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研究生: 魏郁婷
Wei, Yu-Ting
論文名稱: 應用移動式噪音量測平台預測市區道路之黑碳與超細懸浮微粒濃度
Applying mobile noise measurements to predict roadway black carbon and ultrafine particle concentrations in urban areas
指導教授: 林明彥
Lin, Ming-Yeng
學位類別: 碩士
Master
系所名稱: 醫學院 - 環境醫學研究所
Department of Environmental and Occupational Health
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 73
中文關鍵詞: 移動式噪聲量測平台黑碳超細懸浮微粒廣義相加模型
外文關鍵詞: Mobile noise measurements, Generalized additive models (GAMs), Black carbon (BC), Ultrafine particles (UFPs)
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  • 黑碳(BC)對於環境污染有嚴重的影響,特別是在市區交通污染源方面,汽機車所排放出的廢氣已經被證實含有大量的黑碳成分。有研究指出交通排放出的黑碳與整體死亡率與罹患肺癌的風險也呈現增加的趨勢。暴露於超細懸浮微粒(UFP)已被認為是人類健康可能的致病因素。UFP由於體積小,表面積大,容易滲入肺部深處沉積於肺泡,導致肺部發炎甚至是肺癌。目前我國之空氣品質資訊大多為定點空氣品質監測站所提供,但定點測站不能準確地監測大氣中懸浮微粒時空濃度,為解決定點測站可能產生的問題,本研究建構一移動式噪音量測平台(Mobile noise measurements)探討大氣中懸浮微粒之時空分布組成特徵。
    本研究利用移動式噪音量測平台,搭載高時間解析度儀器於台中市區進行噪音、BC、UFP、PM2.5、奈米微粒及多環芳香烴等空氣污染物濃度量測。採樣期程共分為四季(春、夏、秋、冬),各季節採樣約二星期,採樣時間為每天早上(7:00-10:00)與晚上(18:00-21:00)。在檢定懸浮微粒濃度晝夜差異前先以柯-史(Kolmogorov–Smirnov)樣本檢定對欲比較之資料進行常態分佈檢定,在以無母數方法中之Wilcoxon rank sum test進行晝夜檢定,以及克-瓦檢定法(Kruskal-Wallis test)對四季與不同類型路段進行檢定。此外,我們使用廣義相加模型結合噪音參數、氣候條件與街道參數來建立一黑碳與超細懸浮微粒之預測模型。
    研究結果顯示懸浮微粒濃度受到時間與空間變異的影響,且達統計學上顯著差異(p<0.001),說明本研究之移動式噪音量測平台能夠表徵時空變化之懸浮微粒濃度,並在短時間辨別特定區域的熱點。此外,本研究所建立之黑碳與超細懸浮微粒預測模型其解釋力分別為82.6%與84.2%,且決定係數(R2)為0.75和0.84。本研究所建立之預測模型可以提供一個簡便的方法並降低實際測量BC和UFP濃度的成本。最後,希望本研究所建立的模型可以提供流行病學研究及健康風險評估研究,並協助相關機關制定暴露危害防制策略或改善污染。

    SUMMARY
    This study has two major purposes: (1) utilized mobile noise measurements to characterize the spatial and temporal distribution of air pollutants at Taichung city (2) use the generalized additive models (GAMs) to develop a surrogate model with noise parameters, meteorology and Street Canyon index to predict black carbon (BC) and ultrafine particles (UFPs) concentrations. This thesis was conducted from July 2016 to April 2017 at Taichung city. The data in this thesis were obtained from real-time monitoring instruments. The results show that air pollutants in different areas, diurnal pattern and seasons were significantly different (p<0.001). On the basis of the results of BC and UFP prediction model, it can be concluded that can reduce the cost of actually measuring and accurately estimate traffic-related concentrations of BC and UFP. Finally, we hope that the models established in this study can provide people to understand air quality around their environment and assist the government to formulate exposure protection strategies or improve pollution.

    Key words:Mobile noise measurements, Generalized additive models (GAMs), Black carbon (BC), Ultrafine particles (UFPs),

    目錄 第一章 前言 1 1-1 研究背景 1 1-2 研究目的 3 第二章 文獻回顧 4 2-1 懸浮微粒 4 2-1-1 懸浮微粒的來源及特性 4 2-1-2 懸浮微粒分徑指標及健康衝擊 5 2-2 黑碳 7 2-2-1 黑碳的定義與來源 7 2-2-2 黑碳對人體健康的危害 8 2-3 噪音與微粒 10 2-3-1 噪音 10 2-3-2 以噪音作為懸浮微粒替代指標物 (surrogate) 11 2-4 懸浮微粒濃度預測模型 12 2-4-1 廣義相加模型(Generalized Additive Models, GAMs) 12 第三章 研究方法與設備 15 3-1 研究架構 15 3-2 儀器設備 17 3-2-1 快速電移動度粒徑分析儀 18 3-2-2 奈米微粒表面積分析儀 18 3-2-3 氣膠監測量測儀 19 3-2-4 超細微粒計數器 20 3-2-5 多環芳香烴分析儀 21 3-2-6 口袋型微粒碳黑監測儀 21 3-2-7 噪音頻譜分析儀 22 3-2-8 氣象儀 23 3-2-9 行車紀錄器 23 3-3 採樣規劃 24 3-3-1 移動式量測平台 24 3-3-2 實驗地點 26 3-3-3 採樣時間 27 3-4 實驗數據之品保品管 28 3-5 建模參數 29 3-5-1 噪音參數 29 3-5-2 街道參數 30 3-6 廣義相加模型建模 31 第四章 結果與討論 33 4-1 懸浮微粒濃度之時間變異 33 4-1-1 懸浮微粒濃度之晝夜變異 33 4-1-2 懸浮微粒濃度之季節變異 33 4-2 懸浮微粒之空間變異 36 4-3 黑碳微粒預測模型 38 4-3-1 無分組之模型建構結果 38 4-3-2 分組之模型建構結果 44 4-4 模型結果討論與驗證 54 4-4-1 分組數據模型之評估 54 4-4-2 模型預測結果之評估 60 第五章 結論 65 5-1 結論 65 5-2 研究限制 66 5-3 建議 66 參考文獻 67  

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