In this study, an approach in determining effective mixing weight of soot aggregates from dust–soot aerosols is proposed to improve the accuracy of retrieving properties of polluted dusts by means of satellite remote sensing. Based on a pre-computed database containing several variables (such as wavelength, refractive index, soot mixing weight, surface reflectivity, observation geometries and aerosol optical depth (AOD)), the fan-shaped look-up tables can be drawn out accordingly for determining the mixing weights, AOD and single scattering albedo (SSA) of polluted dusts simultaneously with auxiliary regional dust properties and surface reflectivity. To validate the performance of the approach in this study, 6 cases study of polluted dusts (dust–soot aerosols) in Lower Egypt and Israel were examined with the ground-based measurements through AErosol RObotic NETwork (AERONET). The results show that the mean absolute differences could be reduced from 32.95% to 6.56% in AOD and from 2.67% to 0.83% in SSA retrievals for MODIS aerosol products when referenced to AERONET measurements, demonstrating the soundness of the proposed approach under different levels of dust loading, mixing weight and surface reflectivity. Furthermore, the developed algorithm is capable of providing the spatial distribution of the mixing weights and removing the requirement to assume that the dust plume properties are uniform. The case study further shows the spatially variant dust–soot mixing weight would improve the retrieval accuracy in AODmixture and SSAmixture about 10.0% and 1.4% respectively.
Graduate Institute of Space Science, National Central University, Taoyuan 32001, Taiwan;Graduate Institute of Environmental Engineering, National Central University, Taoyuan 32001, Taiwan;Goddard Space Flight Center, NASA, Greenbelt, Maryland, USA;Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan;Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan;Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan;Center for Space and Remote Sensing Research, National Central University, Taoyuan 32001, Taiwan;Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan;Center for Space and Remote Sensing Research, National Central University, Taoyuan 32001, Taiwan;Graduate Institute of Space Science, National Central University, Taoyuan 32001, Taiwan;Center for Space and Remote Sensing Research, National Central University, Taoyuan 32001, Taiwan
Recommended Citation:
Kuo-En Chang,Ta-Chih Hsiao,N Christina Hsu,et al. Mixing weight determination for retrieving optical properties of polluted dust with MODIS and AERONET data[J]. Environmental Research Letters,2016-01-01,11(8)