Men Cong, Ma Yuting, Jiang Haoquan, Tao Haoxiang, Li Zifu, Zuo Jiane
School of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing 100083, China; State Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China; State Key Laboratory of Iron and Steel Industry Environmental Protection, Central Research Institute of Building and Construction, Co. Ltd., MCC Group, Beijing 100088, China.
School of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing 100083, China.
J Environ Sci (China). 2025 Dec;158:694-709. doi: 10.1016/j.jes.2025.03.004. Epub 2025 Mar 8.
The widespread occurrence of antibiotics in urban rivers has raised global concerns for ecological security. Quantitative source-specific risk apportionment of antibiotics is crucial for targeted and effective ecological risk management, but is rarely studied. In this study, a source-specific ecological risk apportionment model for antibiotics was developed by combining the ecological risk quotient (RQ) method and the positive matrix factorization (PMF) model. Based on twenty-two antibiotics in sixty-five water samples from thirteen sites in Beijing in wet and dry seasons, the spatial variation and probabilistic distribution of ecological risk associated with antibiotics were analyzed, and source-specific ecological risk was evaluated. Results showed that for the sum of all antibiotics, the mean concentration of all samples was 671.48 ng/L, and the lower limit of the 90 % confidence interval of RQs was more than ten times the threshold for the high-risk level. The main sources were identified as domestic sewage, pharmaceutical wastewater and livestock discharge. It should be noted that higher contributions to antibiotic concentrations from sources do not always result in higher levels of ecological risk. Domestic sewage and livestock discharge contributed roughly equivalent amounts (36.17 % and 37.59 %, respectively) to antibiotic concentrations. However, domestic sewage was the most dominant source for risk (63.30 %), and livestock discharge only contributed 7.37 % to risk. The study found that evaluating the source-specific ecological risk associated with antibiotics is essential in addition to identifying their sources. The source-specific ecological risk apportionment model developed in this study is also referential for related studies.
