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Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization
Environment International ( IF 11.8 ) Pub Date : 2021-12-02 , DOI: 10.1016/j.envint.2021.107011
James P McCord 1 , Louis C Groff 2, 3 , Jon R Sobus 2
Affiliation  

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.



中文翻译:

定量非靶向分析:弥合污染物发现与风险表征之间的差距

化学品风险评估遵循一个长期存在的范例,该范例整合了危害、剂量反应和暴露信息,以促进定量风险表征。有针对性的分析测量数据直接支持风险评估活动,以及下游风险管理和合规监控工作。然而,有针对性的方法一直难以跟上对数量庞大且不断增长的已知化学品的数据需求。因此,许多当代监测研究利用非靶向分析 (NTA) 方法来筛选风险信息有限的已知化学品。定性 NTA 数据能够识别以前未知的化合物并表征数据贫乏的化合物,以支持危害识别和暴露评估工作。尽管如此,由于围绕其定量解释的不确定性,NTA 数据在基于风险的决策制定中的使用有限。近年来,为弥合这一数量差距做出了重大努力。基于这些进步,定量 NTA 数据与其他高通量数据流和预测模型相结合,有望直接支持 21 世纪基于风险的决策。本文重点介绍了受 NTA 数据影响的化学品风险评估过程的组成部分,调查了现有文献以了解从 NTA 测量中得出化学品定量估计的方法,并提出了将 NTA 数据纳入当代风险评估框架的概念框架。近年来,为弥合这一数量差距做出了重大努力。基于这些进步,定量 NTA 数据与其他高通量数据流和预测模型相结合,有望直接支持 21 世纪基于风险的决策。本文重点介绍了受 NTA 数据影响的化学品风险评估过程的组成部分,调查了现有文献以了解从 NTA 测量中得出化学品定量估计的方法,并提出了将 NTA 数据纳入当代风险评估框架的概念框架。近年来,为弥合这一数量差距做出了重大努力。基于这些进步,定量 NTA 数据与其他高通量数据流和预测模型相结合,有望直接支持 21 世纪基于风险的决策。本文重点介绍了受 NTA 数据影响的化学品风险评估过程的组成部分,调查了现有文献以了解从 NTA 测量中得出化学品定量估计的方法,并提出了将 NTA 数据纳入当代风险评估框架的概念框架。准备好直接支持 21 世纪基于风险的决策。本文重点介绍了受 NTA 数据影响的化学品风险评估过程的组成部分,调查了现有文献以了解从 NTA 测量中得出化学品定量估计的方法,并提出了将 NTA 数据纳入当代风险评估框架的概念框架。准备好直接支持 21 世纪基于风险的决策。本文重点介绍了受 NTA 数据影响的化学品风险评估过程的组成部分,调查了现有文献以了解从 NTA 测量中得出化学品定量估计的方法,并提出了将 NTA 数据纳入当代风险评估框架的概念框架。

更新日期:2021-12-02
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