Literature DB >> 18384237

Distribution and variance/covariance structure of pesticide environmental fate data.

Frank Spurlock1.   

Abstract

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.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18384237     DOI: 10.1897/07-600.1

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  1 in total

1.  Use-exposure relationships of pesticides for aquatic risk assessment.

Authors:  Yuzhou Luo; Frank Spurlock; Xin Deng; Sheryl Gill; Kean Goh
Journal:  PLoS One       Date:  2011-04-01       Impact factor: 3.240

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.