臺灣博碩士論文加值系統

本研究彙整美國環保署及國內之研究結果，對汽油小客車、汽油小貨車及機車使用酒精汽油之尾氣污染物排放係數及尾氣組成分進行計算，進一步參考並修正Taiwan Emission Data System 8.1 (TEDS8.1)內提供之移動源排放量，應用三維空氣品質網格模式Models-3/CMAQ分析使用E3、E5、E10酒精汽油前後對台灣本島地區於2010年4月及10月之空氣品質影響並分析原因。
排放係數彙整結果顯示，TEDS8.1之新車零里程排放係數較文獻量測結果為低，於使用E0汽油之車輛中，TEDS8.1與文獻彙整結果之汽油小客車THC、NOx、CO排放係數比值分別為0.458、0.747、0.485，汽油小貨車分別為0.295、0.505、0.241，機車分別為0.312、0.296、0.345。本研究以上述比值對TEDS8.1之線源網格化排放量進行修正做為E0案例，並以同樣方式計算E3、E5、E10情境之線源排放量進行空氣品質模擬。
模擬結果顯示，原生系污染物NOx、VOC濃度變化較高之區域皆位於交通源排放量高之區域，其變化趨勢與排放量變化趨勢相同，CO則因車種之排放量變化趨勢相反，各測點之濃度變化趨勢主要受鄰近排放網格點的車種組成影響，E3油品情境之全台NOx、VOC、CO濃度平均變化分別為-0.20 ppb、7.03 ppb、0.61 ppb；E5油品情境之全台NOx、VOC、CO濃度平均變化分別為-0.24 ppb、5.28 ppb、0.52 ppb；E10油品情境之全台NOx、VOC、CO濃度平均變化分別為-0.34ppb、0.32 ppb、0.22 ppb；PM2.5的濃度模擬結果顯示，E3、E5之全台平均濃度增量皆為0.00 ug/m3，E10情境則僅0.03 ug/m3；臭氧部分，4月之E3、E5、E10之O3全台平均濃度變化分別為0.11 ppb、0.12 ppb、0.18 ppb，O3-8hr全台平均濃度變化分別為0.10 ppb、0.10 ppb、0.14 ppb，O3max全台濃度變化分別為0.12 ppb、0.10 ppb、0.12 ppb，OT(NO2+O3)全台濃度變化分別為0.03 ppb、-0.01 ppb、-0.04 ppb；10月之E3、E5、E10之O3全台平均濃度變化分別為0.08 ppb、0.09 ppb、0.13 ppb，O3-8hr全台平均濃度變化分別為0.07 ppb、0.06 ppb、0.09 ppb，O3max全台濃度變化分別為0.07 ppb、0.05 ppb、0.04 ppb，OT全台濃度變化分別為-0.01 ppb、-0.05 ppb、-0.10 ppb。
時間與空間分布，本研究以文獻之光化指標界定比值對各測站之臭氧敏感性物種進行判別，其中北部、宜蘭、花東空品區主要為NOx-control，可進一步由敏感性物種之光化學反應解釋OT於該地區之濃度變化主要呈現負值的原因；各空品區之逐時臭氧及NOx的平均濃度變化圖發現兩者間存在相反趨勢關係，臭氧濃度變化之空間分布圖顯示出同樣結果，代表氮氧化物排放量降低伴隨之臭氧與一氧化氮之滴定效應減弱現象為致使臭氧濃度升高的主要原因。
氣象因素影響探討，綜合MCIP及JPROC計算之結果顯示4月之光化反應速率常數約高於10月一成，可能為造成4月臭氧增量濃度較高的原因；風花圖及HYSPLIT前軌跡模擬結果顯示，氣象模擬所得之4、10月風速於高排放源地區差異不大，而高屏空品區因位於台南市區之下風處以及本身擁有較高的前驅物排放量，因此其正午時段之臭氧上升濃度較其他空品區為高。

This study collect and arrange the data by USEPA and domesteic research about the emission factor of using ethanol-blended gasoline in light duty gasoline vehicle (LDGV), light duty gasoline truck, and scooter, then modify the gridded line sources emissions in TEDS8.1 which is used in Models-3/CMAQ to simulate the impact of using E3, E5, E10 gasohol within 2010 April and October in Taiwan. The simulation result shows that average PM2.5 concentration in E3, E5, E10 gasohol scenarios will variate 0.00, 0.00, 0.03 ug/m3 respectively; April’s daily average ozone concentration in E3, E5, E10 scenarios will repectively rise 0.11, 0.12, 0.18 ppb, which October’s result are repectively 0.08 ,0.09, 0.13 ppb; April’s continuous 8 hours average ozone concentration in E3, E5, E10 scenarios will repectively rise 0.10, 0.10, 0.14 ppb, which October’s repectively rise 0.07, 0.06, 0.09 ppb; April’s daily maximum ozone concentration rise respectively 0.12, 0.10, 0.12 ppb, but only 0.07, 0.05, 0.04 ppb in October. The ratio of [H2O2]/[HNO3] indicator shows that Taipei and east area of Taiwan are more likely to be NOx-control region, which implies the different cause in rising ozone concentration. The concentraion average variation in each hour of ozone and NOx implies the main reason in the increasing ozone should be the titration between ozone and NO, however, Kaohsiung and Pintung have much higher hourly ozone increase at noon because of the precursor from Tainan and itself, which can be obsevated by simulation of HYSPLIT forward trajectory.

第一章 前言 1
1.1 研究起源 1
1.2 研究目的 2
第二章 文獻回顧 3
2.1 酒精汽油政策及發展 3
2.2 酒精汽油對於車輛之影響 6
2.3 空氣品質影響 10
2.4 MODELS-3/CMAQ空氣品質模式 13
2.5 臭氧與光化指標 16
第三章 研究方法 21
3.1 研究架構 21
3.2 模擬情境 22
3.3 台灣地區之移動源排放量處理 22
3.3.1 原始排放量 22
3.3.2 排放係數之彙整比較 23
3.4 排放量修正方式： 30
3.5 MODELS-3/CMAQ 研究方法 31
3.5.1 氣象資料 31
3.5.2 排放量處理 32
3.5.3 CMAQ 模擬機制 33
3.6 空氣品質模擬結果 34
3.6.1 污染物濃度變化 34
3.6.2 空氣品質變化之時間與空間分布 34
第四章 結果與討論 37
4.1 排放係數之彙整比較 37
4.2 線源排放量修正結果 43
4.3 空氣品質模擬結果 45
4.3.1 污染物濃度變化 45
4.3.2 空氣品質變化之時間與空間分布 50
4.4 污染物濃度變化特性探討 85
第五章 結論與建議 107
5.1 結論 107
5.2 建議 110
第六章 參考文獻 111

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