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.
Highlights
The steady growth of industrial production and trade in many countries of the world has led to a rapid increase in the generation of municipal and industrial waste in the last decade [1]
Method based on fuzzy logic; Methods based on artificial neural networks; Methods based on metaheuristic algorithms: 1
Statistical optimization methods based on design of experiments and artificial neural network modeling are the mostly used [11]
Summary
The steady growth of industrial production and trade in many countries of the world has led to a rapid increase in the generation of municipal and industrial waste in the last decade [1]. The optimization of the compost maturity (expressed as pH, or electrical conductivity, final C/N ration, germination index or ash content) requires appropriate set-up design of C/N ratio, moisture content, and aeration rate to ensure the conditions suitable for the microbial population growth which controls the organic matter degradation and, respectively, compost maturity [11,12]. Stability is a term that refers to the resistance of a product’s organic matter to extensive degradation or to greater microbiological activity, while maturity describes the ability of a product to be used effectively in agriculture and is related to plant growth and phytotoxicity aspects. Considering the difficulties and costs associated as noted by Mason [30], mathematical models can reduce or even replace the need for with conducting laboratory and pilot experiments, it is desirable to improve the ability experimental work when investigating novel processes. A comprehensive systematic review of the important scientific articles was conducted using the core collection in the Web of Science database for the period of the last 21 years
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