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首页> 外文期刊>Environmental toxicology and chemistry >Distribution And Variance/covariance Structure Of Pesticide Environmental Fate Data
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Distribution And Variance/covariance Structure Of Pesticide Environmental Fate Data

机译：农药环境归宿数据的分布及方差/协方差结构

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摘要

Hydrophobicity, persistence, and volatility data for individual pesticides are widely used in risk assessment and transport modeling, so it is important to understand their distribution, variation, and covariation. Correlations (normalized covariance) among properties across a range of multiple pesticides are also important for understanding fundamental relationships among the properties. For the present study, multiple determinations of 11 physicochemical properties of 262 individual pesticides were compiled, primarily from registrant submissions. A Z-score normality analysis indicates that, barring specific data to the contrary, log normality is a reasonable assumption for three properties commonly treated as random variables in modeling: Organic carbon-normalized soil sorption coefficient, aerobic soil metabolism half-life, and field dissipation half-life. Various percentiles for coefficients of variation of the variables are provided, allowing probabilistic modelers to choose realistic population parameters for sampling distributions. A second data set consisting of median values of individual properties for each pesticide was used to investigate the covariance structure of eight of the most important fate properties across 172 pesticides using correlation analysis and exploratory common factor analysis. That analysis demonstrated the use of common factor analysis for reducing the dimensionality of multicollinear environmental fate data, yielding three new orthogonal variables containing most of the information in the original data, and provided insight into the fundamental data structure.
机译：个别农药的疏水性，持久性和挥发性数据已广泛用于风险评估和运输建模中，因此了解其分布，变异和协变非常重要。跨多种农药的特性之间的相关性（标准化协方差）对于理解特性之间的基本关系也很重要。对于本研究，主要从注册人提交的材料中，对262种农药的11种理化特性进行了多次测定。 Z分数正态性分析表明，除相反的数据外，对数正态性是对在建模中通常视为随机变量的三个属性的合理假设：有机碳归一化土壤吸附系数，好氧土壤代谢半衰期和田间耗散半衰期。提供了变量变化系数的各种百分位数，使概率建模者可以选择实际的总体参数进行抽样分布。使用相关分析和探索性公共因子分析，使用第二种数据集（由每种农药的单个属性的中值组成）调查了172种农药中八个最重要的命运属性的协方差结构。该分析证明了使用公共因子分析降低多共线环境归宿数据的维数，产生了三个新的正交变量，这些变量包含原始数据中的大多数信息，并提供了对基本数据结构的洞察力。

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