PM2.5 refers to a kind of particulate matter whose diameter is equal to or less than 2.5 micrometers in the atmosphere. Due to its characteristics of small particle size, easy-adsorption for toxic substances, long-time suspension in atmosphere and far-distance transportation, PM2.5 can enter the human lung and blood through breath, then cause respiratory diseases and central nervous system diseases. Therefore, people are paying more and more attention to PM2.5. This research is dedicated to identifying the main factors and the significant geographical elements of PM2.5 pollution based on the tools of ArcGIS, SPSS and Canoco, where ArcGIS is used to perform spatial interpolation and extract information while SPSS and Canoco have been implemented to conduct correlation analysis. The results are as follows: (a) The generally distribution of Xian's PM2.5 is the eastern part is higher than the western part; (b) PM2.5 is positively correlated with DEM, RDLS (relief degree of land surface), Aspect. In the process of increasing the buffer radius from 1 kilometer to 5 kilometers, it maintains a strong and significant positive correlation between PM2.5 and each geographical element; and (c) RDLS is the primary geographic factor and has significant influence on the diffusion and distribution of PM2.5 under different buffer radius from 1 kilometer to 5 kilometers.
[1]
Roger Funk,et al.
Efficiency of Big Spring Number Eight (BSNE) and Modified Wilson and Cook (MWAC) samplers to collect PM10, PM2.5 and PM1
,
2016
.
[2]
Limin Jiao,et al.
Spatial and temporal variability of PM2.5 concentration in China
,
2016,
Wuhan University Journal of Natural Sciences.
[3]
Wang Zhen-b,et al.
Spatial-temporal characteristics of the PM_(2.5) in China in 2014
,
2015
.
[4]
Cole Brokamp,et al.
Does the elemental composition of indoor and outdoor PM2.5 accurately represent the elemental composition of personal PM2.5
,
2015
.
[5]
Andrea Pozzer,et al.
Implementing the US air quality standard for PM2.5 worldwide can prevent millions of premature deaths per year
,
2016,
Environmental Health.
[6]
Li Du,et al.
Spatial distribution, seasonal variation and regionalization of PM2.5 concentrations in China
,
2015,
Science China Chemistry.
[7]
Zhanshan Wang,et al.
Spatial-temporal characteristics of PM_(2.5) in Beijing in 2013
,
2015
.