Emission Totals - Emissions (CH4) - Land Use change 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 (CH4) - Land Use change is currently reported for 87 countries. The highest value is 4,022 in Indonesia; the lowest is 0 in Haiti.
The median across all reporting countries is 0.6704, and the mean is 67.56.
Over the past decade 34 countries rose and 35 fell. The largest increase was in El Salvador (up 3,457.1%), and the largest decrease in Burkina Faso (down 100.0%).
Emission Totals - Emissions (CH4) - Land Use change: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Indonesia | 4,022 | 2019 | up 4.4% | volatile |
| 2 | Democratic Republic of Congo | 439.8 | 2019 | down 5.5% | falling |
| 3 | Angola | 243.53 | 2019 | up 1.2% | falling |
| 4 | Central African Republic | 236.81 | 2019 | down 9.8% | rising |
| 5 | Brazil | 189.01 | 2019 | up 361.4% | volatile |
| 6 | Bolivia | 173.81 | 2019 | up 509.5% | volatile |
| 7 | Myanmar | 118.3 | 2019 | down 46.3% | falling |
| 8 | Mozambique | 80.59 | 2019 | down 17.9% | rising |
| 9 | Tanzania | 75.83 | 2019 | down 21.9% | rising |
| 10 | Malaysia | 74.04 | 2019 | down 63.3% | volatile |
| 11 | Cambodia | 29.82 | 2019 | down 45.7% | flat |
| 12 | Thailand | 25.56 | 2019 | down 32.1% | falling |
| 13 | Nepal | 21.67 | 2019 | up 70.4% | volatile |
| 14 | Cameroon | 17.14 | 2019 | up 22.7% | volatile |
| 15 | Laos | 13.99 | 2019 | up 4.8% | volatile |
| 16 | Chad | 12.97 | 2019 | up 18.8% | flat |
| 17 | Mexico | 10.61 | 2019 | down 19.5% | volatile |
| 18 | Venezuela | 10.48 | 2019 | up 898.6% | volatile |
| 19 | South Sudan | 9.28 | 2019 | down 50.7% | falling |
| 20 | India | 7.78 | 2019 | down 81.9% | flat |
| 21 | Congo | 7.66 | 2019 | up 59.6% | falling |
| 22 | Paraguay | 7.22 | 2019 | up 376.0% | volatile |
| 23 | Liberia | 4 | 2019 | down 66.5% | volatile |
| 24 | Ethiopia | 3.92 | 2019 | down 13.8% | falling |
| 25 | Malawi | 3.92 | 2019 | up 53.4% | rising |
| 26 | Colombia | 3.64 | 2019 | up 151.9% | volatile |
| 27 | Honduras | 3.53 | 2019 | down 28.7% | volatile |
| 28 | Madagascar | 3.1 | 2019 | down 30.8% | falling |
| 29 | Nigeria | 2.95 | 2019 | up 5.2% | volatile |
| 30 | Guinea-Bissau | 2.76 | 2019 | down 44.2% | falling |
| 31 | Guatemala | 2.18 | 2019 | down 70.0% | volatile |
| 32 | Vietnam | 2.1 | 2019 | down 11.9% | volatile |
| 33 | Peru | 2.09 | 2019 | up 146.4% | volatile |
| 34 | Nicaragua | 1.87 | 2019 | up 452.2% | volatile |
| 35 | Belize | 1.28 | 2019 | up 216.4% | volatile |
| 36 | Argentina | 1.26 | 2019 | down 72.0% | volatile |
| 37 | Benin | 1.1 | 2019 | up 22.2% | volatile |
| 38 | Guinea | 0.9732 | 2019 | down 69.9% | volatile |
| 39 | Australia | 0.9638 | 2019 | down 68.8% | volatile |
| 40 | Papua New Guinea | 0.9502 | 2019 | up 54.2% | volatile |
| 41 | Gabon | 0.8401 | 2019 | up 51.7% | falling |
| 42 | Guyana | 0.724 | 2019 | up 405.9% | volatile |
| 43 | Costa Rica | 0.6868 | 2019 | up 1,040.9% | volatile |
| 44 | Senegal | 0.6704 | 2019 | down 66.8% | volatile |
| 45 | Uganda | 0.5974 | 2019 | up 83.5% | volatile |
| 46 | Sierra Leone | 0.527 | 2019 | down 42.3% | volatile |
| 47 | Panama | 0.4357 | 2019 | up 39.1% | volatile |
| 48 | Ghana | 0.4087 | 2019 | up 535.6% | volatile |
| 49 | Bangladesh | 0.4073 | 2019 | down 88.4% | volatile |
| 50 | Philippines | 0.3964 | 2019 | up 42.5% | volatile |
| 51 | Bahamas | 0.2745 | 2019 | down 31.6% | volatile |
| 52 | Suriname | 0.2655 | 2019 | up 137.1% | volatile |
| 53 | New Caledonia | 0.1662 | 2019 | — | volatile |
| 54 | Togo | 0.1328 | 2019 | up 16.4% | volatile |
| 55 | Cote d'Ivoire | 0.1058 | 2019 | down 74.0% | volatile |
| 56 | Brunei | 0.0858 | 2019 | down 67.7% | volatile |
| 57 | El Salvador | 0.0747 | 2019 | up 3,457.1% | volatile |
| 58 | Cuba | 0.0582 | 2019 | down 96.2% | volatile |
| 59 | South Africa | 0.0562 | 2019 | up 577.1% | volatile |
| 60 | Ecuador | 0.0332 | 2019 | up 435.5% | volatile |
| 61 | Dominican Republic | 0.0312 | 2019 | up 66.8% | volatile |
| 62 | Trinidad and Tobago | 0.0291 | 2019 | up 592.9% | volatile |
| 63 | East Timor | 0.029 | 2019 | down 65.9% | volatile |
| 64 | Fiji | 0.0166 | 2019 | down 96.2% | volatile |
| 65 | United States | 0.0104 | 2019 | down 76.2% | volatile |
| 66 | Mali | 0.0062 | 2019 | up 47.6% | volatile |
| 67 | Bhutan | 0.0021 | 2019 | down 97.8% | volatile |
| 67 | Comoros | 0.0021 | 2019 | down 83.2% | volatile |
| 67 | Kenya | 0.0021 | 2019 | — | volatile |
| 70 | Burundi | 0 | 2019 | — | volatile |
| 70 | British Virgin Islands | 0 | 2019 | — | volatile |
| 70 | Vanuatu | 0 | 2019 | — | volatile |
| 70 | Burkina Faso | 0 | 2019 | down 100.0% | volatile |
| 70 | Samoa | 0 | 2019 | — | volatile |
| 70 | Puerto Rico | 0 | 2019 | — | volatile |
| 70 | Turks and Caicos Islands | 0 | 2019 | — | volatile |
| 70 | Solomon Islands | 0 | 2019 | — | volatile |
| 70 | Singapore | 0 | 2019 | — | volatile |
| 70 | Sudan | 0 | 2019 | — | volatile |
| 70 | French Polynesia | 0 | 2019 | — | volatile |
| 70 | China | 0 | 2019 | — | volatile |
| 70 | Sri Lanka | 0 | 2019 | down 100.0% | volatile |
| 70 | Gambia | 0 | 2019 | — | volatile |
| 70 | Jamaica | 0 | 2019 | — | volatile |
| 70 | Equatorial Guinea | 0 | 2019 | — | volatile |
| 70 | Grenada | 0 | 2019 | — | volatile |
| 70 | Haiti | 0 | 2019 | — | 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 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).