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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/864

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Title: A review of literature and computer models on exposure assessment
Authors: Butt, T. E.
Clark, M.
Coulon, F.
Oduyemi, Kehinde O. K.
Affiliation: University of Abertay Dundee. School of Contemporary Sciences
Keywords: Risk assessment
Issue Date: 2009
Publisher: Taylor & Francis
Type: Journal Article
Refereed: peer-reviewed
Rights: Published version (c)Taylor & Francis, available from http://dx.doi.org/10.1080/09593330903345952
Citation: Butt, T.E., et al. 2009. A review of literature and computer models on exposure assessment. Environmental Technology. 30(14): pp.1487-1501. Available from http://dx.doi.org/10.1080/09593330903345952
Abstract: At the present time, risk analysis is an effective management tool used by environmental managers to protect the environment from inevitable anthropogenic activities. There are generic elements in environmental risk assessments, which are independent of the subject to which risk analysis is applied. Examples of these elements are: baseline study, hazard identification, hazards' concentration assessment and risk quantification. Another important example of such generic elements is exposure assessment, which is required in a risk analysis process for landfill leachate as it would in any other environmental risk issue. Furthermore, computer models are also being developed to assist risk analysis in different fields. However, in the review of current computer models and literature, particularly regarding landfills, the authors have found no evidence for the existence of a holistic exposure assessment procedure underpinned with a computational method for landfill leachate. This paper, with reference to the relevant literature and models reviewed, discusses the extent to which exposure assessment is absent in landfill risk assessment approaches. The study also indicates a number of factors and features that should be added to the exposure assessment system in order to render it more strategic, thereby enhancing the quantitative risk analysis.
URI: http://hdl.handle.net/10373/864
ISSN: 0959-3330
Appears in Collections:Science Engineering & Technology Collection

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