title: Distribution and variance/covariance structure of pesticide environmental fate data.
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.
authors.affiliation: California Department of Pesticide Regulation, Environmental Monitoring Branch, 1001 I Street, P.O. Box 4015, Sacramento, California 95812, USA. fcspurlock@cdpr.ca.gov
authors.forename: Frank
authors.initials: F
authors.lastname: Spurlock
mesh_terms: D001673:Biodegradation, Environmental; D002244:Carbon; D004777:Environment; D004784:Environmental Monitoring; D007700:Kinetics; D009010:Monte Carlo Method; D000442:Octanols / Q000737:chemistry; D010573:Pesticide Residues / Q000032:analysis* / Q000737:chemistry; D010575:Pesticides / Q000032:analysis*; D011336:Probability; D018570:Risk Assessment; D012984:Software; D012989:Soil Pollutants / Q000032:analysis; D014874:Water Pollutants, Chemical / Q000032:analysis; D018508:Water Purification
chemical_list: D000442:Octanols; D010573:Pesticide Residues; D010575:Pesticides; D012989:Soil Pollutants; D014874:Water Pollutants, Chemical; D002244:Carbon