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Risk assessment of environmental mixture effects

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Risk assessment of environmental mixture effects. / Heys, Kelly; Shore, Richard Francis; Pereira, M. Glória et al.
In: RSC Advances, Vol. 2016, No. 53, 05.2016, p. 47844-47857.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Heys K, Shore RF, Pereira MG, Jones KC, Martin FL. Risk assessment of environmental mixture effects. RSC Advances. 2016 May;2016(53):47844-47857. Epub 2016 May 9. doi: 10.1039/c6ra05406d

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Heys, Kelly ; Shore, Richard Francis ; Pereira, M. Glória et al. / Risk assessment of environmental mixture effects. In: RSC Advances. 2016 ; Vol. 2016, No. 53. pp. 47844-47857.

Bibtex

@article{2b4d95469e09421a81b4874351d7025e,
title = "Risk assessment of environmental mixture effects",
abstract = "In the environment, organisms are exposed to a diverse array of chemicals in complex mixtures. The majority of approaches that aim to assess the risk of environmental chemical mixtures, including those used by regulatory bodies, use toxicity data generated from the individual component chemicals to predict the overall mixture toxicity. It is assumed that the behaviour of chemicals in a mixture can be predicted using the concepts of concentration or dose addition for chemicals with similar mechanisms of action or response addition for dissimilarly acting chemicals. Based on empirical evidence, most traditional risk assessment methods, such as toxic equivalency factors and the hazard index, make the assumption that the components of a mixture adhere to the concentration addition model. Thus, mixture toxicity can be predicted by the summation of the individual component toxicities. However in some mixtures, interactions can occur between chemicals or at target sites that alter the toxicity so that it is more or less than expected from the constituents. Many regulatory and experimental methods for predicting mixture toxicity rely on the use of a concentration addition model so that if interactions occur in mixtures, the risk posed may have been significantly underestimated. This is particularly concerning when considering environmental mixtures which are often highly complex and composed of indeterminate chemicals. Failure to accurately predict the effects chemicals will have if released into the environment, where they can form mixtures, can lead to unexpected detrimental effects on wildlife and ecosystems. The number of confounding factors that may alter the ecotoxicity of a mixture and the accuracy of predictive methods makes risk assessment of environmental mixtures a complex and intimidating task. With this in mind, this review aims show why accurate risk assessment of mixtures is vital by demonstrating the effect they can have on organisms in the environment. Furthermore, it also aims to look at the current challenges facing the assessment of mixture effects and examines future areas of focus that seek to develop methodologies more suitable for environmental mixtures.",
author = "Kelly Heys and Shore, {Richard Francis} and Pereira, {M. Gl{\'o}ria} and Jones, {Kevin Christopher} and Martin, {Francis Luke}",
year = "2016",
month = may,
doi = "10.1039/c6ra05406d",
language = "English",
volume = "2016",
pages = "47844--47857",
journal = "RSC Advances",
issn = "2046-2069",
publisher = "Royal Society of Chemistry",
number = "53",

}

RIS

TY - JOUR

T1 - Risk assessment of environmental mixture effects

AU - Heys, Kelly

AU - Shore, Richard Francis

AU - Pereira, M. Glória

AU - Jones, Kevin Christopher

AU - Martin, Francis Luke

PY - 2016/5

Y1 - 2016/5

N2 - In the environment, organisms are exposed to a diverse array of chemicals in complex mixtures. The majority of approaches that aim to assess the risk of environmental chemical mixtures, including those used by regulatory bodies, use toxicity data generated from the individual component chemicals to predict the overall mixture toxicity. It is assumed that the behaviour of chemicals in a mixture can be predicted using the concepts of concentration or dose addition for chemicals with similar mechanisms of action or response addition for dissimilarly acting chemicals. Based on empirical evidence, most traditional risk assessment methods, such as toxic equivalency factors and the hazard index, make the assumption that the components of a mixture adhere to the concentration addition model. Thus, mixture toxicity can be predicted by the summation of the individual component toxicities. However in some mixtures, interactions can occur between chemicals or at target sites that alter the toxicity so that it is more or less than expected from the constituents. Many regulatory and experimental methods for predicting mixture toxicity rely on the use of a concentration addition model so that if interactions occur in mixtures, the risk posed may have been significantly underestimated. This is particularly concerning when considering environmental mixtures which are often highly complex and composed of indeterminate chemicals. Failure to accurately predict the effects chemicals will have if released into the environment, where they can form mixtures, can lead to unexpected detrimental effects on wildlife and ecosystems. The number of confounding factors that may alter the ecotoxicity of a mixture and the accuracy of predictive methods makes risk assessment of environmental mixtures a complex and intimidating task. With this in mind, this review aims show why accurate risk assessment of mixtures is vital by demonstrating the effect they can have on organisms in the environment. Furthermore, it also aims to look at the current challenges facing the assessment of mixture effects and examines future areas of focus that seek to develop methodologies more suitable for environmental mixtures.

AB - In the environment, organisms are exposed to a diverse array of chemicals in complex mixtures. The majority of approaches that aim to assess the risk of environmental chemical mixtures, including those used by regulatory bodies, use toxicity data generated from the individual component chemicals to predict the overall mixture toxicity. It is assumed that the behaviour of chemicals in a mixture can be predicted using the concepts of concentration or dose addition for chemicals with similar mechanisms of action or response addition for dissimilarly acting chemicals. Based on empirical evidence, most traditional risk assessment methods, such as toxic equivalency factors and the hazard index, make the assumption that the components of a mixture adhere to the concentration addition model. Thus, mixture toxicity can be predicted by the summation of the individual component toxicities. However in some mixtures, interactions can occur between chemicals or at target sites that alter the toxicity so that it is more or less than expected from the constituents. Many regulatory and experimental methods for predicting mixture toxicity rely on the use of a concentration addition model so that if interactions occur in mixtures, the risk posed may have been significantly underestimated. This is particularly concerning when considering environmental mixtures which are often highly complex and composed of indeterminate chemicals. Failure to accurately predict the effects chemicals will have if released into the environment, where they can form mixtures, can lead to unexpected detrimental effects on wildlife and ecosystems. The number of confounding factors that may alter the ecotoxicity of a mixture and the accuracy of predictive methods makes risk assessment of environmental mixtures a complex and intimidating task. With this in mind, this review aims show why accurate risk assessment of mixtures is vital by demonstrating the effect they can have on organisms in the environment. Furthermore, it also aims to look at the current challenges facing the assessment of mixture effects and examines future areas of focus that seek to develop methodologies more suitable for environmental mixtures.

U2 - 10.1039/c6ra05406d

DO - 10.1039/c6ra05406d

M3 - Journal article

VL - 2016

SP - 47844

EP - 47857

JO - RSC Advances

JF - RSC Advances

SN - 2046-2069

IS - 53

ER -