Overview

Worksheets

Summary

Direct Fertilizer N

Indirect Fertilizer N

Direct Crop Residues N

Indirect Crop Residues N

Total N

Rate N

Landuse(ha)

CropProd

CRFactors

N2OEqu&Factors

Lookups

Assumptions

This workbook calculates Total change in Fertilizer (N, P2O5, and K2O) and Pesticide (fungicide and bactericides, herbicides, 

consumption based on EPA's predictions for land use change to 2022. Values are provided by country, region, and crop (where 

use (hectares) was applied to the rate of fertilizer and pesticide consumption (kg per hectare) by country and region to determin

consumption (kg). Regional rates of application were calculated by dividing the sum of total consumption for all countries in tha

agricultural area. Data is formatted to be easily comparable with EPA’s Land Use spreadsheet. 

The four purple tabs contain greenhouse gas emisison calculations for changes in fertilizer application applied to the total chan

and crop production through 2022. Blue tabs contain data on the total change in fertilizer and pesticide consumption for countri

combinations due to EPA’s predicted change in agricultural land-use. Tan tabs contain data on the rate of application of fertilize

by calculating total consumption divided by total area (Area * %Area Fertilizer) across countries and regions. For this analysis, t

equal to "Other CIS", and "Russia and Ukraine" is set equal to "Russia". Historical data for fertilizer and pesticides consumption 

consumption data from the INternational Fertilizer Industry Association (IFA) and FAO agricultural statistics for agricultural area 

consumption (FAOStat), and fertilizer consumption (Fertistat), and is provided in the "Pesticides" and "Fertilizer" worksheets. R

assumptions are also provided in this workbook.

Info on IFA vs Fertistat data

Fertilizer Data This dataset computes the N20 emissions associated with camelina production compared to soybean production. Camelina fer

assumed to be 40 pounds per acre based on the information gathered from a literature review summarized in the FINAL Came

Soybean application rates are taken from the FASOM model for comparison purposes. Fertilizer application rate is then multip

agricultural land use to estimate fertilizer-related emissions.
Description

Summary of Greenhouse Gas emissions from changes in feritlizer application through 2022

Direct Fertilizer N2O emissions from synthetic fertilizers

Indirect Fertilizer N2O emissions from synthetic fertilizers

Direct N2O emissions from crop residue 

Indirect N2O emissions from crop residue 

Total change in Nitrogen fertilizer consumption due to changes in land use (mg)

Rate of Nitrogen fertilizer application (kg/ha)

Change in land use ('000 hectares) calculated by EPA

Change in crop production ('000 metric tons)

Default factors for estimation of N added to soils from crop residues

IPCC (2006) Tier 1 equations and factors for estimating projections in GHG emissions from fertilizer consumption.

Lookup codes

Assumptions behind estimating projections for GHG emissions

otal change in Fertilizer (N, P2O5, and K2O) and Pesticide (fungicide and bactericides, herbicides, and insecticides) 

A's predictions for land use change to 2022. Values are provided by country, region, and crop (where available). Change in land 

 to the rate of fertilizer and pesticide consumption (kg per hectare) by country and region to determine the total change in 

 application were calculated by dividing the sum of total consumption for all countries in that region by the sum of total 

rmatted to be easily comparable with EPA’s Land Use spreadsheet. 

n greenhouse gas emisison calculations for changes in fertilizer application applied to the total change in agricultural land use 

h 2022. Blue tabs contain data on the total change in fertilizer and pesticide consumption for countries and country/crop 

 predicted change in agricultural land-use. Tan tabs contain data on the rate of application of fertilizers and pesticides derived 

ption divided by total area (Area * %Area Fertilizer) across countries and regions. For this analysis, the category "CIS" is set 

Russia and Ukraine" is set equal to "Russia". Historical data for fertilizer and pesticides consumption is based on fertilizer 

 INternational Fertilizer Industry Association (IFA) and FAO agricultural statistics for agricultural area harvested, pesticide 

d fertilizer consumption (Fertistat), and is provided in the "Pesticides" and "Fertilizer" worksheets. Region definitions and data 

ded in this workbook.

N20 emissions associated with camelina production compared to soybean production. Camelina fertilizer application rates are 

per acre based on the information gathered from a literature review summarized in the FINAL Camelina Calculations.xls. 

are taken from the FASOM model for comparison purposes. Fertilizer application rate is then multiplied by change in 

mate fertilizer-related emissions.
Total Emissions from Inorganic Fertilizer and Crop Residues Applied to Agricultural Soils (kg N2O)

(Per thousand ha)

Camelina Soybean

 - -

US Average 1,607.3 -

 - -

Corn Belt - 706.8

Great Plains - 587.9

Lake States - 567.4

North East - 615.5

South Central - 522.2

South East - 550.1

Southwest - 401.3
Direct N2O Emissions from Synthetic Fertilizer Application (kg N2O)

Camelina Soybean

 - -

US Average 704.629 -

 - -

Corn Belt - 138

Great Plains - 126.846

Lake States - 62

North East - 138

South Central - 86

South East - 144

Southwest - 111

convert Mg to kg

Direct Inorganic Fertilizer EF (kg N20-N/kg N)

convert N2O-N to N2O
Indirect N2O Emissions from Synthetic Fertilizer Application (kg N2O)

Cotton Soybean

 - -

US Average 229.0043 -

 - -

Corn Belt - 45

Great Plains - 41.225

Lake States - 20

North East - 45

South Central - 28

South East - 47

Southwest - 36

convert Mg to kg

Volatilization EF [kg N2O–N/(kg NH3–N + NOX–N volatilised)]

Leaching/Runoff EF (kg N20-N/kg N leaching or runoff)

Volatilization from synthetic fertilizer [(kg NH3–N + NOx–N)/kg N applied]

N losses by leaching/runoff (N losses by leaching or runoff/kg N addition)

convert N2O-N to N2O
Direct Emissions from Crop Residues (kg N2O)

Factors not available from IPCC

Camelina Soybean

US Average 549.9116

Corn Belt 428

Great Plains 342.731

Lake States 396

North East 353

South Central 334

South East 293

Southwest 207

convert thousand hectares to hectares

convert Mg to kg

Direct Crop Residue EF

convert N2O-N to N2O

Fraction of palm crop that is renewed annually*

*Age at replanting is 23 years in: Khalid, H, ZZ Zin, and JM Anderson. "Nutrient Cycling in an Oil Palm 

* Age at replanting 20-25 years in Kee, KK. "Nutrient reserves and recycling from oil palm trunks at 
ent Cycling in an Oil Palm Plantation: The Effects of Residue Management Practices During Replanting on Dry Matter and Nutrient Uptake o

g from oil palm trunks at replanting" in 4th International Crop Science Congress. Available at: http://www.cropscience.org.au/icsc2004/poste
tter and Nutrient Uptake of Young Palms." Journal of Oil Palm Research Vol. 12 No. 2,. December 2000, p. 29-37. Available at: http://palmo

ce.org.au/icsc2004/poster/2/3/376_keekk.htm
Available at: http://palmoilis.mpob.gov.my/publications/joprv12n2-p4.pdf
Indirect Emissions from Crop Residues (kg N2O)

Factors not available from IPCC

Camelina Soybean

US Average 123.73011

Corn Belt 96

Great Plains 77.114

Lake States 89

North East 79

South Central 75

South East 66

Southwest 47

convert thousand hectares to hectares

convert Mg to kg

Leaching/Runoff EF (kg N20-N/kg N leaching or runoff)

N losses by leaching/runoff (N losses by leaching or runoff/kg N addition)

convert N2O-N to N2O

Fraction of palm crop that is renewed annually*

*Age at replanting is 23 years in: Khalid, H, ZZ Zin, and JM Anderson. "Nutrient Cycling in an Oil Palm 

* Age at replanting 20-25 years in Kee, KK. "Nutrient reserves and recycling from oil palm trunks at 
ent Cycling in an Oil Palm Plantation: The Effects of Residue Management Practices During Replanting on Dry Matter and Nutrient Uptake o

g from oil palm trunks at replanting" in 4th International Crop Science Congress. Available at: http://www.cropscience.org.au/icsc2004/poste
ter and Nutrient Uptake of Young Palms." Journal of Oil Palm Research Vol. 12 No. 2,. December 2000, p. 29-37. Available at: http://palmo

ce.org.au/icsc2004/poster/2/3/376_keekk.htm
Available at: http://palmoilis.mpob.gov.my/publications/joprv12n2-p4.pdf
Rate of N Application (kg/ha)

Column Index 3 7

Camelina Soybean

US Average 44.8

 33.6

Corn Belt 8.8

Great Plains 8.1

Lake States 4.0

North East 8.8

South Central 5.5

South East 9.2

Southwest 7.1

Conversions

1 kg
Change in Land Use (Thousands of Hectares)

Blue Print = Terminology changed to match Fertistat/FAO nomenclature

Column Index 3 7

Camelina Soybean

US Average 1.00000

Corn Belt 1.0

Great Plains 1.00000

Lake States 1.0

North East 1.0

South Central 1.0

South East 1.0

Southwest 1.0
Change in Total Production (000 MT)

Blue Print = Terminology changed to match Fertistat/FAO nomenclature

Column Index 3 7

Camelina Soybean

US Average 1.8491

 1.8491

Corn Belt 3.380

Great Plains 2.705

Lake States 3.125

North East 2.787

South Central 2.633

South East 2.314

Southwest 1.636

Table 11.2 DEFAULT FACTORS FOR ESTIMATION OF N ADDED TO SOILS FROM CROP RESIDUES a 

A B C D E

Crop Crop Area

Crop 

Harveste

d

Dry matter 

fraction of 

harvested 

product 

(DRY) 

Slope 

± 2 s.d. as 

% of mean Intercept 

± 2 s.d. as 

% of mean 

Units ha kg

Major crop types 

Grains 0.88 1.09 ± 2% 0.88 ± 6% 

Beans & pulsesb 0.91 1.13 ± 19% 0.85 ± 56% 

Tubersc 0.22 0.10 ± 69% 1.06 ± 70% 

Root crops, otherd 0.94 1.07 ± 19% 1.54 ± 41% 

N-fixing forages 0.90 0.30 ± 50% default 0.00 - 

Non-N-fixing forages 0.90 0.30 ± 50% default 0.00 - 

Perennial grasses 0.90 0.30 ± 50% default 0.00 - 

Grass-clover mixtures 0.90 0.30 ± 50% default 0.00 - 

Individual crops 

Maize 0.87 1.03 ± 3% 0.61 ± 19% 

Wheat 0.89 1.51 ± 3% 0.52 ± 17% 

Above-ground residue dry matter AGDM(T) (Mg/ha): 

AGDM(T) = Crop(T) * slope(T) + intercept(T) 

Wheat 0.89 1.51 ± 3% 0.52 ± 17% 

Rice 0.89 0.95 ±19% 2.46 ± 41% 

Barley 0.89 0.98 ± 8% 0.59 ± 41% 

Oats 0.89 0.91 ± 5% 0.89 ± 8% 

Millet 0.90 1.43 ± 18% 0.14 ± 308% 

Sorghum 0.89 0.88 ± 13% 1.33 ± 27% 

Rye

e

0.88 1.09 ± 50% default 0.88 ± 50% default 

Soybeanf

0.91 0.93 ± 31% 1.35 ± 49% 

Dry beang

0.90 0.36 ± 100% 0.68 ± 47% 

Potatoh

0.22 0.10 ± 69% 1.06 ± 70% 

Peanut (w/pod)i 0.94 1.07 ± 19% 1.54 ± 41% 

Alfalfaj

0.90 0.29 ± 31% 0.00 - 

Non-legume hayj 0.90 0.18 ± 50% default 0.00 - 

Oil Palm

Items highlighted indicate crops where NA data has been pulled from crop categories to estimate N2O emissions in the Crop Re

a Source: Literature review by Stephen A. Williams, Natural Resource Ecology Laboratory, Colorado State University. (Email: st

of the original references is given in Annex 11A.1.

b The average above-ground residue:grain ratio from all data used was 2.0 and included data for soya bean, dry bean, lentil, co

c Modelled after potatoes.

d Modelled after peanuts.

e No data for rye. Slope and intercept values are those for all grain. Default s.d.

f The average above-ground residue:grain ratio from all data used was 1.9.

g Ortega, 1988 (see Annex 11A.1). The average above-ground residue:grain ratio from this single source was 1.6. default s.d. f
h The mean value for above-ground residue:tuber ratio in the sources used was 0.27 with a standard error of 0.04.

I The mean value for above-ground residue: pod yield in the sources used was 1.80 with a standard error of 0.10.

j Single source. Default s.d. for root:AGB.

k This is the average above-ground biomass reported as litter or harvest losses. This does not include reported stubble, which a

l Estimate of root turnover to above-ground production based on the assumption that in natural grass systems below-ground bio

root turnover in these systems averages about 40% (30% to 50%) per year. Default s.d.

m This is an estimate of non-tuber roots based on the root:shoot values found for other crops. If unmarketable tuber yield is retu

(unmarketable yield = 0.08 * marketable yield = 0.29 * above-ground biomass) suggest that the total residues returned might the

n This is an estimate of root turnover in perennial systems. Default s.d.

p It is assumed here that grass dominates the system by 2 to 1 over legumes.

Khalid, H; ZZ Zin, and JM Anderson. "Decomposition Processes and Nutrient Release Patterns of Oil Palm Residues." Journa

http://palmoilis.mpob.gov.my/publications/joprv12n1-46.pdf

TABLE 1. RESOURCE QUALITY CHARACTERISTICS OF FRESH OIL PALM RESIDUES 

Nutrient Leaflet Rachis Trunk Root 

N 2.66 0.44 0.58 0.41

P 0.15 0.05 0.06 0.04

K 1.33 1.8 1.86 0.9

Ca 0.62 0.55 0.38 0.07

Mg 0.26 0.17 0.15 0.11

SiO, 1.55 0.39 0.84 0.52

C 47.91 47.34 47.77 48

C/N ratio 18 107 82 117

%

C/N ratio 18 107 82 117

Lignin 24.96 20.96 18.14 23.77

Lignin/N ratio 9.38 47.64 31.28 57.98

Holocellulose 69.86 73.85 83.06 67.39
ESIDUES a 

F G H

N content 

of aboveground 

residues 

(NAG) 

Ratio of 

belowground 

residues to 

aboveground 

biomass 

(RBG-BIO) 

N content 

of belowground 

residues 

(NBG) 

R

2

 adj. 

0.65 0.006 0.22 0.009

0.28 0.008 0.19 0.008

0.18 0.019 0.20 0.014

0.63 0.016 0.20 0.014

- 0.027 0.40 0.022

- 0.015 0.54 0.012

- 0.015 0.80 0.012

- 0.025 0.80 0.016

0.76 0.006 0.22 0.007

0.68 0.006 0.24 0.009

GDM(T) (Mg/ha): 

0.68 0.006 0.24 0.009

0.47 0.007 0.16 NA 

0.68 0.007 0.22 0.014

0.45 0.007 0.25 0.008

0.50 0.007 NA NA 

0.36 0.007 NA 0.006

- 0.005 NA 0.011

0.16 0.008 0.19 0.008

0.15 0.010 NA 0.010

0.18 0.019 0.20 0.014

0.63 0.016 NA NA 

- 0.027 0.40 0.019

- 0.150 0.54 0.012

0.012

N2O emissions in the Crop Residues N worksheet

do State University. (Email: stevewi@warnercnr.colostate.edu) for CASMGS (http://www.casmgs.colostate.edu/). A list

soya bean, dry bean, lentil, cowpea, black gram, and pea.

 source was 1.6. default s.d. for root:AGB.
ard error of 0.04.

rd error of 0.10.

ude reported stubble, which averaged 0.165 x Reported Yields. Default s.d.

ass systems below-ground biomass is approximately equal to twice (one to three times) the above-ground biomass and that

nmarketable tuber yield is returned to the soil then data are derived from Vangessel and Renner, 1990 (see Annex 11A.1)

al residues returned might then be on the order of 0.49 * above-ground biomass. Default s.d.

f Oil Palm Residues." Journal of Oil Palm Research Vol. 12 No. I, June 2000, p. 46-63
 (http://www.casmgs.colostate.edu/). A list
hree times) the above-ground biomass and that

gessel and Renner, 1990 (see Annex 11A.1)

ass. Default s.d.
N2O Equations and Factors

Source: IPCC (2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Vol. 4: Agriculture, Forestry; and Other L

Direct N2O Emissions

Direct Emissions (Overall Equation)

Emissions =

EF for N additions from mineral fertilizer and crop residues =

N Additions from Mineral Fertilizers

N additions to soils from mineral fertilizers =

N Additions from Crop Residues

N additions to soils from crop residues =

where,

Above-ground residue dry matter =

Crop residue summary equation [see Crop Residue Defaults tab fro explanation of letters]

N additions to soils from crop residues =

Indirect N2O Emissions

Note that for indirect emissions, the calculation of N applied to soils from fertilizers or crop residues is the same as for direct em

Indirect Emissions from Volatilization

Emissions =

N lost (from synthetic fertilizer additions) through volatilization =

EF for N lost through volatilization =

Indirect Emissions from Leaching/Runoff

Emissions =

N lost through leaching/runoff (from all N sources) =

EF for N lost through leaching/runoff =
e Gas Inventories. Vol. 4: Agriculture, Forestry; and Other Land Use.

Equation

(N additions to soils from mineral fertilizer + N additions to soils from crop 

residues) × EF

0.01 kg N2O-N / kg N added

kg fertilizer N applied to soils (i.e., change in fertilizer N applications between current and projected year)

above-ground residue dry matter × Crop Area × [N content of aboveground 

residues + ratio of belowground residues to harvested yield for crop × N content 

of belowground residues]

Fresh weight yield (kg fresh weight harvested/ha) × dry matter fraction of 

harvested crop × slope + intercept

Defaults tab fro explanation of letters]

(B / A × C × D + E) × A × (F + G × H)

rom fertilizers or crop residues is the same as for direct emissions

Equation

N additions to soils from mineral fertilizers × N lost through volatilization × EF

0.1 (kg NH3–N + NOx–N) / kg N applied

0.010 kg N2O–N / (kg NH3–N + NOX–N volatilised)

Equation

(N additions to soils from mineral fertilizers + N additions to soils from crop 

residues) × N lost through leaching or runoff × EF

0.3 N losses by leaching or runoff / kg N addition

0.0075 kg N20-N / kg N leaching or runoff
Change in N Application (Mg)

Camelina Soybean

 - -

US Average 44.84000 -

 - -

Corn Belt - 8.8

Great Plains - 8.0720

Lake States - 4.0

North East - 8.8

South Central - 5.5

South East - 9.2

Southwest - 7.1
Lookups

EPA Crop Lookup Country Corn-Only Region All Corn Regions

Wheat 2 Albania Other Eastern Europe Algeria

Cotton 3 Argentina Argentina Argentina

Corn 4 Australia Australia Australia

Sorghum 5 Austria EU Bangladesh

Barley 6 Azerbaijan, Republic of Other CIS Brazil

Soybean 7 Belgium EU Canada

Rapeseed 8 Bangladesh Bangladesh China

Sunflower 9 Bulgaria Other Eastern Europe CIS

Palm 10 Belarus Other CIS Colombia

Peanut 11 Bolivia Other Latin America Cuba

Rice 12 Brazil Brazil Egypt

Sugarbeet 13 Canada Canada EU

Sugarcane 14 Switzerland Rest of World Guatemala

Chile Other Latin America India

China China Indonesia

Colombia Colombia Iran

Costa Rica Other Latin America Iraq

Cuba Cuba Ivory Coast

Czech Republic EU Japan

Germany EU Malaysia

Denmark EU Mexico

Dominican Republic Other Latin America Morocco

Algeria Algeria Myanmar

Ecuador Other Latin America Nigeria

Egypt Egypt Other Africa

Spain EU Other Asia

Estonia EU Other CIS

Ethiopia Other Africa Other Eastern Europe

Finland EU Other Latin America

Fiji Islands Rest of World Other Middle East

France EU Pakistan

United Kingdom EU Paraguay

Ghana Western Africa Peru

Guinea Western Africa Philippines

Greece EU Rest of World

Guatemala Guatemala Russia and Ukraine

Honduras Other Latin America Russia

Croatia Other Eastern Europe South Africa

Hungary EU South Korea

Indonesia Indonesia Taiwan

India India Thailand

Ireland EU Tunisia

Iran Iran Turkey

Iraq Iraq Ukraine

Israel Other Middle East Uruguay

Italy EU Uzbekistan

Ivory Coast Ivory Coast Venezuela

Jordan Other Middle East Vietnam

Japan Japan Western Africa
Kenya Other Africa USA

Cambodia Other Asia

South Korea South Korea

Kuwait Other Middle East

Laos Other Asia

Lebanon Other Middle East

Sri Lanka Other Asia

Lithuania EU

Latvia EU

Morocco Morocco

Moldova, Republic of Other CIS

Madagascar Other Africa

Mexico Mexico

Myanmar Myanmar

Mauritania Western Africa

Malawi Other Africa

Malaysia Malaysia

Nigeria Nigeria

Nicaragua Other Latin America

Netherlands EU

Norway Rest of World

New Zealand Rest of World

Pakistan Pakistan

Peru Peru

Philippines Philippines

Poland EU

Korea, Dem People's Rep Other Asia

Portugal EU

Paraguay Paraguay

Russia Russia

Saudi Arabia Other Middle East

Sudan Other Middle East

El Salvador Other Latin America

Slovakia Other Eastern Europe

Sweden EU

Syrian Arab Republic Other Middle East

Togo Western Africa

Thailand Thailand

Tunisia Tunisia

Turkey Turkey

Taiwan Taiwan

Tanzania, United Rep of Other Africa

Ukraine Ukraine

Uruguay Uruguay

United States of America USA

Uzbekistan Uzbekistan

Venezuela Venezuela

Vietnam Vietnam

South Africa South Africa

Zambia Other Africa

Zimbabwe Other Africa
COUNTRY REGION

Algeria Algeria

Argentina Argentina

Australia Australia

Bangladesh Bangladesh

Brazil Brazil

Canada Canada

China China

Colombia Colombia

Cuba Cuba

Egypt Egypt

Austria EU

Belgium EU

Czech Republic EU

Germany EU

Denmark EU

Spain EU

Estonia EU

Finland EU

France EU

United Kingdom EU

Greece EU

Hungary EU

Ireland EU

Italy EU

Lithuania EU

Latvia EU

Netherlands EU

Poland EU

Portugal EU

Sweden EU

Guatemala Guatemala

India India

Indonesia Indonesia

Iran Iran

Japan Japan

South Korea South Korea

Malaysia Malaysia

Mexico Mexico

Morocco Morocco

Myanmar Myanmar

Nigeria Nigeria

Ethiopia Other Africa

Kenya Other Africa

Madagascar Other Africa

Malawi Other Africa

Tanzania, United Rep of Other Africa

Zambia Other Africa

Zimbabwe Other Africa

Cambodia Other Asia
Laos Other Asia

Sri Lanka Other Asia

Korea, Dem People's Rep Other Asia

Azerbaijan, Republic of Other CIS

Belarus Other CIS

Moldova, Republic of Other CIS

Albania Other Eastern Europe

Bulgaria Other Eastern Europe

Croatia Other Eastern Europe

Slovakia Other Eastern Europe

Bolivia Other Latin America

Chile Other Latin America

Costa Rica Other Latin America

Dominican Republic Other Latin America

Ecuador Other Latin America

Honduras Other Latin America

Nicaragua Other Latin America

El Salvador Other Latin America

Israel Other Middle East

Jordan Other Middle East

Kuwait Other Middle East

Lebanon Other Middle East

Saudi Arabia Other Middle East

Sudan Other Middle East

Syrian Arab Republic Other Middle East

Pakistan Pakistan

Paraguay Paraguay

Philippines Philippines

Switzerland Rest of World

Fiji Islands Rest of World

Norway Rest of World

New Zealand Rest of World

Russia Russia

South Africa South Africa

Taiwan Taiwan

Thailand Thailand

Turkey Turkey

Uruguay Uruguay

Uzbekistan Uzbekistan

Venezuela Venezuela

Vietnam Vietnam

Ghana Western Africa

Guinea Western Africa

Mauritania Western Africa

Togo Western Africa

EU-27 EU-27
Data Assumptions

1.The United States is excluded from dataset, and not included in "Rest of World" calculations

2. Switzerland and Norway are included in Rest Of World category, since they are not members of the EU.

3. Sudan is included in "Other Middle East" category (vs. Other Africa)

4. The Rate of fertilizer application is determined by dividing the total consumption of fertilizer by the agricultural area (Area). Pl

6. Rate of chemical (pesticide) application was determined by dividing the total consumption in tonnes of chemical consumption 

7. "CIS" and "Russia and Ukraine" were removed from the regions/countries as they are covered elsewhere.

8. Peanut is included in FAO's "Groundnut" category, so data label is switched to Groundnut

9. Crop residue factors: If data were NA for individual crops, then proxies were used based on crop categories. This applies to 

10. Emissions are only calculated for mineral (synthetic) fertilizers.

11. Emissions are not reported for crops where IPCC factors are missing. These crops are indicated using pink shading in the 

12. China pesticide consumption is based on total pesticide use value from USDA ERS, and percentage breakdown by pesticid

13. IFA data for sugarcrops is broken down into sugarcane and sugarbeet based on calculated consumption ratios using Fertis

14. Fertilizer growth rate for Brazil based on annual average growth rate calculated by FAO between avg 1999-2001 and 2011.

15. Fertilizer emissions are based on fertilizer consumption estimates from FAO, IFA, and national datasets for India, Russia, a

16. IFA data are used for available country/crop combinations. An avereage of 2006/07 and 2007/08 is taken to account for unc

17. IFA data for sugarcane and sugarbeet are derived from IFA estiamtes for "sugarcrop" and sugarcane to sugarbeet ratios fro

18. European Union
Data Assumptions

1.The United States is excluded from dataset, and not included in "Rest of World" calculations

2. Switzerland and Norway are included in Rest Of World category, since they are not members of the EU.

3. Sudan is included in "Other Middle East" category (vs. Other Africa)

4. The Rate of fertilizer application is determined by dividing the total consumption of fertilizer by the agricultural area (Area). Pl

6. Rate of chemical (pesticide) application was determined by dividing the total consumption in tonnes of chemical consumption 

7. "CIS" and "Russia and Ukraine" are assumed to equal "Other CIS" and "Russia", respectively.

8. Peanut is included in FAO's "Groundnut" category, so data label is switched to Groundnut

9. Crop residue factors: If data were NA for individual crops, then proxies were used based on crop categories. This applies to 

10. Emissions are only calculated for mineral (synthetic) fertilizers.

11. Emissions are now reported for crops where IPCC factors are missing using factors for "Root crops, other". These crops ar

12. China pesticide consumption is based on total pesticide use value from USDA ERS, and percentage breakdown by pesticid

13. IFA data for sugarcrops is broken down into sugarcane and sugarbeet based on calculated consumption ratios using Fertis

14. Fertilizer growth rate for Brazil based on annual average growth rate calculated by FAO between avg 1999-2001 and 2011.

15. Fertilizer emissions are based on fertilizer consumption estimates from FAO and IFA.

16. IFA data are used for available country/crop combinations. An avereage of 2006/07 and 2007/08 is taken to account for unc

17. IFA data for sugarcane and sugarbeet are derived from IFA estiamtes for "sugarcrop" and sugarcane to sugarbeet ratios fro

18. Fertilizer rate of application for EU is based on IFA regional data for EU-27. IFA data only covers wheat, rice, corn, soybean
mbers of the EU.

zer by the agricultural area (Area). Please note that individual country rates match those reported by FAO for Fertistat data.

on in tonnes of chemical consumption by the "Agricultural Area" statistic from FAO's FAOSTAT dataset.

d on crop categories. This applies to Groundnut, Sugarbeet, Rice, Sorghum, Groundnut and Sugarbeet factors, which, are based on "root cro

r "Root crops, other". These crops are indicated using pink shading in the emissions tabs.

nd percentage breakdown by pesticide product is based on average ratio from Vietnam, Thailand and South Korea

ated consumption ratios using Fertistat data for the same country/crop combination. 

O between avg 1999-2001 and 2011.

d 2007/08 is taken to account for uncertainties in crop production and fertilizer use due to temporal or other annual variations.

and sugarcane to sugarbeet ratios from Fertistat. Where Fertistat data were not available to determine ratios for sugarcane to sugarcrop, pro

nly covers wheat, rice, corn, soybean, palm, cotton, sugarcane and sugarbeet. EU regional fertilizer application rates for barley, peanut, rape
O for Fertistat data.

actors, which, are based on "root crop" factors. Sorghum and Rice factors, if missing, are based on "Grains". 

her annual variations.

atios for sugarcane to sugarcrop, proxy countries were chosen to split IFA's "sugarcrop" into sugarcane and sugarbeet. 

ication rates for barley, peanut, rapeseed, sorghum and sunflower are based on Fertistat data. Calculations are conducted separated at the 
and sugarbeet. 

ions are conducted separated at the bottom of the Fertilizer worksheet.