隨著中國經濟的發展，其污染物排放情形也越來越嚴重，由於台灣位在東亞與東南亞的交接處，當鋒面系統通過或是高壓迴流的天氣型態，會受到中國污染物長程輸送的影響。此外台灣為開發中國家，在台灣本島排放的影響下，局地造成高濃度污染的情形也相當嚴重。 本研究利用WRF 模式(Version 3.2.1)設定不同的邊界層參數化(YSU 與MYJ)對於2003 年4 月兩種不同天氣型態模擬台灣春季的氣象場，分別是綜觀效應強的個案一(4/13~4/15)以及綜觀效應弱的個案二(4/17~4/19)，並且利用CMAQ 模式(Version 4.4)，以WRF 氣象場結果，配合排放資料，模擬2003年4 月的空氣污染，討論兩種不同邊界層參數化在兩個期間對於空氣污染物傳輸、分佈的影響。 模擬的結果顯示，個案一期間，風場與邊界層高度模擬的差異使得污染物的分佈與傳輸有25ppb 以上的差別；個案二期間，有明顯的日夜海陸風交替，白天海上風速以YSU 大於MYJ(表示YSU 的海風較強)，但是夜晚陸地風速為YSU 小於MYJ(表示YSU 的陸風較弱)。在污染物的時空分佈，YSU 白天海風較強的情形，使得YSU 污染分佈比起MYJ 較集中於沿海以內的區域，且離岸處MYJ 比YSU 有較高的臭氧濃度分佈。夜晚NO 與臭氧滴定效應，因為YSU 陸風較弱，使得YSU 臭氧低濃度分佈情形比較集中於排放源區附近的區域。與觀測資料比較，YSU 在風速、溫度以及污染物濃度與觀測的偏差比較小，模擬結果比較符合觀測。 The O3 and aerosol problem in Taiwan can be locally produced or long-range transported (LRT) from Gobi desert. The LRT of O3 problems are mostly observed during the spring season under the influence of Asian continental outflow. The O3 concentration about 50 to 70 ppb is observed under the impact of LRT while the locally produced O3 concentration can reach up to 100 ppb easily. To adequately simulate air pollution events in Taiwan, the correct representation of the boundary layer wind, temperature, moisture, flux components and mixing heights, are needed for air quality modeling which are strongly dependent on the boundary layer parameterizations in meteorological models. In this study, meteorological simulations are performed using Weather Research Forecasting (WRF)(V3.2.1) model by applying two different PBL schemes (YSU and MYJ). Community Multiscale Air Quality (CMAQ) modeling system is performed subsequently to study the effect of the PBL physical processes on the meteorological and air quality simulations. The comparison focused on two different atmospheric conditions. Case 1 is under the influence of the Asia continental outflow and the air pollutants is long-range transported (LRT) to northern Taiwan. Case 2 is associated with the land-sea breeze flow and the locally generated ozone concentration can reach up to 120 ppb. The simulation using YSU scheme predicts higher temperature during the night and inducing weaker land breeze flow which would accumulate the NO in the source region. The O3 titration is stronger near the source region and lower in the offshore area. During the daytime, the simulation using YSU scheme predicts higher temperature thus inducing stronger sea breeze flow which would carry the O3 produced in the previous day back into the Taiwan Island. The stronger sea breeze from simulation using YSU would predict higher O3 toward inland and lower O3 in the offshore area than the one using MYJ. Comparison with the observation datasets identifies less bias of the wind speed, temperature and ozone concentration with the simulation using YSU scheme. Wind direction is reasonably captured in both simulations.
