Amid growing concerns regarding the ecological risks posed by emerging contaminants, per- and polyfluoroalkyl substances (PFASs) present significant challenges for risk assessment due to their structural diversity and the paucity of experimental data...
Organophosphate esters (OPEs) have emerged as a significant environmental concern due to their widespread occurrence and potential human health risks. The presence of OPEs in human blood suggests direct interactions with hematological components, whi...
Real-time water quality risk management in wastewater treatment plants (WWTPs) requires extensive data, and data sharing is still just a slogan due to data privacy issues. Here we show an adaptive water system federated averaging (AWSFA) framework ba...
Nanoplastics are a growing environmental concern due to their potential to disrupt cellular functions. Understanding how these particles interact with cell membranes is crucial for assessing their biological effects. In this study, we present a label...
The rapid increase in atmospheric CO, arising from anthropogenic sources, has posed a severe threat to global climate and raised widespread environmental concern. Metal-organic frameworks (MOFs) are promising adsorbents to potentially reduce CO emiss...
Ozone has demonstrated high efficacy in depredating emerging contaminants (ECs) during drinking water treatment. However, traditional quantitative structure-activation relationship (QSAR) models often fall short in effectively normalizing and charact...
Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic estrogen receptors (ERs) to induce genomic effects, as well as to G protein-coupled estrogen receptor (GPER) located on the membrane, thereby inducin...
Microplastics (MPs) and nanoplastics (NPs) present formidable global environmental challenges with serious risks to human health and ecosystem sustainability. Despite their significance, the accurate assessment of environmental MP and NP pollution re...
The marine environment is grappling with microplastic (MP) pollution, necessitating an understanding of its distribution patterns, influencing factors, and potential ecological risks. However, the vast area of the ocean and budgetary constraints make...
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...