Spatial and temporal variability of PM2.5 concentration in China
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- 作者：Gang Xu ; Limin Jiao ; Suli Zhao ; Jiaqi Cheng
- 刊名：Wuhan University Journal of Natural Sciences
- 出版年：2016
- 出版时间：August 2016
- 年：2016
- 卷：21
- 期：4
- 页码：358-368
- 全文大小：844 KB
- 刊物类别：Mathematics and Statistics
- 刊物主题：Mathematics
Computer Science, general
Physics
Life Sciences
Chinese Library of Science - 出版者：Wuhan University, co-published with Springer
- ISSN：1993-4998
- 卷排序：21
文摘
PM2.5 has become an increasing public concern recently because of its visibility reduction and severe health risks. For the whole year of 2013, hourly PM2.5 data of 496 monitoring sites scattered in 74 cities of China are collected to analyze temporal and spatial variability of PM2.5 concentration. Different temporal scales (seasonal variation, monthly variation and daily variation) and spatial scales (urban versus rural, typical areas and national scale) are discussed. Results show that PM2.5 concentration changes significantly in both long-term and short-term scales. An apparent bimodal pattern exists in daily variation of PM2.5 concentration and the daytime peak appears around 10:00 am while the lowest concentration appears around 16:00 pm. Spatial autocorrelation analysis and Ordinary Kriging are used to characterize spatial variability. Moran’s I of PM2.5 concentration in three typical regions, the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region, is 0.906, 0.693, 0.746, respectively, which indicates that PM2.5 is strong spatial correlated. Spatial distribution of annual PM2.5 concentration simulated by Ordinary Kriging shows that 7.94 million km2 (83%) areas fail in meeting the requirement of China’s National Ambient Air Quality Standards Level-2 (35 µg/m3) and there are at least three concentrated highly polluted areas across the country.Keywordsair pollutionPM2.5spatial-temporal variabilityspatial autocorrelation