In this study, Moderate Resolution Imaging Spectroradiometer active fire and land use products were integrated to extract and classify biomass burning (BB) data for South Asia (SA) and Southeast Asia (SEA). Several trend and geographic distribution analyses were conducted at the grid (0.25° × 0.25°) and regional scales. As the principal local form of BB, crop residue burning (CRB) in SA increased by 844 spots/yr, and the Mann-Kendall (MK) τ reached 0.61. Additionally, the CRB in Punjab-Haryana, a region a well-known for severest CRB, presented a significant declining trend. BB in mainland SEA was much more intense and was dominated by forest and shrubland fires. Forest fires in mainland SEA declined at a rate of -209 spots/yr, and shrubland fire conversely grew at a rate of 803 spots/yr, which was likely related to the dramatic land cover change induced by the local swidden agriculture. Unlike other regions, BB in equatorial SEA primarily occurred in the second half of the year (August to October), and it was extremely vulnerable to El Niño events. When the annual sea surface temperature anomalies within the Niño 3 region improved by 1 °C, the annual BB spots and fire radiative power in equatorial SEA increased by 5.18 × 104 and 2.40 × 106 MW, respectively. Although the interannual variations in equatorial SEA were dramatic, the robust Siegel's repeated median estimator still revealed that equatorial SEA BB significantly declined by -1825 spots/yr. This regional decline reflects government endeavors to curb indigenous BB. However, regions with enhanced BB still need to draw more attention, and it is imperative for the Indonesian government to take substantial measures to reduce anthropogenic fire sources during El Niño events.

With China as the study area, MODIS MOD14A1 and MCD12Q1 products were used to derive daily crop residue burning spots from 2014 to 2015. After vectorization of crop residue burning pixels and with the use of fishnet, burning density distribution maps were eventually completed. Meanwhile, the daily air quality data from 150 cities in 2014 and 285 cities in 2015 were used to obtain daily and monthly PM2.5 distribution maps with the Kriging interpolation. The results indicate that crop residue burning occurs in a seasonal pattern, and its spatial distribution is closely related to farming activities. The annual PM2.5 in China decreased 11.81% from 2014 to 2015, and the distribution of PM2.5 in China's east and north is always higher than in China's west and south. Furthermore, the changes in PM2.5 exhibit a hysteresis after crop residue burning in summer and autumn-winter. Regarding summer crop residue burning in China's middle-east, the r between crop residue burning spots and PM2.5 is 0.6921 (P < 0.01) in 2014 and 0.5620 (P < 0.01) in 2015, while the correlation coefficient of autumn-winter crop residue burning in China's northeast is slightly lower with an r of 0.5670 (P < 0.01) in 2014 and 0.6213 (P < 0.01) in 2015. In autumn-winter, crop residue burning can induce evident PM2.5 increase in China's northeast, and that is more obvious than summer crop residue burning in China's middle-east. Furthermore, when data of summer and autumn-winter crop residue burning from 2014 to 2015 are compared, we can see that the change in number of crop residue burning spots significant changes PM2.5 in these regions. Both the summer and autumn-winter crop residue burning areas presented spatial consistency with high PM2.5. By contrast, the results from many aspects indicated that the crop residue burning in spring did not cause a notable change of PM2.5.