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Spatial and Seasonal Variations of the Air Pollution Index and a Driving Factors Analysis in China
Author(s) -
Jiang Hongyue,
Li Hairong,
Yang Linsheng,
Li Yonghua,
Wang Wuyi,
Yan Yachen
Publication year - 2014
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2014.06.0254
Subject(s) - environmental science , air quality index , urban agglomeration , air pollution , air pollution index , china , pollution , economies of agglomeration , geography , physical geography , environmental protection , meteorology , ecology , archaeology , economic growth , economics , biology
In this study, the daily air pollution index (API) of 110 cities based on ground monitoring was conducted on the 2011 data set from the Ministry of Environmental Protection of China. The pollutant concentrations, seasonal variations, and spatial autocorrelations were evaluated. The results show that the major principal pollutants in China are inhalable particles. In addition, the total number of clean days (API ≤ 50) is apparently smaller in the northern cities than in the southern cities as a result of fuel utilization and large‐scale organized central heating. Seasonally, air pollution is most severe in winter and is caused by low‐frequency rainfall, strong northwest winds, dry climate, and high energy consumption; this is followed by spring, which is a season of frequent sandstorms. According to spatial autocorrelation analysis, clusters with high API value agglomeration (High–High clusters) are mainly concentrated in the middle and northern parts of China, whereas clusters with low API agglomeration (Low–Low clusters) are principally concentrated in the southern parts of China due to a favorable climate and abundant rainfall. Meteorological data, including wind speed and temperature, have great impacts on API. The air quality effects of industrial structure, energy use, urban greening, and traffic congestion were also analyzed. With the ecological function of purifying the air, industries that use natural resources and urban greening could help to reduce API, whereas secondary industry and gas use, which have a positive coefficient, increase the API value. The risk of exposure to poor air quality is largest in the winter, smallest in the summer, and remains relatively unchanged in the spring and autumn.