Author Information

V. A. Lancaster
S. Keller-McNulty

Abstract

As an alternative to retesting, the use of inverse theory techniques is proposed to resolve the lack of information inherent in composite sampling methods. This paper evaluates the feasibility of combining composite sampling with the inverse theory technique of linear regularization on an environmental site characterization investigation. Federal legislation has mandated the cleanup of hazardous waste sites, creating the need to characterize these sites for various chemical constituents. An abundance of samples, high measurement costs, and limited budgets create the appeal of compositing samples. We propose that the number of costly laboratory analyses can be reduced by combining composite sampling and inverse theory techniques. The goal of the paper is to estimate the constituent concentration for the sample units used to construct the composite .

A novel application of linear regularization is illustrated with a data set from an environmental investigation into mercury contamination at a waste disposal site in New Mexico. The disposal site has measurements at both the composite and sample unit level. This allows for a rare opportunity to evaluate the assumptions made about the compositing process and to compare estimates based on composite measurements with estimates based on sample unit measurements .

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Apr 27th, 2:00 PM

THE USE OF INVERSE THEORY ON AN ILL-POSED ENVIRONMENTAL COMPOSITE SAMPLING PROBLEM

As an alternative to retesting, the use of inverse theory techniques is proposed to resolve the lack of information inherent in composite sampling methods. This paper evaluates the feasibility of combining composite sampling with the inverse theory technique of linear regularization on an environmental site characterization investigation. Federal legislation has mandated the cleanup of hazardous waste sites, creating the need to characterize these sites for various chemical constituents. An abundance of samples, high measurement costs, and limited budgets create the appeal of compositing samples. We propose that the number of costly laboratory analyses can be reduced by combining composite sampling and inverse theory techniques. The goal of the paper is to estimate the constituent concentration for the sample units used to construct the composite .

A novel application of linear regularization is illustrated with a data set from an environmental investigation into mercury contamination at a waste disposal site in New Mexico. The disposal site has measurements at both the composite and sample unit level. This allows for a rare opportunity to evaluate the assumptions made about the compositing process and to compare estimates based on composite measurements with estimates based on sample unit measurements .