110

19,250 千元

科技發展-環境科學及技術之研究

2021/01/01

2021/12/31

李崇德

監資處

黃健瑋

國立中央大學

環境監測及檢測

PM2.5化學成分，時間與空間分布，近交通源PM2.5，PM2.5污染源，大氣能見度

PM2.5 chemical composition, Temporal and spatial distributions, Near- traffic-source PM2.5, PM2.5 sources, Atmospheric visibility

周崇光；張士昱；莊銘棟；許文昌

黃秋華

03-4226551#

cilia0110@gmail.com

本計畫於環保署板橋、忠明、斗六、嘉義、小港及花蓮六個一般空品測站每六天同步進行一次PM2.5採樣。此外，在臺北市大同站及臺中市臺灣大道站進行近交通污染源採樣。採樣樣本都分析PM2.5質量濃度、水溶性無機離子、碳成分、金屬元素，以推估污染成因和來源，並研究影響大氣能見度因子，提供環保機關擬訂管制策略。 例行性採樣PM2.5質量濃度和環保署其他團隊的常規採樣結果具有一致性，且無明顯偏差，化學成分解析比例占修正後PM2.5質量濃度83~92%足以解釋質量濃度變化特徵。季節變化顯示冬季PM2.5高濃度出現較頻繁，春季逐漸減少，直到秋季才開始增加。高PM2.5和NO3-濃度仍分布在中部以南測站，高濃度的NO3-指出NOx前驅污染源管制的重要性。分析金屬元素，在六個測站普遍檢測到鍋爐燃燒排放或生質燃燒微粒指標成分，以南部測站濃度較高。臺灣大道站及大同站的近交通源採樣比鄰近一般測站有較高的OC與EC濃度，量測的金屬元素大多與揚塵及車輛零件耗損有關。高健康風險金屬元素(如：Pb、As、Cd等)沒有突出高濃度。 從2017到2021年持續檢測PM2.5質量及化學成分濃度，以雙層濾紙修正採樣過程水溶性無機離子和碳成分的揮發和吸附，在揮發和吸附抵銷後，平均可避免低估5~8.5%PM2.5質量濃度。近五年PM2.5化學成分變化趨勢已可用來評估污染源管制有效性：SO42-濃度下降快速，表示SOx管制成效良好；OC濃度降低趨緩與污染來源多元有關，NO3-和其他特徵成分濃度增加顯示受工業活動影響大，EC濃度持續降低，表示柴油車管制具有成效。分析高PM2.5濃度化學成分占比變化顯示：冬季與春季東部及北部應著重於改善移動污染源與含硫燃料鍋爐排放，中部以南地區，可持續加強NOx及VOCs排放源管制；夏季至秋初各地管制標的以含硫燃料鍋爐排放源改善為主。推估近五年各站一、二次OC占比變化，除斗六站外，各地的OC多為一次OC，若能有效管制移動污染源將有助於降低OC以及PM2.5濃度。從測站空間相似度推衍污染源管制空間分布：針對SOx污染源的管制，各地可使用相近管制策略；針對NOx和VOCs污染源，則須因地制宜而有不同管制策略與力道。近五年金屬元素時間與空間分布顯示：空污費於2018年所增設課徵的重金屬成分(As、Cd、Cr、Pb)，近四年與PM2.5質量濃度都呈現下降趨勢，但是兩者下降趨勢稍有不同，小港站受重工業影響， Cd、Cr濃度都是各站中最高。以PMF受體模式分析近五年PM2.5化學成分來源，解析出十項污染源因子，各站貢獻濃度前三高污染源因子大多為「硫酸鹽」、「硝酸鹽」及「車輛排放」，高污染日的其他污染源因子可顯示出地方污染源的特性。以化學成分推估各站影響大氣能見度化學成分，在四季中硫酸鹽及有機物對各測站大氣消光係數貢獻穩定，但硝酸鹽在冬季與春季中部以南各測站貢獻最大。 以CMAQ模式模擬高濃度案例，顯示若能評估NOx與VOCs的有效減量比例及相對應的策略，將可減少O3生成，降低NO3-濃度。2021年冬季與春季的高PM2.5濃度採樣日，大多受在地污染排放影響，長時間的低風速，促使污染濃度累積增加。分析各地污染特徵，發現鍋爐燃燒排放在各地都是重要影響因子。在Covid-19的影響下，2020年各測站SO42-濃度都出現超出預期的降低；但在2021年各地都出現SO42-濃度反彈，不過SO42-濃度仍在未發生疫情的延伸下降趨勢下。當2021年國內爆發疫情時，各地移動污染源貢獻量因人流管制明顯降低，但固定污染源活動降低有限，導致PM2.5濃度變化不大甚至反增。交叉分析富貴角測站空品監測資料和本計畫花蓮站化學成分，發現疫情發生後境外污染影響程度大幅下降，鍋爐指標成分顯著降低。 綜合而言，為降低PM2.5污染，建議持續管制固定污染源，但加強管制移動污染源。現階段若能評估NOx與VOCs的有效減量比例及相關減量策略，將可減少O3生成、降低NO3-濃度和PM2.5高濃度事件的發生，有助於改善中南部地區污染季節能見度。

PM2.5化學成分，時間與空間分布，近交通源PM2.5，PM2.5污染源，大氣能見度

2021期末報告.pdf

31MB

2022/3/1 上午 12:00:00

This project collected PM2.5 simultaneously at the Banqiao, Zhongming, Douliu, Chiayi, Xiaogang, and Hualien sites of the Environmental Protection Administration (EPA) once every six days. Moreover, near-traffic-source samplings were conducted at the Datung site in Taipei city and the Taiwan Boulevard site in Taichung city. The collected samples were analyzed for PM2.5 mass concentrations, water-soluble inorganic ions, carbonaceous contents, and metal elements to derive pollution causes and source contributions. Meanwhile, factors influencing atmospheric visibility were also studied to provide environmental protection institutions for setting up their control measures. The regular sampling results of PM2.5 mass concentrations were consistent with the EPA’s routine sampling by other teams without apparent bias. The reconstructed PM2.5 chemical composition fractions ranged from 84 to 93%, which were enough to account for varying characteristics of mass concentrations. Seasonal variations showed that high PM2.5 mass concentrations frequently occurred in winter, gradually decreased in spring, and started increasing in spring. High PM2.5 and NO3- concentrations were still distributed over the sites southward central Taiwan. High NO3- concentrations indicated the significance of controlling their precursor sources. The analyzed metal elements showed markers of boiler combustion or biomass burning particles occurring pervasively at the six sites but with higher concentrations in the southern sites. The OC and EC concentrations from the near-traffic-source samplings at the Taiwan Boulevard and the Datung sites were higher than the nearby regular sites. The measured metal elements were mainly associated with the suspended dust and the abrasion of vehicle components. The metal element concentrations of high health risk, such as Pb, As, and Cd, were not extraordinarily high. During sampling, the double-filter corrections for the volatilization and absorption of water-soluble inorganic ions and carbonaceous contents were conducted persistently from 2017 to 2021. PM2.5 mass concentrations were prevented from underestimation by 5-8.5% on average after offsetting volatilization and absorption. The variation trend of PM2.5 chemical composition has been used for assessing source control efficacy over the last five years. The rapid decrease of SO42- concentration indicated an effective SOx control, while a slowly decreasing trend of OC concentration might be related to diversified source contributions. The increase of NO3- and other characteristic species implied a significant influence from industrial activities. In contrast, the persistent decrease of EC concentration represented an effective control for Diesel vehicles. The analysis of chemical composition fraction for high PM2.5 concentration showed that eastern and northern Taiwan should improve emissions from mobile sources and sulfur-fuel boilers in winter and spring. As for the areas from central to southern Taiwan, continued control for NOx and VOCs emission sources is necessary. Sulfur-fuel boilers are the main control target in summer and early autumn. Except the Douliu site, the OC and PM2.5 concentrations can be reduced if the mobile sources are effectively controlled. The previous derivation was based on OC were mostly primary from OC apportionment in the recent five years. From the spatial similarity analysis of the various sites, the control of SOx can be similar in all areas, while the control for NOx and VOCs emission sources needs to have diversified control measures and strength at specific locations. For those heavy metals (As, Cd, Cr, and Pb) levied for air pollution fees from 2018, their concentrations had a downward trend but were slightly different from PM2.5. It is noted that the Cd and Cr concentrations at the Xiaogang site are the highest among all sites. In the recent five years, ten source factors were apportioned from PMF receptor modeling on PM2.5 chemical composition. The highest three source factors are “sulfates,” “nitrates,” and “vehicle emissions.” In addition, the other source factors from high pollution days can indicate local source distinction. The estimated atmospheric visibility from chemical composition revealed that sulfates and organic matter contributed stably in contrast to the predominant contribution of nitrates from central to southern Taiwan in winter and spring. The CMAQ model simulation on high concentration events showed that an assessment of effective reduction ratio for NOx and VOCs and the associated source control measures would reduce O3 formation and NO3- concentration. The high PM2.5 concentration days were mainly influenced by local pollution with a long duration of low wind speed to result in pollution accumulation. Boiler combustion emissions were a significant influencing factor in all areas from analyzing area pollution characteristics. Under the influence of Covid-19, SO42- concentrations were exceedingly low in 2020, rebounding in 2021, but were still below the extension trend lines at all sites. The contributions from mobile emission sources were apparently reduced but were less in stationary source emissions resulting in a small variation or even higher PM2.5 concentration. From the cross-analysis of monitoring data at the Fugue air-quality monitoring site and the chemical composition at the Hualien site, this project found a significant reduction in transboundary pollution transport with a noticeable decrease in boiler marker species. In conclusion, suggestions are made for consistent stationary source control with a tightening control for mobile sources to reduce PM2.5 pollution. At the present stage, an assessment on effective reduction ratio for NOx and VOCs and the associated source control measures is necessary to reduce O3 formation, NO3- concentration, and PM2.5 high-concentration event. The accomplishment will eventually improve atmospheric visibility from central to southern Taiwan in the pollution seasons.

PM2.5 chemical composition, Temporal and spatial distributions, Near- traffic-source PM2.5, PM2.5 sources, Atmospheric visibility