Spatiotemporal characterization and mapping of PM2.5 concentrations in southern Jiangsu Province, China

Spatiotemporal characterization and mapping of PM2.5 concentrations in southern Jiangsu Province,... As a result of rapid industrialization and urbanization, China is experiencing severe air pollution problems. Understanding the spatiotemporal variation and trends of air pollution is a key element of an improved understanding of the underlying physical mechanisms and the implementation of the most effective risk assessment and environmental policy in the region. The motivation behind the present work is that the study region of southern Jiangsu province of China is one of the most populated and developed regions in China. The daily concentrations of particulate matter with particle diameter smaller than 2.5 μm (PM2.5) in southern Jiangsu province obtained during the year 2014 were used to derive the variogram model that provided a quantitative characterization of the spatiotemporal (ST) variation of PM2.5 concentrations in the study region. A spatiotemporal ordinary kriging (STOK) technique was subsequently employed to generate informative maps of the ST pollutant distribution in southern Jiangsu province. The results generated by STOK showed that during 2014 about 29.3% of the area was PM2.5 polluted (at various severity levels, according to the criteria established by the Chinese government), and that the number of days characterized as polluted varied from 59 to 164 at different parts of the study region. Nanjing, the capital of Jiangsu province, was the place with the highest PM2.5 pollution (including 3 days of serious pollution). The PM2.5 pollution exhibited a decreasing spatial trend from the western to the eastern part of southern Jiangsu. A similar temporal PM2.5 pattern was found from the western to the eastern part of southern Jiangsu, which was characterized by 4 peaks and 3 troughs linked to different meteorological conditions and human factors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Pollution Elsevier

Spatiotemporal characterization and mapping of PM2.5 concentrations in southern Jiangsu Province, China

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0269-7491
D.O.I.
10.1016/j.envpol.2017.11.077
Publisher site
See Article on Publisher Site

Abstract

As a result of rapid industrialization and urbanization, China is experiencing severe air pollution problems. Understanding the spatiotemporal variation and trends of air pollution is a key element of an improved understanding of the underlying physical mechanisms and the implementation of the most effective risk assessment and environmental policy in the region. The motivation behind the present work is that the study region of southern Jiangsu province of China is one of the most populated and developed regions in China. The daily concentrations of particulate matter with particle diameter smaller than 2.5 μm (PM2.5) in southern Jiangsu province obtained during the year 2014 were used to derive the variogram model that provided a quantitative characterization of the spatiotemporal (ST) variation of PM2.5 concentrations in the study region. A spatiotemporal ordinary kriging (STOK) technique was subsequently employed to generate informative maps of the ST pollutant distribution in southern Jiangsu province. The results generated by STOK showed that during 2014 about 29.3% of the area was PM2.5 polluted (at various severity levels, according to the criteria established by the Chinese government), and that the number of days characterized as polluted varied from 59 to 164 at different parts of the study region. Nanjing, the capital of Jiangsu province, was the place with the highest PM2.5 pollution (including 3 days of serious pollution). The PM2.5 pollution exhibited a decreasing spatial trend from the western to the eastern part of southern Jiangsu. A similar temporal PM2.5 pattern was found from the western to the eastern part of southern Jiangsu, which was characterized by 4 peaks and 3 troughs linked to different meteorological conditions and human factors.

Journal

Environmental PollutionElsevier

Published: Mar 1, 2018

References

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