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研究生:姜詠禎
研究生(外文):Chiang, Yung-Chen
論文名稱:應用受體模式解析台灣空品測站的細懸浮微粒污染來源
論文名稱(外文):A Study of The Source Apportionment of Ambient Fine Particles at Taiwan Air Monitoring Stations by Using Receptor Models
指導教授:蔡春進蔡春進引用關係
指導教授(外文):Tsai, Chuen-Jinn
口試委員:陳仁焜陳裕政蔡春進
口試委員(外文):Chen, Jen-KunChen, Yu-ChengTsai, Chuen-Jinn
學位類別:碩士
校院名稱:國立交通大學
系所名稱:環境工程系所
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:108
語文別:中文
論文頁數:155
中文關鍵詞:PM2.5受體模式正矩陣因子法氣流逆軌跡模式條件機率函數
外文關鍵詞:PM2.5 Receptor ModelsPositive Matrix Factorization methodHYbrid Single-Particle Lagrangian Integrated TrajectoryConditional Probability Function
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細懸浮微粒(氣動直徑小於或等於2.5 m粒狀物質, PM2.5)對於評估空氣品質、健康風險、制定相關污染源管制策略、環境變遷有重大的影響。本文為研究台灣六大空品區PM2.5之可能污染源以及污染事件成因。本文使用行政院環境保護署於2017年1月至2018年12月在台灣板橋、忠明、斗六、嘉義、小港、花蓮環保署空氣品質監測站,所觀測之PM2.5化學成分監測數據,並使用正矩陣因子法(Positive Matrix Factorization, PMF)推估污染來源貢獻,配合氣流逆軌跡模式(HYbrid Single-Particle Lagrangian Integrated Trajectory, HYSPLIT)與條件機率函數(Conditional Probability Function, CPF)結合風向資料,推估污染源來向。
研究結果顯示由北而中而南空品區之PM2.5質量濃度,都以夏季最低,質量濃度較高則發生於春季、冬季,造成季節差異可歸因於污染事件成因差異,例如:北部冬季及春季的境外傳輸影響、中部秋季受到上風污染區域傳輸與環境擴散不佳、南部冬季環境擴散不佳,而花蓮測站在任何季節平均PM2.5質量濃度都是各站最低,顯示環境擴散條件良好。
PMF受體模式解析共有9類因子,分別為二次硫酸鹽、二次硝酸鹽、地殼揚
塵、海鹽、交通排放、工業等金屬冶煉製程、生質燃燒與焚化、重油燃燒及未定量,其中以二次硫酸鹽、二次硝酸鹽為前二高貢獻因子。於板橋測站、小港測站與花蓮測站有較高的海鹽占比;重油燃燒因子在小港測站也相較其他測站有較高的貢獻;嘉義測站與斗六測站除了生質燃燒因子外,其餘因子占比相似,當雲嘉及高雄地區擴散不佳時,污染衍生物在地影響程度大。
PMF受體模式推估結合HYSPLIT及CPF,顯示在低污染時期污染貢獻源主
要來自本地排放源,高污染時期受到環境擴散條件不佳或境外汙染傳輸影響。
Atmospheric suspended fine particles (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm, PM2.5) play an important role in air quality and health risk assessment, setting up control strategies about sources pollutants, and environmental change. This study aims to investigate source contributions and causes of polluting events by observing PM2.5 mass and chemical component concentrations at the stations of Taiwan Environmental Protection Administration (TEPA) at the Banqiao, Zhongming, Douliu, Chiayi, Xiaogang, and Hualien stations from January 2017 to December 2018. Contributing factors (polluting sources) were apportioned by Positive Matrix Factorization (PMF) method and validated by HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Conditional Probability Function (CPF) with wind direction for high contributing sources.
The results show that PM2.5 mass levels were lowest at all sampling sites in summer, and highest at stations in spring and winter. These seasonal variations can be attributed to causes of polluting events, for example, transboundary transports in northern Taiwan in spring, upwind regional transport and bad environmental ventilation in middle Taiwan in autumn, and bad environmental ventilation in southern Taiwan in winter.
PM2.5 source apportionment was characterized by PMF analysis, and the results inferred nine major sources: Secondary sulfate, Secondary nitrate, Crustal dust, Sea salt, Traffic-related emission, Industry, Biomass combustion, Oil combustion and Unknown.
The source apportionment from PMF coupling with HYSPLIT and CPF reveals that the emissions from local sources are mainly responsible during the low polluting period. In contrast, due to bad environmental ventilation or transboundary transport during the comparatively higher polluting period.
摘要 I
Abstract II
誌謝 IV
目錄 V
圖目錄 VII
表目錄 X
一、前言 1
1.1 粒狀懸浮微粒來源與特性 1
1.1.1 微粒中離子成分 2
1.1.2 微粒中碳成分 3
1.1.3 微粒中金屬成分 4
1.2 汙染來源解析相關研究 6
1.3 研究目的 8
二、研究方法 9
2.1 大氣懸浮微粒採集及成分分析 9
2.2 大氣懸浮微粒來源之分析 10
2.2.1 正矩陣因子法(PMF) 10
2.2.2 條件機率函數(CPF) 15
2.2.3 逆軌跡模式 16
2.2.4 富集因子 17
三、研究結果與討論 18
3.1 大氣懸浮微粒質量濃度變化趨勢 18
3.1.1 大氣懸浮微粒質量濃度分析結果 18
3.1.2 污染物濃度與氣象因子 38
3.2 大氣懸浮微粒元素組成和濃度變化趨勢 74
3.2.1 富集因子分析 74
3.2.2 大氣懸浮微粒元素組成 79
3.3 受體模式解析污染來源 91
3.3.1 板橋測站 91
3.3.2 忠明測站 100
3.3.3 斗六測站 108
3.3.4 嘉義測站 116
3.3.5 小港測站 124
3.3.6 花蓮測站 132
3.4 各測站成分組成與污染源推估結果比較 140
3.4.1 主要化學成分區域及季節變化 140
3.4.2 金屬元素成分占比及季節變化 146
3.4.3 汙染來源推估比較 149
四、結論 150
參考文獻 152
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