100

920 千元

2011/04/28

2011/12/31

蔡瀛逸

臺南市政府環境保護局

黃文成

嘉南藥理科技大學

大氣空氣

直讀式PM2.5監測、細懸浮微粒、化學組成、受體模式、健康風險評估、PM2.5管制策略

Direct-reading PM2.5 measurement; Fine particulate matter; Chemical composition; Receptor model; Health risk assessment; PM2.5 control strategy

米孝萱、陳健民、邱嘉斌、陳建隆

蔡瀛逸

06-2660208#

mtsaiyi@mail.chna.edu.tw

本計畫為瞭解細懸浮微粒對台南民眾健康的影響性，透過PM2.5之量測與成份分析，利用受體模式推估污染可能來源與貢獻量，並調查臺南都會地區近年之PM2.5濃度數據與民眾健康及疾病資料數據，建立健康風險評估之濃度效應關係，模擬與推算風險，進行變數及不確定性分析。並配合空品管理計畫推動臺南市細懸浮微粒管制架構，建議管制策略。 以直讀儀監測即時環境PM2.5濃度發現，早上及下午交通尖峰時間，交通路口PM2.5濃度較高，而中午非尖峰時間PM2.5濃度較低。在汽機車車行地下道因無通風設施，其PM2.5濃度呈現較高的現象。室內環境在未開啟空調系統，亦有較高的室內PM2.5濃度。 臺南市中山國中夏季及秋季氣膠總碳量比例最高，平均佔PM2.5質量的42.7%，其次是水溶性離子有36.9%，金屬總量有8.1%及未能分析出之成分有12.3%。臺南市安順國小夏季及秋季PM2.5氣膠以水溶性離子佔最多有31.7%，其次總碳量佔了28.1%，金屬總量有5.4%及未能分析出之成分有34.7%。含碳成分中以OC最多，而離子成分以SO42-最多。地殼金屬元素以Ca、Fe及Na所佔比例最高，人為污染元素以Zn及Cu所佔比例最高。 針對PM2.5濃度的健康風險，長期效應而言，以臺南都會地區2006~2010年之PM2.5年平均濃度，並假設背景濃度為5 g m-3推算臺南都會地區之全死亡率、心血管、腦血管、肺炎及流行性感冒之每年平均死亡率分別增加為9.1%、14.3%、18.3%、26.4%。以短期暴露之影響而言，以臺南都會地區2006~2010年PM2.5日平均濃度，並假設背景濃度為5 g m-3時，推算日死亡率增加7.8%，當訂定PM2.5空氣品質標準年平均標準為15 g m-3、日平均標準為35 g m-3，以比例回推法推算在達成空氣品質標準時所降低之相對風險，當臺南都會地區PM2.5背景濃度為5 g m-3，長期效應影響之全死亡率、心血管、腦血管、肺炎及流行性感冒降低之死亡率分別為5.2%、7.8%、9.7%、13.3%。在短期健康的影響，以背景濃度為5 g m-3時，年死亡人數減少33人。 進一步以受體模式化學質量平衡法(CMB)分析PM2.5污染來源貢獻量，中山國中測站之最大污染源為交通源，貢獻比例夏季介於30.6~60.5 %，秋季介於67.9~76.5 %。其次為硫酸銨，主要為光化反應及遠程傳輸而來，貢獻比例夏季介於24.2~29.6 %，秋季介於18.0~21.7 %，第三大污染源則為生質燃燒，其貢獻比例夏季介於7.4~15.9 %，秋季介於17.5~22.4 %。地殼物質為夏季第四大貢獻源，貢獻比例則介於2.2~13.2 %，而硝酸鹽為秋季第四大污染源，貢獻比例介於2.6~6.8 %。同樣地，安順國小測站之最大污染源為交通源，貢獻比例夏季介於43.8~45.1 %，秋季介於47.2~71.8 %。其次為硫酸銨，主要為光化反應及遠程傳輸而來，貢獻比例夏季介於18.1~24.2 %，秋季介於20.6~22.0 %，第三大污染源則為生質燃燒，其貢獻比例夏季介於7.4~8.4 %，秋季介於8.4~10.6 %，而硝酸鹽則為秋季第四大污染源，貢獻比例介於3.8~6.3 %。上述結果顯示在夏秋季臺南地區之PM2.5污染貢獻來源主要均受交通排放及光化產物之影響。 以線性規劃法及成本效益，在不同PM2.5減量規劃下，考量在PM2.5改善到達12%時，可依加強營建工程管制、洗掃街道揚塵、餐飲業管制、紙錢集中燃燒、減少露天生質燃燒、固定污染源稽查管制等，依序建議優先加強執行，將具有選擇花費最小的策略方案組合。

直讀式PM2.5監測、細懸浮微粒、化學組成、受體模式、健康風險評估、PM2.5管制策略

環保局期末報告定稿by Tsai-final+ BACK COVER.pdf

32MB

2012/3/1 上午 12:00:00

To understand the impact of fine particulate matter (PM2.5) on public health in Tainan City, this study conducted ambient PM2.5 collection and chemical analysis to estimate the possible PM2.5 sources and their contributions by a receptor model. It also investigated the PM2.5 concentration data, public health and disease data of recent years in Tainan metropolitan area to establish the concentration effect relationship for health risk assessment. This study further simulated and estimated risks for the analysis on variables and uncertainty. Based on the results, this study promoted the PM2.5 regulatory framework, and proposed control strategy by working with Air Quality Integration Management Plan in Tainan City. The direct-reading PM2.5 measurement suggested that, the concentration of PM2.5 at traffic intersections was relatively higher during the morning and the afternoon rush hour, while the PM2.5 concentration was lower at noon (off-hour period). The PM2.5 concentration in the underpasses and tunnels of the motor vehicle lanes were relatively higher due to lack of proper ventilation facilities. In indoor environments when the air conditioning system was not on, PM2.5 concentrations were higher. The sampling of summer PM2.5 component concentrations suggested that, the total carbon content of PM2.5 in summer and autumn as measured in Station Jhongshan Junior High School (Station Jhongshan) is the highest with an average level of 42.7%, followed by water-soluble ions at 36.9%, total metal content at 8.1% and unidentified content at 12.3%. Regarding the PM2.5 contents, as measured in Station Anshun Elementary School (Station Anshun), water-soluble ions account for the highest percentage at 31.7%, followed by total carbon content at 28.1%, total metal content at 5.4% and unidentified contents at 34.7%. The carbon contents are mainly of OC (organic carbon) and the majority of ion contents are SO42-. Ca, Fe and Na have the highest percentage among all the crustal metal elements, and Zn and Cu account for the highest percentage of man-made pollution elements. In this study, health risks associated with exposure to PM2.5 for Tainan’s population were assessed based on an epidemiological study for populations from different cities in Taiwan. Results show that, for long-term health effects, percent of increases in total mortality and mortalities caused by cardiovascular diseases, cerebrovascular diseases, and pneumonia and influenza resulted from PM2.5 exposure were 9.1, 14.3, 18.3 and 26.4%, respectively. For the short-term effect resulted from the daily exposure, an increase in total daily mortality was 7.8%. If based on proportional rollback method stated in the USEPA’s guideline, and assuming an annual standard of 15 μg m-3and a daily 24-hr standard of 35 μg m-3 have been achieved, percent decreases in total mortality and mortalities caused by cardiovascular diseases, cerebrovascular diseases, and pneumonia and influenza will be decreased 5.2, 7.8, 9.7, and 13.3%, respectively, assuming a PM2.5 background level of 5 μg m-3. Furthermore, this study also utilized Chemical Mass Balance (CMB), which is a receptor model, to analyze the contributions of PM2.5 sources. The main pollution source measured in Station Jhongshan is traffic (contribution percentage in the range of 30.6~60.5% in summer and of 67.9~76.5% in autumn), followed by ammonium sulfate due to by photochemical reactions and long-distance transportation (contribution percentage in the range of 24.2~29.6% in summer and of 18.0~21.7% in autumn), and the third pollution source of biomass burning (contribution percentage around 7.4~15.9% in summer and 17.5~11.4% in autumn). The crustal elements is the fourth contribution source in summer (contribution percentage in the range of 2.2~13.2%), while nitrate is the fourth contribution source in autumn (contribution percentage in the range of 2.6~6.8%). Similarly, the main pollution source measured in Station Anshun is traffic (contribution percentage in the range of 43.8~45.1% in summer and of 47.2~71.8% in autumn), followed by ammonium sulfate due to photochemical reactions and long-distance transportation (concentration percentage in the range of 18.1~24.2% in summer and of 20.6~22.0% in autumn). The third pollution source is biomass burning (contribution percentage in the range of 7.4~8.4 % in summer and of 8.4~10.6% in autumn). Nitrate is the fourth contribution source (contribution percentage in the range of 3.8~6.3%). This result indicates that the summer PM2.5 pollution contribution sources are mainly subjected to traffic and photochemical reaction products. To assess 12% decrease of PM2.5 concentration in Tainan metropolitan area, this study recommends in order of importance the strengthening of the projects on construction engineering controls, washing and sweeping of road dust, emission restriction on restaurant and dining, burning centralization of ghost-money, reducing outdoor biomass burning, and inspection and control of stationary sources of air pollution and, then, to select the strategic combination with the lowest cost using linear programming and cost benefit analysis.

Direct-reading PM2.5 measurement; Fine particulate matter; Chemical composition; Receptor model; Health risk assessment; PM2.5 control strategy