台灣南部高屏溪河灘地風蝕揚塵事件日（ADEs）是由颱風環流或熱對流吹拂河床裸露地表土所形成新興災害。本研究係沿著高屏溪高灘地設置四個手動採樣點，分別於例行日2012年7月7-14日、2012年1次及2013年6次河灘地風蝕揚塵事件日，以高流量採樣器及衝擊板同時採集PM2.5（空氣動力直徑≤2.5μm）和PM2.5-10（空氣動力直徑2.5-10μm），並合併此兩不同粒徑濃度解析PM10（空氣動力學直徑≤10μm）質量濃度。另沿著高屏溪河床裸露地，擇定5處易產生風蝕揚塵區位，採集代表性表土樣品，以標準篩(Tyler 400 mesh (dp < 38 μm))進行篩分析後，坋土於在懸浮室內進行再懸浮作業，並同時採集PM2.5和PM2.5-10樣品。分別就風蝕揚塵樣品及河川裸露灘地表土樣品則進行化學成份分析，項目包括13種金屬元素，9種水溶性離子物種及2種碳成份。
採樣結果顯示，河灘地風蝕揚塵事件期間PM10質量濃度明顯高於例行日PM10質量濃度，且在風蝕揚塵發生後3-4小時內即會達到峰值。又海鹽微粒（SSs）約分別佔3.56％-5.17％及11.66％-16.47％。河灘地風蝕揚塵事件期間，氯損失百分比（6.33％-14.12％）明顯低於例行採樣區間（29.49％-40.38％），此現象說明，河灘地風蝕揚塵事件期間，即使大量鹼性風蝕揚塵為PM10主要來源，然而風蝕揚塵和海鹽微粒在傳輸過程中進行化學置換反應後，高屏溪沿岸粒狀物環境空氣品質仍係以酸性氣溶膠為主。在2013年河灘地風蝕揚塵事件日中，依據環保署於高屏溪沿岸所設立四座空氣質量監測站氣象資料，河灘地風蝕揚塵事件依盛行風向可區分為南風和西北風等兩個型態，而進一步將風蝕揚塵樣品及表土樣品金屬元素分析結果，分別以無母數統計方法包含Wilcoxon rank-sum test與Kruskal-Wallis test進行檢驗，推導可用來判定高屏溪河灘地風蝕揚塵事件日影響金屬元素判定指標，地殼元素（Fe，Ca或Al）與參考元素（Cd）的質量濃度比值在風蝕揚塵發生時明顯高於風蝕揚塵發生後；而在PM2.5-10及PM2.5兩種粒徑中，又以在PM2.5-10中Fe / Cd、Ca / Cd和Al / Cd的質量濃度比值明顯更高於其在PM2.5；此些指標中，係以（Fe / Cd）2.5-10為最適合用來作為判定指標，可用於有效確認高屏溪河灘地風蝕揚塵對環境空氣品質影響。此外，雖然在河灘地風蝕揚塵發生時PM2.5 / PM10的質量濃度比值分別僅為0.05-0.20，但風蝕揚塵發生時PM2.5濃度高於風蝕揚塵發生後3-3.6倍，因此風蝕揚塵發生時，風蝕揚塵應仍為主要PM2.5貢獻來源之一，上述研究結果有效提供高屏溪河灘地風蝕揚塵基本特性資訊。
由PM10及PM2.5個別CMB受體模擬結果顯示，河灘地風蝕揚塵和海鹽皆是揚塵揚起過程中PM10內主要成份，在河灘地風蝕揚塵發生時及發生後，風蝕揚塵貢獻量為11.5％-33.1％及7.2％-23.0％，在河灘地風蝕揚塵發生後，少量粒徑更細揚塵微粒仍然懸浮在環境空氣中。在PM2.5中，風蝕揚塵在南風型河灘地風蝕揚塵發生時所占比例為6.2％-15.7％;在西北風型河灘地風蝕揚塵發生時所占比例為1.3％-17.4％，而不論在南風型和西北型風蝕揚塵期間，PM2.5中風蝕揚塵比例皆低於其在PM10中比例。風蝕揚塵中主要係以PM2.5-10為主而非PM2.5，係因PM2.5主要生成機制係前驅物經高溫蒸氣和低揮發性化合物進行化學轉化為PM2.5。此外，南風型及西北風型河灘地風蝕揚塵發生後，生質燃燒的貢獻率為7.6％-13.9％及5.6％-13.3％，這現象說明在夏天季節高屏溪沿岸農業廢棄物的露天焚燒為常態汙染情事。由上述PM10受體模式分析結果，風速和風向直接影響不同污染物貢獻百分率，因此導致南風型及西北風型河灘地風蝕揚塵不同採樣點，其主要貢獻者亦明顯不同。

Aeolian dust episodes (ADEs) are emerging disasters occurred from the bare lands of the Kaoping River in southern Taiwan due to typhoons or thermal convections. Four manual sampling sites located along the Kaoping River were conducted to collect PM10 (aerodynamic diameter ≤ 10 μm) with high-volume samplers in an ADE and on regular days in 2012, as well as PM2.5 (aerodynamic diameter ≤ 2.5 μm) and PM2.5–10 (aerodynamic diameter 2.5–10 μm) in six ADEs in 2013. Additionally, soil samples were collected at five potential locations on the surface of bare lands along the Kaoping River Valley. The five soil samples were completely mixed and then sieved with a Tyler 400 mesh (dp < 38 μm) and then resuspended using a dry powder atomizer in a resuspension chamber. Each soil sample could be divided into two independent fractions (i.e., PM2.5 and PM2.5–10). With regard to the ADE and alluvial samples, this study investigated on their chemical contents, including a total of 13 metallic elements, 9 water-soluble ionic species, and 2 carbonaceous species.
Hourly averaged PM10 concentrations increased drastically from noon to evening, and maximum PM10 concentration levels were reached within 3–4 hours. Sea-salt particles (SSs) in PM10 accounted for 3.56%-5.17% on regular days and 11.66%-16.47% during the ADE. Cl- deficit percentages during the ADE (6.33%-14.12%) were much lower than those on regular days (29.49%-40.38%), indicating acidic particles mainly produced by chemical reactions of acidic aerosols with aeolian dust and SSs. Even alkaline aeolian dust is the dominant source of PM10 during the ADE; the atmospheric particles are attributable to acidic particles in the air. Furthermore, ADEs were clustered by the prevailing wind direction as southern and northwestern types according to four Taiwan Environmental Protection Administration air quality monitoring stations along the Kaoping River in southern Taiwan in 2013. With metallic element analysis and nonparametric statistical methods of Wilcoxon rank-sum test and Kruskal-Wallis test, this study successfully derived the metallic indicators of ADEs. The mass ratios of crustal elements (Fe, Ca, or Al) to reference element (Cd) obtained during the ADEs were much higher than those obtained after the ADEs. High mass ratios of Fe/Cd, Ca/Cd, and Al/Cd in PM2.5-10 were observed over the influenced areas of ADEs. Among them, (Fe/Cd)2.5-10 was proven as the best indicator which can be applied to effectively validate the existence of ADEs and evaluate their influences on ambient air quality. Moreover, PM2.5 concentrations during the ADEs were 3-3.6 fold higher than those after the ADEs. PM2.5 should be a contributor to AD, even though the mass ratios of PM2.5/PM10 ranged from 0.05 to 0.20 during the ADEs. Our findings provide valuable information regarding the characteristics of the AD during the ADEs in the Kaoping River.
The CMB receptor modeling results that aeolian dust and sea-salts in PM10 were major components of atmospheric particles during the cluster ADEs. The contribution of AD emitted from the bare lands to PM10 concentration was in the range of 11.5%-33.1% along the Kaoping River during the ADEs as well as 7.2%-23.0% after the ADEs. A small amount of finer aeolian dust emitted from the bare lands of the riverbed could still be suspended in the ambient air during the ensuing the ADEs. The AD in PM2.5 ranged from 6.2% to 15.7% during the S-type ADEs and ranged from 1.3% to 17.4% during the NW-type ADEs. Both of them were less than that of PM10 during the S- and NW-type ADEs. The AD was mainly enriched in PM2.5-10 rather than PM2.5 since the formation of PM2.5 was directly related to the process that high-temperature vapors and low volatility compound chemical transformed to PM2.5. Additionally, the contribution of biomass burning rose significantly in the range of 7.6% to 13.9% after the S-type ADEs and 5.6% to 13.3% after the NW-type ADEs, suggesting the open burning of agricultural debris is commonly observed along the Kaoping River in summer. Based on the source apportionment of PM10, the wind speed and wind direction were directly relevant to different contributors, so the S- and NW-type ADEs cause the difference of major contributors for different sampling sites.

論文審定書………………………………………………………………………i
中文摘要 ………………………………………………………………………ii
Abstract………………………………………………………………………iv
Contents………………………………………………………………………vi
Figure of Contents………………………………………………………………………ix
Table of Contents………………………………………………………………………xi
Chapter I Introduction………………………………………………………………………1
1.1 Motivation of Present Study………………………………………………………………………1
1.2 Objectives………………………………………………………………………3
1.3 Scopes………………………………………………………………………4
Chapter II Literature Review………………………………………………………………………6
2.1 Background of Ambient Air Quality and its Neighboring Surroundings in Kaoping River ………………………………………………………………………6
2.2 Mechanism and Influence of Aeolian Dust………………………………………………………………………8
2.3 Size Distribution of Atmospheric Particles………………………………………………………………………12
2.4 Chemical Characteristics and Fingerprints of Atmospheric Particles………………………………………………………………………15
2.5 Sources of Atmospheric Particles………………………………………………………………………18
Chapter III Experimental Methods………………………………………………………………………22
3.1 Sampling Protocol………………………………………………………………………22
3.1.1 Sampling Protocol #1………………………………………………………………………22
3.1.2 Sampling Protocol #2………………………………………………………………………26
3.2 Collection of Alluvium Soils from the Surface of Bare Lands along the Kaoping River………………………………………………………………………26
3.3 Chemical Analysis………………………………………………………………………28
3.3.1 Analysis of Water-Soluble Ionic Species………………………………………………………………………28
3.3.2 Analysis of Metallic Elements………………………………………………………………………29
3.3.3 Analysis of Carbonaceous Species………………………………………………………………………29
3.3.4 Quality Assurance and Quality Control………………………………………………………………………30
3.4 Analytical Tools for the Meteorological Data and Chemical Constituents……………………………………………………………………… 31
3.4.1 Weather Research and Forecasting Model (WRF)………………………………………………………………………31
3.4.2 Space Analysis Software (SURFER)………………………………………………………………………31
3.4.3 Chemical Mass Balance (CMB) Receptor Model………………………………………………………………………31
3.4.4 Enrichment Factors………………………………………………………………………33
3.4.5 Reconstruction Methods of PM10………………………………………………………………………34
3.4.6 Statistical Analysis………………………………………………………………………36
Chapter IV Influences of Aeolian Dust on Ambient Particulate Air Quality along Kaoping River - A Case Study of Typhoon Doksuri in 2012………………………………………………………………………37
4.1 Spatiotemporal variation of PM10 concentration on regular days and during and after the ADE………………………………………………………………………37
4.2 Water-soluble Ions of PM10 and their Characteristics during and after the ADE in 2012………………………………………………………………………39
4.3 Non-Sea-Salt and Sea-Salt Water-Soluble Ionic Species of PM10 on Regular Days and during and after the ADE in 2012 42
4.4 Metals of PM10 on Regular Days and during and after the ADE in 2012………………………………………………………………………47
4.5 Carbonaceous Species of PM10 on Regular Days and during and after the ADE in 2012………………………………………………………………………49
4.6 Reconstruction of PM10 on Regular Days and during and after the ADE in 2012………………………………………………………………………51
4.7 Fingerprint of Resuspended Alluvium Soils Analyzed based on PM10……………………………………………………………53
4.8 Surface Wind Fields of the ADE during the Typhoon Doksuri………………………………………………………………………55
4.9 Hot Spots of Kaoping River Developed by the ADE in 2012………………………………………………………………………56
4.10 Source Apportionment of PM10 during and after the ADE………………………………………………………………………60
Chapter V Metallic Characteristics of PM2.5 and PM2.5–10 in Clustered Aeolian Dust Episodes Generated from Bare Lands along Kaoping River during Typhoon Season in 2013..….………… ……………….……………..64
5.1 Types of Clustered Aeolian Dust Episodes Defined by Surface Wind Fields………………………………………………………………………64
5.2 Roles of PM2.5 and PM2.5–10 during and after the Clustered ADEs………………………………………………………………………70
5.3 Water-soluable ions of PM2.5 and PM2.5-10 in the Clustered ADEs in 2013………………………………………………………………………73
5.4 Carbonaceous Contents of PM2.5 & PM2.5-10 in the Clustered ADEs in 2013………………………………………………………………………77
5.5 Metallic Elements of PM2.5 & PM2.5-10 for the Clustered ADEs in 2013………………………………………………………………………79
5.5-1 Metallic Elements of PM2.5 and PM2.5-10 in Alluvium Soils………………………………………………………………………82
5.5.2 Enrichment Factors of Metallic Elements in PM2.5 and PM2.5–10………………………………………………………………………85
5.5.3 Effective Metallic Indicator for Identifying the Clustered ADEs in 2013………………………………………………………………………87
5.6 Source Apportionment of PM2.5 and PM10 for the Clustered ADEs………………………………………………………………………91
Chapter VI Conclusions………………………………………………………………………95
6.1 Conclusions………………………………………………………………………95
6.2 Suggestions………………………………………………………………………98
References……………………………………………………………………. 99
Appendix A Calibration Curves of Chemical Analytical Data...........….……..109
Appendix B Chemical Composition of PM10 Resulted from the ADE Induced byTyphoon Doksuri…..…………….…………...……………...112
Appendix C Chemical Composition of PM2.5 and PM2.5-10 Resulted from the S- and NW-type ADEs....…..………………………….…………...114
Appendix D Abbreviation List....…..………………………….……………...117

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