Modeling and optimization of composting technology

How to efficiently dispose of and utilize organic waste such as sewage sludge, green waste, food waste and livestock manure is a crucial issue to develop a healthy ecosystem. Composting technology has been used to treat organic waste and produce a high-valued byproduct. However, the inevitable harmful gases emissions, low efficiency of organic matter transformation, low quality of compost and high mobility of heavy metals have restricted the popularization and application of composting technology. During the last decades, many practical methods have been put forward to improve the composting and decrease the adverse effects. While, the performance of composting is closely related to the raw materials, composting scale, reactor and technological parameters, resulting in the results obtained from the pilot- and laboratory-scale composting cannot be reproduced in full scale composting. Although full-scale composting is closer to reality, it is difficult to control and use more resources. Composting modeling offers the potential to reduce or even replace the need for physical experiment and is also beneficial for reducing resource and time waste. Various kinds of composting models (e.g., physical model, mathematical model, and neural network) were built up to predict composting performance, understand the composting process, discover new theoretical concepts, and solve the composting practical problems. However, with the development of society and economy, there are new problems that occurred during the composting and new models need to be proposed to solve these problems. Understanding the basic concept and principle of composting models is important to modeling and optimization of composting.