Application of Optimization and Modeling for the Composting Process Enhancement

Abstract

Composting is a more environmentally friendly and cost-effective alternative to digesting organic waste and turning it into organic fertilizer. It is a biological process in which polymeric waste materials contained in organic waste are biodegraded by fungi and bacteria. Temperature, pH, moisture content, C/N ratio, particle size, nutrient content and oxygen supply all have an impact on the efficiency of the composting process. To achieve optimal composting efficiency, all of these variables and their interactions must be considered. To this end, statistical optimization techniques and mathematical modeling approaches have been developed over the years. In this paper, an overview of optimization and mathematical modeling approaches in the field of composting processes is presented. The advantages and limitations of optimization and mathematical modeling for improving composting processes are also addressed.

Effects of Functionalized Materials and Bacterial Metabolites on Quality Indicators in Composts

“…Composting represents the group of processes termed as environmentally friendly. Currently, many researchers are working to develop integral composting models capable of describing and predicting various physicochemical and biochemical changes that occur during the biological transformation of waste [ 9 ]. However, this is not the only field where intensive research work is being carried out.…”

“…However, it should be stressed that the size and type of organic material resources are not the only elements that determine a successful composting process. According to Sokač et al [ 9 ], the operational efficiency of the composting process depends on numerous variables such as temperature, pH, moisture content, and the C/N ratio. The cited authors have stated that in order to achieve optimal composting efficiency, all variables and their relationships must be considered at the same time.…”

“…Currently, many researchers are working to develop integral composting models capable of describing and predicting all physicochemical and biochemical changes that occur during the biological transformation of waste [ 9 ]. At the same time, there is research being conducted to identify alternative additives to use in composted biomass to optimize the biochemical processes taking place during waste conversion.…”

Special Issue: Mathematical Modeling and Control of Bioprocesses

“…Sokač et al [8] review the application of mathematical modeling and optimization for enhancing composting, which is a complex process whose efficiency is influenced by temperature, pH, moisture content, C/N ratio, particle size, nutrient content and oxygen supply. In [9], Djema et al derive optimal control strategies based on the Pontryagin maximum principle in order to ensure the domination of the strain of interest in cultures of microalgae in the chemostat described by the Droop model.…”

Comparisons of Bayes factors for 𝟐𝟒 full, fractional, and reduced factorial designs

“…In educational research, the Bayesian analysis for treatment and control groups was discussed through factorial designs (Kassler et al, 2020). The limitations of optimization and mathematical model for improving composting processes are addressed (Sokac et al, 2022). Outlined a thorough knowledge of Bayesian variable selection, Bayesian evaluation of cognitive models (Heck et al, 2022), and opportunities for Bayes factor applications.…”