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Solid waste management (SWM) is an integral component of civil infrastructure and the broader U.S. economy, and policy makers have taken an increasing interest in reducing environmental impacts associated with SWM. In the future, greenhouse gas (GHG) mitigation policies that affect the U.S. energy mix as well as the cost of energy and emissions could significantly impact the strategic direction of SWM. As such, SWM systems must proactively adapt to changing waste composition, policy requirements, and an evolving energy system to cost-effectively and sustainably manage future solid waste. 

SWM life-cycle assessment (LCA) models integrated into an optimization framework can simultaneously consider all possible waste collection and treatment alternatives to find the combination of technologies that optimizes environmental and economic objectives. Such a framework should also be able to represent multi-stage decisions to consider the changes to the SWM system over time. 

The goal of this research was to develop an LCA model capable of analyzing SWM performance – at both the individual process and integrated system levels – taking into account implications of GHG mitigation policies and competing SWM objectives (e.g., costs, emissions, and diversion targets). The Solid Waste Optimization Life-cycle Framework (SWOLF) was developed to perform analysis of SWM as an integrated system. SWOLF is an open source modeling framework capable of developing and evaluating optimal SWM strategies over time while considering changes to waste generation and composition as well as fuel and electricity prices and emissions (go.ncsu.edu/swolf). SWOLF couples a set of life-cycle process models with a multi-stage optimization model that is used to minimize the cost or environmental impacts of a user-defined SWM system over time.