Emission Totals - Emissions (CH4) - Savanna fires 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
208
Highest
597.56
Australia
Lowest
0
Niue
Median
0.0787
Years covered
30
1990–2019
Data points
6,120
What the numbers show
Emission Totals - Emissions (CH4) - Savanna fires is currently reported for 208 countries. The highest value is 597.56 in Australia; the lowest is 0 in Niue.
The median across all reporting countries is 0.0787, and the mean is 17.78.
Over the past decade 62 countries rose and 81 fell. The largest increase was in Syria (up 35,094.0%), and the largest decrease in Belgium (down 100.0%).
Emission Totals - Emissions (CH4) - Savanna fires: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Australia | 597.56 | 2019 | down 17.1% | falling |
| 2 | Angola | 503.75 | 2019 | up 3.8% | rising |
| 3 | Democratic Republic of Congo | 417.3 | 2019 | down 5.1% | rising |
| 4 | Mozambique | 234.1 | 2019 | down 4.0% | flat |
| 5 | Brazil | 231.84 | 2019 | up 129.4% | rising |
| 6 | South Sudan | 230.25 | 2019 | down 40.5% | falling |
| 7 | Central African Republic | 156.11 | 2019 | down 16.8% | falling |
| 8 | Tanzania | 133.1 | 2019 | down 30.0% | falling |
| 9 | Russia | 95.73 | 2019 | up 35.0% | rising |
| 10 | Kazakhstan | 73.68 | 2019 | up 68.5% | volatile |
| 11 | Chad | 59.98 | 2019 | down 24.2% | falling |
| 12 | Mali | 57.26 | 2019 | down 13.0% | falling |
| 13 | Guinea | 51.7 | 2019 | down 8.0% | rising |
| 14 | Ghana | 50.74 | 2019 | down 14.3% | falling |
| 15 | Sudan | 49.55 | 2019 | down 38.8% | falling |
| 16 | Bolivia | 49.05 | 2019 | up 95.5% | flat |
| 17 | Ethiopia | 47.2 | 2019 | down 35.0% | falling |
| 18 | Venezuela | 44.6 | 2019 | up 33.5% | rising |
| 19 | Congo | 44.45 | 2019 | up 18.3% | rising |
| 20 | Madagascar | 42.97 | 2019 | down 22.5% | falling |
| 21 | Senegal | 42.17 | 2019 | up 0.4% | falling |
| 22 | Nigeria | 40.93 | 2019 | down 26.8% | falling |
| 23 | Paraguay | 32.75 | 2019 | up 47.7% | rising |
| 24 | South Africa | 29.64 | 2019 | down 39.6% | falling |
| 25 | Argentina | 27.76 | 2019 | down 25.5% | falling |
| 26 | Iraq | 24.48 | 2019 | up 5,197.5% | volatile |
| 27 | Colombia | 23.2 | 2019 | down 9.9% | rising |
| 28 | Cambodia | 20.26 | 2019 | down 13.9% | falling |
| 29 | United States | 19.54 | 2019 | down 24.9% | rising |
| 30 | Mexico | 19.12 | 2019 | up 17.1% | flat |
| 31 | Indonesia | 18.81 | 2019 | up 10.2% | volatile |
| 32 | Cameroon | 18.31 | 2019 | down 57.9% | falling |
| 33 | Botswana | 17.66 | 2019 | down 46.9% | volatile |
| 34 | Cote d'Ivoire | 16.75 | 2019 | down 54.9% | falling |
| 35 | Burkina Faso | 16.23 | 2019 | down 46.2% | falling |
| 36 | Sierra Leone | 13.42 | 2019 | down 34.0% | volatile |
| 37 | Benin | 12.55 | 2019 | down 12.8% | falling |
| 38 | Namibia | 11.32 | 2019 | down 88.6% | volatile |
| 39 | Myanmar | 10.31 | 2019 | down 55.6% | rising |
| 40 | Togo | 7.65 | 2019 | down 46.6% | falling |
| 41 | Uganda | 7.36 | 2019 | down 65.5% | falling |
| 42 | Canada | 6.73 | 2019 | up 38.4% | volatile |
| 43 | Syria | 6.48 | 2019 | up 35,094.0% | volatile |
| 44 | Gabon | 5.63 | 2019 | up 56.7% | rising |
| 45 | Turkmenistan | 5.42 | 2019 | up 823.6% | volatile |
| 46 | Guinea-Bissau | 5.35 | 2019 | down 1.6% | falling |
| 47 | India | 5.24 | 2019 | down 59.4% | rising |
| 48 | Malawi | 4.5 | 2019 | up 6.1% | falling |
| 49 | Thailand | 4.46 | 2019 | down 37.0% | flat |
| 50 | Laos | 4.17 | 2019 | down 5.4% | volatile |
| 51 | Honduras | 3.63 | 2019 | up 39.7% | volatile |
| 52 | China | 3.49 | 2019 | down 61.7% | volatile |
| 53 | Mongolia | 3.2 | 2019 | down 19.6% | falling |
| 54 | Iran | 2.44 | 2019 | up 332.8% | flat |
| 55 | Niger | 2.34 | 2019 | up 6.3% | falling |
| 56 | Vietnam | 2.12 | 2019 | down 51.9% | flat |
| 57 | Kenya | 2.07 | 2019 | up 39.8% | volatile |
| 58 | Nicaragua | 2.06 | 2019 | up 139.3% | volatile |
| 59 | Papua New Guinea | 2.05 | 2019 | down 9.7% | volatile |
| 60 | Mauritania | 1.78 | 2019 | down 59.3% | volatile |
| 61 | Guatemala | 1.75 | 2019 | down 46.6% | volatile |
| 62 | Liberia | 1.37 | 2019 | down 67.1% | volatile |
| 63 | Ukraine | 1.34 | 2019 | down 8.3% | volatile |
| 64 | Eswatini | 1.3 | 2019 | up 150.1% | flat |
| 65 | Gambia | 1.21 | 2019 | down 35.3% | falling |
| 66 | Peru | 1.1 | 2019 | up 114.3% | volatile |
| 67 | Nepal | 1.01 | 2019 | up 32.2% | volatile |
| 68 | Azerbaijan | 1 | 2019 | up 811.7% | volatile |
| 69 | Guyana | 0.8983 | 2019 | up 37.8% | volatile |
| 70 | Suriname | 0.8553 | 2019 | up 0.5% | volatile |
| 71 | Panama | 0.8379 | 2019 | down 6.3% | volatile |
| 72 | Ecuador | 0.6882 | 2019 | up 58.5% | volatile |
| 73 | Philippines | 0.6601 | 2019 | down 14.3% | rising |
| 74 | Chile | 0.6006 | 2019 | down 0.8% | volatile |
| 75 | Turkey | 0.5539 | 2019 | up 13.2% | volatile |
| 76 | Algeria | 0.5417 | 2019 | down 70.2% | volatile |
| 77 | Uzbekistan | 0.4724 | 2019 | down 0.9% | falling |
| 78 | Spain | 0.4682 | 2019 | down 43.7% | volatile |
| 79 | Belize | 0.4635 | 2019 | up 244.4% | volatile |
| 80 | Rwanda | 0.4562 | 2019 | up 212.9% | volatile |
| 81 | Burundi | 0.4344 | 2019 | up 9.2% | falling |
| 82 | Cuba | 0.4216 | 2019 | down 75.7% | volatile |
| 83 | Lesotho | 0.3291 | 2019 | down 44.4% | volatile |
| 84 | Costa Rica | 0.2959 | 2019 | up 93.0% | rising |
| 85 | France | 0.2818 | 2019 | up 164.8% | volatile |
| 86 | Bangladesh | 0.2455 | 2019 | down 77.6% | volatile |
| 87 | Pakistan | 0.2095 | 2019 | down 46.6% | rising |
| 88 | Portugal | 0.1819 | 2019 | down 69.6% | volatile |
| 89 | New Caledonia | 0.1794 | 2019 | — | volatile |
| 90 | Uruguay | 0.1783 | 2019 | down 36.6% | flat |
| 91 | Romania | 0.1712 | 2019 | up 47.1% | volatile |
| 92 | Malaysia | 0.1634 | 2019 | down 63.5% | volatile |
| 93 | Georgia | 0.1623 | 2019 | up 1,011.6% | volatile |
| 94 | Belarus | 0.1489 | 2019 | up 32.8% | volatile |
| 95 | East Timor | 0.1475 | 2019 | up 0.3% | volatile |
| 96 | El Salvador | 0.1443 | 2019 | up 632.5% | volatile |
| 97 | Afghanistan | 0.1432 | 2019 | up 185.3% | volatile |
| 98 | United Kingdom | 0.1428 | 2019 | up 636.1% | volatile |
| 99 | North Macedonia | 0.1246 | 2019 | up 2,442.9% | volatile |
| 100 | Armenia | 0.123 | 2019 | up 12,200.0% | volatile |
| 101 | Egypt | 0.1122 | 2019 | up 3,769.0% | volatile |
| 102 | Serbia | 0.0989 | 2019 | up 371.0% | volatile |
| 103 | Bulgaria | 0.0827 | 2019 | up 170.3% | volatile |
| 104 | Eritrea | 0.0805 | 2019 | up 631.8% | volatile |
| 105 | Sri Lanka | 0.0769 | 2019 | down 94.2% | volatile |
| 106 | Tunisia | 0.0668 | 2019 | up 9,442.9% | volatile |
| 107 | Bosnia and Herzegovina | 0.0662 | 2019 | up 524.5% | volatile |
| 108 | Greece | 0.0572 | 2019 | down 83.1% | volatile |
| 109 | Dominican Republic | 0.0558 | 2019 | down 42.8% | volatile |
| 110 | Italy | 0.054 | 2019 | down 60.4% | volatile |
| 111 | Libya | 0.0533 | 2019 | — | volatile |
| 112 | Bahamas | 0.0457 | 2019 | down 75.1% | volatile |
| 113 | North Korea | 0.0452 | 2019 | down 86.3% | volatile |
| 114 | Comoros | 0.0353 | 2019 | up 11,666.7% | volatile |
| 115 | Somalia | 0.0333 | 2019 | down 82.5% | volatile |
| 116 | Morocco | 0.031 | 2019 | down 53.1% | volatile |
| 117 | Croatia | 0.0309 | 2019 | up 8.8% | volatile |
| 118 | Albania | 0.0266 | 2019 | down 18.4% | volatile |
| 119 | Kyrgyzstan | 0.0262 | 2019 | up 41.6% | volatile |
| 120 | Finland | 0.0231 | 2019 | down 4.5% | volatile |
| 121 | New Zealand | 0.0225 | 2019 | up 11,150.0% | volatile |
| 122 | South Korea | 0.02 | 2019 | down 37.9% | volatile |
| 123 | Montenegro | 0.0178 | 2019 | up 1,383.3% | volatile |
| 124 | Bhutan | 0.0173 | 2019 | up 302.3% | volatile |
| 124 | Japan | 0.0173 | 2019 | down 49.6% | volatile |
| 126 | Lebanon | 0.0165 | 2019 | — | volatile |
| 127 | Jamaica | 0.0131 | 2019 | up 133.9% | volatile |
| 128 | Moldova | 0.0123 | 2019 | up 4,000.0% | volatile |
| 129 | Saudi Arabia | 0.0119 | 2019 | down 92.4% | volatile |
| 130 | Israel | 0.011 | 2019 | — | volatile |
| 131 | Norway | 0.0103 | 2019 | — | volatile |
| 132 | Haiti | 0.0085 | 2019 | up 13.3% | falling |
| 132 | Ireland | 0.0085 | 2019 | — | volatile |
| 134 | Hungary | 0.0047 | 2019 | down 62.1% | volatile |
| 135 | Greenland | 0.0041 | 2019 | — | volatile |
| 136 | Trinidad and Tobago | 0.004 | 2019 | down 14.9% | volatile |
| 137 | Palestine | 0.0035 | 2019 | — | volatile |
| 138 | Estonia | 0.0018 | 2019 | up 800.0% | volatile |
| 138 | Poland | 0.0018 | 2019 | down 76.0% | volatile |
| 140 | Czechia | 0.0012 | 2019 | up 100.0% | volatile |
| 140 | Puerto Rico | 0.0012 | 2019 | — | volatile |
| 142 | Cyprus | 0.001 | 2019 | — | volatile |
| 143 | Fiji | 0.0007 | 2019 | down 98.8% | volatile |
| 144 | Germany | 0.0006 | 2019 | unchanged | volatile |
| 144 | Latvia | 0.0006 | 2019 | down 89.3% | volatile |
| 144 | Slovakia | 0.0006 | 2019 | up 200.0% | volatile |
| 147 | Tajikistan | 0.0002 | 2019 | down 99.2% | volatile |
| 148 | Aruba | 0 | 2019 | — | flat |
| 148 | Andorra | 0 | 2019 | — | flat |
| 148 | United Arab Emirates | 0 | 2019 | — | volatile |
| 148 | American Samoa | 0 | 2019 | — | flat |
| 148 | Antigua and Barbuda | 0 | 2019 | — | flat |
| 148 | Austria | 0 | 2019 | — | volatile |
| 148 | Belgium | 0 | 2019 | down 100.0% | volatile |
| 148 | Bahrain | 0 | 2019 | — | flat |
| 148 | Bermuda | 0 | 2019 | — | flat |
| 148 | Barbados | 0 | 2019 | — | volatile |
| 148 | Brunei | 0 | 2019 | down 100.0% | volatile |
| 148 | Switzerland | 0 | 2019 | — | volatile |
| 148 | Cape Verde | 0 | 2019 | — | flat |
| 148 | Cayman Islands | 0 | 2019 | — | flat |
| 148 | Dominica | 0 | 2019 | — | flat |
| 148 | Denmark | 0 | 2019 | down 100.0% | volatile |
| 148 | Faroe Islands | 0 | 2019 | — | flat |
| 148 | Micronesia (country) | 0 | 2019 | — | flat |
| 148 | Gibraltar | 0 | 2019 | — | volatile |
| 148 | Equatorial Guinea | 0 | 2019 | — | volatile |
| 148 | Grenada | 0 | 2019 | — | flat |
| 148 | Guam | 0 | 2019 | — | flat |
| 148 | Hong Kong | 0 | 2019 | down 100.0% | volatile |
| 148 | Isle of Man | 0 | 2019 | — | flat |
| 148 | Iceland | 0 | 2019 | — | volatile |
| 148 | Jordan | 0 | 2019 | — | volatile |
| 148 | Kiribati | 0 | 2019 | — | flat |
| 148 | Saint Kitts and Nevis | 0 | 2019 | — | volatile |
| 148 | Kuwait | 0 | 2019 | — | flat |
| 148 | Saint Lucia | 0 | 2019 | — | flat |
| 148 | Lithuania | 0 | 2019 | down 100.0% | volatile |
| 148 | Luxembourg | 0 | 2019 | — | flat |
| 148 | Macao | 0 | 2019 | — | flat |
| 148 | Maldives | 0 | 2019 | — | flat |
| 148 | Marshall Islands | 0 | 2019 | — | flat |
| 148 | Malta | 0 | 2019 | — | flat |
| 148 | Northern Mariana Islands | 0 | 2019 | — | flat |
| 148 | Mauritius | 0 | 2019 | — | volatile |
| 148 | Netherlands | 0 | 2019 | — | volatile |
| 148 | Nauru | 0 | 2019 | — | flat |
| 148 | Oman | 0 | 2019 | — | volatile |
| 148 | Palau | 0 | 2019 | — | flat |
| 148 | French Polynesia | 0 | 2019 | — | flat |
| 148 | Qatar | 0 | 2019 | — | flat |
| 148 | Singapore | 0 | 2019 | — | flat |
| 148 | Solomon Islands | 0 | 2019 | — | volatile |
| 148 | Sao Tome and Principe | 0 | 2019 | — | volatile |
| 148 | Slovenia | 0 | 2019 | — | volatile |
| 148 | Sweden | 0 | 2019 | — | volatile |
| 148 | Seychelles | 0 | 2019 | — | flat |
| 148 | Turks and Caicos Islands | 0 | 2019 | down 100.0% | volatile |
| 148 | Tonga | 0 | 2019 | — | flat |
| 148 | Tuvalu | 0 | 2019 | — | flat |
| 148 | Saint Vincent and the Grenadines | 0 | 2019 | — | flat |
| 148 | British Virgin Islands | 0 | 2019 | — | flat |
| 148 | United States Virgin Islands | 0 | 2019 | — | flat |
| 148 | Vanuatu | 0 | 2019 | — | volatile |
| 148 | Samoa | 0 | 2019 | — | flat |
| 148 | Taiwan | 0 | 2019 | down 100.0% | volatile |
| 148 | Cook Islands | 0 | 2019 | — | flat |
| 148 | Niue | 0 | 2019 | — | flat |
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).