Literature DB >> 20673965

The use of modelling to predict levels of estrogens in a river catchment: how does modelled data compare with chemical analysis and in vitro yeast assay results?

Jan L Balaam1, Darren Grover, Andrew C Johnson, Monika Jürgens, James Readman, Andy J Smith, Stefan White, Richard Williams, John L Zhou.   

Abstract

Effluent discharges at Rodbourne sewage treatment works (STWs) were assessed using chemical and in vitro biological analysis as well as modelling predictions. Results showed that Rodbourne STW discharged less estrone (E1) than expected, but similar 17beta-estradiol (E2) and 17alpha-ethinyl estradiol (EE2) to those predicted by a widely cited effluent prediction model. The Exposure Analysis Modelling System (EXAMS) model was set up using measured effluent concentrations as its starting point to predict estrogen concentrations along a 10 km length of the receiving water of the River Ray. The model adequately simulated estrogen concentrations along the river when compared to July 2007 measured data. The model predicted combined estrogen equivalents in reasonable agreement with estrogenicity as measured by passive sampler (POCIS) extracts using the yeast estrogen screen. Using gauged mean flow values for 2007 the model indicated that the most important determinand for estrogen exposure in the Ray was not season, but proximity to the Rodbourne effluent. Thus, fish in the first 3 km downstream of Rodbourne were typically exposed to two or even three times more estrogens than those living 7-10 km further downstream. The modelling indicated that, assuming the effluent estrogen concentrations measured in February 2008 were typical, throughout the year the whole length of the Ray downstream of Rodbourne would be estrogenic, i.e. exceeding the 1 ng/L E2 equivalent threshold for endocrine disruption. Crown Copyright 2010. Published by Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20673965     DOI: 10.1016/j.scitotenv.2010.07.019

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


  5 in total

1.  Is the toxicity of pesticide mixtures on river biofilm accounted for solely by the major compounds identified?

Authors:  Sandra Kim Tiam; Soizic Morin; Berta Bonet; Helena Guasch; Agnès Feurtet-Mazel; Mélissa Eon; Patrice Gonzalez; Nicolas Mazzella
Journal:  Environ Sci Pollut Res Int       Date:  2014-08-01       Impact factor: 4.223

2.  Application of the GREAT-ER model for environmental risk assessment of nonylphenol and nonylphenol ethoxylates in China.

Authors:  Lai Zhang; Yan Cao; Xuewen Hao; Yongyong Zhang; Jianguo Liu
Journal:  Environ Sci Pollut Res Int       Date:  2015-09-10       Impact factor: 4.223

3.  Ecological Risk Assessment of Pharmaceuticals in the Transboundary Vecht River (Germany and The Netherlands).

Authors:  Daniel J Duarte; Gunnar Niebaum; Volker Lämmchen; Eri van Heijnsbergen; Rik Oldenkamp; Lucia Hernández-Leal; Heike Schmitt; Ad M J Ragas; Jörg Klasmeier
Journal:  Environ Toxicol Chem       Date:  2021-05-28       Impact factor: 4.218

4.  What Works? the Influence of Changing Wastewater Treatment Type, Including Tertiary Granular Activated Charcoal, on Downstream Macroinvertebrate Biodiversity Over Time.

Authors:  Andrew C Johnson; Monika D Jürgens; François K Edwards; Peter M Scarlett; Helen M Vincent; Peter von der Ohe
Journal:  Environ Toxicol Chem       Date:  2019-08       Impact factor: 3.742

Review 5.  Improving Toxicity Assessment of Pesticide Mixtures: The Use of Polar Passive Sampling Devices Extracts in Microalgae Toxicity Tests.

Authors:  Sandra Kim Tiam; Vincent Fauvelle; Soizic Morin; Nicolas Mazzella
Journal:  Front Microbiol       Date:  2016-09-09       Impact factor: 5.640

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.