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Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals
Transition metals are a group of elements widespread in aquatic environments that can be hazardous when concentrations exceeding threshold values. Due to insufficient data, criteria maximum concentrations (CMCs) of only seven transition metals for protecting aquatic life have been recommended by the...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776129/ https://www.ncbi.nlm.nih.gov/pubmed/26936420 http://dx.doi.org/10.1038/srep22515 |
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author | Wang, Ying Wu, Fengchang Mu, Yunsong Zeng, Eddy Y. Meng, Wei Zhao, Xiaoli Giesy, John P. Feng, Chenglian Wang, Peifang Liao, Haiqing Chen, Cheng |
author_facet | Wang, Ying Wu, Fengchang Mu, Yunsong Zeng, Eddy Y. Meng, Wei Zhao, Xiaoli Giesy, John P. Feng, Chenglian Wang, Peifang Liao, Haiqing Chen, Cheng |
author_sort | Wang, Ying |
collection | PubMed |
description | Transition metals are a group of elements widespread in aquatic environments that can be hazardous when concentrations exceeding threshold values. Due to insufficient data, criteria maximum concentrations (CMCs) of only seven transition metals for protecting aquatic life have been recommended by the USEPA. Hence, it is deemed necessary to develop empirical models for predicting the threshold values of water quality criteria (WQC) for other transition metals for which insufficient information on toxic potency is available. The present study established quantitative relationships between recommended CMCs and physicochemical parameters of seven transition metals, then used the developed relationships to predict CMCs for other transition metals. Seven of 26 physicochemical parameters examined were significantly correlated with the recommended CMCs. Based on this, five of the seven parameters were selected to construct a linear free energy model for predicting CMCs. The most relevant parameters were identified through principle component analysis, and the one with the best correlation with the recommended CMCs was a combination of covalent radius, ionic radius and electron density. Predicted values were largely consistent with their toxic potency values. The present study provides an alternative approach to develop screening threshold level for metals which have insufficient information to use traditional methods. |
format | Online Article Text |
id | pubmed-4776129 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47761292016-03-09 Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals Wang, Ying Wu, Fengchang Mu, Yunsong Zeng, Eddy Y. Meng, Wei Zhao, Xiaoli Giesy, John P. Feng, Chenglian Wang, Peifang Liao, Haiqing Chen, Cheng Sci Rep Article Transition metals are a group of elements widespread in aquatic environments that can be hazardous when concentrations exceeding threshold values. Due to insufficient data, criteria maximum concentrations (CMCs) of only seven transition metals for protecting aquatic life have been recommended by the USEPA. Hence, it is deemed necessary to develop empirical models for predicting the threshold values of water quality criteria (WQC) for other transition metals for which insufficient information on toxic potency is available. The present study established quantitative relationships between recommended CMCs and physicochemical parameters of seven transition metals, then used the developed relationships to predict CMCs for other transition metals. Seven of 26 physicochemical parameters examined were significantly correlated with the recommended CMCs. Based on this, five of the seven parameters were selected to construct a linear free energy model for predicting CMCs. The most relevant parameters were identified through principle component analysis, and the one with the best correlation with the recommended CMCs was a combination of covalent radius, ionic radius and electron density. Predicted values were largely consistent with their toxic potency values. The present study provides an alternative approach to develop screening threshold level for metals which have insufficient information to use traditional methods. Nature Publishing Group 2016-03-03 /pmc/articles/PMC4776129/ /pubmed/26936420 http://dx.doi.org/10.1038/srep22515 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Ying Wu, Fengchang Mu, Yunsong Zeng, Eddy Y. Meng, Wei Zhao, Xiaoli Giesy, John P. Feng, Chenglian Wang, Peifang Liao, Haiqing Chen, Cheng Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title | Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title_full | Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title_fullStr | Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title_full_unstemmed | Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title_short | Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals |
title_sort | directly predicting water quality criteria from physicochemical properties of transition metals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776129/ https://www.ncbi.nlm.nih.gov/pubmed/26936420 http://dx.doi.org/10.1038/srep22515 |
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