Atmospheric quality monitoring in the Qilian mountains nature reserve using the dark target-deep blue fusion algorithm

Aerosol optical depth (AOD) is an important physical parameter to characterize atmospheric pollution, and inversion of AOD is of great significance to monitor the atmospheric quality of Qilian Mountain National Nature Reserve. This study employs MODIS remote sensing data and utilizes the Dark Target algorithm, the Deep Blue algorithm, and a fusion of both to retrieve AOD. The findings are as follows: 1) The average AOD values retrieved by all three methods generally show an initial increase followed by a decrease. The fusion algorithm covers a larger area and achieves accuracy above 80%. 2) The Dark Target-Deep Blue fusion algorithm exhibits high correlation with the MCD19A2 product, with a correlation coefficient exceeding 70% and consistent trends in high and low AOD values. 3) Spatial distribution and factor analysis from 2006 to 2021 indicate a shift in AOD changes from a dispersed to a more clustered distribution, with a significant negative correlation between NDVI and AOD. Decrease in AOD across 2006 to 2021 reflects significant recent improvements in ecological restoration of mines within the reserve.