Geographically-resolved life cycle assessment and techno-economic analysis of engineered climate solutions with an innovative framework for decision support

Abstract

The urgent challenge of addressing climate change requires a thorough evaluation of engineered solutions to ensure they are both economically viable and environmentally sustainable. This dissertation performs a comprehensive assessment of two key climate technologies: microalgae biorefineries for biofuel production and anaerobic digestion (AD) systems for reducing greenhouse gas (GHG) emissions on dairy farms. Using high-resolution life cycle assessment (LCA) and techno-economic analysis (TEA), it provides detailed insights into the sustainability performance of these technologies. In addition, this work goes further by introducing a decision-support framework that improves the interpretation of LCA and TEA results, enhancing decision-makers' ability to form sustainable policies and implement actionable outcomes that drive the transition to green energy solutions. The first segment of this dissertation integrates high-resolution thermal and biological modeling with LCA and TEA to evaluate and compare two different microalgae biorefinery configurations targeting renewable diesel (RD) and sustainable aviation fuel (SAF) production in the United States. A dynamic engineering process model captures mass and energy balances for biomass growth, storage, dewatering, and conversion with hourly resolution. These configurations support facilities in remote areas and cultivation on marginal lands, enabling large-scale biofuel production. The two pathways under examination share identical biomass production and harvesting assumptions but differ in their conversion processes. The first pathway evaluates hydrothermal liquefaction (HTL) to produce RD, while the second explores the Hydroprocessed Esters and Fatty Acids (HEFA) process to produce SAF. Results indicate that the Minimum Fuel Selling Price (MFSP) for RD could decrease from $3.70-$7.30 to $1.50-$4.10 per liter of gasoline equivalent, and for SAF from $9.90-$19.60 to $2.20-$7.30 per liter under future scenarios with increased lipid content and reduced CO2 delivery costs. Optimization analyses reveal pathways to achieve an MFSP of $0.75 per liter and 70% GHG emissions reductions compared to petroleum fuels for both pathways. Additional analysis covers the water footprint, land-use change emissions, and other environmental impacts, with a focus on strategic research and development investments to reduce production costs and environmental burdens from microalgae biofuels. Beyond renewable transportation fuels, achieving a sustainable energy future will require innovations in the circular economy, such as waste-to-energy systems that reduce GHG emissions while simultaneously producing renewable energy. Accordingly, the second segment of this dissertation examines the GHG reduction potential of adopting AD technology on large-scale dairy farms across the contiguous United States. Regional and national GHG reduction estimates were developed through a robust life cycle modeling framework paired with sensitivity and uncertainty analyses. Twenty dairy configurations were modeled to capture key differences in housing and manure management practices, applicable AD technologies, regional climates, storage cleanout schedules, and land application methods. Monte Carlo uncertainty bounds suggest that AD adoption could reduce GHG emissions from the large-scale dairy industry by 2.45-3.52 million metric tons (MMT) of CO2-equivalent (CO2-eq) per year when biogas is used solely in renewable natural gas programs, and as much as 4.53-6.46 MMT of CO2-eq per year when combined heat and power is implemented as an additional biogas use case. At the farm level, AD technology may reduce GHG emissions from manure management systems by 58.1-79.8%, depending on the region. The study highlights the regional variations in GHG emissions from manure management strategies, alongside the challenges and opportunities surrounding broader AD adoption. It is vital to confirm that engineered climate solutions offer real improvements and to identify key enhancements needed to replace existing technologies. This process hinges on effective policy and decision-making. To address these challenges, the final segment of this dissertation introduces the Environmental Comparison and Optimization Stakeholder Tool for Evaluating and Prioritizing Solutions (ECO-STEPS). ECO-STEPS offers a decision-support framework that utilizes outputs from LCA and TEA to help decision-makers evaluate and prioritize engineered climate solutions based on economic viability, environmental impacts, and resource use. The tool's framework combines stakeholder rankings for key sustainability criteria with diverse statistical weighting methods, offering decision support aligned with long-term sustainability goals across various technology sectors. Applied to a biofuels case study, ECO-STEPS compares algae-based RD, soybean biodiesel (BD), corn ethanol, and petroleum diesel, using an expert survey to determine criteria rankings. Results indicate that soybean BD is a strong near-term solution for the biofuels sector, given its economic viability and relatively low environmental impacts. In contrast, corn ethanol, while economically competitive, demonstrates poor environmental performance across multiple sustainability themes. Algae-based RD emerges as a promising long-term option as ongoing research and development reduce costs. The results of this case study illustrate that ECO-STEPS provides a flexible and comprehensive framework for stakeholders to navigate complex decision-making processes in the pursuit of sustainable climate solutions. In conclusion, the integration of high-resolution LCA, TEA, and a stakeholder-driven decision-support framework in this dissertation presents a comprehensive approach to evaluating engineered climate solutions. The results from these studies provide geographically resolved insights into the sustainability performance of key climate technologies, offering actionable pathways for optimizing biofuel production, reducing GHG emissions, and supporting sustainable decision-making to advance the transition to a green economy.