The Application of a Statistical Trend Analysis Model to Ground Water Monitoring Data from Solid Waste Landfills |
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| Authors: | Amy D Lachance Michael R Stoline |
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| Institution: | Amy D. Lachance received her bachelor's degree in geology from Dartmouth College in 1984 and her master's degree in geology from Western Michigan University in 1992. She is currently employed by the Michigan Department of Environmental Quality (Waste Management Division, 350 Ottawa NW, Grand Rapids, MI 49503) as a district geologist.;Michael R. Stoline received his Ph.D. in statistics from the University of Iowa in 1967. He is a professor in the Department of Mathematics and Statistics at Western Michigan University (Kalamazoo, MI 49008). His current research focus is the development and implementation of statistical procedures to improve our understanding and management of hazardous environmental sites. |
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| Abstract: | A statistical trend methodology is used to compare ground water quality between eight landfill sites in western Michigan as a case study. Monitoring data were collected over a 15-year period on 36 parameters at an upgradient and downgradient well selected at each of the eight sites. This yielded a total of 576 monitoring data sets available for analysis. New trend and contamination indices are introduced that are used to compare ground water contamination between these eight sites. These indices are used to assess each landfill's relative potential for environmental harm.
Many questions remain unanswered, but what is demonstrated here is that this type of methodology has the potential to be used to assess trends of ground water chemistry concentrations at landfill sues in a region. A specific purpose of such an assessment could be to provide a quantified basis for the prioritization of funds allocated for cleanup of contaminated landfill sites. Having a technical capability to reduce large amounts of ground water monitoring data to appropriate summaries, which then can be used to assess environmental contamination between several sites, could also have important economic and health implications in other settings. Hopefully this paper will encourage further development of such technologies for these purposes. |
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