Emission Totals - Emissions (CO2eq) (AR5) - Forestland 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...
Countries reporting
197
Highest
45,200
Solomon Islands
Lowest
-651,765
China
Median
-31.66
Years covered
30
1990–2019
Data points
5,793
What the numbers show
Emission Totals - Emissions (CO2eq) (AR5) - Forestland is currently reported for 197 countries. The highest value is 45,200 in Solomon Islands; the lowest is -651,765 in China.
The median across all reporting countries is -31.66, and the mean is -13,772.
Over the past decade 94 countries rose and 56 fell. The largest increase was in Myanmar (up 14,495.7%), and the largest decrease in Kyrgyzstan (down 35,165.7%).
Emission Totals - Emissions (CO2eq) (AR5) - Forestland: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Solomon Islands | 45,200 | 2019 | up 2,907.3% | volatile |
| 2 | Burkina Faso | 17,596 | 2019 | up 92.7% | volatile |
| 3 | Philippines | 2,462 | 2019 | up 111.7% | volatile |
| 4 | South Sudan | 2,062 | 2019 | up 722.8% | volatile |
| 5 | Myanmar | 1,552 | 2019 | up 14,495.7% | volatile |
| 6 | Venezuela | 957.77 | 2019 | down 35.3% | rising |
| 7 | Senegal | 355 | 2019 | down 85.3% | volatile |
| 8 | Thailand | 291.47 | 2019 | up 100.7% | volatile |
| 9 | Malaysia | 280.34 | 2019 | down 99.2% | volatile |
| 10 | Afghanistan | 154.66 | 2019 | up 26.9% | volatile |
| 11 | North Korea | 88.44 | 2019 | up 106.1% | volatile |
| 12 | Northern Mariana Islands | 60.93 | 2019 | up 2,219.1% | volatile |
| 13 | Iran | 55.68 | 2019 | up 100.1% | volatile |
| 14 | Iraq | 44.33 | 2019 | up 185.7% | volatile |
| 15 | Trinidad and Tobago | 43.51 | 2019 | down 16.3% | volatile |
| 16 | Chad | 34.47 | 2019 | up 1,295.1% | volatile |
| 17 | Haiti | 10.19 | 2019 | up 107.4% | rising |
| 18 | Samoa | 2.37 | 2019 | up 29.5% | rising |
| 19 | Angola | 0 | 2019 | — | flat |
| 19 | Andorra | 0 | 2019 | — | flat |
| 19 | Armenia | 0 | 2019 | up 100.0% | volatile |
| 19 | Burundi | 0 | 2019 | — | volatile |
| 19 | Belgium | 0 | 2019 | up 100.0% | volatile |
| 19 | Bangladesh | 0 | 2019 | — | volatile |
| 19 | Bahamas | 0 | 2019 | — | flat |
| 19 | Botswana | 0 | 2019 | — | flat |
| 19 | Central African Republic | 0 | 2019 | — | flat |
| 19 | Cote d'Ivoire | 0 | 2019 | — | volatile |
| 19 | Democratic Republic of Congo | 0 | 2019 | up 100.0% | volatile |
| 19 | Congo | 0 | 2019 | — | flat |
| 19 | Comoros | 0 | 2019 | — | flat |
| 19 | Ecuador | 0 | 2019 | up 100.0% | volatile |
| 19 | Egypt | 0 | 2019 | up 100.0% | volatile |
| 19 | Finland | 0 | 2019 | up 100.0% | rising |
| 19 | Gabon | 0 | 2019 | — | flat |
| 19 | Georgia | 0 | 2019 | up 100.0% | volatile |
| 19 | Gibraltar | 0 | 2019 | — | flat |
| 19 | Gambia | 0 | 2019 | — | flat |
| 19 | Equatorial Guinea | 0 | 2019 | — | volatile |
| 19 | Greece | 0 | 2019 | up 100.0% | volatile |
| 19 | Grenada | 0 | 2019 | — | flat |
| 19 | Guyana | 0 | 2019 | — | flat |
| 19 | Honduras | 0 | 2019 | — | flat |
| 19 | Indonesia | 0 | 2019 | up 100.0% | volatile |
| 19 | Israel | 0 | 2019 | up 100.0% | volatile |
| 19 | Jordan | 0 | 2019 | — | flat |
| 19 | Libya | 0 | 2019 | — | flat |
| 19 | Liechtenstein | 0 | 2019 | down 100.0% | volatile |
| 19 | Lesotho | 0 | 2019 | — | flat |
| 19 | Monaco | 0 | 2019 | — | flat |
| 19 | Madagascar | 0 | 2019 | up 100.0% | volatile |
| 19 | Maldives | 0 | 2019 | — | flat |
| 19 | Marshall Islands | 0 | 2019 | — | flat |
| 19 | Montenegro | 0 | 2019 | up 100.0% | volatile |
| 19 | Malawi | 0 | 2019 | — | flat |
| 19 | Namibia | 0 | 2019 | — | flat |
| 19 | New Caledonia | 0 | 2019 | up 100.0% | volatile |
| 19 | Nigeria | 0 | 2019 | — | flat |
| 19 | Nepal | 0 | 2019 | up 100.0% | volatile |
| 19 | Nauru | 0 | 2019 | — | flat |
| 19 | Pakistan | 0 | 2019 | — | flat |
| 19 | Papua New Guinea | 0 | 2019 | — | flat |
| 19 | Portugal | 0 | 2019 | up 100.0% | volatile |
| 19 | French Polynesia | 0 | 2019 | up 100.0% | volatile |
| 19 | Qatar | 0 | 2019 | — | flat |
| 19 | Saudi Arabia | 0 | 2019 | — | flat |
| 19 | Sudan | 0 | 2019 | up 100.0% | volatile |
| 19 | San Marino | 0 | 2019 | up 100.0% | rising |
| 19 | Somalia | 0 | 2019 | — | flat |
| 19 | Sao Tome and Principe | 0 | 2019 | — | flat |
| 19 | Suriname | 0 | 2019 | — | volatile |
| 19 | Seychelles | 0 | 2019 | — | flat |
| 19 | Turks and Caicos Islands | 0 | 2019 | — | flat |
| 19 | Turkmenistan | 0 | 2019 | up 100.0% | volatile |
| 19 | East Timor | 0 | 2019 | — | flat |
| 19 | Tonga | 0 | 2019 | — | flat |
| 19 | Tanzania | 0 | 2019 | — | flat |
| 78 | Faroe Islands | -0.0688 | 2019 | up 34.9% | falling |
| 79 | Greenland | -0.0926 | 2019 | down 322.8% | volatile |
| 80 | Aruba | -0.1222 | 2019 | down 32.4% | volatile |
| 81 | Tuvalu | -0.1997 | 2019 | down 0.8% | rising |
| 82 | Mongolia | -0.8294 | 2019 | up 94.5% | volatile |
| 83 | Barbados | -1.83 | 2019 | down 32.4% | volatile |
| 84 | Niue | -2.18 | 2019 | — | volatile |
| 85 | Bahrain | -2.89 | 2019 | down 27.2% | falling |
| 86 | Kuwait | -2.98 | 2019 | up 87.1% | rising |
| 87 | Cook Islands | -3.11 | 2019 | up 14.1% | volatile |
| 88 | Cayman Islands | -3.7 | 2019 | down 32.4% | volatile |
| 89 | Saint Vincent and the Grenadines | -3.75 | 2019 | unchanged | volatile |
| 90 | Oman | -3.87 | 2019 | — | volatile |
| 91 | Malta | -4.53 | 2019 | down 908.9% | volatile |
| 92 | Moldova | -4.69 | 2019 | up 99.7% | volatile |
| 93 | Belize | -5.41 | 2019 | down 9.1% | flat |
| 94 | Guinea-Bissau | -5.98 | 2019 | unchanged | falling |
| 95 | Dominica | -13.93 | 2019 | down 32.4% | volatile |
| 96 | Singapore | -17.01 | 2019 | up 68.6% | falling |
| 97 | Brunei | -17.95 | 2019 | up 85.8% | volatile |
| 98 | Mauritius | -27.72 | 2019 | down 181.3% | volatile |
| 99 | Niger | -31.66 | 2019 | up 56.6% | falling |
| 100 | Micronesia (country) | -34.93 | 2019 | up 90.8% | volatile |
| 101 | Sri Lanka | -36.08 | 2019 | down 16.9% | volatile |
| 102 | Benin | -42.84 | 2019 | up 50.0% | flat |
| 103 | American Samoa | -50.37 | 2019 | down 6.2% | rising |
| 104 | El Salvador | -61.5 | 2019 | up 0.4% | flat |
| 105 | Cape Verde | -62.92 | 2019 | unchanged | volatile |
| 106 | Lebanon | -78.51 | 2019 | down 2,127.1% | volatile |
| 107 | Mali | -79.93 | 2019 | up 98.3% | volatile |
| 108 | Jamaica | -98.77 | 2019 | up 96.3% | volatile |
| 109 | Sierra Leone | -113.96 | 2019 | up 0.1% | volatile |
| 110 | Iceland | -118.65 | 2019 | down 88.0% | volatile |
| 111 | Tajikistan | -128.66 | 2019 | up 63.3% | volatile |
| 112 | Saint Lucia | -146.37 | 2019 | down 10.1% | flat |
| 113 | Guam | -158.4 | 2019 | — | volatile |
| 114 | United States Virgin Islands | -165.46 | 2019 | down 181.1% | volatile |
| 115 | Guinea | -178.93 | 2019 | down 20.7% | volatile |
| 116 | Eritrea | -214.85 | 2019 | down 29.0% | falling |
| 117 | Panama | -271.45 | 2019 | up 62.2% | rising |
| 118 | Cyprus | -279.05 | 2019 | down 1.4% | volatile |
| 119 | Luxembourg | -279.7 | 2019 | up 46.1% | rising |
| 120 | Colombia | -281.42 | 2019 | up 96.8% | volatile |
| 121 | Bolivia | -319 | 2019 | up 25.0% | rising |
| 122 | Togo | -328.93 | 2019 | down 63.1% | falling |
| 123 | Syria | -332.33 | 2019 | up 50.6% | rising |
| 124 | Albania | -352.01 | 2019 | up 71.5% | volatile |
| 125 | Mozambique | -365.66 | 2019 | up 0.5% | volatile |
| 126 | Mexico | -373.62 | 2019 | up 99.5% | volatile |
| 127 | Liberia | -378.36 | 2019 | down 0.1% | flat |
| 128 | Rwanda | -415.01 | 2019 | up 16.8% | rising |
| 129 | Algeria | -440.78 | 2019 | up 81.7% | volatile |
| 130 | Eswatini | -475.61 | 2019 | up 1.4% | flat |
| 131 | South Africa | -500.14 | 2019 | up 21.7% | rising |
| 132 | Netherlands | -558.59 | 2019 | up 33.4% | falling |
| 133 | Estonia | -574.06 | 2019 | up 85.0% | volatile |
| 134 | Slovenia | -965.27 | 2019 | up 91.9% | rising |
| 135 | Nicaragua | -978.42 | 2019 | down 267.2% | volatile |
| 136 | Slovakia | -1,097 | 2019 | up 87.6% | rising |
| 137 | Cameroon | -1,133 | 2019 | unchanged | volatile |
| 138 | Guatemala | -1,134 | 2019 | up 46.1% | volatile |
| 139 | Bhutan | -1,318 | 2019 | up 80.1% | rising |
| 140 | Australia | -1,585 | 2019 | up 96.2% | volatile |
| 141 | Mauritania | -1,751 | 2019 | down 643.3% | volatile |
| 142 | Bosnia and Herzegovina | -1,786 | 2019 | down 709.8% | volatile |
| 143 | Paraguay | -1,880 | 2019 | down 463.4% | volatile |
| 144 | Uruguay | -1,905 | 2019 | up 81.2% | rising |
| 145 | Morocco | -1,939 | 2019 | up 58.0% | rising |
| 146 | Uganda | -2,017 | 2019 | unchanged | flat |
| 147 | Dominican Republic | -2,161 | 2019 | down 11.5% | volatile |
| 148 | Cambodia | -2,224 | 2019 | down 118.6% | volatile |
| 149 | Azerbaijan | -2,371 | 2019 | down 18.8% | falling |
| 150 | Denmark | -2,544 | 2019 | down 117.7% | volatile |
| 151 | Fiji | -2,650 | 2019 | up 0.2% | flat |
| 152 | Puerto Rico | -2,691 | 2019 | down 18.9% | falling |
| 153 | Kazakhstan | -2,986 | 2019 | up 0.2% | volatile |
| 154 | Cuba | -3,049 | 2019 | up 70.3% | rising |
| 155 | Switzerland | -3,051 | 2019 | up 2.7% | falling |
| 156 | Peru | -3,247 | 2019 | up 75.4% | rising |
| 157 | Kyrgyzstan | -3,267 | 2019 | down 35,165.7% | volatile |
| 158 | Uzbekistan | -3,365 | 2019 | up 71.0% | volatile |
| 159 | Tunisia | -3,802 | 2019 | down 188.1% | volatile |
| 160 | Ireland | -3,889 | 2019 | down 19.9% | flat |
| 161 | Hungary | -4,125 | 2019 | down 21.2% | flat |
| 162 | Laos | -4,410 | 2019 | down 1,014.3% | volatile |
| 163 | Croatia | -4,810 | 2019 | down 342.3% | volatile |
| 164 | Latvia | -5,711 | 2019 | up 64.7% | rising |
| 165 | Lithuania | -6,030 | 2019 | down 26.7% | falling |
| 166 | Ethiopia | -6,343 | 2019 | down 6.4% | volatile |
| 167 | Serbia | -6,725 | 2019 | up 81.1% | volatile |
| 168 | Czechia | -6,894 | 2019 | up 10.5% | rising |
| 169 | Austria | -7,440 | 2019 | down 16.0% | rising |
| 170 | Costa Rica | -7,442 | 2019 | down 718.4% | volatile |
| 171 | Kenya | -7,728 | 2019 | down 29,238.9% | volatile |
| 172 | New Zealand | -13,541 | 2019 | up 43.9% | rising |
| 173 | United Kingdom | -13,596 | 2019 | down 0.2% | rising |
| 174 | Italy | -13,614 | 2019 | up 61.7% | rising |
| 175 | Spain | -15,140 | 2019 | up 22.8% | volatile |
| 176 | Vietnam | -17,342 | 2019 | down 234.6% | volatile |
| 177 | Norway | -20,215 | 2019 | up 15.8% | falling |
| 178 | Ukraine | -24,178 | 2019 | up 35.3% | rising |
| 179 | Ghana | -25,023 | 2019 | down 222.2% | volatile |
| 180 | Argentina | -27,952 | 2019 | up 22.1% | rising |
| 181 | Romania | -28,562 | 2019 | down 771.3% | volatile |
| 182 | Turkey | -28,650 | 2019 | up 33.3% | falling |
| 183 | Japan | -37,836 | 2019 | up 63.4% | rising |
| 184 | Bulgaria | -38,226 | 2019 | down 35.5% | falling |
| 185 | Germany | -39,106 | 2019 | down 38.7% | rising |
| 186 | India | -40,537 | 2019 | down 65.5% | volatile |
| 187 | Belarus | -43,554 | 2019 | up 8.1% | rising |
| 188 | Sweden | -44,980 | 2019 | up 13.2% | falling |
| 189 | Poland | -45,791 | 2019 | up 45.9% | falling |
| 190 | South Korea | -48,594 | 2019 | up 23.7% | falling |
| 191 | Chile | -58,269 | 2019 | down 59.7% | volatile |
| 192 | France | -67,237 | 2019 | up 6.3% | falling |
| 193 | Canada | -80,720 | 2019 | down 147.2% | volatile |
| 194 | Brazil | -269,413 | 2019 | up 46.6% | falling |
| 195 | United States | -331,408 | 2019 | up 25.1% | rising |
| 196 | Russia | -622,212 | 2019 | up 21.9% | falling |
| 197 | China | -651,765 | 2019 | down 95.2% | falling |
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 1961–2019 with projections for 2030 and 2050 for some categories of emissions or 1990–2019 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).