Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization

Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose–response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and comp...

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Autores principales:	James P. McCord, Louis C. Groff, II, Jon R. Sobus
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2022
Materias:	Non-targeted analysis Risk characterization Exposure modeling Quantitation Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/92dd7890885a4367bb81c61ba48f0934
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spelling	oai:doaj.org-article:92dd7890885a4367bb81c61ba48f09342021-12-04T04:32:06ZQuantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization0160-412010.1016/j.envint.2021.107011https://doaj.org/article/92dd7890885a4367bb81c61ba48f09342022-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S016041202100636Xhttps://doaj.org/toc/0160-4120Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose–response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and compliance monitoring efforts. Yet, targeted methods have struggled to keep pace with the demands for data regarding the vast, and growing, number of known chemicals. Many contemporary monitoring studies therefore utilize non-targeted analysis (NTA) methods to screen for known chemicals with limited risk information. Qualitative NTA data has enabled identification of previously unknown compounds and characterization of data-poor compounds in support of hazard identification and exposure assessment efforts. In spite of this, NTA data have seen limited use in risk-based decision making due to uncertainties surrounding their quantitative interpretation. Significant efforts have been made in recent years to bridge this quantitative gap. Based on these advancements, quantitative NTA data, when coupled with other high-throughput data streams and predictive models, are poised to directly support 21st-century risk-based decisions. This article highlights components of the chemical risk assessment process that are influenced by NTA data, surveys the existing literature for approaches to derive quantitative estimates of chemicals from NTA measurements, and presents a conceptual framework for incorporating NTA data into contemporary risk assessment frameworks.James P. McCordLouis C. Groff, IIJon R. SobusElsevierarticleNon-targeted analysisRisk characterizationExposure modelingQuantitationEnvironmental sciencesGE1-350ENEnvironment International, Vol 158, Iss , Pp 107011- (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Non-targeted analysis Risk characterization Exposure modeling Quantitation Environmental sciences GE1-350
spellingShingle	Non-targeted analysis Risk characterization Exposure modeling Quantitation Environmental sciences GE1-350 James P. McCord Louis C. Groff, II Jon R. Sobus Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
description	Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose–response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and compliance monitoring efforts. Yet, targeted methods have struggled to keep pace with the demands for data regarding the vast, and growing, number of known chemicals. Many contemporary monitoring studies therefore utilize non-targeted analysis (NTA) methods to screen for known chemicals with limited risk information. Qualitative NTA data has enabled identification of previously unknown compounds and characterization of data-poor compounds in support of hazard identification and exposure assessment efforts. In spite of this, NTA data have seen limited use in risk-based decision making due to uncertainties surrounding their quantitative interpretation. Significant efforts have been made in recent years to bridge this quantitative gap. Based on these advancements, quantitative NTA data, when coupled with other high-throughput data streams and predictive models, are poised to directly support 21st-century risk-based decisions. This article highlights components of the chemical risk assessment process that are influenced by NTA data, surveys the existing literature for approaches to derive quantitative estimates of chemicals from NTA measurements, and presents a conceptual framework for incorporating NTA data into contemporary risk assessment frameworks.
format	article
author	James P. McCord Louis C. Groff, II Jon R. Sobus
author_facet	James P. McCord Louis C. Groff, II Jon R. Sobus
author_sort	James P. McCord
title	Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
title_short	Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
title_full	Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
title_fullStr	Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
title_full_unstemmed	Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
title_sort	quantitative non-targeted analysis: bridging the gap between contaminant discovery and risk characterization
publisher	Elsevier
publishDate	2022
url	https://doaj.org/article/92dd7890885a4367bb81c61ba48f0934
work_keys_str_mv	AT jamespmccord quantitativenontargetedanalysisbridgingthegapbetweencontaminantdiscoveryandriskcharacterization AT louiscgroffii quantitativenontargetedanalysisbridgingthegapbetweencontaminantdiscoveryandriskcharacterization AT jonrsobus quantitativenontargetedanalysisbridgingthegapbetweencontaminantdiscoveryandriskcharacterization
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Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization

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