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On-line Access: 2010-11-08

Received: 2010-03-10

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Journal of Zhejiang University SCIENCE A 2010 Vol.11 No.11 P.857-867

10.1631/jzus.A1000092


Application of land use regression for estimating concentrations of major outdoor air pollutants in Jinan, China


Author(s):  Li Chen, Shi-yong Du, Zhi-peng Bai, Shao-fei Kong, Yan You, Bin Han, Dao-wen Han, Zhi-yong Li

Affiliation(s):  College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution and Control, Tianjin 300071, China, College of Urban and Environmental Science, Tianjin Normal University, Tianjin 300387, China, Jinan Institute of Environmental Sciences, Jinan 250014, China

Corresponding email(s):   amychenli1981@126.com, zbai@nankai.edu.cn

Key Words:  Land use regression (LUR), Air pollution, Background concentration, Geographic information system (GIS)


Li Chen, Shi-yong Du, Zhi-peng Bai, Shao-fei Kong, Yan You, Bin Han, Dao-wen Han, Zhi-yong Li. Application of land use regression for estimating concentrations of major outdoor air pollutants in Jinan, China[J]. Journal of Zhejiang University Science A, 2010, 11(11): 857-867.

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journal="Journal of Zhejiang University Science A",
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pages="857-867",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1000092"
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%T Application of land use regression for estimating concentrations of major outdoor air pollutants in Jinan, China
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%A Shi-yong Du
%A Zhi-peng Bai
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%A Yan You
%A Bin Han
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%I Zhejiang University Press & Springer
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A1 - Shi-yong Du
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A1 - Yan You
A1 - Bin Han
A1 - Dao-wen Han
A1 - Zhi-yong Li
J0 - Journal of Zhejiang University Science A
VL - 11
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SP - 857
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DOI - 10.1631/jzus.A1000092


Abstract: 
SO2, NO2, and PM10 are the major outdoor air pollutants in China, and most of the cities in China have regulatory monitoring sites for these three air pollutants. In this study, we developed a land use regression (LUR) model using regulatory monitoring data to predict the spatial distribution of air pollutant concentrations in Jinan, China. Traffic, land use and census data, and meteorological and physical conditions were included as candidate independent variables, and were tabulated for buffers of varying radii. SO2, NO2, and PM10 concentrations were most highly correlated with the area of industrial land within a buffer of 0.5 km (R2=0.34), the distance from an expressway (R2=0.45), and the area of residential land within a buffer of 1.5 km (R2=0.25), respectively. Three multiple linear regression (MLR) equations were established based on the most significant variables (p<0.05) for SO2, NO2, and PM10, and R2 values obtained were 0.617, 0.640, and 0.600, respectively. An LUR model can be applied to an area with complex terrain. The buffer radii of independent variables for SO2, NO2, and PM10 were chosen to be 0.5, 2, and 1.5 km, respectively based on univariate models. Intercepts of MLR equations can reflect the background concentrations in a certain area, but in this study the intercept values seemed to be higher than background concentrations. Most of the cities in China have a network of regulatory monitoring sites. However, the number of sites has been limited by the level of financial support available. The results of this study could be helpful in promoting the application of LUR models for monitoring pollutants in Chinese cities.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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