Estimation of atmospheric particulate matter based on MODIS haze optimized transformation

Abstract

This research is an attempt to simulate the relationship between haze optimized transformation (HOT) and aerosol optical thickness (AOT), and explore the influence of typical ground covers on this relationship using the 6S atmospheric radiative transfer model for the Chinese city of Nanjing. The HOT data were derived from moderate resolution imaging spectroradiometer (MODIS) satellite images recorded in the winter and spring seasons of December 2007–May 2009. They were analysed in conjunction with ground observed atmospheric particulate matter (PM) data so as to establish their quantitative relationship. Such a relationship may open a new avenue for remotely estimating atmospheric PM based on HOT. The results obtained indicate that HOT is related positively to AOT. This relationship is most accurately depicted by a second-order polynomial equation. Although built-up areas, waterbodies, and vegetation have differing HOT values, all of them bear a close and consistent correlation with AOT. HOT of built-up areas, waterbodies, and vegetative surfaces derived from MODIS images is also positively correlated with PM₁₀ (PM with diameter <10 μm), which was measured near the surface. The second-order polynomial equation has a coefficient of determination (R²) value of 0.375 (built-up), 0.344 (water), and 0.362 (vegetation) and a root mean squared error (RMSE) of 0.0258, 0.0264, and 0.0261, respectively. The closeness in R² value and RMSE for different ground covers suggests that correlation is marginally affected by the ground cover. It is thus concluded that HOT can be used as a reliable alternative for estimating PM₁₀ from MODIS data.

Acknowledgements

We thank the two anonymous reviewers for their helpful comments. The data used in this study were acquired as part of the NASA's Earth Science Enterprise. The algorithms were developed by the MODIS Science Teams. The data were processed by the MODIS Adaptive Processing System (MODAPS) and Goddard Distributed Active Archive Center (DAAC), and are archived and distributed by the Goddard DAAC. This research was funded by the National Natural Science Foundation of China (No. 41271382), the National Science and Technology Support Plan of China (No. 2008BAC34B07), the Key Fundamental Research Projects of Natural Science in Universities affiliated with the Jiangsu Province (No. 08KJA170001), the ‘211’ Key Discipline Construction Project, the Key Short-term Projects of Inviting Overseas Experts to the Nanjing Normal University, and a project funded by the Priority Academic Programme Development of Jiangsu Higher Education Institutions, China.