Pearson, HBC, Comber, SDW, Braungardt, C et al. (3 more authors) (2018) Determination and prediction of zinc speciation in estuaries. Environmental Science & Technology, 52 (24). pp. 14245-14255. ISSN 0013-936X
Abstract
Lowering of the estuarine Environmental Quality Standard for zinc in the UK to 121 nM reflects rising concern regarding zinc in ecosystems and is driving the need to better understand its fate and behaviour and to develop and parameterise speciation models to predict the metal species present. For the first time, an extensive dataset has been gathered for the speciation of zinc within an estuarine system with supporting physico-chemical characterisation, in particular dissolved organic carbon. WHAM/Model VII and Visual MINTEQ speciation models were used to simulate zinc speciation, using a combination of measured complexation variables and available defaults. Data for the five estuarine transects from freshwater to seawater endmembers showed very variable patterns of zinc speciation depending on river flows, seasons, and potential variations in metal and ligand inputs from in situ and ex situ sources. There were no clear relationships between free zinc ion concentration [Zn2+] and measured variables such as DOC concentration, humic and biological indices. Simulations of [Zn2+] carried out with both models at high salinities or by inputting site specific complexation capacities were successful, but overestimated [Zn2+] in low salinity waters, probably owing to an underestimation of the complexation strength of the ligands present. Uncertainties in predicted [Zn2+] are consistently smaller than standard deviations of the measured values, suggesting that the accuracy of the measurements is more critical than model uncertainty in evaluating the predictions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright © 2018 American Chemical Society. This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Environmental Modeling after peer review. To access the final edited and published work see https://doi.org/10.1021/acs.est.8b04372 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Earth Surface Science Institute (ESSI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Nov 2018 09:50 |
Last Modified: | 13 Nov 2019 01:38 |
Status: | Published |
Publisher: | American Chemical Society |
Identification Number: | 10.1021/acs.est.8b04372 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138704 |