A research team led by Professor Xue Yong from the School of Environment and Spatial Informatics of CUMT has published a study entitled “Detecting the layer height of smoke and dust aerosols over land and ocean using ultraviolet dual-wavelength measurements” in Remote Sensing of Environment, a leading international journal in the field. Li Pei, a CUMT doctoral student, is the first author of the paper, which resulted from collaborative research involving scholars from the Italian National Research Council.

The vertical distribution of atmospheric aerosols significantly impacts climate change, air quality, cloud-aerosol interactions, remote sensing monitoring, and global transport. However, existing methods for retrieving Aerosol Layer Height (ALH) based on passive radiation observations are often confounded by surface reflectance, performing well mainly over oceans or dark land surfaces.

Addressing this limitation, the study proposes a novel Ultraviolet Dual-wavelength (UVD) method. This approach utilizes the Ultraviolet Aerosol Index (UVAI), Aerosol Optical Depth (AOD), and the Ångström Exponent (AE) for cloud screening and aerosol type identification (distinguishing smoke from dust). It enhances the sensitivity of radiation differences to ALH by calculating the logarithmic difference of normalized radiance at 340 nm and 378 nm wavelengths. Furthermore, the normalized effect of the dual-wavelength differential partially offsets errors arising from AOD uncertainty, making the UVD's response to ALH more stable and sensitive.

The research developed Look-Up Tables (LUTs) for smoke and dust aerosols for the retrieval process. The method was validated using CALIOP satellite lidar observations across case studies including North American biomass burning, Siberian wildfires, and Atlantic dust storms. Overall, the UVD method effectively improves the stability and applicability of ALH retrieval, offering a new technical pathway for advancing atmospheric aerosol monitoring.