The purpose of this project is to provide the following support for the daily forecast of air quality over the Taiwan area: (1) Provide hardware and software maintenance of EPA’s “Air Quality Forecast Auxiliary System” and update relevant database to facilitate the operation of air-quality daily forecast; (2) Develop and apply numerical models to simulate the deflation and transport of atmospheric mineral dust over the East Asia region and predict the impact over the Taiwan area, including the arrival time, duration, concentration, with more than 48 hours’ warming time for strong events; (3) Apply dynamic air quality models to provide simulations of local and foreign air pollutants including those from biomass burning, and provide 24 to 48 hr forecasts to assist routine operation of air quality forecasts; (4) Incorporate the temperature profiler data and the air pollution model output into the statistical scheme to improve the forecasting skill; (5) Utilize the MODIS satellite data to improve the analysis and forecast of aerosol concentration, as well as for the verification of numerical model results; (6) Conduct detailed analyses for selected air pollution episodes to facilitate the improvement of air quality forecasts; (7) Provide manpower support in EPA for daily analysis and forecast of air pollution. In addition, evaluations of forecast results, including those from the statistical forecasts and the numerical forecasts, are conducted to assess the performance of each forecasting method. The statistical methods show gradual but limited improvements; further enhancement may come from “model output statistics.” Our atmospheric mineral dust model persistently gives superior performance over other international models for the forecast of dust incursion over Taiwan; the arrival time is generally well predicted, but the maximum concentration sometime deviates significantly from the observation. As for the dynamic air quality model, the greatest uncertainty exists in the emission inventory and next to it the meteorological forecasts as well as the chemical mechanisms. Our future work will focus on the reduction of these uncertainties.

atmospheric,dynamic,and,chemistry,model,,atmospheric,dust,,biomass,burning,,atmospheric,stability,,MOIDIS