Probabilistic approaches for risk assessment and regulatory criteria development: current applications, gaps, and opportunities.
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| Title: | Probabilistic approaches for risk assessment and regulatory criteria development: current applications, gaps, and opportunities. |
|---|---|
| Authors: | Flinders, Camille1 (AUTHOR) cflinders@ncasi.org, Barnhart, Brad2 (AUTHOR), Morrison, Emily B3 (AUTHOR), Anderson, Paul D4 (AUTHOR), Landis, Wayne G5 (AUTHOR) |
| Source: | Integrated Environmental Assessment & Management. Nov2025, Vol. 21 Issue 6, p1281-1292. 12p. |
| Subject Terms: | *Environmental health, Monte Carlo method, Uncertainty (Information theory), Risk management in business, Regulatory compliance, Bayesian analysis, Heterogeneity |
| Abstract: | Traditional ecological and human health risk assessment often relies on deterministic frameworks that preclude the presence of variability or uncertainty among input parameters characterizing exposure, effects, and risk. To promote increased realism and generate more robust risk management decisions, probabilistic risk assessment (PRA) has been introduced as a foundational grouping of techniques that seeks to broadly characterize variability among its components. Although multiple methods exist (e.g., Monte Carlo simulations, Bayesian networks), along with some federal and state regulatory guidance, gaps remain in prescriptive regulatory recommendations for the implementation of PRA methods. This article describes specific probabilistic approaches for risk characterization and assessment, regulatory support of PRA, challenges that may limit more widespread use, and opportunities for its expanded use in regulatory areas where it is not currently applied. Taken together, we hope to advance the understanding of probabilistic methodologies and their versatility for robust, transparent, data-based environmental risk assessment and standards derivation across a range of media that align with regulatory objectives to protect aquatic and terrestrial biota, human health, and vulnerable populations. Key points Probabilistic risk assessment (PRA) is a collection of risk assessment methods that incorporates uncertainty and variability to estimate the likelihood of exposure, risk, or hazard to different segments of an exposed assemblage or population. Although more robust and offering greater transparency than risk estimates based on conservative point estimates, PRA remains underutilized in ecological and human health risk assessment and associated regulatory frameworks. This article, and those in this special series, describe the value and applicability, current barriers and opportunities, and developments necessary to expand the use of PRA in environmental regulation across media and aspects of environmental and human health risk management. [ABSTRACT FROM AUTHOR] |
| Copyright of Integrated Environmental Assessment & Management is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 190282298 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Probabilistic approaches for risk assessment and regulatory criteria development: current applications, gaps, and opportunities. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Flinders%2C+Camille%22">Flinders, Camille</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> cflinders@ncasi.org</i><br /><searchLink fieldCode="AR" term="%22Barnhart%2C+Brad%22">Barnhart, Brad</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Morrison%2C+Emily+B%22">Morrison, Emily B</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Anderson%2C+Paul+D%22">Anderson, Paul D</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Landis%2C+Wayne+G%22">Landis, Wayne G</searchLink><relatesTo>5</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Integrated+Environmental+Assessment+%26+Management%22">Integrated Environmental Assessment & Management</searchLink>. Nov2025, Vol. 21 Issue 6, p1281-1292. 12p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Environmental+health%22">Environmental health</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty+%28Information+theory%29%22">Uncertainty (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+management+in+business%22">Risk management in business</searchLink><br /><searchLink fieldCode="DE" term="%22Regulatory+compliance%22">Regulatory compliance</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+analysis%22">Bayesian analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Heterogeneity%22">Heterogeneity</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Traditional ecological and human health risk assessment often relies on deterministic frameworks that preclude the presence of variability or uncertainty among input parameters characterizing exposure, effects, and risk. To promote increased realism and generate more robust risk management decisions, probabilistic risk assessment (PRA) has been introduced as a foundational grouping of techniques that seeks to broadly characterize variability among its components. Although multiple methods exist (e.g., Monte Carlo simulations, Bayesian networks), along with some federal and state regulatory guidance, gaps remain in prescriptive regulatory recommendations for the implementation of PRA methods. This article describes specific probabilistic approaches for risk characterization and assessment, regulatory support of PRA, challenges that may limit more widespread use, and opportunities for its expanded use in regulatory areas where it is not currently applied. Taken together, we hope to advance the understanding of probabilistic methodologies and their versatility for robust, transparent, data-based environmental risk assessment and standards derivation across a range of media that align with regulatory objectives to protect aquatic and terrestrial biota, human health, and vulnerable populations. Key points   Probabilistic risk assessment (PRA) is a collection of risk assessment methods that incorporates uncertainty and variability to estimate the likelihood of exposure, risk, or hazard to different segments of an exposed assemblage or population. Although more robust and offering greater transparency than risk estimates based on conservative point estimates, PRA remains underutilized in ecological and human health risk assessment and associated regulatory frameworks. This article, and those in this special series, describe the value and applicability, current barriers and opportunities, and developments necessary to expand the use of PRA in environmental regulation across media and aspects of environmental and human health risk management. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Integrated Environmental Assessment & Management is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/inteam/vjaf016 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1281 Subjects: – SubjectFull: Environmental health Type: general – SubjectFull: Monte Carlo method Type: general – SubjectFull: Uncertainty (Information theory) Type: general – SubjectFull: Risk management in business Type: general – SubjectFull: Regulatory compliance Type: general – SubjectFull: Bayesian analysis Type: general – SubjectFull: Heterogeneity Type: general Titles: – TitleFull: Probabilistic approaches for risk assessment and regulatory criteria development: current applications, gaps, and opportunities. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Flinders, Camille – PersonEntity: Name: NameFull: Barnhart, Brad – PersonEntity: Name: NameFull: Morrison, Emily B – PersonEntity: Name: NameFull: Anderson, Paul D – PersonEntity: Name: NameFull: Landis, Wayne G IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 15513777 Numbering: – Type: volume Value: 21 – Type: issue Value: 6 Titles: – TitleFull: Integrated Environmental Assessment & Management Type: main |
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