With the deepening of industrialization and urbanization, PM2.5 pollution in Chengdu-Chongqing urban agglomeration has become increasingly serious, showing obvious regional and compound characteristics. Based on the daily average PM 2.5 data of air quality monitoring stations in Chengdu-Chongqing urban agglomeration 20 15-20 17, combined with multi-source data such as regional meteorology, remote sensing and statistical yearbook, this paper analyzes PM 2 (inverse distance interpolation method). The global and local spatial autocorrelation of ρ(PM2.5) is discussed by Moran's I index and LISA index, and the influence of natural, economic and social factors on ρ(PM2.5) is studied by spatial regression model. The results show that: ① there are obvious temporal and spatial differences in the concentration distribution of PM2.5 in Chengdu-Chongqing urban agglomeration. In time, 2065 438+05pm 2.5 was the most polluted. The annual average value of ρ(PM2.5) is 54.38 μ g ∕ m3, and the pollution situation of PM2.5 is reduced year by year in 20 16 and 20 17, and the annual average value of ρ(PM2.5) is 53.68 respectively. ...

Key words:

Spatial autocorrelation spatial regression model of spatial and temporal distribution of PM2.5 in Chengdu-Chongqing urban agglomeration

Classification number:

X5 13 (air pollution and its prevention)

Funding fund:

Chongqing Postgraduate Research Innovation Project, National Social Science Fund Major Project, Central University Project.

Online release date:

2019-12-19 (the first online date of Wanfang platform does not mean the publication time of the paper).