突破曲線聯用質譜法鑑別水中金屬汙染物原生物種分析

本研究利用突破曲線(Breakthrough Curve, BTC)技術結合感應耦合電漿質譜法(Inductively Coupled Plasma-Mass Spectrometry, ICP-MS)，建立一套可保留物種原始型態且無需前處理的金屬污染物型態鑑定方法，針對水中金屬污染物樣品進行ppb等級微量金屬的定量分析。我們以Na (I)、Mg (II)、Fe (III)為代表陽離子，確認理論架構，探討其在不同環境中的突破行為，並以突破時間(tBT)作為判別物種型態的關鍵指標。突破時間(tBT)受物種電荷態、選擇性係數與競爭離子濃度如[H⁺]控制，其在吸附平衡常數(K)與平衡狀態下物種濃度(C)之乘積KC << 1的條件下，能反映金屬的型態。相較於離子層析(IC)與紫外可見光譜(UV-Vis)等傳統技術常因洗脫或取樣條件改變物種型態，BTC具備保留金屬原生型態的優勢，特別適用於分析含多離子背景或高酸鹼性的極端環境下複雜樣品。實驗結果證明，不同HNO3.環境競爭下Na (I)、Mg (II)、Fe (III)的tBT隨[H⁺]提升而減少且符合理論模型所預期之結果。污染源物種辨識與後端選擇性去除有害物種於特定環境科學至關重要。以砷為例，其不同氧化還原型態變化常見於自然與工業環境之中。As (III)與As (V)於水環境中的毒性隨物種型態不同而異。於弱酸條件下，As (III)呈現極短突破時間，推估主要以中性物種形式(H₃AsO₃)存在，其吸附行為與As (V)著明顯不同；由突破曲線可展現出物種相關tBT，使得在不改變其自然狀態下成功分辨兩者。As (V)因其負電特性顯著與吸附材產生作用並使突破時間增加。在10 ppm鹽酸(HCl)中，tBT約為120分鐘，當HCl濃度提升兩倍至20 ppm時(競爭離子濃度亦提升兩倍)，tBT縮短兩倍至60分鐘。根據實驗數據可推估其物種應為H2AsO4-，此猜測亦能於Pourbaix diagram獲得支持。透過突破曲線聯用質譜法(BTC-ICP-MS)，我們不僅能實現高選擇性與即時定量的金屬物種判別，更無需複雜前處理的情況下，深入掌握污染物於極端環境中的遷移與形態轉化行為，其在良好的真空質譜環境中具有足夠質量解析度有助於微量元素分析；此方法具備了低基質干擾、操作簡便與自然型態分析的特性，對於極端環境條件下的廢水處理優化、環境污染源監測，均具有重要的應用潛力與實務價值。

This study employs breakthrough curve (BTC) in conjunction with inductively coupled plasma-mass spectrometry (ICP-MS) to create a method for identifying metal pollutants while retaining their original states, eliminating the need for pre-treatment. This method quantitatively analyzes trace levels of metals in contaminated water samples down to parts per billion (ppb). The study uses cations, i.e., sodium (Na (I)), magnesium (Mg (II)), and iron (Fe (III)), to verify the theoretical framework by examining their breakthrough behavior in various acidic and alkaline environments. Breakthrough time (tBT) relates to adsorption behavior and is a key indicator of speciation. The variation in tBT is influenced by factors such as the species' charge states, selectivity coefficients, and the concentration of competing ions; this occurs under conditions where the product of the adsorption equilibrium constant (K) and the equilibrium concentration of a species (C) satisfies the condition KC << 1. Compared to traditional techniques such as ion chromatography (IC) and ultraviolet-visible spectroscopy (UV-Vis), which often alter the species during analysis or require high-purity ppm levels of samples, BTC preserves the native states of metals at trace levels. This makes it particularly suitable for analyzing complex samples with a multi-ion background or in highly acidic or alkaline conditions. Experimental results indicate that under varying concentrations of nitric acid (HNO3), the tBT of Na (I), Mg (II), and Fe (III) decreases significantly with increasing levels of [H⁺], in line with expected theoretical outcomes. Identifying species and selectively removing harmful ones is essential in various environmental science studies. For example, arsenic exhibits different redox state variations in natural and industrial environments. The contamination species As (III) and As (V) differ across environments, leading to variations in toxicity. Under weakly acidic conditions, As (III) displays an extremely short breakthrough time, suggesting it primarily exists in the form of a neutral species (H₃AsO₃), with its adsorption behavior significantly differing from that of As (V); the breakthrough curve reveals species-related tBT, allowing successful differentiation between the two without altering their natural state. As (V), due to its negative charge characteristics, interacts significantly with the adsorbent material and increases the breakthrough time. In 10 ppm hydrochloric acid (HCl), the tBT is approximately 120 minutes. When the HCl concentration is doubled to 20 ppm (with the concentration of competing ions also doubled), the tBT is reduced to 60 minutes. Based on experimental data, it can be inferred that the species was H2AsO4-, aligning with the theoretical prediction from the Pourbaix diagram. By integrating breakthrough curve technology with mass spectrometry (BTC-ICP-MS), we achieve high selectivity and real-time quantification for distinguishing metal species, while gaining insights into the migration and transformation behaviors of pollutants in extreme environments without complex pre-treatment. This method is characterized by low matrix interference, ease of operation, and in situ analysis, presenting significant potential applications and practical value for optimizing wastewater treatment and monitoring sources of environmental pollution under extreme conditions.