AUTHOR=Lu Yaqiong , Yang Xianyu , Wang Haofan , Jiang Mengjiao , Wen Xiaohang , Zhang Xiaoling , Meng Lixia TITLE=Exploring the effects of land use and land cover changes on meteorology and air quality over Sichuan Basin, southwestern China JOURNAL=Frontiers in Ecology and Evolution VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2023.1131389 DOI=10.3389/fevo.2023.1131389 ISSN=2296-701X ABSTRACT=

Accurate characterization of land use and land cover changes (LULCC) is essential for numerical models to capture LULCC-induced effects on regional meteorology and air quality, while outdated LULC dataset largely limits model capability in reproducing land surface parameters, particularly for complex terrain. In this study, we incorporate land cover data from MODIS in 2019 into the Weather Research and Forecasting (WRF) model to simulate the impacts of LULC on meteorological parameters over the Sichuan Basin (SCB). Further, we conduct Community Multiscale Air Quality (CMAQ) simulations with WRF default LULC and MODIS 2019 to probe the effects on regional air quality. Despite consistency found between meteorological observations and WRF-CMAQ simulations, the default WRF land cover data does not accurately capture rapid urbanization over time compared with MODIS. Modeling results indicate that magnitude changes trigged by LULCC are highly varied across SCB and the impacts of LULCC are more pronounced over extended metropolitan areas due to alteration by urbanization, featured by elevating 2-m temperature up to 2°C and increased planetary boundary layer height (PBLH) up to 400 m. For air quality implications, it is found that LULCC leads to basin-wide O3 enhancements with maximum reaching 21.6 μg/m3 and 57.2 μg/m3 in the daytime and nighttime, respectively, which is mainly attributed to weakening NOx titration effects at night. This work contributes modeling insights into quantitative assessment for impacts of LULCC on regional meteorology and air quality which pinpoints optimization of the meteorology-air quality model.