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This article in JEQ

  1. Vol. 41 No. 4, p. 1238-1245
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    Received: July 29, 2011
    Published: July, 2012


    * Corresponding author(s): tmzimmer@usgs.gov
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doi:10.2134/jeq2011.0271

Evaluating Changes in Matrix-Based, Recovery-Adjusted Concentrations in Paired Data for Pesticides in Groundwater

  1. Tammy M. Zimmerman *a and
  2. Kevin J. Breena
  1. a U.S. Geological Survey, Pennsylvania Water Science Center, 215 Limekiln Rd., New Cumberland, PA 17070. Chemical names of all the pesticide compounds mentioned in this paper are listed in Supplemental Table S1. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Assigned to Associate Editor Pierre Benoit

Abstract

Pesticide concentration data for waters from selected carbonate-rock aquifers in agricultural areas of Pennsylvania were collected in 1993–2009 for occurrence and distribution assessments. A set of 30 wells was visited once in 1993–1995 and again in 2008–2009 to assess concentration changes. The data include censored matched pairs (nondetections of a compound in one or both samples of a pair). A potentially improved approach for assessing concentration changes is presented where (i) concentrations are adjusted with models of matrix-spike recovery and (ii) area-wide temporal change is tested by use of the paired Prentice-Wilcoxon (PPW) statistical test. The PPW results for atrazine, simazine, metolachlor, prometon, and an atrazine degradate, deethylatrazine (DEA), are compared using recovery-adjusted and unadjusted concentrations. Results for adjusted compared with unadjusted concentrations in 2008–2009 compared with 1993–1995 were similar for atrazine and simazine (significant decrease; 95% confidence level) and metolachlor (no change) but differed for DEA (adjusted, decrease; unadjusted, increase) and prometon (adjusted, decrease; unadjusted, no change). The PPW results were different on recovery-adjusted compared with unadjusted concentrations. Not accounting for variability in recovery can mask a true change, misidentify a change when no true change exists, or assign a direction opposite of the true change in concentration that resulted from matrix influences on extraction and laboratory method performance. However, matrix-based models of recovery derived from a laboratory performance dataset from multiple studies for national assessment, as used herein, rather than time- and study-specific recoveries may introduce uncertainty in recovery adjustments for individual samples that should be considered in assessing change.

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Copyright © 2012. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.