Factors and Their Interaction Effects on the Distribution of PM2.5 in the Yangtze River Delta Based on Grids

被引:0
|
作者
Huang X.-G. [1 ,2 ,3 ]
Zhao J.-B. [2 ,3 ]
Xin W.-D. [1 ]
机构
[1] College of Geographical Sciences, Shanxi Normal University, Linfen
[2] Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an
[3] School of Geography and Tourism, Shaanxi Normal University, Xi'an
来源
Huanjing Kexue/Environmental Science | 2021年 / 42卷 / 07期
关键词
Factors; Grid; Interaction effect; PM[!sub]2.5[!/sub; Spatial distribution; Yangtze River Delta;
D O I
10.13227/j.hjkx.202012101
中图分类号
学科分类号
摘要
Spatial features of PM2.5 concentration in the Yangtze River Delta in 2016 were analyzed using remote sensing data. Selecting factors among meteorology, topography, vegetation, and emission list of air pollutants, factors and their interaction effects on the spatial distribution of PM2.5 concentration were studied based on GAM, with an evaluation unit of 0.25°×0.25° for the grid. It showed that: ① With a more significant difference between the north and south, PM2.5 concentration was generally higher in the north and west but lower in the south and east. In the southern part of the delta, the concentration was mostly lower than 35 μg•m-3, with noncompliance of the PM2.5 concentration scattered in urban areas like islands. Meanwhile, PM2.5 concentration is generally over 35 μg•m-3, and the pollution appeared like sheets. ② Besides, PM2.5 concentration showed an apparent positive spatial autocorrelation with "High-High" PM2.5 agglomeration areas in the north of the delta and "Low-Low" PM2.5 agglomeration areas in the south. ③ Based on GAM, hypsography, temperature, and precipitation negatively affected PM2.5 concentration, whereas pollutant emissions positively affected it. The effect of wind was minor when its speed <2.5 m•s-1, and more negatively significant when its speed ≥2.5 m•s-1. Hypsography, temperature, and precipitation were higher in the southern part of the delta, but they were lower in the northern part, leading to a higher PM2.5 concentration in the northern parts and lower in the southern parts. A higher wind speed in the east and lower in the west also led to a concentration difference between them. ④ All factors had passed a significant pair interaction test, except for hypsography and PM2.5 emission, and they all showed a significant interaction effect on the distribution of PM2.5 in the Yangtze River Delta. © 2021, Science Press. All right reserved.
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页码:3107 / 3117
页数:10
相关论文
共 37 条
  • [1] Ming L L, Jin L, Li J, Et al., PM<sub>2.5</sub> in the Yangtze River Delta, China: chemical compositions, seasonal variations, and regional pollution events, Environmental Pollution, 223, pp. 200-212, (2017)
  • [2] Zhang X Y, Xu X D, Ding Y H, Et al., The impact of meteorological changes from 2013 to 2017 on PM<sub>2.5</sub> mass reduction in key regions in China, Science China Earth Sciences, 62, 12, pp. 1885-1902, (2019)
  • [3] Huang X G, Zhao J B, Cao J J, Et al., Evolution of the distribution of PM<sub>2.5</sub> concentration in the Yangtze River economic belt and its influencing factors, Environmental Science, 41, 3, pp. 1013-1024, (2020)
  • [4] Guo J P, Xia F, Zhang Y, Et al., Impact of diurnal variability and meteorological factors on the PM<sub>2.5</sub>-AOD relationship: Implications for PM<sub>2.5</sub> remote sensing, Environmental Pollution, 221, pp. 94-104, (2017)
  • [5] Zhang Z Y, Zhang X L, Gong D Y, Et al., Evolution of surface O<sub>3</sub> and PM<sub>2.5</sub> concentrations and their relationships with meteorological conditions over the last decade in Beijing, Atmospheric Environment, 108, pp. 67-75, (2015)
  • [6] He X, Lin Z S., Interactive effects of the influencing factors on the changes of PM<sub>2.5</sub> concentration based on GAM model, Environmental Science, 38, 1, pp. 22-32, (2017)
  • [7] Huang X G, Shao T J, Zhao J B, Et al., Influence factors and spillover effect of PM<sub>2.5</sub> concentration on Fen-wei Plain, China Environmental Science, 39, 8, pp. 3539-3548, (2019)
  • [8] Wang S R, Yu Y Y, Wang Q G, Et al., Source apportionment of PM<sub>2.5</sub> in Nanjing by PMF, China Environmental Science, 35, 12, pp. 3535-3542, (2015)
  • [9] Chen G, Liu J Y, Huangfu Y Q, Et al., Seasonal variations and source apportionment of ambient PM<sub>10</sub> and PM<sub>2.5</sub> at urban area of Hefei, China, China Environmental Science, 36, 7, pp. 1938-1946, (2016)
  • [10] Zhang Y F, Ma Y, Qi L, Et al., Determination and source apportionment of aromatic acids in PM<sub>2.5</sub> from the northern suburb of Nanjing in winter, Environmental Science, 37, 7, pp. 2436-2442, (2016)