降雨沖刷空氣中微量金屬及其對新店溪水源區金屬濃度影響之推估

Abstract

隨著都市化與工業發展的加速，空氣中微量金屬污染已成為日益嚴重的環境問題。除空氣污染之外，降雨沖刷將空氣中金屬污染物帶至河川的影響程度仍有待進一步瞭解。 本研究旨在探討降雨對空氣中微量金屬的沖刷效應，並推估其對新店溪水源區上游河川中金屬濃度的潛在影響。研究選取2025年一月與五月兩場具代表性的降雨事件，分別代表鋒面型與對流型降雨特徵，並依據降雨強度進行不同頻率的雨水採樣，一月為每30分鐘，五月為每15分鐘。共分析雨水中14種金屬 (Ti、V、Cr、Mn、Fe、Ni、Cu、Zn、As、Se、Cd、Ba、Hg、Pb)，並利用感應耦合電漿質譜儀 (ICP-MS) 進行定量分析。再透過指數衰減模型估算金屬濃度隨時間下降的速率 (b值) ，並以K-means群聚分析將各金屬依其b值進行分類。 結果顯示，降雨強度為影響金屬沖刷效率的關鍵因素。五月的對流性降雨強度高、時間短，多數金屬呈現較高的b值，如Ti = 12.3、Ba = 7.80、Mn = 7.48，顯示沖刷效率較佳；而一月的長時間鋒面降雨則相對較低。此外，Hg與Se在兩場事件中均展現穩定且偏低的b值，顯示其在大氣中具高度穩定性。 透過質量守恆推估，雖然一月雨水中的金屬濃度較高，但由於較大之逕流體積與河川流量，其稀釋效應明顯，導致推估之河川金屬濃度相對較低。反之，五月事件雖然雨水濃度較低，但因為徑流體積及河川水體積較小，導致其相對稀釋能力較低，對河川金屬濃度的提升影響更為顯著。群聚分析將14種金屬依其沖刷行為模式分為三類：第一類為Ti、Mn、Ba；第二類為Zn、Pb、Cu、Ni、Cr、Cd、Fe；第三類為As、Se、Hg、V，可反應其在大氣中的物理化學特性與潛在污染來源。研究結果有助於深入理解濕沉降過程中金屬動態行為，並可作為污染源解析與都市河川水質管理之參考依據。

With rapid urbanization and industrial development, airborne metal pollution has become an escalating environmental concern, posing threats to both ecosystems and human health. Although rainfall acts as a natural mechanism for removing atmospheric pollutants, the atmospheric washout of airborne metals by rainfall remains insufficiently understood. This study investigated the washout behaviors of 14 metals, including Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Hg, and Pb, during two rainfall events in January and May 2025, representing different precipitation characteristics. Rainwater samples were collected and analyzed using inductively coupled plasma mass spectrometry (ICP-MS). The exponential decline model was applied to quantify concentration reduction over time (b values), and K-means clustering was conducted to classify the metals based on their temporal profiles. Results indicated that rainfall intensity significantly influenced metal washout efficiency. The high-intensity, short-duration convective rainfall in May resulted in higher b values for most metals, for example, Ti = 12.3, Ba = 7.80, and Mn = 7.48, compared to the low-intensity, long-duration frontal rainfall in January. Hg and Se consistently exhibited low b values in both events, suggesting high atmospheric persistence. Mass balance estimations further revealed that, despite higher rainwater metal concentrations in January, the larger rainfall runoff volume and river discharge diluted the inputs more effectively, resulting in lower estimated river concentrations. Conversely, lower rainwater concentrations in May, combined with lower rainfall runoff and river volume, resulted in elevated riverine metal concentrations due to limited dilution. Cluster analysis grouped the metals into three categories based on their washout behaviors, offering insight into their atmospheric characteristics and potential emission sources. These findings enhance the understanding of metal dynamics during wet deposition and offer practical implications for source identification and water quality management in urban watersheds.