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Assessing Contaminant Mobilization from Waste Materials: Application of Bayesian Parameter Estimation to Batch Extraction Tests at Varying Liquid-to-Solid Ratios
- Source :
- Environmental Science & Technology. 42:3717-3723
- Publication Year :
- 2008
- Publisher :
- American Chemical Society (ACS), 2008.
-
Abstract
- We investigated the release of chloride, sulfate, sodium, copper, chromium, and dissolved organic carbon from a demolition waste material and a municipal waste incineration product Batch leaching tests at the liquid-to-solid ratios (L/S ratios) 1, 2, 5, 10, and 50 L kg(-1) were carried out and the parameters of a mass balance-partitioning model were estimated from measured concentrations in the extracts by applying a Bayesian approach using a Markov Chain Monte Carlo sampler. We assessed the uncertainty of the model parameters, the desorption isotherms, and the model-predicted concentrations, respectively. Both the excellent fit to the experimental data and a comparison between the model-predicted and independently measured concentrations at the L/S ratios of 0.25 and 0.5 L kg(-1) showed the applicability of the model for almost all studied substances and both materials. Since experimental difficulties impede extraction tests at L/S ratios representative of field soil-water contents, the predictability of concentrations in this range is of great practical relevance for risk assessments. We conclude that batch extraction tests at varying L/S ratios provide, at moderate experimental cost, a powerful complement to established test designs like column leaching or single batch extraction tests.
- Subjects :
- Municipal solid waste
Environmental engineering
Analytical chemistry
chemistry.chemical_element
Bayes Theorem
Incineration
General Chemistry
Models, Theoretical
Chloride
Refuse Disposal
Chromium
chemistry.chemical_compound
Explosive Agents
chemistry
Desorption
Dissolved organic carbon
medicine
Environmental Chemistry
Environmental Pollutants
Leaching (metallurgy)
Sulfate
medicine.drug
Subjects
Details
- ISSN :
- 15205851 and 0013936X
- Volume :
- 42
- Database :
- OpenAIRE
- Journal :
- Environmental Science & Technology
- Accession number :
- edsair.doi.dedup.....dcd304f2a87fb2b01ff597c747192bcf
- Full Text :
- https://doi.org/10.1021/es702171z