環保專案成果報告查詢系統

專案計畫編號	EPA-107-L101-02-A024
經費年度	107
計畫經費	1,837 千元
預算科目	科技發展-環境科學及技術之研究
專案開始日期	2018/01/09
專案結束日期	2018/12/31
專案主持人	李崇德
主辦單位	監資處
承辦人	黃健瑋
執行單位	國李中央大學
專案分類	環境監測及檢測
中文關鍵字	PM2.5化學成分監測、PM2.5化學成分時間與空間分布特徵、推估PM2.5污染源及能見度影響因子、金屬元素自動儀器監測評估
英文關鍵字	PM2.5 chemical component monitoring, Characteristics of temporal and spatial distributions of PM2.5 chemical components, PM2.5 source apportionment and visibility influencing factors, Assessment of automated monitoring of metal elements
協同主持人	王家麟、周崇光、張士昱、蕭大智、許文昌
共同主持人
計畫聯絡人	黃秋華
計畫聯絡電話	03-4226551#
計畫聯絡信箱	cwhuang@epa.gov.tw

中文摘要	本計畫呈現2018年1月到2018年11月(外加2017年12月)於板橋、忠明、斗六、嘉義、小港及花蓮測站6天1次例行採樣以及分析的PM2.5水溶性離子、碳成分、金屬元素等化學成分成果。此外，本年度還評估元素監測自動儀器適宜性及新增建置有機物分析方法。以所分析的水溶性離子成分、碳成分及金屬元素成分，本計畫配合天氣因子、風場模擬等資料，用來探討PM2.5質量濃度與化學成分時間與空間分布特性、解析污染來源及評估能見度影響因子。結果顯示，PM2.5濃度於採樣期間呈現由東(10 μg m-3)而北而南(24 μg m-3)遞增，花蓮、板橋、忠明站在春季濃度最高，斗六、嘉義、小港站以冬季最高，夏季則為各測站PM2.5濃度最低季節。各測站PM2.5化學成分多以SO42-與OC為主，但是斗六、嘉義及小港站的冬季以NO3-為主。金屬成分可分成高、中、低濃度群，高濃度元素群來源多為自然源，中濃度金屬元素群多來自燃油燃燒、燃煤燃燒、金屬冶煉、交通排放，低濃度金屬元素群則來自燃煤燃燒、金屬表面塗敷、剎車及輪胎磨損。半揮發性離子修正結果顯示NO3-和Cl-分別在夏季和春季揮發比例最高，NH4+則季節變化穩定；溫度、污染來源、揮發成分的化合物結合型態都是影響揮發特性的因子。石英濾紙吸附的碳成分正干擾變化穩定，在採集碳成分微粒揮發的負干擾主要受污染源及污染事件差異影響。有機物分析方法成功地利用以氣流型調制器為核心的全面二維氣相層析串連時間飛行質譜儀 (GC×GC-TOF MS)，分析微粒中微量有機成分，板橋站PM2.5有機物以含氮化合物以及塑化劑占最大比例。解析採樣期間PM2.5大於35 μg m-3的事件日，從北到南有逐漸增加趨勢，多數污染事件成因為環境擴散條件不佳受到在地污染累積影響，常從採樣前天夜晚累積延續到採樣日，區域污染傳輸則常與在地污染同日發生而加劇污染事件。此外，冬末春初污染事件常有高臭氧濃度。比較所有事件與非事件樣本PM2.5化學成分，NO3-濃度占比增大現象與過去三年研究結果一致。如果分季節，比較事件與當季非事件期間PM2.5化學成分濃度差異百分比，發現冬季污染事件SO42-和NO3-增量相當，燃油與燃媒燃燒指標元素的增量較為明顯。春季污染事件以NO3-與Cl 有明顯增量，SO42-增量較小，碳成分中則以EC增量較大，交通排放與燃油燃煤燃燒對於春季污染物濃度的貢獻十分顯著。秋季污染事件的NO3-與Cl 增量明顯，SO42-增量較小，各站有生質燃燒、工業排放及交通污染貢獻。 PMF受體模式解析以「硫酸鹽與燃燒排放」、「硝酸鹽與燃燒排放」為前二高貢獻因子。板橋、忠明及花蓮站以「硫酸鹽與燃燒排放」因子為主，斗六、嘉義及小港站最高占比因子則是「硝酸鹽與燃燒排放」；顯示區域污染傳輸對於台中以北及花蓮地區影響程度大，雲林縣以南地區則受到擴散條件不佳，污染衍生物的在地影響程度大。為推估大氣消光係數(bext)，各站以PM2.5化學成分、氣體分子、相對濕度代入修正的IMPROVE方程式，結果以硫酸鹽對bext貢獻最為穩定而顯著，但冬季斗六、嘉義及小港站硝酸鹽的貢獻較多。同樣地，SO42-是統計廻歸分析影響能見度最為穩定而顯著因子，與修正的IMPROVE方程式推估結果一致。金屬元素自動儀器與手動儀器廻歸分析結果指出：相關性良好的元素，分別是來自交通排放 (Zn、Ba、V、Cu)、燃煤燃燒(Pb)、燃油燃燒(V)、生質燃燒(K)、金屬冶煉(Mn、Cu、Pb)等污染源，這些大多是大氣常見的金屬元素，因此自動儀器在定性污染源辨識上仍具有價值。從污染成因和污染源管制角度來看，各項污染源燃燒排放及停滯環境是污染主要成因，NOx及構成光化學反應前驅氣體的控制將有助於降低高PM2.5事件，公私場所在夜間作業應注意控制污染排放，塑化劑及含氮有機物的來源值得關注。
中文關鍵字	PM2.5化學成分監測、PM2.5化學成分時間與空間分布特徵、推估PM2.5污染源及能見度影響因子、金屬元素自動儀器監測評估

中文摘要

本計畫呈現2018年1月到2018年11月(外加2017年12月)於板橋、忠明、斗六、嘉義、小港及花蓮測站6天1次例行採樣以及分析的PM2.5水溶性離子、碳成分、金屬元素等化學成分成果。此外，本年度還評估元素監測自動儀器適宜性及新增建置有機物分析方法。以所分析的水溶性離子成分、碳成分及金屬元素成分，本計畫配合天氣因子、風場模擬等資料，用來探討PM2.5質量濃度與化學成分時間與空間分布特性、解析污染來源及評估能見度影響因子。結果顯示，PM2.5濃度於採樣期間呈現由東(10 μg m-3)而北而南(24 μg m-3)遞增，花蓮、板橋、忠明站在春季濃度最高，斗六、嘉義、小港站以冬季最高，夏季則為各測站PM2.5濃度最低季節。各測站PM2.5化學成分多以SO42-與OC為主，但是斗六、嘉義及小港站的冬季以NO3-為主。金屬成分可分成高、中、低濃度群，高濃度元素群來源多為自然源，中濃度金屬元素群多來自燃油燃燒、燃煤燃燒、金屬冶煉、交通排放，低濃度金屬元素群則來自燃煤燃燒、金屬表面塗敷、剎車及輪胎磨損。半揮發性離子修正結果顯示NO3-和Cl-分別在夏季和春季揮發比例最高，NH4+則季節變化穩定；溫度、污染來源、揮發成分的化合物結合型態都是影響揮發特性的因子。石英濾紙吸附的碳成分正干擾變化穩定，在採集碳成分微粒揮發的負干擾主要受污染源及污染事件差異影響。有機物分析方法成功地利用以氣流型調制器為核心的全面二維氣相層析串連時間飛行質譜儀 (GC×GC-TOF MS)，分析微粒中微量有機成分，板橋站PM2.5有機物以含氮化合物以及塑化劑占最大比例。解析採樣期間PM2.5大於35 μg m-3的事件日，從北到南有逐漸增加趨勢，多數污染事件成因為環境擴散條件不佳受到在地污染累積影響，常從採樣前天夜晚累積延續到採樣日，區域污染傳輸則常與在地污染同日發生而加劇污染事件。此外，冬末春初污染事件常有高臭氧濃度。比較所有事件與非事件樣本PM2.5化學成分，NO3-濃度占比增大現象與過去三年研究結果一致。如果分季節，比較事件與當季非事件期間PM2.5化學成分濃度差異百分比，發現冬季污染事件SO42-和NO3-增量相當，燃油與燃媒燃燒指標元素的增量較為明顯。春季污染事件以NO3-與Cl 有明顯增量，SO42-增量較小，碳成分中則以EC增量較大，交通排放與燃油燃煤燃燒對於春季污染物濃度的貢獻十分顯著。秋季污染事件的NO3-與Cl 增量明顯，SO42-增量較小，各站有生質燃燒、工業排放及交通污染貢獻。 PMF受體模式解析以「硫酸鹽與燃燒排放」、「硝酸鹽與燃燒排放」為前二高貢獻因子。板橋、忠明及花蓮站以「硫酸鹽與燃燒排放」因子為主，斗六、嘉義及小港站最高占比因子則是「硝酸鹽與燃燒排放」；顯示區域污染傳輸對於台中以北及花蓮地區影響程度大，雲林縣以南地區則受到擴散條件不佳，污染衍生物的在地影響程度大。為推估大氣消光係數(bext)，各站以PM2.5化學成分、氣體分子、相對濕度代入修正的IMPROVE方程式，結果以硫酸鹽對bext貢獻最為穩定而顯著，但冬季斗六、嘉義及小港站硝酸鹽的貢獻較多。同樣地，SO42-是統計廻歸分析影響能見度最為穩定而顯著因子，與修正的IMPROVE方程式推估結果一致。金屬元素自動儀器與手動儀器廻歸分析結果指出：相關性良好的元素，分別是來自交通排放 (Zn、Ba、V、Cu)、燃煤燃燒(Pb)、燃油燃燒(V)、生質燃燒(K)、金屬冶煉(Mn、Cu、Pb)等污染源，這些大多是大氣常見的金屬元素，因此自動儀器在定性污染源辨識上仍具有價值。從污染成因和污染源管制角度來看，各項污染源燃燒排放及停滯環境是污染主要成因，NOx及構成光化學反應前驅氣體的控制將有助於降低高PM2.5事件，公私場所在夜間作業應注意控制污染排放，塑化劑及含氮有機物的來源值得關注。

中文關鍵字

PM2.5化學成分監測、PM2.5化學成分時間與空間分布特徵、推估PM2.5污染源及能見度影響因子、金屬元素自動儀器監測評估

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	期末報告定稿.pdf	38MB	工作報告	2019/2/1 上午 12:00:00

摘要	This study presents the results of regular PM2.5 (aerodynamic diameters equal to or smaller than 2.5 μm) collection at the Banqiao, Zongming, Douliu, Chiayi, Xiaogang, and Hualien sites in Taiwan every six days from January to November in 2018 (with the additional December 2017 data). PM2.5 mass, water-soluble inorganic ions, carbonaceous contents, and metal elements were resolved for further analysis. In addition, the work also assessed the comparability of metal element monitoring from an automated instrument and established a new organic compound analytical method. Utilizing the analyzed water-soluble inorganic ions, carbonaceous contents, and metal elements, this study investigated the characteristics of temporal and spatial distributions of PM2.5 mass and chemical components, apportioned source contributions, and evaluated atmospheric visibility influencing factors. The results showed that PM2.5 mass levels increased in the order from east (10 μg m-3), north, to the south (24 μg m-3) of Taiwan during the sampling period. The season of highest PM2.5 mass levels at the Banqiao, Zongming, and Hualien sites were in spring, while that of the Douliu, Chiayi, and Xiaogan sites were in winter. Summer was the lowest season of PM2.5 mass levels at all sites. In general, SO42- and organic carbon were the two most abundant components at all sites except NO3- at the Douliu, Chiayi, and Xiaogan sites in winter. Among high, medium, and low concentration groups of metal elements, high concentration group was with natural origins, while medium concentration group was with contributions mostly from fuel oil and coal burnings, metal refining, and traffic emissions. In contrast, the low concentration group was with characteristics of coal burning, metal surface coating, and brake and tire wearing. The volatilizations of NO3- and Cl- were the highest in summer and spring, respectively, while NH4+ was relatively stable across seasons. Influencing volatilization factors include ambient temperature, pollution sources, and chemical compound forms of volatilized components. Meanwhile, positive interferences of volatilized organic carbons adsorbed by quartz-fiber filters varied less than negative interferences from volatilization of the collected carbonaceous particles. Volatilization of the collected carbonaceous particles were primarily under the influences of pollution sources and events. For the trace contents of organic compounds, this study successfully utilized gas flow modulator as a core with a full fledge of two-dimension gas chromatography coupled with time-flight mass spectrometry. The Qualitative organic contents of PM2.5 comprised mostly nitrogenous and phthalate compounds at the Banqiao site. During the sampling period, events with PM2.5 greater than 35 μg m-3 tended to increase from north to south. Most events were under the influences of bad environmental ventilation and local source emissions and frequently originated from previous night of the sampling day. The events often got worse accompanied by regional pollution transport on the same day. In addition, high ozone concentration frequently occurred in the pollution events of late winter and early spring. From the resolved component ratios in PM2.5, NO3- was the sole component increased greatly in all high PM2.5 events in contrast to non-event samples, which was consistent with the findings over the past three years. For seasonal variations, the enhancements of SO42-, NO3-, and fuel oil- and coal-burning tracers were predominant in winter. However, in spring, NO3-, Cl , EC, traffic emissions, fuel oil- and coal-burning tracers increased prevalently but with less SO42- increase. Similarly, the enhancements of NO3-, Cl , biomass burning, industrial sources, and traffic emissions were significant but with less SO42- in fall. For source apportionment using positive matrix factorization, “sulfate and combustion emissions” and “nitrate and combustion emissions” were the two most significant factors at all sites. The factor of “sulfate and combustion emissions” was dominant at the Banqiao, Zongming, and Hualien sites in contrast to the dominance of “nitrate and combustion emissions” at the Douliu, Chiayi, and Xiaogang sites. This implies regional transport is prominent in the areas north to Taichung City and Hualien County, while accumulated pollutants derived from local sources are important in the areas south to Yulin County. To estimate atmospheric light extinction coefficient (bext), this study inserted PM2.5 chemical components, gas species, and relative humidity (RH) into the revised Interagency Monitoring of Protected Visual Environments (IMPROVE) equation. Sulfate contributed bext the most of all components at all sites except nitrate at the Douliu, Chiayi, and Xiaogang sites in winter. Similarly, SO42- was the most important factor in influencing atmospheric visibility from statistical regression analysis, which was consistent with the finding in the revised IMPROVE equation. The regression analysis of metal elements between automated and manual collection methods showed that metal elements with good correlation were those from sources of traffic emissions (Zn、Ba、V、Cu), coal burning (Pb), fuel-oil burning (V), biomass burning (K), and metal smelting (Mn、Cu、Pb). As those elements are abundant in the atmosphere, the automated instrument is still valuable in qualitative identification of pollution sources. Looking into the causes of pollution events and control measures, fuel burning emissions and stagnant environment are main causes of pollution. The control of NOx and ozone precursors will help in reducing high PM2.5 events. Stringent control on evening emissions of public and private sectors is necessary. The origins of nitrogenous and phthalate compounds are of concern.
英文關鍵字	PM2.5 chemical component monitoring, Characteristics of temporal and spatial distributions of PM2.5 chemical components, PM2.5 source apportionment and visibility influencing factors, Assessment of automated monitoring of metal elements

摘要

This study presents the results of regular PM2.5 (aerodynamic diameters equal to or smaller than 2.5 μm) collection at the Banqiao, Zongming, Douliu, Chiayi, Xiaogang, and Hualien sites in Taiwan every six days from January to November in 2018 (with the additional December 2017 data). PM2.5 mass, water-soluble inorganic ions, carbonaceous contents, and metal elements were resolved for further analysis. In addition, the work also assessed the comparability of metal element monitoring from an automated instrument and established a new organic compound analytical method. Utilizing the analyzed water-soluble inorganic ions, carbonaceous contents, and metal elements, this study investigated the characteristics of temporal and spatial distributions of PM2.5 mass and chemical components, apportioned source contributions, and evaluated atmospheric visibility influencing factors. The results showed that PM2.5 mass levels increased in the order from east (10 μg m-3), north, to the south (24 μg m-3) of Taiwan during the sampling period. The season of highest PM2.5 mass levels at the Banqiao, Zongming, and Hualien sites were in spring, while that of the Douliu, Chiayi, and Xiaogan sites were in winter. Summer was the lowest season of PM2.5 mass levels at all sites. In general, SO42- and organic carbon were the two most abundant components at all sites except NO3- at the Douliu, Chiayi, and Xiaogan sites in winter. Among high, medium, and low concentration groups of metal elements, high concentration group was with natural origins, while medium concentration group was with contributions mostly from fuel oil and coal burnings, metal refining, and traffic emissions. In contrast, the low concentration group was with characteristics of coal burning, metal surface coating, and brake and tire wearing. The volatilizations of NO3- and Cl- were the highest in summer and spring, respectively, while NH4+ was relatively stable across seasons. Influencing volatilization factors include ambient temperature, pollution sources, and chemical compound forms of volatilized components. Meanwhile, positive interferences of volatilized organic carbons adsorbed by quartz-fiber filters varied less than negative interferences from volatilization of the collected carbonaceous particles. Volatilization of the collected carbonaceous particles were primarily under the influences of pollution sources and events. For the trace contents of organic compounds, this study successfully utilized gas flow modulator as a core with a full fledge of two-dimension gas chromatography coupled with time-flight mass spectrometry. The Qualitative organic contents of PM2.5 comprised mostly nitrogenous and phthalate compounds at the Banqiao site. During the sampling period, events with PM2.5 greater than 35 μg m-3 tended to increase from north to south. Most events were under the influences of bad environmental ventilation and local source emissions and frequently originated from previous night of the sampling day. The events often got worse accompanied by regional pollution transport on the same day. In addition, high ozone concentration frequently occurred in the pollution events of late winter and early spring. From the resolved component ratios in PM2.5, NO3- was the sole component increased greatly in all high PM2.5 events in contrast to non-event samples, which was consistent with the findings over the past three years. For seasonal variations, the enhancements of SO42-, NO3-, and fuel oil- and coal-burning tracers were predominant in winter. However, in spring, NO3-, Cl , EC, traffic emissions, fuel oil- and coal-burning tracers increased prevalently but with less SO42- increase. Similarly, the enhancements of NO3-, Cl , biomass burning, industrial sources, and traffic emissions were significant but with less SO42- in fall. For source apportionment using positive matrix factorization, “sulfate and combustion emissions” and “nitrate and combustion emissions” were the two most significant factors at all sites. The factor of “sulfate and combustion emissions” was dominant at the Banqiao, Zongming, and Hualien sites in contrast to the dominance of “nitrate and combustion emissions” at the Douliu, Chiayi, and Xiaogang sites. This implies regional transport is prominent in the areas north to Taichung City and Hualien County, while accumulated pollutants derived from local sources are important in the areas south to Yulin County. To estimate atmospheric light extinction coefficient (bext), this study inserted PM2.5 chemical components, gas species, and relative humidity (RH) into the revised Interagency Monitoring of Protected Visual Environments (IMPROVE) equation. Sulfate contributed bext the most of all components at all sites except nitrate at the Douliu, Chiayi, and Xiaogang sites in winter. Similarly, SO42- was the most important factor in influencing atmospheric visibility from statistical regression analysis, which was consistent with the finding in the revised IMPROVE equation. The regression analysis of metal elements between automated and manual collection methods showed that metal elements with good correlation were those from sources of traffic emissions (Zn、Ba、V、Cu), coal burning (Pb), fuel-oil burning (V), biomass burning (K), and metal smelting (Mn、Cu、Pb). As those elements are abundant in the atmosphere, the automated instrument is still valuable in qualitative identification of pollution sources. Looking into the causes of pollution events and control measures, fuel burning emissions and stagnant environment are main causes of pollution. The control of NOx and ozone precursors will help in reducing high PM2.5 events. Stringent control on evening emissions of public and private sectors is necessary. The origins of nitrogenous and phthalate compounds are of concern.

英文關鍵字

PM2.5 chemical component monitoring, Characteristics of temporal and spatial distributions of PM2.5 chemical components, PM2.5 source apportionment and visibility influencing factors, Assessment of automated monitoring of metal elements