由於都會區民眾較易曝露於高濃度之空氣污染,且民眾平均有80%以上之時間處於室內環境,本研究藉由室內外空氣品質監測及暴露健康風險評估,並且配合大氣擴散模式AERMOD(AMS / EPA Regulatory Model, AERMOD)模擬,了解民眾暴露於室內外空氣污染之健康效益。因此,本研究選擇台北縣市之校區、社區與大安區北部三類型作為本研究探討案例,分析各案例之固定污染源(Stationary source)包括餐飲業與加油站業,與移動污染源(Mobile source)包括車輛排放之空氣污染物,如PM10、SO2、NO2、CO與O3濃度,並藉由管制策略用以改善空氣品質,最後透過空氣資源整合效益模型(Air Resources Co-Benefits Model, ARCoB)由死亡與疾病之相對風險值(Relative risk, RR)計算校區、社區與大安區北部之空氣品質改善所帶給民眾於個人終生平均壽命增加與節省年醫療支出之效益。 研究結果顯示,空氣污染物改善以單位濃度1 μg/m3下相對應之增加個人終生平均壽命與降低年醫療支出之整體效益結果顯示,PM10改善後獲致之健康效益最大,說明PM10對人體之健康影響最明顯;CO改善後獲致之健康效益最小,原因為流行病學研究CO之劑量濃度反應(Dose-Response Curve)指出,CO原本濃度就不高,經改善情況後,反應於人體健康並非明顯,故其減量後健康效益最差。
Due to people who live in urban area have more opportunities to expose in air pollutants of high concentration and people have 80% time stay in door. This paper is to monitor the air quality and the exposed health risk appraisal by indoor outer space. Moreover, the study also compares AERMOD(AMS/EPA Regulatory Model, AERMOD) test for realizing the efficiency of people who expose in indoor outer space. As result, the paper to study and discuss the residents district affect by Stationary source (e.g. restaurant industry, oil station), and Mobile source including the air pollutants by vehicles (e.g. PM10, SO2, NO2, CO, and O3) in the school, communication and region of Taipei city, county. In addition, the improvement of air quality by control way and finally the study will use the Air Resources Co-Benefits Model, ARCoB in order to evaluate the average life of residents and the efficiency of medical expense by Relative risk of die and diseases.. The result shows that for the unit density of the air pollutant improvement 1 μg/m3 corresponds to increase life expectancy of the individual and reduce the medical expenditure shows that the improvement of PM10 has more benefits for health which explains PM10 is the most obvious health influence to the human body; CO can improvement the health of inhabitants for the smallest benefits because the Epidemiology studies Dose-Response Curve of CO shows that CO concentration originally is not high level. In addition, after improving the situation, the reaction to the human body health is not so obvious so after reducing the amount the health benefit is the worst.