Optimising waste management technologies through statistical entropy analysis: A quantitative approach to enhanced resource recovery

Abstract

The recovery of valuable materials from waste streams is essential to achieving global sustainability. Despite the variety of waste management technologies available, systematic and quantitative methods for evaluating and optimising their performance remain limited. This study addresses this gap by focusing on the optimisation of waste management technologies through the statistical entropy analysis (SEA). For the case study, the FLUWA® (fly ash washing) technology for recovering Zn, Pb, and Cu from municipal solid waste incineration (MSWI) fly ash was chosen. Four technology configurations, varying in material intensity and metal recovery efficiency, were analysed. The assessment used a comprehensive dataset from long-term monitoring (2018–2022), complemented by laboratory and pilot-scale experiments. It included the chemical composition and properties of the technological streams. After statistical data treatment (removal of outliers, calculation of mean values and standard deviations), a material flow analysis (MFA) was performed. Subsequently, SEA was applied to quantify changes in statistical entropy (SE). The results show that the basic configuration of FLUWA® increases SE (ΔHMETALS=+3.4 %), indicating dilution and loss of target metals. Optimisation of the extraction step led to substantial entropy reductions (ΔHMETALS =−16.3 % and ΔHMETALS=−23.8 % in two optimised cases), reflecting enhanced metal recovery and reduced dissipation. Additionally, coagulation and flocculation were found to have no effect on SE (ΔHMETALS=0), suggesting that these steps may be redundant from the perspective of metal recovery. By identifying inefficiencies and opportunities for process enhancement, SEA supports the transition toward more effective waste management systems and promotes the circular economy.