國內捷運站及飛機客艙之生物氣膠影響因子探討; The determinants of bioaerosol in metro station and domestic airplane cabin in Taiwan

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Title:	國內捷運站及飛機客艙之生物氣膠影響因子探討;The determinants of bioaerosol in metro station and domestic airplane cabin in Taiwan
Authors:	周俊佑;Chun-Yu Chou
Contributors:	中國醫藥大學：職業安全衛生學系
Keywords:	捷運站;飛機客艙;生物氣膠;metro;cabin;bioaerosol
Date:	2008-06-26
Issue Date:	2009-08-12 15:20:59 (UTC+8)
Abstract:	近年來大眾交通工具發展迅速，飛機、捷運等長途運輸工具出現，大幅縮短民眾交通所須花費的時間。目前國內航線平均每月有五、六十萬人次搭乘，捷運每月有三千四百萬人次搭乘，隨著乘客人數的增加，其室內空氣品質的重要性也相對提升。本研究進行探討及預測評估捷運站內及國內線飛機客艙生物氣膠與環境相關因子的關聯性。研究期間為2007年7月至12月，共選取5個捷運測站及隨機選取國內線3架飛機24航段。於地下站3個測站服務站外及月台測得之細菌濃度與環境因子進行多變項分析，經調整之細菌濃度(CFU/m3)與人數、溫度(℃)、濕度(%)、CO2(ppm) 、時間階段、及測站可分別取得CO2及細菌濃度之預測模式，分別為CO2(ppm) = 743.9 + 3.883 (RH, %) + 0.198 (Person) + 59.282T1 + 63.969T2 + 139.201T3 + 168.839T4 + 267.759T5 + 253.559T6 + 203.554T7 - 602.860S1 - 342.656S2 (R2=0.881)及Log(Bacterial concentration, CFU/m3) = 1.992 + 0.008(RH, %) + 0.001(CO2, ppm) - 0.136T1 - 0.219T2 - 0.212T3 - 0.301T4 - 0.326T5 - 0.519T6 - 0.461T7 - 0.625S1 + 0.729S2 (R2=0.837)。建議可藉由建立之預測模式於地下站3個測站內進行CO2及細菌濃度濃度預測。 Several mass transportation systems have been established in Taiwan. Each month, approximately 500-600 thousand passengers are carried on domestic airlines, and 34 million passengers are carried on metro in Taiwan. Along with the increasing passenger population, the indoor air quality should be more important than ever. This study was to assess the determinants of bioaerosol in the metro station and airplane cabin in Taiwan. During July to December 2007, twenty-four domestic flights and five metro stations were selected for sample collection. In the multivariate analysis, the determinants included bacterial, person, temperature, humidity, carbon dioxide, timing and stations.We focused on three underground metro stations. The results of two regression forecasting models showed CO2 (ppm) = 743.9 + 3.883 (RH, %) + 0.198 (Person) + 59.282T1 + 63.969T2 + 139.201T3 + 168.839T4 + 267.759T5 + 253.559T6 + 203.554T7 - 602.860S1 - 342.656S2 (R2=0.881) and Log(Bacterial concentration, CFU/m3) = 1.992 + 0.008 (RH, %) + 0.001(CO2, ppm) - 0.136T1 - 0.219T2 - 0.212T3 - 0.301T4 - 0.326T5 - 0.519T6 - 0.461T7 - 0.625S1 + 0.729S2 (R2=0.837). The results show that we can take these models as an effective tool to predict CO2 and bacterial concentration in these three underground stations.
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