Quantifying contributions from unmonitored point-source discharges in an urban river using optical and nitrate isotopic tracers under dry-weather conditions

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Abstract

Small-scale wastewater treatment facilities in urban streams often operate under less stringent management, yet their contributions to organic pollution can significantly impact aquatic ecosystems. Continuous monitoring of these discharges remains challenging, necessitating prompt assessment methods. This study applies an end-member mixing analysis (EMMA) approach using stable isotope ratios and optical indices to estimate the contribution of organic matter from small, unidentified point sources. To simplify source attribution and improve methodological efficiency, background DOM—primarily from baseflow and natural organic inputs—was treated as a single end-member. This approach reduces the complexity of end-member sampling while maintaining robust estimates of unknown point-source contributions. Wastewater discharges from a swine wastewater treatment plant and two food-processing facilities were evaluated for their downstream impact. The EMMA model demonstrated that fluorescence index (FI) and biological index (BIX) provided the most reliable estimates of point-source contributions at downstream sites, yielding consistent results with both measured loading data and model outputs based on the dual nitrate isotope pair (δ¹⁵N-NO₃ - δ¹⁸O-NO₃). However, further downstream, the isotopic model yielded more robust assessments, likely due to its lower susceptibility to biogeochemical alternations during DOM transport compared to the spectroscopic indices. This study demonstrates the effectiveness of optical and isotopic tracers for point-source attribution in urban watersheds, particularly in irregularly monitored or unmonitored settings.

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Jeon, P., Oh, H., Lee, S., Kim, M. S., Hong, S., Baek, K., & Hur, J. (2025). Quantifying contributions from unmonitored point-source discharges in an urban river using optical and nitrate isotopic tracers under dry-weather conditions. Environmental Technology and Innovation, 40. https://doi.org/10.1016/j.eti.2025.104399

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