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Modeling Urban PM2.5 Concentration by Combining Regression Models and Spectral Unmixing Analysis in a Region of East China

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Abstract

Understanding the spatial distribution of PM2.5 concentration and its contributing environmental variables is critical to develop strategies of addressing adverse effects of the particulate pollution. In this study, a range of meteorological and land use factors were incorporated into a linear regression (LR) model and a logistic model-based regression (LMR) model to simulate the annual and winter PM2.5 concentrations. The vegetation cover, derived from a linear spectral unmixing analysis (LSUA), and the normalized difference built-up index (NDBI), were found to improve the goodness of fit of the models. The study shows that (1) both the LR and the LMR agree on the predicted spatial patterns of PM2.5 concentration and (2) the goodness of fit is higher for the models established based on the annual PM2.5 concentration than that based on the winter PM2.5. The modeling results show that higher PM2.5 concentration coincided with the major urban area for the annual average but focused on the suburban and rural areas for the winter. The methods introduced in this study can potentially be applied to similar regions in other developing countries.

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Acknowledgements

We appreciate the constructive comments from anonymous reviewers that contribute to the improvement of this paper. This study was supported by the research project “Remote sensing technology for studying urban haze pollution” awarded by the Zhejiang Province Science and Technology Public Welfare Project (2013C33027) and Zhejiang Province Science and Technology Project (LY12D01003), Zhejiang A & F University.

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Authors and Affiliations

  1. Department of Environmental Resources, Zhejiang A & F University, Lin-An, Zhejiang Province, China

    Jiae Xiang, Lihua Xu, Maozhen Zhang & Mengping Tang

  2. Department of Geography and Environmental Resources, Southern Illinois University-Carbondale, Carbondale, IL, USA

    Ruopu Li, Guangxing Wang, Guangping Qie & Qing Wang

Authors
  1. Jiae Xiang
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  2. Ruopu Li
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  3. Guangxing Wang
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  4. Guangping Qie
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  5. Qing Wang
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  6. Lihua Xu
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  7. Maozhen Zhang
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  8. Mengping Tang
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Correspondence to Ruopu Li or Lihua Xu.

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Xiang, J., Li, R., Wang, G. et al. Modeling Urban PM2.5 Concentration by Combining Regression Models and Spectral Unmixing Analysis in a Region of East China. Water Air Soil Pollut 228, 250 (2017). https://doi.org/10.1007/s11270-017-3421-6

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  • DOI: https://doi.org/10.1007/s11270-017-3421-6

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