Closed municipal and industrial waste landfill sites create potential hazard of ground water pollution. Pollutants that occur in leachate infiltrate to the soil substratum, where they are carried to in underground water. A municipal waste landfill substratum can be used for elimination of pollutants contained in leachates. Model research was performed with the use of a sand bed and artificially prepared leachates. Efficiency of filtration in a bed of defined thickness was assessed based on change of COD value. Results of the model tests have indicated that the mass of pollutants contained in leachate filtered through porous ground layer depends on the mass of supplied pollutants, intensity of supplied leachate, and layer thickness. Increase of the mass of pollutants supplied to a unit area of ground layer causes reduction of the relative value of COD mass. The method of evaluation of quality of water seeping through the aeration layer presented in this paper allows for estimation of the flowing out pollutants mass. Based on the test results obtained, efficiency of purification in the aeration zone can be assessed; likewise, safe thickness of the filtration layer under the landfill site can be designed.

In this paper we present results of research on the transformation of chemical forms of two elements (Cu, Zn) that occurred at the highest concentration in sewage sludge being processed in a composting process. The factor that had impact on the direction of the observed transformation was the amount of straw added to the mix with sewage sludge at the batch preparation stage including elimination of an additional source of organic carbon (straw). The analysis of contents of Cu and Zn chemical forms was performed applying Tessiere’s methodology. It was ascertained that reduction of supplementation has positive impact on the allocation of tested elements in organic (IV) and residual (V) fractions with a simultaneous decrease of heavy metals mobile forms share in bioavailable fractions, mostly ion exchangeable (I) and carbonate (II). Using an artificial neural network (ANN), a tool was developed to classify composts based on Austrian standards taking into account only I ÷ IV fractions treated as a labile, potentially bioavailable, part of heavy metals bound in various chemical forms in compost. The independent variables that were predictors in the ANN model were the composting time, C/N, and total content of the given element (total Cu, Zn). The sensitivity coefficients for three applied predictors varied around 1, which proves their significant impact on the final result. Correctness of the predictions of the generated network featuring an MLP 3-5-3 structure for the test set was 100%.

Landfill leachate makes a potential source of ground water pollution. Municipal waste landfill substratum can be used for removal of pollutants from leachate. Model research was performed with use of a sand bed and artificially prepared leachates. Effectiveness of filtration in a bed of specific thickness was assessed based on the total solids content. Result of the model research indicated that the mass of pollutants contained in leachate filtered by a layer of porous soil (m_f) depends on the mass of pollutants supplied (m_d). Determined regression functions indicate agreement with empirical values of variable m′_f. The determined regression functions allow for qualitative and quantitative assessment of influence of the analysed independent variables (m′_d, l, ω) on values of mass of pollutants flowing from the medium sand layer. Results of this research can be used to forecast the level of pollution of soil and underground waters lying in the zone of potential impact of municipal waste landfill.