Assessing and discussing the efficacy in high-resolution aerosol optical depth using HJ-1 data

Atmospheric aerosol, which is an important parameter required for climate change studies, local air quality monitoring, global aerosol transport modeling, atmospheric correction and global aerosol characterization, decreases seriously regional air quality and may have a negative impact on public human health. Because aerosols had complex sources and the short lifetime, it is difficult to study the particles directly. Remote sensing satellites provided the best ways to characterize spatial field and regional characterization of aerosol particles. The study presents a prototype method for extracting high resolution aerosol optical depth (AOD) in eastern China using remote sensing satellites data. An AOD derivation experiment by HJ-1 CCD data was carried out in Zhejiang province, China, in April 22th, 2010. NASA´s aerosol retrieval algorithm was introduced in the study which was developed Robert C. Levy and Lorraine A. Remer based on the Dark Dense Vegetation(DDV) algorithm of Kaufman. The Look-up Table was computed from the 6S RT model. The results had been validated by MODIS atmospheric aerosols production suggesting that the HJ-1 data works well for atmosphere particles detection under complex land characteristic of eastern China, especially in Zhejiang province. Such investigations are expanding satellites for AOD detection, as well as exploring the potential capability for air quality monitoring for HJ-1 data. A very large potential for HJ-1 as an efficient satellite data to retrieve aerosol products was also demonstrated in the study.