The Air Pollution and Health team's research of Prof. Steve Yim focuses on the interactions between climate and air quality, and the resultant impacts on public health and ecosystem. The team's ongoing research is to develop, advance and utilize the state-of-the-art multi-scale atmospheric models, along with measurement and statistical approaches, to understand the mechanisms that drive the climate-air quality interactions, and evaluate the impacts on human exposure, mosquito abundance and soil acidity.
Particular interests are in investigating air quality impacts of sectoral emissions and transboundary air pollution at multiple spatial scales, studying regional climate change due to land-use changes and global climate change, and evaluating and quantifying the effects of air pollution on respiratory and cardiovascular diseases. The team also assesses and develops emission control scenarios to provide scientific-based policy solutions for a sustainable environment in present and future years.
The position will be required to develop and apply modeling techniques to simulate the spatial distribution of air pollutants in a city at a high spatial resolution. The model development requires to collect data at different aspects. The position will have to work on the data collection, data processing, model development and application, and data analyses. The position has to document the model development and results in reports and peer-review international journals.
Key Responsibilities:
- to collect required data for model development;
- to develop models capable of simulating the spatial distribution of air pollutants at high spatial resolution;
- to apply the developed models to simulate the spatial distribution of air pollutant;
- to analyze the model results of various air pollutants considering meteorological processes and chemical reactions; and
- to document the model development and results in reports and peer-review international journals.
Key Competencies and Requirements:
- To have a master degree in atmospheric science/geography/meteorology/environment
- To have experience in development of spatial models especially land-use regression model or machine learning
