臺灣博碩士論文加值系統

在2010年二月到四月泰國清邁地區的乾燥季節期間，在三個不同的地點進行兩時期密集採樣，採集PM10氣膠微粒，探討氣膠水溶性無機鹽類，羧酸，醣醇類的質量濃度特性差異與可能的污染來源。結果發現清邁市區PM10氣膠的有機及無機物種濃度總是比郊區及山林地區的濃度為高，顯示市區有較多的污染傳入。醋酸是最豐富的單元酸，再者為甲酸，草酸是兩時期最主要的二元羧酸。在PM10事件日，PM10中羧酸的質量濃度比非事件日時高。在白天時期，因化石燃料的排放和生質燃燒過程的污染物，在大氣光化環境下，形成羧酸微粒。脫水內醚醣(Levoglucosan，Levo)和阿拉伯醇(arabitol)是醣醇類的主要成分，兩者在山林採樣點的PM10微粒中佔 0.53-1.48%，顯示山林間存在生質燃燒。Levoglucosan在PM10事件日的夜晚都發現高質量濃度，顯示生質燃燒大部分發生在夜晚。此外，氣膠中醋酸和甲酸的比值(A/F)大於1，同時顯示生質燃燒或車輛排放出的廢氣是主要的污染來源。而在兩時期，malonic/succinic 的比值介於0.94-1.72，顯示清邁地區大氣環境同時充斥著交通原生污染源及二次光化產物的影響。由兩時期的物種指標：K/Levo= 0.78-2.68, Levo/Mannosan= 5.73-36.2的比例關係發現有明確的生質燃燒特徵，其中脫水內醚糖是視為清邁地區周圍的山林燃燒最具指標意義的氣膠有機物種。研究歸納發現清邁地區大氣污染來源最主要來自光化產生的二次氣膠和生質燃燒中硬木和軟木的樹葉/皮燃燒所貢獻。

PM10 aerosol was collected during two periods between February and April of dry season 2010 at urban, suburban and mountain sites in Chiang Mai basin, Thailand. Characteristics and provenance of water-soluble inorganic species, carboxylic acids, anhydrosugars and sugar alcohols in PM10 were investigated. Concentrations of inorganic and organic species in PM10 aerosol at urban site are always higher than at suburban and mountain sites, indicating that more sources were transported to urban area. Acetic acid was the most abundant monocarboxylic acids, followed by formic acid. Oxalic acid was the dominant dicarboxylic acid species during both periods. Concentration of carboxylic acids during the PM10 episode was higher than that during non-episodic pollution. Carboxylic acids with a peak at daytime during the PM10 episode indicate that carboxylic acids are formed by photochemical reaction and/or are emitted directly by fossil fuels and biomass burning processes. Levoglucosan (Levo) and arabitol were the most dominant anhydrosugar and sugar alcohol, respectively, the ratios of levoglucosan to PM10 in forest fire are 0.53-1.48% by PM10 mass. High concentration of levoglucosan was found at nighttime in both periods, indicating that biomass burning contributed during nighttime. Mass ratio of acetic to formic acids (A/F) > 1 is often used to demonstrate the primary source by wood burning or vehicular emission. This study showed that the contribution of primary sources caused from biomass burning. Moreover, the ratios of M/S in the range of 0.94-1.72 during both periods indicated there exists simultaneously the impaction of primary traffic-related emissions and secondary photochemical pollution on Chiang Mai ambient environment. The discriminator ratios of biomass burning reported here are 0.78-2.68 of K/Levo, 5.73-36.2 of Levo/Mannosan. Levoglucosan was found to be the most useful marker for biomass burning emitted from forest fire event in the mountain around Chiang Mai basin. The most significant contribution to PM10 in Chiang Mai basin was the photochemical formation of secondary aerosols and primary source from biomass burning contributed by hardwood and softwood of leaves/bark trees.

CONTENTS

ABSTRACT I
CHINESE ABSTRACT II
ACKNOWLEDGEMENTS III
CONTENTS V
LIST OF TABLES VIII
LIST OF FIGURES X

CHAPTER 1 INTRODUCTION 1
1.1 Introduction 1
1.2 Purpose 3

CHAPTER 2 LITERATURE REVIEW 4
2.1 Aerosol formation mechanism 4
2.2 Carboxylic acids in atmospheric aerosols 5
2.3 Sources of carboxylic acids 8
2.3.1 Direct emissions from anthropogenic sources 8
2.3.1.1 Biomass combustion 8
2.3.1.2 Motor exhaust emissions 9
2.3.2 Emissions from biogenic sources 10
2.3.3 Photochemical production of carboxylic acids
from precursors 11
2.4 Anhydrosugars and sugar alcohols 19

CHAPTER 3 EXPERIMENTAL 26
3.1 Sampling 26
3.2 Sampling handing 29
3.3 Chemical analysis and quality assurance 29
3.4 Other data 35

CHAPTER 4 RESULTS AND DISCUSSION 37
4.1 Meteorological conditions 37
4.2 Mass concentration of PM10 aerosols 39
4.3 Aerosol composition of PM10 during non episodic pollution
and PM10 episode periods 42
4.4 Concentration of chemical species in daytime
and nighttime during non episodic pollution period
and PM10 episode 47
4.5 Contribution of chemical species 53
4.6 Composition of mass ratios with other studies 63
4.6.1 Carboxylic acids 63
4.6.2 Anhydrosugars 65
4.7 Relationships among chemical species in daily PM10
and gaseous pollutants 67
4.8 Comparison with literature data 69

CHAPTER 5 CONCLUSIONS 74
5.1 Conclusion 74
5.2 Suggestions for the future work 77
REFERENCE 78
LIST OF TABLES

Table 2.1 Saccharides commonly found in atmospheric
aerosol and their sources (Caseiro et al., 2007) 25
Table 3.1 Ion Chromatography Dionex DX-600
gradient elution ratio 31
Table 3.2 The names and chemical structures of carboxylic acids 33
Table 3.3 The names and chemical structures of anhydrosugars
and sugar alcohols 34
Table 3.4 Method detection limits (MDLs) of four chemical
compound groups measured using IC systems 35
Table 4.1 Meteorological and related air pollution information
during the period of study at the suburban site 38
Table 4.2 Mean (?bSD) chemical composition of PM10 aerosol
during non-episode pollution period and
PM10 episode emitted from sampling site 43
Table 4.3 Summary presentation of research findings
related to acetic/formic and malonic/succinic
ratios in aerosol 64
Table 4.4 Comparison of ratios for various wood burning
and atmosphere aerosols (reported in the literature) 66



Table 4.5 Varimax-rotated principal component loadings
of daily PM10 chemical species, gaseous pollutants
and wind during intensive observation period
of this study 68
Table 4.6 Inorganic salt concentrations (µg m-3) measured at various
sampling sites around the world in recent years 71
Table 4.7 Carboxylic acids concentrations (ng m-3)
measured at various sampling sites
around the world in recent years 72
Table 4.8 Anhydrosugars and sugar alcohols
concentrations (ng m-3) measured at various
sampling sites around the world in recent years 73











LIST OF FIGURES

Figure 2.1 Idealized schematic of the distribution
of surface area of an atmospheric aerosol
(Whitby and Cantrell, 1976) 4
Figure 2.2 Production cycle of carboxylic acids
in the atmosphere (Sun and Ariya, 2006) 7
Figure 3.1 Ecotech MicroVol 1100 Particulate Samplers 28
Figure 3.2 Map of Chiang Mai Basin areas
identifying the location of air sampling sites 28
Figure 3.3 Step for MicroVol sampling and analysis flow chart 32
Figure 3.4 Wind rose charts during intensive
observation period (a) IOP1 and IOP2 36
Figure 4.1 PM10 mass concentration of intensive observation
period with PCD data during period of study 40
Figure 4.2 Correlation of PM10 concentration from PCD data
with PM10 concentration from observed site
during period of this study 41
Figure 4.3 Mean of inorganic species concentration
in daytime and nighttime (a) during non episodic
pollution period and (b) during the PM10 episode
emitted from sampling sites 48

Figure 4.4 Mean of carboxylic acids concentration
in daytime and nighttime (a) during non episodic
pollution period and (b) during the PM10 episode
emitted from sampling sites 50
Figure 4.5 Mean of anhydrosugar and sugar alcohols
concentration in daytime and nighttime
(a) during non episodic pollution period and
(b) during the PM10 episode emitted from
sampling sites 52
Figure 4.6 Contribution of individual species to total
composition in PM10 during intensive observation
period of each sites 54
Figure 4.7 Contribution of individual species to total
amount of inorganic species in PM10
during intensive observation period of each sites 55
Figure 4.8 Contribution of individual species to total
amount of carboxylic acids in PM10 during
intensive observation period of each sites 57
Figure 4.9 Correlation of potassium concentration with
oxalic acid concentration of each site sampling 58
Figure 4.10 Contribution of individual species to
total amount of anhydrosugars in PM10
during intensive observation period of each sites 60
Figure 4.11 Correlation of levoglucosan concentration with
potassium concentration of each site sampling 61
Figure 4.12 Contribution of individual species to total
amount of sugar alcohols in PM10 during
intensive observation period of each sites 62

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