臺灣博碩士論文加值系統

著旅遊業在宜蘭縣迅速發展，交通污染日益嚴重。車輛廢氣排放已成為郊區空氣污染的主要來源之一。雪山隧道是台北到宜蘭最便捷道路，為了確保模擬真實性，使用計算流體動力學流體模型(Computational Fluid Dynamics, CFD)模擬隧道內接近出口150公尺的濃度；亦於連接頭城交流道總長度2公里範圍進行數值模擬，使用加州線源分散模型(California Line Source Dispersion Model, CALINE4)軟體模擬移動源交通空氣污染物於頭城交流道暴露的濃度。研究假日塞車時間和平日交通狀況之間的空氣質量差異。此外，為了得到三維方向污染物分布情況，本研究利用無人機(Unmanned Air Vehicle , UAV)搭載氣體感測器，進行頭城交流道空氣品質監測。本研究首先收集台灣中央氣象局的地面氣象數據、地面和探空數據，車輛的排放率由中華民國行政院環境保護署國內全國性排放清冊Taiwan Emission Data System (TEDS9.0)估計。此外，交通量由交通運輸部運輸研究所及交通部提供。為了證明模擬的數據，本研究使用無人飛機(Unmanned Aerial Vehicle, UAV)量測 PM2.5濃度，及使用SOx，NOx與CO氣體分析儀進行驗證。
為了評估預測濃度，進行設定參數模擬敏感度分析，根據不同類型的道路和空氣污染物排放率，設定模型參數和氣象條件，以評估污染物的增量影響，及預測時間和空間變化的空氣品質，本研究亦探討高峰時段或週末的交通量和污染物排放及濃度分布。雪山隧道出口假日污染物濃度SOx, CO, NO, PM2.5 及溫度分別為0.003 ~ 0.008 ppm, 7.5 ~ 15 ppm, 1.5 ~ 2.5 ppm , 40 ~ 80 μg/m3及40 ~ 45度，平日濃度分別為 0.002 ~ 0.003 ppm, 3.4 ~ 9 ppm, 0.7 ~ 1.8 ppm, 40 ~ 60 μg/m3及30 ~ 35度。使用無人飛機驗證模擬得知，垂直高度為9, 7.0, 5.0與 3.0公尺時，假日PM2.5濃度分別為45~48，30~35，25~30與與48〜50 μg/m3 ,平日PM2.5濃度則分別為40〜45, 25〜30, 15〜20, 45〜48與45〜50 μg/m3。

With the development of tourism grown rapidly in Ilan County, the pollution resulted from traffic is increasingly serious. The vehicle exhaust emission has become one of the major sources of air pollution in the suburban area. Hsuehshan tunnel is the most convenient road, from Taipei to Iilan. In order to ensure the authenticity of the simulation, the concentration of the last 150 meters at Hsuehshan tunnel was simulated by Computational Fluid Dynamics fluid model (CFD). Then, the air quality at Tocheng interchange along 2km length of highway was simulated by California Line Source Dispersion Model (CALINE4). The differences of air quality between rush hours and normal traffic condition were also investigated. The concentration of line source air pollutants exposed at the junction of the city. In order to get the distribution of three-dimensional of pollutants, Unmanned Aerial Vehicle (UAV) with PM2.5 and CO sensors installed under the UAV was developed. One of objectives was to validate air quality forecast.
Firstly, it is important to collect local meteorological data, including ground and aerial, data of source by Taiwan Center Weather Bureau. The emission rate of the sources is also estimated by Environmental Protection Agency Taiwan Emission Data System (TEDS9.0). In addition, the traffic volume was supplied by Ministry of Transportation and Communications. UAV with PM10 sensor were used to verify PM10 concentrations and ensure the data of simulation with accurate prediction. Gas analyzers of SOx (Sulfur oxides), NOx (nitrogen oxides) and CO (carbon monoxide) were used to verify the accurate simulation. According to the different kinds of road and air pollutant emission rate, the parameters of the model and meteorological conditions are necessary to be set to assess the incremental impact of the pollutant SOx, CO, NO and PM2.5 in weekend is 0.003 - 0.008 ppm, 7.5 - 15 ppm, 1.5 - 2.5 ppm ad 40 - 80 μg/m3, respectively. Furthermore, the ambient temperature distribution in the tunnel is about 40 - 45°C in tunnel. In weekdays, vehicle speed is 60 km / hr and the natural wind speed is 2.0 m / s. The concentration ranges are 0.002 ~ 0.003 ppm, 3 ~ 9 ppm, 0.7 ~ 1.8 ppm and 35 ~50 predicted. Use Unmanned Aerial Vehicle (UAV) to verify that PM2.5 concentration of vertical changes concentration of vertical changes at 9.0, 7.0, 5.0, and 3.0 meter height is 45 - 48, 30 - 35, 25 - 30 and 50 -52 μg/m3, respectively. In addition, predicted PM2.5 concentration is 40 - 45, 25 - 30, 45 – 48 and 45 – 50 μg/m3 in weekday, respectively.

中文摘要 I
ABSTRACT II
Table Catalog VII
Figure Catalog VIII
CHAPTER 1 INTRODUCTION 1
1-1 Motivation 1
1-2 Objectives 3
1-3 Structure of This Study 3
CHAPTER 2 LITERATURE REVIEW 5
2-1 Traffic pollutants 5
2-2 Prediction Model 6
2-2-1 Line source dispersion model 7
2-2-2 Computational fluid dynamics 10
2-3 Selected model 12
2-3-1 CALINE4 model 12
2-3-2 ANSYS FLUENT 16
2-4 Traffic 18
2-4-1 Type of vehicles 18
2-4-2 Vehicle density 19
2-5 Measurement 19
2-5-1 Gas analyzer 19
2-5-2 UAV 20
2-6 Data analysis 20
2-6-1 Model Sensitivity Analysis 20
2-6-2 Statistic analysis 22
2-6-3 Pollutant standard 22
2-7 Health risk assessment 25
CHAPTER 3 METHOD AND MATERIALS 27
3-1 Study Region 27
3-2 Data Collection 28
3-2-1 Traffic volume 28
3-2-2 Emission rate 28
3-2-3 Meteorology 29
3-3 Design of Model 31
3-3-1 CALINE4 31
3-3-2 FLUENT 34
3-4 Measurement 44
3-4-1 Gas analyzer 44
3-4-2 High volume sampler 45
3-4-3 UAV 45
3-5-1 Model Sensitivity Analysis 51
3-5-2 Statistic 51
CHAPTER 4 RESULTS AND DISSCUSSION 56
4-1 Data Collection 56
4-1-1 Vehicle volume 56
4-1-2 Vehicles Emission rate 60
4-1-3 Meteorology 63
4-2 Comparison of weekday and weekend in tunnel 66
4-2-1 Pressure distribution 66
4-2-2 Concentration in tunnel 68
4-3 Comparison in Toucheng intersection 81
4-3-1 Comparison with modeled of PM2.5 in different Height level 81
4-3-3 PM2.5 101
4-3-4 UAV 102
4-4 Data analysis 107
4-4-1 Model Sensitivity Analysis 108
4-4-2 CFD Relative resident 113
4-4-3 Model verification 115
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS 119
5-1 Conclusion 119
Appendix 1 The pollutant emission rate of each vehicles 143
Appendix 2 Comparison of Tunnel Simulation and measurement 145

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