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Journal of Zhejiang University-SCIENCE A

, Volume 11, Issue 11, pp 857–867 | Cite as

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

  • Chen Li
  • Shi-yong Du
  • Zhi-peng Bai
  • Kong Shao-fei
  • You Yan
  • Han Bin
  • Han Dao-wen
  • Zhi-yong Li
Article

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.

Key words

Land use regression (LUR) Air pollution Background concentration Geographic information system (GIS) 

CLC number

X51 

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Copyright information

© Zhejiang University and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Chen Li
    • 1
    • 2
    • 3
  • Shi-yong Du
    • 4
  • Zhi-peng Bai
    • 1
    • 2
  • Kong Shao-fei
    • 1
    • 2
  • You Yan
    • 1
    • 2
  • Han Bin
    • 1
    • 2
  • Han Dao-wen
    • 4
  • Zhi-yong Li
    • 1
    • 2
  1. 1.College of Environmental Science and EngineeringNankai UniversityTianjinChina
  2. 2.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution and ControlTianjinChina
  3. 3.College of Urban and Environmental ScienceTianjin Normal UniversityTianjinChina
  4. 4.Jinan Institute of Environmental SciencesJinanChina

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