Literature DB >> 30577122

Predicting distribution coefficients for antibiotics in a river water-sediment using quantitative models based on their spatiotemporal variations.

Jinpeng Tang1, Sai Wang1, Jingjing Fan2, Shengxin Long2, Lin Wang2, Chen Tang2, Nora Fungyee Tam3, Yang Yang4.   

Abstract

Antibiotics are widely used in humans and animals, but their presence in environmental matrices after use is of great concern. Distribution behavior of antibiotics in natural water-sediment systems is influenced by sediment properties, but how these properties, such as surface area, affect their distribution between water and sediment phases remains unclear. The concentrations of antibiotics also vary both spatially and temporally. In this study, a solid/liquid distribution coefficient Kd(pre) was proposed and evaluated in 12 quantitative predicting models based on aquatic field data compared with a bulk coefficient Kd. Results confirmed by the occurrence pattern, concentration levels and spatiotemporal distributions indicated that the characteristics of antibiotics pollution in rural northwestern Guangzhou were generally consistent with previous investigations, suggesting that this investigation was representative of the present aquatic pollution status of antibiotics. The median concentrations were <100 ng·L-1 and 220 ng·g-1 (d.w.) in the water and sediments, respectively. The most pronounced high concentrations of total antibiotic residue found were 778.0 ng·L-1 for sulfonamides (SAs) in water and 1596.9 ng·g-1 (d.w.) for fluoroquinolones (FQs) in sediments at site 13 in December of 2016, probably due to its dense population, high frequency of antibiotic use and low water flow. Moreover, 12 quantitative models were established with a high level of robustness and ability to spatiotemporally predict the Kd for each of the 12 antibiotics. The models revealed that pH, organic matter and specific surface area of sediments played significant roles in influencing the adsorption of SAs, FQs, tetracyclines (TCs) and (macrolides) MLs. Our findings provide insights into the effects of physicochemical properties on distribution of antibiotics, predicting their fate and transport, as well as assessments of exposure and risk of these emerging pollutants to aquatic ecosystems.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibiotic; Predictive model; Sediment physicochemical property; Water-sediment distribution coefficient

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Year:  2018        PMID: 30577122     DOI: 10.1016/j.scitotenv.2018.11.163

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Distribution, residue level, sources, and phase partition of antibiotics in surface sediments from the inland river: a case study of the Xiangjiang River, south-central China.

Authors:  Leilei Chen; Haipu Li; Yang Liu; Yue Cui; Yue Li; Zhaoguang Yang
Journal:  Environ Sci Pollut Res Int       Date:  2019-11-27       Impact factor: 4.223

2.  Transformation of Tetracycline by Manganese Peroxidase from Phanerochaete chrysosporium.

Authors:  Xuemei Sun; Yifei Leng; Duanji Wan; Fengyi Chang; Yu Huang; Zhu Li; Wen Xiong; Jun Wang
Journal:  Molecules       Date:  2021-11-11       Impact factor: 4.411

  2 in total

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