近期研究重點：
1. 大氣邊界層
探討大氣邊界層（Atmospheric Boundary Layer, ABL）的結構與演變過程，以及其與地表物理過程之交互作用，包括地表熱通量、水氣通量與動量通量。研究重點在於不同綜觀尺度與局地氣象條件下，邊界層動力如何影響亂流發展、混合層高度及污染物的擴散行為。
2. 都市氣象與都市熱島效應
探討都市化過程對局地氣象變化的影響，包括都市熱島強度、風場改變與大氣穩定度特性。關於都市形態、土地利用與人為熱排放如何改變都市邊界層結構，及其對空氣品質的影響。
3. CMAQ 空氣品質模擬
應用Community Multiscale Air Quality (CMAQ）進行區域與都市尺度空氣品質模擬，探討細懸浮微粒（PM2.5）與臭氧污染問題。
建構空氣品質預報系統以及提升空氣品質預報技術
4. 氣象過程對空氣污染傳輸與擴散之影響
分析綜觀尺度天氣型態、邊界層穩定度、風場結構與降水過程，如何影響空氣污染物的傳輸、累積與移除機制，包含長程傳輸、污染物累積與垂直混合過程對空氣品質的影響。
5. 臭氧化學與氣膠生成過程
探討臭氧生成與二次氣膠形成的化學機制，包括 NOx–VOC 敏感區間與光化學反應過程，藉以提升氣象條件與排放變化如何影響臭氧與 PM2.5 濃度變化。
6. 污染源–受體關係與來源解析
透過模式敏感度分析與污染來源解析技術，量化排放源對觀測污染物濃度的貢獻，釐清影響下風處受體區之主要污染來源與傳輸途徑。
7. 極端空氣污染事件與氣候變異影響
探討大尺度氣候變異（如季風環流、ENSO 及綜觀天氣型態）與局部氣象條件，如何影響極端空氣污染事件的發生、強度與持續時間。藉由分析大尺度氣象背景，加深對臺灣及東亞地區空氣品質變化機制的理解，並協助制定有效的污染防制策略。
8. 整合衛星資料以提升空氣品質研究
整合衛星遙測產品、地面觀測與數值模式，以強化空氣品質分析與預報能力。利用衛星反演之氣膠、氣體與氣象資訊，提升空間覆蓋率並降低不確定性，並進行模式驗證、資料同化與物理化學過程解析。
9. 空氣污染防制與減量策略之發展
將氣象–空氣品質交互作用的科學認知，轉化為實務可行的污染管制策略，包括評估不同減排情境、在各類氣象條件下優化防制措施，並提供空氣品質預報與政策制定之科學依據。
My recent research highlights：
1. Boundary-layer meteorology and land–atmosphere energy exchange processes :
Investigating the structure and evolution of the atmospheric boundary layer (ABL) and its interactions with land-surface processes, including surface heat, moisture, and momentum fluxes. Emphasis is placed on how boundary-layer dynamics regulate turbulence, mixing height, and pollutant dispersion under varying synoptic and local meteorological conditions.
2. Urban meteorology and urban heat island (UHI) effects :
Studying the impacts of urbanization on local meteorological conditions, including urban heat island intensity, altered wind fields, and thermal stratification. This research focuses on the role of urban morphology, land use, and anthropogenic heat in modifying urban boundary-layer structures and their implications for thermal comfort and air quality.
3. Air quality modeling using the Community Multiscale Air Quality (CMAQ) model :
Applying the CMAQ chemical transport model to simulate regional and urban-scale air pollutant distributions, with particular attention to PM2.5 and ozone. Research includes model configuration, emissions processing, meteorological coupling, and performance evaluation against surface and vertical observations.
4. Impacts of meteorological processes on the transport and dispersion of air pollutants :
Analyzing how synoptic weather patterns, boundary-layer stability, wind fields, and precipitation influence the transport, accumulation, and removal of air pollutants. This includes assessing long-range transport, stagnation events, and vertical mixing processes that modulate surface air quality.
5. Ozone chemistry and aerosol processes :
Examining the chemical mechanisms governing ozone formation and secondary aerosol production, including NOX–VOC sensitivity regimes and photochemical reactions. The research aims to improve understanding of how meteorology and emissions jointly control ozone and PM2.5 variability.
6. Source–receptor relationships and source apportionment :
Quantifying the contributions of local and regional emission sources to observed air pollutant concentrations using model-based sensitivity analyses and source apportionment techniques. This research supports the identification of dominant pollution sources and pathways affecting downwind receptors.
7. Extreme Air Pollution Events and Climate Influences :
Exploring how large-scale climate variability (e.g., monsoon circulation, ENSO-related anomalies, and persistent synoptic patterns) and local meteorological conditions contribute to the occurrence, intensity, and duration of extreme air pollution events. By examining broader meteorological conditions, we aim to improve understanding of air quality dynamics in Taiwan and East Asia and to support more effective pollution mitigation strategies.
8. Integrating satellite data to enhance air quality research :
Integrates satellite remote sensing products with surface observations and numerical models to improve air quality analyses and forecasting. Satellite-derived aerosol, trace gas, and meteorological information are used for model evaluation, data assimilation, and process interpretation, enhancing spatial coverage and reducing uncertainties in air quality assessments.
9. Development of air pollution control and mitigation strategies :
Translating scientific understanding of meteorology–air quality interactions into effective pollution control strategies. This includes evaluating emission-reduction scenarios, optimizing mitigation measures across different meteorological conditions, and providing scientific support for air quality forecasting and policy-making.