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Stochastic Model of the Diffusion of Pollutants in Landfill Management Using Monte Carlo Simulation

  • Bogusław Bieda
Chapter

Abstract

Hazardous waste landfills, as well as landfills for other than hazardous or inert waste, require the application of technical solutions that comply with the Regulation of the Minister of Environment of 24 March 2003 on the detailed requirements regarding the location, construction, operation and closure, that should to be met by the particular types of landfills (D.U. 2003) (Official Journal “Dz. U.” No. 61, item 549). In line with the requirements of the abovementioned regulation, it is necessary to isolate the deposited waste from the subsoil with a natural geological barrier. This applies to the other than hazardous or inert waste with the thickness no less than 1 m (for the hazardous waste it is 5 m) and the filtration coefficient (diffusion) k ≤ 1.0 × 109 m/s. If artificial geological barrier is to be used, its thickness cannot be less than 0.5 m and the permeability cannot be greater than that of the natural barrier. Synthetic isolation needs to supplement the natural or artificial geological barrier, depending on which one is used. The shape of the basin needs to make it impossible for the precipitation water from the surrounding area to flow into the basin. A drainage system should be built at the bottom and on the slopes of the landfill that would ensure its reliable functioning during the service life of the landfill and during the period of 30 years after its closure. Uncertainty can be described with the help of parameters such as variance (informing about the distribution of a random variable value) or standard deviation, or with the help of other statistical methods, e.g. the MC method. The employment of MC simulation for the modelling of propagation delay of waste in porous media is a very useful tool that can be used to assess the life cycle of a modern landfill.

Keywords

Hydraulic Conductivity Subject Literature Retardation Coefficient Isolation Barrier Geological Barrier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Faculty of ManagementAGH University of Science and TechnologyKrakówPoland

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