Literature DB >> 25929038

[Simulation and influencing factors of spatial distribution of PM2.5 concentrations in Chongqing].

Jian-Sheng Wu, Xing Liao, Jian Peng, Xiu-Lan Huang.   

Abstract

Land use regression model (LUR model) was used to simulate the spatial distribution of PM2.5 concentrations in Chongqing with the software of ArcGIS. This research was conducted with a total of 17 PM2.5 concentrations of monitoring points from 17 air quality monitoring stations recorded in the official website of Chongqing Environmental Protection Bureau. Among them, 16 were chosen as the dependent variables, and the last one was chosen for land use regression model validation test. At each site location, we constructed circular buffers with ArcGIS and captured information on roads, population, land use and DEM. Based on the buffer information, 56 potential geographic predictors were built. Finally 3 variables: cropland area within 500 m of the air quality monitoring sites, the site locations' DEM and primary road length within 1 000 m of the 56 predictors were left for predicting 84% of the variation of PM2.5 concentrations and the Pearson coefficients between the 3 variables and PM2.5 concentrations were 0.695, - 0.599 and 0.394, respectively. The validation test result showed that the spatial distribution map of PM2.5 predicted extremely well with an error rate of only 0.027. And the return map results showed: (1 ) PM2.5 concentrations were high in the center of the main city; (2) PM2.5 concentrations were high along the road and (3) the distribution was closely correlated to the DEM of sampling locations.

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Year:  2015        PMID: 25929038

Source DB:  PubMed          Journal:  Huan Jing Ke Xue        ISSN: 0250-3301


  2 in total

1.  Assessment of the spatio-temporal pattern of PM2.5 and its driving factors using a land use regression model in Beijing, China.

Authors:  Lingqiang Kong; Guangjin Tian
Journal:  Environ Monit Assess       Date:  2020-01-06       Impact factor: 2.513

2.  Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing-Tianjin-Hebei Region, China, from 2013 to 2018.

Authors:  Lili Wang; Qiulin Xiong; Gaofeng Wu; Atul Gautam; Jianfang Jiang; Shuang Liu; Wenji Zhao; Hongliang Guan
Journal:  Int J Environ Res Public Health       Date:  2019-11-04       Impact factor: 3.390

  2 in total

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