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標題: GTx,TPAQM和MM5模式污染物模擬之比較
Comparison of trajectory determinations by GTx,TPAQM and MM5
作者: 謝政育
Hsieh, Cheng Yu
關鍵字: GTx;高斯軌跡傳遞係數模式;TPAQM;MM5;pre-treatment meteorological part;光化學軌跡模式;PSU-NCAR第五代中尺度氣象模式;氣象前處理模組
出版社: 環境工程學系
由於台灣已進入工業化的社會,在所處環境的空氣品質越來越惡劣下,為了有效提供環保署相關的空氣污染管制決策,環保署成立空氣品質模式支援中心,並針對於台灣的獨特地型和模擬成果,選取了高斯軌跡傳遞係數模式 (GTx)和光化學軌跡模式 (TPAQM) 為優選模式之一,因此研究中選取了GTx 和TPAQM和全球廣泛使用的PSU-NCAR第五代中尺度氣象模式 (MM5) 三模式,探討其模式所模擬結果之間的相關性。

The air quality in Taiwan is more and more abominable in recent years. In order to offer the Environmental Protection Administration (EPA) air pollution control policies effectively, the Environmental Protection Administration establishes the 「Air Quality Modeling Center ,Taiwan」. Besides, for the complex topography in Taiwan, Gaussian Trajectory transfer-coefficient modeling system (GTx) and Trajectory Photochemical Air Quality Model (TPAQM) are considered as the better tool to investigate the issue about air quality. In this study, the correlations between simulations and observations were studied using GTx, TPAQM and the Fifth-Generation NCAR / Penn State Mesoscale Model (MM5).
The experiments carried out at Beitou primary school and Jhongsing Village were choose as study cases. The analysis of the wind field are as follows: RMSE, MAE , BIAS and CORREL of U component in TPAQM are 1.70 , 1.23, -0.33 and 0.57 respectively, but 3.64 , 2.75, -1.71 and 0.42 respectively in MM5; besides, V component in TPAQM are 1.62 , 1.06 , 0.13 and 0.60 respectively , but 3.00 , 2.33, -0.88 and 0.38 respectively in MM5. Therefore, it can be found that the display of TPAQM is superior to the wind field of MM5 simulation.
In the simulations of back-trajectory, results of GTx and MM5 simulation showed that the alternating drainage wind and upslope wind system are driven by the mountainous in Nan-Tou valley in center Taiwan, but MM5 seems that there is not formulation of this mechanism; therefore may causes the trajectory error.
Joining to GTx main program with pre-treatment meteorological part of TPAQM and MM5, the simulations of the three models are not good comparing with observations. The correlation coefficient in SO2 of MM5 simulation is 0.5; the correlation coefficient in NOx of TPAQM simulation is 0.44; the correlation coefficient in PM10 of GTx simulation is 0.42; but while neglecting the comparison of observations, it would be found that concentration of pollutants simulation in the three models are of good mutuality with observations.
In this study, the simulations in MM5 often overestimated the wind field or the pollutant simulation. The cause should be there are no observations in the boundary conditions and the insufficient observations. Therefore, more observations are required for complete simulations to compare the different mechanisms of models.
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