Literature DB >> 27387795

Temporal-spatial variation and partitioning prediction of antibiotics in surface water and sediments from the intertidal zones of the Yellow River Delta, China.

Shengnan Zhao1, Xinhui Liu2, Dengmiao Cheng3, Guannan Liu4, Baocui Liang1, Baoshan Cui1, Junhong Bai1.   

Abstract

As special zones, the intertidal zones of the Yellow River Delta (YRD) are highly variable along with time and space. Fluvial-marine and land-ocean interactions which frequently occur in these areas have a great impact on the fate of pollutants. Antibiotics, which contribute to antibiotic-resistant genes (ARGs), are widely detected in wastewater, natural water, soil, sediments, and even drinking water. Therefore, it is meaningful to investigate the occurrence and fate of antibiotics in these special zones. In this study, eight antibiotics belonging to tetracyclines (TCs), fluoroquinolones (FQs), and macrolides (MLs) were detected in the surface water and sediments from the intertidal zones of YRD during two seasons. Two models were established to predict the partitioning coefficients of norfloxacin (NOR) and erythromycin (ETM) using physicochemical properties of sediments, respectively. The total concentrations of these antibiotics were 82.94-230.96ng·L(-1) and 40.97-207.44ng·g(-1), respectively, in the surface water and sediments. Seasonal variation was mainly influenced by the frequency of antibiotics use and environment factors. The regions with river supply exhibited the highest concentrations of antibiotics in surface water and sediments. Meanwhile, particle-size fractions, cation exchange capability (CEC), and metal ions content played dominant roles in the partitioning behaviors of NOR and ETM between the surface water and sediments. Both models established in this study featured accuracy and feasibility, which provided the methods for predicting the partitioning coefficients of emerging contaminants similar in structures to NOR and ETM in the intertidal zones.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibiotics; Partitioning prediction; Temporal–spatial variation; The intertidal zones

Mesh:

Substances:

Year:  2016        PMID: 27387795     DOI: 10.1016/j.scitotenv.2016.06.216

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


  12 in total

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