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研究生:吳思緯
研究生(外文):Wu, Sih-Wei
論文名稱:細懸浮微粒(PM2.5)區域性來源與污染事件形成機制之模擬分析
論文名稱(外文):A modeling study on formation mechanism of air pollution episodes and their regional sources using process analysis method
指導教授:張艮輝張艮輝引用關係
指導教授(外文):Chang, Ken-Hui
口試委員:鄭福田張能復林文印陳杜甫
口試委員(外文):Jeng, Fu-TienChang, Len-FuLin, Wen-YinnChen, Tu-Fu
口試日期:2016-07-14
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:環境與安全衛生工程系
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:251
中文關鍵詞:事件日強迫法整合程序速率法CMAQ
外文關鍵詞:EpisodesBFMIPRCMAQ
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近年來PM2.5議題已是民眾關注之焦點,而臺灣中部及雲嘉投地區為臺灣高PM2.5濃度區域,對於產生高PM2.5污染之成因,乃解決PM2.5問題之關鍵,因此進行本研究。本研究以MM5/CMAQ模式,進行2010年(12個月)之模擬分析,藉由五種案例以探討影響臺灣PM2.5之區域性來源,以及選擇在臺中市、雲嘉投地區並藉由整合程序速率(Integrated Process Rate,IPR)分析法對各測站各污染事件進行污染成因分析。
依探討區域性來源之結果,臺灣原生PM之影響為9.83 μg/m3 (39%)、臺灣PM前驅物之影響為6.26 μg/m3 (25%)、東亞直接影響為5.68 μg/m3 (22%)、東亞間接影響為3.0 μg/m3 (12%)以及東亞背影為0.54 μg/m3 (2%),其中境外傳輸之影響(東亞直接+東亞間接+東亞背景)合計為9.22 μg/m3 (36%)。為了解各PM2.5污染事件之影響來源,於2010年之中高污染事件(36 ≤ PM2.5日平均濃度< 71 μg/m3)中,其境外傳輸影響合計為18.5 μg/m3 (38%);在非常高污染事件(PM2.5日平均濃度≥ 71 μg/m3)中,其境外傳輸影響合計為35.9 μg/m3 (42%);由上述可看出越嚴重之污染事件,其境外傳輸之影響也越高。
以IPR探討特定測站之空氣污染事件成因,臺中市測站皆以排放量、水平平流為主要貢獻。雲嘉投地區的部分,其發生PM2.5高污染事件之各種主要物理、化學程序皆不相同;除了排放量外,市區測站PM2.5之高濃度發生多以水平平流之貢獻為主;過渡測站則是以氣膠程序為主;沿海測站則是以水平平流為主要貢獻;山區測站的部分,則是以垂直平流為主要貢獻。

In recent years, PM2.5 issues are the focus of public attention,the central Taiwan, Yunlin, Chiayi and Nantou area are Taiwan high PM2.5 concentration region. To understand the generation of high PM2.5 pollution, the key is to solve the problem of PM2.5,therefore conduct the study.In this study, using MM5 / CMAQ model, conducted in 2010 (12 months) of the simulation analysis,With five kinds of cases in order to investigate the effect of regional sources of Taiwan PM2.5, and using Integrated Process Rate (IPR) analysis cause of air pollution episode.
Discussion of the results according to regional sources, the impact of Taiwan's original PM to 9.83 μg/m3 (39%), the impact of Taiwan PM precursors to 6.26 μg/m3 (25%), the impact of East Asia directly to 5.68 μg/m3 (22%), the impact of East Asia indirectly, 3.0 μg/m3 (12%), the impact of East Asia and back to 0.54 μg/m3 (2%), including total of the impact of long-range transport (East direct + indirect + East Asia East Asia background) amounted to 9.22 μg/m3 (36%). To understand the The impact of the source of PM2.5 pollution incident, in 2010 among high pollution episodes,which impact of long-range transport amounted to 18.5 μg/m3 (38%);in very high pollution episodes,which impact of long-range transport amounted to 35.9 μg/m3 (42%).From the above, the more serious the pollution episodes, the impact of its ong-range transportis also higher.
In the integration process rate (IPR), to understand the episodes of air pollution in the stations, finding Taichung station’s main contribution of emissions and horizontal advection. Yunlin, Chiayi and Nantou area, its main variety of physical, chemical processes, are not same. In addition to emissions, the urban’s station high PM2.5 concentration mainly occurs of horizontal advection. Transition station main contribution is aerosol processes. Coastal station main contribution is horizontal advection. In the mountain station, the main contribution is vertical advection.

中文摘要 i
目錄 iii
表目錄 vi
圖目錄 ix
第一章 前言 1
1.1研究緣起 1
1.2研究目的 2
第二章 文獻回顧 3
2.1敏感度分析方法介紹 3
2.1.1強迫法(Brute Force Method, BFM) 3
2.1.2 強迫法(BFM)之應用 4
2.2 整合程序速率法(IPR) 7
2.2.1 整合程序速率法之研究 7
2.2.2 整合程序速率法之應用 8
2.3長程傳輸對懸浮微粒之影響 11
第三章 研究方法 20
3.1研究流程 20
3.2模式使用說明 22
3.2.1模擬範圍 22
3.2.2模擬時間之選擇 23
3.2.3排放量說明 23
3.2.3.1人為源 23
3.2.3.2生物源 24
3.2.4氣象資料 26
3.2.5初始條件與邊界條件 26
3.2.6 細懸浮微粒之質量濃度計算方法 26
3.3臺灣大氣中PM2.5之區域性來源分析 27
3.3.1 臺灣大氣中PM2.5之區域性來源模擬 27
3.3.2 各排放案例說明 27
3.4 臺灣PM2.5之污染來源類型分析 31
3.5 PM2.5污染事件篩選 32
3.5.1 事件日篩選原則 32
3.5.2 模式性能評估 33
3.6 以整合程序速率法分析各事件日之形成機制 34
第四章 結果與討論 35
4.1基準案例模式模擬分析 35
4.1.1地形 35
4.1.2氣象資料 35
4.1.3排放量說明 42
4.1.4空氣品質模式基準案例PM2.5濃度模擬結果 45
4.2 臺灣大氣中PM2.5之區域性來源分析 47
4.2.1 PM2.5 47
4.2.1.1 全年 47
4.2.1.2 四季 51
4.2.1.3 小結 56
4.2.2 PM2.5組成份 64
4.2.2.1 全年 64
4.2.2.2 四季 67
4.2.2.3 小結 73
4.3 臺灣PM2.5事件之污染類型分析 76
4.3.1 PM2.5各污染事件之區域來源分析 76
4.3.1.1 中高污染事件(36 ≤ PM2.5 < 71 μg/m3) 76
4.3.1.2 非常高污染事件( PM2.5 ≥ 71 μg/m3) 81
4.3.1.3 所有污染事件( PM2.5 ≥ 36 μg/m3) 85
4.3.2 PM2.5各污染事件之污染來源類型分析 89
4.3.2.1 中高污染事件(36 ≤ PM2.5 < 71 μg/m3) 89
4.3.2.2 非常高污染事件( PM2.5 ≥ 71 μg/m3) 97
4.3.2.3 所有污染事件( PM2.5 ≥ 36 μg/m3) 104
4.4 PM2.5污染事件之篩選 112
4.4.1模式性能評估 115
4.4.1.1模擬值與觀測時間序列分析 116
4.4.1.2模擬值與觀測誤差定量分析 121
4.4.2 模擬結果之空間分佈分析 125
4.4.2.1 台中市、雲嘉投地區PM2.5模擬結果 125
4.4.2.2 氣象資料之事件日模擬情形_風場 130
4.5 以整合程序速率法分析臺中市地區污染事件之形成機制 139
4.5.1 1月15日之污染事件 139
4.5.2 綜合討論分析 147
4.6 以整合程序速率法分析雲嘉投地區污染事件之形成機制 149
4.6.1 12月21 - 22日之污染事件 149
4.6.2 綜合討論分析 158
第五章 結論與建議 160
5.1 結論 160
5.1.1臺灣大氣中PM2.5之區域性來源分析 160
5.1.2 PM2.5污染事件之臺灣境內外來源分析 161
5.1.3以整合程序速率法分析臺中市地區污染事件之形成機制 162
5.1.4以整合程序速率法分析雲嘉近地區污染事件之形成機制 162
5.2 建議 163
參考文獻 164
附錄A 168
附錄B 172
附錄C 206


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