Stochastic optimisation of organic waste-to-resource value chain.

Organic fraction municipal solid waste (OFMSW) has a high potential for energy and value-added product recovery due to its carbon- and nutrient-rich composition; however, traditional value chains have treated OFMSW as an undesired by-product. This study focuses on value chain optimisation to assist the transition to resource recovery value chains. To achieve this, this work combined two stage stochastic mathematical optimisation with geographical spatial analysis and time series waste generation analysis. Existing infrastructure in England, including anaerobic digestion plants and road transportation networks, were included in the model. To account for uncertainty in waste generation, multiple scenarios and their associated probabilities were developed based on environmental variables. The optimisation problem was solved to further advance the understanding of economically optimal waste-to-resource value chains under waste generation variability. The pertinent decision variables included sizing, technology selection, waste flows and location of thermochemical treatment sites. The model highlights the potential reduction in system profitability as a result of different operating constraints, such as minimum plant operating capacity factors and landfill taxation. The latter was shown to have the largest impact on profitability as overconservative systems designs were implemented to hedge against the waste variability. Such computer-aided models offer opportunities to overcome the challenges posed by waste generation variability and waste to resource value chain transformation.

Waste-to-Resource value chain optimisation: Combining spatial, chemical and technoeconomic aspects.

Due to complex composition of carbohydrates, lipid, protein, cellulose, hemicellulose and lignin, wastewater (WW) and organic fraction municipal solid waste (OFMSW) represent nutrient and carbon rich resources. Conventionally, value chains in the waste sector have considered OFMSW and WW as unwanted by-products as opposed to potential valuable resources. Full exploitation of these resources calls for a value chain transformation towards proactive resource recovery. This study focuses on the waste supply chain optimisation to recover value added products from OFMSW. The research leads to a systems-modelling approach, which integrates spatial data analyses, mathematical mixed integer linear programming (MILP) optimisation and technology performance evaluation to inform the design of waste-to-resource value chains. A UK based study on OFMSW is presented to demonstrate the efficacy of the approach. The study captures variation in OFMSW quantity and composition, incorporating over 600 existing anaerobic digestion (AD) operational plants in the UK, while potential sites for new waste-recovery facilities are identified, accounting for transportation and logistics, using a GIS-based analysis. Key outcomes are analysed (technology type, size, location, logistical connections), placing emphasis on the need to consider the value of the resource recovery potential over the lifetime of an AD or thermochemical treatment facility in the design process. Such an approach offers a promising pathway for tackling the open challenges currently hindering the waste-to-resource transformation.