Preliminary Assessment of a Biogas-based Power Plant from Organic Waste in the North Netherlands

Environmental assessment of the production of itaconic acid from wheat straw under a biorefinery approach

This study performs the environmental assessment of itaconic acid (IA) production from wheat straw. The Life Cycle Assessment (LCA) methodology is used to determine the environmental hotspots, considering impact categories such as Global Warming (GW), Fossil Resource Scarcity (FRS), Water Consumption (WC), among others. A sensitivity analysis was performed considering an optimization of the steam explosion process and 100% renewable energy. Results report an impact of about 14.33 kg CO₂ eq in GW, 4.15 kg of oil eq in FRS, for each kg of IA produced for the baseline scenario. Moreover, the pretreatment and fermentation stages constitute hotspots of the IA production. In addition, using a renewable energy source in production would reduce the impact by 82% in GW, 71% in PM and 82% in FRS categories. The optimization of the steam explosion process presents a better performance in GW and FRS but also lies in an increase in WC.

Integration of Artificial Intelligence into Biogas Plant Operation

In the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the following sections, the current situation of implementations of Artificial Intelligence in the biogas plant operation and in the similar industries will be represented. Moreover, considering that all the information gathered from literature and operational needs, an implementation model will be presented.