ORIGINAL RESEARCH
Temporal-Spatial Variations of Concentrations
of PM10 and PM2.5 in Ambient Air
Liu Jie1,2, Hou Kepeng1,2, Wang Xiaodong1,2, Yang Peng3
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1Faculty of Land and Resources Engineering, Kunming University of Science and Technology, Kunming, China
2Postdoctorate Station of Mining Industry Engineering, Kunming University of Science and Technology, Kunming, China
3Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China
Submission date: 2016-04-03
Final revision date: 2016-06-01
Acceptance date: 2016-06-11
Publication date: 2016-11-24
Pol. J. Environ. Stud. 2016;25(6):2435-2444
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ABSTRACT
Since the space points’ average concentrations of PM obtained by air quality automatic monitoring
sites were less representative of PM pollution levels in the Beijing area, it was necessary to improve
the spatial resolution of PM concentrations on the basis of continuous time series. In order to solve the
problem, we used one-hour average concentrations of PM from March 2013 to February 2014 obtained by
monitoring sites. Firstly, concentration variations with time scale of PM2.5 and PM10 were researched to find
out their correlations and pollution grades in continuous time series. Secondly, in order to realize the spatial
distribution characteristics from points to surfaces, MATLAB spatial interpolation tools were used to predict
the average concentrations of PM on any latitude-longitude grid in regional surface, then spatial interpolation
on longitudes and latitudes, and the PM concentrations were researched by radial basis functions based on
biharmonic green function. Finally, by constructing decision functions and sample sets, the interpolation
results were tested by k-fold cross validation to analyze the error distribution between monitoring values
and fitted values, and then they were compared with Kriging interpolation results realized by DACE tool in
MATLAB. The results showed there were periodical variations and significant correlations on the average
concentrations of PM from March 2013 to February 2014 in Beijing. The PM pollutions also had obvious
regional characteristics. Interpolation results of radial basis function interpolation on PM concentrations
could represent their spatial distribution in Beijing, since the method had a certain precision to improve
utilization of spatial information. Moreover, the analysis showed that the main factors of PM pollution
were dust storms and strong winds in spring and autumn, rainfall and the warm wet climate in summer,
and cold fronts and snowfall in winter. Pollution characteristics in the Beijing area were higher in the south
and lower in the north, and the pollution sources might be regional transport as well as local anthropogenic
sources. The conjoint analysis on time series and spatial interpolation of concentrations had significance for
further research of time-space relationship of PM, and it also provided a method for understanding regional
pollution characteristics.