A systematic review for non-targeted analysis of per- and polyfluoroalkyl substances (PFAS).

This review follows the PRISMA guidelines to provide a systematic review of 115 peer reviewed articles that used non-targeted analysis (NTA) methods to detect per- and polyfluoroalkylated substances (PFAS). This literature highlights the significant positive impact of NTA in understanding PFAS in the environment. Within the literature a geographical bias exists, with most NTA studies (∼60 %) conducted in the United States and China.

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model.

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study therefore demonstrates a novel multi-criteria decision making (MCDM) framework utilizing machine learning (ML) algorithms coupled with toxicological prioritization index tool (i.e.

Assessment of PAH exposure and health risks among South Korean firefighters based on urinary PAH metabolites.

Polycyclic aromatic hydrocarbons (PAHs) comprise a group of compounds resulting from the incomplete combustion of organic matter. Firefighters engaged in fire suppression are highly exposed to PAHs. This study centered on evaluating the exposure levels and health risks of PAHs in South Korean firefighters involved in firefighting activities.

Identification of organic chemical indicators for tracking pollution sources in groundwater by machine learning from GC-HRMS-based suspect and non-target screening data.

In this study, the strong analytical power of gas chromatography coupled to a high resolution mass spectrometry (GC-HRMS) in suspect and non-target screening (SNTS) of organic micropollutants was combined with machine learning tools for proposing a novel and robust systematic environmental forensics workflow, focusing on groundwater contamination. Groundwater samples were collected from four different regions with diverse contamination histories (namely oil [OC], agricultural [AGR], industrial [IND], and landfill [LF]), and a total of 252 organic micropollutants were identified, including pharmaceuticals, personal care products, pesticides, polycyclic aromatic hydrocarbons, plasticizers, phenols, organophosphate flame retardants, transformation products, and others, with detection frequencies ranging from 3 % to 100 %. Amongst the SNTS identified compounds, a total of 51 chemical indicators (i.