USEtox—the UNEP-SETAC toxicity model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment
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Background, aim and scope
In 2005, a comprehensive comparison of life cycle impact assessment toxicity characterisation models was initiated by the United Nations Environment Program (UNEP)–Society for Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative, directly involving the model developers of CalTOX, IMPACT 2002, USES-LCA, BETR, EDIP, WATSON and EcoSense. In this paper, we describe this model comparison process and its results—in particular the scientific consensus model developed by the model developers. The main objectives of this effort were (1) to identify specific sources of differences between the models’ results and structure, (2) to detect the indispensable model components and (3) to build a scientific consensus model from them, representing recommended practice.
Materials and methods
A chemical test set of 45 organics covering a wide range of property combinations was selected for this purpose. All models used this set. In three workshops, the model comparison participants identified key fate, exposure and effect issues via comparison of the final characterisation factors and selected intermediate outputs for fate, human exposure and toxic effects for the test set applied to all models.
Through this process, we were able to reduce inter-model variation from an initial range of up to 13 orders of magnitude down to no more than two orders of magnitude for any substance. This led to the development of USEtox, a scientific consensus model that contains only the most influential model elements. These were, for example, process formulations accounting for intermittent rain, defining a closed or open system environment or nesting an urban box in a continental box.
The precision of the new characterisation factors (CFs) is within a factor of 100–1,000 for human health and 10–100 for freshwater ecotoxicity of all other models compared to 12 orders of magnitude variation between the CFs of each model, respectively. The achieved reduction of inter-model variability by up to 11 orders of magnitude is a significant improvement.
USEtox provides a parsimonious and transparent tool for human health and ecosystem CF estimates. Based on a referenced database, it has now been used to calculate CFs for several thousand substances and forms the basis of the recommendations from UNEP-SETAC’s Life Cycle Initiative regarding characterisation of toxic impacts in life cycle assessment.
Recommendations and perspectives
We provide both recommended and interim (not recommended and to be used with caution) characterisation factors for human health and freshwater ecotoxicity impacts. After a process of consensus building among stakeholders on a broad scale as well as several improvements regarding a wider and easier applicability of the model, USEtox will become available to practitioners for the calculation of further CFs.
KeywordsCharacterisation factors Characterisation modelling Comparative impact assessment Comparison Consensus model Freshwater ecotoxicity Harmonisation Human exposure Human toxicity LCIA Life cycle impact assessment Toxic impact
Most of the work for this project was carried out on a voluntary basis and financed by in-kind contributions from the authors’ home institutions which are therefore gratefully acknowledged. The work was performed under the auspices of the UNEP-SETAC Life Cycle Initiative which also provided logistic and financial support and facilitated stakeholder consultations. The financial support from ACC (American Chemical Council) and ICMM (International Council on Mining and Metals) is also gratefully acknowledged. A number of persons have contributed to the process and success of the model comparison and scientific consensus model development. The authors are grateful for the participation of Miriam Diamond, Louise Deschênes, Bill Adams, Andrea Russel, Jeroen Guinée, Pierre-Yves Robidoux, Stefanie Hellweg, Evangelia Demou, Stig Irving Olsen, Cécile Bulle, Sau Soon Chen, Manuel Olivera, Julian Marshall, Bert-Droste Franke, Peter Fantke, Oleg Travnikov, Dick de Zwart, Peter Chapman, Kees van Gestel and Thomas H. Slone.
- Bachmann TM (2006) Hazardous substances and human health: exposure, impact and external cost assessment at the European scale. Trace metals and other contaminants in the environment, 8. Elsevier, Amsterdam, p 570Google Scholar
- Cowan CE, Mackay D, Feijtel TCJ, van de Meent D, Di Guardo A, Davies J, Mackay N (eds) (1994) The multi-media fate model: a vital tool for predicting the fate of chemicals. SETAC. SETAC Press, Denver, COGoogle Scholar
- EC (1999) Externalities of fuel cycles—ExternE Project. Vol. 7—methodology, 2nd edn. European Commission DG XII, Science Research and Development, JOULE, Brussels, LuxembourgGoogle Scholar
- EC (2003) Technical guidance document on risk assessment in Support of Commission Directive 93/67/EEC on Risk Assessment for new notified substances. Commission Regulation (EC) no. 1488/94 on risk assessment for existing substances. Directive 98/8/EC of the European Parliament and of the Council concerning the placing of biocidal products on the market—part I, Institute for Health and Consumer Protection, European Chemicals Bureau, European Joint Research Centre (JRC) Ispra, ItalyGoogle Scholar
- EC (2005) ExternE—externalities of energy: Methodology 2005 update. Office for Official Publication of the European Communities, LuxembourgGoogle Scholar
- ECOTOX (2001) ECOTOXicology Database system. http://www.epa.gov/ecotox
- Fenner K, Scheringer M, Stroebe M, Macleod M, McKone T, Matthies M, Klasmeier J, Beyer A, Bonnell M, Le Gall AC, Mackay D, Van De Meent D, Pennington D, Scharenberg B, Suzuki N, Wania F (2005) Comparing estimates of persistence and long-range transport potential among multimedia models. Environ Sci Technol 39(7):1932CrossRefGoogle Scholar
- Gold LS, Manley NB, Slone TH, Rohrbach L, Backman-Garfinkel G (2005) Supplement to the carcinogenic potency database (CPDB) Results of animal bioassays published in the general literature through 1997 and by the National Toxicology Program in 1997–1998. Toxicol Sci 85(2):747–808CrossRefGoogle Scholar
- Gold LS et al (2008) The carcinogenic potency database (CPDB). http://potency.berkeley.edu/chemicalsummary.html
- Hauschild M, Wenzel H (1998) Environmental assessment of products, vol 2: scientific background. Kluwer, Hingham, MA, USA, p 565Google Scholar
- Heijungs R, Guinée JB, Huppes G, Lankreijer RM, Udo de Haes HA, Wegner Sleeswijk A, Ansems AMM, Eggels PG, van Duin R, Goede AP (1992) Environmental life cycle assessment of products. Centre of Environmental Sciences, Leiden, The NetherlandsGoogle Scholar
- Howard PH, Meylan WM (eds) (1997) Handbook of physical properties of organic chemicals. Lewis Publishers (CRC Press cop), Michigan, 1585 ppGoogle Scholar
- Howard PH, Boethling RS, Jarvis WF, Meylan WM, Michalenko EM (1991) Handbook of environmental degradation rates. Lewis Publishers, MichiganGoogle Scholar
- Huijbregts MAJ, Thissen U, Guinée JB, Jager T, Kalf D, van de Meent D, Ragas AMJ, Wegener Sleeswijk A, Reijnders L (2000) Priority assessment of toxic substances in life cycle assessment. Part I: calculation of toxicity potentials for 181 substances with the nested multi-media fate, exposure and effects model USES-LCA. Chemosphere 41(4):541–573CrossRefGoogle Scholar
- Huijbregts MAJ, Geelen LMJ, Van De Meent D, Hertwich EG, McKone TE (2005a) A comparison between the multimedia fate and exposure models CalTOX and uniform system for evaluation of substances adapted for life-cycle assessment based on the population intake fraction of toxic pollutants. Environ Toxicol Chem 24(2):486–493CrossRefGoogle Scholar
- IUCLID (2000) IUCLID CD-ROM Year 2000 edition. Public data on high volume chemicalsGoogle Scholar
- Jolliet O, Brent A, Goedkoop M, Itsubo N, Mueller-Wenk R, Peña C, Schenk R, Stewart M, Weidema B (2003a) The LCIA Framework. SETAC–UNEP Life Cycle Initiative, LausanneGoogle Scholar
- Ligthart T et al (2004) Declaration of Apeldoorn on LCIA of Non-Ferrous Metals. http://lcinitiative.unep.fr/includes/file.asp?site=lcinit&file=38D1F49D-6D64-45AE-9F64-578BA414E499
- Mackay D, Seth R (1999) The role of mass balance modelling in impact assessment and pollution prevention. In: Sikdar SK, Diweakar U (eds) Tools and methods for pollution prevention. Kluwer, The Netherlands, pp 157–179Google Scholar
- Mackay D, Shiu WY, Lee SC, Ma KC (2006) Handbook of physical–chemical properties and environmental fate for organic chemicals. Science, Technology, Engineering, I–IV. CRC, Boca RatonGoogle Scholar
- Margni M (2003) Source to intake modeling in life cycle impact assessment. PhD thesis, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 138 ppGoogle Scholar
- Margni M, Pennington DW, Birkved M, Larsen HF, Hauschild M (2002) Test set of organic chemicals for LCIA characterisation method comparison. OMNITOX project reportGoogle Scholar
- McKone TE (2001) Ecological toxicity potentials (ETPs) for substances released to air and surface waters. Environmental Health Sciences Division, School of Public Health, University of California, Berkeley, CA 94720Google Scholar
- McKone T, Bennett D, Maddalena R (2001) CalTOX 4.0 Technical support document, vol 1. LBNL-47254, Lawrence Berkeley National Laboratory, Berkeley, CAGoogle Scholar
- NCMS (2008) SOLV-DB. http://solvdb.ncms.org/index.html
- Pant R, Van Hoof G, Schowanek D, Feijtel TCJ, De Koning A, Hauschild M, Olsen SI, Pennington DW, Rosenbaum RK (2004) Comparison between three different LCIA methods for aquatic ecotoxicity and a product environmental risk assessment: insights from a detergent case study within OMNIITOX. Int J Life Cycle Assess 9(5):295–306CrossRefGoogle Scholar
- Payet J (2004) Assessing toxic impacts on aquatic ecosystems in life cycle assessment (LCA). PhD thesis, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 190 ppGoogle Scholar
- Rosenbaum RK (2006) Multimedia and food chain modelling of toxics for comparative risk and life cycle impact assessment. PhD thesis, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 192 ppGoogle Scholar
- SRC (2008) Environmental Fate Data Base (EFDB). http://www.syrres.com/esc/efdb.htm
- Stroebe M, Scheringer M, Hungerbühler K, Held H (2004) Inter-comparison of multimedia modeling approaches: modes of transport, measures of long range transport potential and the spatial remote state. Sci Total Environ 321(1–3):1–20Google Scholar
- USEPA (2007) Estimation Programs Interface EPI Suite. http://www.epa.gov/opptintr/exposure/pubs/episuite.htm
- Vermeire T, Pieters M, Rennen M, Bos P (2001) Probabalistic assessment factors for human health risk assessment—a practical guide. National Institute for Health and the Environment, Bilthoven, The NetherlandsGoogle Scholar
- Wania F, MacKay D (2000) A comparison of overall persistence values and atmospheric travel distances calculated by various multi-media fate models. WECC Wania Environmental Chemists Corp., under Chlorine Chemistry Council Contracts No. 9461 and 9462, Toronto, Ontario, CanadaGoogle Scholar
- Wegmann F, Cavin L, MacLeod M, Scheringer M, Hungerbühler K (2008) A software tool for screening chemicals of environmental concern for persistence and long-range transport potential. Environ Model Softw 24(2):228–237 http://dx.doi.org/10.1016/j.envsoft.2008.06.014
- Wenzel H, Hauschild M, Alting L (1998) Environmental assessment of products, vol 1: methodology, tools and case studies in product development. Kluwer, Hingham, MA, USA, p 560Google Scholar