Emerging contaminants (ECs) in industrial parks pose a multi-source, transboundary threat to aquatic ecosystems and drinking water safety. Current ECs studies are often fragmented, focusing separately on sources, treatment performance, or ecological risks. Here, this study established an integrated “source–sink–fate” framework within a representative industrial park upstream of Dongjiang River, a major drinking water source for Greater Bay Area. The framework quantitatively combined with industrial emission sources, treatment processes in wastewater treatment plants (WWTPs), and downstream ecological risks, which could generate risk priority and management lists. Results showed that phthalic acid esters (PAEs) were intensively discharged from electronics and food and beverage (7.5–5572.2 ng/L), while per– and polyfluoroalkyl substances (PFAS; 1.6–157.4 ng/L) and organophosphate esters (OPEs; 49.6–4849.8 ng/L) were mainly associated with textile and manufacturing. Conventional WWTPs exhibited limited or even negative removal efficiencies for some ECs (−28.9% to 71.5%), indicating potential secondary pollution risks. The multi-model analysis of source apportionment indicated a complex interplay of point and non-point sources in this park. Risk quotient (RQ) analysis identified PAEs (RQ mix ≥ 1.0; particularly DBP, DPhP, and DNOP) and pharmaceuticals (ACE) as high risks to priority control targets. Importantly, the generalizability of this framework lied in its systematic analytical outputs, including source contribution rankings, and risk-based priority control lists, rather than site-specific concentrations. This framework provides a transferable, quantitative tool to support proactive ECs risk management in other industrial clusters and mixed-source watersheds. • A “source–sink–fate” framework was established to track ECs in an industrial park. • The framework was used for broad-spectrum rapid screening and risk assessment of ECs. • PAEs of electronics and OPEs of machinery were the main ECs sources in industries. • PMF, PLS-DA and Spearman multi-analysis were used to reveal ECs source profiles. • PMF and RQ were used to assess ecological risks and the priority control lists.
Deng et al. (Sun,) studied this question.