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系統識別號 U0026-1202201500034400
論文名稱(中文) 沙塵暴對台灣北部地區空氣中病毒及細菌濃度之影響
論文名稱(英文) Ambient Viral and Bacterial Distribution during Asian Dust Storm in Taiwan
校院名稱 成功大學
系所名稱(中) 環境醫學研究所
系所名稱(英) Institute of Environmental and Occupational Health
學年度 103
學期 1
出版年 104
研究生(中文) 蔣岳崇
研究生(英文) Ngok-Song Cheong
學號 s76015011
學位類別 碩士
語文別 英文
論文頁數 83頁
口試委員 指導教授-蘇慧貞
召集委員-林傳堯
口試委員-曾俊傑
中文關鍵字 沙塵暴  長程傳輸  A型流感病毒  腸病毒  活性細菌  總細菌 
英文關鍵字 Asian dust storm  Long-Range Transport  Influenza virus  enterovirus  Total/Viable bacteria 
學科別分類
中文摘要 目的:藉由分析台灣北部都市和近郊空氣中細菌、腸病毒及流感病毒於背景日及長程傳輸事件時之濃度,以探討長傳事件及其類型對台灣北部空氣中細菌、腸病毒及流感病毒分佈之影響。並初步分析空氣中細菌與氣象因子及空氣污染物之相關性。

材料與方法:監測2013/9– 2014/4期間沙塵暴動向以進行沙塵暴事件及前後日之每日空氣樣本採集,且於此時間區間的每月第二週採集背景日樣本。於石門區富貴角及大安區台灣大學以空氣幫浦搭配內含鐵氟龍濾紙的三層濾紙匣進行採樣,並以reverse transcription quantitative PCR (RT-qPCR) 定量腸病毒和流感病毒;總及活性細菌則分別以qPCR及propidium monoazide搭配qPCR進行定量。採樣後依據氣象測站之溫度和風速、環保署測站之污染物濃度資料、主要氣流方向 (HYSPLIT模型推估) 和衛星相片評估沙塵暴對採樣點之影響,以及該次長傳事件屬於沙塵或非沙塵事件;將採樣時間分成事件前、期間及後,並比較病毒及細菌濃度。最後以Spearman Correlation Coefficient初探細菌濃度與空氣污染物與氣象因子的相關性。

研究結果:共採集二次沙塵暴 (2013/11/17-2013/11/18、2013/11/25-2013/11 /29) 和三次非沙塵長程傳輸 (2013/09/16-2013/09/17、2013/10/12-2013/10/13、2014/01/03- 2014/01/05) 的空氣樣本。A型流感病毒只有富貴角在一月非沙塵長程傳輸前跟期間可測得,濃度分別為0.87與10.19 copies/m3。而在背景日的細菌部分,總與活性細菌的濃度變化趨勢,無地理區上的差異。然而,沙塵暴對此2測站空氣中細菌分佈之影響不同;富貴角測站在沙塵暴期間所測得之總 (1.40 log copies/m3) 及活性細菌 (0.85 log copies/m3) 濃度高出沙塵暴前及後檢測值0.23-0.41 log copies/m3。但台大測站則為沙塵暴前的總細菌 (1.44 log copies/m3) 與活性細菌 (0.77 log copies/m3) 的平均濃度最高,沙塵暴期間次之 (總:1.25 log copies/m3;活性:0.45 log copies/m3)。而非沙塵長程傳輸則對2測站均明顯影響,長傳期間和/或後的空氣中細菌濃度高於長傳前;一月的事件中總及活性細菌的濃度在長傳期間及後濃度分別為0.60-1.62 log copies/m3 (總) 和0.34-0.78 log copies/m3 (活性),以及1.05-1.90 log copies/m3 (總) 和1.19-1.23 log copies/m3 (活性);長傳前則為0.57-1.19 log copies/m3 (總) 和0.17-0.80 log copies/m3 (活性)。此外,研究也發現,在2種類型的長程傳輸期間的細菌活性仍可高於33%,顯示長傳可帶來仍具有活性、可能造成健康危害的細菌。相關性結果顯示在沙塵暴期間,總細菌與PM2.5濃度呈負相關(r=-0.76、p<0.05),活性細菌濃度則與NO2 (r=-0.68、p<0.05)、NOX (r=-0.61、p<0.05)、CO (r=-0.70、p<0.05) 和風速 (r=-0.66、p<0.05) 呈顯著負相關;然在沙塵暴前和後未發現影響細菌濃度之顯著因子 (p > 0.05)。但在背景日則發現總 (r=0.56、p<0.01) 和活性 (r=0.49、p<0.05) 細菌分別與PM10 呈正相關且達統計上的顯著。

結論:總細菌與活性細菌在背景日的濃度變化趨勢相似,然富貴角測站的細菌及A型流感病毒濃度增加情形受長程傳輸之影響大於台大測站。再者,非沙塵長傳事件對台灣北部的影響似乎高於沙塵暴,其會增加台大及富貴角測站空氣中細菌濃度,且可能持續到事件後2天。由本研究可知,未來當長程傳輸事件可能發生時,事件期間及後2天應該要避免在石門等北部沿海地區戶外活動。此外,空氣污染物和氣象因子對細菌濃度之影響性在背景日及沙塵暴事件不同,背景日的總和活性細菌與PM10均為正相關;而在沙塵暴期間,當PM、NO、NOx、CO及風速高時,空氣中細菌濃度則較低。本研究納入分析之長傳事件仍少,未來可繼續累積事件數以期能獲得更為明確之結論。
英文摘要 Objectives: To evaluate the impacts of the occurrence and type of long-range transportation (LRT) on the distribution of virus and bacteria in Northern Taiwan by quantifying the levels of enterovirus, influenza A virus and bacteria in ambient air on the days before, during, and after LRT and background days. Also, this study preliminarily investigates the relationships between the ambient bacterial concentrations with air pollutants and meteorological factors.

Methods and Materials: The present study monitors the Asian Dust Storm (ADS) events from September 2013 to April 2014. When ADS occurred in the desert and possibly affect Taiwan, daily air samples were collected on the days before, during and after ADS. Also, during this period, a continuous 3-days sampling were performed in the second week of each month to take daily air samples for background days. Two sampling stations located in Northern Taiwan were adopted: Cape Fukuei (CF, Shimen District, New Taipei City) and National Taiwan University (NTU, Daan District, Taipei City). Cassettes with 37-mm Teflon filters (0.2 µm) were utilized to capture ambient enterovirus, influenza Avirus, and bacteria. Daily filter samples were collected using vacuum air pumps for 24 hr. After sampling, reverse transcription quantitative PCR (RT-qPCR) was applied to quantify enterovirus and influenza A virus, and qPCR and propidium monoazide coupled with qPCR were respectively used to quantify total and viable bacteria. We would confirm whether the LRT belongs to ADS and its effect on Taiwan based on the data of meteorological conditions (temperature and wind speed, from Taiwan Centeral Weather Bureau (Taiwan CWB)) and air pollutions (PM10 and PM2.5, from Taiwan Environmental Protection Administration (Taiwan EPA)), the source of air mass (48-hr backward trajectory produced by HYSPLIT model), and satellite images of MODIS sensor. Spearman Correlation Coefficient was used to analyze the relationships that viable and total bacteria have with air pollutants (PM10, PM2.5, NO2, NO, NOX, CO, O3 and SO2) and meteorological factors (temperature, RH, wind speed and cumulative rainfall).

Results and Discussion: A total of two ADS (11/17/2013-11/18/2013, 11/25/2013-11/29/2013) and three frontal pollution cases (FP) (09/16/2013-09/17/2013, 10/12/2013-10/13/2013, 01/03/2014-01/05/2014) were identified in this study. Influenza A virus only detected in the samples collected on the days before and during the FP (1/3-1/5, 2014), with concentrations of 0.87 and 10.19 (copies/m3), respectively. In term of bacteria on background days, the trend of cell concentrations at CF and NTU stations was similar, showed without geographic difference. However, ADS affects the distribution of bacterial concentrations in the atmosphere at two stations in different levels. The total (1.40 log copies/m3) and viable (0.85 log copies/m3) concentrations of bacteria during ADS days at CF station were higher than those detected after ADS (0.23-0.41 log copies/m3). For NTU station, the total (1.44 log copies/m3) and viable (0.77 log copies/m3) concentrations of bacteria before ADS were the highest, and followed by those found on the days during ADS (1.25 and 0.45 log copies/m3 for total and viable cells, respectively). In term of FP events, the impacts of FP were observed at not only CF station but also NTU station. The days during and/or after FP have higher bacterial concentrations than the days before FP. In FP event occurred in January, the respective concentrations of total and viable bacteria were 0.60-1.62 and 0.34-0.78 log copies/m3 for the days during FP as well as 1.05-1.90 and 1.19-1.23 log copies/m3 for the days after FP, which were more abundant than those quantified from the days before FP (0.57-1.19 and 0.17-0.80 log copies/m3 for total and viable cells, respectively). Surprisingly, this study found the bacterial viability were greater than 34% during the event days regardless LRT types, showing the LRT can carry bacteria that are viable and may have adverse health effects. The results of correlation analyses show that PM10 levels significantly and positively correlated with total (r=0.56, p<0.01) and viable (r=0.49, p<0.05) bacterial concentrations both on background days. During ADS days, negative correlations between total bacteria and PM2.5 (r=-0.76, p<0.05), and between viable bacteria and NO2 (r=-0.68, p<0.05), NOX (r=-0.61, p<0.05), CO (r= -0.70, p<0.05) and wind speed (r=-0.66, p<0.05). However, there were no environmental factors significantly associated with bacterial levels on the days before and after ADS (p>0.05).

Conclusions: The temporal distribution of total and viable bacterial concentrations between CF and NTU stations were similar, while LRT affects ambient bacteria and influenza A virus at CF station is higher than those at NTU station. Moreover, the impacts of FP on Northern Taiwan seem higher than ADS. FP increased the concentration of bacteria at CF and NTU stations and may continue to two days after FP. Therefore, during and 2 days after LRT, people should avoid activities outdoors in Northern Taiwan, especially the North Coast of Taiwan such as Shimen area. The associations of ambient bacteria with air pollutants and meteorological factors on background days were different from those during ADS days. The enhancers of ambient bacterial levels were the increase of PM10 on background days, but the decline of PM2.5, NO2, NOX, CO and wind speed during ADS days instead.
論文目次 Table of Contents
中文摘要 II
ABSTRACT IV
ACKNOWLEDGEMENTS VII
LISTS OF TABLES 3
LISTS OF FIGURES 4
CHAPTER I INTRODUCTION 7
1.1 Dust Storms 7
1.1.1 Influences of Dust Storms on Downwind Area 8
1.2 Association between ADS Conditions and Microorganisms 9
1.2.1 Impacts of Meteorological Factors on Viruses and Bacteria 10
1.2.2 Association of Air Pollutants with Viruses and Bacteria 12
1.3 Importance of Viruses and Bacteria 13
1.3.1 Influenza A virus and Enterovirus 14
1.3.2 Total Bacteria and Viable Bacteria 16
1.4 Study Purposes and Importance 17
CHAPTER II MATERIALS AND METHODS 19
2.1 Study Design 19
2.2 ADS Arrival Determination 19
2.3 Sampling 20
2.4 Sample Pretreatment 21
2.5 Viral RNA Isolation 21
2.6 Virus Quantification 22
2.7 Total and Viable Bacteria DNA Isolation 22
2.8 Bacteria Quantification 23
2.9 Meteorological Information and Air Pollutants 23
2.10 Statistical Analysis 24
CHAPTER III RESULTS 25
3.1 Quality Control for Viral and Bacterial Analyses 25
3.2 ADS Confirmation 25
3.3 Viral Concentration 26
3.4 Bacterial Concentration 27
3.5 Characteristics of Meteorology and Air Pollutants 29
3.6 Relationships among Bacteria, Meteorological Information and Air Pollutant 29
CHAPTER IV DISCUSSION 31
4.1 Bacterial Concentrations during ADS Events 31
4.2 Bacterial Concentrations during FP Events 32
4.3 Relationships between Bacteria and Environmental factors 33
4.4 Viruses during Asian Dust Storm and Background Days 34
CHAPTER V CONCLUSION 37
REFERENCES 39
TABLES 45
FIGURES AND FIGURE LEGENDS 56
APPENDIXES 81
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