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RECORD NUMBER: 49 OF 982

OLS Field Name OLS Field Data
Main Title Asymmetric Loss Function for Superfund Remediation Decisions.
Author Flatman, G. T. ; Englund, E. J. ;
CORP Author Environmental Monitoring Systems Lab., Las Vegas, NV.
Publisher 1992
Year Published 1992
Report Number EPA/600/A-92/207;
Stock Number PB93-106763
Additional Subjects Superfund ; Remedial action ; Environmental monitoring ; Sampling ; Waste management ; Concentration(Composition) ; Hazardous materials ; Decision making ; Asymmetry ; Numerical analysis ; Error analysis ; Public health ; Nomographs ; Reprints ; Loss function ; Cleanup operations
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB93-106763 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/08/1993
Collation 8p
Abstract
At a Superfund remediation site the decision is a classification problem, discriminating between polluted blocks to be remediated and background blocks to be left untreated. The concentration of the pollutant in a block is estimated from sampling. The more samples taken the better the estimates, but what is the optimum sample size. The errors are computed by subtracting the estimate from the block averages of an exhaustive sampling. The time-honored least squares algorithm is the obvious way to evaluate a given sample size, but least squares assumes a symmetric loss function. Superfund remediation has an asymmetric cost-plus-loss function; false positives (clean blocks judged dirty) have a relatively small fixed cost while false negative (polluted blocks judged clean) have public-health-losses that increase with concentration. Minimizing an asymmetric cost-plus-loss function will find a different optimum sample size than would the traditional least squares approach.