Til hovedinnhold
English
Publikasjoner

Development of a Bayesian network for probabilistic risk assessment of pesticides

Vitenskapelig artikkel
Publiseringsår
2021
Tidsskrift
Integrated Environmental Assessment and Management
Eksterne nettsted
Cristin
Arkiv
Doi
Forfattere
Sophie Mentzel, Merete Grung, Knut-Erik Tollefsen, Marianne Stenrød, Karina Petersen, S. Jannicke Moe

Sammendrag

Conventional environmental risk assessment of chemicals is based on a calculated risk quotient, representing the ratio of exposure to effects of the chemical, in combination with assessment factors to account for uncertainty. Probabilistic risk assessment approaches can offer more transparency by using probability distributions for exposure and/or effects to account for variability and uncertainty. In this study, a probabilistic approach using Bayesian network modeling is explored as an alternative to traditional risk calculation. Bayesian networks can serve as meta-models that link information from several sources and offer a transparent way of incorporating the required characterization of uncertainty for environmental risk assessment. To this end, a Bayesian network has been developed and parameterized for the pesticides azoxystrobin, metribuzin, and imidacloprid. We illustrate the development from deterministic (traditional) risk calculation, via intermediate versions, to fully probabilistic risk characterization using azoxystrobin as an example. We also demonstrate the seasonal risk calculation for the three pesticides.