Hydrophobicity Parameter (log Kow) Estimation for Some Phenolic Compounds of Pharmaceutical Interest from Retention Studies with Mobile Phase Composition in Reversed‐Phase Liquid Chromatography

Elucidating governing factors of PFAS removal by polyamide membranes using machine learning and molecular simulations

Per- and polyfluoroalkyl substances (PFASs) have recently garnered considerable concerns regarding their impacts on human and ecological health. Despite the important roles of polyamide membranes in remediating PFASs-contaminated water, the governing factors influencing PFAS transport across these membranes remain elusive. In this study, we investigate PFAS rejection by polyamide membranes using two machine learning (ML) models, namely XGBoost and multimodal transformer models. Utilizing the Shapley additive explanation method for XGBoost model interpretation unveils the impacts of both PFAS characteristics and membrane properties on model predictions. The examination of the impacts of chemical structure involves interpreting the multimodal transformer model incorporated with simplified molecular input line entry system strings through heat maps, providing a visual representation of the attention score assigned to each atom of PFAS molecules. Both ML interpretation methods highlight the dominance of electrostatic interaction in governing PFAS transport across polyamide membranes. The roles of functional groups in altering PFAS transport across membranes are further revealed by molecular simulations. The combination of ML with computer simulations not only advances our knowledge of PFAS removal by polyamide membranes, but also provides an innovative approach to facilitate data-driven feature selection for the development of high-performance membranes with improved PFAS removal efficiency.

Insights into the efficiencies of different biological treatment systems for pharmaceuticals removal: A review

This review presents a comprehensive analysis of current research on biological treatment processes for removing pharmaceutical compounds (PhCs) from wastewater. Unlike previous studies on this topic, our study specifically delves into the effectiveness and drawbacks of various treatment approaches such as traditional wastewater treatment facilities (WWTP), membrane bioreactors (MBRs), constructed wetlands (CW), and moving bed biofilm reactors (MBBR). Through the examination and synthesis of information gathered from more than 200 research studies, we have created a comprehensive database that delves into the effectiveness of eliminating 19 particular PhCs, including commonly studied compounds such as acetaminophen, ibuprofen, diclofenac, naproxen, ketoprofen, indomethacin, salicylic acid, codeine, and fenoprofen, amoxicillin, azithromycin, ciprofloxacin, ofloxacin, tetracycline, atenolol, propranolol, and metoprolol. This resource provides a depth and scope of information that was previously lacking in this area of study. Notably, among these pharmaceuticals, azithromycin demonstrated the highest removal rates across all examined treatment systems, with the exception of WWTPs, while carbamazepine consistently exhibited the lowest removal efficiencies across various systems. The analysis showcases the diverse results in removal efficiency impacted by factors such as system configuration, operation specifics, and environmental circumstances. The findings emphasize the critical need for continued innovation and research, specifically recommending the integration of advanced oxidation processes (AOPs) with existing biological treatment methods to improve the breakdown of recalcitrant compounds like carbamazepine. PRACTITIONER POINTS: Persistent pharmaceuticals harm aquatic ecosystems and human health. Biological systems show varying pharmaceutical removal efficiencies. Enhancing HRT and SRT improves removal but adds complexity and costs. Tailored treatment approaches needed based on contaminants and conditions.

Occurrence and Fate of Bisphenol A and its Congeners in Two Wastewater Treatment Plants and Receiving Surface Waters in Romania

The present study investigated the distribution and environmental fate of Bisphenol A (BPA), the 4-hydroxyacetophenone (4-HAP) metabolite, and 5 other bisphenol congeners in 2 municipal wastewater treatment plants (WWTPs) and their receiving rivers in Romania. Accordingly, a new, highly sensitive and accurate solid-phase extraction-liquid chromatography-electrospray ionization-tandem mass spectrometry method was developed and validated. This technique generated low limit of quantitation values: below 2.3 ng/L for surface water and less than 2.4 and 2.7 ng/L for WWTP effluent and influent water. The sum of detected analytes in wastewater was between 1337 and 16 118 ng/L for influent samples and between 15 and 96 ng/L for effluent samples. In surface water, the total of all compounds was somewhere between 34 and 240 ng/L. The highest concentration observed was for BPA in all 3 types of analyzed water (up to 9140 ng/L for influent, as high as 75 ng/L for effluent, and a maximum of 135 ng/L in surface waters). All analyzed samples were free of bisphenols B, C, and F. For all analytes detected in surface water, the concentration values were higher than those determined in the effluent samples, which may be caused by intrinsic contamination of the 2 rivers (Danube and Jiu Rivers). Values of environmental risk coefficients, calculated for both effluents and surface waters, indicated a low ecological risk or no ecological risk for 3 types of organisms (algae, daphnia, and fish). Human risk assessment calculation suggests no risk to human health as a result of the presence of BPA in either of the 2 rivers. Environ Toxicol Chem 2021;40:435-446. © 2020 SETAC.