Jul 2026· Environmental Science &
Technology· Vol 60, pp. 26678-26692· 0 citations· 58 references
Abstract
Agricultural ditches play an underappreciated role in accumulating or attenuating waterborne emerging contaminants (ECs) from farmlands to downstream aquatic ecosystems. Here, we present the first nationwide assessment of ECs in ditches across major agricultural regions of China, through analyzing over 300 compounds at 183 sampling sites. A multicriteria assessment framework was applied to prioritize contaminants along the farmland ditch–river continuum by integrating scenario-specific occurrence patterns, transferable environmental fate properties, and toxicological profiles covering cytotoxicity, ecotoxicity, and human health endpoints. Principal component analysis was used to derive data-driven weights from the nationally representative data set, enabling objective synthesis of commonly used risk dimensions while reflecting the agricultural ditch context, avoiding the subjectivity of expert-assigned scoring. The prioritization identified per- and polyfluoroalkyl substances (PFASs) as the highest-priority pollutants owing to their extreme persistence, bioaccumulation potential, and human health risks, followed by several pesticides (notably tebuconazole and fipronil), bisphenol A, di-n-octyl phthalate, and natural hormones. Cluster analysis revealed two distinct pathways to high priority: source-intensive contaminants driven by continuous agricultural inputs and legacy-type persistent chemicals attributed to intrinsic molecular stability. Over 60% of the top-ranked substances appear on international regulatory watch lists, including those of China, the EU, and the US EPA, confirming the framework’s practical relevance. Beyond providing priority rankings for agricultural ditch management, our methodology offers a transparent and adaptable template for contaminant prioritization in other environmental settings.
Emerging contaminants (ECs), particularly PFAS and antibiotics, occur as mixtures in urban rivers, yet conventional mass-based receptor models provide limited support for toxicity-oriented source-category prioritization. Here, we apply a PMF-SRC workflow that integrates toxicity weighting into receptor modeling to enab...
Le-Tian Zhang, Jia-Qi Yang, Nan-Yang Yu et al.· Journal of Hazardous Materia...· 0 citations
Preventive pesticide monitoring in tropical agricultural catchments is frequently constrained by limited analytical capacity, incomplete environmental datasets, and the large number of potentially relevant compounds requiring evaluation. To address these limitations, this study developed and applied a multicriteria scr...
Graphical abstract outlines the aims of the study, the approach, findings and opportunities.
Contaminants of emerging concern (CEC), such as pharmaceuticals, hormones and industrial chemicals, pose a significant challenge for the water industry due to their presence in matrices including wastewater and drinking wate...
P. Neale, M. Dingemans, Marty Hancock et al.· Journal of Water and Health· 0 citations
Emerging contaminants (ECs), such as pharmaceuticals, microplastics (MPs), per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAH), endocrine-disrupting compounds (EDC) and heavy metals, are progressively affecting soil ecosystems through multiple inputs such as wastewater irrigation, biosoli...
K. S. Kiran, M. Elayarajan, S. Suganya et al.· Plant Science Today· 0 citations
The rapid expansion of the 'Blue Economy' in tropical estuaries has created complex pollution profiles, necessitating robust methodologies to identify high-risk contaminants. Current prioritisation approaches often suffer from concentration bias, which masks trace-level but highly toxic compounds. This study, centred o...
Nitenpyram (NIT), a widely used neonicotinoid insecticide, has gained attention due to its extensive use in agriculture and veterinary medicine and frequent detection in aquatic and terrestrial environments. Although considered relatively short-lived, evidence suggests NIT exhibits complex environmental behavior and no...
Yun-Xiu Zhao, Wen-Jing Li, Qiu-Tong Li et al.· Environmental Reviews· 0 citations
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