SWOT Analysis of the MERLIN-Expo Tool and Its Relevance in Legislative Frameworks

  • Tineke De WildeEmail author
  • Frederik Verdonck
  • Alice Tediosi
  • Taku Tanaka
  • Roseline Bonnard
  • Zoran Banjac
  • Panagiotis Isigonis
  • Elisa Giubilato
  • Andrea Critto
  • Alex Zabeo
  • Nicoleta Alina Suciu
  • James Garratt
  • Philippe Ciffroy
Part of the The Handbook of Environmental Chemistry book series (HEC, volume 57)


The MERLIN-Expo tool was evaluated using a SWOT analysis, which was based on expert judgement and literature review. A list of criteria was set up containing the major model characteristics, which were divided in general model criteria and relevance model criteria. Relevance model criteria were defined as criteria, which are highly depending on the regulatory framework the model is used in. From the analysis presented above, it appeared that certain regulatory chemical frameworks (e.g. REACH, biocides) are stricter towards their requirements compared to others (e.g. site-specific/local regulatory frameworks). Based on expert judgement, the MERLIN-Expo tool was evaluated using the general and relevance criteria. MERLIN-Expo has many advanced functionalities (such as uncertainty analysis, modular approach, dynamic model, combines environmental fate with pharmacokinetics) and models (many fate processes and environmental compartments, different human populations). At the same time, the threat is that current (regulatory) applicability frameworks do not always require these advanced assessment functionalities. The MERLIN-Expo tool appeared to be most suitable for the site-specific assessment as this is the most flexible framework. Based on this analysis, weaknesses of the MERLIN-Expo tool for its use in a certain regulatory framework could also be identified. These weaknesses are at the same time further development opportunities for MERLIN-Expo. On general model characteristics, MERLIN-Expo was identified as a highly documented (both for novice and expert level), transparent, user-friendly tool with regular trainings. Its main treat now is to ensure continuing support and mechanisms for future developmental work and updates.


Exposure models MERLIN-Expo Multimedia models Regulatory framework SWOT analysis 


  1. 1.
    RISKCYCLE (2011) Deliverable 5.2. Review of models used to assess human toxicity and exotoxicological impacts of chemicalsGoogle Scholar
  2. 2.
    Fryer M, Collins CD, Ferrier H, Colvile RN, Nieuwenhuijsen MJ (2006) Human exposure modelling for chemical risk assessment: a review of current approaches and research and policy implications. Environ Sci Policy 9:261–274CrossRefGoogle Scholar
  3. 3.
    Fryer ME, Collins CD, Colvile RN, Ferrier H, Nieuwenhuijsen MJ (2004) Evaluation of currently used exposure models to define a human exposure model for use in chemical risk assessment in the UK. The Interdepartmental Group on Health Risks from Chemicals, 167 ppGoogle Scholar
  4. 4.
    WHO (2005) Harmonization Project Document No. 3. Principles of characterizing and applying human exposure modelsGoogle Scholar
  5. 5.
    EPA (1999) EPA-453/D-99-001. TRIM.Expo Technical Support Document, p 223Google Scholar
  6. 6.
    Chen Y, Ma H (2006) Model comparison for risk assessment: a case study of contaminated groundwater. Chemosphere 63:751–761CrossRefGoogle Scholar
  7. 7.
    Huijbregts MAJ, Geelen LMJ, Hertwich EG, McKone TE, Van De Meent D (2005) 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 24:486–493CrossRefGoogle Scholar
  8. 8.
    Mackay D, Webster E, Cousins I, Cahill T, Foster K, Gouin T (2001) An introduction to multimedia models. CEMC Report No. 200102Google Scholar
  9. 9.
    OECD (2004) Guidance document on the use of multimedia models for estimating overall environmental persistence and long-range transport. OECD Series on Testing and Assessment No. 45. JT00160339Google Scholar
  10. 10.
    Park MVDZ, Delmaar JE, Van Engelen JGM (2006) Comparison of consumer exposure modelling tools. Inventory of possible improvements of ConsExpo. RIVM report 320104006/2006Google Scholar
  11. 11.
    Rong-Rong Z, Che-Sheng Z, Zhong-Peng H, Xiao-Meng S (2012) Review of environmental multimedia models. Environ Forensics 13:216–224CrossRefGoogle Scholar
  12. 12.
    Rosenbaum RK, Bachman TM, 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 toxicity model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int J Life Cycle Assess 13:532–546CrossRefGoogle Scholar
  13. 13.
    Rovira J, Nadal M, Domingo JL, Tanaka T, Suciu NA, Trevisan M, Capri E, Segui X, Darbra RM, Schuhmacher M (2013) A revision of current models for environmental and human health impact on risk assessment for application to emerging chemicals. In: Bilitewski B, Darbra RM, Barcelo D (eds) Global risk-based management of chemical additives II. Risk-based assessment and management strategies. SpringerGoogle Scholar
  14. 14.
    Schwartz S, Berding V, Trapp S, Matthies M (1998) Quality criteria for environmental risk assessment software. Using the example of EUSES. Environ Sci Pollut Res 5:217–222CrossRefGoogle Scholar
  15. 15.
    Webster A, Mackay D, Wania F, Arnot J, Gobas F, Gouin T, Hubbarde J, Bonnell M (2005) Development and application of models of chemical fate in Canada. Modelling guidance document. CEMN Report No. 200501Google Scholar
  16. 16.
    Bonnard R (2006) Common errors in the use of the CalTOX model to assess human health risks linked to industrial emissions of pollutants. Hum Ecol Risk Assess 12:1000–1010CrossRefGoogle Scholar
  17. 17.
    Maddalena RL, McKone TE, Layton DW (1995) Comparison of multimedia transport and transformation models – regional fugacity model vs. calTOX. Chemosphere 30:869–889CrossRefGoogle Scholar
  18. 18.
    Rosenbaum RK, Huijbregts MAJ, Henderson AD, Margni M, McKone TE, van de Meent D, Hauschild MZ, Shaked S, Sheng Li D, Gold LS, Jolliet O (2011) USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties. Int J Life Cycle Assess 16:710–727CrossRefGoogle Scholar
  19. 19.
    Sleeswijk AW, Heijungs R (2010) GLOBOX: a spatially differentiated global fate, intake and effect model for toxicity assessment in LCA. Sci Total Environ 108:2817–2832CrossRefGoogle Scholar
  20. 20.
    McKone TE, Bennett DH, Maddalena RL (2002) CalTOX, Multimedia, Mulitipathway Exposure Model Technical Support Document 2002, Lawrence Berkeley National Laboratory report LBNL-47254Google Scholar
  21. 21.
    Lijzen JPA, Rikken MGJ (2004) Euses, Background report. RIVM report no. 601900005/2004Google Scholar
  22. 22.
    Sleeswijk AW (2006) GLOBOX – a spatially differentiated multimedia fate and exposure model. Environ Sci Pollut Res 13:143–143CrossRefGoogle Scholar
  23. 23.
    Larsbo M, Jarvis N (2003) MACRO 5.0. A model of water flow and solute transport in macroporous soil. Technical description, p 52Google Scholar
  24. 24.
    Ciffroy P, Alfonso B, Altenpohl A, Banjac D, Bierkens J, Brochot C, Critto A, De Wilde T, Fait G, Garratt J, Giubilato E, Grange E, Johansson E, Rodmyski A, Reschwann K, Suciu N, Tanaka T, Tediosi A, Van Holderbeke M, Verdonck F (2016) Modelling the exposure to chemicals for risk assessment: a comprehensive library of multimedia and PBPK models for integration, prediction, uncertainty and sensitivity analysis - the MERLIN-Expo tool. Sci Tot Env 568:770–784CrossRefGoogle Scholar
  25. 25.
    Leistra M, van der Linden AMA, Boesten JJTI, Tiktak A, van den Berg A (2001) PEARL model for pesticide behaviour and emissions in soil-plant systems. Description of processes. Alterra report 13, RIVM report 711401009, Alterra, Wageningen, 107 ppGoogle Scholar
  26. 26.
    Gorener A, Toker K, Ulucay K (2012) Application of combined SWOT and AHP: a case study for a manufacturing firm. Procedia Soc Behav Sci 58:1525–1534CrossRefGoogle Scholar
  27. 27.
    Kangas J, Kurttila M, Kajanus M, Kangas A (2003) Evaluating the management strategies of a forestland estate—the S-O-S approach. J Environ Manage 69:349–358CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Tineke De Wilde
    • 1
    Email author
  • Frederik Verdonck
    • 1
  • Alice Tediosi
    • 2
  • Taku Tanaka
    • 3
  • Roseline Bonnard
    • 4
  • Zoran Banjac
    • 5
  • Panagiotis Isigonis
    • 6
  • Elisa Giubilato
    • 6
  • Andrea Critto
    • 6
  • Alex Zabeo
    • 6
  • Nicoleta Alina Suciu
    • 7
  • James Garratt
    • 8
  • Philippe Ciffroy
    • 3
  1. 1.ArcheWondelgemBelgium
  2. 2.Aeiforia srlGariga di PodenzanoItaly
  3. 3.Electricité de France (EDF) R&DNational Hydraulic and Environment LaboratoryChatouFrance
  4. 4.INERIS, Unité Impact Sanitaire et Expositions (ISAE)Verneuil en HalatteFrance
  5. 5.IDAEA-CSICBarcelonaSpain
  6. 6.Department of Environmental Sciences, Informatics and StatisticsUniversity Ca’ Foscari VeniceMestre-VeneziaItaly
  7. 7.Università Cattolica Del Sacro CuorePiacenzaItaly
  8. 8.Enviresearch, The Nanotechnology CentreNewcastle UniversityNewcastle upon TyneUK

Personalised recommendations