Evaluation of models for dermal exposure assessment in farming systems in developing countries

Dermal Exposure Assessment is a crucial aspect within the risk assessment of pesticide use as it may lead to the development and improvement of measures to reduce the health risk of pesticides users. Even though, tools for dermal exposure assessment are available, their implementation in developing countries is problematic as they are designed under working conditions in industrialized countries and most of them are not specifically focused on processes like pesticide management. This paper evaluates dermal exposure models finding out the most appropriate ones to assess dermal exposure of pesticide use in farming systems in developing countries. Seven models (i.e. COSHH, DERM, DREAM, EASE, PHED, RISKOFDERM and STOFFENMANAGER) were evaluated according to a multi-criteria analysis and four models (i.e. DERM, DREAM, PHED and RISKOFDERM) were selected for the assessment of dermal exposure in the case study of potato farming systems in Vereda La Hoya in the highlands in Colombia. The model estimations were compared with dermal exposure measurements made in the study area. The results show that the four models provide different dermal exposure estimations which are not comparable. Because of the simplicity of the algorithms and the specificity of the determinants, the models DERM and DREAM were found to be the most appropriate ones. In addition, it was found that model outcomes would be more accurate in the assessment if determinants like climate conditions, cleaning of the equipment, task duration, personal protective equipment and hygiene habits are included in the models. When comparing the final model assessment of dermal exposure in the study area, DREAM was found as the model that assesses more appropriately dermal exposure because of the qualitative assessment and the type of determinants included in the model.


Published in:
Journal of Environmental Engineering and Ecological Science, 3, 1
Year:
2013
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 Record created 2017-03-12, last modified 2018-03-17

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