Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020
Considering the current severe atmospheric pollution problems in China, a comprehensive understanding of the distribution and spatial variability of PM2.5 is critically important for controlling pollution and improving the future atmospheric environment. This study first explored the distribution of...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/13/11/1847 |
| _version_ | 1797469169995743232 |
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| author | Chunmei Bai Ping Yan |
| author_facet | Chunmei Bai Ping Yan |
| author_sort | Chunmei Bai |
| collection | DOAJ |
| description | Considering the current severe atmospheric pollution problems in China, a comprehensive understanding of the distribution and spatial variability of PM2.5 is critically important for controlling pollution and improving the future atmospheric environment. This study first explored the distribution of PM2.5 concentrations in China, and then developed a methodology of “dependence analysis” to investigate the relationship of PM2.5 in different cities in China. The data of daily PM2.5 concentrations were collected from the environmental monitoring stations in 295 cities in China. This study also developed a set of procedures to evaluate the spatial dependence of PM2.5 among the 295 Chinese cities. The results showed that there was a total of 154 city pairs with dependence type “11”, under a significance level of 0.5%. Dependence type “11” mainly occurred between nearby cities, and the distance between 89.0% of the dependent city pairs was less than 200 km. Furthermore, the dependent pairs mainly clustered in the North China Plain, the Northeast Plain, the Middle and Lower Yangtze Plain and the Fen-Wei Plain. The geographic conditions of the Plain areas were more conducive to the spread of PM2.5 contaminants, while the mountain topography was unfavorable for the formation of PM2.5 dependencies. The dependent city couples with distances greater than 200 km were all located within the Plain areas. The high concentration of PM2.5 did not necessarily lead to PM2.5 dependences between city pairs. The methodology and models developed in this study will help explain the concentration distributions and spatial dependence of the main atmospheric pollutants in China, providing guidance for the prevention of large-scale air pollution, and the improvement of the future atmospheric environment. |
| first_indexed | 2024-03-09T19:16:42Z |
| format | Article |
| id | doaj.art-f68206167bc144099a73828bfbd0161b |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-09T19:16:42Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-f68206167bc144099a73828bfbd0161b2023-11-24T03:43:12ZengMDPI AGAtmosphere2073-44332022-11-011311184710.3390/atmos13111847Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020Chunmei Bai0Ping Yan1School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaSchool of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaConsidering the current severe atmospheric pollution problems in China, a comprehensive understanding of the distribution and spatial variability of PM2.5 is critically important for controlling pollution and improving the future atmospheric environment. This study first explored the distribution of PM2.5 concentrations in China, and then developed a methodology of “dependence analysis” to investigate the relationship of PM2.5 in different cities in China. The data of daily PM2.5 concentrations were collected from the environmental monitoring stations in 295 cities in China. This study also developed a set of procedures to evaluate the spatial dependence of PM2.5 among the 295 Chinese cities. The results showed that there was a total of 154 city pairs with dependence type “11”, under a significance level of 0.5%. Dependence type “11” mainly occurred between nearby cities, and the distance between 89.0% of the dependent city pairs was less than 200 km. Furthermore, the dependent pairs mainly clustered in the North China Plain, the Northeast Plain, the Middle and Lower Yangtze Plain and the Fen-Wei Plain. The geographic conditions of the Plain areas were more conducive to the spread of PM2.5 contaminants, while the mountain topography was unfavorable for the formation of PM2.5 dependencies. The dependent city couples with distances greater than 200 km were all located within the Plain areas. The high concentration of PM2.5 did not necessarily lead to PM2.5 dependences between city pairs. The methodology and models developed in this study will help explain the concentration distributions and spatial dependence of the main atmospheric pollutants in China, providing guidance for the prevention of large-scale air pollution, and the improvement of the future atmospheric environment.https://www.mdpi.com/2073-4433/13/11/1847dependence analysisPM2.5 pollutioncity pairs |
| spellingShingle | Chunmei Bai Ping Yan Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 Atmosphere dependence analysis PM2.5 pollution city pairs |
| title | Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 |
| title_full | Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 |
| title_fullStr | Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 |
| title_full_unstemmed | Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 |
| title_short | Dependence Analysis of PM2.5 Concentrations in 295 Chinese Cities in the Winter of 2019–2020 |
| title_sort | dependence analysis of pm2 5 concentrations in 295 chinese cities in the winter of 2019 2020 |
| topic | dependence analysis PM2.5 pollution city pairs |
| url | https://www.mdpi.com/2073-4433/13/11/1847 |
| work_keys_str_mv | AT chunmeibai dependenceanalysisofpm25concentrationsin295chinesecitiesinthewinterof20192020 AT pingyan dependenceanalysisofpm25concentrationsin295chinesecitiesinthewinterof20192020 |