Project No: 16309026

Title: Satellite-Constrained Data Assimilation of Southeast Asia Biomass Burning Impacts on Hong Kong Trace Gases

Principal Investigator: Prof. Dasa GU

Co-Investigator: Prof. Qi YING

Abstract:

Biomass burning is a major source of trace gases and aerosols, with significant impacts on air quality, climate, biogeochemical cycles, and public health. While its role in atmospheric composition is well-established, the spatiotemporal variability of biomass burning emissions and their transport mechanisms remain poorly understood. Therefore, characterizing emission dynamics and pollutant transport from biomass burning across different global regions is essential. In Southeast Asia (SEA), extensive biomass burning occurs primarily through agricultural land clearing and conversion, with fire activity intensified during El Niño–Southern Oscillation-associated droughts. Transboundary pollutants from SEA biomass burning affect surrounding regions and have attracted international attention, particularly regarding air quality in Hong Kong and the Pearl River Delta. Despite considerable research on biomass burning contributions to air pollution, most studies in Hong Kong have focused on particulate matter, including black carbon and secondary organic aerosols. Accurately quantifying the impacts of SEA biomass burning on trace gas pollutants remains challenging due to limited in-situ measurements in Hong Kong. This project addresses these gaps by integrating satellite remote sensing observations with in-situ measurements to assess the impacts of SEA biomass burning on trace gases in Hong Kong, specifically CO, CO₂, CH₄, alkyl nitrates, and halocarbons. Satellite data will be used to characterize biomass burning intensity in SEA and to investigate trace gas emissions and transport patterns. Long-term in-situ measurements will monitor trace gas distributions to identify the specific contributions from SEA biomass burning. Statistical analyses and model simulations will quantify pollutant contributions from different emission sources and clarify transport processes. The resulting long-term datasets and emission estimates will advance atmospheric chemistry and climate change research while providing scientific support for air quality policy evaluation and improvement.