The article discusses an innovative system used for aerobic biostabilisation and biological drying of solid municipal waste. A mechanical–biological process (MBT) of municipal solid waste (MSW) treatment were carried out and monitored in 5 bioreactors. A two-stage biological treatment process has been used in the investigation. In the first step an undersize fraction was subjected to the biological stabilisation for a period of 14 days as a result of which there was a decrease of loss on ignition, but not sufficient to fulfill the requirements of MBT technology. In the second stage of a biological treatment has been applied 7-days intensive bio-drying of MSW using sustained high temperatures in bioreactor. The article presents the results of the chemical composition analysis of the undersize fraction and waste after biological drying, and also the results of temperature changes, pH ratio, loss on ignition, moisture content, combustible and volatile matter content, heat of combustion and calorific value of wastes. The mass balance of the MBT of MSW with using the innovative aeration system showed that only 14.5% of waste need to be landfilled, 61.5% could be used for thermal treatment, and nearly 19% being lost in the process as CO2 and H2O.

This paper presents a voltammetric segmented voltage sweep mode that can be used to identify and measure heavy metals' concentrations. The proposed sweep mode covers a set of voltage ranges that are centered around the redox potentials of the metals that are under analysis. The heavy metal measurement system can take advantage of the historical database of measurements to identify the metals with higher concentrations in a given geographical area, and perform a segmented sweep around predefined voltage ranges or, alternatively, the system can perform a fast linear voltage sweep to identify the voltammetric current peaks and then perform a segmented voltage sweep around the set of voltages that are associated with the voltammetric current peaks. The paper also includes the presentation of two auto-calibration modes that can be used to improve system's reliability and proposes the usage of a Gaussian curve fitting of voltammetric data to identify heavy metals and to evaluate their concentrations. Several simulation and experimental results, that validate the theoretical expectations, are also presented in the paper.