Impacts of snow and cloud covers on satellite-derived PM_2.5 levels.

ABSTRACT: Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM_2.5) levels, whereas snow/cloud covers often lead to a large proportion of non-random missing AOD values. As a result, the fully covered and unbiased PM_2.5 estimates will be hard to generate. Among the current approaches to deal with the data gap issue, few have considered the cloud-AOD relationship and none of them have considered the snow-AOD relationship. This study examined the impacts of snow and cloud covers on AOD and PM_2.5 and made full- coverage PM_2.5 predictions by considering these impacts. To estimate missing AOD values, daily gap-filling models with snow/cloud fractions and meteorological covariates were developed using the random fores

SUBMITTER: Bi J 

PROVIDER: S-EPMC6662717 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature