Volume 36 Issue 4
Apr.  2023
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XU Wenli, CHEN Qiangqiang. Spatial-Temporal Variation Characteristics and Pollutants Analysis of Urban PM2.5 in the Yellow River Basin[J]. Research of Environmental Sciences, 2023, 36(4): 637-648. doi: 10.13198/j.issn.1001-6929.2022.10.06
Citation: XU Wenli, CHEN Qiangqiang. Spatial-Temporal Variation Characteristics and Pollutants Analysis of Urban PM2.5 in the Yellow River Basin[J]. Research of Environmental Sciences, 2023, 36(4): 637-648. doi: 10.13198/j.issn.1001-6929.2022.10.06

Spatial-Temporal Variation Characteristics and Pollutants Analysis of Urban PM2.5 in the Yellow River Basin

doi: 10.13198/j.issn.1001-6929.2022.10.06
Funds:  National Social Science Foundation of China (No.21BJY117)
  • Received Date: 2022-07-31
  • Rev Recd Date: 2022-09-26
  • Analyzing and revealing the spatial and temporal characteristics of PM2.5 in cities of the Yellow River Basin is of great significance for winning the battle against air pollution and promoting the establishment and improvement of the cross-regional cooperative control mechanism of air pollution and the green high-quality development. Based on the PM2.5 concentration monitoring data of 456 monitoring stations, this paper analyzed the spatial and temporal variation characteristics and evolution pattern of PM2.5 in 70 cities in the Yellow River Basin from 2015 to 2021 by using the Moran index and standard deviation ellipse method, and identified the pollution sources by Pearson correlation coefficient analysis method. The results showed that: (1) PM2.5 concentration reflected monthly and seasonal changes. The monthly average concentration showed a ‘U-shaped’ distribution with a wide and slow bottom, reaching the maximum in December or January. In terms of seasons, the average concentration in winter was the highest (1.9-2.6 times that of summer), followed by spring and autumn, and the lowest in summer. The annual average concentration decreased in general, showing a spatial differentiation of downstream > midstream > upstream. (2) The spatial aggregation of PM2.5 was characterized by ‘low-low’ agglomeration in the upstream, ‘high-high’ agglomeration in the downstream, and insignificant spatial aggregation in the midstream. The number of cities with positive spatial correlation agglomeration increased first and then decreased, while the number of cities with negative spatial correlation agglomeration was relatively small. (3) The spatial distribution pattern of PM2.5 generally followed a ‘northwest-southeast’ geographical spatial trend, and the concentration distribution showed the characteristics of geographical spatial decentralization and gradual reduction of distribution range. (4) PM2.5 pollution in upstream cities was complex and diverse, mainly including PM10, NO2, CO and SO2. PM10, NO2 and CO were the main sources in midstream cities, and PM10 and CO were the main sources in downstream cities. The spatial heterogeneity of PM2.5 concentration in cities of the Yellow River Basin was obvious, and there was a significant positive spatial correlation agglomeration in the upstream and downstream. Collaborative prevention and control in cities will help to further improve air quality in the Yellow River Basin.

     

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