Integrated social development on analyzing the distribution, risk and source apportionment of antibiotics pollution in mountainous rivers

• 42 antibiotics amounted 0.05-7.4 × 10 5 ng/L are detected from 9 mountainous rivers in Chongqing. • Ofloxacin (RQ: 0.22-2.43 × 10 4 ) and lincomycin (RQ: 0.07-1.06 × 10 4 ) exhibit high risks in various water bodies. • Regional socioeconomic factors drive the occurrence and distribution of antibiotics. • PMF model reveals sources of antibiotics and ToxPi recommends 7 priority antibiotics. Antibiotics, as the widespread drugs stimulate the evolution of antibiotic resistance, threatening human and ecosystem health worldwide. However, studies rarely conducted in rivers among the regional scale with diverse economic development, which limits the management efficient of antibiotic control. Therefore, we investigated the concentration, distribution, risk and source apportionment of 54 antibiotics in 9 mountainous rivers, where the economic social development divers among their watersheds in Chongqing, China. The results showed that the concentrations of antibiotics detected in surface water, effluent of wastewater treatment plants, hospital, livestock and aquaculture sewage were 0.13-290 ng/L, 2.17-590 ng/L, 6.58-2.16 × 10 5 ng/L, 4.5-7.4 × 10 5 ng/L and 4.41-7.49 × 10 3 ng/L, respectively. The order of total antibiotic concentrations along the investigated rivers was Laixi River > Changshou Lake > Longxi River > Fujiang River > Jialing River > Qiongjiang River > Yangtze River > Wujiang River > Qijiang River. The risk quotient indicates that ofloxacin and lincomycin exhibited high risk. Through Mantel test and correlation analysis screened antibiotics associated with anthropogenic factors. Municipal wastewater had a positive impact on QNs. The positive matrix factorization model was used to identify the main sources of antibiotics in surface water with special focus on the Longxi River, revealing the livestock and aquaculture were main contributions, respectively. The ToxPi method was employed to prioritize antibiotics in surface water, and seven compounds were recommended as priority chemicals of concern in the future. This work provides a valuable regional scale dataset of antibiotics in the mountainous rivers, which promises valuable insights for controlling antibiotic contamination.