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研究生:王文正
研究生(外文):Wen-Cheng Wang
論文名稱:以空氣品質模式及受體模式解析懸浮微粒排放源之貢獻量
論文名稱(外文):Source contributions of suspended particles using Air Quality Model and Receptor Model
指導教授:陳康興陳康興引用關係
指導教授(外文):Kang-Shin Chen
學位類別:博士
校院名稱:國立中山大學
系所名稱:環境工程研究所
學門:工程學門
學類:環境工程學類
論文種類:學術論文
畢業學年度:97
語文別:中文
論文頁數:210
中文關鍵詞:空氣品質模式CMBTAPM高屏空品區受體模式
外文關鍵詞:TAPMKao-Ping airshedCMBair quality modelreceptor model
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台灣地區依行政區域之劃分,共分七大空品區。其中,以高屏空品區最具惡劣之空氣品質狀況。高屏空品區空品不良率介於6.65 −13.56% (1998−2007年),為次差之雲嘉南空品區(2.58 − 6.98%)之2倍以上。石化、鋼鐵、電力等高污染性工業為高屏地區之主要發展產業,綜以人口、車輛密度、地形及氣象等因素致使污染物擴散不易,令空氣污染問題更為嚴重。於秋末、冬季及春季,受東北季風與中央山脈地形的影響,形成不利空氣污染擴散的環境,伴隨污染物隨季風之跨區域傳送,加上高屏地區工廠及移動車輛廢氣排放,形成全國最糟之空氣品質。

本研究主要應用TAPM (The Air Pollution Model)及CMB (Chemical Mass Balance)解析高屏地區懸浮微粒之物化現象及流佈,期以空氣品質模式及受體模式分析下,解析高屏地區重大污染源對大氣懸浮微粒之貢獻,掌握重要傳輸途徑與重要污染源,並瞭解氣象因素、地形因素及污染源在大氣懸浮污染事件之因果關係。空品模式解析結果可得工業型都市(小港)污染來源主要來自點源排放(49.1%),其次為面源(35.0%)及鄰近地區之傳輸(7.8%)。商業型都市(屏東)與郊區(潮州)之鄰近地區傳輸具極高之比例(屏東:39.1%;潮州:48.7%)。受體模式分析顯示,PM2.5之來源以汽油車及柴油車為主(小港汽油車:43%;柴油車17%。屏東汽油車:45%;柴油車:19%。潮州汽油車:12%;柴油車:29%)。PM2.5-10則以鋪面道路為主(小港:40%,屏東:48%,潮州:50%)。於兩種模式之交互應用下,可先以空品模式得知大區域之主要污染源類型,於特定點再利用受體模式得知當地污染類型,實施有效且較為細緻之空氣污染防治方法。
Air quality of the Kao-Ping airshed has been the worst of all airsheds which are divided into seven groups by districts in Taiwan. The percentage of annual bad air quality (Pollution Standard Index, PSI > 100) in the Kao-Ping airshed (6.65−13.56%) was twice than it in the Yun-Chia-Nan airshed (2.58−6.98%) during the past decade (1998−2007). Oil refineries, petrol/plastic industries, power plants, and iron/steel/metal plants are the major industries in the Kaohsiung metropolitan area. Due to intensive industrial and traffic activities, the Kao-Ping area has the poorest air quality in Taiwan − either increased ground-level concentrations of particulate matter (PM) or ozone (O3) associated with unfavorable meteorological conditions − particularly between late fall and mid-spring

The temporal and spatial characterization of suspended particles in the Kao-Ping area was analyzed by using TAPM (air quality model) and CMB (receptor model) to understand the contributions of the major emission sources. Estimations using the TAPM model suggest that point-source emissions were the predominant contributors (about 49.1%) to PM10 concentrations at Hsiung-Kong industrial site in Kaohsiung City, followed by area sources (approximately 35.0%) and neighboring transport (7.8%). Because Ping-Tung City (urban) and Chao-Chou town (rural) are located downwind of Kaohsiung City when north or northeasterly winds prevail, the two sites also experience severe pollution events despite the lack of industrial sources; neighboring transport contributed roughly 39.1% to PM10 concentrations at Ping-Tung and 48.7% at Chao-Chou.

Results of CMB (chemical mass balance) modeling show that the main contributors to PM2.5 mass are vehicle exhaust (gasoline vehicle emission: 43% and diesel vehicle emission: 17% at Hsiung-Kong; gasoline vehicle emission: 45% and diesel vehicle emission: 19% at Ping-Tung; gasoline vehicle emission: 12% and diesel vehicle emission: 29% at Chao-Chou). And the main contribution to PM2.5-10 mass is the paved road emission (Hsiung-Kong: 40%; Ping-Tung: 48%; Chao-Chou: 50%). It is recommended that air quality model is an appropriate tool to large area and receptor model is more suitable to specific point to identify emission sources by the results in this study.
謝誌I
摘要II
ABSTRACT III
目 錄 V
表目錄 VIII
圖目錄 IX
第一章 前言 1-1
1.1 研究緣起 1-1
1.2 研究目的 1-1
1.3 研究架構 1-2
第二章 文獻回顧 2-1
2.1 高屏地區空氣品質趨勢2-1
2.2 指標污染物(PM10 及O3)趨勢變化 2-3
2.3 懸浮微粒特性概述 2-10
2.4 高屏空品區氣象概述 2-15
2.5 空氣品質模式及受體模式之相關研究 2-19
2.5.1 空品模式 2-19
2.5.1.1 箱型模式(Box model) 2-19
2.5.1.2 高斯模式(Gaussian model)2-20
2.5.1.3 計算流體動力模式
(Computational fluid dynamic model) 2-21
2.5.2 受體模式 2-23
2.5.2.1 化學質量平衡法(CMB) 2-23
2.5.2.2 主成分分析/絕對主成分分析(PCA /APCA) 2-24
2.5.2.3 正矩陣因子化法(PMF)2-25
VI
第三章 研究方法 3-1
3.1 TAPM 模式概述 3-1
3.1.1 TAPM 大氣制御方程式 3-1
3.1.2 TAPM 污染物傳輸制御方程式 3-3
3.1.3 TAPM 地表使用分類 3-9
3.1.4 模式評估工具 3-10
3.2 逆軌跡模式 3-11
3.3 CMB 模式概述 3-12
第四章 結果與討論 4-1
4.1 TAPM 模擬結果 4-1
4.1.1 模擬案例概述 4-1
4.1.2 春季案例(2005/3/8−10) 4-3
4.1.2.1 春季天氣條件 4-3
4.1.2.2 春季模擬結果 4-7
4.1.3 夏季案例(2005/7/12−14) 4-10
4.1.3.1 夏季天氣條件 4-10
4.1.3.2 夏季模擬結果 4-14
4.1.4 秋季案例(2005/10/12−14) 4-17
4.1.4.1 秋季天氣條件 4-17
4.1.4.2 秋季模擬結果 4-21
4.1.5 冬季案例(2005/12/16−18) 4-24
4.4.5.1 冬季天氣條件 4-24
4.4.5.2 冬季模擬結果 4-28
4.1.6 工業型、商業型及郊區之氣膠來源分佈 4-31
4.2 軌跡模式分析 4-32
4.3 受體模式分析結果 4-34
VII
4.3.1 受體點大氣物種濃度 4-34
4.3.2 指紋資料敏感性分析 4-37
4.3.3 污染源貢獻量 4-41
第五章 結論與建議 5-1
5-1 結論 5-1
5-2 建議 5-3
參考文獻 參-1
附錄A 模擬案例風場模擬結果 附A-1
附錄B 模擬案例PM10 濃度場模擬結果 附B-1
附錄C 作者簡歷 附C-1
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