Literature DB >> 22370411

Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States.

Paul E Stackelberg1, Jack E Barbash, Robert J Gilliom, Wesley W Stone, David M Wolock.   

Abstract

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 μg L. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.
Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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Year:  2012        PMID: 22370411     DOI: 10.2134/jeq2011.0200

Source DB:  PubMed          Journal:  J Environ Qual        ISSN: 0047-2425            Impact factor:   2.751


  4 in total

1.  Spatial distribution of triazine residues in a shallow alluvial aquifer linked to groundwater residence time.

Authors:  Lara Sassine; Corinne Le Gal La Salle; Mahmoud Khaska; Patrick Verdoux; Patrick Meffre; Zohra Benfodda; Benoît Roig
Journal:  Environ Sci Pollut Res Int       Date:  2016-07-22       Impact factor: 4.223

2.  Estimating the High-Arsenic Domestic-Well Population in the Conterminous United States.

Authors:  Joseph D Ayotte; Laura Medalie; Sharon L Qi; Lorraine C Backer; Bernard T Nolan
Journal:  Environ Sci Technol       Date:  2017-10-18       Impact factor: 9.028

Review 3.  A review of nonoccupational pathways for pesticide exposure in women living in agricultural areas.

Authors:  Nicole C Deziel; Melissa C Friesen; Jane A Hoppin; Cynthia J Hines; Kent Thomas; Laura E Beane Freeman
Journal:  Environ Health Perspect       Date:  2015-01-30       Impact factor: 9.031

4.  Hypospadias and maternal exposure to atrazine via drinking water in the National Birth Defects Prevention study.

Authors:  Jennifer J Winston; Michael Emch; Robert E Meyer; Peter Langlois; Peter Weyer; Bridget Mosley; Andrew F Olshan; Lawrence E Band; Thomas J Luben
Journal:  Environ Health       Date:  2016-07-15       Impact factor: 5.984

  4 in total

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