4.5 Article

Spatio-temporal variation and influence factors of PM2.5 concentrations in China from 1998 to 2014

Journal

ATMOSPHERIC POLLUTION RESEARCH
Volume 8, Issue 6, Pages 1151-1159

Publisher

TURKISH NATL COMMITTEE AIR POLLUTION RES & CONTROL-TUNCAP
DOI: 10.1016/j.apr.2017.05.005

Keywords

PM2.5 pollution; Spatio-temporal variation; Grey correlation analysis; Influence factors; China

Funding

  1. Guizhou Province Science and Technology fund [LKT[2012]07, 25]

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Based on the remote sensing retrieval of PM2.5 concentration data in the long-time series, both the linear regression and grey system correlation analysis methods were employed to analyze the spatial and temporal pattern, variation trend and the main influencing factors of PM2.5 concentration in China from 1998 to 2014. The results showed that only 16.21% -24.67% of the land area in China PM2.5 concentrations reached the annual average criterion value of 10 mg/m(3) set by the World Health Organization (WHO) in 1998-2014; the PM2.5 concentrations were greater than 95 mg/m(3) mainly in Xinjiang Taklimakan Desert, west of Tianjin and the central region of Hebei. PM2.5 concentration was less than 10 mg/m(3) mainly in Tibet, western Sichuan, northeastern Yunnan, Taiwan, northern Xinjiang, northern Inner Mongolia and northwest of Heilongjiang. High PM2.5 concentration in the northwest of China was mainly affected by sand and dust, while it was mainly caused by human activities in the eastern region. Except for Taiwan, low PM2.5 concentration areas were mainly located in the economically backward regions. The positive indicators in highly correlation with PM2.5 concentration include the average temperature, the proportion of primary and secondary industry to GDP, industrial consumption, the proportion of fulfilled amount of investment in real estate development to GDP, SO2 emissions and population density. The negative indicators in highly correlation with PM2.5 concentration include the average precipitation, the average wind velocity, the proportion of the tertiary industry to GDP, and the greening coverage rate of the built-up areas. (C) 2017 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.

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