关键词: AQI指数, 空间插值法, 空间自相关分析, 核密度估计, 中国

Abstract: Based on the daily air quality index (AQI) data of 367 cities published by the Chinese Ministry of Environmental Protection from 2014 to 2016, a series of spatial data statistical models such as spatial autocorrelation model, kernel density estimation model and spatial interpolation method are comprehensively used. The results show that: ①AQI of cities in China decreased from 2014 to 2016, and the number of cities with air pollution decreased, indicating that the air quality of cities had been improved. The seasonal mean AQI of China is as follows: winter, spring, autumn, summer. The pattern of spatial heterogeneity is not obvious in summer and autumn, while the spatial pattern is obvious in spring and winter, showing a special seasonal distribution pattern of high level in the north and low level in the south, and high level in inland and low level along the coastal. ②The spatial distribution of AQI spatial distribution in China′s cities shows a continuous enhanced spatial agglomeration situation, forming a moderate polluted area with the core of the three provinces of Hebei, Shandong and Henan provinces and spreading to the middle north of Hubei province, and the medium pollution area with Urumqi and Artux city as the core. The Southern China area with the core of the Pearl River Delta city group is the stable area of better air quality. ③From the kernel density estimation map, it can be found that the spatial distribution pattern of China′s urban AQI is characterized by six main density core regions and three secondary core density regions, while the basic pattern has changed significantly in some areas in 2014-2016. This paper comprehensively analyzes the spatial distribution characteristics of urban air quality based on different time scales, aiming to provide scientific basis for developing relevant air quality control policies in various cities of China.

Key words: AQI index, spatial interpolation, spatial autocorrelation, kernel density estimation, China