This project uses NC State’s waste data to build a data-driven circularity model, analyzing economic and environmental impacts that serve as a case study for potential industrial symbiosis in the Research Triangle region.

Project Overview

Team: Campus As A Classroom. Climate and Sustainability Academy, College of Agriculture and Life Sciences, Partnerships Office, Waste Reduction and Recycling, University Sustainability Office. External Collaborators: Novo Nordisk and Kalundborg Symbiosis

Duration: August – December 2025

Status: Complete

Focus: Consumption and Production

Primary Contact: Christopher Galik

Summary

The Campus Circularity Model project evaluated waste management practices at NC State University with a goal to advance regional circular economy partnerships. The primary objectives of the project were to evaluate existing waste streams, establish a data-driven circularity model, uncover opportunities for symbiotic partnerships, and construct an engagement framework to communicate findings to stakeholders. 

The model included 8 sub-models across four end-of-life scenarios: compost, reuse, landfill, and recycling. For each scenario, both an economic model and an environmental model were created using NC State Waste Reduction and Diversion data from fiscal year 2024.

The environmental models calculate carbon abatement in metric tons of carbon dioxide equivalent (MTCO2e) per dry ton of feedstock and product (based on methodologies from EPA WARM and GREET). The economic models evaluate the market value or cost associated with materials on a dollar-per-ton basis, factoring in conversion efficiencies from raw feedstock to final product. By visualizing supply flows from generation points to potential end uses, the model provides a structured technical basis for comparing waste utilization options and driving regional collaboration.

Findings

Highlights of the analysis across the four waste management systems:

Recycling System: Traditional recyclables like scrap metal and corrugated cardboard have strong environmental and financial returns but other materials can be difficult to process.

Compost System: Campus has high volumes of organic waste and strong existing composting infrastructure. While certain high-value conversion pathways (such as Sustainable Aviation Fuel or PLA hydrolysis) offer high market values per product ton, their per-ton feedstock value is lower due to conversion efficiencies. Pathways like biomass burial yield significant gross carbon abatement, whereas pathways like biodiesel maximize market value.

Reuse System: Direct reuse provides the highest environmental impact with the lowest financial cost, avoiding both landfill disposal and new product manufacturing. NC State’s surplus sales and departmental transfers show strong performance, particularly in electronics, office furniture, pallets, and food recovery.

Landfill System: Landfilling and specialized medical waste disposal are costly and  a source of significant greenhouse gas emissions. Diverting landfill-bound plastic waste into alternatives like composite lumber or polyethylene waxes offers carbon abatement and potential cost recovery.

Looking Ahead

Transparent data modeling is essential for turning industrial waste into regional economic opportunities. The model created in this project demonstrated actual waste supply for campus and revealed opportunities for innovation in hard-to-recycle materials like mixed plastics and lab waste. It also showed that conversion efficiency is critical in circular economy models. A high market price per unit of refined product does not automatically translate to a high return per ton of raw waste if conversion yields are low. 

The model was successful in showing the scalability of the circular economy if broadened to more companies in the Research Triangle. Establishing shared-value partnerships is key to making industrial symbiosis and localized recycling economically viable. 

The results of this project kickstarted a second project phase, which focused on expanding the model to include waste data from several companies in the Research Triangle.