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研究生:林子涵
研究生(外文):Lin,Tzuhan
論文名稱:應用GPS探討空氣品質測站測值與周圍微環境空氣汙染物在不同時序的相關性研究
論文名稱(外文):Spatiotemportal Analysis of the Relationship between Ambient Air Monitoring Station and Surrounding Microenvironments Using Global Positioning System Technology
指導教授:唐進勝唐進勝引用關係董道興董道興引用關係
指導教授(外文):Tang CSTung TH
口試委員:張立德
口試委員(外文):Chang LT
口試日期:2012-07-30
學位類別:碩士
校院名稱:輔仁大學
系所名稱:公共衛生學系碩士班
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:111
中文關鍵詞:全球定位系統微環境空氣品質測站空氣污染物
外文關鍵詞:global positioning systemmicroenvironmentstationary ambient stationair pollutant
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目的:
多數空氣汙染研究常以空氣品質測站數值代表個人暴露,但個人微環境汙染物濃度會隨著時間及空間有所改變。本研究目的是應用直讀式採樣設備搭配全球定位系統(global position system, GPS)以瞭解汙染物的分布狀況,以及探討空氣品質測站的定點監測資料與測站周圍微環境濃度值的相關性。

方法:
依所規劃的路線,配戴GPS軌跡記錄器與直讀式採樣設備,以步行的方式繞行空氣品質測站周圍。步行路線的選擇包含如交通、校園、工地等微環境。偵測的汙染物包括懸浮微粒(particulate matter, PM)、粒相多環芳香族碳氫化合物(polycyclic aromatic haydrocarbons, PAHs)、一氧化碳(carbon monoxide, CO)等。採樣日共計4季,每季各7日,包含假日與非假日以及每日早、中、晚各時段。將座標與各汙染物濃度結合後繪製出污染物濃度變化圖,並將同時間微環境汙染物濃度值與測站監測值相除以求比值,以探討兩者差異隨時空之變化情形及影響因素。

結果:
本研究發現空氣品質測站周圍微環境中各季節污染物之平均濃度分別為PM10、PM2.5在冬季最高(75.77 μg/m3, 40.56 μg/m3),秋季PAHs濃度最高(113.78 ng/m3),CO濃度以夏季最高(4.62 ppm)。採樣時段方面,PM10、PM2.5與CO最高濃度出現在早上時段,PAHs在晚上具有較高的濃度。一般日各汙染物濃度普遍高於假日。PM10、PM2.5與PAHs在汙染源(如燃燒紙錢)出現之處會有較高的濃度,校園內各汙染物濃度皆較其他微環境低。歸納各類污染物的微環境與定點濃度差異,發現距離長短、不同路段、不同採樣時段、一般日與假日間、不同季節方面都有顯著的影響,只有PAHs會受到不同風向的顯著影響,而PM10、PM2.5與PAHs在一般環境與汙染環境之間都有顯著差異的情形。

結論:
本研究建立的GPS技術可以提供活動記錄參考,並瞭解微環境在不同時空下污染物的濃度分布和來源,並據以判斷微環境與測站汙染物濃度的差異,以及探討其影響因素。


Purpose
The data from stationary ambient monitoring (SAM) sites was used to estimate personal exposure in numerous air pollution researches. However, the associations between SAM data and personal exposures are confounded by various factors. This study is conducted to investigate the spatial and temporal distribution of air pollutants, and to explore the relationship between SAM data and surrounding microenvironments concentrations by using global positioning system (GPS).

Methods
Researcher wore GPS data loggers and continuous air monitoring equipments walking around the SAM by scheduled route consisting of traffic roads, shops, restaurants, and campus. The monitored pollutants included multi-sized particles, particle-bound polycyclic aromatic hydrocarbons (PAHs), and carbon monoxide. The sampling days consisted of morning, noon, and evening, as well as weekends and weekdays in different seasons. The time-location data obtained from GPS was linked to environmental pollutants data to draw the pollution maps. The ratios of microenvironmental pollutant concentration and the SAM values (M/S) were calculated to explore the spatiotemporal variations and affecting factors.

Results
The results of this study showed that highest mean seasonal PM10 and PM2.5 concentrations around the SAM during the monitored period were 75.77 and 40.56 μg/m3 in winter, while highest mean seasonal PAHs level was 113.78 ng/m3 in autumn, and the highest mean seasonal CO was 4.62 ppm appeared in summer. During the whole day, the highest mean levels of PM10, PM2.5, and CO were appeared in daytime, but the highest mean PAHs level was appeared in nighttime. Besides, the mean concentrations of all pollutants during the weekday were higher than those of weekend. Whenever the pollution sources (e.g. burning paper money) appeared in the microenvironments, the higher PM10, PM2.5, and PAHs levels could be found in the same time. The campus had the lowest concentrations of all pollutants. Distances between SAM and microenvironments, road sections, sampling period, weekday and weekend, and season had significant effects on the M/S ratio in each pollutant. Wind direction was found to affect the M/S ration only in PAHs. The M/s ratio in PM10, PM2.5, and PAHs were also affected by pollution sources.


Conclusion
The GPS methodologies developed in this study was found to be a promising mean for tracking of research subjects in microenvironment-based exposure assessment. Combining air pollutants msp with spatiotemporal information will improve the understanding of relationships between these SAM data and actual personal exposures, and the effects of pollution source and meteorological factors.

目錄 ……………………………………………………...……………………..VII
表目錄 ……………………………………………………………………………..IX
圖目錄 ……………………………………………………………………………...X
第一章 前言 …………………………………………………………………………1
第二章 文獻回顧 ……………………………………………………………………4
第一節 空氣汙染物之流行病學研究 4
第二節 全球衛星定位系統與相關應用研究 8
第三節 各地微環境空氣汙染物分佈研究 10
第三章 材料與方法 ………………………………………………………………..12
第一節 研究策略 12
一、採樣時間 12
二、研究架構 13
第二節 實驗儀器 14
一、GPS軌跡記錄器 14
二、汙染物分析儀器 17
第三節 採樣步驟 23
一、採樣前置步驟 23
二、採樣步驟 24
三、採樣處理相關細節 26
四、儀器紀錄間隔 26
第四節 儀器的品質保證與品質管制 27
第五節 空氣品質測站儀器與採樣儀器資料測值比對處理 28
一、PM10與PM2.5校正係數 29
二、PAHs校正係數 30
三、CO校正係數 30
第六節 統計方法 31
第四章 結果 ………………………………………………………………………..34
第一節、微環境與測站汙染物和氣象因子的分佈 34
第二節、微環境與空品測站各類污染物與氣象因子相關性分析 40
第三節、微環境與空品測站各類污染物與單因子檢定分析 41
第四節、各類污染物M/S比值與單因子檢定分析 46
第五節、各類污染物之M/S比值與相關因子迴歸分析 48
第六節、各類污染物之M/S比值分類與相關因子邏輯斯分析 54
第五章 討論 …………………………………………………………...……………..59
第六章 結論與建議 ……………………………………………...…………………..63
第一節、結論 63
第二節、限制與建議 66
參考文獻 ………………………………………………………………………… ….103

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