A Molecular Topology Approach to Predicting Pesticide Pollution of Groundwater

Various models have proposed methods for the discrimination of polluting and nonpolluting compounds on the basis of simple parameters, typically adsorption and degradation constants. However, such attempts are prone to site variability and measurement error to the extent that compounds cannot be rel...

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Bibliographic Details
Published in:Environmental science & technology 2001-06, Vol.35 (11), p.2282-2287
Main Author: Worrall, Fred
Format: Article
Language:English
Subjects:
Agriculture
Agronomy. Soil science and plant productions
Applied sciences
Biological and medical sciences
Earth sciences
Earth, ocean, space
Engineering and environment geology. Geothermics
Exact sciences and technology
Forecasting
Fundamental and applied biological sciences. Psychology
Groundwaters
Models, Theoretical
Molecules
Natural water pollution
Pesticides
Pesticides - analysis
Pollution
Pollution, environment geology
Regression Analysis
Risk Assessment
Soil and water pollution
Soil Pollutants - analysis
Soil science
Water Movements
Water Pollutants, Chemical - analysis
Water pollution
Water treatment and pollution
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Summary:Various models have proposed methods for the discrimination of polluting and nonpolluting compounds on the basis of simple parameters, typically adsorption and degradation constants. However, such attempts are prone to site variability and measurement error to the extent that compounds cannot be reliably classified nor the chemistry of pollution extrapolated from them. Using observations of pesticide occurrence in U.S. groundwater it is possible to show that polluting from nonpolluting compounds can be distinguished purely on the basis of molecular topology. Topological parameters can be derived without measurement error or site-specific variability. A logistic regression model has been developed which explains 97% of the variation in the data, with 86% of the variation being explained by the rule that a compound will be found in groundwater if 6 < 0.55. Where 6χp is the sixth-order molecular path connectivity. One group of compounds cannot be classified by this rule and prediction requires reference to higher order connectivity parameters. The use of molecular approaches for understanding pollution at the molecular level and their application to agrochemical development and risk assessment is discussed.
ISSN:0013-936X
1520-5851
DOI:10.1021/es001593g