Investigation on transformation products (TPs) of environmental contaminants is important for chemical exposure risk assessments. However, the task of identifying potential TPs in complex environmental matrices is very challenging. Advanced data-mining techniques have greatly accelerated the process of TP recognition and identification, which should be included as part of an integrated analytical workflow along with robust sample preparation and data acquisition protocols. In this review, the methods for enrichment of TPs from various sample matrix and the data acquisition modes by high-resolution mass spectrometry (HRMS) are summarized. Further, advanced data-mining techniques including suspect screening by in-silico prediction, case-control strategy, stable isotope labeling, mass defect filtering, and product ion filtering are critically reviewed. The gaps in the current knowledge and future trends for the identification of TPs are also discussed.

环境污染物转化产物 (TP) 的调查对于化学品暴露风险评估非常重要。然而，在复杂环境矩阵中识别潜在 TP 的任务非常具有挑战性。先进的数据挖掘技术极大地加速了 TP 识别和鉴定的过程，应将其作为集成分析工作流程的一部分以及强大的样品制备和数据采集协议。在这篇综述中，总结了从各种样品基质中富集 TPs 的方法和高分辨率质谱 (HRMS) 的数据采集模式。此外，先进的数据挖掘技术，包括通过计算机进行的嫌疑人筛查对预测、病例控制策略、稳定同位素标记、质量缺陷过滤和产物离子过滤进行了严格审查。还讨论了识别 TP 的当前知识和未来趋势的差距。