A review of mathematical models for composting

Area of Science:

• Environmental Science
• Biotechnology
• Chemical Engineering

Background:

• Composting is a vital process for managing organic waste.
• The complex, dynamic nature of composting involves numerous operating parameters.
• Mathematical modeling offers a powerful approach to simulate, predict, and optimize composting outcomes.

Purpose of the Study:

• To provide an up-to-date review and assessment of the state-of-the-art in composting modeling.
• To analyze trends in composting modeling over the past 40 years.
• To identify areas for future development in composting modeling.

Main Methods:

• Comprehensive literature review of 40 years of composting modeling research.
• Analysis of trends in targeted systems, model objectives, kinetics, and mass/heat transfer.
• Exploration of substrate/microorganism fractionation, biological processes, kinetics, energy, and mass balances.

Main Results:

• Models are most sensitive to microbial growth/death rates, consumption rates, and product yields.
• Identified trends in modeling approaches, including biological processes and kinetic models.
• Sensitivity analyses highlight critical parameters for accurate composting simulations.

Conclusions:

• Mathematical modeling is crucial for optimizing composting efficiency, cost, and environmental impact.
• Further research is needed in areas like volume change, pH, maturation, and artificial intelligence in composting models.
• This review provides a foundation for developing more advanced and predictive composting models.