3B.1
AGRICULTUREINVENTORY
ELABORATION
PART 2SIMULATION
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 data 93 per cent emission factors 64 per cent methods 11 per cent
STATE-OF-ART OF NAI PARTIES
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)
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
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 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.6
PRELIMINARY KEY SOURCE DETERMINATION
CHILE, 1994 GHG-Inventory (Gg CO2-equivalent) (1)
SECTOR/sub-sector CO2 CH4 N2OTOTALS
Gg/year Gg/year Gg/year
ENERGY 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
- AGRICULTURE, FORESTRY, FISHING 787.1 14.7 3.1 804.9
- 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 44.1 248.0 2162.1
- CEMENT 1021.1 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
0.0
SOLVENT USE 0.0 0.0 0.0 0.0
3B.7
PRELIMINARY KEY SOURCE DETERMINATION
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 1304.8 2313.9
- RICE CULTIVATION 134.4 134.4
- 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
- AGRICULTURAL RESIDUE BURNING 52.0 607.5 659.5
WASTE: 0.0 1560.3 206.7 1767.0
- WASTEWATER TREATMENT: 3.2 3.2
- SOILD WASTE DISPOSAL LANDS 1557.1 1557.1
- INDUSTRIAL SOLID WASTE DISPOSAL 0.0
- UNTREATED WASTE WATER RUNOFF 206.7 206.7
- INDUSTRIAL LIQUID WASTES 202.9 202.9
TOTAL NATIONAL 38097.0 10142.8 9615.2 57854.9
1994 GHG-Inventory of Chile (Gg in CO2-equivalent) (Non-energy sectors)
3B.8
KEY SOURCES FOR THE 1994 GHG-Inventory of Chile
SECTOR/sub-sectorGg/yr CO2-
equiv.
ContributionSector
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
- Sewage waters 3,2 0,0% 100,0% Energy
KSKS
NKSNKS
3B.9
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
INVENTORY ELABORATION.SIGNIFICANCE OF SUBSOURCES
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
3B.11
Determination of Significant Sub-Source 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.12
Low Level of Data Availability
1 Disaggregation between dairy and non-dairy cattle, based on expert`s judgment
MODULE AGRICULTURE
SUBMODULEMETHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC ANIMALS AND MANURE MANAGEMENT
WORKSHEET 4-1
SHEET 1 of 2 METHANE EMISSIONS FROM ENTERIC FERMENTATION
COUNTRY ANYWHERE
YEAR 2003
STEP 1 STEP 2 STEP 3
A B C D E F
Animal SpeciesNº of
animals
EF for Enteric Ferment
ation
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 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 5,0
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 1,9
Horses 10,0 18,0 180,0 1,6 16,0 0,20
Mules & Assess NO 10,0 0,9
Swine 1.500,0 1,5 2250,0 3,0 4500,0 6,00
Poultry 4.000,0 NE 0,018 72,0 0,07
Totals 318930,0 12076,50 331,01
3B.13
Determining significant animal species
MODULE AGRICULTURE
SUBMODULE METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC LIVESTOCKENTERIC FERMENTATION AND MANURE MANAGEMENT
WORKSHEET 4-1
SHEET 1 OF 2 METHANE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT
COUNTRY Hypothetical
YEAR 2003
STEP 1 STEP 2 STEP 3A B C D E F
Livestock Type Number of Animals
Emissions Factor for
Enteric Fermentation
Emissions from Enteric Fermentation
Emissions Factor for Manure
Management
Emissions from Manure
Management
Total Annual Emissions from
Domestic Livestock
(1000s) (kg/head/yr) (t/yr) (kg/head/yr) (t/yr) (Gg)C = (A x B) E = (A x D) F =(C + E)/1000
Dairy Cattle 1000 57 57,000.00 0.00 57.00
Non-dairy Cattle 5000 49 245,000.00 0.00 245.00
Buffalo 0 55 0.00 0.00 0.00
Sheep 3000 5 15,000.00 0.00 15.00
Goats 50 5 250.00 0.00 0.25
Camels 0 46 0.00 0.00 0.00
Horses 10 18 180.00 0.00 0.18
Mules & Asses 0 10 0.00 0.00 0.00
Swine 1500 1.5 2,250.00 0.00 2.25
Poultry 4000 0 0.00 0.00 0.00
Totals 319,680.00 0.00 319.68
>25%
Worksheet 4-1s1
Conclusion: Tier 2 method, supported by an enhanced characterization, for the non-dairy cattle
No other significant species
3B.14
Enhanced CharacterizationNon-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.15
Enhanced CharacterizationNon-Dairy Cattle
Parameter Symbol Cows Steer
Young Source
Weight (kg) 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
Feeding Situation Ca 0.28 0.23 0.25 Table 4-5 IPCC-GPG, and expert’s judgment
Females giving birth (%)
- 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
3B.16
Enhanced CharacterizationNon-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
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
0.49 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
Gross Energy Intake (MJ/day)
GE 139.3 130.4
117.7 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
3B.17
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.18
Tier-2 Estimation of CH4 emissionsEnteric Fermentation - Non-Dairy Cattle
Parameter Symbol
Cows Steer Young
Comments
Gross Energy Intake (MJ/day) (from the enhanced characterization)
GE 139.3
130.4 117.7 Calculated using equation 4.11, IPCC-GPG
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, IPCC-GPG
Portion of group in total population (%)
- 40 40 20 Expert judgment, industry data
Population of group (thousand heads)
- 2,000 2,000 1,000
CH4 Emissions
(Gg CH4/yr
- 110 103 46 Weighed EF= 52
3B.19
Tier-2 Estimation of CH4 emissionsEnteric 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.20
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.21
Medium Level of AD Availability
Climate Region
Production System
Population (1,000 hd)
Cows Steers
Young
Warm Extensive Grazing 1,473 828 610
Intensive Grazing 228 414 120
Feedlot 40 92 96
Temperate
Extensive Grazing 348 201 161
Intensive Grazing 150 275 75
Feedlot 15 31 32
Total 5,153 2,254 1,841 1,094
New Total: 5,153·103 heads (against FAO: 5,000·103 heads )
3B.22
Tier-2 Estimation of CH4 emissionsEnteric 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.23
Enhanced characterization, Non-Dairy Cattle Warm Climate - Extensive
Grazing
Parameter Symbol
Cows
Steer
Young
Comments
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
Feeding Situation Ca 0.33 0.33 0.33 Table 4-5 IPCC-GPG, and expert judgment
Females giving birth (%)
- 60 - - Country-specific data
Feed Digestibility (%)
DE 57 57 57 Country-specific data
Maintenance coefficient
Cfi 0.335
0.322
0.322 Table 4-4 IPCC-GPG
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
Comments in green indicate improvements over previous example
3B.24
Enhanced characterization, Non-Dairy Cattle
Warm Climate - Extensive Grazing
Parameter Symbol
Cows Steer Young
Comments
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
Gross Energy Intake (MJ/day)
GE 162.2 170.0 111.2 Calculated using equation 4.11, IPCC-GPGTo 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.25
Enhanced characterization, Non-Dairy Cattle Temperate Climate - Intensive
Grazing
Parameter Symbol
Cows
Steer
Young
Comments
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
Net Energy Maintenance (MJ/day)
NEm 30.2 28.3 19.6 Calculated using equation 4.1, IPCC-GPG
Net Energy Activity (MJ/day)
NEa 5.1 4.8 3.3 Calculated using equation 4.2a, IPCC-GPG
Comments in green indicate improvements over previous example
3B.26
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
Gross Energy Intake (MJ/day)
GE 120.1
123.9
121.5 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
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 (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, IPCC-GPG).
18 estimates of EF were obtained (next slide)
3B.28
Medium Level of Data Availability
Climate Region
Production System
EF (kg CH4/head/yr)
Cows Steers Young
Warm Extensive Grazing
63.8 66.9max
43.8
Intensive Grazing
47.7 51.5 48.4
Feedlot 41.5min
49.3 52.8
Temperate
Extensive Grazing
61.5 66.7 49.5
Intensive Grazing
47.3 48.8 47.8
Feedlot 41.5min
49.3 52.8
Range from 41.5 to 66.9
3B.29
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.30
Medium Level of Data Availability
MODULE AGRICULTURE
SUBMODULE METHANE AND NITROUS OXIDE EMISSIONS FROM DOMESTIC LIVESTOCKENTERIC FERMENTATION AND MANURE MANAGEMENT
WORKSHEET 4-1
SHEET 1 OF 2 METHANE EMISSIONS FROM DOMESTIC LIVESTOCK ENTERIC FERMENTATION AND MANURE MANAGEMENT
COUNTRY Hypothetical
YEAR 2003
STEP 1 STEP 2 STEP 3A B C D E F
Livestock Type Number of Animals
Emissions Factor for
Enteric Fermentation
Emissions from Enteric Fermentation
Emissions Factor for Manure
Management
Emissions from Manure
Management
Total Annual Emissions from
Domestic Livestock
(1000s) (kg/head/yr) (t/yr) (kg/head/yr) (t/yr) (Gg)C = (A x B) E = (A x D) F =(C + E)/1000
Dairy Cattle 1000 57 57,000.00 0.00 57.00
Non-dairy Cattle 5153 57 293,721.00 0.00 293.72
Buffalo 0 55 0.00 0.00 0.00
Sheep 3000 5 15,000.00 0.00 15.00
Goats 50 5 250.00 0.00 0.25
Camels 0 46 0.00 0.00 0.00
Horses 10 18 180.00 0.00 0.18
Mules & Asses 0 10 0.00 0.00 0.00
Swine 1500 1.5 2,250.00 0.00 2.25
Poultry 4000 0 0.00 0.00 0.00
Totals 368,401.00 0.00 368.40
Worksheet 4-1s1
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)
3B.32
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.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)
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
3B.35
Direct N2O Emissions from Agricultural Soils
NAI GHG Inventory Training WorkshopAgriculture Sector
3B.36
AnthropogenicN inputs to soils
Mineral fertilizers
Histosols cultivation
N-fixing crops
Sewage sludges
Crop residues
Animal manuresFraction of …
(from the mass balance)
Other practicesdealing with soil N
3B.37
Assess individual contribution of different N sources to determineones (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-specificAD1 and default AD2 and emission factors is acceptable
AGRICULTURAL SOILS
It is also acceptable to mix Tiers 1a and 1b for different N sources, which willdepend on the activity data availability
3B.38
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.39
Use of N-FertilizersFrom 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
Barley 1 356 (371) 1,488 (1400) 19.1
Maize 1,225 2,233 n/a
Rice 98 4,800 n/a
Soybeans 231 1,982 n/a
Potatoes 25 18,000 n/a
Total 2,779 -- 130
1 Barley data from industry sources, shown in parentheses
3B.40
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.41
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.42
Emissions of N2O from Synthetic Fertilisers
MODULE AGRICULTURE
SUBMODULE AGRICULTURAL SOILS
WORKSHEET 4-5
SHEET 1 OF 5 DIRECT NITROUS OXIDE EMISSIONS FROM AGRICULTURAL FIELDS, EXCLUDING CULTIVATION OFHISTOSOLS
COUNTRY Hypothetical
YEAR 2003
STEP 1 STEP 2A B C
Type of N input to soil Amount of N Factor for Direct Soil Input Direct Emissions Emissions
EF1
(kg N/yr) (kg N2O–N/kg N) (Gg N2O-N/yr)
C = (A x B)/1 000 000
Synthetic fertiliser (FSN) 117,000,000.00 0.012 1.40
Animal waste (FAW) 65,793,280.00 0.0125 0.82
N-fixing crops (FBN) 0.0125 0.00
Crop residue (FCR) 0.00 0.0125 0.00
Total 2.23
Combined EF(CS and defaultt)
3B.43
Indirect N2O Emissions from
Agricultural Soils
NAI GHG Inventory Training WorkshopAgriculture Sector
3B.44
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.45
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 NH3 AND NOXCOUNTRY Hypothetical
YEAR 2003
STEP 6A B C D E F G H
Type of Synthetic Fraction of Amount of Total N Fraction of Total N Excretion Emission Factor Nitrous Oxide Deposition Fertiliser N Synthetic Synthetic N Excretion by Total Manure N by Livestock that EF4
Emissions
Applied to Fertiliser N Applied to Soil Livestock Excreted that Volatilizes Soil, NFERT
Applied that that Volatilizes NEX Volatilizes
Volatilizes FracGASMFracGASFS
(kg N/yr) (kg N/kg N) (kg N/kg N) (kg N/yr) (kg N/kg N) (kg N/kg N) (kg N2O–N/kg N) (Gg N2O–N/yr)
C = (A x B) F = (D x E) H = (C + F) x G /1 000 000
Total 130000000 0.1 13,000,000.00 249,240,080.00 0.2 49,848,016.00 0.01 0.63
From Table 4-17IPCC Guidelines V2
From Table 4.18IPCC-GPG Default value
3B.46
MODULE AGRICULTURE
SUBMODULE AGRICULTURAL SOILS
WORKSHEET 4-5
SHEET 5 OF 5 INDIRECT NITROUS OXIDE EMISSIONS FROM LEACHING
COUNTRY Hypothetical
YEAR 2003
STEP 7 STEP 8I J K L M N
Synthetic Fertiliser Livestock N Fraction of N That Emission Factor Nitrous Oxide Emissions Total Indirect Use NFERT Excretion NEX Leaches EF5
From Leaching Nitrous Oxide
FracLEACH Emissions
(kg N/yr) (kg N/yr) (kg N/kg N) (Gg N2O–N/yr) (Gg N2O/yr)
M = (I + J) x K x L/1 000 000 N = (H + M)[44/28]
130,000,000.00 249,240,080.00 0.3 0.025 2.84 5.46
Indirect N2O Emissions from Leaching & Runoff
From Table 4-17IPCC Guidelines V2
From Table 4.18IPCC-GPG
3B.47
Field Burning of Crop
Residues
NAI GHG Inventory Training WorkshopAgriculture Sector
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 BURNINGMain issues derived from the Decision-
Tree
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 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);
CROP RESIDUES BURNING
3B.50
MODULE AGRICULTURE
SUBMODU
LE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHE
ET 4-4
SHEET 1 OF 3
COUNTRY
FICTICIOUS LAND
YEAR 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 Productio
n 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
. 0,00 0,00 0,00
1. OPEN THE IPCC SOFTWARE AND CHOOSE THE YEAR OF THE INVENTORY2. CLICK IN “SECTORS” IN THE MENU BAR, AND THEN CLICK IN AGRICULTURE3. 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 theexisting residue-producing crops
3B.51
B. Residue/cropRatio
A. Annual cropProduction
(Gg)
C. Quantity ofresidues
(Gg biomass)
FIELD BURNING OF CROP RESIDUES
Worksheet 4-4, sheet 1
Flowchart to be applied to each crop Priority order forcollectable AD1:
1. Values collected frompublished statistics2. If not available,
values can bederived from:
a) crop area (in kha)b) crop yield(in ton ha-1)
3. From FAO DB
Priority order fornon-collectable AD2:1. CS values-research2. CS values-expert
judgment3. Values from countrieswith similar conditions
4. Default values(search EFDB)
3B.52
FIELD BURNING OF CROP RESIDUES
Worksheet 4-4, sheet 1
Flowchart to be applied to each crop
D. Dry matterFraction
E. Total quantity ofdry residue
(Gg dm)
C. Quantity ofresidue
(Gg biomass)from previous slide
Priority order fornon-collectable AD:1. CS values-research2. CS values-expert
judgment3. Values from countrieswith similar conditions4. IPCC default values
(search EFDB)
3B.53
E. Quantity ofdry residue
(Gg dm)from previous slide
F. Fraction burnedin fields
H. Total biomassburned
(Gg dm burned)
FIELD BURNING OF CROP RESIDUES
Worksheet 4-4, sheet 1
Flowchart to be applied to each crop
G. Fractionoxidised
Priority order fornon-collectable AD:1. CS values-research2. CS values-expert
judgment3. Values from countrieswith similar conditions
(No default values)
For default values,search EFDB as
combustion efficiency
To avoid doublecounting, a mass balance
of crop residue biomass mustbe internally performed:Fburned= Total biomass –(Fremoved from the field+
Featen by animals+Fother uses)
3B.54
4. OPEN THE SHEET 4-4s2 OF “AGRICULTURE” UNDER “SECTORS”
MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 2 OF 3
COUNTRY FICTICIOUS LAND
YEAR 2002
STEP 4 STEP 5
I J K L
Carbon Total Carbon Nitrogen- Total Nitrogen
Fraction of Released Carbon Ratio Released
Crops 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.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 slideI. C fractionin residue
J. C released(Gg C)
Priority order fornon-collectable AD:1. CS values-research2. CS values-expert
judgment3. Values from countrieswith similar conditions
4. Default values(search EFDB)
K. N/C ratio
L. N released(Gg N)
Total C and N releasedare obtained by
addding the valuesobtained per each
individual crop
3B.56
Worksheet 4-4, sheet 3
5. OPEN THE SHEET 4-4s3 OF “AGRICULTURE” UNDER “SECTORS”
MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 3 OF 3
COUNTRY FICTICIOUS LAND
YEAR 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
Total emissionestimates
3B.57
6. GO TO THE “OVERVIEW” MODULE7. OPEN THE WORHSHEET 4-S2TABLE 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
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 0
E Prescribed Burning of Savannas 1 0 2 36
F Field Burning of Agricultural Residues (1) 44 1 33 921
1 Cereals
2 Pulse
3 Tuber and Root
4 Sugar Cane
5 Other (please specify)
G Other (please specify)
Total emissionestimates
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
MNon-CO2
emission rates(search EFDB)
OConversion
ratios
C-Nemitted
(Gg C emitted asCH4 or CO;
Gg N emitted asN2O or NOX)
P1CH4 emited(Gg CH4)
P2CO emited
(Gg CO)
P3N2O emited(Gg N2O)
P4NOX emited(Gg NOX)
EFs:If no CS values,
use defaults(Table 4-16, Reference Manual,
1996 Revised Guidelines)
3B.59
FIELD BURNING OF CROP RESIDUES
Emission factors
3B.60
FIELD BURNING OF CROP RESIDUESEmission estimates using CS values
Wheat residues (1 of 3)
MODULE AGRICULTURE
SUBMODU
LE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHE
ET 4-4
SHEET 1 OF 3
COUNTRY
FICTICIOUS
YEAR 2002
STEP 1 STEP
2 STEP 3
Crops A B C D E F G H
(specify locally
Annual Residue
toQuantity of
Dry Matter
Quantity of
Fraction Fractio
n Total
Biomass
important Production Crop Ratio
ResidueFractio
nDry
ResidueBurned
in Oxidise
d Burned
crops) Fields
(Gg crop) (Gg biomass) (Gg dm) (Gg dm)
C = (A x B) E = (C x
D)
H = (E x F xG)
Wheat 18.350,50 1,50 27.525,8 0,9024.773,
20,12 0,96 2.735,0
AD fromnational statistics
CS activity data,from research and
monitoring
3B.61
FIELD BURNING OF CROP RESIDUESEmission estimates using CS values
Wheat residues (2 of 3) MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 2 OF 3
COUNTRY FICTICIOUS
YEAR 2002
STEP 4 STEP 5
I J K L
Carbon Total Carbon Nitrogen- Total Nitrogen
Fraction of Released Carbon Ratio Released
Crops Residue
(Gg C) (Gg N)
J = (H x I) L = (J x K)
Wheat 0,45 1.230,7 0,0032 3,94
CS activity data,from research and
monitoring
3B.62
FIELD BURNING OF CROP RESIDUESEmission estimates using CS values
Wheat residues (3 of 3) MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 3 OF 3
COUNTRY FICTICIOUS
YEAR 2002
STEP 6
M N O P
Gas Emission Ratio EmissionsConversion
RatioEmissions
(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)
N2O 0,018 0,07 44/28 0,11
NOx 0,121 0,48 46/14 1,57
CS values for CH4/N2OD for CO/NOX
3B.63
FIELD BURNING OF CROP RESIDUESEmission estimates using default
valuesWheat residues (1 of 3)
MODULE AGRICULTURE
SUBMODULE
FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET
4-4
SHEET 1 OF 3
COUNTRY FICTICIOUS
YEAR 2002
STEP 1 STEP 2 STEP
3
Crops A B C D E F G H
(specify locally
Annual Residue
toQuantit
y of Dry
Matter Quantit
y of Fracti
on Fraction
Total Biomass
important
Production
Crop Ratio
Residue FractionDry
Residue
Burned in
Oxidised Burned
crops) Fields
(Gg crop)
(Gg biomass
)
(Gg dm)
(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
0,8319.800
,20,12 0,94 2.140,4CS value,
from monitoring orexpert judgment
AD:1. from
national statistics, or2. from FAO database:
(www.fao.org, then “FAOSTAT-Agriculture” and “Crops primary”)
Activity data,taken from EFDB
3B.64
FIELD BURNING OF CROP RESIDUESEmission estimates using default
valuesWheat residues (2 of 3)
Default activity data,from EFDB
MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 2 OF 3
COUNTRY FICTICIOUS
YEAR 2002
STEP 4 STEP 5
I J K L
Carbon Total Carbon Nitrogen- Total Nitrogen
Fraction of Released Carbon Ratio Released
Crops Residue
(Gg C) (Gg N)
J = (H x I) L = (J x K)
Wheat 0,48 1.027,4 0,012 12,33
EF ID= 43716 EF ID= 43796
3B.65
FIELD BURNING OF CROP RESIDUESEmission estimates using CS values
Wheat residues (3 of 3)
Default values,from EFDB
MODULE AGRICULTURE
SUBMODULE FIELD BURNING OF AGRICULTURAL RESIDUES
WORKSHEET 4-4
SHEET 3 OF 3
COUNTRY FICTICIOUS
YEAR 2002
STEP 6
M N O P
Emission
RatioEmissions 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)
N2O 0,007 0,09 44/28 0,14
NOx 0,121 1,49 46/14 4,90
EF ID=43583, 43548,
43543, 43549
3B.66
FIELD BURNING OF CROP RESIDUESDifferences in emission estimates
If CS or D values are used
Emissions Emissions Per cent
Gas emitted
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%
3B.67
Prescribed Burning of Savannas
NAI GHG Inventory Training WorkshopAgriculture Sector
3B.68
PRESCRIBED BURNING OF SAVANNASMain 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
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 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.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 4-3s14. FILL IN WITH THE DATA MODULE AGRICULTURE
SUBMODULE PRESCRIBED BURNING OF SAVANNAS
WORKSHEET 4-3
SHEET 1 OF 3
COUNTRY FICTICIOUS LAND
YEAR 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) (Gg dm) (Gg dm) (Gg dm)
C = (A x B) E = (C x D) G = (E x F) H = (E - G)
15,5 7 108,50 0,85 92,23 0,45 41,50
50,72
0,00 0,00 0,00
0,00
Sources for AD on categories of savannas andarea covered by category:
1. National statistics2. National mapping systems
Sources for AD on biomass density:1. National statistics
2. National vegetation surveys and mapping3. National expert judgment
4. Data provided by third countries with similar features5. IPCC defaults (Table 4-14, Reference Manual, 1996
Revised Guidelines)
The first 3 steps isto determine:
1. the categories ofsavannas existing per
ecological unit2. the area burned
per category3. the biomass density
per category
3B.71
PRESCRIBED BURNING OF SAVANNASFlow chart to estimate non-CO2 emissionsTo be applied to each savanna category
BBiomass density
(ton dm/ha)
AArea burned
(k ha)
CTotal biomass
exposed to burning(Gg dm)
EBiomass actually
Burned(Gg dm)
FF of living
biomass burnedG
Living biomassactually burned
(Gg dm)
DF actually burned
HDead biomass
actually burned(Gg dm)
Ideally, CS valuesbased on measurements.If not, CS values based
on expert judgment.If not, default values
(search EFDB)
3B.72
5. GO SHEET 4-3s2 IN “SECTORS/AGRICULTURE” OF THE IPCC SOFTWARE6. FILL IT WITH THE DATA
MODULE AGRICULTURE
SUBMODULE PRESCRIBED BURNING OF SAVANNAS
WORKSHEET 4-3
SHEET 2 OF 3
COUNTRY FICTICIOUS LAND
YEAR 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.73
PRESCRIBED BURNING OF SAVANNAS
GLiving biomass
actually burned (Gg dm)from previous slide
HDead biomass
actually burned (Gg dm)from previous slide
Flow chart to estimate non-CO2 emissionsApplicable per each savanna category
I1Fraction of livingbiomass oxidised
(Gg dm)
I2Fraction of deadbiomass oxidised
(Gg dm)
J1Oxidised living
biomass(Gg dm)
J2Oxidised dead
biomass(Gg dm)
K1C fraction of
living biomass
K2C fraction of
dead biomass
L2C released fromdead biomass
(Gg C)
L1C released fromliving biomass
(Gg C)
LTotal C released
(Gg C)
MN/C ratio
NTotal N released
(Gg N)
If no CS values,defaults in EFDB, as
combustion efficiency
3B.74
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 3 OF 3
COUNTRY FICTICIOUS LAND
YEAR 2002
STEP 4 STEP 5
L M N O P Q R
Total Carbon
Released
Nitrogen- Carbon
Ratio
Total Nitrogen Content
Emissions
Ratio
Emissions Conversion
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)
0,004 1,03 16/12 CH4 1,37
0,06 15,46 28/12 CO 36,08
257,75 0,015 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
TOTAL EMISSIONESTIMATES
3B.75
9. GO TO “OVERVIEW” MODULE8. OPEN THE WORKSHEET 4S2TABLE 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
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 0
E Prescribed Burning of Savannas 1 0 2 36
F Field Burning of Agricultural Residues (1) 44 1 33 921
1 Cereals
2 Pulse
3 Tuber and Root
4 Sugar Cane
5 Other (please specify)
G Other (please specify)
Total emission estimatesFrom Savanna Burning
3B.76
PRESCRIBED BURNING OF SAVANNAS
LTotal C released
(Gg C)from previous slide
NTotal N released
(Gg N)from previous slide
ON2O & NOx
emission rates
OCH4 & CO
emission rates
PN2O-N released
(Gg N)
PCH4-C released
(Gg C)
PNOx-N released
(Gg N)
PCO-C released
(Gg C)
QN2O & NOx
conversion rates
QCH4 & CO
conversion rates
R N2O emitted
(Gg N2O)
RNOx emitted
(Gg NOX)
RCH4 emitted
(Gg CH4)
RCO emitted
(Gg CO)
If no CS EFs,defaults in EFDB
Applicable to aggregated figures
3B.77
PRESCRIBED BURNING OF SAVANNASExamples of default emission factors
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
3B.79
PRESCRIBED BURNING OF SAVANNAS
Emission estimates using CS values
STEP 1 STEP 2
A B C D E F G H
Savanna category
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)
North15,5 7,00 108,50 0,85 92,23 0,55 50,72
41,50
Centre
145,8 5,00 729,00 0,95 692,55 0,50 346,28
346,28
South22,0 4,00 88,00 1,00 88,00 0,45 39,60
48,40
Totals
436,60
436,18
AD from national statistics(census, surveys, mapping)
CS values(field measurements, expert’s
judgment)
3B.80
PRESCRIBED BURNING OF SAVANNAS
Emission estimates using CS values
STEP 3
I J K L
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)
NorthLiving 0,9 37,35 0,4 14,94
Dead 0,95 48,19 0,45 21,68
CentreLiving 0,9 324,77 0,4 129,91
Dead 0,95 280,48 0,45 126,22
SouthLiving 0,9 41,38 0,4 16,55
Dead 0,95 35,74 0,45 16,08
TotalsLiving 403,50 325,39
Dead 364,41
CS values(field measurements, lab
analysis, expert’s judgment)
3B.81
PRESCRIBED BURNING OF SAVANNAS
Emission estimates using CS 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
Nitrogen-
Carbon Ratio
Total Nitrogen
Content
Emissions Ratio
Emissions
Conversion
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)
0,006 2,06 16/12 CH4 2,75
0,06 20,62 28/12 CO 48,11
0,0142 4,88 P = (N x
O)
R = (P x Q)
0,006 0,03 44/28 N2O 0,05
0,121 0,59 46/14 NOx 1,94
CS values for CH4 & N2OD values for CO & NOx
3B.82
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 0,95 103,08 0,55 56,69
EF ID= 43475
EF ID= 43485
EF ID= 43518
46,38
145,80 6,00 874,80 0,95 831,06 0,55 457,08
EF ID= 43445
EF ID= 43485
EF ID= 43518
373,98
22,00 4,00 88,00 0,95 83,60 0,45 37,62
EF ID= 43480
EF ID= 43485
EF ID= 43515
45,98
551,39
466,34
Default valuestaken from EFDB
AD fromnational statisitcs
3B.83
PRESCRIBED BURNING OF SAVANNASEmission estimates using default
values STEP 3
I J K L
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)
NorthLiving 0,94 53,29 0,4 21,32
Dead 0,94 43,60 0,45 19,62
CentreLiving 0,94 429,66 0,4 171,86
Dead 0,94 351,54 0,45 158,19
SouthLiving 0,94 35,36 0,4 14,15
Dead 0,94 43,22 0,45 19,45
TotalsLiving 518,31 404,59
Dead 438,36
EF ID= 45949 Experts
Default valuestaken from EFDB
CS valuestaken from expert’s
judgment
3B.84
PRESCRIBED BURNING OF SAVANNASEmission 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
Nitrogen-
Carbon Ratio
Total Nitrogen Content
Emissions
Ratio
Emissions Conversion
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)
0,005 2,02 16/12 CH4 2,70
0,06 24,29 28/12 CO 56,64
0,0095 3,84 P = (N x
O)
R = (P x Q)
EF ID= 45998
0,007 0,03 44/28 N2O 0,04
0,121 0,47 46/14 NOx 1,53
defaults
Default valuestaken from EFDB
3B.85
PRESCRIBED BURNING OF SAVANNAS
Difference of estimates
PRESCRIBED BURNING OF SAVANNAS
Emissions Emissions Per cent
Gas emitted
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%
3B.86
RICE CULTIVATION
NAI GHG Inventory Training WorkshopAgriculture Sector
3B.87
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.88
RICE CULTIVATIONMethodological
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.89
RICE CULTIVATIONActivity 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.90
RICE CULTIVATIONMain 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
3B.91
RICE CULTIVATIONNumerical 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.92
RICE CULTIVATION
MODULE AGRICULTURE
SUBMODULE METHANE EMISSIONS FROM FLOODED RICE FIELDS
WORKSHEET 4-2
SHEET 1 OF 1
COUNTRY FICTICIOUS LAND
YEAR 2002
A B C D E
Water Management Regime 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
(m2 /1 000 000 000) (g/m2) (Gg)
E = (A x B x C x D)
Irrigated
Continuously Flooded
0,285 1 2 20 11,40
Intermittently Flooded
Single Aeration
0,1 0,5 2 20 2,00
Multiple Aeration
0,00
Rainfed Flood 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 statisticsor international databases
(FAO, IRRI)
Scaling factor for watermanagement: local research or
other country’s use or EFDB(Agriculture, Rice Production,
Intermitently Flooded, Single aeration)
Enhancement factor for organicammendements: local research or
taken from the EFDB(Agriculture, Rice Production)
EF: local researchor other country’s use
or from EFDBRegional units, fromnational estatistics ormapping agencies or
expert judgment
Top Related