Study on spatial distribution of crop residue burning and PM2.5 change in China

Abstract

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 PM 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 PM in China decreased 11.81% from 2014 to 2015, and the distribution of PM in China's east and north is always higher than in China's west and south. Furthermore, the changes in PM 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 PM 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 PM 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 PM in these regions. Both the summer and autumn-winter crop residue burning areas presented spatial consistency with high PM. By contrast, the results from many aspects indicated that the crop residue burning in spring did not cause a notable change of PM.

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

“…According to Figure 4, it is noted that there is no clear linear correlation between the number of crop residue burning spots and mean PM 2.5 concentrations at the provincial level. Different from Yin et al's findings [16], this research suggests that crop residue burning, even with the largest intensity (the number of crop residue burning spots in Heilongjiang province was the most in China during this period) exerted limited influence on the variations of PM 2.5 concentrations at a large scale, which was also influenced significantly by a diversity of emission sources and meteorological factors. Therefore, we would suggest further examination of the influence of crop residue burning on local PM 2.5 concentrations.…”

“…The difference in processing methods exerts slight influences on the following analysis, as the calculated number of crop residue burning spots for each day generally changed proportionally. Yin et al [16] attempted to establish a qualitative linkage between the number of crop residue burning spots and the temporal variation of PM 2.5 concentrations at a regional scale. The result suggested that a long-term variation of the total number of crop residue burning spots was generally consistent with the average PM 2.5 concentrations within specific regions.…”

“…However, compared with traffic, industry emissions, and other major emission sources, few in-depth studies on the quantitative influences of crop residue burning on the variations of local and regional PM 2.5 concentrations have been conducted. Yin et al [16] examined the spatial and seasonal distribution of crop residue burning across China and its correlation with regional PM 2.5 concentrations. This research [16] attempted to establish qualitative correlations between the intensity of crop residue burning and regional PM 2.5 concentrations by analyzing the total number of crop residue burning spots and the spatio-temporal variations of regional PM 2.5 concentrations, respectively.…”

“…Yin et al [16] examined the spatial and seasonal distribution of crop residue burning across China and its correlation with regional PM 2.5 concentrations. This research [16] attempted to establish qualitative correlations between the intensity of crop residue burning and regional PM 2.5 concentrations by analyzing the total number of crop residue burning spots and the spatio-temporal variations of regional PM 2.5 concentrations, respectively. Yin et al [16] provided a feasible solution for linking the temporal variations of regional PM 2.5 concentrations to the influencing area and intensity of regional crop residue burning activities.…”

“…This research [16] attempted to establish qualitative correlations between the intensity of crop residue burning and regional PM 2.5 concentrations by analyzing the total number of crop residue burning spots and the spatio-temporal variations of regional PM 2.5 concentrations, respectively. Yin et al [16] provided a feasible solution for linking the temporal variations of regional PM 2.5 concentrations to the influencing area and intensity of regional crop residue burning activities. However, this research simply revealed that the temporal variation of the total number of crop residue burning spots within a large region was generally consistent with that of regional PM 2.5 concentrations.…”