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  • Original Article
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Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels

Journal of Exposure Science & Environmental Epidemiology volume 25, pages 457–466 (2015)Cite this article

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Abstract

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000–2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

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Acknowledgements

This work was partially supported by NASA Applied Sciences Program (grant no. NNX09AT52G, PI: Y Liu). In addition, this publication was made possible by USEPA grant R834799. Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA. Further, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication. The work of Chao Yu was supported by the China Scholarship Council (CSC) under the State Scholarship Fund. We thank Dr. Steven Platnick and Jerusha Barton for their technical support.

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Authors and Affiliations

  1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

    Chao Yu & Liangfu Chen

  2. Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA

    Chao Yu, Xueying Zhang & Yang Liu

  3. University of the Chinese Academy of Sciences, Beijing, China

    Chao Yu

  4. Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

    Larry Di Girolamo

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  1. Chao Yu
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  2. Larry Di Girolamo
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  3. Liangfu Chen
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  4. Xueying Zhang
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  5. Yang Liu
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Correspondence to Yang Liu.

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Supplementary Information accompanies the paper on the Journal of Exposure Science and Environmental Epidemiology website

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Yu, C., Di Girolamo, L., Chen, L. et al. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels. J Expo Sci Environ Epidemiol 25, 457–466 (2015). https://doi.org/10.1038/jes.2014.49

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