Spatiotemporal Variation Air Quality Index Characteristics in China's Major Cities During 2014-2020

2014-2020年中国主要城市空气质量指数时空变化特征

阅读:3

Abstract

The temporal and spatial variation characteristics of air quality index (AQI) in major cities in China were explored in this paper using statistical analysis, hot spot analysis, spatial autocorrelation, mean center, and geographic detector based on the daily AQI data from 2014 to 2020. The results show that ① the annual AQI average value dropped from 94 to 67 from 2014 to 2020. The percentage of cities with daily AQI excellent rates between 0.8 and 1 is significantly increasing, reaching 77% in 2020. ② AQI is highest and lowest in winter and summer, respectively. The trend of the monthly AQI average value is roughly in a U shape. Moreover, the AQI in January and December is high, and the AQI in August and September is low. ③ The spatial distribution of the annual AQI average in China's major cities shows agglomeration effects. The hot spots are distributed in North China and Xinjiang, and the cold spots are mainly distributed in the northeast and southern regions of China. ④ The average center of the annual AQI average of major cities in China was distributed in Sanmenxia City and Luoyang City, Henan Province, from 2014 to 2020 with a relatively small mean center migration range. ⑤ Based on the geographical detector model, the impact of total precipitation, 10-m u component of wind, 10-m v component of wind, surface pressure, and 2-m temperature on AQI is analyzed, and it is concluded that 2-m temperature has the greatest impact on AQI. Meanwhile, it is explored that GDP and population density have a certain impact on air quality. Therefore, analyzing the temporal and spatial characteristics of air quality provides some scientific basis for the regional collaborative governance of air pollution and the in-depth fight against pollution in China.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。