Artificial Intelligence in the Development of Greenhouse Gas Emission Inventories for Commuting: A Case Study at the University of Sao Paulo’s Butantan Campus

Marcio Maia Vilela; José Aquiles Baesso Grimoni

doi:10.1590/SciELOPreprints.18063

##article.authors##

Marcio Maia Vilela University of São Paulo https://orcid.org/0000-0002-0623-9229
- Conceptualization
- Data Curation
- Formal Analysis
- Investigation
- Methodology
- Validation
- Visualization
- Writing – Original Draft Preparation
- Writing – Review & Editing
José Aquiles Baesso Grimoni University of São Paulo https://orcid.org/0000-0002-7553-3907
- Conceptualization
- Data Curation
- Formal Analysis
- Investigation
- Methodology
- Supervision
- Validation
- Visualization
- Writing – Original Draft Preparation
- Writing – Review & Editing

DOI:

https://doi.org/10.1590/SciELOPreprints.18063

Keywords:

GHG Emissions, commuting, artificial intelligence, HEIs, butantan campus, sustainability, urban mobility

Abstract

Higher Education Institutions (HEIs) play a crucial role in mitigating climate change, as centres of research and sustainable practices. This article addresses USP’s Butantan Campus, using generative Artificial Intelligence (AI) tools An Origin-Destination survey (6,700 responses), calculated distances, transport modes, and associated emissions. Commuting accounts for a GHG emissions, exceeding Scope 1 and 2 emissions under certain contexts. Including Scope 3 in HEIs’ GHG inventories is critical and proposes strategies to reduce emissions, such as prioritising sustainable public transport, creating cross-sectoral committees, and adopting a "green curriculum" within HEIs. AI innovates GHG inventories and public policies. HEIs must lead by example