Research on the Spatiotemporal Variation Characteristics of Different Aerosol Types and Aerosol Optical Depth Based on MODIS Data - Shujin Meng; Yong Wan; Fangfang Chen; Yuyu Chen; Xiaowen Li; Weiliang Gu; Yongshou Dai (Aerosol and Air Quality Research)
Abstract The monitoring of atmospheric aerosols is of significant importance for research on climate change, air pollution, and remote sensing. The Shandong Peninsula, situated in the coastal region of eastern China, holds a unique geographical position. Neglecting the spatiotemporal variations in aerosol characteristics caused by local atmospheric circulation and regional emissions in this area could potentially compromise the accuracy of assessing aerosol radiative and climate effects. This study utilized the MOD04_3k product from the long-term observations of MODIS spanning nearly a decade (2013–2022). In comparison with aerosol optical depth (AOD) data from the global aerosol robotic network (AERONET) for validation, employing an aerosol relative optical thickness classification method, the research and analysis focused on the spatiotemporal distribution characteristics, long-term trends, and differences in aerosol parameters and types across different regions of Shandong Province. The study ultimately obtained refined spatial discrepancies and temporal dynamic variation information regarding aerosol parameters and their types in the Shandong region. The analysis indicates that there is an overall declining trend in the annual variation of AOD in different regions of Shandong Province, with the highest values occurring during the summer among all four seasons. Additionally, the aerosol types in the northern and central regions of Shandong vary with the changing seasons, while there are no significant seasonal differences in the western and eastern regions. Due to the significant differences in the climatic effects of various types of aerosols, this study holds significant practical value for atmospheric radiation transmission, air quality improvement, and climate simulation predictions in the region.