環境資源報告成果查詢系統

104年度臺南市細懸浮微粒固定污染源排放特徵與管制措施研擬計畫

中文摘要 本計畫乃臺南市政府環境保護局 (以下簡稱環保局) 調查分析本市歷年空氣品質不良事件日之細懸浮微粒(PM2.5)濃度分佈特性,探討本市歷年PM2.5濃度之時空分佈及變化趨勢,藉由管道PM2.5檢測及成分分析,建置指紋特徵資料及排放量,以模式模擬分析各類原生性細懸浮微粒排放源對本市周界細懸浮微粒濃度之貢獻量,以及依成本效益分析,研擬本市原生性細懸浮微粒排放源之管制順序。 彙整98年第一季~105年第三季4座監測站出現高濃度日(日平均值大於35μg/m3) 之比例計算,發生總次數比例大小依次為臺南站26.8%、新營站25.6%、善化站24.0%、安南站23.6%。各測站發生高濃度日之總和依序為:臺南站1348日、新營站1285日、善化站1203日、安南站1181日,數據顯示大臺南地區因地理位置不同而產生PM2.5高濃度日之差異性。臺南地區新營站、善化站、安南站、臺南站4座測站空品不良之發生成因之比較,較高比例PM2.5濃度與PM10濃度同時飆高,推測以原生性粒狀污染物為污染來源,而此現象在臺南地區PM2.5高濃度期間的污染成因之主因。 本計畫執行期間(366日)臺南4座監測站出現PM2.5濃度高等級(達54μg/m3)日數共計152日,各監測站出現高等級濃度次數(小時數)分別為新營站787小時、善化站826小時、安南站785小時、臺南站690小時,依相同成因選取時段撰寫污染成因分析及對策報告共54份。 歷年臺南市4測站在歷年PM10事件日中PM2.5/PM10比值之頻率分析圖顯示,僅新營站與常態分布相似,在善化站、安南站、臺南站PM10事件日中,PM2.5 對粒狀污染物的貢獻高於 PM10 的貢獻。 本計畫使用時間序列法公式為Holland(1999)年提出之迴歸公式完成PM2.5在新營站、臺南站、善化站與安南站4站之年變化趨勢分析,並通過統計分析的檢定,分析趨勢中可發現臺南市4站之濃度呈現遞減趨勢,其年變化率在 -2.7% ~ -4.8% 之間。 彙整102~104年全國30座執行PM2.5手動監測之測站區分為七大空品區、澎湖、金門、及馬祖,計算其年平均值變化。各空品區逐月濃度以12月至2月之間為最高,逐季以第一季或第四季濃度最高。以全國30座測站手動監測年平均值做比較,最高值均出現於雲嘉南空品區,年平均值最低值均出現於恆春站。102年執行至今手動監測數據之總平均,前3大最高值分別斗六站(33.5 µg/m3)、嘉義站(32.9 µg/m3)、及金門站(31.6 µg/m3)。 本計畫執行9根次管道PM2.5檢測,檢測結果顯示FPM排放特徵成分中,陰陽離子以硫酸根及鈉離子居多,重金屬以鋁及鐵居多。由排放量計算顯示,台灣紙業M01雜項紙漿製造程序P006管道粒狀物排放量73.12公噸/年及細懸浮微粒排放量44.55公噸/年均為9根次管道中之最高。大統益公司M05植物油處理製造程序P509管道粒狀物排放量0.11公噸/年及細懸浮微粒排放量0.07公噸/年則為9根次管道中之最低。 臺南原生性PM2.5排放貢獻量空間分布中,點源各行業之貢獻量範圍介於0.34 ~ 9.05 μg/m3,以鋼鐵工業之貢獻量為最高值,區域最高值出現於永康區,其值為10.27 μg/m3,推測應是受鋼鐵業最大貢獻量之影響所致。線源各篩選行業之最高值貢獻量範圍介於0.43 ~ 7.08 μg/m3,以柴油大貨車之貢獻量為最高值,區域性最高值都位於東區、北區以及永康交界處。面源各行業之最高值貢獻量範圍介於0.056 ~ 21.84 μg/m3,以鋪面道路之貢獻量為最高值,區域性高值皆位於東區、北區及永康交界處,與所有線源模擬貢獻量高值處有相似結果。臺南市原生性細懸浮微粒於點源、線源、面源等污染來源,除了農業燃燒之一期稻作及二期稻作有其季節期間特性外,其餘污染源在全年之每噸細懸浮微粒貢獻比例並無明顯之季節變化。 本研究採用LINGO 線性規劃模擬結果,針對點源、線源、面源共26種行業別,將以全臺南市細懸浮微粒濃度減量5%、10%、15%、16%、17%以及17.7%等六種管制情境進行模擬,在全臺南市細懸浮微粒濃度減量5%之情境下,總成本418萬元;減量10%之情境下,總成本5657萬元;減量15%之情境下,總成本2.09億元;減量16%之情境下,總成本至4.26億元;減量17%之情境下,總成本略達至11.9億元;但管制比例一旦提升至17.7%時,總成本則提高到788.8億元,其原因在17.7%減量情境時,各行業之細懸浮微粒減量比例皆已達或近達該行業防制措施之最大控制效率。 本計畫戴奧辛空氣品質監測分析結果顯示新營站及臺南站周界戴奧辛濃度穩定,並無明顯之變化。本計畫周界重金屬分析結果與歷年數據比較,差異性較大,估計由於環保署檢測PM10中重金屬,而本計畫檢測PM2.5中重金屬所造成之差異。 本計畫之成果掌握本市細懸浮微粒時空分布及高污染潛勢區域,以利研擬適宜之相關管制策略,建置本市主要固定污染源之總懸浮微粒與細懸浮微粒排放指紋資料庫、排放係數與排放量,並藉由研擬本市原生性細懸浮微粒排放源之最佳成本效益管制順序,提供環保局作為污染減量及管制策略之依據。
中文關鍵字 細懸浮微粒、高濃度事件日、排放指紋特徵、貢獻量分析

基本資訊

專案計畫編號 01-D34-B001 經費年度 104 計畫經費 4735 千元
專案開始日期 2015/10/01 專案結束日期 2016/09/30 專案主持人 王怡敦
主辦單位 臺南市政府環境保護局 承辦人 鄭秀雯 執行單位 南台灣環境科技股份有限公司

成果下載

類型 檔名 檔案大小 說明
期末報告 104年台南PM2.5計畫.pdf 17MB
英文摘要 The project is directed by the Tainan Municipal Environmental Protection Bureau (TEPA) to investigate the concentration distribution of fine suspended particles (PM2.5) on the day of adverse air quality events over the years, to analyze the spatial and temporal distribution of PM2.5 concentration and its changing trend, to test the pipeline PM2.5 concentration and composition and then to establish of fingerprint characteristics of the emissions, to simulate the contribution of various types of primary PM2.5 emission sources to the perimeter in the city, and to do the cost-effectiveness analysis, providing TEPA a control strategy of PM2.5 emissions in the Tainan city. According to the ambient PM2.5 data from the first quarter of 2009 to the third quarter of 2016, the proportion of the total number of high-concentration days (daily average concentration over 35μg/m3) in the four air quality monitoring stations was 26.8% in Tainan Station (TNS), 25.6% in Hsinyin Station (HYS), 24.0% in Shanghua Station (SHS), 23.6% in Annan Station (ANS). The total PM2.5 high-concentration days of the stations were as follows: TNS 1340 days, HYS 1281 days, SHS 1202 days, ANS 1179 days. The data show that there is a difference in PM2.5 concentration in the Tainan city due to its geographical location. The causes of the occurrence of bad air in the stations were compared. It is concluded that on the PM2.5 high-concentration days, particulate pollutants were not dominated by fine particles or coarse particles, which mean the main cause of particulate pollution could be the primary particulate. During the implementation of the project from October 2015 to September 2016, the occurrence of high-level PM2.5 concentration (hourly concentration over 54μg/m3) days at four monitoring stations in Tainan was 152 days. The number of high-level concentrations (hours) in the four stations were HYS 787 hours, SHS 826 hours,ANS 785 hours, and TNS 690 hours. According to the same pollution source, the time periods were selected and totally 54 reports of pollution source analysis and control strategy have been written. The frequency analysis chart of the PM2.5/PM10 ratio in the PM10 high concentration days shows that only the HYS is similar to the normal distribution; while in the SHS, the ANS, and the TNS, the contribution of PM2.5 to particulate pollutants is higher than that of PM10. The Holland (1999) time series method is used to calculate the change trend of PM2.5 in the four air quality monitoring stations in Tainan city. And through the statistical analysis of the test, the PM2.5 concentration of four stations showed a decreasing trend of the annual rate of change -2.7% ~ -4.8%. Total 30 PM2.5 manual monitoring stations were divided into seven air quality control areas (AQCA), Penghu, Jinmen and Matsu, and the PM2.5 concentration data from the year of 2013 to 2015 have been calculated. Monthly concentration of AQCAs show that, the PM2.5 concentration from December to February nest year are the highest period, and quarterly concentration showed that the highest concentrations are in the first quarter or the fourth quarter. Yearly average concentration showed that the highest value is found in the Yunlin, Chiayi, Tainan AQCA, and the lowest is in Hengchun station. To the date, the three highest PM2.5 concentration have been recorded are Douliou station 33.5 μg /m3, Chiayi Station 32.9 μg/m3, and Jinmen Station 31.6 μg/m3. The project carried out nine pipeline PM2.5 concentration and composition analysis. The results show that, within filterable particulate matter (FPM) emission, sulfate and sodium ions are the majority to the anions and cations category, and aluminum and iron are majority to the heavy metals category. From the calculation of yearly emission discharge, the total suspended particulate matter (TSP) in the pipeline P006 to the M01 miscellaneous pulp manufacturing process of Taiwan Pulp & Paper Corporation is 73.12 T/year and that of PM2.5 is 44.55 T / year, which both are the highest among the nine pipes. The TSP in the pipeline P509 to the M05 Vegetable Oil Processing Manufacturing Procedure of TTET Union Corporation is 0.11 T/year and that of PM2.5 is 0.07 T / year, which both are the lowest among the nine pipes. In the spatial distribution of contribution of PM2.5 in Tainan city, the contribution of each point source in the industry is in the range of 0.34 ~ 9.05 μg/m3. The contribution of iron and steel industry is the highest, and the highest value appears in Yongkang area (10.27 μg/m3), which is supposed to be due to the maximum contribution of the steel industry. The contribution of the highest value of the line source in each screening industry ranged from 0.43 ~ 7.08 μg/m3, with the contribution of the diesel truck being the highest and the highest regional value at the junction of the Eastern, North and Yongkang. The contribution of the highest value of area source was 0.056 ~ 21.84 μg/m3, the contribution of pavement was the highest, and the highest regional value was occurred at the junction of the Eastern, North and Yongkang. The areas with high values of area sources are similar to that of line sources. The primary source of PM2.5 in the point source, line source, area source and other sources of pollution, except the first and the second period of agricultural combustion of a rice has its seasonal time period, the discharge of other sources of PM2.5 pollution is no significant seasonal changes within a year. In this study, the LINGO linear programming is used to simulated the cost related to the reduction of the PM2.5 emission of 26 pollution sources. Six control scenarios will be simulated, i.e., 5%, 10%, 15%, 16%, 17% and 17.7%. The total cost will be 4.18 million NT dollars in the context of a reduction of 5%. The total cost will be 56.57 million NT dollars in the context of a reduction of 10%. The total cost will be 209 million NT dollars in the context of a reduction of 15%. The total cost will be 426 billion NT dollars in the context of a reduction of 16%. The total cost will be 1190 billion NT dollars in the context of a reduction of 17%. However, once the regulatory ratio is raised to 17.7%, the total cost is increased to 78880 billion NT dollars. The reason is that in the 17.7% reduction scenario, the proportion of PM2.5 in various industries has reached or nearly reached the maximum control efficiency of the industry's control measures. The ambient Dioxin has been tested at the HYS and TNS. The results showed that the concentration of dioxin was no significant change at the HYS and TNS, comparing the results of ambient Dioxin concentration at these two stations in the past. The results of the analysis of ambient heavy metals in the HYS are quite different from those of previous years. The possible reason of the differences could be due that ambient heavy metals were detected in PM10 in the past research by EPA, and thus those were detected in PM2.5 in this project. The achievements of this project are to show the spatial and temporal distribution of PM2.5 and high pollution potential areas in the city to facilitate the development of appropriate control strategies. The establishment of the city's main pollution sources of TSP and PM2.5 emissions from fingerprint databases, emission factors and emissions. And the results of the project provide the Tainan EPA with the basis for pollution abatement and control strategies by developing the best cost-effectiveness control sequence for the city's indigenous PM2.5 emission sources.
英文關鍵字 fine suspended particles, high concentration event days, emission fingerprint, contribution analysis