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This article in JEQ

  1. Vol. 36 No. 2, p. 508-520
    Received: Nov 11, 2005

    * Corresponding author(s): marc_serre@unc.edu
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Spatiotemporal Nonattainment Assessment of Surface Water Tetrachloroethylene in New Jersey

  1. Yasuyuki Akitaa,
  2. Gail Carterb and
  3. Marc L. Serre *a
  1. a Dep. of Environmental Science & Engineering, School of Public Health, Univ. of North Carolina-Chapel Hill, Rosenau Hall CB# 7431 Chapel Hill, NC 27599-7431
    b New Jersey Dep. of Environmental Protection, Division of Science, Research, and Technology, P.O. Box 409, Trenton, NJ 08625-0409


Tetrachloroethylene (PCE) is one of the most frequently detected volatile organic compounds (VOCs) in water systems across the USA. In New Jersey, the Department of Environmental Protection (NJDEP) monitors surface water quality at several sites throughout the state. However due to budget and scientific limitations, the sampling data is insufficient to assess all river streams in New Jersey. To address this problem, the objective of this study is to utilize a framework for the space/time estimation of PCE throughout all river reaches in New Jersey over the 1999 through 2003 time period and to track how this concentration evolves over time. We use the Bayesian maximum entropy (BME) mapping method to take into account the composite spatiotemporal variability of PCE, and we produce maps providing a stochastic description of the distribution of PCE at all times throughout the river network. In addition, we conduct a nonattainment assessment analysis by applying a criterion based on the estimated probability distribution function that allows us to identify the river miles that are highly likely in nonattainment of the standard, those that are highly likely in attainment of the standard, and the remaining labeled as nonassessed. Using this criterion we investigate how the river miles contaminated by PCE vary over space and time, and we identify watershed management areas (WMAs) with contamination problems. Finally, a cross validation comparison with a purely spatial analysis demonstrates that the space/time framework leads to a better estimation and a reduction of the number of nonassessed miles.

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