Human activities are responsible for the release of innumerous substances into the aquatic environment. Some of these substances can be used as pollution tracers to identify contamination sources and to prioritize monitoring and remediation actions. Thus, their identification and quantification are of high priority. However, due to their presence in complex matrices and at significantly low concentrations, a pre-treatment/concentration step is always required. As an alternative to the currently used pre-treatment methods, mainly based on solid-phase extractions, aqueous biphasic systems (ABS) composed of ionic liquids (ILs) and K₃C₆H₅O₇ are here proposed for the simultaneous extraction and concentration of mixtures of two important pollution tracers, caffeine (CAF) and carbamazepine (CBZ). An initial screening of the IL chemical structure was carried out, with extraction efficiencies of both tracers to the IL-rich phase ranging between 95 and 100%, obtained in a single-step. These systems were then optimized in order to simultaneously concentrate CAF and CBZ from water samples followed by HPLC-UV analysis, for which no interferences of the ABS phase-forming components and other interferents present in a wastewater effluent sample have been found. Based on the saturation solubility data of both pollution tracers in the IL-rich phase, the maximum estimated concentration factors of CAF and CBZ are 28595- and 8259-fold. IL-based ABS can be thus envisioned as effective pre-treatment techniques of environmentally-related aqueous samples for a more accurate monitoring of mixtures of pollution tracers.

人类活动导致无数物质释放到水生环境中。其中一些物质可用作污染示踪剂，以识别污染源并确定监测和补救措施的优先级。因此，它们的识别和量化具有高度优先性。然而，由于它们存在于复杂的基质中并且浓度非常低，因此总是需要预处理/浓缩步骤。作为目前使用的预处理方法的替代方法，主要基于固相萃取，由离子液体 (ILs) 和 K ₃ C ₆ H ₅ O _{7组成的水性双相系统 (ABS)}此处提出用于同时提取和浓缩两种重要污染示踪剂咖啡因 (CAF) 和卡马西平 (CBZ) 的混合物。对 IL 化学结构进行了初步筛选，两种示踪剂对富含 IL 相的提取效率在 95% 到 100% 之间，一步获得。然后对这些系统进行优化，以便同时从水样中浓缩 CAF 和 CBZ，然后进行 HPLC-UV 分析，没有发现废水样品中存在 ABS 相形成组分和其他干扰物的干扰。根据富 IL 相中两种污染示踪剂的饱和溶解度数据，CAF 和 CBZ 的最大估计浓度因子为 28595 倍和 8259 倍。