Comparison of simulated pesticide concentrations in surface drinking water with monitoring data: explanations for observed differences and proposals for a new regulatory modeling approach. 2014

Michael F Winchell, and Nathan J Snyder
Stone Environmental, Inc. , 535 Stone Cutters Way, Montpelier, Vermont 05602, United States.

A primary component to human health risk assessments required by the U.S. Environmental Protection Agency in the registration of pesticides is an estimation of concentrations in surface drinking water predicted by environmental models. The assumptions used in the current regulatory modeling approach are designed to be "conservative", resulting in higher predicted pesticide concentrations than would actually occur in the environment. This paper compiles previously reported modeling and monitoring comparisons and shows that current regulatory modeling methods result in predictions that universally exceed observed concentrations from the upper end of their distributions. In 50% of the modeling/monitoring comparisons, model predictions were more than 229 times greater than the observations, while, in 25% of the comparisons, model predictions were more than 4500 times greater than the observations. The causes for these overpredictions are identified, followed by suggestions for alternative modeling approaches that would result in predictions of pesticide concentrations closer to those observed.

UI MeSH Term Description Entries
D008962 Models, Theoretical Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D009010 Monte Carlo Method In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993) Method, Monte Carlo
D010575 Pesticides Chemicals used to destroy pests of any sort. The concept includes fungicides (FUNGICIDES, INDUSTRIAL); INSECTICIDES; RODENTICIDES; etc. Pesticide
D004784 Environmental Monitoring The monitoring of the level of toxins, chemical pollutants, microbial contaminants, or other harmful substances in the environment (soil, air, and water), workplace, or in the bodies of people and animals present in that environment. Monitoring, Environmental,Environmental Surveillance,Surveillance, Environmental
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D014481 United States A country in NORTH AMERICA between CANADA and MEXICO.
D014484 United States Environmental Protection Agency An agency in the Executive Branch of the Federal Government. It was created as an independent regulatory agency responsible for the implementation of federal laws designed to protect the environment. Its mission is to protect human health and the ENVIRONMENT. Environmental Protection Agency (U.S.),Environmental Protection Agency,Environmental Protection Agency, United States,USEPA
D014874 Water Pollutants, Chemical Chemical compounds which pollute the water of rivers, streams, lakes, the sea, reservoirs, or other bodies of water. Chemical Water Pollutants,Landfill Leachate,Leachate, Landfill,Pollutants, Chemical Water
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D060766 Drinking Water Water that is intended to be ingested. Bottled Water,Potable Water,Water, Bottled,Water, Drinking,Water, Potable

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