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Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents
Human exposure to pesticide mixtures can occur from the diet and other sources. Realistic exposure and risk assessments should include multiple sources and compounds and include the relative hazards of the different compounds. The EU-funded Euromix project is developing new web-based tools to facili...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469822/ https://www.ncbi.nlm.nih.gov/pubmed/30734911 http://dx.doi.org/10.1007/s11356-019-04440-7 |
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author | Kennedy, Marc C. Garthwaite, David G. de Boer, Waldo J. Kruisselbrink, Johannes W. |
author_facet | Kennedy, Marc C. Garthwaite, David G. de Boer, Waldo J. Kruisselbrink, Johannes W. |
author_sort | Kennedy, Marc C. |
collection | PubMed |
description | Human exposure to pesticide mixtures can occur from the diet and other sources. Realistic exposure and risk assessments should include multiple sources and compounds and include the relative hazards of the different compounds. The EU-funded Euromix project is developing new web-based tools to facilitate these calculations. A case study is presented that exemplifies their use for a population of UK residents, including exposure from crop-spraying. A UK pesticide usage survey provided information on real pesticide combinations applied to crops of wheat, potatoes, sugar beet and dessert apples. This information was combined with outputs from two alternative simulation models of spray drift to estimate dermal, oral and inhalation exposures of residents. These non-dietary exposures were combined with dietary exposure estimates using the Monte Carlo Risk Assessment software to produce a distribution of aggregated and cumulative exposures. Compounds are weighted by relative potency to generate a measure of overall risk. Uncertainty quantification was also included in the distribution of exposures. These tools are flexible to allow diverse sources of exposure and can provide important information to decision-makers and help to prioritise testing of pesticide mixtures. Including non-dietary sources changed the prioritisation of pesticide mixtures, when compared to dietary exposure alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11356-019-04440-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6469822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-64698222019-05-03 Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents Kennedy, Marc C. Garthwaite, David G. de Boer, Waldo J. Kruisselbrink, Johannes W. Environ Sci Pollut Res Int Research Article Human exposure to pesticide mixtures can occur from the diet and other sources. Realistic exposure and risk assessments should include multiple sources and compounds and include the relative hazards of the different compounds. The EU-funded Euromix project is developing new web-based tools to facilitate these calculations. A case study is presented that exemplifies their use for a population of UK residents, including exposure from crop-spraying. A UK pesticide usage survey provided information on real pesticide combinations applied to crops of wheat, potatoes, sugar beet and dessert apples. This information was combined with outputs from two alternative simulation models of spray drift to estimate dermal, oral and inhalation exposures of residents. These non-dietary exposures were combined with dietary exposure estimates using the Monte Carlo Risk Assessment software to produce a distribution of aggregated and cumulative exposures. Compounds are weighted by relative potency to generate a measure of overall risk. Uncertainty quantification was also included in the distribution of exposures. These tools are flexible to allow diverse sources of exposure and can provide important information to decision-makers and help to prioritise testing of pesticide mixtures. Including non-dietary sources changed the prioritisation of pesticide mixtures, when compared to dietary exposure alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11356-019-04440-7) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2019-02-08 2019 /pmc/articles/PMC6469822/ /pubmed/30734911 http://dx.doi.org/10.1007/s11356-019-04440-7 Text en © The Author(s) 2019 OpenAccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Article Kennedy, Marc C. Garthwaite, David G. de Boer, Waldo J. Kruisselbrink, Johannes W. Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title | Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title_full | Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title_fullStr | Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title_full_unstemmed | Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title_short | Modelling aggregate exposure to pesticides from dietary and crop spray sources in UK residents |
title_sort | modelling aggregate exposure to pesticides from dietary and crop spray sources in uk residents |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469822/ https://www.ncbi.nlm.nih.gov/pubmed/30734911 http://dx.doi.org/10.1007/s11356-019-04440-7 |
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