Multi Objective Approach to Designing Solvent Recovery Pathways Via Economic and Environmental Metrics | AIChE

Multi Objective Approach to Designing Solvent Recovery Pathways Via Economic and Environmental Metrics


Lehr, A. - Presenter, Rowan University
Geier, J., Rowan University
Mackley, M., Rowan University
Yenkie, K., Rowan University
Aboagye, E., Rowan University
Chea, J. D., Rowan University
The usage and disposal of solvents in industry have a significant impact on the environment. Their release into the environment have adverse effects on human health, ecosystem quality, climate change, and resources(Goedkoop and Spriensma, 2001) and can be quantified as emissions from the air, water, and soil associated with the processing and disposal of hazardous solvents. One of the ways to measure the environmental impacts of waste materials is through their life cycle assessment (LCA) that can characterize emissions over the entire life of a product. During a life cycle assessment, midpoint impacts characterization such as carcinogens, ecotoxicity, eutrophication, global warming, non-carcinogens, respiratory effects, and acidification are assessed (Jolliet et al., 2003). These midpoint categories are further grouped into three or four central damage assessment or endpoint categories. By assessing the life cycle of a product, various environmental decisions can be implemented to reduce emissions and impacts associated with solvent wastes. Traditional methods of waste solvent disposal, such as incineration has proved to be less favorable to the environment. There is an immediate need for efficient solvent recovery pathways.

Although solvent recovery processes improve the cost and sustainability, there has not been an integrated method to simultaneously quantify the environmental impacts and economics of the process. A multi-objective optimization approach is one of the tools that can be implemented (Diwekar, 2013). Previous work on the evaluation of the economic feasibility of the solvent recovery options has already been accomplished (Chea et al., 2020). This work is an extension of the previous study, where we incorporate the sustainability matrix into the framework. This is implemented by using a multi-objective optimization approach. The sustainability index used is the Sustainable Process Index (SPI). SPI quantifies the arable area needed to provide goods and services. Every process requires a certain area within the ecosystem to take place. The SPI is made up of seven footprints, quantified as area, namely: area needed for installations and infrastructure, renewable resources, non-renewable resources, fossil carbon usage, areas to embed air, water, and soil emissions after the process(Krotscheck and Narodoslawsky, 1996; Narodoslawsky and Krotscheck, 1995). In many studies, we observe that the economic evaluation is at the forefront of process selection, however, when we are targeting recovery from waste streams, as in case of solvent-containing streams, along with meeting the minimum cost requirements we also need to ensure that we are not posing an additional burden on our ecosystem.