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A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks

Comparing risks among pesticides has substantial utility for decision makers. However, if rating schemes to compare risks are to be used, they must be conceptually and mathematically sound. We address limitations with pesticide risk rating schemes by examining in particular the Environmental Impact...

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Autores principales: Peterson, Robert K.D., Schleier, Jerome J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4006226/
https://www.ncbi.nlm.nih.gov/pubmed/24795854
http://dx.doi.org/10.7717/peerj.364
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author Peterson, Robert K.D.
Schleier, Jerome J.
author_facet Peterson, Robert K.D.
Schleier, Jerome J.
author_sort Peterson, Robert K.D.
collection PubMed
description Comparing risks among pesticides has substantial utility for decision makers. However, if rating schemes to compare risks are to be used, they must be conceptually and mathematically sound. We address limitations with pesticide risk rating schemes by examining in particular the Environmental Impact Quotient (EIQ) using, for the first time, a probabilistic analytic technique. To demonstrate the consequences of mapping discrete risk ratings to probabilities, adjusted EIQs were calculated for a group of 20 insecticides in four chemical classes. Using Monte Carlo simulation, adjusted EIQs were determined under different hypothetical scenarios by incorporating probability ranges. The analysis revealed that pesticides that have different EIQs, and therefore different putative environmental effects, actually may be no different when incorporating uncertainty. The EIQ equation cannot take into account uncertainty the way that it is structured and provide reliable quotients of pesticide impact. The EIQ also is inconsistent with the accepted notion of risk as a joint probability of toxicity and exposure. Therefore, our results suggest that the EIQ and other similar schemes be discontinued in favor of conceptually sound schemes to estimate risk that rely on proper integration of toxicity and exposure information.
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spelling pubmed-40062262014-05-02 A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks Peterson, Robert K.D. Schleier, Jerome J. PeerJ Agricultural Science Comparing risks among pesticides has substantial utility for decision makers. However, if rating schemes to compare risks are to be used, they must be conceptually and mathematically sound. We address limitations with pesticide risk rating schemes by examining in particular the Environmental Impact Quotient (EIQ) using, for the first time, a probabilistic analytic technique. To demonstrate the consequences of mapping discrete risk ratings to probabilities, adjusted EIQs were calculated for a group of 20 insecticides in four chemical classes. Using Monte Carlo simulation, adjusted EIQs were determined under different hypothetical scenarios by incorporating probability ranges. The analysis revealed that pesticides that have different EIQs, and therefore different putative environmental effects, actually may be no different when incorporating uncertainty. The EIQ equation cannot take into account uncertainty the way that it is structured and provide reliable quotients of pesticide impact. The EIQ also is inconsistent with the accepted notion of risk as a joint probability of toxicity and exposure. Therefore, our results suggest that the EIQ and other similar schemes be discontinued in favor of conceptually sound schemes to estimate risk that rely on proper integration of toxicity and exposure information. PeerJ Inc. 2014-04-22 /pmc/articles/PMC4006226/ /pubmed/24795854 http://dx.doi.org/10.7717/peerj.364 Text en © 2014 Peterson and Schleier III http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Agricultural Science
Peterson, Robert K.D.
Schleier, Jerome J.
A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title_full A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title_fullStr A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title_full_unstemmed A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title_short A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
title_sort probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks
topic Agricultural Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4006226/
https://www.ncbi.nlm.nih.gov/pubmed/24795854
http://dx.doi.org/10.7717/peerj.364
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