTREATED WASTE WATER RUNOFF 206.7 - INDUSTRIAL LIQUID WASTES 202.9 TOTAL NATIONAL38097.010142.89615.257854.9 1994 GHG-Inventory of Chile (Gg in CO2-equivalent) (Non-energy sectors)

8. 3B.8 KEY SOURCES FOR THE 1994 GHG-Inventory of Chile SECTOR/sub-sector Gg/yr CO 2 - equiv. Contribution Sector Ind.Cumul. - Road transport13049,422,6% Energy - Energy industries9492,016,4%39,0%Energy - Processing industries and construction9319,816,1%55,1%Energy - Enteric fermentation5564,89,6%64,7%Agriculture - Residential, commercial, institutional4780,58,3%73,0%Energy - Agricultural soils, direct N 2 O4693,98,1%81,1%Agriculture - Solid waste disposal lands1557,12,7%83,8%Waste - Agricultural soils, indirect N 2 O1495,92,6%86,3%Agriculture - Manure management-N 2 O1304,82,3%88,6%Agriculture - Cement1021,11,8%90,4%Energy - Manure management-CH 4 1009,11,7%92,1%Agriculture - Iron and ferroalloys812,21,4%93,5%Industrial Processes - Agriculture, Forestry, Fishing804,91,4%94,9%Energy - Agricultural residue burning659,51,1%96,0%Agriculture - Oil and natural gas659,41,1%97,2%Industrial Processes - Agricultural soils, pasture range and paddock559,21,0%98,1%Agriculture - Chemical products292,10,5%98,7%Industrial Processes - Waste water runoff206,70,4%99,0%Agric./Waste - Industrial liquid residues202,90,4%99,4%Waste - C mining195,30,3%99,7%Energy - Rice cultivation134,40,2%99,9%Agriculture - Sewage waters3,20,0%100,0%Energy KS NKS

9. 3B.9 Significance of animal species: Example for CH 4 emissions from Enteric Fermentation and Manure Management Emissions estimated by Tier 1 To simplify: country with no division into agroecological units INVENTORY ELABORATION. SIGNIFICANCE OF SUBSOURCES

10. 3B.10 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 INVENTORY ELABORATION. SIGNIFICANCE OF SUBSOURCES

11. 3B.11 Determination of Significant Sub- Source Categories For significant species = enhanced characterization and Tier-2, if possible Perform a rough estimation of CH 4 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)

12. 3B.12 Low Level of Data Availability 1 Disaggregation between dairy and non-dairy cattle, based on expert`s judgment MODULEAGRICULTURE SUBMODULE METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC ANIMALS AND MANURE MANAGEMENT WORKSHEET4-1 SHEET1 of 2 METHANE EMISSIONS FROM ENTERIC FERMENTATION COUNTRYANYWHERE YEAR2003 STEP 1 STEP 2 STEP 3 ABCDEF Animal SpeciesNº of animals EF for Enteric Fermenta tion Emissions from Enteric Fermentation EF for Manure Manage ment Emissions due to Manure Management Total emissions from domestic animals (1000s) (kg/head/year ) (ton/year) (kg/head/year ) (ton/year)(Gg/year) C = (A x B) E = (A x D)F =(C + E)/1000 Dairy cattle1.000,057,057000,02,02000,059,00 Non-dairy cattle5.000,049,0245000,01,05000,0250,00 BuffaloNO55,0 5,0 Sheep3.000,05,015000,00,16480,015,48 Goats50,05,0250,00,178,50,26 CamelsNO46,0 1,9 Horses10,018,0180,01,616,00,20 Mules & AssessNO10,0 0,9 Swine1.500,01,52250,03,04500,06,00 Poultry4.000,0NE 0,01872,00,07 Totals 318930,0 12076,50331,01

13. 3B.13 Determining significant animal species >25% Worksheet 4-1s1 Conclusion: Tier 2 method, supported by an enhanced characterization, for the non-dairy cattle No other significant species

14. 3B.14 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 CH 4 emissions Procedure is described in IPCC-GPG (pages 4.10-4.20)

15. 3B.15 Enhanced Characterization Non-Dairy Cattle ParameterSymbolCowsSteerYoungSource Weight (kg)W400450230Table A-2, IPCC-GL V3 Weight Gain (kg/day)WG000.3Table A-2, IPCC-GL V3 Mature Weight (kg)MW400450425Table A-2, IPCC-GL V3 Feeding SituationCaCa 0.280.230.25Table 4-5 IPCC-GPG, and expert’s judgment Females giving birth (%)-67--Table A-2, IPCC-GL V3 Feed Digestibility (%)DE60 Table A-2, IPCC-GL V3 Maintenance coefficientCf i 0.3350.322 Table 4-4 IPCC-GPG Net Energy Maintenance (MJ/day) NE m 30.031.519.0Calculated using equation 4.1, IPCC-GPG Net Energy Activity (MJ/day) NE a 8.47.24.8Calculated using equation 4.2a, IPCC-GPG

16. 3B.16 Enhanced Characterization Non-Dairy Cattle Parameter SymbolCowsSteerYoung Comments Growth coefficient C--0.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NE g --4.0 Calculated using equation 4.3a, IPCC-GPG Pregnancy coefficient CPCP 0.1-- Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NE P 3.0-- Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NE ma /D E 0.49 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth NE ga /DE0.28 Calculated using equation 4.10, IPCC-GPG Gross Energy Intake (MJ/day) GE139.3130.4117.7 Calculated using equation 4.11, IPCC- GPG 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

17. 3B.17 Tier-2 Estimation of CH 4 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 CH 4 conversion rate (Y m ) In this example of country with no CS-data, a default value for Y m (MCF) can be obtained from the IPCC-GPG

18. 3B.18 Tier-2 Estimation of CH 4 emissions Enteric Fermentation - Non-Dairy Cattle ParameterSymb ol CowsSteerYoungComments Gross Energy Intake (MJ/day) (from the enhanced characterization) GE139.3130.4117.7Calculated using equation 4.11, IPCC- GPG CH 4 conversion factorYmYm 0.06 Table 4.8, IPCC-GPG, and EFDB Emission Factor (kg CH 4 /head/yr) EF54.851.346.3Calculated using equation 4.14, IPCC- GPG Portion of group in total population (%) -40 20Expert judgment, industry data Population of group (thousand heads) -2,000 1,000 CH 4 Emissions (Gg CH 4 /yr -11010346Weighed EF= 52

19. 3B.19 Tier-2 Estimation of CH 4 emissions Enteric Fermentation by Non-Dairy Cattle Tier-2 estimation for non-dairy cattle: 259 Gg CH 4 (245 Gg CH 4 by Tier 1) Weighed EF: 52 kg CH 4 /head/yr (49 kg CH 4 /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

20. 3B.20 Medium Level of AD Availability For AD 1, 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

21. 3B.21 Medium Level of AD Availability Climate Region Production SystemPopulation (1,000 hd) CowsSteersYoung Warm Extensive Grazing1,473828610 Intensive Grazing228414120 Feedlot409296 Temperate Extensive Grazing348201161 Intensive Grazing15027575 Feedlot153132 Total5,1532,2541,8411,094 New Total: 5,153·10 3 heads (against FAO: 5,000·10 3 heads )

22. 3B.22 Tier-2 Estimation of CH 4 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’

23. 3B.23 Enhanced characterization, Non-Dairy Cattle Warm Climate - Extensive Grazing ParameterSymbolCow s Stee r Youn g Comments Weight (kg)W420380210Country-specific data Weight Gain (kg/day)WG00.2 Country-specific data Mature Weight (kg)MW420440430Country-specific data Feeding SituationCaCa 0.33 Table 4-5 IPCC-GPG, and expert judgment Females giving birth (%) -60--Country-specific data Feed Digestibility (%)DE57 Country-specific data Maintenance coefficient Cf i 0.3350.322 Table 4-4 IPCC-GPG Net Energy Maintenance (MJ/day) NE m 31.127.717.8Calculated using equation 4.1, IPCC-GPG Net Energy Activity (MJ/day) NE a 10.39.25.9Calculated using equation 4.2a, IPCC-GPG Comments in green indicate improvements over previous example

24. 3B.24 Enhanced characterization, Non-Dairy Cattle Warm Climate - Extensive Grazing Parameter SymbolCowsSteerYoung Comments Growth coefficient C-1.00.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NE g -3.42.4 Calculated using equation 4.3a, IPCC-GPG Pregnancy coefficient CPCP 0.1-- Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NE P 3.1-- Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NE ma /DE0.48 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth NE ga /DE0.26 Calculated using equation 4.10, IPCC-GPG Gross Energy Intake (MJ/day) GE162.2170.0111.2 Calculated using equation 4.11, IPCC- GPG 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

25. 3B.25 Enhanced characterization, Non-Dairy Cattle Temperate Climate - Intensive Grazing ParameterSymbolCow s Stee r YoungComments Weight (kg)W405390240Country-specific data Weight Gain (kg/day)WG0.150.330.65Country-specific data Mature Weight (kg)MW445470452Country-specific data Feeding SituationCaCa 0.17 Table 4-5 IPCC-GPG, and expert judgment Females giving birth (%) -81--Country-specific data Feed Digestibility (%)DE72 Country-specific data Maintenance coefficient Cf i 0.3350.322 Table 4-4 IPCC-GPG Net Energy Maintenance (MJ/day) NE m 30.228.319.6Calculated using equation 4.1, IPCC-GPG Net Energy Activity (MJ/day) NE a 5.14.83.3Calculated using equation 4.2a, IPCC-GPG Comments in green indicate improvements over previous example

26. 3B.26 Enhanced characterization, Non-Dairy Cattle Temperate Climate, Intensive Grazing Parameter SymbolCowsSteerYoung Comments Growth coefficient C0.81.00.9 p.4.15, IPCC-GPG Net Energy Growth (MJ/day) NE g 3.05.79.2 Calculated using equation 4.3a, IPCC-GPG Pregnancy coefficient CPCP 0.1-- Table 4.7, IPCC-GPG Net Energy Pregnancy (MJ/day) NE P 3.0-- Calculated using equation 4.8, IPCC-GPG Portion of GE that is available for maintenance NE ma /DE0.53 Calculated using equation 4.9, IPCC-GPG Portion of GE that is available for growth. NE ga /DE0.34 Calculated using equation 4.10, IPCC-GPG Gross Energy Intake (MJ/day) GE120.1123.9121.5 Calculated using equation 4.11, IPCC- GPG 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

27. 3B.27 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 (Y m ), 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 (Y m =0.06, from Table 4.8, IPCC- GPG). 18 estimates of EF were obtained (next slide)

28. 3B.28 Medium Level of Data Availability Climate Region Productio n System EF (kg CH 4 /head/yr) CowsSteersYoung Warm Extensive Grazing 63.866.9 max 43.8 Intensive Grazing 47.751.548.4 Feedlot41.5 min 49.352.8 Temperate Extensive Grazing 61.566.749.5 Intensive Grazing 47.348.847.8 Feedlot41.5 min 49.352.8 Range from 41.5 to 66.9

29. 3B.29 Medium Level of Data Availability Weighed EF (Tier 2, CS-AD): 57 kg CH 4 /head/yr (range: 42-67 kg CH 4 /head/yr) EF for Tier 2 (with default and aggregated AD): 52 kg CH 4 /head/yr EF for Tier 1: 49 kg CH 4 /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 CH 4 /year Total for Tier 2 (with default and aggregated AD): 259 Gg CH 4 /year Total for Tier 1: 245 Gg CH 4 /year

30. 3B.30 Medium Level of Data Availability Worksheet 4-1s1

31. 3B.31 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)

32. 3B.32 Highest Level of Data Availability Emission factors could be improved by: developing local capacities for measuring CH 4 emissions by individuals characterising diverse feeds used by their CH 4 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

33. 3B.33 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)

34. 3B.34 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 Tier- 1 with default AD/EF Priority should be given to improve the quality of AD estimates

35. 3B.35 Direct N 2 O Emissions from Agricultural Soils NAI GHG Inventory Training Workshop Agriculture Sector

36. 3B.36 Anthropogenic N inputs to soils Mineral fertilizers Histosols cultivation N-fixing crops Sewage sludges Crop residues Animal manures Fraction of … (from the mass balance) Other practices dealing with soil N

37. 3B.37 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 N 2 O 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 AD 1, AD 2 and emission factors For non-significant sub-categories, Tier 1a along with country-specific AD 1 and default AD 2 and emission factors is acceptable AGRICULTURAL SOILS It is also acceptable to mix Tiers 1a and 1b for different N sources, which will depend on the activity data availability

38. 3B.38 Direct N 2 O – 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 EF 1 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 N 2 O 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 N 2 O 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)

39. 3B.39 Use of N-Fertilizers From the FAO database: CropArea (1,000 ha) Crop Yield (kg dm/ha) Use of N Fertilizer (1000 t N) Wheat8241,545n/a Barley 1 356 (371)1,488 (1400)19.1 Maize1,2252,233n/a Rice984,800n/a Soybeans2311,982n/a Potatoes2518,000n/a Total2,779--130 1 Barley data from industry sources, shown in parentheses

40. 3B.40 Direct N 2 O – 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, EF 1 was estimated to be 0.9% for fertilizer applied to barley crops in the country Since there are no organic soils in the country, EF 2 is not needed

41. 3B.41 Synthetic Fertilisers: Determination of F SN and EF 1 F SN : annual amount of fertiliser N applied to soils, adjusted by amount of N that volatilises as NH 3 and NO x To adjust for volatilisation, use IPCC default value from Table 4-17, IPCC Guidelines, V2: 0.1 kg (NO x +NH 3 )-N/kg fertiliser-N It is determined that: F SN = 19,000 (1-0.1) = 17,100 t fertiliser-N (barley) F SN = 111,000 (1-0.1) = 99,900 t fertiliser-N (all other crops) Total fertiliser-N = 117,000 t fertiliser-N EF 1 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 EF 1 is calculated as follows: EF 1 = weighed average= 17.1/117 (0.9) + 99.9/117 (1.25) = 1.20 % From worksheet 4-5s1, the annual emission of N 2 O-N from use of synthetic fertilizer was estimated as 1.40 Gg N 2 O-N

42. 3B.42 Emissions of N 2 O from Synthetic Fertilisers Combined EF (CS and defaultt)

43. 3B.43 Indirect N 2 O Emissions from Agricultural Soils NAI GHG Inventory Training Workshop Agriculture Sector

44. 3B.44 Indirect N 2 O – Agricultural Soils We will assume that the country only covers the following sources: N 2 O (G) : from volatilisation of applied synthetic fertiliser and animal manure N, and its subsequent deposition as NO x and NH 4. N 2 O (L) : from leaching and runoff of applied fertiliser and animal manure Indirect N 2 O emissions are estimated using Tier 1a method and IPCC default emission factors Next slides show calculations as performed by IPCC Software

45. 3B.45 Indirect N 2 O Emissions from Atmospheric Depositions From Table 4-17 IPCC Guidelines V2 From Table 4.18 IPCC-GPG Default value

46. 3B.46 Indirect N 2 O Emissions from Leaching & Runoff From Table 4-17 IPCC Guidelines V2 From Table 4.18 IPCC-GPG

47. 3B.47 Field Burning of Crop Residues NAI GHG Inventory Training Workshop Agriculture Sector

48. 3B.48 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) 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 Only one method is available to estimate emissions from this source category CROP RESIDUES BURNING Main issues derived from the Decision-Tree

49. 3B.49 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 CH 4, CO, N 2 O, NO X Other constants (conversion ratios): C to CH4 or CO (16/12; 28/12, respectively) N to N2O or NOX (44/28; 46/14, respectively); CROP RESIDUES BURNING

50. 3B.50 MODULEAGRICULTURE SUBMODUL E FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEE T 4-4 SHEET1 OF 3 COUNTRY FICTICIOUS LAND YEAR2002 STEP 1STEP 2STEP 3 CropsABCDEFGH (specify locallyAnnualResidue toQuantity ofDry MatterQuantity ofFraction Total Biomass importantProduction Crop RatioResidueFraction Dry Residue Burned inOxidised Burned crops) Fields (Gg crop) (Gg biomass) (Gg dm) C = (A x B) E = (C x D) H = (E x F xG) 0,00 Wheat157501,320.475,000,8517.403,750,750,911.747,53 Maize520015.200,000,52.600,000,50,91.170,00 Rice10501,41.470,000,851.249,500,850,9955,87. 0,00 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 Main residue-producing crops: Cereals (wheat, barley, oat, rye, rice, maize, sorghum, sugar cane) Pulses (peas, bean, lentils) Potatoes, peanut, others Identify the existing residue- producing crops

51. 3B.51 B. Residue/crop Ratio A. Annual crop Production (Gg) C. Quantity of residues (Gg biomass) FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop Priority order for collectable AD 1 : 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 Priority order for non-collectable AD 2 : 1. CS values-research 2. CS values-expert judgment 3. Values from countries with similar conditions 4. Default values (search EFDB)

52. 3B.52 FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop D. Dry matter Fraction E. Total quantity of dry residue (Gg dm) C. Quantity of residue (Gg biomass) from previous slide 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)

53. 3B.53 E. Quantity of dry residue (Gg dm) from previous slide F. Fraction burned in fields H. Total biomass burned (Gg dm burned) FIELD BURNING OF CROP RESIDUES Worksheet 4-4, sheet 1 Flowchart to be applied to each crop G. Fraction oxidised 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) For default values, search EFDB as combustion efficiency 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)

54. 3B.54 4. OPEN THE SHEET 4-4s2 OF “AGRICULTURE” UNDER “SECTORS” MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET2 OF 3 COUNTRYFICTICIOUS LAND YEAR2002 STEP 4 STEP 5 IJKL CarbonTotal CarbonNitrogen-Total Nitrogen Fraction ofReleasedCarbon RatioReleased Crops Residue (Gg C) (Gg N) J = (H x I) L = (J x K) 0,00 Wheat0,485.638,820,01267,67 Maize0,47549,900,0211,00 Rice0,41391,910,0145,49. 0,00

55. 3B.55 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 I. C fraction in residue J. C released (Gg C) 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) K. N/C ratio L. N released (Gg N) Total C and N released are obtained by addding the values obtained per each individual crop

56. 3B.56 Worksheet 4-4, sheet 3 5. OPEN THE SHEET 4-4s3 OF “AGRICULTURE” UNDER “SECTORS” MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET3 OF 3 COUNTRYFICTICIOUS LAND YEAR2002 STEP 6 MNOP Emission RatioEmissionsConversion RatioEmissions from Field Burning of Agricultural Residues (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH 4 0,00532,90 16/1243,87 CO0,06394,84 28/12921,29 N = (L x M) P = (N x O) N2ON2O0,0070,59 44/280,93 NO x 0,12110,18 46/1433,46 Total emission estimates

57. 3B.57 6. GO TO THE “OVERVIEW” MODULE 7. OPEN THE WORHSHEET 4-S2 TABLE 4 SECTORAL REPORT FOR AGRICULTURE (Sheet 2 of 2) SECTORAL REPORT FOR NATIONAL GREENHOUSE GAS INVENTORIES (Gg) GREENHOUSE GAS SOURCE AND SINK CATEGORIES CH 4 N2ON2O NO x CONMVOC 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 Cultivation0 1 Irrigated0 2 Rainfed0 3 Deep Water0 4 Other (please specify) D Agricultural Soils 0 E Prescribed Burning of Savannas10236 F Field Burning of Agricultural Residues (1) 44133921 1 Cereals 2 Pulse 3 Tuber and Root 4 Sugar Cane 5 Other (please specify) G Other (please specify) Total emission estimates

58. 3B.58 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 Total N released (Gg N from all crops) from previous slide M Non-CO 2 emission rates (search EFDB) O Conversion ratios C-N emitted (Gg C emitted as CH 4 or CO; Gg N emitted as N 2 O or NO X ) P1 CH 4 emited (Gg CH4) P2 CO emited (Gg CO) P3 N 2 O emited (Gg N2O) P4 NO X emited (Gg NOX) EFs: If no CS values, use defaults (Table 4-16, Reference Manual, 1996 Revised Guidelines)

59. 3B.59 FIELD BURNING OF CROP RESIDUES Emission factors

60. 3B.60 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (1 of 3) MODULEAGRICULTURE SUBMODUL E FIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEE T 4-4 SHEET1 OF 3 COUNTRY FICTICIOUS YEAR2002 STEP 1 STEP 2 STEP 3 CropsABCDEFGH (specify locally AnnualResidue toQuantity of Dry Matter Quantity of Fraction Total Biomass importantProduction Crop Ratio ResidueFraction Dry Residue Burned inOxidised Burned crops) Fields (Gg crop) (Gg biomass) (Gg dm) C = (A x B) E = (C x D) H = (E x F xG) Wheat18.350,501,5027.525,80,9024.773,20,120,962.735,0 AD from national statistics CS activity data, from research and monitoring

61. 3B.61 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (2 of 3) MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET2 OF 3 COUNTRYFICTICIOUS YEAR2002 STEP 4 STEP 5 IJKL CarbonTotal CarbonNitrogen-Total Nitrogen Fraction ofReleasedCarbon RatioReleased Crops Residue (Gg C) (Gg N) J = (H x I) L = (J x K) Wheat0,451.230,70,00323,94 CS activity data, from research and monitoring

62. 3B.62 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (3 of 3) MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET3 OF 3 COUNTRYFICTICIOUS YEAR2002 STEP 6 MNOP GasEmission RatioEmissionsConversion RatioEmissions (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH 4 0,003113,83 16/125,10 CO0,0673,84 28/12172,30 N = (L x M) P = (N x O) N2ON2O0,0180,07 44/280,11 NO x 0,1210,48 46/141,57 CS values for CH 4 /N 2 O D for CO/NO X

63. 3B.63 FIELD BURNING OF CROP RESIDUES Emission estimates using default values Wheat residues (1 of 3) MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET1 OF 3 COUNTRY FICTICIOU S YEAR2002 STEP 1 STEP 2 STEP 3 CropsABCDEFGH (specify locally AnnualResidue to Quantity of Dry Matter Quantity of Fractio n Total Biomass importan t Productio n Crop RatioResidueFraction Dry Residue Burned in Oxidised Burned crops) Fields (Gg crop) (Gg biomass) (Gg dm) EF ID= 43555 C = (A x B) EF ID= 43636 E = (C x D) EF ID= 45941 H = (E x F xG) Wheat18.350,51,30 23.855, 7 0,83 19.800, 2 0,120,942.140,4 CS value, from monitoring or expert judgment AD: 1. from national statistics, or 2. from FAO database: (www.fao.org, then “FAOSTAT-www.fao.org Agriculture” and “Crops primary”) Activity data, taken from EFDB

64. 3B.64 FIELD BURNING OF CROP RESIDUES Emission estimates using default values Wheat residues (2 of 3) Default activity data, from EFDB MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET2 OF 3 COUNTRYFICTICIOUS YEAR2002 STEP 4 STEP 5 IJKL CarbonTotal CarbonNitrogen-Total Nitrogen Fraction ofReleasedCarbon RatioReleased Crops Residue (Gg C) (Gg N) J = (H x I) L = (J x K) Wheat0,481.027,40,01212,33 EF ID= 43716EF ID= 43796

65. 3B.65 FIELD BURNING OF CROP RESIDUES Emission estimates using CS values Wheat residues (3 of 3) Default values, from EFDB MODULEAGRICULTURE SUBMODULEFIELD BURNING OF AGRICULTURAL RESIDUES WORKSHEET4-4 SHEET3 OF 3 COUNTRYFICTICIOUS YEAR2002 STEP 6 MNOP Emission RatioEmissionsConversion RatioEmissions (Gg C or Gg N) (Gg) N = (J x M) P = (N x O) CH 4 0,0055,14 16/126,85 CO0,0661,64 28/12143,83 N = (L x M) P = (N x O) N2ON2O0,0070,09 44/280,14 NO x 0,1211,49 46/144,90 EF ID= 43583, 43548, 43543, 43549

66. 3B.66 FIELD BURNING OF CROP RESIDUES Differences in emission estimates If CS or D values are used Emissions Per cent Gas emittedGg gas of using difference CS valuesDefaults CH 4 5,106,85-25% CO172,30143,8320% N2ON2O0,110,14-18% NO x 1,574,90-68%

67. 3B.67 Prescribed Burning of Savannas NAI GHG Inventory Training Workshop Agriculture Sector

68. 3B.68 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) 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 Only one methods is available to estimate emissions from this source category

69. 3B.69 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 CH 4, CO, N 2 O, NO X Other constants (conversion ratios): C to CH4 or CO (16/12; 28/12, respectively) N to N2O or NOX (44/28; 46/14, respectively)

70. 3B.70 1.OPEN THE IPCC SOFTWARE AND CHOOSE THE YEAR OF THE INVENTORY 2.GO TO THE MENU BAR AND CLICK IN “SECTORS” AND THEN IN “AGRICULTURE” 3.OPEN THE SHEET 4-3s1 4.FILL IN WITH THE DATA MODULEAGRICULTURE SUBMODULEPRESCRIBED BURNING OF SAVANNAS WORKSHEET4-3 SHEET1 OF 3 COUNTRYFICTICIOUS LAND YEAR2002 STEP 1STEP 2 ABCDEFGH 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) C = (A x B) E = (C x D) G = (E x F)H = (E - G) 15,57108,500,8592,230,4541,50 50,72 0,00 Sources for AD on categories of savannas and area covered by category: 1. National statistics 2. National mapping systems Sources for AD on biomass density: 1. National statistics 2. National vegetation surveys and mapping 3. National expert judgment 4. Data provided by third countries with similar features 5. IPCC defaults (Table 4-14, Reference Manual, 1996 Revised Guidelines) The first 3 steps is to determine: 1. the categories of savannas existing per ecological unit 2. the area burned per category 3. the biomass density per category

71. 3B.71 PRESCRIBED BURNING OF SAVANNAS Flow chart to estimate non-CO 2 emissions To be applied to each savanna category B Biomass density (ton dm/ha) A Area burned (k ha) C Total biomass exposed to burning (Gg dm) E Biomass actually Burned (Gg dm) F F of living biomass burned G Living biomass actually burned (Gg dm) D F actually burned H Dead 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)

72. 3B.72 5. GO SHEET 4-3s2 IN “SECTORS/AGRICULTURE” OF THE IPCC SOFTWARE 6. FILL IT WITH THE DATA MODULEAGRICULTURE SUBMODULEPRESCRIBED BURNING OF SAVANNAS WORKSHEET4-3 SHEET2 OF 3 COUNTRYFICTICIOUS LAND YEAR2002 STEP 3 IJKL 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) Living0,937,350,4516,81 Dead0,9548,195240,94 Living 0,00 Dead 0,00

73. 3B.73 PRESCRIBED BURNING OF SAVANNAS G Living biomass actually burned (Gg dm) from previous slide H Dead biomass actually burned (Gg dm) from previous slide Flow chart to estimate non-CO 2 emissions Applicable per each savanna category I1 Fraction of living biomass oxidised (Gg dm) I2 Fraction of dead biomass oxidised (Gg dm) J1 Oxidised living biomass (Gg dm) J2 Oxidised dead biomass (Gg dm) K1 C fraction of living biomass K2 C fraction of dead biomass L2 C released from dead biomass (Gg C) L1 C released from living biomass (Gg C) L Total C released (Gg C) M N/C ratio N Total N released (Gg N) If no CS values, defaults in EFDB, as combustion efficiency

74. 3B.74 7. GO TO SHEET 4.3s3 IN “SECTORS/AGRICULTURE” 8. FILL IT GO THE DATA MODULEAGRICULTURE SUBMODULEPRESCRIBED BURNING OF SAVANNAS WORKSHEET4-3 SHEET3 OF 3 COUNTRYFICTICIOUS LAND YEAR2002 STEP 4STEP 5 LM N OPQR Total Carbon Released Nitrogen- Carbon Ratio Total Nitrogen Content Emissions Ratio EmissionsConversion Ratio Emissions from Savanna Burning (Gg C) (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,0041,0316/12 CH 4 1,37 0,0615,4628/12 CO36,08 257,750,0153,87 P = (N x O) R = (P x Q) 0,0070,0344/28 N 2 O0,04 0,1210,4746/14 NO x 1,54 TOTAL EMISSION ESTIMATES

75. 3B.75 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 CH 4 N2ON2O NO x CONMVOC 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 Cultivation0 1 Irrigated0 2 Rainfed0 3 Deep Water0 4 Other (please specify) D Agricultural Soils 0 E Prescribed Burning of Savannas10236 F Field Burning of Agricultural Residues (1) 44133921 1 Cereals 2 Pulse 3 Tuber and Root 4 Sugar Cane 5 Other (please specify) G Other (please specify) Total emission estimates From Savanna Burning

76. 3B.76 PRESCRIBED BURNING OF SAVANNAS L Total C released (Gg C) from previous slide N Total N released (Gg N) from previous slide O N2O & NOx emission rates O CH4 & CO emission rates P N2O-N released (Gg N) P CH4-C released (Gg C) P NOx-N released (Gg N) P CO-C released (Gg C) Q N2O & NOx conversion rates Q CH4 & CO conversion rates R N2O emitted (Gg N2O) R NOx emitted (Gg NOX) R CH4 emitted (Gg CH4) R CO emitted (Gg CO) If no CS EFs, defaults in EFDB Applicable to aggregated figures

77. 3B.77 PRESCRIBED BURNING OF SAVANNAS Examples of default emission factors

78. 3B.78 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

79. 3B.79 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values STEP 1STEP 2 ABCDEFGH Savan na catego ry 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) C = (A x B) E = (C x D) G = (E x F) H = (E - G) North 15,57,00108,500,8592,230,5550,72 41,50 Centre 145,85,00729,000,95692,550,50346,28 South 22,04,0088,001,0088,000,4539,60 48,40 Total s 436,60 436,18 AD from national statistics (census, surveys, mapping) CS values (field measurements, expert’s judgment)

80. 3B.80 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values STEP 3 IJKL Savanna category Biomass type 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) North Living0,937,350,414,94 Dead0,9548,190,4521,68 Centre Living0,9324,770,4129,91 Dead0,95280,480,45126,22 South Living0,941,380,416,55 Dead0,9535,740,4516,08 Totals Living 403,50 325,39 Dead 364,41 CS values (field measurements, lab analysis, expert’s judgment)

81. 3B.81 PRESCRIBED BURNING OF SAVANNAS Emission estimates using CS values SUBMODULEPRESCRIBED BURNING OF SAVANNAS WORKSHEET4-3 SHEET3 OF 3 COUNTRYCHILE YEAR2002 STEP 4STEP 5 M N OPQR Nitrogen- Carbon Ratio Total Nitrogen Content Emissions Ratio EmissionsConversi on Ratio Emissions from Savanna Burning (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,0062,0616/12 CH 4 2,75 0,0620,6228/12 CO48,11 0,01424,88 P = (N x O) R = (P x Q) 0,0060,0344/28 N 2 O0,05 0,1210,5946/14 NO x 1,94 CS values for CH4 & N2O D values for CO & NOx

82. 3B.82 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values STEP 1STEP 2 ABCDEFGH 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) C = (A x B) E = (C x D) G = (E x F)H = (E - G) 15,507,00108,500,95103,080,5556,69 EF ID= 43475 EF ID= 43485 EF ID= 43518 46,38 145,806,00874,800,95831,060,55457,08 EF ID= 43445 EF ID= 43485 EF ID= 43518 373,98 22,004,0088,000,9583,600,4537,62 EF ID= 43480 EF ID= 43485 EF ID= 43515 45,98 551,39 466,34 Default values taken from EFDB AD from national statisitcs

83. 3B.83 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values STEP 3 IJKL Savanna category 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) North Living0,9453,290,421,32 Dead0,9443,600,4519,62 Centre Living0,94429,660,4171,86 Dead0,94351,540,45158,19 South Living0,9435,360,414,15 Dead0,9443,220,4519,45 Totals Living 518,31 404,59 Dead 438,36 EF ID= 45949Experts Default values taken from EFDB CS values taken from expert’s judgment

84. 3B.84 PRESCRIBED BURNING OF SAVANNAS Emission estimates using default values SUBMODULEPRESCRIBED BURNING OF SAVANNAS WORKSHEET4-3 SHEET3 OF 3 COUNTRYCHILE YEAR2002 STEP 4STEP 5 M N OPQR Nitrogen- Carbon Ratio Total Nitrogen Content Emissions Ratio EmissionsConversion Ratio Emissions from Savanna Burning (Gg N) (Gg C or Gg N) (Gg) N = (L x M) P = (L x O) R = (P x Q) 0,0052,0216/12 CH 4 2,70 0,0624,2928/12 CO56,64 0,00953,84 P = (N x O) R = (P x Q) EF ID= 45998 0,0070,0344/28 N 2 O0,04 0,1210,4746/14 NO x 1,53 defaults Default values taken from EFDB

85. 3B.85 PRESCRIBED BURNING OF SAVANNAS Difference of estimates PRESCRIBED BURNING OF SAVANNAS Emissions Per cent Gas emitted Gg gas of using difference CS valuesDefaults CH 4 2,752,702% CO48,1156,64-15% N2ON2O0,050,049% NO x 1,941,5327%

86. 3B.86 RICE CULTIVATION NAI GHG Inventory Training Workshop Agriculture Sector

87. 3B.87 RICE CULTIVATION Anaerobic decomposition of organic material in flooded rice fields produces CH 4 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 CH 4 release into the atmosphere: Diffusion loss across the water surface (least important process) CH 4 loss as bubbles (ebullition) (common and significant mechanism, especially if soil texture is not clayey) CH4 transport through rice plants (most important phenomenon)

88. 3B.88 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 CH 4 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

89. 3B.89 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)www.fao.org/ag/agp/agpc/docwww.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)

90. 3B.90 RICE CULTIVATION Main features from decision-tree If no rice is produced, then reported as “NO” If not key source: 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 If keysource: 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

91. 3B.91 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

92. 3B.92 RICE CULTIVATION MODULEAGRICULTURE SUBMODULEMETHANE EMISSIONS FROM FLOODED RICE FIELDS WORKSHEET4-2 SHEET1 OF 1 COUNTRYFICTICIOUS LAND YEAR2002 ABCDE Water Management RegimeHarvested AreaScaling Factor for Methane Emissions Correction Factor for Organic Amendment Seasonally Integrated Emission Factor for Continuously Flooded Rice without Organic Amendment CH 4 Emissions (m 2 /1 000 000 000) (g/m 2 )(Gg) E = (A x B x C x D) IrrigatedContinuously Flooded 0,285122011,40 Intermittently Flooded Single Aeration0,10,52202,00 Multiple Aeration 0,00 RainfedFlood Prone 0,00 Drought Prone 0,00 Deep Water Water Depth 50-100 cm 0,00 Water Depth > 100 cm 0,00 Totals 0,385 13,40 AD from national statistics or international databases (FAO, IRRI) Scaling factor for water management: local research or other country’s use or EFDB ( Agriculture, Rice Production, Intermitently Flooded, Single aeration ) Enhancement factor for organic ammendements: local research or taken from the EFDB (Agriculture, Rice Production) EF: local research or other country’s use or from EFDB Regional units, from national estatistics or mapping agencies or expert judgment

93. 3B.93 THANK YOU SERGIO GONZALEZ sgonzale@inia.cl