• Energy Research

In Poland, special attention is focused on sustainable municipal waste management. As a result, new waste incineration plants are being planned. They are considered to be modern, ecologically friendly, and renewable energy sources. The waste from conventional incineration, which contains hazardous substances, must be disposed of in an appropriate manner. This study used advanced statistical tools, such as control charts, trend analysis, and time series analysis. The analysis was based on the leachability of selected elements and chemical compounds in incineration bottom ashes (IBAs) from the Waste to Energy Plant in Kraków, which were weathered for 2 weeks. The analysis was performed for 34 weeks. The obtained leachability results were compared with the leachability limit values of individual components. Based on the analysis of the control charts, it was found that in the case of selected samples, the leachability limit values for processing outside the plant using the R5 recovery process (LLVR5) values were exceeded. Seasonality analysis was performed using the autocorrelation function (ACF), the partial autocorrelation function (PACF), and the frequency analysis. Based on the obtained results, it was concluded that the leachability of elements and chemical compounds from waste does not confirm the occurrence of seasonality. It was found that from the exceedances of the LLVR5 mean that the two-week weathering is not sufficient and further studies should be carried out. The research methodology, which was presented on the example of the leachability of elements and compounds from IBA, can also be used for other waste analyses.

Selection of the optimal properties of coal as a natural sorbent, both as a sample collected from a seam or of the coal seam itself, requires various parameters to be determined and may not be based on the knowledge of metamorphism degree only. In order to improve the predictions of sorption capacity and the kinetics, analyses of correlation and multiple regression based on the results of laboratory studies were performed for 15 coal samples with various coal rank. The maximum vitrinite reflectance (R0) for low-rank coals was 0.78%–0.85%, and 0.98%–1.15% and 1.85%–2.03% for medium- and high-rank coals, respectively. Coal samples were subjected to technical and petrographic analysis. The gravimetric method was used to perform sorption tests using methane, in order to determine the sorption capacity and the effective diffusion coefficient for each of the coals. Pycnometric methods were used to determine the textural parameters of coals, such as the percentage porosity and specific pore volume. The studies were further supplemented with an evaluation of the mechanical properties of the coals, Vickers micro-hardness, and elastic modulus. This work shows that the statistical multiple regression method enables a computational model including the selected petrophysical parameters displaying synergy with the specific sorption property—capacity or kinetics—to be created. The results showed the usefulness of this analysis in providing improved predictions of the optimal sorption properties of coal as a natural sorbent.