Occurrence, fate, and risk assessment of antibiotics in conventional and advanced drinking water treatment systems: From source to tap

被引:5
作者
Zhang, Guorui [1 ]
Zhang, Chao [2 ]
Liu, Jie [1 ]
Zhang, Yixiang [3 ,4 ]
Fu, Wenjie [2 ]
机构
[1] Lanzhou Univ, Coll Pastoral Agr Sci & Technol, Ctr Grassland Microbiome, State Key Lab Herbage Improvement & Grassland Agro, Lanzhou 730020, Peoples R China
[2] Guangxi Normal Univ, Key Lab Ecol Rare & Endangered Species & Environm, Coll Environm & Resources, Minist Educ, Guilin 541004, Peoples R China
[3] Tsinghua Univ, Dept Chem, Beijing 100084, Peoples R China
[4] Tsinghua Univ, Key Lab Organ Optoelect & Mol Engn, Minist Educ, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Antibiotics; Drinking water treatment; Indicator; Risk assessment; Random forest; Source tracking; PERSONAL CARE PRODUCTS; ORGANIC MICROPOLLUTANTS; PHARMACEUTICALS; CHEMICALS; REMOVAL; SURFACE; PLANTS; RIVERS; AREA;
D O I
10.1016/j.jenvman.2024.120746
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The occurrence and removal of 38 antibiotics from nine classes in two drinking water treatment plants (WTPs) were monitored monthly over one year to evaluate the efficiency of typical treatment processes, track the source of antibiotics in tap water and assess their potential risks to ecosystem and human health. In both source waters, 18 antibiotics were detected at least once, with average total antibiotic concentrations of 538.5 ng/L in WTP1 and 569.3 ng/L in WTP2. The coagulation/flocculation and sedimentation, sand filtration and granular activated carbon processes demonstrated limited removal efficiencies. Chlorination, on the other hand, effectively eliminated antibiotics by 48.7 +/- 11.9%. Interestingly, negative removal was observed along the distribution system, resulting in a significant antibiotic presence in tap water, with average concentrations of 131.5 ng/L in WTP1 and 362.8 ng/L in WTP2. Source tracking analysis indicates that most antibiotics in tap water may originate from distribution system. The presence of antibiotics in raw water and tap water posed risks to the aquatic ecosystem. Untreated or partially treated raw water could pose a medium risk to infants under six months. Water parameters, for example, temperature, total nitrogen and total organic carbon, can serve as indicators to estimate antibiotic occurrence and associated risks. Furthermore, machine learning models were developed that successfully predicted risk levels using water quality parameters. Our study provides valuable insights into the occurrence, removal and risk of antibiotics in urban WTPs, contributing to the broader understanding of antibiotic pollution in water treatment systems.
引用
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页数:9
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