博碩士論文 107326005 詳細資訊




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姓名 蔡伊亭(I-Ting Tsai)  查詢紙本館藏   畢業系所 環境工程研究所
論文名稱 台灣都會區PM2.5化學成分與大氣光學特性
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摘要(中) 本文連結環保署2020年「細懸浮微粒(PM2.5)化學成分監測及分析計畫」在板橋、忠明(西屯)、小港測站的PM2.5 (氣動直徑小於或等於2.5 μm粒狀物)化學成分和「空氣能見度監測規劃及應用服務計畫」光學量測數據,探討影響台灣都會區大氣能見度的PM2.5化學成分及環境因子,研究過程運用PM2.5光學特性,解析各地的氣膠類型和可能的污染來源,並瞭解不同季節氣膠化學成分對於大氣的光學效應。
本文比較人工觀測、大氣消光係數量測轉換值、PM2.5化學成分估算消光係數轉換的能見度,顯示推估與人工觀測的能見度大略有相似的時間變化趨勢,但估算的能見度高於人工觀測能見度相當多,三者間差異與能見度評估方法、氣膠化合物結合型態、人工觀測目標物選取有關。各測站PM2.5化學成分普遍以有機物、硫酸銨及硝酸銨影響大氣能見度較大。在低溫高濕的環境下,大氣能見度有衰減的現象,但在高濃度的PM2.5環境下,環境濕度對能見度的影響並不顯著。從短時間的變化來看,氣膠吸光和散光係數的晝夜變化與交通排放和氣象條件相關聯,黑碳(Black Carbon, BC)小時濃度的日變化也和交通排放相關;另外,本文使用Aethalometer Model評估BC貢獻源,同樣得到以交通排放為主(約占80%)。
以雙變量條件機率函數呈現板橋、忠明(西屯)及小港測站潛在高污染來源,發現板橋測站除了車輛排放外,可能會受到工業區和焚化廠帶來的污染。忠明(西屯)測站受到西風影響時,會帶來聚集於西側的高污染源,南方則另有生質燃燒影響。小港站可能受到船舶排放、工業區、鋼鐵、煉油廠、交通污染的影響。依據氣膠光學厚度(Aerosol Optical Depth, AOD)及AE ( Ångström exponent, AE) 數值進行的氣膠分類,發現三個測站在四季都以都市型微粒為主,以車輛排放產生的微粒居多,忠明和小港站在PM2.5 >25 μg m-3時,AOD高值大多發生在高風速低相對濕度的環境下。
總結來說,大氣能見度數值會受到不同評量基礎的影響,PM2.5化學成分以有機碳、硫酸銨及硝酸銨影響大氣能見度較大,在台灣都會區影響大氣能見度主要為移動污染源和環境因子;三個測站氣膠類型大多以細小粒徑的都市型微粒為主,顯示PM2.5對台灣都會區影響重大。
摘要(英) This study associated with PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) chemical speciation at the Banqiao, Zhongming, and Xiaogang sites in “The 2020 Project of Chemical Speciation Monitoring and Analysis of Fine Particulate Matter (PM2.5)” and optical measurements in “Plan and Application of Atmospherical Visibility Monitoring Construction” to investigate PM2.5 chemical speciation and environmental factors on atmospheric visibility in Taiwan’s metropolis. This work used PM2.5 optical properties to resolve aerosol types and potential sources and revealed the optical effects of aerosol chemical components in different seasons during the study.
The atmospheric visibilities from estimated and manual observations were roughly consistent in time variation, but estimated values were much higher than manual ones from comparisons among manual observation, conversion from the atmospheric optical property, and estimates from PM2.5 chemical speciation. The differences mentioned above are related to the visibility conversion method, aerosol compound forms, and objects selected from manual observation. Organic matter, ammonium sulfate, and ammonium nitrate of PM2.5 chemical components affect atmospheric visibility predominantly. Low temperature and high relative humidity degraded atmospheric visibility significantly but turned insignificant for high PM2.5 levels. The diurnal and nocturnal variations of aerosol light absorption and scattering coefficients were associated with traffic emissions and meteorological factors. The hourly variations of black carbon (BC) in a day were also related to traffic emissions. Likewise, traffic emissions were a dominant source of BC (around 80%) estimated from the Aethalometer Model.
This study adopted conditional bivariate probability function to explore high polluting potential sources at the Banqiao, Zhongming (Xitun), and Xiaogang sites. The results showed that industrial parks and municipal incinerators might pollute the Banqiao site in addition to traffic emissions. The Zhongming (Xitun) site was influenced by the west wind transporting high polluting source contributions from the west plus additional biomass burning from the south. In comparison, the Xiaogang site was under the influence of ship emissions, industrial parks, iron and steel manufacturing, refinery, and traffic pollutions. Based on aerosol optical depth (AOD) and AE (Ångström exponent), the three sites were classified into urban-type aerosols mostly discharged by vehicle emissions in four seasons. For PM2.5 >25 μg m-3, high AOD values mainly occurred in high wind speed and low relative humidity environments at the Zhongming and Xiaogang sites.
In summary, atmospheric visibility will be affected by different assessment bases. Organic carbon, ammonium sulfate, and ammonium nitrate affected atmospheric visibility greater than other components in PM2.5 chemical speciation. Mobile sources and environmental factors influence atmospheric visibility mainly in Taiwan’s metropolis. In principle, the aerosol types at the three sites are fine urban-type aerosols, which demonstrates a significant influence of PM2.5.
關鍵字(中) ★ 細懸浮微粒(PM2.5)
★ 大氣能見度
★ 氣膠化學成分與大氣光學
關鍵字(英) ★ Fine particulate matter (PM2.5)
★ Atmospheric visibility
★ Aerosol chemical composition and the atmospheric optics
論文目次 摘要 I
Abstract III
致謝 V
目錄 VI
圖目錄 IX
表目錄 XII
第一章 前言 1
1-1 研究緣起 1
1-2 研究目的 3
第二章 文獻回顧 4
2-1 細懸浮微粒(PM2.5)的重要性 4
2-1-1 PM2.5對環境的影響 4
2-1-2 PM2.5對人體的危害 4
2-2 細懸浮微粒(PM2.5)的組成來源 6
2-2-1 PM2.5水溶性無機離子 6
2-2-2 PM2.5碳成分 7
2-2-3 PM2.5金屬元素 9
2-3 PM2.5對大氣能見度的影響 11
2-4 氣膠光學特性 13
2-4-1 氣膠吸光特性 14
2-4-2 氣膠散光特性 16
2-4-3 氣膠的混合狀態 18
2-5 氣膠光學厚度(Aerosol Optical Depth, AOD) 20
2-6 雙變量條件機率函數(CBPF) 22
第三章 研究方法 24
3-1 研究架構 24
3-2 採樣地點與時間 25
3-2-1 採樣地點 26
3-2-2 採樣時間 27
3-3 PM2.5手動採樣儀器 28
3-3-1 MetOne SASS PM2.5採樣器 28
3-3-2 MetOne E-FRM PM2.5採樣器 29
3-4 PM2.5質量濃度和化學成分分析方法 31
3-4-1 濾紙採樣前準備 31
3-4-2 水溶性無機離子分析方法 31
3-4-3 碳成分分析方法 33
3-4-4 質量濃度秤重分析 35
3-5 光學量測儀器 37
3-5-1 長光徑可見光透射儀 (Long Path Visibility Transmissometer) 37
3-5-2 室外積分式散光儀 (Open-Air Integrating Nephelometer) 38
3-5-3 黑碳多波段吸光儀 (MetOne BC-1054) 39
3-6 Ångström exponent 42
3-7 Revised IMPROVE 模擬消光係數 43
3-8 氣流軌跡模式(NOAA HYSPLIT) 46
3-8 雙變量條件機率函數CBPF法 47
第四章 結果與討論 48
4-1 數據選取 48
4-2 大氣能見度的人工與儀器觀測比較 49
4-2-1 可見光透射儀與(散光儀+吸光儀)的消光係數比較 54
4-3 氣膠化學成分與大氣消光係數 58
4-3-1 Revised IMPROVE方程式推估大氣消光係數與貢獻因子 58
4-3-2 大氣消光係數與氣象因子 63
4-3-3 大氣能見度與相對濕度 67
4-3-4 大氣消光係數與Revised IMPROVE方程式推估結果 70
4-4 氣膠光學參數與PM2.5化學成分 72
4-4-1 光學參數日變化 76
4-4-2 單一散射反照率(Single-scattering albedo, SSA) 83
4-5 氣膠黑碳與吸光係數 86
4-5-1 氣膠吸收指數(Absorption Ångstrom Exponent, AAE) 86
4-5-2 多波段黑碳判別污染源 93
4-6 雙變量條件機率函數CBPF法 97
4-6-1 板橋站 97
4-6-2 忠明(西屯)站 101
4-6-3 小港站 105
4-7 PM2.5與AOD 109
4-7-1 氣膠化學成分與 AOD 109
4-7-2 氣象條件與AOD 123
4-8 三個城市間大氣能見度特質 127
4-8-1 共通性 127
4-8-2 差異性 128
第五章 結論與建議 131
5-1 結論 131
5-2 建議 133
參考文獻 134
附錄一 各測站2019/12月~ 2020/11月逆推氣流軌跡圖 149
附錄二 各測站PM2.5氣流軌跡來源 161
附錄三 利用CBPF及風花圖判別可能污染來源 164
附錄四 潛在污染源地圖 188
附錄五 口試委員意見與回覆 191
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李崇德、周崇光、張士昱、蕭大智、許文昌(2020)” 109年度細懸浮微粒(PM2.5)
化學成分監測及分析計畫”,期末報告(定稿本),環保署,台北,
    109年11月
指導教授 李崇德(Chung-Te Lee) 審核日期 2021-9-27
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