EPA-96-L105-03-002

096

6,400 千元

2007/01/04

2008/12/31

陳正平 教授

監資處

吳權芳

國立台灣大學 大氣科學系

環境資訊系統

空氣品質預報、大氣動力化學模式、大氣沙塵、生質燃燒、大氣穩定度、MODIS

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

朱定中,博士,王國英,教授,王天胤,講師

陳正平 教授

(02)33663937

jpchen@as.ntu.edu.tw

本計畫針對台灣地區的空氣品質之例行性預報作業進行方法之研發與改進，並提供作業上必要的協助。主要工作內容包括維護現有「空氣品質預報輔助系統」，更新系統資料庫，以利每日進行次日空氣品質預報作業；配合本署東亞沙塵影響台灣地區之預報作業，進行東亞沙塵起沙及傳輸預報模擬，綜合預報模式與氣象預報之結果，推估沙塵侵台時間、影響範圍及濃度分布狀況，對可能侵台的東亞沙塵事件提供24至48小時之預警。同時也協助發展空氣品質動力預報模式，以模擬包括生質燃燒等等本土以及外來空氣污染物濃度，提供24至48小時預測，以輔助例行性空氣品質預報作業。此外也分析高污染事件之空氣品質(PSI>100)資料，以及環保署逆溫儀觀測資料，配合氣象模式，以瞭解邊界層大氣穩定度與污染物濃度之關係，作為預報改進之參考依據。同時針對高污染事件，進行高解析度動力化學模式模擬並分析討論。動力化學模式預報模式結果以及逆溫儀觀測資料也將應用於改善客觀預報法內之統計迴歸法。 本計畫也負責環保署MODIS衛星資料接收系統之維護與保固，確保相關影像產品之例行性輸出，並應用影像產品於輔助空氣品質預報作業與結果驗證。

空氣品質預報、大氣動力化學模式、大氣沙塵、生質燃燒、大氣穩定度、MODIS

期末報告.pdf

42MB

[期末報告]公開完整版

2008/3/1 上午 12:00:00

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