Investigation On The Spatial-temporal Distribution Of PM2.5 Based On Multiple Spatial-temporal Data

The PM2.5 air pollution can detriment human's health significantly.As issues of PM2.5 air pollution frequently occurred,it is nowadays a hot topic of social attention and academic interests.The spatial-temporal distribution of PM2.5 concentrations is one of the most popular academic focus.Knowledge of the present state and the spatial-temporal distribution of PM2.5 air pollution is important to understand the PM2.5 air pollution problem.The Geographic Information System(GIS),developed from the 1960 s,has shown a great power in spatial analysis,hence obtained broad applications as an interdisciplinary tool,especially in the environmental science.This paper investigated the spatial-temporal distribution of PM2.5 air pollution with GIS techiniques,analyzed the multi-source spatial-temporal data collected from various approach,obtained plenty of meaningful discovery.This paper investigated the spatial-temporal distribution of PM2.5 from four aspects,based on the GIS and the geospatial statistical methods.(1)Different spatialization methods for discrete data.The PM2.5 data obtained at monitoring stations and aerosol optical depth obtained by remote sensing were fused to yield more accurate PM2.5 spatial distribution,using cokriging algorithm.Meanwhile,the landuse data and nighttime data were also fused for the spatialization of census data,using multivariate linear regression model.(2)The distribution of population exposure to PM2.5 air pollution.After obtaining the spatialization of both PM2.5 air pollution and the population census data,these two types of spatialization results were combined to analyze the population-weighted PM2.5 air pollution distribution and the intensity of population exposure to PM2.5 air pollution.(3)Extraction of the heavily polluted area.The intensity of population exposure to PM2.5 air pollution were using the head/tail breaks classification method;the power-law distribution was used to test the distribution of PM2.5 air pollution heavily polluted area.(4)An application example of Beijing City using aforementioned methods was discussed.The distribution of PM2.5 air pollution of Beijing in 2014-2015 were discussed first and then utilized to evaluate the rationality of distribution of the PM2.5 monitoring stati ons in Beijing,corresponding optimization proposal was also suggested in this paper.The major significance of this study is to explore the distribution of PM2.5 air pollution using geospatial statistical tools systematically and to portray the present situation of PM2.5 air pollution with heavily PM2.5 air pollution area based on the concept of natural cities.And the results show that the distribution of PM2.5 air pollution have significant regional difference and seasonal difference,the distribution of the heavily PM2.5 air pollution area in China follows the power-law distribution well,but the boundaries of which differ from the boundaries of administrative cities;some even cross several administrative cities;multiple cities should work together to control the PM2.5 air pollution effectively.