Emerging contaminants follow class-specific mechanistic regimes in sediment–water partitioning
- 1School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China
- 2School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China; Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou, 510275, China; Corresponding author. School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China.
Abstract
Understanding the sediment–water partitioning of emerging contaminants is essential for assessing their mobility, persistence and ecological risks in river systems. However, the mechanisms driving large differences in partitioning behaviour across contaminant classes remain poorly resolved at the basin scale. Here we show that major emerging contaminant classes follow distinct mechanistic regimes in sediment–water partitioning. Analysis of a nationwide dataset comprising 5085 paired sediment–water records across China's major river basins reveals that antibiotics are predominantly controlled by molecular descriptors, per- and polyfluoroalkyl substances are strongly modulated by ion-mediated interfacial processes, and endocrine-disrupting chemicals exhibit synergistic regulation by molecular, geochemical and basin-scale factors. Integration with molecular dynamics simulations confirms these class-specific mechanisms at the molecular interface, while a multi-branch multi-head attention framework enables accurate prediction ( R 2 = 0.76–0.92) and spatially explicit mapping of high-accumulation versus high-mobility zones. By identifying class-specific mechanistic regimes, this work provides both improved predictive capability and a clearer mechanistic basis for basin-scale risk assessment of emerging contaminants.
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BibTeX
@article{wu2026emerging,
title = {{Emerging contaminants follow class-specific mechanistic regimes in sediment–water partitioning}},
author = {Taiwu Wu and Zhenhua Tang and Shiting Zheng and Hongyan Huang and Xinzhe Zhu},
journal = {Environmental Science and Ecotechnology},
year = {2026},
month = sep,
doi = {10.1016/j.ese.2026.100751},
url = {https://doi.org/10.1016/j.ese.2026.100751},
note = {CC BY},
}
RIS
TY - JOUR
TI - Emerging contaminants follow class-specific mechanistic regimes in sediment–water partitioning
AU - Taiwu Wu
AU - Zhenhua Tang
AU - Shiting Zheng
AU - Hongyan Huang
AU - Xinzhe Zhu
PY - 2026
DA - 2026/09/01
JO - Environmental Science and Ecotechnology
DO - 10.1016/j.ese.2026.100751
UR - https://doi.org/10.1016/j.ese.2026.100751
AB - Understanding the sediment–water partitioning of emerging contaminants is essential for assessing their mobility, persistence and ecological risks in river systems. However, the mechanisms driving large differences in partitioning behaviour across contaminant classes remain poorly resolved at the basin scale. Here we show that major emerging contaminant classes follow distinct mechanistic regimes in sediment–water partitioning. Analysis of a nationwide dataset comprising 5085 paired sediment–water records across China's major river basins reveals that antibiotics are predominantly controlled by molecular descriptors, per- and polyfluoroalkyl substances are strongly modulated by ion-mediated interfacial processes, and endocrine-disrupting chemicals exhibit synergistic regulation by molecular, geochemical and basin-scale factors. Integration with molecular dynamics simulations confirms these class-specific mechanisms at the molecular interface, while a multi-branch multi-head attention framework enables accurate prediction ( R 2 = 0.76–0.92) and spatially explicit mapping of high-accumulation versus high-mobility zones. By identifying class-specific mechanistic regimes, this work provides both improved predictive capability and a clearer mechanistic basis for basin-scale risk assessment of emerging contaminants.
SN - 2666-4984
ER -