交通排放為超細懸浮微粒(粒徑<100 nm)主要來源，居住於鄰近交通頻繁地區可能對人體產生呼吸道疾病或心血管疾病等健康危害，然而用來監測超細懸浮微粒濃度之儀器通常價格昂貴且笨重，尋找便宜且方便之替代測量方式有其必要性。為解決上述問題，本研究除建構一移動式量測平台(mobile platform)探討大氣中懸浮微粒之時空分布組成特徵外，亦結合噪音、氣象及地理資訊建立一超細微粒濃度預測模型(UFP predict model)。
為獲得高時間及空間解析度之空氣污染物分布情形，本研究以移動式量測平台搭載高時間解析度儀器(快速微粒電動度粒徑分析儀、氣動粒徑分析儀、奈米微粒表面積分析儀、氣膠監視量測儀、超細微粒計數器、多環芳香烴分析儀、音頻分析儀)，量測受台中港工業區影響之沙鹿、龍井、梧棲其PM2.5、超細微粒及多環芳香烴等空氣污染物濃度，採樣時程共分為四個季節(秋、冬、春、夏)，各季節之採樣至少約1個禮拜，採樣時間為早上(7:00-10:00 AM)與晚上(18:00-21:00 PM)，超細微粒預測模型則以廣義相加模型(Generalized additive model)進行建模。
研究結果顯示超細微粒數目濃度、多環芳香烴等懸浮微粒濃度指標顯著受時間與空間變異所影響(p<0.001)，此外，本研究所建立之超細微粒預測模型其解釋力及決定係數(R2)分別高達80%和0.77，即本研究所建構之超細微粒預測方程式能有效預測台中地區之超細微粒濃度，並提供較便宜且迅速之方式獲得大氣中超細微粒濃度，量測結果將可結合流行病學研究及健康危害風險評估技術，以瞭解居民之主要暴露來源。

Vehicle emissions are the main source of ultrafine particles (UFP, diameter < 100 nm). People living in near roadway have increased respiratory diseases and cardiovascular mortalities. However, most of the UFP concentration measurement instruments are expensive and bulky. To solve the problems, we used a mobile platform measurement to build a UFP prediction model with noise, geographical and meteorological data.
To obtain the spatial and temporal resolution of air pollutants, we constructed a mobile platform equipped with high resolution monitoring instruments (FMPS, APS, NSAM, DustTrak, P-TRAK, PAS, Sound Analyzer) to measure PM2.5, ultrafine particle (UFP), and polycyclic aromatic hydrocarbons (PAHs) concentrations around Taichung Harbor Industrial Area (Shalu, Longjing, Wuci). Sampling was conducted during morning (7:00-10:00 AM) and evening (18:00-21:00 PM) on both weekdays and weekends in each season. We proposed a generalized additive model to predict UFP number concentration in the study area.
The result indicates that most of daytime air pollution indicators were significantly influenced by temporal and spatial variations (p<0.001). In addition, the proposed model can explain 80% of deviance and has coefficient of determination (R2) of 0.77. Furthermore, the developed UFP model can predict UFP concentrations precisely and conveniently in Taichung. Besides, the results from this study could also be applied for epidemiology studies and health risk assessments.

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