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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/79707

    Title: 台北都會區PM1.0微粒物理特徵描述與含碳氣膠來源分析;Characteristics and sources of carbonaceous aerosols and PM1.0 in Taipei urban area
    Authors: 王瑜慧;Wang, Yu-Hui
    Contributors: 環境工程研究所
    Keywords: 黑碳;交通排放;來源分析;PM1.0;PM1.0;Source analysis;Traffic emissions;Black carbon
    Date: 2018-11-28
    Issue Date: 2019-04-02 15:15:32 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 現今雖然已有許多關於交通排放進行氣膠特性分析的研究,但對於超細懸浮微粒PM1.0與都市背景碳來源評估仍較缺乏,故本研究選擇在都市中高車流量地區利用最新七波段氣膠吸收光儀 (Aethalometer, Magee, AE33)於不同波段的吸光訊號評估不同黑碳來源排放,並建立即時監測系統進行道路連續監測,同時進行測量的儀器還包括錐形元件震盪微量天平 (TEOM, R&P 1400a)、奈米微粒表面積監測儀 (NSAM, TSI 3550)和掃描式電移動度粒徑分析儀 (SMPS, TSI 3936)。分別量測黑碳濃度、質量濃度、表面積濃度、數目濃度和粒徑分佈,並以氣象塔紀錄環境溫、濕度變化、風速和風向的分布。利用上述不同量測結果與氣象資料進行分析,由不同研究方式的結果作綜合性分析及整合,探討都市環境中微粒與黑碳成份與來源隨時間的濃度變化和特性。
    量測結果分析上,在六個月量測期間,顯示黑碳、數目濃度與肺部沉積受到交通量與季節變化較明顯 。在一日變化分析上,黑碳、數目濃度與肺部沉積表面積在平日尖峰時刻有明顯峰值,顯示在此量測地區黑碳、數目濃度與肺部沉積表面積可做為交通排放指標。微粒特性結果顯示,幾何平均、密度、BC/PM1.0與AAE在整個量測期間晝夜變化明顯,顯示白天交通排放明顯。有效密度與AAE值,分別介於0.3 g/cm3 ~ 2.0 g/cm3之間與1.1~1.3之間。
    碳來源分析上,利用Aethalometer model計算求得BCTr與BCBrC,分別代表交通排放的黑碳與含有較高有機成分的褐碳。在整個量測期間,發現不同風向影響BCTr與BCBrC濃度分佈明顯。由一日變化結果顯示在東風(60o~120 o)方向下污染來源受到近交通排放影響,東南風(120o~180 o)方向下的褐碳則在早上、中午與晚上的用餐時間有峰值,顯示可能受到人為排放影響,例如:廚房油煙。而在西南(180o~270 o)方向下在風速較大時濃度較高,顯示可能受到較遠處交通排放影響。
    不同風向特徵分析上,頻率分布結果顯示東風方向微粒粒徑與有效密度在三個風向下最小,確立在東風方向下微粒主要受到近交通排放影響。而在西南風向下,幾何平均粒徑與黑碳所佔比例在三段風向下最大,主要受到較遠高速公路的污染物傳輸所影響,且高速公路可能多含有柴油引擎排放,其排放成分相較於其他種類汽車含有較多黑碳。在不同風向下微粒粒徑分佈隨著東風、東南風與西南風向分佈越大,分別代表近交通排放的影響、交通排放與人為活動排放影響以及較遠高速公速傳輸老化微粒影響,微粒粒徑分佈鋒值則分別為28 nm、40 nm與51 nm。此外,進行不同風向下個測量值之間相關性作分析,加強不同風向下不同污染來源的證據。而由Aethalometer model模型計算求得的BCTr與BCBrC與其他量測結果相符合,也與各量測值具有相關性。
    ;This study established a real-time monitoring system and placed in a trailer station located in Taipei urban high-traffic area. Aethalometer (Magee, AE33), which can provide absorption signals at seven wavelengths, was used to evaluate equivalent black carbon (BC), potential brown carbon (BrC) and their related sources. At the same time, Tapered Element Oscillating Microbalances (TEOM). R&P 1400a), Nanoparticle Surface Area Monitor (NSAM, TSI 3550) and Scanning Mobility Particle Sizer (SMPS, TSI 3080) were employed to measure black carbon concentration, mass concentration, surface area concentration, number concentration, and particle size distribution, respectively. All-In-One Weather Sensor (AIO Weather, Climatronics) was used to record environmental temperature and humidity, wind speed and wind direction. In terms of integrating different measurements and meteorological data, a comprehensive picture of characteristics of PM1.0 and black carbon in Taiwan urban environment was clearly depicted. It was found BC, particle number concentration and lung deposition surface area concentration were significantly affected by the traffic volume and demonstrated seasonal variations. Their diurnal patterns in workdays all have clear peaks at rush hours, which suggest that BC, number concentration and lung deposition surface area concentration can be good indicators for traffic related emissions. In addition, particle size, density, BC/PM1.0 and AAE also have strong diurnal variations and influenced by traffic related emissions as well. The effective density and AAE range from 0.3 g/cm3 to 2.0 g/cm3 and between 1.1 and 1.3, respectively.
    Based on the wind-roses analysis, in the east (60o~120o), near/fresh traffic emissions is the dominant source of particulate pollutions. In the southeast (120o~180o), BrC concentrations show peaks in the morning, noon and evening, indicating that human activities, such as cooking, could be the emission sources. In the southwest (180o~270o), the concentration is higher when the wind speed is larger, implying that it is affected by the far-distance/transported traffic related emissions. Furthermore, the frequency distribution results show that the particle size and effective density are smallest in the east wind direction. While, the particle size and effective density are the largest in the southwest wind direction, reflecting the influences of aging particles transported from a highway located at 3 km away. The particle size distributions also echo the impacts of traffic emissions and human activities emissions. The results of correlation analysis between different measurements again evidence the influences of wind directions and the potential emission sources. In the source analysis of carbonaceous aerosols, BCTr and BrC were calculated by the Aethalometer model. During the observation period, it was found that the relative abundance of BCTr and BrC is varying with wind directions and consistent with the conclusions mentioned here.
    Appears in Collections:[環境工程研究所 ] 博碩士論文

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