Integrated Multidimensional Air Quality Study (IMAQS) in Taiwan
Research Field
My name is Fang-Yi Cheng. I received a bachelor’s degree in Atmospheric Sciences from National Central University (NCU), Taiwan, and a Ph.D. in Earth and Atmospheric Sciences from the University of Houston. In August 2009, I joined the Department of Atmospheric Sciences at National Central University, where I am currently a full professor.
My research integrates boundary-layer and urban meteorology with chemical transport modeling to examine PM2.5 and ozone formation, source–receptor relationships, and the impacts of meteorological and climate variability on air quality. Through the use of WRF–CMAQ simulations, observational analyses, and process-based diagnostics, my work aims to advance understanding of meteorological controls on pollutant transport, transformation, and accumulation, and to support the development of effective air pollution mitigation and control strategies, particularly in urban and coastal regions.
Our laboratory focuses on air quality research from an integrated, multidisciplinary perspective, encompassing meteorology, emissions, and atmospheric chemistry. We aim to advance the understanding of the physical and chemical processes governing air pollutant formation, transport, and dispersion, with particular emphasis on boundary-layer dynamics, urban meteorology, and extreme air pollution events.
Our research approach relies on the integration of numerical air quality modeling, ground-based observations, and satellite remote sensing data. By combining chemical transport models (e.g., WRF–CMAQ) with observational analyses, we evaluate model performance, diagnose key processes, and improve forecasting capability. Through close collaboration with government agencies and industry partners, our work supports air quality forecasting, early warning systems, and science-based pollution mitigation strategies.
1. Boundary-layer meteorology and land–atmosphere energy exchange processes
2. Urban meteorology and urban heat island (UHI) effects
3. Air quality modeling using the Community Multiscale Air Quality (CMAQ) model
4. Impacts of meteorological processes on the transport and dispersion of air pollutants
5. Ozone chemistry and aerosol processes
6. Source–receptor relationships and source apportionment
7. Extreme Air Pollution Events and Climate Influences
8. Integrating satellite data to enhance air quality research
9. Development of air pollution control and mitigation strategies
- Outstanding Teaching Award, College of Earth Sciences, National Central University 2025
- Luo Jialun young scholar outstanding research award, National Central University 2022
- Outstanding Industry Collaboration Award, National Central University 2021, 2022
- MOST Outstanding YOUTH Research Project Grant 2020 ~ 2023
- Outstanding research award, National Central University 2014, 2017, 2020-2025.
B.S., Department of Atmospheric Sciences, National Central University, Taiwan
M.S., Geosciences Department, University of Houston, Houston, Texas, USA
Ph.D., Department of Earth and Atmospheric Sciences, University of Houston, Houston, Texas, USA.
Job Description
- Study how synoptic weather systems and boundary-layer dynamics influence air quality.
- Evaluate meteorological influences on pollutant transport and dispersion, such as synoptic weather patterns, stagnation events, long-range transport, and precipitation-driven removal.
- Investigate ozone chemistry and aerosol processes, including NOx–VOC sensitivity regimes and secondary aerosol formation under different meteorological conditions.
- Apply satellite remote sensing data in combination with surface observations to support model evaluation and process analysis.
- Participate in case studies of extreme air pollution events, examining the roles of climate variability (e.g., monsoon circulation and ENSO-related anomalies) and local meteorology.
Preferred Intern Educational Level
graduate-level students
Skill sets or Qualities
- Strong motivation and enthusiasm for research in atmospheric science and air quality.
- Good English communication skills and a strong sense of responsibility.
- A background in atmospheric science, environmental science, or related disciplines is preferred.
- Experience in programming languages such as Fortran and Python, as well as experience with statistical software or other relevant programming tools, is highly desirable.