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Bayesian Networks in Environmental Risk Assessment: A review.

  • Kaikkonen, Laura1, 2
  • Parviainen, Tuuli1, 2
  • Rahikainen, Mika3
  • Uusitalo, Laura4
  • Lehikoinen, Annukka2, 5
  • 1 Ecosystems and Environment Research Programme, University of Helsinki, Helsinki, Finland. , (Finland)
  • 2 Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland. , (Finland)
  • 3 Bioeconomy Statistics, Natural Resource Institute Finland, Helsinki, Finland. , (Finland)
  • 4 Programme for Environmental Information, Finnish Environment Institute, Helsinki, Finland. , (Finland)
  • 5 Ecosystems and Environment Research Programme, University of Helsinki (Kotka Maritime Research Centre), Kotka, Finland. , (Finland)
Published Article
Integrated Environmental Assessment and Management
Wiley (John Wiley & Sons)
Publication Date
Aug 25, 2020
DOI: 10.1002/ieam.4332
PMID: 32841493


Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of human activities' and other stressors' adverse effects on the environment. Bayesian Networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modelling. This paper reviews the use of BNs in ERA based on peer-reviewed publications. Following a systematic mapping protocol, we identified studies where BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA particularly in recent years and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors' experience, we outline general guidelines and development ideas for using BNs in ERA. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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