在大氣環境中，多環芳香烴化合物 （Polycyclic aromatic hydrocarbons, PAHs）主要來自不完全燃燒或是熱裂解過程，其中一些化合物已被鑑定為對人體健康具有高致癌和致突變性的潛在能力。長期暴露在PM2.5下亦已被認為和肺癌、心血管疾病死亡率的增加有關。在臺灣，石油化學和鋼鐵工業主要座落於南部地區，所衍生出的空氣污染問題一直受到研究學者之關注。因此本研究將分為二個部分來探討。首先，藉由南臺灣黑潮圈地區大氣PAHs的分佈情形，來釐清其可能污染來源，及在大氣傳輸上所扮演的角色。其次，結合大氣PM2.5-PAHs量測數據與環保署即時監測站的空品氣象監測資料，建立PM2.5-PAHs小時濃度的網格預測模式，並驗證其適切性。
在南臺灣黑潮圈地區大氣PAHs分佈方面，研究結果指出所有測站總PAHs濃度(氣相+固相)均呈現冬季最高，夏季最低的季節性變化趨勢，其夏季濃度範圍為0.87±0.36-17.7±2.88 ng/m3，秋季為1.21±0.32-65.1±57.4 ng/m3 和冬季為　2.41±1.85-40.8±6.97 ng/m3；在PAHs濃度區域變化方面，都會型測站大氣總PAHs濃度最高，比都會海岸型測站高約2-4倍，高於鄉村海岸型測站約4-26倍，約為離島海岸型測站17-54倍高。透過大氣PAHs成分組成、PAHs特徵比值及主成分分析結果，可將南臺灣黑潮圈地區大氣PAHs來源分為交通來源、工業來源與自然土壤來源三類。另外，藉由氣團逆軌跡傳輸路徑的分析亦證實冬季期間來自臺灣西南部的污染氣團是相當重要的人為PAHs污染貢獻來源，其他季節則未發現此一情形。顯示臺灣南部大氣PAHs之跨境傳輸對離島海域具有決定性的影響。
本研究同時利用空品和氣象即時監測資料為基礎，結合現地採樣實測資料，建構出PM2.5-PAHs小時濃度的網格預測模式，並驗證其適切性。結果顯示所有採樣測站PM2.5-PAHs實測值與模式預測值有顯著的相關性（n=92, R=0.817**, p<0.01）。雖然採樣期間可能受到室內環境其他PAHs污染源的干擾，但52位個案其個人環境採樣72小時實測值與72小時暴露平均預測值仍有良好的顯著相關性（R=0.729**, p<0.01）。在空間季節性變化分析方面，可以發現各季節PM2.5-PAHs之污染熱區大致可分為二個地方，一處為北高雄左營、仁武地區附近，另一處則為南高雄前鎮、小港地區一帶為主，推測這些可能亦是與當地交通和工業活動來源有關。本研究相信利用PM2.5-PAHs網格預測模式可以針對個人暴露量作為一個完善的監控工具，進而評估在空氣污染下造成的健康風險。

關鍵字：多環芳香烴、黑潮圈、主成分分析、氣團逆軌跡、跨境傳輸、PM2.5-PAHs網格預測模式

Atmospheric Polycyclic aromatic hydrocarbons (PAHs) are compounds mainly result from incomplete combustion or pyrolysis processes, which have been identified as with high carcinogenic and mutagenic potential for human health. Long-term exposure to particulate matter (PM), especially for PM2.5, has been demonstrated consistently associating with incidences of lung cancer and cardiovascular mortality. South Taiwan is the area accommodating most of petrochemical and steel industries of Taiwan, and its air quality has been concerned for decades. The aims of this study are: (1) to investigate the temporal and spatial distributions of atmospheric PAHs in the Kuroshio Sphere of southern Taiwan, and to identify PAHs sources for understanding the effects of atmospheric air mass transport on the study area. (2) to develop a new modeling strategy in simulating, on an hourly basis, grid-scale PM2.5-PAHs levels, through measured PM2.5-PAHs data incorporating real-time data from air monitoring sites of EPA.
In terms of the temporal and spatial distribution of atmospheric PAHs in the Kuroshio Sphere of southern Taiwan, the results indicated higher PAHs concentrations occurred in the winter and autumn. The concentration ranges of PAHs were 0.87±0.36-17.7±2.88 ng/m3 in summer, 1.21±0.32-65.1±57.4 ng/m3 in autumn and 2.41±1.85-40.8±6.97 ng/m3 in winter, respectively. The concentrations at the urban site were 2-4 times of the urban coastal site, 4-26 times of rural coastal site and 17-54 times of offshore island site. The PAH compositional pattern, diagnostic ratios and principal component analysis indicated that the major sources of PAHs in the study area can be classified into three categories. The first source is vehicular emissions (gasoline and diesel) contributed from the local traffic, the second is from natural soils, and the third is attributed to the industrial activities including coke oven and incinerator emissions. The results from back trajectories also demonstrated that atmospheric PAHs were produced by local sources but were also influenced by transboundary movement of terrestrial pollutants.
In terms of PM2.5-PAHs grid-scale model construction, the results revealed good correlations between the predicted and the measured PM2.5-PAHs concentrations at all sites (n=92, R=0.817**, p<0.01) and each site. The predicted values of 72-hr personal exposure for 52 cases were found significantly (R=0.729**, p<0.01) correlated with those analyzed from portable personal monitors, even though interferences from indoor should be noted. Two PM2.5-PAHs hot spot areas in the seasonal contour map were observed: one at northern Kaohsiung near Zuoying and Renwu area, and the other at the southern Kaohsiung near Qianzhen and Xiaogang area. The sources of PM2.5-PAHs at both sites are related to local traffic sources and industrial activities. Overall, the PM2.5-PAHs grid-scale model could provide a useful and versatile tool to apply in personal exposure analysis and in the health risk assessment of air pollution.

Keywords: PAHs, Kuroshio Sphere, Principal component analysis, Back trajectories, Transboundary movement, PM2.5-PAHs grid-scale model

論文審定書 i
摘要 ii
Abstract iv
目錄 vi
表目錄 ix
圖目錄 x
第一章　前言 1
1-1　研究動機 1
1-2　研究目的 2
第二章　文獻回顧 3
2-1　多環芳香烴（PAHs）概述 3
2-1-1　多環芳香烴之特性 3
2-1-2　多環芳香烴之來源 5
2-2　多環芳香烴之氣/固分配 5
2-3　大氣多環芳香烴相關研究 6
2-4　PM2.5概述 7
2-5　PM2.5之來源 7
2-6　PM 2.5對人體健康之影響 10
2-7　GIS地理資訊系統內插方法的應用 11
第三章　南臺灣黑潮圈大氣PAHs時空分佈現況 14
3-1　研究背景 14
3-2　材料與方法 15
3-2-1　採樣測站設置 15
3-2-2　空氣樣品採集 15
3-2-3　樣品前處理步驟與定量分析 17
3-2-4　品管與品保（QA/QC） 19
3-3　結果與討論 21
3-3-1　大氣總PAHs濃度變化 21
3-3-2　大氣PAHs 的氣/固分配 23
3-3-3　大氣PAHs 成分組成 27
3-3-4　大氣PAHs來源分析－PAHs特徵比值 31
3-3-5　主成分分析（Principal Component Analysis, PCA） 34
3-3-6　冬季大氣跨境傳輸案例分析 41
3-7　小結 45
第四章　PM2.5-PAHs網格預測模式的建立與應用 46
4-1　研究背景 46
4-2　材料與方法 47
4-2-1　環境採樣測站設置 47
4-2-2　個人環境暴露採樣設置 47
4-2-3　空氣品質與氣象參數即時監測資料收集 48
4-2-4　樣品前處理步驟與定量分析 49
4-2-5　品管與品保（QA/QC） 50
4-3　結果與討論 52
4-3-1　大氣懸浮微粒（PM2.5和PM10）及PM2.5-PAHs之濃度變化 52
4-3-2　懸浮微粒實測值與空品測站監測數據之相關性 54
4-3-3　PM2.5-PAHs來源分析 54
4-3-4　PM2.5-PAHs與空氣污染物、氣象參數之相關性 54
4-3-5　PM2.5-PAHs 網格預測模式之建構 59
4-3-6　PM2.5-PAHs網格模式驗證評估及其應用 61
4-4　小結 67
第五章　結論與建議 68
5-1　結論 68
5-2　建議 70
參考文獻 71
附錄1　氣相PAHs空白試驗及方法偵測極限(ng) 79
附錄2　固相PAHs空白試驗及方法偵測極限(ng) 81
附錄3　各採樣地點溫度與logKP值的線性關係logKp=m(1/T)+b 83
附錄4　PM2.5石英濾紙空白試驗及方法偵測極限(ng) 84
個人簡歷 85

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