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Int. J. Environ. Res. Public Health 2018, 15(1), 114;

Spatiotemporal Patterns of Ground Monitored PM2.5 Concentrations in China in Recent Years

School of Statistics, Shanxi University of Finance & Economics, 696 Wucheng Road, Taiyuan 030006, China
LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road 11A, Beijing 10010, China
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 9 January 2018 / Accepted: 10 January 2018 / Published: 11 January 2018
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This paper firstly explores the space-time evolution of city-level PM 2.5 concentrations showed a very significant seasonal cycle type fluctuation during the period between 13 May 2014 and 30 May 2017. The period from October to April following each year was a heavy pollution period, whereas the phase from April to October of the current year was part of a light pollution period. The average monthly PM 2.5 concentrations in mainland China based on ground monitoring, employing a descriptive statistics method and a Bayesian spatiotemporal hierarchy model. Daily and weekly average PM 2.5 concentrations in 338 cities in mainland China presented no significant spatial difference during the severe pollution period but a large spatial difference during light pollution periods. The severe PM 2.5 pollution areas were mainly distributed in the Beijing-Tianjin-Hebei urban agglomeration in the North China Plain during the beginning of each autumn-winter season (September), spreading to the Northeast Plains after October, then later continuing to spread to other cities in mainland China, eventually covering most cities. PM 2.5 pollution in China appeared to be a cyclic characteristic of first spreading and then centralizing in the space in two spring-summer seasons, and showed an obvious process of first diffusing then transferring to shrinkage alternation during the spring-summer season of 2015, but showed no obvious diffusion during the spring-summer season of 2016, maintaining a stable spatial structure after the shrinkage in June, as well as being more concentrated. The heavily polluted areas are continuously and steadily concentrated in East China, Central China and Xinjiang Province. View Full-Text
Keywords: PM2.5 pollution; Bayeasian statistical model; spatiotemporal patterns PM2.5 pollution; Bayeasian statistical model; spatiotemporal patterns

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Li, J.; Han, X.; Li, X.; Yang, J.; Li, X. Spatiotemporal Patterns of Ground Monitored PM2.5 Concentrations in China in Recent Years. Int. J. Environ. Res. Public Health 2018, 15, 114.

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