2017年台灣麥寮、大城地區細懸浮微粒(PM2.5)金屬元素成分特性與季節變化

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題名:	2017年台灣麥寮、大城地區細懸浮微粒(PM2.5)金屬元素成分特性與季節變化
作者:	宋昆霖;LIN, SONG KUN
貢獻者:	環境工程研究所
關鍵詞:	細懸浮微粒(PM2.5);PM2.5質量濃度;PM2.5金屬元素成分;金屬元素比值;CBPF
日期:	2022-09-12
上傳時間:	2022-10-04 12:25:13 (UTC+8)
出版者:	國立中央大學
摘要:	本文配合2017年「細懸浮微粒(PM2.5)化學成分監測及分析計畫」在雲林縣麥寮(冬季)、彰化縣大城(春、夏、秋季)環保署測站以手動和自動監測解析PM2.5金屬元素濃度的特性及季節變化，推論污染來源。結果顯示，PM2.5濃度以秋季>冬季>春季>夏季，總金屬元素濃度不論是手動或自動儀器，四季主要金屬元素都是Al、Fe、Na、Mg、K、Ca、Pb，這些元素顯示出雲林麥寮大城地區受到當地交通排放、海水、鄰近六輕工業區內的煉鋼廠(台塑重工內)以及燃煤電廠影響。金屬元素Cu、Zn、Mo、Cd、Pb、Sb、Se、Sn、Tl的富集度高達百倍，污染源可能為:交通排放、燃煤燃燒、金屬加工、鋅冶金、燃油燃燒，另外，四季地殼元素Igeo指數的Cu、Zn、Sn、Pb、V、Zn、Pb、V和Ni元素都大於1，表示有中等程度污染，可能污染來源為: 交通排放、燃煤燃燒、金紙燃燒、金屬加工。 PMF (Positive Matrix Factorization, PMF)受體模式推估顯示，麥寮、大城測站主要污染源以「燃油燃燒」、「船舶排放」、「海鹽」、「化石燃料燃燒」、「工業區混合來源」、「石化工業」為主。結合雙變量條件機率函數推論污染來向，大城站春季以「燃油燃燒、船舶排放」占比最高；燃油燃燒可能來自西濱快速道路，船舶排放可能從北方較遠海面傳輸過來。「化石燃料燃燒」占比最高為春季，可能受西濱快速道路影響，「石化工業區」占比最高為夏季，可能從六輕工業區傳輸過來。最後，本文比較四種來源推論方法，發現PMF是唯一可以量化來源貢獻的方法。 ;This study collaborated with the “2017 PM2.5 chemical composition monitoring and analysis study” to resolve characteristics, seasonal variations, and pollution sources of PM2.5 metal elements from manual and automatic monitoring at the Mailiao, Yunlin County (Winter) and Dacheng, Changhua County (Spring, Summer, Autumn) in 2017. The results showed that PM2.5 mass concentrations varied from high to low in the order of Autumn> Winter> Spring> Summer. The predominant metal elements in mass concentration are Al, Fe, Na, Mg, K, Ca, and Pb. Related sources of these metal elements can be derived from local traffic emissions, sea salt, steel manufacturing plant within Formosa Plastics Corporation, and coal-fired power plants of the neighboring Sixth Naphtha Cracker Complex (SNCC). The enrichment factors of metal elements could be as high as 100 folds for Cu, Zn, Mo, Cd, Pb, Sb, Se, Sn, and Tl. The potential sources were traffic emissions, coal combustion, metal processing, zinc metallurgy, and oil combustion. In addition, the crustal element Igeo indices for Cu, Zn, Sn, Pb, V, Zn, Pb, V, and Ni were greater than one indicating moderate polluting at least. Potential sources were traffic emissions, coal combustion, joss paper burning, and metal processing. PMF (Positive Matrix Factorization, PMF) source apportionment showed that “Oil combustion”, “Ship emissions”, “Sea-salt”, “Fossil fuel combustion”, “Industrial mixed sources”, and “Petrochemical industry” were predominant sources at the Mailiao and Dacheng areas. Combining with the conditional bivariate probability function for source orientation, this study showed that “Oil combustion” and “Ship emissions” had the highest probability in spring. The “Oil combustion” might be from the West Coast Expressway, and “Ship emissions” could be transported from farther northern sea waters. “Fossil fuel combustion” might be influenced by the West Coast Expressway with the highest proportion in spring. In contrast, the “petrochemical industry” was transported from the SNCC and had the highest proportion in summer. Finally, this study compared four source inference methods to find that PMF was the only method to apportion source contributions quantitatively.
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