Estimating PM2.5 concentrations in Yangtze River Delta region of China using random forest model and the Top-of-Atmosphere reflectance

Journal of Environmental Management
Lijuan YangShaode Yu

Abstract

Previous studies that have used remote sensing data to estimate the PM2.5 concentrations mainly focused on the retrieval of aerosol optical depth (AOD) with moderate-to-low spatial resolution. However, the complex process of retrieving AOD from satellite Top-of-Atmosphere (TOA) reflectance always generates the missingness of AOD values due to the limitation of AOD retrieval algorithms. This study validated the possibility of using satellite TOA reflectance for estimating PM2.5 concentrations, rather than using conventional AOD products retrieved from remote sensing imageries. Given that the TOA-PM2.5 relationship cannot be accurately expressed by simple linear correlation, we developed a random forest model that integrated satellite TOA reflectance from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B product, meteorological fields and land-use variables to estimate the ground-level PM2.5 concentrations. The highly-polluted Yangtze River Delta (YRD) region of eastern China was employed as our study case. The results showed that our model performed well with a site-based and a time-based CV R2 of 0.92 and 0.88, respectively. The derived annual and seasonal distributions of PM2.5 concentrations exhibited high PM2.5 ...Continue Reading

References

Jul 1, 2007·Atmospheric Environment·Naresh KumarAndrew Foster
Sep 3, 2016·Journal of the Air & Waste Management Association·Meytar Sorek-HamerItai Kloog
May 24, 2017·Environmental Science & Technology·Xuefei HuYang Liu
Mar 15, 2018·Environmental Science & Technology·Cole BrokampPatrick Ryan

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Citations

Mar 20, 2021·The Science of the Total Environment·Tunde Ogbemi EtchieNedunchezhian Swaminathan

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