Abstract
Daily air quality index (AQI) of 161 Chinese cities obtained from the Ministry of Environmental Protection of China in 2015 is conducted. In this study, to better explore spatial distribution and regional characteristic of AQI, global and local spatial autocorrelation is utilized. Pearson’s correlation is introduced to determine the influence of single urban indicator on AQI value. Meanwhile, multiple linear stepwise regression is chosen to estimate quantitatively the most influential urban indicators on AQI. The spatial autocorrelation analysis indicates that the AQI value of Chinese 161 cities shows a spatial dependency. Higher AQI is mainly located in north and northwest regions, whereas low AQI is concentrated in the south and the Qinghai-Tibet regions. The low AQI and high AQI values in China both exhibit relative immobility through seasonal variation. The influence degree of three adverse urban driving factors on AQI value is ranked from high to low: coal consumption of manufacturing > building area > coal consumption of the power industry. It is worth noting that the risk of exposed population to poor quality is greater in the northern region than in other regions. The results of the study provide a reference for the formulation of urban policy and improvement of air quality in China.
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Acknowledgements
We would like to express our gratitude to Xiaojuan Li from Nanjing University for support and assistance during data collection. We thank Ran Xu from the National Geographic Information Bureau of Surveying and Mapping for data arrangement. This research was supported by the National Key Basic Research Program of China (973 Program) (No. 2014CB238906) and the National Natural Science Foundation of China (Grant Nos. 41472322, 41172310).
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Pu, H., Luo, K., Wang, P. et al. Spatial variation of air quality index and urban driving factors linkages: evidence from Chinese cities. Environ Sci Pollut Res 24, 4457–4468 (2017). https://doi.org/10.1007/s11356-016-8181-0
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DOI: https://doi.org/10.1007/s11356-016-8181-0