環保專案成果報告查詢系統

專案計畫編號
經費年度	109
計畫經費	19,550 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	2020/01/08
專案結束日期	2020/12/31
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	國立中央大學
專案分類	大氣空氣、環境監測及檢測
中文關鍵字	PM2.5化學成分監測、PM2.5化學特徵時間和空間分布、交通源PM2.5化學特徵、PM2.5污染源推估、大氣能見度影響因子
英文關鍵字	PM2.5 chemical component monitoring, Temporal and spatial distributions of PM2.5 chemical characteristics, PM2.5 chemical characteristics of traffic sources, PM2.5 source apportionment, Atmospheric visibility-influencing factors.
協同主持人	周崇光、張士昱、蕭大智、莊銘棟、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	cilia0110@gmail.com

中文摘要	本計畫於2020年在環保署板橋、忠明、斗六、嘉義、小港及花蓮測站每六天一次同步進行例行性PM2.5採樣，另外，為瞭解機動車輛排放特徵，在臺中市臺灣大道測站進行近交通源PM2.5採樣。例行性與近交通源樣本分析PM2.5水溶性無機離子、碳成分、金屬元素，例行性樣本同時分析了塑化劑成分。所分析的PM2.5化學成分(含2019年12月)，配合監測站空品數據、環境因子以及模式模擬資料，本計畫探討與推演PM2.5質量濃度與化學成分的時間與空間分布特徵、高濃度事件特徵、特定情境特徵、污染源因子、大氣能見度影響因子等議題。 2020年PM2.5質量濃度和環保署常規手動採樣結果具有一致性，PM2.5質量濃度在冬、春、秋三季呈現由東至北再向南部遞增趨勢；冬季PM2.5最主要化學成分在花蓮與板橋站為OC，其餘測站都是NO3-，春、夏、秋季，各站最主要成分大多是OC。2020年SO42-不再是最主要成分，顯示出管制含硫燃料燃燒源的成效。各測站共同的高濃度金屬元素(Na和K)，在空間上呈現由東至北向南部遞增的分布，各測站突顯的金屬元素，展現了地區間污染源特徵。2020年各季節分別修正補償12~21%的NH4+與17~38%的NO3-質量濃度損失。若無進行修正，對於單一樣本有機碳成分質量濃度會造成從高估89%到低估23%的誤差分布。塑化劑在各站大氣濃度甚低，以DEHP、DBP、DnOP濃度相對較高。臺灣大道的近交通源採樣，上班較下班時段多有較高的PM2.5質量濃度、NO3-、OC、EC濃度，兩時段較突出的化學成分為OC，代表汽油車排放特徵。2020年冬季發生高PM2.5濃度日(≥ 30 μg m-3)集中於中部以南測站，以在地污染影響較大，且前夜污染｢殘留」普遍存在這些測站；春季的高PM2.5濃度日則大幅下降。2020年8月受到日本西之島火山灰傳輸影響，花蓮站PM2.5濃度增加2倍以上，PM2.5富含SO42-、NH4+及地殼元素，並以稀土元素Y增量近10倍最為顯著。分類近四年採樣日PM2.5質量濃度為高、中、低濃度群，發現管制NO3-前驅污染源，可於中濃度群(15~35 μg m-3)就有PM2.5減量效益。透過CMAQ模式模擬高PM2.5濃度事件NO3-的增量機制，發現日間光化學作用與夜間N2O5異相水解反應為主要成因。近四年PM2.5濃度較高期間(12月~4月)SO42-濃度遞減穩定，顯示固定污染源化石燃料燃燒活動逐漸降低，但各地2020年EC濃度普遍反增，NO3-與OC則於2019和2020年反增或是持平，顯示移動污染源，將成為改善高PM2.5濃度期間空氣品質的主要目標。在傳統節日後採樣的樣本富含煙火和拜香指標金屬元素。在冬、春季台灣北部及東部受到境外污染傳輸影響時，SO42-、NO3-、NH4+、K+以及鋼鐵、水泥、燃煤指標元素都有顯著的濃度增量。嘉義站Ba、Pb及Ga金屬元素明顯增量，顯示受到燃煤燃燒、鋼鐵業、生質燃燒、民俗活動傳輸影響。二次有機碳推估成果指出加強中部以南地區揮發性有機氣體污染源的排放管制，將有助於減少衍生性PM2.5濃度。比較PM2.5濃度在COVID-19疫情期間與過去三年延伸的下降趨勢，中部至雲嘉地區可能因工業活動的降低而有較多的PM2.5減量。以PMF (positive matrix factorization)受體模式推估近四年數據得出九項污染源因子，其中，硫酸鹽、硝酸鹽與車輛排放是各測站前三大污染源，車輛排放於近四年斗六以北測站影響逐年增加。以IMPROVE修正方程式推估大氣消光係數(bext)，發現各測站硫酸鹽和有機物在各季節對bext貢獻量穩定，硝酸鹽在冬、春季對斗六以南測站貢獻量最高。在大氣能見度統計廻歸分析中，同樣發現SO42-、NO3-、OC是重要的PM2.5化學成分。在PM2.5化學成分採樣檢測經驗與最新技術方面，本計畫已完成彙整32篇近年各國相關文獻。綜合而言，本計畫持續提供臺灣六個都市測站PM2.5質量濃度與化學成分(含塑化劑)和近交通源PM2.5指標化學成分數據，並推演出 PM2.5時間與空間分布特徵，另外還解析特定時間和地點PM2.5化學成分特徵、污染源因子貢獻占比、影響大氣能見度因子等議題，研究成果可做為健康風險評估和管制策略擬定的科學基礎資料。
中文關鍵字	PM2.5化學成分監測、PM2.5化學特徵時間和空間分布、交通源PM2.5化學特徵、PM2.5污染源推估、大氣能見度影響因子

中文摘要

本計畫於2020年在環保署板橋、忠明、斗六、嘉義、小港及花蓮測站每六天一次同步進行例行性PM2.5採樣，另外，為瞭解機動車輛排放特徵，在臺中市臺灣大道測站進行近交通源PM2.5採樣。例行性與近交通源樣本分析PM2.5水溶性無機離子、碳成分、金屬元素，例行性樣本同時分析了塑化劑成分。所分析的PM2.5化學成分(含2019年12月)，配合監測站空品數據、環境因子以及模式模擬資料，本計畫探討與推演PM2.5質量濃度與化學成分的時間與空間分布特徵、高濃度事件特徵、特定情境特徵、污染源因子、大氣能見度影響因子等議題。 2020年PM2.5質量濃度和環保署常規手動採樣結果具有一致性，PM2.5質量濃度在冬、春、秋三季呈現由東至北再向南部遞增趨勢；冬季PM2.5最主要化學成分在花蓮與板橋站為OC，其餘測站都是NO3-，春、夏、秋季，各站最主要成分大多是OC。2020年SO42-不再是最主要成分，顯示出管制含硫燃料燃燒源的成效。各測站共同的高濃度金屬元素(Na和K)，在空間上呈現由東至北向南部遞增的分布，各測站突顯的金屬元素，展現了地區間污染源特徵。2020年各季節分別修正補償12~21%的NH4+與17~38%的NO3-質量濃度損失。若無進行修正，對於單一樣本有機碳成分質量濃度會造成從高估89%到低估23%的誤差分布。塑化劑在各站大氣濃度甚低，以DEHP、DBP、DnOP濃度相對較高。臺灣大道的近交通源採樣，上班較下班時段多有較高的PM2.5質量濃度、NO3-、OC、EC濃度，兩時段較突出的化學成分為OC，代表汽油車排放特徵。2020年冬季發生高PM2.5濃度日(≥ 30 μg m-3)集中於中部以南測站，以在地污染影響較大，且前夜污染｢殘留」普遍存在這些測站；春季的高PM2.5濃度日則大幅下降。2020年8月受到日本西之島火山灰傳輸影響，花蓮站PM2.5濃度增加2倍以上，PM2.5富含SO42-、NH4+及地殼元素，並以稀土元素Y增量近10倍最為顯著。分類近四年採樣日PM2.5質量濃度為高、中、低濃度群，發現管制NO3-前驅污染源，可於中濃度群(15~35 μg m-3)就有PM2.5減量效益。透過CMAQ模式模擬高PM2.5濃度事件NO3-的增量機制，發現日間光化學作用與夜間N2O5異相水解反應為主要成因。近四年PM2.5濃度較高期間(12月~4月)SO42-濃度遞減穩定，顯示固定污染源化石燃料燃燒活動逐漸降低，但各地2020年EC濃度普遍反增，NO3-與OC則於2019和2020年反增或是持平，顯示移動污染源，將成為改善高PM2.5濃度期間空氣品質的主要目標。在傳統節日後採樣的樣本富含煙火和拜香指標金屬元素。在冬、春季台灣北部及東部受到境外污染傳輸影響時，SO42-、NO3-、NH4+、K+以及鋼鐵、水泥、燃煤指標元素都有顯著的濃度增量。嘉義站Ba、Pb及Ga金屬元素明顯增量，顯示受到燃煤燃燒、鋼鐵業、生質燃燒、民俗活動傳輸影響。二次有機碳推估成果指出加強中部以南地區揮發性有機氣體污染源的排放管制，將有助於減少衍生性PM2.5濃度。比較PM2.5濃度在COVID-19疫情期間與過去三年延伸的下降趨勢，中部至雲嘉地區可能因工業活動的降低而有較多的PM2.5減量。以PMF (positive matrix factorization)受體模式推估近四年數據得出九項污染源因子，其中，硫酸鹽、硝酸鹽與車輛排放是各測站前三大污染源，車輛排放於近四年斗六以北測站影響逐年增加。以IMPROVE修正方程式推估大氣消光係數(bext)，發現各測站硫酸鹽和有機物在各季節對bext貢獻量穩定，硝酸鹽在冬、春季對斗六以南測站貢獻量最高。在大氣能見度統計廻歸分析中，同樣發現SO42-、NO3-、OC是重要的PM2.5化學成分。在PM2.5化學成分採樣檢測經驗與最新技術方面，本計畫已完成彙整32篇近年各國相關文獻。綜合而言，本計畫持續提供臺灣六個都市測站PM2.5質量濃度與化學成分(含塑化劑)和近交通源PM2.5指標化學成分數據，並推演出 PM2.5時間與空間分布特徵，另外還解析特定時間和地點PM2.5化學成分特徵、污染源因子貢獻占比、影響大氣能見度因子等議題，研究成果可做為健康風險評估和管制策略擬定的科學基礎資料。

中文關鍵字

PM2.5化學成分監測、PM2.5化學特徵時間和空間分布、交通源PM2.5化學特徵、PM2.5污染源推估、大氣能見度影響因子

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	109年細懸浮微粒(PM2.5)化學成分監測及分析計畫.pdf	34MB		2021/6/1 上午 12:00:00

摘要	This study collected PM2.5 (aerodynamic diameters equal to or smaller than 2.5 μm) regularly every six days per shift at the Banqiao, Zhongming, Douliu, Chiayi, Xiaogang, and Hualien air quality monitoring sites of Environmental Protection Administration (EPA) in Taiwan in 2020. Besides, PM2.5 was collected near traffic sources at the Taiwan Boulevard site for finding vehicle emissions characteristics. PM2.5 mass, water-soluble inorganic ions, carbonaceous contents, and metal elements were analyzed for the regular and near-source samples. Meanwhile, phthalate esters were also analyzed for the regular samples. This study investigated and derived the characteristics of temporal and spatial distributions of PM2.5 mass and chemical components (including the data of December 2019), high concentration events, specific scenarios, the apportioned source factors, and atmospheric visibility-influencing factors by utilizing the analyzed PM2.5 chemical components, air quality monitoring data, environmental factors, and the corresponding model simulation products. The PM2.5 mass concentration of this study is consistent with that of the EPA's regular manual collection. Seasonal PM2.5 mass levels increased from east, north, to the south of Taiwan during winter, spring, and autumn. Organic carbon (OC) was the most abundant component at the Hualien and Banqiao sites and NO3- for the other sites in winter. In contrast, OC was the most abundant component at most sites in spring, summer, and autumn. SO42- lost the role as the leading component in 2020, which reflected an effective control on the combustion sources of sulfur-containing fossil fuel. The mutual high-abundance metal elements (Na and K) across sites increased in concentrations from east, north, to the south of Taiwan. The distinct metal elements exhibited source characteristics among sites. The volatilization corrections compensated 12~21% and 17~38% of NH4+ and NO3- mass losses, respectively, in 2020. The error distribution of OC concentration will spread from 89% overestimation to 23% underestimation. Similarly, positive interferences also showed no spatial distinction. Ambient levels of phthalate esters were very low, with relatively high values for DEHP, DBP, and DnOP at each site. For near-source traffic emissions at the Taiwan Boulevard site, PM2.5 mass, NO3-, OC, and EC concentrations were higher during on- than off-duty rush hours. OC representing gasoline vehicle emissions was the most abundant component during on- and off-duty rush hours. The high PM2.5 concentration days (≥ 30 μg m-3), caused by local pollution and predominantly with “residual layer” in the preceding night, were mainly distributed south to central Taiwan in winter 2020. By contrast, the number of high PM2.5 concentration days declined considerably in spring. In August 2020, the PM2.5 concentration at the Hualien site increased more than twice with the abundance of SO42-, NH4+, and crustal elements and a 10-fold increase of rare-earth element Yttrium was the most stunning discovery under the influence of the long-range transport of the erupted Nishinoshima of Japan. By classifying PM2.5 mass concentrations of sampling days of the recent four years into high, medium, and low concentration groups, PM2.5 reduction benefits are evident for the medium concentration group (15~35 μg m-3) when NO3- precursor emission sources are in control. The results from Community Multiscale Air Quality Model (CMAQ) discovered that daytime photochemical reaction and nighttime N2O5 heterogeneous hydrolysis were the mechanism of NO3- enhancement in high PM2.5 concentration events. The stable declination of SO42- concentration during higher PM2.5 concentration period (from December to April) of the recent four years implied a reduction of fossil-fuel combustion activities from stationary sources. In contrast, reversibly increased EC concentration in 2020 and either reversibly increased or in the flat fashion of NO3- and OC concentrations in 2019 and 2020 imply that mobile sources will be the next target for improving the air quality of high PM2.5 concentration period. The samples collected after traditional festivals were rich in the tracer elements of firecracker and incense. Concentration enhancements of SO42-, NO3-, NH4+, K+, tracer elements of iron and steel, cement, and coal-burning were obvious when eastern and northern parts of Taiwan were under the influence of transboundary pollution transport in winter and spring. The richness of metal elements Ba, Pb, and Ga at the Chiayi site indicated the influences of coal-burning, iron and steel, biomass burning, and local folk activities. The estimate on secondary organic carbon indicates that a stringent control of volatile organic compounds in the area south to central Taiwan will help reduce secondary PM2.5 concentration. By comparing PM2.5 concentration during the COVID-19 pandemic period with that of the extension from the past three years, more PM2.5 reduction was found from the reduced industrial activities in the central and Yulin-Chiayi areas of Taiwan. From source apportionment approach using positive matrix factorization (PMF), “Sulfate”, “Nitrate”, and “Vehicle emissions” were the three most significant factors in the nine resolved source factors across all sites, and the influence of vehicle emissions increased gradually at the sites north to the Douliu site. For estimating the atmospheric light extinction coefficient (bext), the results computed from the revised Interagency Monitoring of Protected Visual Environments (IMPROVE) equation revealed that sulfate and organic matter contributed to bext stably and nitrate contributed the most to the area south to the Douli site in winter and spring. Similarly, SO42-, NO3-, and OC were significant factors influencing ambient visibility from the statistical regression analysis. For the most updated sampling and measuring techniques for PM2.5 chemical components, this study reviewed 32 papers from studies in various countries in recent years. In summary, this study consistently provides PM2.5 mass and chemical components (including phthalate esters) data from the six urban sites and near traffic-source site to derive temporal and spatial characteristics of PM2.5 in Taiwan. Additional derivations from the collected data include the characteristics of PM2.5 chemical components at specific time and sites, fractions of source factor contribution, and factors influencing atmospheric visibility. The results of this study will serve as the data cornerstone of health risk assessment and control measure delivery.
英文關鍵字	PM2.5 chemical component monitoring, Temporal and spatial distributions of PM2.5 chemical characteristics, PM2.5 chemical characteristics of traffic sources, PM2.5 source apportionment, Atmospheric visibility-influencing factors.

摘要

This study collected PM2.5 (aerodynamic diameters equal to or smaller than 2.5 μm) regularly every six days per shift at the Banqiao, Zhongming, Douliu, Chiayi, Xiaogang, and Hualien air quality monitoring sites of Environmental Protection Administration (EPA) in Taiwan in 2020. Besides, PM2.5 was collected near traffic sources at the Taiwan Boulevard site for finding vehicle emissions characteristics. PM2.5 mass, water-soluble inorganic ions, carbonaceous contents, and metal elements were analyzed for the regular and near-source samples. Meanwhile, phthalate esters were also analyzed for the regular samples. This study investigated and derived the characteristics of temporal and spatial distributions of PM2.5 mass and chemical components (including the data of December 2019), high concentration events, specific scenarios, the apportioned source factors, and atmospheric visibility-influencing factors by utilizing the analyzed PM2.5 chemical components, air quality monitoring data, environmental factors, and the corresponding model simulation products. The PM2.5 mass concentration of this study is consistent with that of the EPA's regular manual collection. Seasonal PM2.5 mass levels increased from east, north, to the south of Taiwan during winter, spring, and autumn. Organic carbon (OC) was the most abundant component at the Hualien and Banqiao sites and NO3- for the other sites in winter. In contrast, OC was the most abundant component at most sites in spring, summer, and autumn. SO42- lost the role as the leading component in 2020, which reflected an effective control on the combustion sources of sulfur-containing fossil fuel. The mutual high-abundance metal elements (Na and K) across sites increased in concentrations from east, north, to the south of Taiwan. The distinct metal elements exhibited source characteristics among sites. The volatilization corrections compensated 12~21% and 17~38% of NH4+ and NO3- mass losses, respectively, in 2020. The error distribution of OC concentration will spread from 89% overestimation to 23% underestimation. Similarly, positive interferences also showed no spatial distinction. Ambient levels of phthalate esters were very low, with relatively high values for DEHP, DBP, and DnOP at each site. For near-source traffic emissions at the Taiwan Boulevard site, PM2.5 mass, NO3-, OC, and EC concentrations were higher during on- than off-duty rush hours. OC representing gasoline vehicle emissions was the most abundant component during on- and off-duty rush hours. The high PM2.5 concentration days (≥ 30 μg m-3), caused by local pollution and predominantly with “residual layer” in the preceding night, were mainly distributed south to central Taiwan in winter 2020. By contrast, the number of high PM2.5 concentration days declined considerably in spring. In August 2020, the PM2.5 concentration at the Hualien site increased more than twice with the abundance of SO42-, NH4+, and crustal elements and a 10-fold increase of rare-earth element Yttrium was the most stunning discovery under the influence of the long-range transport of the erupted Nishinoshima of Japan. By classifying PM2.5 mass concentrations of sampling days of the recent four years into high, medium, and low concentration groups, PM2.5 reduction benefits are evident for the medium concentration group (15~35 μg m-3) when NO3- precursor emission sources are in control. The results from Community Multiscale Air Quality Model (CMAQ) discovered that daytime photochemical reaction and nighttime N2O5 heterogeneous hydrolysis were the mechanism of NO3- enhancement in high PM2.5 concentration events. The stable declination of SO42- concentration during higher PM2.5 concentration period (from December to April) of the recent four years implied a reduction of fossil-fuel combustion activities from stationary sources. In contrast, reversibly increased EC concentration in 2020 and either reversibly increased or in the flat fashion of NO3- and OC concentrations in 2019 and 2020 imply that mobile sources will be the next target for improving the air quality of high PM2.5 concentration period. The samples collected after traditional festivals were rich in the tracer elements of firecracker and incense. Concentration enhancements of SO42-, NO3-, NH4+, K+, tracer elements of iron and steel, cement, and coal-burning were obvious when eastern and northern parts of Taiwan were under the influence of transboundary pollution transport in winter and spring. The richness of metal elements Ba, Pb, and Ga at the Chiayi site indicated the influences of coal-burning, iron and steel, biomass burning, and local folk activities. The estimate on secondary organic carbon indicates that a stringent control of volatile organic compounds in the area south to central Taiwan will help reduce secondary PM2.5 concentration. By comparing PM2.5 concentration during the COVID-19 pandemic period with that of the extension from the past three years, more PM2.5 reduction was found from the reduced industrial activities in the central and Yulin-Chiayi areas of Taiwan. From source apportionment approach using positive matrix factorization (PMF), “Sulfate”, “Nitrate”, and “Vehicle emissions” were the three most significant factors in the nine resolved source factors across all sites, and the influence of vehicle emissions increased gradually at the sites north to the Douliu site. For estimating the atmospheric light extinction coefficient (bext), the results computed from the revised Interagency Monitoring of Protected Visual Environments (IMPROVE) equation revealed that sulfate and organic matter contributed to bext stably and nitrate contributed the most to the area south to the Douli site in winter and spring. Similarly, SO42-, NO3-, and OC were significant factors influencing ambient visibility from the statistical regression analysis. For the most updated sampling and measuring techniques for PM2.5 chemical components, this study reviewed 32 papers from studies in various countries in recent years. In summary, this study consistently provides PM2.5 mass and chemical components (including phthalate esters) data from the six urban sites and near traffic-source site to derive temporal and spatial characteristics of PM2.5 in Taiwan. Additional derivations from the collected data include the characteristics of PM2.5 chemical components at specific time and sites, fractions of source factor contribution, and factors influencing atmospheric visibility. The results of this study will serve as the data cornerstone of health risk assessment and control measure delivery.

英文關鍵字

PM2.5 chemical component monitoring, Temporal and spatial distributions of PM2.5 chemical characteristics, PM2.5 chemical characteristics of traffic sources, PM2.5 source apportionment, Atmospheric visibility-influencing factors.