本研究於2008年5月至2009年4月期間，藉由高流量空氣採樣器在中山大學校園內收集高雄近岸大氣中之多環芳香烴化合物(Polycyclic aromatic hydrocarbons, PAHs)，以GC/MS分析其濃度，配合多環芳香烴化合物特徵比與相關性分析、群集分析(Hierarchical Cluster Analysis, HCA) 、主成分分析(Principal Component Analysis, PCA)等統計方法來判別其可能來源。最後利用資料群集處理技術(Group Method of Data Handling, GMDH)進行建模，篩選出影響大氣多環芳香烴化合物之主要因子，透過模式來驗證採樣期間多環芳香烴化合物之趨勢變化，並預測前一年度大氣多環芳香烴化合物之變化情形。

採樣期間總多環芳香烴（氣相＋固相）年平均濃度為14.2 ng/m3，以六月濃度最低（2.22 ng/m3），一月濃度最高（32.4 ng/m3），整體趨勢來看，呈現冬季濃度高於夏季。在日夜間濃度變化方面，夜間平均濃度（19.1 ng/m3）高於日間平均濃度（11.1 ng/m3）。所測得多環芳香烴化合物濃度中以氣態為主要貢獻，氣相多環芳香烴環數分佈情形主要以低分子量2、3-Ring為主，而4、5-Ring多以氣/固相共存，6、7-Ring之高分子量化合物則以顆粒態佔主要貢獻。另一方面，當中元節、沙塵暴事件日發生時，不同於一般例行性採樣結果，單位總懸浮微粒上所含之多環芳香烴濃度隨懸浮微粒濃度增加而增加。

於相關性分析結果中，氣相與固相多環芳香烴對溫度、濕度呈現顯著負相關，表示多環芳香烴濃度受季節性之影響有明顯變化；空品資料部分則以SO2、NOx、PM10等呈顯著正相關，顯示污染物來源可能為當地交通工具排放及船舶運輸導致。此外，多環芳香烴化合物特徵比分析結果推測其污染來源傾向於柴油燃燒及汽油燃燒部分，而群集分析（HCA）及主成分分析（PCA）分析結果則說明主要與柴油引擎排放及油品燃燒有關。

最後以資料群集處理技術（GMDH）建模，將氣象資料與空品資料作輸入值進行模式運算，經模式篩選後，發現所挑選出之影響因子與相關性分析中顯著相關部分相似，且模式預測效能皆為合理的評估標準內。以2008~2009年GMDH演算結果預測2007~2008年PAHs濃度變化，於氣相結果中，除中元節時期外，部分預測值普遍略高出實測值。固相則是秋、冬季預測結果皆高估實測值許多。可能因2007~2008年氣象與空品資料變化不同於2008~2009年，如氣象資料於夏季期間，夏季輸入資料較穩定，參數無太大變化，實際上也相對影響污染物擴散導致。

Coastal atmospheric concentrations of polycyclic aromatic hydrocarbons (PAHs) were measured at top of a building on campus of the National Sun Yat-sen University of Kaohsiung. Concentrations of 52 PAH compounds were analyzed in both gaseous and particulate phases in air samples collected from May 2008 through April 2009. PAHs diagnostic, Hierarchical Analysis (HCA) and Principal Component Analysis (PCA) were employed to determine the potential sources of PAHs. The Group Method of Data Handling (GMDH) was applied to relate atmospheric PAH concentration to air quality variables like SO2 and O3, as well as meteorological conditions like precipitation and temperature.
During the sampling period the mean of total PAH concentrations was 14.2 ng/m3. Over all, PAH concentrations in winter were higher than summer, with the lowest concentrations of PAHs occurred in June (2.22 ng/m3), while the highest occurred in January (32.4 ng/m3). The night-time concentrations of PAHs are higher than daytime. The 2, 3-ring PAHs were mostly present in the gaseous phase, 4-ring were dominant in the gaseous phase, while 5, 6, 7-ring PAHs were mostly present in the particulate phase. During the Ghost festival and Asian dust storm events, atmospheric concentrations of PAHs and PAHs/TSP ratios were both found increased.
Meteorological conditions, such as temperature and relative humidity, may strongly affect PAH concentrations, the gaseous and particulate PAHs correlate significantly with SO2, NOx, and PM10. Result from analyses of diagnostic rations, HCA and PCA, indicates the major sources of PAHs include gasoline and diesel exhaust.
By using GMDH, a reasonable appraisal index was obtained for the pattern forecast potency with the meteorological and air quality variables. The GMDH algorithm obtained during 2008~2009 was tested in predictions and compared with what measured in 2007~2008.

摘要
Abstract
圖目錄 IV
表目錄 VII
附錄 IX
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 PAHs之物理及化學特性 3
2-2 PAHs的來源 8
2-3 多環芳香烴化合物之毒理特性 9
2-4 多環芳香烴化合物的化學指紋鑑識 11
2-5 環境中背景因素之影響 12
2-6高雄地區環境及氣候概況 13
2-6-1 氣溫 15
2-6-2 風速 16
2-6-3 風向 17
2-6-4 降雨量 18
2-6-5 相對溼度 19
2-7 高雄地區空氣汙染物濃度變化 19
2-7 資料群集處理技術(Group Method of Data Handling, GMDH) 22
第三章 實驗材料與研究方法 24
3-1 採樣設計 24
3-1-1 採樣地點 24
3-1-2 採樣時間 24
3-2 實驗方法與採樣設備 26
3-2-1 材料 26
3-2-2 儀器設備 26
3-3 試藥及器具前處理 27
3-4 採樣方法 28
3-5 樣品分析 28
3-5-1 PAHs分析 28
3-6 品保及品管（QA/QC） 29
3-6-1 空白實驗 29
3-6-2 方法偵測極限 （Method Detection Limit, MDL） 30
3-6-3 擬似標準品回收率 30
3-7 階層群集方法（Hierarchical Cluster Analysis, HCA） 35
3-8主成份分析法 （Principal Component analysis, PCA） 35
3-9 資料群集處理技術 (Group Method of Data Handling, GMDH) 36
3-9-1 GMDH演算法之基本參數設定與說明 39
3-9-2 GMDH演算法驗證績效指標 42
第四章 結果與討論 44
4-1大氣中多環芳香烴濃度 44
4-1-1 總懸浮微粒濃度 44
4-1-2 總多環芳香烴濃度 48
4-1-3 多環芳香烴日夜濃度變化 55
4-1-4 大氣中各環數多環芳香烴濃度分佈 56
4-1-5 大氣中氣-固相多環芳香烴濃度分佈 60
4-1-6 多環芳香烴濃度與背景參數影響條件之相關性 64
4-2大氣中多環芳香烴來源分析 69
4-3 階層群集分析（Hierarchical Cluster Analysis, HCA） 77
4-4 主成分分析（Principal Component Analysis , PCA） 80
4-5 資料群集處理技術（Group Method of Data Handling, GMDH） 88
4-5-1 氣相多環芳香烴預測結果 88
4-5-2 固相多環芳香烴預測結果 91
4-5-3 氣、固相預測結果分析 94
4-5-4 實際案例預測結果 97
第五章 結論與建議 102
5-1 結論 102
5-2 建議 103
參考文獻 105
附錄 112

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