Engaging Communities to Discover Environmentally and Socially Optimal Waste Management Decisions

Waste management is a key stakeholder in the pursuit of many sustainability goals, for example, recycling of materials, utilization of organic wastes to generate energy and/or soil amendment while minimizing landfilling and can contribute to climate goals. Determining the best treatment options for waste streams, economically, environmentally, and socially for any given municipality is a complex decision dependent upon existing infrastructure, available funds, and local policy goals such as climate action plans. It is very difficult to evaluate options without the assistance of mathematical modeling to represent these systems, often referred to as decision support tools (DSTs). DSTs help to facilitate identification of the best solution given the characteristics of the waste stream, the existing infrastructure, specific policy goals in a given location. However, the tools can be challenging for nonexperts to use, and with the rapidly changing waste management landscape, they need updates to represent emerging waste management options and expand decisions beyond one or two metrics. This work engages stakeholders early and throughout the project to increase shared understanding of a widely used DST called the Solid Waste Optimization Life-Cycle Framework (SWOLF) and learn about the short- and longer-term targets for the stakeholders. This knowledge shapes technologies added to SWOLF as well as shape scenario analysis to best serve these stakeholders. SWOLF represents waste management options from a life cycle perspective; that is, the materials and energy flow across the entire chain of operations rather than just at the facility level and applies optimization techniques to allow for consideration of multiple objectives, in this case cost, carbon, and nutrients. Overall, this project provides better DSTs as well as uncover better approaches to developing DSTs that are more accessible to end users.

The overarching goal of this work is to transform decision-making toward environmentally, economically, and socially optimized waste management by improving model development through early and frequent engagement with stakeholders. Determining the best treatment options for waste streams, economically, environmentally, and socially for any given municipality is a complex decision dependent upon existing infrastructure, available funds, and local policy goals, e.g., climate action plans. Decision support tools exist for waste management; however, even the best among them have need for inclusion of ability to model novel management options and social impacts. In particular, these existing tools generally address waste management decisions with respect to a single objective, such as minimizing cost or emissions, and do not reflect the reality that decision makers need to select waste management alternatives on the basis of multiple, conflicting criteria. An 'alternative' waste management approach in this context is multi-faceted, consisting of a mix of potential investments in technologies, logistics resources, and manpower, which further argues for a systems modeling approach to addressing such questions. The project uses and enhances the Solid Waste Optimization Life-Cycle Framework (SWOLF) model for analysis of waste management strategies: (1) To identify mixes of strategies that optimize stakeholders' objectives with respect to cost savings, greenhouse gas reductions, and social impacts. (2) To create life cycle inventory (LCI) data for novel waste management options and integrate these into SWOLF expanding the set of SWOLF environmental and economic objectives to include an option for social benefit maximization. (3) The project's final modeling extension integrates the enhanced SWOLF model into a multi-objective optimization framework that identifies the efficient frontier of candidate solutions (across economic, environmental, and social objectives), and then helps direct a stakeholder to its preferred solution along that frontier. Using this extended modeling framework, waste management system analysis is applied using stakeholder-identified variables, metrics, and decision-making criteria. The intellectual merit of this project includes improving communication strategies between stakeholders and modelers, development of LCI data for novel waste treatment processes, improved multi-objective optimization modeling capacity for solid waste management, and waste management systems analysis tailored to stakeholders' geography and situation. The broader impacts of this project include undergraduate, graduate, and postdoctoral mentoring, networking across three academic institutions, and collaborating with a variety of stakeholders. Further, through model-presentation workshops the project improves the broader research communities' ability to create impact models and help waste management. The workshops also allow sustainability professionals make informed and aligned decisions based on their resources and goals.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.