Multi-Stakeholder Decision-Making for the Development of Livestock Waste-to-Biogas Systems

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

1604374 PI: Zavala Tejeda Title: Multi-Stakeholder Decision-Making for the Development of Livestock Waste-to-Biogas Systems Livestock waste generated at U.S. animal feeding operations is estimated to be 300 million tons per year. Most of this waste is disposed of in lagoons or stored outdoors to decompose, leading to numerous environmental issues such as greenhouse gas (methane and nitrous oxide) and ammonia emissions, eutrophication of surface waters resulting from phosphorus runoff, and human exposure to pathogenic bacteria. Biogas production from livestock waste provides a promising alternative to address these issues while providing a wide range of valuable byproducts such as electricity, bedding, and organic fertilizer. The EPA's AgSTAR program reports that about 8,000 U.S. farms could support biogas systems, providing about 1,600 MW of electricity (enough to power one million homes) and reducing methane emissions by 1.8 million metric tons (equivalent to taking 6.5 million cars off the road). Despite this potential, the development of biogas systems has been limited by high technology costs, competing prices for natural gas obtained from non-renewable sources, and limited government policies and incentives. This project aims to develop optimization models and the necessary solution approaches as a multi-stakeholder decision making tool for developing biogas production systems from livestock waste. The proposed work is cross-disciplinary, combining ideas from multi-objective and stochastic optimization, social choice and economics, high-performance computing, and agricultural and energy systems. A key scientific objective of the proposed project is the development of computationally efficient solution strategies for multi-stakeholder, multi-objective optimization problems. The proposed project will pioneer the incorporation of credible social objective metrics into optimization models. The PIs propose new metrics for incorporating the impact of decisions on multiple stakeholders into the model. The models developed will capture a wider range of technologies and configurations not considered before. In particular, the PIs will model interactions between waste transport, storage, and processing systems, feedstocks and nutrient management systems, biogas and electricity production and delivery systems, and district utility systems. The ability to couple these systems will provide new opportunities to achieve economic viability and to evaluate environmental and social impacts. The developed frameworks will identify socially-optimal compromise solutions that factor in the priorities of multiple stakeholders (urban/rural communities, environmental groups, farmers, technology providers, and local/regional governments). This will be achieved by using statistical metrics, such as the conditional value at risk and the generalized entropy index. The use of these metrics will enable policy makers to assess the impact of their decisions on stakeholder satisfaction. The project team has access to real data sets and a group of stakeholders for formulating realistic case studies that may have immediate impact on the decision-making processes of the involved stakeholders. The PIs plan to train a PhD student and develop new teaching materials for undergraduate and graduate courses. They also propose outreach activities to increase public awareness on the effects of methane emissions from animal farms and recruit students from underrepresented minorities into STEM fields.