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Challenges for exposure prediction in ecological risk assessment
Author(s) -
Di Guardo Antonio,
Hermens Joop LM
Publication year - 2013
Publication title -
integrated environmental assessment and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 57
eISSN - 1551-3793
pISSN - 1551-3777
DOI - 10.1002/ieam.1442
Subject(s) - organism , biochemical engineering , computer science , environmental science , variety (cybernetics) , risk analysis (engineering) , risk assessment , ecosystem , ecology , environmental resource management , biology , artificial intelligence , engineering , business , paleontology , computer security
Evaluating organism exposure in the ecosystems is a difficult task and can be carried out measuring or predicting concentrations in the environment. Although current regulatory approaches favor a modeling approach, they either use a static representation of the environment and of the chemical discharge or a simplified dynamic approach (e.g., dealing with pesticides). Improving the ecological realism of exposure prediction offers a number of challenges. Some are related to the understanding of basic mechanisms such as bioavailability and the determination of internal exposure or the need to develop new paradigms for polar and ionized chemicals. Other issues are the need to provide monitoring data to understand the environmental fate of chemical mixtures, polar and ionized chemicals and metabolites, to understand the complexity of exposure in spatially and temporally variable environments. Exposure models require the development of suitable approaches to simulate the complexity of exposure in the ecosystems including the development of a variety of temporal and spatial scenarios and the integration of submodels (such as aquatic and terrestrial food webs). Finally, the integration of dynamic exposure and effect models is envisaged to fully carry out a more realistic ecological risk assessment. Integr Environ Assess Manag 2013;9:e4–e14. © 2013 SETAC