Exposure and Toxicity Characterization of Chemical Emissions and Chemicals in Products: Global Recommendations and Implementation in USEtox.

Life cycle impact assessment characterization factors chemical toxicity dose-response modelling global guidance human toxicity impacts near-field exposure

Journal

The international journal of life cycle assessment
ISSN: 0948-3349
Titre abrégé: Int J Life Cycle Assess
Pays: Germany
ID NLM: 101659490

Informations de publication

Date de publication:
May 2021
Historique:
entrez: 18 6 2021
pubmed: 19 6 2021
medline: 19 6 2021
Statut: ppublish

Résumé

Reducing chemical pressure on human and environmental health is an integral part of the global sustainability agenda. Guidelines for deriving globally applicable, life cycle based indicators are required to consistently quantify toxicity impacts from chemical emissions as well as from chemicals in consumer products. In response, we elaborate the methodological framework and present recommendations for advancing near-field/far-field exposure and toxicity characterization, and for implementing these recommendations in the scientific consensus model USEtox. An expert taskforce was convened by the Life Cycle Initiative hosted by UN Environment to expand existing guidance for evaluating human toxicity impacts from exposure to chemical substances. This taskforce evaluated advances since the original release of USEtox. Based on these advances, the taskforce identified two major aspects that required refinement, namely integrating near-field and far-field exposure and improving human dose-response modeling. Dedicated efforts have led to a set of recommendations to address these aspects in an update of USEtox, while ensuring consistency with the boundary conditions for characterizing life cycle toxicity impacts and being aligned with recommendations from agencies that regulate chemical exposure. The proposed framework was finally tested in an illustrative rice production and consumption case study. On the exposure side, a matrix system is proposed and recommended to integrate far-field exposure from environmental emissions with near-field exposure from chemicals in various consumer product types. Consumer exposure is addressed via submodels for each product type to account for product characteristics and exposure settings. Case study results illustrate that product-use related exposure dominates overall life cycle exposure. On the effect side, a probabilistic dose-response approach combined with a decision tree for identifying reliable points of departure is proposed for non-cancer effects, following recent guidance from the World Health Organization. This approach allows for explicitly considering both uncertainty and human variability in effect factors. Factors reflecting disease severity are proposed to distinguish cancer from non-cancer effects, and within the latter discriminate reproductive/developmental and other non-cancer effects. All proposed aspects have been consistently implemented into the original USEtox framework. The recommended methodological advancements address several key limitations in earlier approaches. Next steps are to test the new characterization framework in additional case studies and to close remaining research gaps. Our framework is applicable for evaluating chemical emissions and product-related exposure in life cycle assessment, chemical alternatives assessment and chemical substitution, consumer exposure and risk screening, and high-throughput chemical prioritization.

Identifiants

pubmed: 34140756
doi: 10.1007/s11367-021-01889-y
pmc: PMC8208704
mid: NIHMS1704857
doi:

Types de publication

Journal Article

Langues

eng

Pagination

899-915

Subventions

Organisme : NIEHS NIH HHS
ID : P42 ES027704
Pays : United States

Références

Food Chem Toxicol. 2017 Nov;109(Pt 1):428-438
pubmed: 28939300
Environ Health Perspect. 2018 May 29;126(5):057008
pubmed: 29847084
Lancet Glob Health. 2015 Nov;3(11):e712-23
pubmed: 26475018
Environ Health Perspect. 2018 Dec;126(12):125001
pubmed: 30540492
Environ Toxicol Chem. 2017 Dec;36(12):3463-3470
pubmed: 28671290
J Clean Prod. 2017 Sep 10;161:957-967
pubmed: 32461713
Environ Health Perspect. 2013 Jan;121(1):23-31
pubmed: 23086705
Chemosphere. 2016 Nov;163:490-498
pubmed: 27565317
Environ Sci Technol. 2019 Jan 15;53(2):719-732
pubmed: 30516957
Environ Int. 2020 May;138:105642
pubmed: 32179322
Environ Sci Technol. 2017 Aug 15;51(16):9089-9100
pubmed: 28682605
Environ Sci Technol. 2020 May 19;54(10):6224-6234
pubmed: 32364377
Environ Sci Technol. 2019 Jun 18;53(12):6855-6868
pubmed: 31132267
Environ Sci Technol. 2015 Aug 4;49(15):8924-31
pubmed: 26102159
Environ Int. 2021 Jan;146:106194
pubmed: 33115697
Int J Life Cycle Assess. 2019 Jun 1;24(6):1009-1026
pubmed: 32632341
J Expo Sci Environ Epidemiol. 2017 Mar;27(2):152-159
pubmed: 26758569
Environ Sci Technol. 2004 Oct 15;38(20):5450-7
pubmed: 15543750
Environ Sci Technol. 2008 Oct 1;42(19):7032-7
pubmed: 18939523
Environ Int. 2020 Feb;135:105336
pubmed: 31884133
Sci Total Environ. 2017 Jan 1;574:1182-1208
pubmed: 27644856
Environ Sci Technol. 2015 Jun 2;49(11):6760-71
pubmed: 25932772
Risk Anal. 2021 Apr;41(4):627-644
pubmed: 33073419
Environ Int. 2016 Jul-Aug;92-93:87-96
pubmed: 27062422
Environ Toxicol Chem. 2017 Dec;36(12):3450-3462
pubmed: 28618056
Environ Health Perspect. 2015 Dec;123(12):1241-54
pubmed: 26006063
Integr Environ Assess Manag. 2005 Jul;1(3):181-244
pubmed: 16639884
Environ Int. 2016 Sep;94:508-518
pubmed: 27318619
Waste Manag Res. 2001 Jun;19(3):201-16
pubmed: 11699855
Environ Health Perspect. 2018 Jun 28;126(6):067009
pubmed: 29968566
Lancet. 2018 Nov 10;392(10159):1923-1994
pubmed: 30496105
Environ Sci Technol. 2015 Nov 3;49(21):12823-31
pubmed: 26444519
Lancet. 2017 Sep 16;390(10100):1260-1344
pubmed: 28919118
Indoor Air. 2016 Dec;26(6):836-856
pubmed: 26562829
Environ Health Perspect. 2014 May;122(5):499-505
pubmed: 24569956
Environ Toxicol Chem. 2018 Dec;37(12):2955-2971
pubmed: 30178491

Auteurs

Peter Fantke (P)

Quantitative Sustainability Assessment, Department of Technology, Management and Economics, Technical University of Denmark, Produktionstorvet 424, 2800 Kgs. Lyngby, Denmark.

Weihsueh A Chiu (WA)

Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.

Lesa Aylward (L)

Queensland Alliance for Environmental Health Sciences, University of Queensland, Brisbane, Australia.

Richard Judson (R)

National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.

Lei Huang (L)

Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, USA.

Suji Jang (S)

Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.

Todd Gouin (T)

TG Environmental Research, Sharnbrook, MK44 1PL, UK.

Lorenz Rhomberg (L)

Gradient, Boston, Massachusetts 02108, USA.

Nicolò Aurisano (N)

Quantitative Sustainability Assessment, Department of Technology, Management and Economics, Technical University of Denmark, Produktionstorvet 424, 2800 Kgs. Lyngby, Denmark.

Thomas McKone (T)

School of Public Health, University of California, Berkeley, California 94720, USA.

Olivier Jolliet (O)

Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, USA.

Classifications MeSH