Forest fire emissions have a great impact on local air quality and the global climate. However, the current and detailed regional forest fire emissions inventories remain poorly studied. Here we used Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate monthly emissions from forest fires at a spatial resolution of 500 m × 500 m in southwest China from 2013 to 2017. The spatial and seasonal variations of forest fire emissions were then analyzed at the provincial level. The results showed that the annual average emissions of CO2
, CO, CH4
, PM, black carbon, organic carbon, and non-methane volatile organic compounds from forest fires were 1423.19 × 103
, 91.66 × 103
, 4517.08, 881.07, 1545.04, 1268.28, 9838.91, 685.55, 7949.48, and 12,724.04 Mg, respectively. The forest fire emissions characteristics were consistent with the characteristics of forest fires, which show great spatial and temporal diversity. Higher pollutant emissions were concentrated in Yunnan and Tibet, with peak emissions occurring in spring and winter. Our work provides a better understanding of the spatiotemporal representation of regional forest fire emissions and basic data for forest fire management departments and related research on pollution and emissions controls. This method will also provide guidance for other areas to develop high-resolution regional forest fire emissions inventories.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited