Study of the presence and environmental risk of organic contaminants policed by the European Union and other organic compounds in the water resources of a region overlapping protected areas: The Guadiaro River basin (southern Spain)

Prioritization of organic contaminants in China's groundwater based on national-scale monitoring data and their persistence, bioaccumulation, and toxicity

There has been increasing concern regarding the adverse environmental and health effects of organic pollutants. A list of priority control organic pollutants (PCOPs) can provide regulatory frameworks for the use and monitoring of organic compounds in the environment. In this study, 20,010 groundwater samples were collected from 15 "first level" groundwater resource zones in China. Fifty (50) organic compounds were analyzed based on their prevalence, occurrence, and physicochemical properties (persistence, bioaccumulation, and toxicity). Results showed that 16 PCOPs, including 12 pesticides, 3 aromatic hydrocarbons (AHs), and 1 phthalate ester, were recognized. Pesticides and AHs accounted for 75 % and 18.75 % of the high-priority pollutants, respectively. There were significant differences in PCOPs between confined and phreatic groundwater. Higher concentrations of pesticides were mainly detected in phreatic groundwater. PCOPs detected in samples from the 15 groundwater resource zones were mainly pesticides and AHs. The groundwater data indicate that the organic compounds detected in the Yellow River Basin (YRB), Yangtze River Basin (YZB), Liaohe River Basin (LRB), and Songhua River Basin (SRB) are mainly categorized as Q1 (high priority) and Q2 (medium priority) pollutants based on the contaminants ranking system in China. The findings from this study offer a snapshot of the wide distribution of PCOPs in the surveyed regions, and are expected to establishing treatment and prevention measures at both the regional and national levels in China.

Integrating molecular descriptors for enhanced prediction: Shedding light on the potential of pH to model hydrated electron reaction rates for organic compounds

Hydrated electron reaction rate constant (ke-aq) is an important parameter to determine reductive degradation efficiency and to mitigate the ecological risk of organic compounds (OCs). However, OC species morphology and the concentration of hydrated electrons (e-aq) in water vary with pH, complicating OC fate assessment. This study introduced the environmental variable of pH, to develop models for ke-aq for 701 data points using 3 descriptor types: (i) molecular descriptors (MD), (ii) quantum chemical descriptors (QCD), and (iii) the combination of both (MD + QCD). Models were screened using 2 descriptor screening methods (MLR and RF) and 14 machine learning (ML) algorithms. The introduction of QCDs that characterized the electronic structure of OCs greatly improved the performance of models while ensuring the need for fewer descriptors. The optimal model MLR-XGBoost(MD + QCD), which included pH, achieved the most satisfactory prediction: R2tra = 0.988, Q2boot = 0.861, R2test = 0.875 and Q2test = 0.873. The mechanistic interpretation using the SHAP method further revealed that QCDs, polarizability, volume, and pH had a great influence on the reductive degradation of OCs by e-aq. Overall, the electrochemical parameters (QCDs, pH) related to the solvent and solute are of significance and should be considered in any future ML modeling that assesses the fate of OCs in aquatic environment.