Quantitative structure-activity relationship models for the reaction rate coefficients between dissolved organic matter and PPCPs

Organic Cation Transporter Mediates the Uptake of Quaternary Ammonium Compounds in Arabidopsis

Quaternary ammonium compounds (QACs), widely used in consumer products and pharmaceuticals, are increasingly released into soils and can accumulate in plants, posing significant ecological and health risks. While plant uptake mechanisms for QACs remain poorly characterized, this study identifies organic cation transporter 1 (OCT1) as a potential mediator of QAC absorption in Arabidopsis. Root uptake experiments demonstrated reduced QAC accumulation under treatments with metabolic and OCT inhibitors. Transcriptional upregulation of AtOCT1 in QAC-exposed wild-type plants, along with functional validation through yeast heterologous expression systems, implicated this transporter in cationic pollutant absorption. Comparative analysis revealed 12%-42% lower root QAC concentrations in AtOCT1 mutants compared to wild-type plants, while overexpression lines exhibited 9.4%-43% increases in accumulation alongside enhanced sensitivity. Molecular docking simulations demonstrated stronger binding affinities between AtOCT1 and QACs compared to its native substrate L-carnitine, with microscale thermophoresis confirming direct interactions. Quantitative structure-activity relationship analysis identified electronic energy, molecular weight, and polarizability as critical determinants of AtOCT1-mediated transport efficiency. These findings establish the biological and structural role of AtOCT1 in cationic pollutant uptake, advancing mechanistic understanding of transporter-mediated plant accumulation of ionizable organic pollutants.

A machine learning framework to predict PPCP removal through various wastewater and water reuse treatment trains

The persistence of pharmaceuticals and personal care products (PPCPs) through wastewater treatment and resulting contamination of aquatic environments and drinking water is a pervasive concern, necessitating means of identifying effective treatment strategies for PPCP removal. In this study, we employed machine learning (ML) models to classify 149 PPCPs based on their chemical properties and predict their removal via wastewater and water reuse treatment trains. We evaluated two distinct clustering approaches: C1 (clustering based on the most efficient individual treatment process) and C2 (clustering based on the removal pattern of PPCPs across treatments). For this, we grouped PPCPs based on their relative abundances by comparing peak areas measured via non-target profiling using ultra-performance liquid chromatography-tandem mass spectrometry through two field-scale treatment trains. The resulting clusters were then classified using Abraham descriptors and log K ow as input to the three ML models: support vector machines (SVM), logistic regression, and random forest (RF). SVM achieved the highest accuracy, 79.1%, in predicting PPCP removal. Notably, a 58-75% overlap was observed between the ML clusters of PPCPs and the Abraham descriptor and log K ow clusters of PPCPs, indicating the potential of using Abraham descriptors and log K ow to predict the fate of PPCPs through various treatment trains. Given the myriad of PPCPs of concern, this approach can supplement information gathered from experimental testing to help optimize the design of wastewater and water reuse treatment trains for PPCP removal.

Introducing a prediction method for the photodegradation of p-cresol, a phenolic contaminant of emerging concern, in wastewater effluent

Despite extensive efforts to understand the photodegradation of phenolic contaminants of emerging concern (PhCECs) in aquatic systems, prediction methods, especially in waters containing effluent organic matter (EfOM), remain underdeveloped. This study introduces a prediction method for p-cresol, a representative PhCECs, based on correlations between EfOM optical parameters and p-cresol kinetic parameters. We examined p-cresol photodegradation in various EfOM samples, characterized by their optical properties, and used the reaction rate coefficient between EfOM and p-cresol, α3EfOM⁎, to quantify and predict p-cresol degradation in different wastewater effluent samples. Results showed significant correlations between p-cresol's photodegradation rate constant (0.144 to 0.441 h-1) and EfOM characteristics, with α3EfOM⁎ values ranging from 4 × 1011 to 10 × 1011 M-1 s-1. The method was validated with p-cresol at concentrations ranging from 25 to 100 μM and multiple EfOM samples. The method's applicability was further evaluated using propranolol, a pharmaceutical contaminant of emerging concern, demonstrating its versatility for predicting the degradation behavior of other contaminants in different wastewater samples. The method accurately predicted p-cresol and propranolol degradation across diverse wastewater samples, suggesting its potential for expansion to other classes of contaminants, aiding in water quality management, improving wastewater treatment processes, and enhancing environmental risk assessments.

Potential of solar photodegradation of antibiotics in shallow ditches: Kinetics, the role of dissolved organic matter and prediction models

Shallow ditches, which generally receive livestock or domestic sewage, are widely distributed in rural and suburban areas, making them important sites for antibiotic exposure. Because of the easy penetration of solar irradiation, the photochemical reactions of antibiotics tend to be active in shallow ditches. This study investigated the photodegradation potential of 21 commonly used antibiotics belonging to five categories in a typical shallow ditch by conducting simulated solar irradiation experiments. The influence of dissolved organic matter (DOM) in ditch water on the photodegradation of antibiotics was analyzed, and a model based on DOM changes was established to predict the degradation behavior of antibiotics. The results indicated that the degradation rates of different varieties of antibiotics in ultrapure water and ditch water followed the trend of fluoroquinolones > tetracyclines > sulfonamides > macrolides > lincosamides. In ditch water, direct photodegradation and photooxidation mediated by 3DOM∗ played predominant roles in the antibiotic photodegradation, whereas the contributions of singlet oxygen (1O2) and hydroxyl radicals (·OH) varied significantly depending on the reactivity of the antibiotics. A simple and effective model was proposed for predicting the photodegradation process of antibiotics in ditch water based on the degree of DOM photobleaching determined by excitation-emission matrix fluorescence spectroscopy coupled with parallel factor analysis. The prediction model was simplified by considering the similarity in photochemical properties within the same category of antibiotics and was validated by field tests. This study fills a critical research gap by evaluating the photodegradation of antibiotics in shallow ditches, thereby providing valuable insights into their fate and transport in shallow ditch water.

Effects of dissolved organic matter from different sources on ritonavir photolysis

With the misuse of antiviral drugs, the residual levels of ritonavir (RTV) in aquatic environments continue to increase, potentially posing threats to ecosystems and human health. However, the current understanding of the photochemical behavior of RTV in water, especially the mechanism by which dissolved organic matter (DOM) from different sources affects the indirect photolysis of RTV, remains limited. This study systematically investigated the effects of DOM from different sources (including sludge, algae, dustfall, and soil, namely SL-DOM, AL-DOM, DF-DOM, and SO-DOM, respectively) on the photodegradation of RTV for the first time. DOM exhibited a dual role in RTV degradation, with SL-DOM and AL-DOM accelerating the degradation process, while DF-DOM and SO-DOM inhibited it. Direct photolysis accounted for 40-53% of the overall photodegradation, underscoring its significant contribution to the degradation process. Quenching and competitive kinetics experiments revealed that 3DOM⁎ is the dominant contributor to the indirect photolysis of RTV. Exogenous DOM (DF-DOM, SO-DOM) exhibited higher generation rate and steady-state concentraiton of 3DOM⁎, while endogenous DOM (SL-DOM, AL-DOM) exhibited higher quantum yields of 3DOM⁎ and reactivity, leading to distinct mechanisms for the indirect photodegradation of RTV. This study explored the effects of DOM from different sources on the photodegradation of RTV, providing important insights into how DOM affects the photochemical behavior and ecological risk of RTV. It also provides a reference for exploring the photochemical behavior of other drugs.

Recent advances in the role of dissolved organic matter during antibiotics photodegradation in the aquatic environment

The presence of residual antibiotics in the environment is a prominent issue. Photodegradation behavior is an important way of antibiotics reduction, which is closely related to dissolved organic matter (DOM) in water. The review provides an overview of the latest advancements in the field. Classification, characterization of DOM, and the dominant mechanisms for antibiotic photodegradation were discussed. Furthermore, it summarized and compared the effects of DOM on different antibiotics photodegradation. Moreover, the review comprehensively considered the factors influencing the photodegradation of antibiotics in the aquatic environment, including the characteristics of light, temperature, dosage of DOM, concentration of antibiotics, solution pH, and the presence of coexisting ions. Finally, potential directions were proposed for the development of predictive models for the photodegradation of antibiotics. Based on the review of existing literature, this paper also considered several pathways for the future study of antibiotic photodegradation. This study allows for a better understanding of the DOM's environmental role and provides important new insights into the photochemical fate of antibiotics in the aquatic environment.