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

Received: March 1, 2016
Revised: May 18, 2016
Accepted: June 26, 2016
Download Citation: ||  

Cite this article:
Bilal, M., Nichol, J.E. and Spak, S.N. (2017). A New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables. Aerosol Air Qual. Res. 17: 356-367.


  • 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.

Keywords: PM2.5; SARA AOD; MOD04 C006; Binning approach; Hong Kong

Share this article with your colleagues 


Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

77st percentile
Powered by
   SCImago Journal & Country Rank

2022 Impact Factor: 4.0
5-Year Impact Factor: 3.4

Call for Papers for the special issue on: "Carbonaceous Aerosols in the Atmosphere"

Aerosol and Air Quality Research partners with Publons

CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit
CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit

Aerosol and Air Quality Research (AAQR) is an independently-run non-profit journal that promotes submissions of high-quality research and strives to be one of the leading aerosol and air quality open-access journals in the world. We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.