Adding Realism to the Assessment of Occupational Exposure to Pesticides Using Probabilistic Modelling: A Case Study on Aggregate Exposure to Pyrethroids

firstₚage Download PDF settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessAbstract Adding Realism to the Assessment of Occupational Exposure to Pesticides Using Probabilistic Modelling: A Case Study on Aggregate Exposure to Pyrethroids † by Ana Fernandez-AgudoAna Fernandez-Agudo SciProfiles Scilit Preprints. org Google Scholar 1, *, Agathi CharistouAgathi Charistou SciProfiles Scilit Preprints. org Google Scholar 2, Niki ArapakiNiki Arapaki SciProfiles Scilit Preprints. org Google Scholar 2, Kyriaki MacheraKyriaki Machera SciProfiles Scilit Preprints. org Google Scholar 2, Mercedes Alba GonzalezMercedes Alba Gonzalez SciProfiles Scilit Preprints. org Google Scholar 1, Maria del Carmen Gonzalez CaballeroMaria del Carmen Gonzalez Caballero SciProfiles Scilit Preprints. org Google Scholar 1 and Jose V. TarazonaJose V. Tarazona SciProfiles Scilit Preprints. org Google Scholar 1 1 National Environmental Health Centre, Instituto de Salud Carlos III, 28222 Madrid, Spain 2 Benaki Phytopathological Institute, Kifisia 145 61, Greece * Author to whom correspondence should be addressed. † Presented at the 1st International Electronic Conference on Toxics, 20–22 March 2024; Available online: https: //sciforum. net/event/IECTO2024. Proceedings 2024, 102 (1), 51; https: //doi. org/10. 3390/proceedings2024102051 Published: 3 April 2024 Download keyboardₐrrowdown Download PDF Download PDF with Cover Download XML Download Epub Download Supplementary Material Versions Notes Keywords: pesticide exposure; probabilistic modeling; pyrethroids; occupational exposure assessment; aggregate exposure; monte carlo simulations; risk evaluation Pyrethroid usage has risen due to restrictions on other insecticides, prompting interest in biomonitoring data as exposure indicators. Occupational exposure, particularly in Plant Protection Product (PPP) applications, is a focus. Regulatory agencies, like the European Food Safety Authority (EFSA), use tools such as OPEX (https: //r4eu. efsa. europa. eu/app/opex) (accessed on 2 April 2024) to assess non-dietary exposure, employing mainly worst-case scenarios for increased protection. This research explores OPEX's suitability for non-regulatory realistic aggregate exposure estimations via probabilistic modeling and Monte Carlo simulations. This study uses as background information/data generated within projects funded by EFSA and is part of a case study under the EU PARC project estimating aggregated pyrethroid exposure. This study uses workflows for operators and workers, integrating tasks and applying Monte Carlo simulations for exposure estimation variability. Probability distributions replace default values, addressing real-world uncertainties. The intention is to present a conceptual model for three occupational exposure scenarios, highlighting variability in task roles and exposure routes. Monte Carlo simulations offer full probability distributions, aiding sensitivity and uncertainty analyses. This study plans to compare aggregated exposure, including dietary exposure, with some preliminary results. The ongoing project aims to refine default values via a probabilistic assessment strategy. To conclude, there is a need for aggregate exposure models considering shared neurotoxicity among pyrethroids. The proposed approach, based on the regulatory OPEX tool, facilitates comparisons between assessments conducted for regulatory purposes and aggregate assessments. Pyrethroids are chosen due to their proximity to concerning dietary exposure levels. This study's innovative approach aims to refine occupational exposure assessments, identify aggregate exposure risks, and enhance pesticide risk evaluation in occupational settings, contributing valuable insights for future studies. Supplementary MaterialsThe following are available online at https: //www. mdpi. com/article/10. 3390/proceedings2024102051/s1. Author ContributionsConceptualization and methodology, J. V. T. ; software, A. F. -A. ; validation, A. F. -A. , A. C. , N. A. , K. M. , M. A. G. , M. d. C. G. C. and J. V. T. ; formal analysis, A. F. -A. , A. C. , N. A. , K. M. , M. A. G. , M. d. C. G. C. and J. V. T. ; resources and data curation, A. C. , N. A. and K. M. ; writing—original draft preparation, A. F. -A. ; writing—review and editing, A. F. -A. , A. C. , N. A. , K. M. , M. A. G. , M. d. C. G. C. and J. V. T. ; visualization, A. F. -A. All authors have read and agreed to the published version of the manuscript. FundingThis research was funded by Partnership for the Assessment of Risks for Chemicals (PARC). Co-founded by the EU, Grant number ID: 101057014. Institutional Review Board StatementNot applicable. Informed Consent StatementNot applicable. Data Availability StatementThe original data presented in the study are openly available at https: //doi. org/10. 3390/toxics10080451, https: //doi. org/10. 2903/j. efsa. 2022. 7032, https: //doi. org/10. 2903/sp. efsa. 2015. EN-846, https: //doi. org/10. 2903/sp. efsa. 2012. EN-346. Conflicts of InterestThe authors declare no conflict of interest. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author (s) and contributor (s) and not of MDPI and/or the editor (s). MDPI and/or the editor (s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https: //creativecommons. org/licenses/by/4. 0/). Share and Cite MDPI and ACS Style Fernandez-Agudo, A. ; Charistou, A. ; Arapaki, N. ; Machera, K. ; Alba Gonzalez, M. ; Gonzalez Caballero, M. d. C. ; Tarazona, J. V. Adding Realism to the Assessment of Occupational Exposure to Pesticides Using Probabilistic Modelling: A Case Study on Aggregate Exposure to Pyrethroids. Proceedings 2024, 102, 51. https: //doi. org/10. 3390/proceedings2024102051 AMA Style Fernandez-Agudo A, Charistou A, Arapaki N, Machera K, Alba Gonzalez M, Gonzalez Caballero MdC, Tarazona JV. Adding Realism to the Assessment of Occupational Exposure to Pesticides Using Probabilistic Modelling: A Case Study on Aggregate Exposure to Pyrethroids. Proceedings. 2024; 102 (1): 51. https: //doi. org/10. 3390/proceedings2024102051 Chicago/Turabian Style Fernandez-Agudo, Ana, Agathi Charistou, Niki Arapaki, Kyriaki Machera, Mercedes Alba Gonzalez, Maria del Carmen Gonzalez Caballero, and Jose V. Tarazona. 2024. "Adding Realism to the Assessment of Occupational Exposure to Pesticides Using Probabilistic Modelling: A Case Study on Aggregate Exposure to Pyrethroids" Proceedings 102, no. 1: 51. https: //doi. org/10. 3390/proceedings2024102051 Article Metrics No No Article Access Statistics Multiple requests from the same IP address are counted as one view.