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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. 

Heat recirculation in Joule-heated reactors. 

Biorefineries can reduce carbon dioxide emissions while serving the global chemical demand market. Governments are also using carbon pricing policies, such as carbon taxes, cap-and-trade models, and carbon caps, as a strategy to reduce emissions. The use of biomass feedstocks in conjunction with carbon capture usage and storage technologies are mitigation strategies for global warming. Businesses can invest in these technologies to accommodate the adoption of these policies. Rapid action is necessary to halt global warming, which results in aggressive policies. In this work, a multi-period process design and planning problem is developed for the design and capacity expansion of biorefineries. The three carbon pricing policies are integrated into the model and parameters are selected according to the aggressive scenario denoted by the Paris Agreement. The results show that the cap-and-trade policy achieves a higher net present value evaluation over the carbon tax model across all pareto points due to the flexibility of the allowances in the cap-and-trade policy. The carbon cap model substantial investments are required in carbon capture technologies to adhere to the emissions constraints. 

Chemical recycling of plastics is a promising technology to reduce carbon footprint and ease the pressure of waste treatment. Specifically, highly efficient conversion technologies for polyolefins will be the most effective solution to address the plastic waste crisis, given that polyolefins are the primary contributors to global plastic production. Significant challenges encountered by plastic waste valorization facilities include the uncertainty in the composition of the waste feedstock, process yield, and product price. These variabilities can lead to compromised performance or even render operations infeasible. To address these challenges, this work applied the robust optimization-based framework to design an integrated polyolefin chemical recycling plant. Data-driven surrogate model was built to capture the separation units behavior and reduce the computational complexity of the optimization problem. It was found that when process yield and price uncertainties were considered, wax products became more favorable, and pyrolysis became the preferred reaction technology. 

The potential of replacing steam cracking with ODHE using a B-CHA catalyst is first investigated through comprehensive techno-economic and life-cycle assessments.