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Title (Primary) Receptor-oriented approaches in wildlife and human exposure modelling: a comparative study
Author Loos, M.; Schipper, A.M.; Schlink, U.; Strebel, K.; Ragas, A.M.J.;
Journal Environmental Modelling & Software
Year 2010
Department STUDIEN;
Volume 25
Issue 4
Language englisch;
Keywords Environmental risk assessment; Contaminant exposure; Model comparison; Chemical stressors; Multiple stressors
Abstract Five human and five wildlife receptor-oriented exposure models were compared with the aim to identify similarities, differences and areas where both fields can learn from each other. Similarities were revealed in exposure endpoints, chemical stressors and extent of model validation. Differences were observed in effect endpoints, non-chemical stressors, exposure routes and media, and parameter uncertainty assessment. The most outstanding differences related to the simulation of behaviour and the representation of individuals and space. Whereas human models use static individuals and obtain activity patterns from databases, activity patterns for wildlife tend to be an emerging property of dynamic individuals, resulting from interactions with the surrounding environment. These differences can be explained by differences in legislation, dominant exposure routes and data availability. Wildlife models can serve as a source of inspiration for human models with respect to the simulation of emergent activity patterns and the inclusion of non-chemical stressors. Human models can act as a source of inspiration for wildlife models when it comes to including multiple exposure routes and the compilation and use of activity data. These adaptations could result in a more holistic approach, in line with current environmental policy that advances towards a more integrated health approach.
ID 10263
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=10263
Loos, M., Schipper, A.M., Schlink, U., Strebel, K., Ragas, A.M.J. (2010):
Receptor-oriented approaches in wildlife and human exposure modelling: a comparative study
Environ. Modell. Softw. 25 (4), 369 - 382