Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 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 - Indirect emissions (N2O) - Manure applied to Soils is currently reported for 193 countries. The highest value is 49.4 in China; the lowest is 0.0003 in Niue.
The median across all reporting countries is 0.2599, and the mean is 1.22.
Emission Totals - Indirect emissions (N2O) - Manure applied to Soils: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 49.4 | 2050 | β | rising |
| 2 | India | 20.88 | 2050 | β | rising |
| 3 | United States | 19.34 | 2050 | β | rising |
| 4 | Brazil | 13.82 | 2050 | β | rising |
| 5 | Russia | 9.34 | 2050 | β | falling |
| 6 | Indonesia | 6.97 | 2050 | β | volatile |
| 7 | Pakistan | 6.05 | 2050 | β | volatile |
| 8 | France | 5.48 | 2050 | β | falling |
| 9 | Germany | 4.6 | 2050 | β | falling |
| 10 | Mexico | 4.11 | 2050 | β | rising |
| 11 | Vietnam | 3.68 | 2050 | β | volatile |
| 12 | Iran | 3.47 | 2050 | β | rising |
| 13 | Myanmar | 3.28 | 2050 | β | volatile |
| 14 | Spain | 3.18 | 2050 | β | rising |
| 15 | United Kingdom | 3.13 | 2050 | β | falling |
| 16 | Colombia | 2.92 | 2050 | β | rising |
| 17 | Ukraine | 2.72 | 2050 | β | falling |
| 18 | Poland | 2.62 | 2050 | β | falling |
| 19 | Italy | 2.5 | 2050 | β | falling |
| 20 | Bangladesh | 2.46 | 2050 | β | rising |
| 21 | Philippines | 2.21 | 2050 | β | rising |
| 22 | Mozambique | 2.06 | 2050 | β | volatile |
| 23 | Canada | 2.05 | 2050 | β | rising |
| 24 | Nigeria | 1.77 | 2050 | β | volatile |
| 25 | Netherlands | 1.74 | 2050 | β | rising |
| 26 | Thailand | 1.67 | 2050 | β | rising |
| 27 | Argentina | 1.56 | 2050 | β | rising |
| 28 | Romania | 1.5 | 2050 | β | falling |
| 29 | Ireland | 1.45 | 2050 | β | rising |
| 30 | Uzbekistan | 1.42 | 2050 | β | rising |
| 31 | Uganda | 1.36 | 2050 | β | volatile |
| 32 | Venezuela | 1.34 | 2050 | β | rising |
| 33 | Kazakhstan | 1.3 | 2050 | β | flat |
| 34 | Belarus | 1.25 | 2050 | β | falling |
| 35 | Australia | 1.21 | 2050 | β | rising |
| 36 | Japan | 1.19 | 2050 | β | rising |
| 37 | Peru | 1.15 | 2050 | β | rising |
| 38 | Denmark | 1.1 | 2050 | β | falling |
| 39 | South Korea | 0.9638 | 2050 | β | volatile |
| 40 | Ecuador | 0.9379 | 2050 | β | rising |
| 41 | Belgium | 0.9298 | 2050 | β | falling |
| 42 | Guatemala | 0.9286 | 2050 | β | volatile |
| 43 | Chile | 0.9268 | 2050 | β | rising |
| 44 | Burkina Faso | 0.9232 | 2050 | β | volatile |
| 45 | Afghanistan | 0.8991 | 2050 | β | rising |
| 46 | Mongolia | 0.8173 | 2050 | β | rising |
| 47 | Turkey | 0.815 | 2050 | β | rising |
| 48 | Nepal | 0.7753 | 2050 | β | rising |
| 49 | Dominican Republic | 0.7575 | 2050 | β | volatile |
| 50 | Bolivia | 0.7329 | 2050 | β | volatile |
| 51 | Malaysia | 0.7102 | 2050 | β | rising |
| 52 | Cambodia | 0.6712 | 2050 | β | rising |
| 53 | Laos | 0.6615 | 2050 | β | volatile |
| 54 | Ethiopia | 0.6564 | 2050 | β | rising |
| 55 | Turkmenistan | 0.6549 | 2050 | β | rising |
| 56 | Tanzania | 0.6405 | 2050 | β | rising |
| 57 | Austria | 0.6222 | 2050 | β | falling |
| 58 | Serbia | 0.6055 | 2050 | β | rising |
| 59 | Sudan | 0.5846 | 2019 | up 7.2% | rising |
| 60 | Hungary | 0.5538 | 2050 | β | falling |
| 61 | Switzerland | 0.5507 | 2050 | β | falling |
| 62 | Kenya | 0.5379 | 2050 | β | rising |
| 63 | Cuba | 0.529 | 2050 | β | rising |
| 64 | Portugal | 0.5144 | 2050 | β | rising |
| 65 | South Africa | 0.5111 | 2050 | β | rising |
| 66 | Czechia | 0.5039 | 2050 | β | falling |
| 67 | Nicaragua | 0.4575 | 2050 | β | rising |
| 68 | Angola | 0.4536 | 2050 | β | volatile |
| 69 | New Zealand | 0.4532 | 2050 | β | rising |
| 70 | Taiwan | 0.4506 | 2050 | β | rising |
| 71 | Madagascar | 0.4459 | 2050 | β | rising |
| 72 | Sweden | 0.4328 | 2050 | β | falling |
| 73 | Cameroon | 0.4076 | 2050 | β | rising |
| 74 | Greece | 0.4067 | 2050 | β | falling |
| 75 | Norway | 0.3703 | 2050 | β | falling |
| 76 | South Sudan | 0.3667 | 2019 | up 9.8% | rising |
| 77 | Honduras | 0.3649 | 2050 | β | rising |
| 78 | North Korea | 0.3562 | 2050 | β | rising |
| 79 | Democratic Republic of Congo | 0.3528 | 2050 | β | rising |
| 80 | Morocco | 0.34 | 2050 | β | rising |
| 81 | Paraguay | 0.3166 | 2050 | β | rising |
| 82 | Mali | 0.3081 | 2050 | β | volatile |
| 82 | Tajikistan | 0.3081 | 2050 | β | rising |
| 84 | Chad | 0.3078 | 2050 | β | volatile |
| 85 | Bulgaria | 0.3067 | 2050 | β | falling |
| 86 | Uruguay | 0.2999 | 2050 | β | rising |
| 87 | Finland | 0.2998 | 2050 | β | falling |
| 88 | Costa Rica | 0.2987 | 2050 | β | rising |
| 89 | Haiti | 0.2934 | 2050 | β | rising |
| 90 | Lithuania | 0.2893 | 2050 | β | falling |
| 91 | Egypt | 0.2851 | 2050 | β | rising |
| 92 | Albania | 0.2845 | 2050 | β | rising |
| 93 | Kyrgyzstan | 0.2833 | 2050 | β | rising |
| 94 | Ghana | 0.2805 | 2050 | β | volatile |
| 95 | El Salvador | 0.2714 | 2050 | β | rising |
| 96 | Somalia | 0.2637 | 2050 | β | rising |
| 97 | Bosnia and Herzegovina | 0.2599 | 2050 | β | rising |
| 98 | Croatia | 0.2598 | 2050 | β | falling |
| 99 | Algeria | 0.2569 | 2050 | β | rising |
| 100 | Moldova | 0.2466 | 2050 | β | falling |
| 101 | Niger | 0.2425 | 2050 | β | rising |
| 102 | Cote d'Ivoire | 0.2383 | 2050 | β | volatile |
| 103 | Rwanda | 0.2282 | 2050 | β | volatile |
| 104 | Senegal | 0.2247 | 2050 | β | volatile |
| 105 | Slovakia | 0.2166 | 2050 | β | falling |
| 106 | Togo | 0.2131 | 2050 | β | volatile |
| 107 | Iraq | 0.2116 | 2050 | β | rising |
| 108 | Papua New Guinea | 0.2042 | 2050 | β | rising |
| 109 | Benin | 0.1979 | 2050 | β | rising |
| 110 | Central African Republic | 0.1959 | 2050 | β | volatile |
| 111 | Saudi Arabia | 0.1847 | 2050 | β | volatile |
| 112 | Yemen | 0.1676 | 2050 | β | rising |
| 113 | Sri Lanka | 0.1608 | 2050 | β | falling |
| 114 | Malawi | 0.1596 | 2050 | β | volatile |
| 115 | Tunisia | 0.148 | 2050 | β | volatile |
| 116 | Panama | 0.1446 | 2050 | β | rising |
| 117 | Azerbaijan | 0.1322 | 2050 | β | rising |
| 118 | Slovenia | 0.1291 | 2050 | β | falling |
| 119 | Latvia | 0.128 | 2050 | β | falling |
| 120 | Syria | 0.1191 | 2050 | β | volatile |
| 121 | Guinea | 0.111 | 2050 | β | volatile |
| 122 | North Macedonia | 0.102 | 2050 | β | falling |
| 123 | Mauritania | 0.0975 | 2050 | β | rising |
| 124 | Georgia | 0.097 | 2050 | β | falling |
| 125 | Kuwait | 0.092 | 2050 | β | volatile |
| 126 | Israel | 0.0882 | 2050 | β | rising |
| 127 | Estonia | 0.0827 | 2050 | β | falling |
| 128 | Puerto Rico | 0.0791 | 2050 | β | falling |
| 129 | Brunei | 0.071 | 2050 | β | volatile |
| 130 | Trinidad and Tobago | 0.0696 | 2050 | β | volatile |
| 131 | Fiji | 0.0683 | 2050 | β | volatile |
| 132 | Burundi | 0.0676 | 2050 | β | volatile |
| 133 | Libya | 0.0637 | 2050 | β | volatile |
| 134 | Guinea-Bissau | 0.0583 | 2050 | β | rising |
| 135 | Namibia | 0.0579 | 2050 | β | rising |
| 136 | Eritrea | 0.0531 | 2050 | β | rising |
| 137 | Liberia | 0.0476 | 2050 | β | volatile |
| 138 | Botswana | 0.0472 | 2050 | β | rising |
| 139 | East Timor | 0.0468 | 2050 | β | rising |
| 140 | Jordan | 0.0464 | 2050 | β | volatile |
| 141 | Jamaica | 0.045 | 2050 | β | rising |
| 142 | Cape Verde | 0.0443 | 2050 | β | volatile |
| 143 | Cyprus | 0.043 | 2050 | β | rising |
| 144 | Lebanon | 0.0413 | 2050 | β | volatile |
| 144 | Montenegro | 0.0413 | 2050 | β | rising |
| 146 | Luxembourg | 0.041 | 2050 | β | falling |
| 147 | United Arab Emirates | 0.0407 | 2050 | β | volatile |
| 148 | Guyana | 0.0396 | 2050 | β | rising |
| 149 | Armenia | 0.0385 | 2050 | β | rising |
| 150 | Lesotho | 0.0331 | 2050 | β | rising |
| 151 | Suriname | 0.0324 | 2050 | β | rising |
| 152 | Gabon | 0.0319 | 2050 | β | rising |
| 153 | Iceland | 0.0288 | 2050 | β | falling |
| 154 | Barbados | 0.0268 | 2050 | β | rising |
| 155 | Sierra Leone | 0.0238 | 2050 | β | volatile |
| 156 | Samoa | 0.023 | 2050 | β | rising |
| 157 | Bhutan | 0.0217 | 2050 | β | rising |
| 158 | Eswatini | 0.0203 | 2050 | β | rising |
| 159 | Congo | 0.0199 | 2050 | β | volatile |
| 160 | Bahamas | 0.018 | 2050 | β | volatile |
| 161 | Vanuatu | 0.0174 | 2050 | β | rising |
| 162 | Belize | 0.0139 | 2050 | β | rising |
| 163 | Gambia | 0.0121 | 2050 | β | rising |
| 163 | Malta | 0.0121 | 2050 | β | rising |
| 165 | New Caledonia | 0.0118 | 2050 | β | rising |
| 166 | Palestine | 0.0105 | 2050 | β | rising |
| 166 | Tonga | 0.0105 | 2050 | β | rising |
| 168 | Oman | 0.0104 | 2050 | β | volatile |
| 169 | Mauritius | 0.0102 | 2050 | β | volatile |
| 170 | Singapore | 0.008 | 2050 | β | volatile |
| 171 | Solomon Islands | 0.0077 | 2050 | β | rising |
| 172 | French Polynesia | 0.0063 | 2050 | β | rising |
| 173 | Saint Lucia | 0.0062 | 2050 | β | rising |
| 174 | Qatar | 0.0059 | 2050 | β | volatile |
| 175 | Kiribati | 0.0058 | 2050 | β | volatile |
| 176 | Dominica | 0.0047 | 2050 | β | rising |
| 176 | Micronesia (country) | 0.0047 | 2050 | β | rising |
| 178 | Antigua and Barbuda | 0.0042 | 2050 | β | rising |
| 179 | Macao | 0.0039 | 2050 | β | volatile |
| 180 | Sao Tome and Principe | 0.0038 | 2050 | β | volatile |
| 181 | Saint Vincent and the Grenadines | 0.0031 | 2050 | β | rising |
| 182 | Cook Islands | 0.003 | 2050 | β | rising |
| 183 | Seychelles | 0.0024 | 2050 | β | volatile |
| 184 | Grenada | 0.0023 | 2050 | β | rising |
| 185 | Saint Kitts and Nevis | 0.0022 | 2050 | β | rising |
| 186 | Comoros | 0.002 | 2050 | β | rising |
| 187 | Tuvalu | 0.0016 | 2050 | β | rising |
| 188 | Faroe Islands | 0.0015 | 2050 | β | falling |
| 189 | Equatorial Guinea | 0.0013 | 2050 | β | rising |
| 190 | Hong Kong | 0.0012 | 2050 | β | volatile |
| 191 | Bahrain | 0.001 | 2050 | β | volatile |
| 192 | Nauru | 0.0003 | 2050 | β | rising |
| 192 | Niue | 0.0003 | 2050 | β | rising |
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).