Detection of haze and its intensity based on visibility and relative humidity estimated from MODIS data

ABSTRACT

Over recent years, air pollution has become a serious environmental problem with frequent occurrence of hazy days in many Chinese cities. In this study, a satellite-based method was developed to detect haze and its intensity for the Chinese city of Nanjing. This detection was based on the joint consideration of two indices, visibility, and relative humidity. They were determined from the Moderate Resolution Imaging Spectroradiometer-derived aerosol optical thickness, surface temperature, and precipitable water vapour data. Evaluated against the in situ measured results, haze and its intensity were found to be detected at a maximum accuracy of 81.7% and 60%, respectively. Of the two indices, visibility plays a more important role than relative humidity in affecting the detection accuracy. It is concluded that it is feasible to detect haze and its intensity from satellite data.

Acknowledgements

The data used in this study were acquired as part of 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. We thank the two anonymous reviewers for their helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was funded by the National 973 Project: [Gran Number 2014CB953802], the National Natural Science Foundation of China: [Grant Number 41671428], the ‘135’ Key Planning Cultivation Direction Project of Institute of Remote Sensing and Digital Earth: [Grant Number Y3ZZ15101A], the Talents Program of the Chinese Academy of Sciences (CAS) ‘Drought and derivative disaster remote sensing and assessment under global change’, CEODE-CAS Funding ‘Multi-source remote sensing aerosolcloud interactions and impacts on precipitation’, and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.