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| How Did Distribution Patterns of Particulate Matter Air Pollution (PM(2.5)and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level | |
| Fan, Zhiyu1,2; Zhan, Qingming1,2; Zhan, Meng1,2; Yang, Chen3; Liu, Huimin4 | |
| 2020-09 | |
| 发表期刊 | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
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| EISSN | 1660-4601 |
| 摘要 | Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM(2.5)and PM(10)during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM(2.5)and PM(10)concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R(2)of 0.711 and 0.732 for PM(2.5)and PM10, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM(2.5)in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM(10)in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM(10)drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future. |
| 关键词 | COVID-19 PM pollution spatiotemporal patterns spatial correlation analysis influencing factors multi-scale geographically weighted regression (MGWR) |
| DOI | 10.3390/ijerph17176274 |
| WOS关键词 | YANGTZE-RIVER DELTA ; PM2.5 CONCENTRATIONS ; ANTHROPOGENIC EMISSIONS ; AMBIENT PM2.5 ; REGRESSION ; TRENDS ; APPORTIONMENT ; URBANIZATION ; DETERMINANTS ; MORTALITY |
| WOS研究方向 | Environmental Sciences & Ecology ; Public, Environmental & Occupational Health |
| WOS类目 | Environmental Sciences ; Public, Environmental & Occupational Health |
| 出版者 | MDPI |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 专题 | 新冠肺炎 循证社会科学证据集成 |
| 作者单位 | 1.Wuhan Univ; 2.Collaborat Innovat Ctr Geospatial Technol; 3.Peking Univ; 4.Chinese Univ Hong Kong |
| 推荐引用方式 GB/T 7714 | Fan, Zhiyu,Zhan, Qingming,Zhan, Meng,et al. How Did Distribution Patterns of Particulate Matter Air Pollution (PM(2.5)and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level[J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,2020. |
| APA | Fan, Zhiyu,Zhan, Qingming,Zhan, Meng,Yang, Chen,&Liu, Huimin.(2020).How Did Distribution Patterns of Particulate Matter Air Pollution (PM(2.5)and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. |
| MLA | Fan, Zhiyu,et al."How Did Distribution Patterns of Particulate Matter Air Pollution (PM(2.5)and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020). |
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