

Almost 850 organic and green waste composting plants are operated in Germany (Federal Statistical Office 2019), which produce climate-damaging methane during the composting process. The release of such greenhouse gas emissions is influenced by a variety of factors such as the nature of the source material, the composting process used, the geometry of the windrows and external factors (temperature, precipitation, air exchange, etc. ).
Composting is a biological process with parallel conversion, decomposition and degradation processes. The microbiological population changes constantly during composting depending on the environment – aerobic or anaerobic. Under anaerobic conditions in particular, considerable quantities of greenhouse gases are released. In order to ensure aerobic conditions, a good oxygen supply in the so-called windrow body is necessary. The decision as to when to intervene in the composting process is usually made by the respective employees based on their experience. The composting process is often only monitored and controlled on a random basis.
In the current project, a sensor- and AI-based measurement and forecasting system is to be developed and tested on a technical scale, with which degradation processes during composting can be monitored and controlled based on models. In addition to fulfilling regulatory and legal requirements, this will enable plant operators to plan, implement and document operating processes, personnel and machine deployment as well as emission protection measures based on data for the first time. Early forecast-based process control can prevent anaerobic environment conditions, reduce greenhouse gas emissions by 50 to 90 % and significantly improve compost quality. Digital data acquisition, transmission and evaluation also enables the integration of decentralized operating sites at any distance from a company’s headquarters.