台灣都會區細懸浮微粒(PM2.5)濃度變化影響因子、污染來源及其對大氣能見度影響

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施韋羽(Wei- Yu Shih) 查詢紙本館藏

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論文名稱

台灣都會區細懸浮微粒(PM2.5)濃度變化影響因子、污染來源及其對大氣能見度影響
(Variations of urban fine suspended particulate matter (PM2.5) from various environmental factors and sources and its role on atmospheric visibility in Taiwan)

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摘要(中)

都會地區細懸浮微粒(PM2.5)特性及來源對民眾健康影響和污染源管制相當重要。本文彙整2011年3月9日至2012年3月29日期間，在台灣北、中、南都會區三個空品監測站(新莊站、忠明站、小港站)進行共63次的PM2.5手動檢測質量及成分濃度，目的是藉由系統性收集PM2.5空間及時間變化，探討都會區PM2.5濃度受季節變化、不同檢測方法和儀器套件、不同天氣型態、潛在污染來源的影響，並研究大氣能見度和各種PM2.5成分及污染源的關係。
研究結果發現，新莊站和忠明站PM2.5平均質量濃度都以春季最高，小港站則是以冬季濃度最高。依據天氣系統型態分析，新莊站和忠明站除了本地污染外，還受到亞洲大陸污染長程傳輸影響；南部地區由於受到亞洲大陸氣流傳輸影響較小，小港站主要應該是當地污染源排放加上環境對流擴散不佳的影響。在春、秋及冬季各站主要的成分都是SO42-，夏季則是有機碳(OC)濃度接近SO42-。夏季時，NO3-揮發比值最高，其餘揮發離子則較無季節性變化。
整體觀測期間，三個監測站大多以R&P 2000 FRM (Federal Reference Method) 的PM2.5檢測濃度最低，空品站的自動監測濃度最高，R&P2300微粒成分採樣器則是介於兩者之間，且當質量濃度較高時，彼此間的差距也越大。其中，造成R&P2000與R&P2300檢測結果差異主要是受到R&P2300裝設蜂巢管影響。
天氣型態(Chuang et al., 2008)對分析指出發生高壓迴流(HPPC)、高壓推擠(HPP)及鋒前暖區+弱南風(WAF+WSW)時，北部有高PM2.5質量濃度，北部在東北季風及西南季風期間濃度較低。中、南部則在HPPC、HPP及東北季風三種天氣類型較容易呈現高濃度PM2.5，並在WAF+WSW及西南季風期間有低濃度。
利用PMF (Positive Matrix Factorization) (U.S. EPA, 2008)模式進行PM2.5污染源推估，三個監測站都解析出6個污染源，且都以Secondary nitrate and chloride的貢獻百分比最高，其次分別為Secondary sulfate、Gasoline emission、Soil dust、Diesel emission、Biomass burning。以PM2.5化學成分、污染來源和環境因子對大氣能見度進行多元迴歸分析，三個監測站PM2.5主要受到二次無機離子潮解的氣膠含水量，使大氣能見度降低。
總結來說，台灣都會區PM2.5濃度隨著季節及不同天氣系統的改變而有所變化，PMF解析結果顯示交通排放對大氣PM2.5濃度有顯著貢獻，可提供給相關單位進行都市來源管制的評估；此外，PM2.5成分中的二次無機離子對都市能見度降低有重大影響。

摘要(英)

The characteristics and source contributions are very important in residents’ health effect and source control. This work compiles 63 samples of PM2.5 mass and speciations manually collected at three air quality monitoring stations (Xinzhuang, Chungming, and Siaogang) located in the metropolitan areas of northern, central, and southern Taiwan from March 9, 2011 to March 29, 2012. The aim of this work is studying seasonal variations of urban PM2.5, the effects of various measurement methods and instrumental units, different weather types, and potential source contributions on PM2.5. Moreover, the relationship of various PM2.5 speciations and sources with visibility is also investigated.
The results show that the highest PM2.5 mass concentrations at the Xinzhuang and Chungming stations are occurred in spring, while that of the Siaogang station is in winter. For the weather patterns results, the sources of Xinzhuang and Chungming stations are contributed from local sources as well as long-range transport of Asian continent based on weather pattern analysis. In contrast, Siaogang station is affected locally plus poor ventilation in the environment. The major species is SO42- in almost all the stations and seasons except for the summer. Organic carbon concentration is very close to SO42- and highest vaporization proportion of NO3- is observed in summer while other volatile ions are without seasonal variations.
For the whole observation study, the collected PM2.5 concentration is the lowest when using R&P 2000 FRM (Federal Reference Method), highest for referring to the data of air quality stations, and in the middle for the data from R&P2300 speciation sampler. In addition, the differences among sampling methods become wider when the collected concentrations are higher. The deviations between R&P2000 and R&P2300 are inferred to be affected by honeycomb denuders installed in the R&P 2300 sampler.
High PM2.5 concentration was observed in the north for the weather patterns of High Pressure Peripheral Circulation (HPPC), High Pressure system Pushing (HPP), and Warm area Ahead of a cold Front coupling with Weak Southern Wind (WAF+WSW) based on the weather pattern analysis (Chuang et al., 2008). Lower PM2.5 concentration frequently occurred in the periods of Northeastern and Southwest monsoons. In contrast, high PM2.5 concentrations were normally appeared in HPPC, HPP, and Northeastern monsoon and low for WAF+WSW and Southwestern monsoon in the central and southern Taiwan.
Six source types were resolved from PMF (U.S. EPA, 2008) (Positive Matrix Factorization) source apportionment for all three stations. Secondary nitrate and chloride contributed highest followed by Secondary sulfate, Gasoline emission, Soil dust, Diesel emission, and Biomass burning. Multiple regression analysis on atmospheric visibility using PM2.5 species, sources types, and environmental factors showed that visibility is mainly reduced by the water content deliquesced from secondary inorganic ions.
In summary, Taiwan urban PM2.5 is varied by seasons and weather patterns. Traffic emissions contributed significantly to atmospheric PM2.5, which may help the authorities in urban pollution control and assessment. Moreover, secondary inorganic ions are significant in reducing urban visibility.

關鍵字(中)

★ 細懸浮微粒(PM2.5)
★ 天氣型態
★ PMF模式
★ 大氣能見度

關鍵字(英)

★ Fine particulate matter (PM2.5)
★ weather patterns
★ PMF model
★ Atmospheric visibility

論文目次

摘要 I
Abstract III
致謝 V
目錄 VI
圖目錄 X
表目錄 XIII
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 細懸浮微粒(PM2.5)特性 3
2.2 氣膠形成來源 3
2.3 氣膠化學組成 4
2.3.1 氣膠水溶性離子來源 4
2.3.2 氣膠碳成分 4
2.4 台灣都會區細懸浮微粒(PM2.5)特性 7
2.5 大氣能見度與細懸浮微粒(PM2.5)的關係 9
2.6 手動採樣FRM篩選器的差異討論 10
2.7 受體模式正矩陣因子法PMF(Positive Matrix Factorization)應用 13
2.8 PMF來源解析的風向推估方法CPF ( Conditional probability function) 17
第三章研究方法 18
3.1 研究架構 18
3.2 採樣地點時程及地點 20
3.2.1 採樣地點概述 20
3.2.2 採樣時間及採樣次數 22
3.3 PM2.5自動監測儀器及手動採樣儀器 24
3.3.1 R&P2000 PM2.5氣膠質量濃度採樣器 24
3.3.2 R&P2300 PM2.5氣膠質量濃度採樣器 25
3.3.3 自動監測儀器 27
3.4 手動採樣分析方法 29
3.4.1 採樣濾紙前準備 29
3.4.2 質量濃度秤重分析 30
3.4.3 水溶性離子分析方法 31
3.4.4 碳成分檢驗分析方法 32
3.4.5 微粒揮發NO3-、NH4+、Cl-及OC補償方法 34
3.5 ISORROPIA模式 36
3.6 正矩陣因子法PMF (Positive Matrix Factorization)操作 37
3.6.1 輸入資料處理 38
3.6.2 操作流程 39
3.7 條件機率函數CPF ( Conditional probability function)推估方法 42
第四章結果與討論 43
4.1 北、中、南都會區手動檢測與自動監測儀器PM2.5質量濃度變化趨勢 43
4.1.1 新莊空品監測站手動檢測和自動監測質量濃度變化 44
4.1.2 忠明空品站手動檢測和自動監測質量濃度變化 48
4.1.3 小港空品站手動檢測和自動監測質量濃度變化 52
4.1.4 R&P2000手動檢測和空品站PM2.5質量濃度線性定量關係 56
4.1.5 R&P2000和R&P2300手動檢測PM2.5質量濃度線性迴歸定量關係 60
4.1.6 R&P2000與R&P2300及空品站PM2.5質量濃度比值 64
4.1.7 利用揮發離子推估R&P2000與R&P2300的PM2.5質量濃度 66
4.2 北、中、南都會區PM2.5手動檢測成分濃度變化趨勢 68
4.2.1 PM2.5手動檢測成分濃度扣除採樣空白後的影響 68
4.2.2 新莊監測站PM2.5成分濃度隨季節及時間變化 70
4.2.3 忠明監測站PM2.5成分濃度隨季節及時間變化 73
4.2.5 PM2.5成分濃度質量閉合(Mass Closure)評估 79
4.3 揮發離子濃度推估 85
4.3.1 環境最高溫度(TMax)及修正後PM2.5質量濃度關係推估揮發NO3-濃度 85
4.3.2 環境最高溫度(TMax)及修正後PM2.5質量濃度關係推估揮發Cl-濃度 88
4.3.2 環境最高溫度(TMax)及修正後PM2.5質量濃度關係推估揮發NH4+濃度 91
4.4 R&P2000和R&P2300手動檢測PM2.5質量濃度差異探討 94
4.4.1 WINS衝擊器、VSCC旋風離心器及Harvard impactor (R&P 2300)三者對PM2.5採集濃度差異比較 94
4.4.2 Harvard impactor(R&P 2300)裝設濾紙匣及蜂巢管對PM2.5採集質量濃度的影響 97
4.5 北、中、南都會區PM2.5濃度變化影響因子及來源推估 101
4.5.1 台灣北、中、南都會區PM2.5濃度變化彼此關聯性 101
4.5.2 天氣型態對台灣北、中、南都會區PM2.5濃度變化影響 108
4.5.3 受體模式PMF推估北、中、南都會區PM2.5潛在來源 114
4.5.4 不同天氣型態各污染來源貢獻百分比分佈 153
4.6 台灣北、中、南都會區PM2.5濃度及氣象因子對大氣能見度影響 157
4.6.1 PM2.5成分及天氣因子對大氣能見度的多元迴歸分析 157
4.6.2 PM2.5推估來源及天氣因子對大氣能見度的多元迴歸分析 167
第五章結論與建議 171
5.1 結論 171
5.2建議 173
第六章參考文獻 174
附錄1 各監測站周邊建設及四周環境位置 183
附錄2 各監測站R&P2000與R&P2300及空品站PM2.5質量濃度比值 185
附錄3 各監測站溫度分布圖 191
附錄4 新莊站及忠明站各季節相關係數矩陣 192
附錄5 新莊站及小港站各季節相關係數矩陣 194
附錄6 忠明站及小港站各季節相關係數矩陣 196
附錄7 各監測站高壓迴流(HPPC)典型天氣圖及逆軌跡圖 198
附錄8 各監測站高壓推擠(HPP)典型天氣圖及逆軌跡圖 199
附錄9 各監測站鋒前暖區(WAF)典型天氣圖及逆軌跡圖 200
附錄10 各監測站弱南風(WSW)典型天氣圖及逆軌跡圖 201
附錄11 各監測站東北季風典型天氣圖及逆軌跡圖 202
附錄12 各監測站西南季風典型天氣圖及逆軌跡圖 203
附錄13 新莊站PMF執行Bootstrapping模式結果 204
附錄14 忠明站PMF執行Bootstrapping模式結果 206
附錄15 小港站PMF執行Bootstrapping模式結果 208
附錄16 口試委員意見答覆 210

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指導教授

李崇德(Chung-Te Lee)

審核日期

2013-1-29

推文