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A New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables

Category: PM2.5, Atmospheric Aerosols and Urban Air Quality

Volume: 17 | Issue: 2 | Pages: 356-367
DOI: 10.4209/aaqr.2016.03.0097
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Muhammad Bilal1, Janet E. Nichol 1, Scott N. Spak2

  • 1 Department of Land Surveying and Geo-Informatics, the Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
  • 2 Center for Global and Regional Environmental Research, University of Iowa, Iowa City, USA


A new binning approach for prediction of PM2.5 at 500 m resolution is introduced.
Binned weather conditions improve the prediction of PM2.5.
Surface low pressure is the most important meteorological predictor in Hong Kong.
The SARA binning model is much more efficient and robust than previous models.
The SARA binning model can accurately predict PM2.5 during high pollution events.


Fine particulate matter (PM2.5) has recently gained attention worldwide as being responsible for severe respiratory and cardiovascular diseases, but point based ground monitoring stations are inadequate for understanding the spatial distribution of PM2.5 over complex urban surfaces. In this study, a new approach is introduced for prediction of PM2.5 which uses satellite aerosol optical depth (AOD) and binning of meteorological variables. AOD from the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) aerosol products, MOD04_3k Dark-Target (DT) at 3 km, MOD04 DT at 10 km, and MOD04 Deep-Blue (DB) at 10 km spatial resolution, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m resolution were obtained for Hong Kong and the industrialized Pearl River Delta (PRD) region. The SARA AOD at 500 m alone achieved a higher correlation (R = 0.72) with PM2.5 concentrations than the MODIS C6 DT AOD at 3 km (R = 0.60), the DT AOD at 10 km (R = 0.61), and the DB AOD at 10 km (R = 0.51). The SARA binning model ([PM2.5] = 110.5 [AOD] + 12.56) was developed using SARA AOD and binning of surface pressure (996–1010 hPa). This model exhibits good correlation, accurate slope, low intercept, low errors, and accurately represents the spatial distribution of PM2.5 at 500 m resolution over urban areas. Overall, the prediction power of the SARA binning model is much better than for previous models reported for Hong Kong and East Asia, and indicates the potential value of applying meteorologically-specific empirical models and incorporating boundary layer height in operational PM2.5 forecasting from satellite AOD retrievals.


PM2.5 SARA AOD MOD04 C006 Binning approach Hong Kong

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