USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties

  • Ralph K. RosenbaumEmail author
  • Mark A. J. Huijbregts
  • Andrew D. Henderson
  • Manuele Margni
  • Thomas E. McKone
  • Dik van de Meent
  • Michael Z. Hauschild
  • Shanna Shaked
  • Ding Sheng Li
  • Lois S. Gold
  • Olivier Jolliet



The aim of this paper is to provide science-based consensus and guidance for health effects modelling in comparative assessments based on human exposure and toxicity. This aim is achieved by (a) describing the USEtox™ exposure and toxicity models representing consensus and recommended modelling practice, (b) identifying key mechanisms influencing human exposure and toxicity effects of chemical emissions, (c) extending substance coverage.


The methods section of this paper contains a detailed documentation of both the human exposure and toxic effects models of USEtox™, to determine impacts on human health per kilogram substance emitted in different compartments. These are considered as scientific consensus and therefore recommended practice for comparative toxic impact assessment. The framework of the exposure model is described in details including the modelling of each exposure pathway considered (i.e. inhalation through air, ingestion through (a) drinking water, (b) agricultural produce, (c) meat and milk, and (d) fish). The calculation of human health effect factors for cancer and non-cancer effects via ingestion and inhalation exposure respectively is described. This section also includes discussions regarding parameterisation and estimation of input data needed, including route-to-route and acute-to-chronic extrapolations.

Results and discussion

For most chemicals in USEtox™, inhalation, above-ground agricultural produce, and fish are the important exposure pathways with key driving factors being the compartment and place of emission, partitioning, degradation, bioaccumulation and bioconcentration, and dietary habits of the population. For inhalation, the population density is the key factor driving the intake, thus the importance to differentiate emissions in urban areas, except for very persistent and mobile chemicals that are taken in by the global population independently from their place of emission. The analysis of carcinogenic potency (TD50) when volatile chemicals are administrated to rats and mice by both inhalation and an oral route suggests that results by one route can reasonably be used to represent another route. However, we first identify and mark as interim chemicals for which observed tumours are directly related to a given exposure route (e.g. for nasal or lung, or gastrointestinal cancers) or for which absorbed fraction by inhalation and by oral route differ greatly.


A documentation of the human exposure and toxicity models of USEtox™ is provided, and key factors driving the human health characterisation factor are identified. Approaches are proposed to derive human toxic effect factors and expand the number of chemicals in USEtox™, primarily by extrapolating from an oral route to exposure in air (and optionally acute-to-chronic). Some exposure pathways (e.g. indoor inhalation, pesticide residues, dermal exposure) will be included in a later stage. USEtox™ is applicable in various comparative toxicity impact assessments and not limited to LCA.


Consensus Human exposure Human health LCIA Life cycle impact assessment Toxicity USEtox 



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 for the USEtox™ consortium from ACC (American Chemical Council) and ICMM (International Council on Mining and Metals) is also gratefully acknowledged.

Supplementary material

11367_2011_316_MOESM1_ESM.doc (5.7 mb)
ESM 1 (DOC 5.67 mb)


  1. Arnot JA, Gobas FAPC (2003) A generic QSAR for assessing the bioaccumulation potential of organic chemicals in aquatic food webs. QSAR Comb Sci 22:337–345CrossRefGoogle Scholar
  2. Assies JA (1997) Risk indicators for use in life-cycle impact assessment: An approach based on sustainability. Center for Energy and Environmental Studies (IVEM), University of Groningen, NetherlandsGoogle Scholar
  3. Barnthouse LW, Fava JA, Humphreys K, Hunt R, Laibson L, Noesen S, Norris GA, Owens JW, Todd J, Vigon B, Weitz K, Young JS (1997) Life-cycle impact assessment: the state of the art, 2nd edn. SETAC, Pensacola (FL), USAGoogle Scholar
  4. Bennett DH, Margni M, McKone TE, Jolliet O (2002a) Intake fraction for multimedia pollutants: a tool for life cycle analysis and comparative risk assessment. Risk Anal 22(5):903–916CrossRefGoogle Scholar
  5. Bennett DH, McKone TE, Evans JS, Nazaroff WW, Margni MD, Jolliet O, Smith KR (2002b) Defining intake fraction. Environ Sci Technol 36(9):207A–211ACrossRefGoogle Scholar
  6. Bernstein L, Gold LS, Ames BN, Pike MC, Hoel DG (1985a) Letter to the editor: toxicity and carcinogenic potency. Risk Anal 5:263–264CrossRefGoogle Scholar
  7. Bernstein L, Gold LS, Ames BN, Pike MC, Hoel DG (1985b) Some tautologous aspects of the comparison of carcinogenic potency in rats and mice. Fundam Appl Toxicol 5:79–86CrossRefGoogle Scholar
  8. Birak P, Yurk J, Adeshina F, Lorber M, Pollard K, Choudhury H, Kroner S (2001) Travis and arms revisited: a second look at a widely used bioconcentration algorithm. Toxicol Ind Health 17(5–10):163–175CrossRefGoogle Scholar
  9. Chiu WA, White P (2006) Steady-state solutions to PBPK models and their applications to risk assessment I: route-to-route extrapolation of volatile chemicals. Risk Anal 26(3):769–780CrossRefGoogle Scholar
  10. Cox LA, Ricci PF (eds) (1990) New risks: issues and management. SpringerGoogle Scholar
  11. Crettaz P, Pennington D, Rhomberg L, Brand B, Jolliet O (2002) Assessing human health response in life cycle assessment using ED10s and DALYs: part 1-cancer effects. Risk Anal 22(5):931–946CrossRefGoogle Scholar
  12. Czub G, McLachlan MS (2004) A food chain model to predict the levels of lipophilic organic contaminants in humans. Environ Toxicol Chem 23(10):2356–2366CrossRefGoogle Scholar
  13. Dowdy D, McKone TE, Hsieh DPH (1996) The use of the molecular connectivity index for estimating biotransfer factors. Environ Sci Technol 30:984–989CrossRefGoogle Scholar
  14. Dreyer LC, Niemann AL, Hauschild MZ (2003) Comparison of three different LCIA methods: EDIP97, CML2001 and eco-indicator 99: does it matter which one you choose? Int J Life Cycle Assess 8(4):191–200CrossRefGoogle Scholar
  15. 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
  16. FAO (2002) FAO Statistical Databases (FAOSTAT) Food and Agriculture Organization of the United Nations.
  17. Franco A, Prevedouros K, Alli R, Cousins IT (2007) Comparison and analysis of different approaches for estimating the human exposure to phthalate esters. Environ Int 33:283–291CrossRefGoogle Scholar
  18. Franco A, Trapp S (2010) A multimedia activity model for ionizable compounds: validation study with 2,4-dichlorophenoxyacetic acid, aniline and trimethoprim. Environ Toxicol Chem 4:789–799CrossRefGoogle Scholar
  19. Goedkoop M, Müller-Wenk R, Hofstetter P, Spriensma R (1998) The eco-indicator 99 explained. Int J Life Cycle Assess 3(6):352–360CrossRefGoogle Scholar
  20. Gold LS (2011) The Carcinogenic Potency Project and Database (CPDB) University of California, Berkeley; Lawrence Berkeley National Laboratory; National Library of Medicine’s (NLM®).
  21. Gold LS, Slone TH, Bernstein L (1989) Summary of carcinogenic potency and positivity for 492 rodent carcinogens in the carcinogenic potency database. Environ Health Perspect 79:259–272CrossRefGoogle Scholar
  22. Guinée J, Heijungs R (1993) A proposal for the classification of toxic substances within the framework of life cycle assessment of products. Chemosphere 26(10):1925–1944CrossRefGoogle Scholar
  23. Guinée JB, De Koning A, Pennington DW, Rosenbaum RK, Hauschild M, Olsen SI, Molander S, Bachmann TM, Pant R (2004) Bringing science and pragmatism together: a tiered approach for modelling toxicological impacts in LCA. Int J Life Cycle Assess 9(5):320CrossRefGoogle Scholar
  24. Hauschild MZ, Huijbregts MAJ, Jolliet O, MacLeod M, Margni M, Van de Meent D, Rosenbaum RK, McKone TE (2008) Building a model based on scientific consensus for life cycle impact assessment of chemicals: the search for harmony and parsimony. Environ Sci Technol 42(19):7032–7037CrossRefGoogle Scholar
  25. Heijungs R (1995) Harmonization of methods for impact assessment. Environ Sci Pollut Res 2(4):217–224CrossRefGoogle Scholar
  26. Henderson A, Hauschild M, Van de Meent D, Huijbregts MAJ, Larsen HF, Margni M, McKone TE, Payet J, Rosenbaum RK, Jolliet O (2011) USEtox fate and ecotoxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties. Int J Life Cycle Assess. doi: 10.1007/s11367-011-0294-6
  27. Hendriks AJ, Smitkova H, Huijbregts MAJ (2007) A new twist on an old regression: transfer of chemicals to beef and milk in human and ecological risk assessment. Chemosphere 70(1):46–56CrossRefGoogle Scholar
  28. Hertwich E, Matales SF, Pease WS, McKone TE (2001) Human toxicity potentials for life-cycle assessment and toxics release inventory risk screening. Environ Toxicol Chem 20(4):928–939CrossRefGoogle Scholar
  29. Hogan L, Beal R, Hunt R (1996) Threshold inventory interpretation methodology: a case study of three juice container systems. Int J Life Cycle Assess 1:159–167CrossRefGoogle Scholar
  30. Huijbregts MAJ, Rombouts LJA, Ragas AMJ, Van de Meent D (2005) Human-toxicological effect and damage factors of carcinogenic and noncarcinogenic chemicals for life cycle impact assessment. Integr Environ Assess Manage 1(3):181–192CrossRefGoogle Scholar
  31. 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
  32. Humbert S, Marshall JD, Shaked S, Spadaro JV, Nishioka Y, Preiss P, McKone TE, Horvath A, Jolliet O (2011) Intake fractions for particulate matter: recommendations for life cycle assessment. Environ Sci Technol 45(11):4808–4816CrossRefGoogle Scholar
  33. ISO (2006) ISO 14040 International Standard. Environmental management—life cycle assessment—principles and framework. International Organisation for Standardization, Geneva, SwitzerlandGoogle Scholar
  34. JMPR (2004) Joint Meeting on Pesticide Residues. Monographs and evaluations Accessed 17–23 May 2004
  35. Jolliet O, Margni M, Charles R, Humbert S, Payet J, Rebitzer G, Rosenbaum RK (2003) IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Assess 8(6):324–330CrossRefGoogle Scholar
  36. Jolliet O, Pennington D, Rebitzer G, Müller-Wenk R, Bare J, Brent A, Goedkoop M, Heijungs R, De Haes HU, Itsubo N, Peña C, Potting J, Stewart M, Weidema B (2004) The LCIA midpoint-damage framework of the UNEP/SETAC life cycle initiative. Int J Life Cycle Assess 9(6):394–404CrossRefGoogle Scholar
  37. Jolliet O, Rosenbaum RK, Chapmann P, McKone T, Margni M, Scheringer M, van Straalen N, Wania F (2006) Establishing a framework for life cycle toxicity assessment: findings of the Lausanne review workshop. Int J Life Cycle Assess 11(3):209–212CrossRefGoogle Scholar
  38. Juraske R, Anton A, Castells F (2008) Estimating half-lives of pesticides in/on vegetation for use in multimedia fate and exposure models. Chemosphere 70:1748–1755CrossRefGoogle Scholar
  39. Kramer HJ, van den Ham WA, Slob W, Pieters MN (1996) Conversion factors estimating indicative chronic no-observed-adverse-effect levels from short-term toxicity data. Regul Toxicol Pharm 23(3):249–255CrossRefGoogle Scholar
  40. Ligthart T, Aboussouan L, Van de Meent D, Schönnenbeck M, Hauschild M, Delbeke K, Struijs J, Russel A, Udo de Haes H, Atherton J, van Tilborg W, Karman C, Korenromp R, Sap G, Baukloh A, Dubreuil A, Adams W, Heijungs R, Jolliet O, De Koning A, Chapmann P, Verdonck F, van der Loos R, Eikelboom R, Kuyper J (2004) Declaration of Apeldoorn on LCIA of Non-Ferrous Metals.
  41. Lu FC (1995) A review of the acceptable daily intakes of pesticides assessed by WHO. Regul Toxicol Pharm 21:352–364CrossRefGoogle Scholar
  42. Mackay D, Seth R (1999) The Role of Mass Balance Modelling in Impact Assessment and Pollution Prevention. In: Sikdar SK, Diwekar U (eds) Tools and methods for pollution prevention. Kluwer, The Netherlands, pp 157–179Google Scholar
  43. Margni M (2003) Source to intake modeling in life cycle impact assessment. Ph.D, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, SwitzerlandGoogle Scholar
  44. McKone T, Bennett D, Maddalena R (2001) CalTOX 4.0 technical support document, Vol. 1. Lawrence Berkeley National Laboratory, Berkeley, CAGoogle Scholar
  45. McKone TE (2001) Ecological toxicity potentials (ETPs) for substances released to air and surface waters. School of Public Health, University of California, Berkeley, CA, Environmental Health Sciences Division, 94720Google Scholar
  46. McKone TE, Kyle AD, Jolliet O, Olsen SI, Hauschild M (2006) Dose–response modeling for life cycle impact assessment—findings of the Portland review workshop. Int J Life Cycle Assess 11(2):137–140CrossRefGoogle Scholar
  47. Molander S, Lidholm P, Schowanek D, Recasens M, Fullana I, Palmer P, Christensen FM, Guinée JB, Hauschild M, Jolliet O, Pennington DW, Carlson R, Bachmann TM (2004) OMNIITOX—operational life-cycle impact assessment models and information tools for practitioners. Int J Life Cycle Assess 9(5):282–288CrossRefGoogle Scholar
  48. Moser GA, McLachlan MS (2002) Modeling digestive tract absorption and desorption of lipophilic organic contaminants in humans. Environ Sci Technol 36(15):3318–3325CrossRefGoogle Scholar
  49. NLM (2011) Hazardous Substances Data Bank (HSDB®) National Library of Medicine’s (NLM) Toxicology Data Network (TOXNET®).
  50. Olsen SI, Christensen FM, Hauschild M, Pedersen F, Larsen HF, Tørsløv J (2001) Life cycle impact assessment and risk assessment of chemicals—a methodological comparison. Environ Impact Assess Rev 21(4):385CrossRefGoogle Scholar
  51. Owens JW (1997) Life-cycle assessment in relation to risk assessment: an evolving perspective. Risk Anal 17(3):359CrossRefGoogle Scholar
  52. 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):295CrossRefGoogle Scholar
  53. Pennington D, Crettaz P, Tauxe A, Rhomberg L, Brand B, Jolliet O (2002) Assessing human health response in life cycle assessment using ED10s and DALIs: part 2-noncancer effects. Risk Anal 22(5):947–963CrossRefGoogle Scholar
  54. Pennington DW, Margni M, Ammann C, Jolliet O (2005) Multimedia fate and human intake modeling: spatial versus nonspatial insights for chemical emissions in Western Europe. Environ Sci Technol 39(4):1119–1128CrossRefGoogle Scholar
  55. Pennington DW, Margni M, Payet J, Jolliet O (2006) Risk and regulatory hazard based toxicological effect indicators in life cycle assessment (LCA). Hum Ecotoxicological Risk Assess J 12(3):450–475CrossRefGoogle Scholar
  56. Pennington DW, Rydberg T, Potting J, Finnveden G, Lindeijer E, Jolliet O, Rebitzer G (2004) Life cycle assessment part 2: current impact assessment practice. Environ Int 30(5):721–739CrossRefGoogle Scholar
  57. Poulin P, Krishnan K (1996) A tissue composition-based algorithm for predicting tissue:air partition coefficients of organic chemicals. Toxicol Appl Pharmacol 136(1):126–130CrossRefGoogle Scholar
  58. Price K, Haddad S, Krishnan K (2003) Physiological modeling of age-specific changes in the pharmacokinetics of organic chemicals in children. J Toxicol Env Health - Part A 66(5):417–433CrossRefGoogle Scholar
  59. Rosenbaum RK, Bachmann TK, Gold LS, Huijbregts MAJ, Jolliet O, Juraske R, Koehler A, Larsen HF, MacLeod M, Margni M, McKone TE, Payet J, Schuhmacher M, Van de Meent D, Hauschild MZ (2008) USEtox—the UNEP/SETAC-consensus model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int J Life Cycle Assess 13(7):532–546CrossRefGoogle Scholar
  60. Rosenbaum RK, Margni M, Jolliet O (2007) A flexible matrix algebra framework for the multimedia multipathway modeling of emission to impacts. Environ Int 33(5):624–634CrossRefGoogle Scholar
  61. Rosenbaum RK, McKone TE, Jolliet O (2009) CKow: a dynamic model for chemical transfer to meat and milk. Environ Sci Technol 43(21):8191–8198CrossRefGoogle Scholar
  62. Smitkova H, Huijbregts MAJ, Hendriks AJ (2005) Comparison of three fish bioaccumulation models for ecological and human risk assessment and validation with field data. SAR QSAR Environ Res 16(5):483–493CrossRefGoogle Scholar
  63. Trapp S, Franco A, Mackay D (2010) Activity-based concept for transport and partitioning of ionizing organics. Environ Sci Technol 44(16):6123–6129CrossRefGoogle Scholar
  64. Travis C, Arms A (1988) Bioconcentration of organics in beef, milk, and vegetation. Environ Sci Technol 22(3):271–274CrossRefGoogle Scholar
  65. Udo de Haes H, Jolliet O, Finnveden G, Goedkoop M, Hauschild M, Hertwich E, Hofstetter P, Klöpffer W, Krewitt W, Lindeijer E, Mueller-Wenk R, Olson S, Pennington D, Potting J, Steen B (2002) Life-cycle impact assessment: striving towards best practice. SETAC, Pensacola, USAGoogle Scholar
  66. USEPA (1997) Exposure factors handbook—volume I. Office of Research and Development, Washington, DCGoogle Scholar
  67. USEPA (2011) Integrated Risk Information System (IRIS)
  68. van Zelm R, Huijbregts MAJ, Van de Meent D (2009) USES-LCA 2.0—a global nested multi-media fate, exposure, and effects model. Int J Life Cycle Assess 14(3):282–284CrossRefGoogle Scholar
  69. Zeise L, Wilson R, Crouch E (1984) Use of acute toxicity to estimate carcinogenic risk. Risk Anal 4(3):187–199CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Ralph K. Rosenbaum
    • 1
    Email author
  • Mark A. J. Huijbregts
    • 5
  • Andrew D. Henderson
    • 4
  • Manuele Margni
    • 2
  • Thomas E. McKone
    • 3
  • Dik van de Meent
    • 5
    • 6
  • Michael Z. Hauschild
    • 1
  • Shanna Shaked
    • 4
  • Ding Sheng Li
    • 4
  • Lois S. Gold
    • 7
  • Olivier Jolliet
    • 4
  1. 1.Section for Quantitative Sustainability Assessment, Department of Management EngineeringTechnical University of Denmark (DTU)LyngbyDenmark
  2. 2.Department of Chemical EngineeringCIRAIG, École Polytechnique de MontréalStn. Centre-ville, MontréalCanada
  3. 3.University of California Berkeley, Lawrence Berkeley National LaboratoryBerkeleyUSA
  4. 4.Department of Environmental Health Sciences, School of Public HealthUniversity of MichiganAnn ArborUSA
  5. 5.Department of Environmental ScienceRadboud University NijmegenNijmegenThe Netherlands
  6. 6.National Institute of Public Health and the Environment (RIVM)BilthovenNetherlands
  7. 7.University of California Berkeley, and Children’s Hospital Oakland Research Institute (CHORI)OaklandUSA

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