<b>Addressing Uncertainty in Economic and Environmental Assessments of Emerging Energy Technologies</b>

<p dir="ltr">The transition to alternative energy is critical for achieving global sustainability goals, yet economic and environmental uncertainties present significant challenges to its widespread adoption. This dissertation explores the impact of uncertainty in the economic and environmental assessment of various emerging energy technologies, including bio-jet fuels, microgrids, and rare-earth permanent magnets. Utilizing a combination of techno-economic analysis (TEA), life cycle assessments (LCA), and optimization modeling, this study categorizes sources of uncertainty and integrates probabilistic approaches to improve assessment reliability.</p><p dir="ltr">Key findings highlight the role of policy incentives, market fluctuations, and technological advancements in shaping the economic feasibility of emerging energy systems. Monte Carlo simulations and time-series forecasting were employed to evaluate policy uncertainties, while multi-objective genetic algorithms optimized microgrid design under variable conditions. The results demonstrate that incorporating uncertainty quantification into economic and environmental assessments significantly enhances decision-making for stakeholders, providing more robust frameworks for evaluating investment risks and policy impacts.</p><p dir="ltr">This research contributes to bridging the gap between laboratory-scale alternative energy innovations and their commercial-scale implementation by providing methodologies that account for real-world variability and risk factors. By incorporating scenario analysis and sensitivity assessments, this study provides a deeper understanding of how different uncertainty variables interact to shape financial viability and sustainability outcomes. In the case of bio-jet fuels, the research identifies key economic barriers such as fluctuating ethanol feedstock costs, conversion efficiency variances, and regulatory uncertainties, all of which have significant implications for commercial scalability. For microgrid technologies, this dissertation presents optimization techniques that balance cost-effectiveness, energy reliability, and carbon footprint reduction, offering practical insights for developers and policymakers. Finally, in the rare earth permanent magnet sector, the study examines how supply chain disruptions and geopolitical uncertainties influence the cost structure and market competitiveness of novel manufacturing approaches.</p><p dir="ltr">By systematically addressing these factors, this dissertation advances the development of robust assessment frameworks that inform clean and alternative energy investments and policy decisions. This work demonstrates that integrating uncertainty management strategies into techno-economic and environmental analyses enhances the precision of predictions, reduces investment risks, and improves strategic planning for stakeholders. The methodologies and insights presented herein serve as a foundation for future research aimed at further refining uncertainty quantification approaches and expanding their applicability to emerging energy technologies.</p>