Bayesian Networks in Environmental Risk Assessment: A Review - Kaikkonen, Laura; Parviainen, Tuuli; Rahikainen, Mika; Uusitalo, Laura; Lehikoinen, Annukka (Society of Environmental Toxicology and Chemistry (SETAC), 2020)
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 the adverse effects of human activities and other stressors 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 modeling. This paper reviews the use of BNs in ERA based on peer‐reviewed publications. Following a systematic mapping protocol, we identified studies in which 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.
Keywords: Causal inference; decision support systems; Integrated modeling; risk analysis