Integrated Sensitivity and Monte Carlo Modeling of SSbD-Based Sustainability Metrics in Chemical Frameworks

Abstract

The increasing complexity of environmental and societal challenges necessitates the development of comprehensive and quantitative frameworks for sustainable chemistry assessment. Traditional approaches such as green chemistry and Circular Chemistry primarily emphasize efficiency and resource circulation but often lack integration of social, economic, and system-level dimensions. In this study, a quantitative evaluation framework based on Safe-and-Sustainable-by-Design (SSbD) principles is developed to compare the sustainability performance of five chemistry paradigms across eight dimensions, including environmental, social, economic, systems thinking, circularity, safety, sufficiency, and life-cycle considerations. A multi-dashboard computational model is implemented in MATLAB 2019b to visualize framework performance and structural relationships. Sensitivity analysis is conducted to evaluate the influence of dimension weighting on composite sustainability scores, while Monte Carlo simulation (N = 10,000) is applied to assess uncertainty and robustness. Results indicate that SSbD and Sustainable Chemistry consistently outperform traditional frameworks, with higher composite scores (~0.78–0.85) and lower sensitivity to parameter variation. Furthermore, SSbD demonstrates strong alignment with safety and life-cycle priorities, while maintaining robustness under uncertainty. The findings highlight the importance of integrating multiple sustainability strategies and provide a quantitative decision-support tool for advancing sustainable chemical design.