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An Empirical Approach to the Performance Assessment of Solid Waste Landfills

Department of Engineering and Environmental Management, Air Force Institute of Technology (AFIT/ENV, Bldg 640), 2950 P Street, Wright-Patterson Air Force Base, Ohio 45433-7765, U.S.A.

R.J. Murphy

Department of Civil and Environmental Engineering, University of South Florida, ENB 118, 4202 E. Fowler Ave , Tampa, FL 33620-5350, U S.A.

R.I. Stessel

Department of Civil and Environmental Engineering, University of South Florida, ENB 118, 4202 E. Fowler Ave , Tampa, FL 33620-5350, U S.A.

Several methods and models have been developed to simulate or assess the probability, magnitude and potential consequences of the leakage of aqueous environmental contaminants from solid waste landfills and similar facilities. The various models incorporate many common factors, including climatological and geological char acteristics. Each model, however, employs a unique approach to the problem, assigns different relative weights to factors, and relies upon extrapolation of small-scale experimental data and/or the designers' subjective judgment in predicting the various mechanisms of full-scale landfill failure that lead to contaminant migration. As a result, no two models are likely to yield the same assessment of a given facility, and no one model has been validated as a predictor of long-term landfill performance. More than 500 landfills, virtually all unlined and now closed, were analyzed to determine the correlation between a multitude of observable parameters and the actual performance of these landfills over periods up to 90 years. Landfill surface area, seismic impact, freeze/thaw cycling, potential evaporation relative to pre cipitation, and several other factors were found to be significantly correlated with performance. The results of this empirical analysis suggest that the many existing models may be refined to acknowledge relevant landfill performance parameters, and their relative weights and critical values. © 1997 ISWA

Key Words: Environmental risk • model • leachate • solid waste • contaminant migration • landfill • monitoring.

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