Emission Totals - Emissions (N2O) - Crop Residues by country
The FAOSTAT domain Emissions Totals summarizes the greenhouse gas (GHG) emissions generated from agriculture and forest land. They consist of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) emissions from crop and livestock activities, forest management and include land use and land use change...
What the numbers show
Emission Totals - Emissions (N2O) - Crop Residues is currently reported for 185 countries. The highest value is 112.69 in United States; the lowest is 0 in Maldives.
The median across all reporting countries is 0.6002, and the mean is 4.12.
Over the past decade 1 countries rose and 1 fell. The largest increase was in Sudan (up 77.4%), and the largest decrease in South Sudan (down 32.9%).
Emission Totals - Emissions (N2O) - Crop Residues: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United States | 112.69 | 2050 | β | rising |
| 2 | China | 102.37 | 2050 | β | rising |
| 3 | India | 85.03 | 2050 | β | rising |
| 4 | Brazil | 49.04 | 2050 | β | volatile |
| 5 | Argentina | 31.35 | 2050 | β | volatile |
| 6 | Russia | 26.88 | 2050 | β | rising |
| 7 | Indonesia | 19.49 | 2050 | β | rising |
| 8 | Canada | 15.88 | 2050 | β | rising |
| 9 | France | 15.3 | 2050 | β | rising |
| 10 | Nigeria | 14.27 | 2050 | β | volatile |
| 11 | Bangladesh | 14.25 | 2050 | β | rising |
| 12 | Australia | 13.9 | 2050 | β | rising |
| 13 | Myanmar | 13.8 | 2050 | β | rising |
| 14 | Pakistan | 10.79 | 2050 | β | rising |
| 15 | Germany | 10.56 | 2050 | β | rising |
| 16 | Ukraine | 10.47 | 2050 | β | rising |
| 17 | Vietnam | 10.27 | 2050 | β | rising |
| 18 | Mexico | 9.55 | 2050 | β | rising |
| 19 | Turkey | 9.35 | 2050 | β | rising |
| 20 | Thailand | 7.92 | 2050 | β | rising |
| 21 | Philippines | 7.76 | 2050 | β | rising |
| 22 | Ethiopia | 7.47 | 2050 | β | rising |
| 23 | Iran | 7.3 | 2050 | β | rising |
| 24 | Egypt | 6.55 | 2050 | β | rising |
| 25 | United Kingdom | 5.48 | 2050 | β | rising |
| 26 | Italy | 5.05 | 2050 | β | rising |
| 27 | Spain | 4.89 | 2050 | β | rising |
| 28 | Poland | 4.84 | 2050 | β | falling |
| 29 | Cambodia | 4.81 | 2050 | β | volatile |
| 30 | Kazakhstan | 4.69 | 2050 | β | rising |
| 31 | Nepal | 4.28 | 2050 | β | rising |
| 32 | Tanzania | 4.13 | 2050 | β | volatile |
| 33 | South Africa | 4.07 | 2050 | β | rising |
| 34 | Romania | 3.75 | 2050 | β | rising |
| 35 | Paraguay | 3.45 | 2050 | β | volatile |
| 36 | Niger | 3.1 | 2050 | β | volatile |
| 37 | Hungary | 3.09 | 2050 | β | rising |
| 38 | Syria | 2.93 | 2050 | β | rising |
| 39 | Madagascar | 2.45 | 2050 | β | rising |
| 40 | Morocco | 2.42 | 2050 | β | rising |
| 41 | Afghanistan | 2.38 | 2050 | β | rising |
| 42 | Sudan | 2.37 | 2019 | up 77.4% | rising |
| 43 | North Korea | 2.34 | 2050 | β | rising |
| 44 | Uganda | 2.29 | 2050 | β | volatile |
| 45 | Burkina Faso | 2.25 | 2050 | β | volatile |
| 46 | Colombia | 2.24 | 2050 | β | rising |
| 47 | Denmark | 2.24 | 2050 | β | rising |
| 48 | Mali | 2.19 | 2050 | β | volatile |
| 49 | Iraq | 2.13 | 2050 | β | rising |
| 50 | Bolivia | 2.12 | 2050 | β | volatile |
| 51 | Peru | 2.07 | 2050 | β | rising |
| 52 | Kenya | 2.05 | 2050 | β | rising |
| 53 | Uruguay | 2.01 | 2050 | β | volatile |
| 54 | Japan | 1.98 | 2050 | β | falling |
| 55 | Belarus | 1.96 | 2050 | β | flat |
| 56 | Serbia | 1.89 | 2050 | β | rising |
| 57 | Malawi | 1.87 | 2050 | β | volatile |
| 58 | Democratic Republic of Congo | 1.82 | 2050 | β | volatile |
| 59 | Czechia | 1.81 | 2050 | β | rising |
| 60 | Laos | 1.64 | 2050 | β | rising |
| 61 | Algeria | 1.61 | 2050 | β | rising |
| 62 | Guinea | 1.57 | 2050 | β | volatile |
| 63 | Mozambique | 1.53 | 2050 | β | volatile |
| 64 | Uzbekistan | 1.49 | 2050 | β | rising |
| 65 | Venezuela | 1.45 | 2050 | β | volatile |
| 66 | Bulgaria | 1.36 | 2050 | β | rising |
| 67 | Chile | 1.2 | 2050 | β | rising |
| 68 | Greece | 1.19 | 2050 | β | rising |
| 69 | South Korea | 1.13 | 2050 | β | falling |
| 70 | Sweden | 1.12 | 2050 | β | rising |
| 71 | Cameroon | 1.08 | 2050 | β | volatile |
| 72 | Ghana | 1.08 | 2050 | β | volatile |
| 73 | Austria | 1.08 | 2050 | β | rising |
| 74 | Ecuador | 0.9943 | 2050 | β | rising |
| 75 | Chad | 0.9785 | 2050 | β | volatile |
| 76 | Sri Lanka | 0.9713 | 2050 | β | rising |
| 77 | Saudi Arabia | 0.9641 | 2050 | β | volatile |
| 78 | Finland | 0.9518 | 2050 | β | rising |
| 79 | Cote d'Ivoire | 0.9495 | 2050 | β | rising |
| 80 | Senegal | 0.8979 | 2050 | β | rising |
| 81 | Angola | 0.8877 | 2050 | β | volatile |
| 82 | Benin | 0.8505 | 2050 | β | volatile |
| 83 | Malaysia | 0.8098 | 2050 | β | rising |
| 84 | Slovakia | 0.7911 | 2050 | β | rising |
| 85 | Belgium | 0.7526 | 2050 | β | rising |
| 86 | Croatia | 0.7218 | 2050 | β | rising |
| 87 | Tunisia | 0.7169 | 2050 | β | rising |
| 88 | Guatemala | 0.6786 | 2050 | β | rising |
| 89 | Rwanda | 0.666 | 2050 | β | volatile |
| 90 | Lithuania | 0.6578 | 2050 | β | rising |
| 91 | Sierra Leone | 0.6534 | 2050 | β | rising |
| 92 | Moldova | 0.6426 | 2050 | β | rising |
| 93 | Netherlands | 0.6002 | 2050 | β | rising |
| 94 | Turkmenistan | 0.5864 | 2050 | β | rising |
| 95 | Azerbaijan | 0.5787 | 2050 | β | rising |
| 96 | Togo | 0.5505 | 2050 | β | volatile |
| 97 | Ireland | 0.5015 | 2050 | β | rising |
| 98 | El Salvador | 0.4948 | 2050 | β | rising |
| 99 | Kyrgyzstan | 0.4667 | 2050 | β | rising |
| 100 | Yemen | 0.4503 | 2050 | β | volatile |
| 101 | Nicaragua | 0.4457 | 2050 | β | rising |
| 102 | Cuba | 0.3791 | 2050 | β | rising |
| 103 | Latvia | 0.3666 | 2050 | β | rising |
| 104 | Norway | 0.3366 | 2050 | β | rising |
| 105 | Dominican Republic | 0.3273 | 2050 | β | rising |
| 106 | Taiwan | 0.3236 | 2050 | β | falling |
| 107 | Bosnia and Herzegovina | 0.3142 | 2050 | β | rising |
| 108 | Liberia | 0.2896 | 2050 | β | rising |
| 109 | Honduras | 0.287 | 2050 | β | rising |
| 110 | Burundi | 0.2838 | 2050 | β | rising |
| 111 | Switzerland | 0.272 | 2050 | β | rising |
| 112 | Somalia | 0.2685 | 2050 | β | rising |
| 113 | Haiti | 0.2643 | 2050 | β | rising |
| 114 | Eritrea | 0.2642 | 2050 | β | rising |
| 115 | Portugal | 0.2572 | 2050 | β | falling |
| 116 | Tajikistan | 0.2516 | 2050 | β | rising |
| 117 | New Zealand | 0.2499 | 2050 | β | rising |
| 118 | South Sudan | 0.2004 | 2019 | down 32.9% | falling |
| 119 | Estonia | 0.1975 | 2050 | β | rising |
| 120 | North Macedonia | 0.168 | 2050 | β | flat |
| 121 | Guyana | 0.1619 | 2050 | β | rising |
| 122 | Panama | 0.1553 | 2050 | β | rising |
| 123 | Georgia | 0.1515 | 2050 | β | falling |
| 124 | Central African Republic | 0.1476 | 2050 | β | rising |
| 125 | Guinea-Bissau | 0.1466 | 2050 | β | rising |
| 126 | Albania | 0.142 | 2050 | β | falling |
| 127 | Armenia | 0.1265 | 2050 | β | rising |
| 128 | Gambia | 0.1264 | 2050 | β | volatile |
| 129 | Slovenia | 0.124 | 2050 | β | rising |
| 130 | Mauritania | 0.1178 | 2050 | β | rising |
| 131 | Libya | 0.1144 | 2050 | β | rising |
| 132 | Israel | 0.104 | 2050 | β | rising |
| 133 | Lebanon | 0.0986 | 2050 | β | rising |
| 134 | Bhutan | 0.0909 | 2050 | β | rising |
| 135 | Costa Rica | 0.0907 | 2050 | β | falling |
| 136 | Namibia | 0.0853 | 2050 | β | rising |
| 137 | East Timor | 0.0652 | 2050 | β | volatile |
| 138 | Suriname | 0.0594 | 2050 | β | rising |
| 139 | Lesotho | 0.0549 | 2050 | β | falling |
| 140 | Botswana | 0.0424 | 2050 | β | volatile |
| 141 | Mongolia | 0.0378 | 2050 | β | falling |
| 142 | Luxembourg | 0.0353 | 2050 | β | rising |
| 143 | Jordan | 0.0299 | 2050 | β | volatile |
| 144 | Eswatini | 0.026 | 2050 | β | flat |
| 145 | Cyprus | 0.0245 | 2050 | β | falling |
| 146 | Belize | 0.0225 | 2050 | β | volatile |
| 147 | Palestine | 0.022 | 2050 | β | rising |
| 148 | Comoros | 0.0211 | 2050 | β | rising |
| 149 | Congo | 0.017 | 2050 | β | rising |
| 150 | Gabon | 0.0167 | 2050 | β | volatile |
| 151 | Oman | 0.0087 | 2050 | β | volatile |
| 152 | Cape Verde | 0.0055 | 2050 | β | volatile |
| 153 | Kuwait | 0.0052 | 2050 | β | volatile |
| 154 | Fiji | 0.0049 | 2050 | β | falling |
| 154 | Montenegro | 0.0049 | 2050 | β | volatile |
| 156 | Malta | 0.0043 | 2050 | β | rising |
| 157 | Papua New Guinea | 0.0038 | 2050 | β | volatile |
| 158 | Trinidad and Tobago | 0.0027 | 2050 | β | falling |
| 159 | New Caledonia | 0.0018 | 2050 | β | volatile |
| 160 | Qatar | 0.0017 | 2050 | β | volatile |
| 161 | Jamaica | 0.0015 | 2050 | β | falling |
| 161 | Sao Tome and Principe | 0.0015 | 2050 | β | volatile |
| 163 | Solomon Islands | 0.0009 | 2050 | β | volatile |
| 164 | United Arab Emirates | 0.0008 | 2050 | β | volatile |
| 164 | Mauritius | 0.0008 | 2050 | β | rising |
| 166 | Brunei | 0.0005 | 2050 | β | volatile |
| 166 | Iceland | 0.0005 | 2050 | β | volatile |
| 168 | Puerto Rico | 0.0003 | 2050 | β | volatile |
| 168 | Vanuatu | 0.0003 | 2050 | β | rising |
| 170 | Saint Vincent and the Grenadines | 0.0002 | 2050 | β | volatile |
| 171 | Bahamas | 0.0001 | 2050 | β | flat |
| 171 | Barbados | 0.0001 | 2050 | β | volatile |
| 171 | Dominica | 0.0001 | 2050 | β | volatile |
| 171 | Faroe Islands | 0.0001 | 2050 | β | rising |
| 171 | Micronesia (country) | 0.0001 | 2050 | β | rising |
| 171 | Grenada | 0.0001 | 2050 | β | falling |
| 171 | French Polynesia | 0.0001 | 2050 | β | volatile |
| 178 | Antigua and Barbuda | 0 | 2050 | β | flat |
| 178 | Bahrain | 0 | 2050 | β | flat |
| 178 | Bermuda | 0 | 2050 | β | volatile |
| 178 | Guam | 0 | 2050 | β | flat |
| 178 | Hong Kong | 0 | 1990 | β | volatile |
| 178 | Saint Kitts and Nevis | 0 | 2050 | β | flat |
| 178 | Saint Lucia | 0 | 1979 | β | flat |
| 178 | Maldives | 0 | 2050 | β | volatile |
About this data
The FAOSTAT domain Emissions Totals summarizes the greenhouse gas (GHG) emissions generated from agriculture and forest land. They consist of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) emissions from crop and livestock activities, forest management and include land use and land use change processes. Data are computed at Tier 1 of the IPCC Guidelines for National greenhouse gas (GHG) Inventories (IPCC, 1996; 1997; 2000; 2002; 2006; 2014). Estimates are available by country, with global coverage for the period 1961β2019 with projections for 2030 and 2050 for some categories of emissions or 1990β2019 for others. The database is updated annually. The FAOSTAT domain Emissions Totals disseminates information estimates of CH4, N2O and CO2 emissions/removals and their aggregates in CO2eq in units of kilotonnes (kt, or 106 kg). The latter are computed by using the IPCC Fifth Assessment report global warming potentials, AR5 (IPCC, 2014).