Multi-Stakeholder Optimization for Identification of Relevant Life Cycle Assessment Endpoint Indicators

Endpoint indicators provide a concise representation of environmental impacts by aggregating multiple midpoint indicators into a single value. Traditional endpoint weighting systems, however, are often limited by biases introduced through panel reviews and a lack of robustness in scientific process models. Additionally, they typically fail to account for the preferences of key stakeholders, including industry, government, and the public. This work addresses these limitations by developing an endpoint indicator that incorporates stakeholder preferences and minimizes dissatisfaction. A multi-stakeholder optimization framework was formulated to achieve this goal, employing distance, downside risk, and conditional value at risk as objective functions. Stakeholder preferences were derived from emissions data for industry, federal spending on environmental issues for government, and public surveys for societal input. Results highlight regional variations in midpoint indicator weightings across Texas, California, Delaware, and the United States. Furthermore, the influence of public and government preferences reveals a prioritization of human health concerns over environmental impacts. This framework offers a novel approach to creating endpoint indicators that align with stakeholder priorities, promoting more inclusive and collaborative environmental decision-making.