Evolving reporting requirements demand precise tracking of Greenhouse Gas (GHG) emissions from business travel. This project tested new methods of GHG accounting using NC State’s own travel data.

Project Overview

Team: Climate and Sustainability Academy, Poole College of Management, Procurement and Business Services, University Sustainability Office
External Collaborator: Bank of America

Duration: September 2024 – May 2025

Status: Complete

Focus: Climate

Primary Contact: Christopher Galik

Summary

Driven by evolving national and international reporting requirements, as well as voluntary corporate governance initiatives, there is an increasing trend to better  track greenhouse gas emissions associated with business travel. The university environment provides an opportunity to better understand this evolving landscape and to test approaches for GHG accounting and reduction. This project explored the travel preferences and behaviors of the NC State university community through an in-house electronic survey, developed an improved process for automating travel data collection and analysis, created a custom web-based engine to recommend lower emission itineraries, and identified a variety of policies and practices to further reduce emissions. The project included two elements:

Travel preference and behavior survey: A Qualtrics online survey was developed in Fall 2024 and distributed to a random sample of 1,549 NC State faculty, students, and staff. Questions sought information on sustainable practice awareness, travel preferences, and travel planning behavior.

Alternative emissions estimation processes: The project explored alternative approaches to travel emissions estimation, beginning with a reexamination of a dataset. Upon review, this dataset was found to have significant data quality issues, including sparse data with numerous missing values, duplicate entries and incomplete flight details, and a lack of information on origin airports. Though invoice processing using Optical Character Recognition (OCR), PyMuPDF (A Python package), and ChatGPT (a Large Language Model, or LLM) was helpful in identifying airport codes and other key travel-related data points, automation was not possible due to Two-Factor Authentication (2FA). A second approach using enhanced procurement card data allowed for a more accurate and efficient estimation process.

Findings

The survey of the university community demonstrates the dominance of cost and time considerations when making travel plans. Mirroring global trends, NC State University faculty, students, and staff are expecting to travel substantially more in the coming years. Though respondents report awareness of climate change and GHG reduction, their awareness of sustainable travel and NC State’s sustainability practices and travel policies is much less, presenting a need and opportunity for improved information and communication.

Improving the process by which NC State accounts for its emissions was a necessary first step in better understanding the magnitude of Scope 3 travel emissions and the methods best suited to reduce them. The new emissions estimation process was also more efficient and achieved a higher level of precision, resulting in a 5% reduction in estimated air travel emissions while saving an estimated 15 hours of staff time annually.

Looking Ahead

Collectively, the work demonstrates how universities and other medium to large knowledge organizations can improve travel emissions estimation and reporting processes, relatively quickly, at low upfront cost, and with potential long-term savings.

Use of a comprehensive, organization-wide travel booking platform is a common recommendation to improve the quantity and quality of travel data, but this may be difficult for some organizations. Instead, efforts should continue to improve upon data collection processes, such as developing alternative mechanisms for tracking or making travel-based expenditures. Travel and virtual travel cards, provide improved data management and opportunities to highlight sustainable travel options. Revising the travel authorization process itself can also provide an opportunity to improve data collection, for instance requiring airport codes for each leg of the journey, leveraging APIs to enable automatic travel data extraction, cleaning, and analysis, and integration of artificial intelligence tools to present sustainable travel options.