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概率分析揭示了环境影响商数和类似系统在评估农药风险方面的基本局限性。

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

机构信息

Department of Land Resources and Environmental Sciences, Montana State University , Bozeman, Montana , USA.

出版信息

PeerJ. 2014 Apr 22;2:e364. doi: 10.7717/peerj.364. eCollection 2014.

Abstract

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.

摘要

比较不同农药的风险对决策者具有重要意义。然而,如果要使用风险评级方案进行比较,那么这些方案必须在概念上和数学上都是合理的。我们通过特别使用概率分析技术来检查环境影响商数(EIQ),从而解决了农药风险评级方案的局限性。为了说明将离散风险评级映射到概率的后果,我们首次针对四类 20 种杀虫剂计算了调整后的 EIQ。使用蒙特卡罗模拟,通过纳入概率范围,在不同的假设情况下确定了调整后的 EIQ。分析表明,具有不同 EIQ 的杀虫剂(因此具有不同的潜在环境影响)在纳入不确定性时实际上可能没有差异。EIQ 方程无法按照其结构考虑不确定性,也无法提供可靠的农药影响比率。EIQ 也不符合毒性和暴露的联合概率作为风险的公认概念。因此,我们的结果表明,应停止使用 EIQ 和其他类似方案,转而采用基于毒性和暴露信息的适当整合来估计风险的合理方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a224/4006226/ae94f17c7a69/peerj-02-364-g001.jpg

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