Stochastic modelling of landfill processes incorporating waste heterogeneity and data uncertainty.
A landfill is a very complex heterogeneous environment and as such it presents many modelling challenges. Attempts to develop models that reproduce these complexities generally involve the use of large numbers of spatially dependent parameters that cannot be properly characterised in the face of data uncertainty. An alternative method is presented, which couples a simplified microbial degradation model with a stochastic hydrological and contaminant transport model. This provides a framework for incorporating the complex effects of spatial heterogeneity within the landfill in a simplified manner, along with other key variables. A methodology for handling data uncertainty is also integrated into the model structure. Illustrative examples of the model's output are presented to demonstrate effects of data uncertainty on leachate composition and gas volume prediction.
Zacharof
A I
AI
Centre for Environmental Control and Waste Management, Department of Civil and Environmental Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK. a.zacharof@imperial.ac.uk
Butler
A P
AP
D004785:Environmental Pollutants / Q000032:analysis*; D005544:Forecasting; D005740:Gases; D008962:Models, Theoretical; D012037:Refuse Disposal; D015203:Reproducibility of Results; D018505:Waste Management
D004785:Environmental Pollutants; D005740:Gases