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Performance of the CalTOX fate and exposure model in a case study for a dioxin-contaminated site
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
Number of Authors: 3
2015 (English)In: Environmental science and pollution research international, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 22, no 11, 8719-8727 p.Article in journal (Refereed) Published
Abstract [en]

Soil with high levels of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) is found at contaminated sites all over the world. Transfer of PCDD/Fs from contaminated soil to the food chain could lead to elevated human exposure. As a complement to available monitoring data, multimedia fate and exposure modeling can be applied to support risk assessment of sites with PCDD/F contaminated soil. In this study, we evaluated the performance of the CalTOX fate and exposure model for 2,3,7,8-substituted PCDD/Fs against measured concentrations in air, soil, grass, carrots, potatoes, milk, meat, and eggs from a contaminated site in northern Sweden. The calculated total toxic equivalent (TEQ) concentrations agree with measurements within a factor of 10 for all exposure media but one. Results for individual congeners demonstrated that the model did not always perform well at describing key processes that mobilize PCDD/Fs out of soils, such as transfer into root crops and ingestion of soil by chickens. Uncertainty in only a small subset of input parameters affects the model output. Improved information and models describing transfer of soil particles onto leafy vegetation by rain splash and biotransfer factors for PCDD/Fs to milk, meat, and eggs are particular research needs to reduce uncertainties in model-based assessments.

Place, publisher, year, edition, pages
2015. Vol. 22, no 11, 8719-8727 p.
Keyword [en]
CalTOX, Contaminated soil, Fate and exposure modeling, PCDD/F, Dioxins, Risk assessment, Uncertainty analysis, Monte Carlo analysis
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-118523DOI: 10.1007/s11356-014-4037-7ISI: 000354960300069OAI: oai:DiVA.org:su-118523DiVA: diva2:826691
Available from: 2015-06-25 Created: 2015-06-22 Last updated: 2017-12-04Bibliographically approved

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