Dynamic Sustainability Modeling under Energy and Emission Uncertainty: Tools for Resilient Policy and Industrial Decision-Making
DOI:
https://doi.org/10.61978/catalyx.v2i4.1328Keywords:
sustainable manufacturing, sensitivity analysis, Monte Carlo simulation, emission factor variability, energy price modeling, policy planning, uncertainty quantificationAbstract
Uncertainty in energy markets and emission factors presents a significant challenge to sustainable manufacturing. This study aims to develop a simulation-based sensitivity framework to assess how variability in fossil fuel prices and emission coefficients impacts sustainability outcomes. Using One-At-a-Time (OAT), Tornado analysis, and Monte Carlo simulations, the study evaluates the influence of energy prices (oil, coal, natural gas) and emission factors (CO₂ per GJ for various fuels) on manufacturing sustainability. The framework incorporates real-world parameter ranges and applies probabilistic modeling to capture compound uncertainties. Sensitivity analysis reveals that coal and oil prices are the most influential variables in cost-driven assessments, while emission factor variation particularly for coal and diesel introduces significant uncertainty in carbon accounting. Monte Carlo simulations, run over 10,000 iterations, show wide variability in sustainability scores, underscoring the need for risk-informed planning. Tornado diagrams visually rank variable importance, facilitating policy and operational prioritization. Contextual influences, such as national energy mixes and regulatory environments, further shape parameter sensitivity. Findings demonstrate the strategic value of compound modeling in subsidy targeting, supply chain planning, and compliance forecasting. This study contributes a practical, adaptable framework for sustainability modeling under uncertainty. By quantifying the probabilistic impact of volatile energy and emissions data, it enhances the credibility and utility of manufacturing assessments. The framework supports policymakers and industry leaders in designing robust, context-specific strategies for sustainable transitions.
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