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