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Open AccessArticle

Spatiotemporal Trend Analysis of PM2.5 Concentration in China, 1999–2016

1
Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
National & Local Joint Engineering Lab for Big Data Analysis and Computing Technology, Beijing 100190, China
4
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(8), 461; https://doi.org/10.3390/atmos10080461
Received: 12 July 2019 / Revised: 1 August 2019 / Accepted: 8 August 2019 / Published: 12 August 2019
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Abstract

China is experiencing severe PM2.5 (fine particles with a diameter of 2.5 μg or smaller) pollution problem. Little is known, however, about how the increasing concentration trend is spatially distributed, nor whether there are some areas that experience a stable or decreasing concentration trend. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here, we present a pixel-based linear trend analysis of annual PM2.5 concentration variation in China during the period 1999–2016, and our results provide guidance about where to prioritize management efforts and affirm the importance of controlling coal energy consumption. We show that 87.9% of the whole China area had an increasing trend. The drastic increasing trends of PM2.5 concentration during the last 18 years in the Beijing–Tianjin–Hebei region, Shandong province, and the Three Northeastern Provinces are discussed. Furthermore, by exploring regional PM2.5 pollution, we find that Tarim Basin endures a high PM2.5 concentration, and this should have some relationship with oil exploration. The relationship between PM2.5 pollution and energy consumption is also discussed. Not only energy structure reconstruction should be repeatedly emphasized, the amount of coal burned should be strictly controlled. View Full-Text
Keywords: PM2.5 pollution; spatiotemporal trend analysis; energy consumption; pixel-based linear trend analysis PM2.5 pollution; spatiotemporal trend analysis; energy consumption; pixel-based linear trend analysis
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Zhao, J.; Wang, X.; Song, H.; Du, Y.; Cui, W.; Zhou, Y. Spatiotemporal Trend Analysis of PM2.5 Concentration in China, 1999–2016. Atmosphere 2019, 10, 461.

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