Master of Environmental Data Science
Creating a Reproducible Model of Annual Emissions Outputs for a Sock Manufacturer’s Supply Chain
As the global business landscape faces escalating concerns of climate change, more companies are seeking to provide products and services with less environmental impacts. Specifically, these companies are interested in greenhouse gas (GHG) emissions associated with the production and consumption of their products and services. Darn Tough, a Vermont-based sock manufacturer, is one of these companies, and they plan to achieve a 55% reduction in total GHG emissions from their 2019 baseline level by 2030. Darn Tough strives to create an emissions model that is accurate, reproducible, and user-friendly that will help them to reach this goal. Through this project, the capstone team will create an improved model based upon Darn Tough’s existing model for quantifying GHG emissions from the sock production supply chain. This project also aims to develop an interactive application for visualizing annual GHG emissions through parameters (e.g., varying production levels). These deliverables will allow Darn Tough to identify critical points in the supply chain, make effective strategies for reducing GHG emissions, and enable the company to continue enhancing and promoting its sustainable brand.