Effect of land surface parameters on meteorology and ozone air quality simulations in the Great Bay Area, China

Abstract

Land surface parameters play a crucial role in simulations of weather and air quality. This study investigated the impact of underlying surface parameters on meteorological fields and pollutant concentrations in the Greater Bay Area (GBA), China, during warm and cold season. Updated land surface parameters, namely land use type, leaf area index, vegetation fraction, albedo, and roughness length, were incorporated to improve simulations. The model showed 7%–14% improvements (in terms of the index of agreement) in wind speed simulations, whereas temperature and relative humidity were not sensitive to the adoption of updated parameters. Moreover, compared with the model with default parameters, the model with updated natural underlying surface parameters showed a 2–3 m/s reduction in cross-border wind speed during cold season in the GBA. The model also showed a 1–2 m/s increase in the wind speed in urban areas, owing to thermal contrast. During periods in which clean air came from the north, the reduced wind speed hindered ozone removal in the GBA. The use of updated underlying surface parameters enhanced the urban heat island effect by ∼2 K and increased the wind speed over urban areas by ∼2 m/s. The intensified urban heat island circulation generated strong updrafts and intensified sea breezes, promoting the penetration of sea breezes inland. Additionally, the intensified sea breeze and urban heat island circulation contributed to a ∼10-ppb reduction in ozone concentrations. Hence, incorporating the latest land surface parameters improved the simulation of meteorological fields and influenced cross-border pollutant transportation. This study highlights the importance of considering underlying surface characteristics in regional modelling and provides insights for air pollutant management.