Probabilistic Risk Assessment Approaches Better Protect Susceptible Populations.

IF 8.4 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Jayme Coyle, Bradley Barnhart, Raymond Harbison, Kan Shao, A Wallace Hayes, Giffe Johnson
{"title":"Probabilistic Risk Assessment Approaches Better Protect Susceptible Populations.","authors":"Jayme Coyle, Bradley Barnhart, Raymond Harbison, Kan Shao, A Wallace Hayes, Giffe Johnson","doi":"10.1093/inteam/vjaf101","DOIUrl":null,"url":null,"abstract":"<p><p>Across all of its program areas, the United States Environmental Protection Agency conducts risk assessments to evaluate the potential adverse effects of environmental hazards on ecological and human health. Traditionally, these assessments rely on deterministic methods that use point estimates for key parameters and incorporate uncertainty factors and precautionary assumptions to account for uncertainties in data and variability in environmental conditions, exposure pathways, and population characteristics. However, these approaches are unnecessarily conservative for the general population yet fail to transparently account for the vulnerabilities of susceptible populations. Probabilistic risk assessment (PRA) offers a more refined approach that utilizes distributional data to better characterize uncertainty and response. By leveraging empirical data and probabilistic modeling, PRA allows for a more transparent, precise quantification of risk that ensures targeted protection for susceptible populations. This article examines how PRA enhances each phase of risk assessment-hazard identification, dose-response assessment, exposure assessment, and risk characterization-to produce a more scientifically robust assessment of risk for susceptible populations, including both human and ecological receptors. We review the literature and discuss practical applications of PRA in regulatory contexts to illustrate its advantages over deterministic approaches. Finally, we discuss key implementation challenges and propose future research directions to advance risk assessment methodologies and improve policy decision-making.</p>","PeriodicalId":13557,"journal":{"name":"Integrated Environmental Assessment and Management","volume":" ","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrated Environmental Assessment and Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1093/inteam/vjaf101","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Across all of its program areas, the United States Environmental Protection Agency conducts risk assessments to evaluate the potential adverse effects of environmental hazards on ecological and human health. Traditionally, these assessments rely on deterministic methods that use point estimates for key parameters and incorporate uncertainty factors and precautionary assumptions to account for uncertainties in data and variability in environmental conditions, exposure pathways, and population characteristics. However, these approaches are unnecessarily conservative for the general population yet fail to transparently account for the vulnerabilities of susceptible populations. Probabilistic risk assessment (PRA) offers a more refined approach that utilizes distributional data to better characterize uncertainty and response. By leveraging empirical data and probabilistic modeling, PRA allows for a more transparent, precise quantification of risk that ensures targeted protection for susceptible populations. This article examines how PRA enhances each phase of risk assessment-hazard identification, dose-response assessment, exposure assessment, and risk characterization-to produce a more scientifically robust assessment of risk for susceptible populations, including both human and ecological receptors. We review the literature and discuss practical applications of PRA in regulatory contexts to illustrate its advantages over deterministic approaches. Finally, we discuss key implementation challenges and propose future research directions to advance risk assessment methodologies and improve policy decision-making.

概率风险评估方法更好地保护易感人群。
美国环境保护局在其所有方案领域开展风险评估,以评估环境危害对生态和人类健康的潜在不利影响。传统上,这些评估依赖于确定性方法,对关键参数使用点估计,并纳入不确定性因素和预防性假设,以解释数据的不确定性以及环境条件、暴露途径和人口特征的可变性。然而,这些方法对一般人群来说是不必要的保守,但未能透明地考虑到易感人群的脆弱性。概率风险评估(PRA)提供了一种更精细的方法,利用分布数据更好地表征不确定性和响应。通过利用经验数据和概率模型,PRA允许更透明、更精确的风险量化,确保对易感人群提供有针对性的保护。本文探讨了PRA如何加强风险评估的每个阶段——危害识别、剂量-反应评估、暴露评估和风险表征——以对易感人群(包括人类和生态受体)产生更科学可靠的风险评估。我们回顾文献并讨论PRA在监管背景下的实际应用,以说明其优于确定性方法的优势。最后,我们讨论了关键的实施挑战,并提出了未来的研究方向,以推进风险评估方法和改善政策决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Integrated Environmental Assessment and Management
Integrated Environmental Assessment and Management ENVIRONMENTAL SCIENCESTOXICOLOGY&nbs-TOXICOLOGY
CiteScore
5.90
自引率
6.50%
发文量
156
期刊介绍: Integrated Environmental Assessment and Management (IEAM) publishes the science underpinning environmental decision making and problem solving. Papers submitted to IEAM must link science and technical innovations to vexing regional or global environmental issues in one or more of the following core areas: Science-informed regulation, policy, and decision making Health and ecological risk and impact assessment Restoration and management of damaged ecosystems Sustaining ecosystems Managing large-scale environmental change Papers published in these broad fields of study are connected by an array of interdisciplinary engineering, management, and scientific themes, which collectively reflect the interconnectedness of the scientific, social, and environmental challenges facing our modern global society: Methods for environmental quality assessment; forecasting across a number of ecosystem uses and challenges (systems-based, cost-benefit, ecosystem services, etc.); measuring or predicting ecosystem change and adaptation Approaches that connect policy and management tools; harmonize national and international environmental regulation; merge human well-being with ecological management; develop and sustain the function of ecosystems; conceptualize, model and apply concepts of spatial and regional sustainability Assessment and management frameworks that incorporate conservation, life cycle, restoration, and sustainability; considerations for climate-induced adaptation, change and consequences, and vulnerability Environmental management applications using risk-based approaches; considerations for protecting and fostering biodiversity, as well as enhancement or protection of ecosystem services and resiliency.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信