Affinity zone identification approach for joint control of PM2.5 pollution over China. (October 2020)
- Record Type:
- Journal Article
- Title:
- Affinity zone identification approach for joint control of PM2.5 pollution over China. (October 2020)
- Main Title:
- Affinity zone identification approach for joint control of PM2.5 pollution over China
- Authors:
- Yao, Xuefeng
Ge, Baozhu
Yang, Wenyi
Li, Jianjun
Xu, Danhui
Wang, Wei
Zheng, Haitao
Wang, Zifa - Abstract:
- Abstract: In recent years, the Chinese government has made great efforts to jointly control and prevent air pollution, especially fine particulate matter (PM2.5 ). However, these efforts are challenged by technical constraints due to the significant temporal and spatial heterogeneity of PM2.5 across China. In this study, the Affinity Zone Identification Approach (AZIA), which combines rotated principal component analysis (RPCA) with revised clustering analysis, was developed and employed to regionalize PM2.5 pollution in China based on data from 1496 air quality monitoring sites recorded from 2013 to 2017. Two clustering methods, cluster analysis with statistical test (CAST) and K-center-point (K-medoids) clustering, were compared and revised to eliminate unspecified sites. Site zonation was finally extended to the municipality scale for the convenience of the controlling measures. The results revealed that 17 affinity zones with 5 different labels from clean to heavily polluted areas could be identified in China. The heavily polluted areas were mainly located in central and eastern China as well as Xinjiang Province, with regional average annual PM2.5 concentrations higher than 66 μ g/m 3 . The new approach provided more comprehensive and detailed affinity zones than obtained in a previous study (Wang et al., 2015b). The North China Plain and Northeastern China were both further divided into northern and southern parts based on different pollution levels. In addition, fiveAbstract: In recent years, the Chinese government has made great efforts to jointly control and prevent air pollution, especially fine particulate matter (PM2.5 ). However, these efforts are challenged by technical constraints due to the significant temporal and spatial heterogeneity of PM2.5 across China. In this study, the Affinity Zone Identification Approach (AZIA), which combines rotated principal component analysis (RPCA) with revised clustering analysis, was developed and employed to regionalize PM2.5 pollution in China based on data from 1496 air quality monitoring sites recorded from 2013 to 2017. Two clustering methods, cluster analysis with statistical test (CAST) and K-center-point (K-medoids) clustering, were compared and revised to eliminate unspecified sites. Site zonation was finally extended to the municipality scale for the convenience of the controlling measures. The results revealed that 17 affinity zones with 5 different labels from clean to heavily polluted areas could be identified in China. The heavily polluted areas were mainly located in central and eastern China as well as Xinjiang Province, with regional average annual PM2.5 concentrations higher than 66 μ g/m 3 . The new approach provided more comprehensive and detailed affinity zones than obtained in a previous study (Wang et al., 2015b). The North China Plain and Northeastern China were both further divided into northern and southern parts based on different pollution levels. In addition, five affinity zones were first recognized in western China. The findings provide not only a theoretical basis to further display the temporal and spatial variations in PM2.5 but also an effective solution for the cooperative control of air pollution in China. Graphical abstract: Image 1 Highlights: An innovative approach was developed for the joint control of PM2.5 in China. The approach is more objective than those established in previous studies. The regionalization of PM2.5 at the municipality scale in China is first provided. 17 affinity zones with 5 different PM2.5 pollution levels were identified in China. … (more)
- Is Part Of:
- Environmental pollution. Volume 265(2020)Part B
- Journal:
- Environmental pollution
- Issue:
- Volume 265(2020)Part B
- Issue Display:
- Volume 265, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 265
- Issue:
- 2
- Issue Sort Value:
- 2020-0265-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10
- Subjects:
- PM2.5 -- Affinity zone identification approach -- Zoning -- Cluster analysis -- RPCA
Pollution -- Periodicals
Pollution -- Environmental aspects -- Periodicals
Environmental Pollution -- Periodicals
Pollution -- Périodiques
Pollution -- Aspect de l'environnement -- Périodiques
Pollution -- Effets physiologiques -- Périodiques
Pollution
Pollution -- Environmental aspects
Periodicals
Electronic journals
363.73 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02697491 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envpol.2020.115086 ↗
- Languages:
- English
- ISSNs:
- 0269-7491
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.539000
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