Page 281 - GHES-3-3

Global Health Economics and
Sustainability

ORIGINAL RESEARCH ARTICLE
Healthcare, smartphones, and the carbon

footprint

Gloria Wu * , Sahil Saini 1 , Ethan Pan 1 , Ivan Chim 2 , Brian Hoang 3 ,
1
Samson Nguyen 4 , Mary Nguyen 5 , and Hrishi Paliath-Pathiyal 6
1 Department of Ophthalmology, School of Medicine, University of California, San Francisco,
California, United States of America
2 Department of Biology, School of Biological Sciences, University of California San Diego, San
Diego, California, United States of America
3 Department of Computer Science, School of Engineering, University of California Davis, Davis,
California, United States of America
4 Department of Biology, College of Science, San Jose State University, San Jose, California, United
States of America
5 Department of Biology, Charlie Dunlop School of Biological Sciences, University of California Irvine,
Irvine, California, United States of America
6 Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern
University, Fort Lauderdale, Florida, United States of America

Abstract
Academic editor:
Mihajlo Jakovljevic M.D. Ph.D. MAE Smartphones are widely used by physicians and patients. The carbon footprint
*Corresponding author: of healthcare devices is poorly documented. Physicians report an average daily
Gloria Wu smartphone usage of 1 – 5 h for activities, such as reviewing diagnostic information,
(gloria.wu@ucsf.edu)
capturing patient photographs, conducting telehealth consultations, and advancing
Citation: Wu, G., Saini, S., Pan, E., their medical education. Meanwhile, patients generate billions of daily queries on
Chim, I., Hoang, B., Nguyen, S.,
Nguyen, M., & Paliath-Pathiyal, H. Google and millions on ChatGPT, trends likely to increase as artificial intelligence (AI)-
(2025). Healthcare, smartphones, driven search engines and large language models (LLMs) become more sophisticated
and the carbon footprint. Global and accessible. To explore the associated environmental impact, we evaluated the
Health Econ Sustain, 3(3):273-284.
https://doi.org/10.36922/ghes.8359 average lifetime carbon emissions linked to smartphone usage and the energy costs
of manufacturing selected smartphone models. Our data were sourced from publicly
Received: January 1, 2025
accessible databases, corporate 10-K statements, and corporate social responsibility
1st revised: May 17, 2025 reports available on company websites. We then validated these findings by using
2nd revised: May 31, 2025 four types of LLMs, including ChatGPT, Gemini, Claude.ai, and Meta AI. We found that
all LLMs produced carbon emission estimates that differed from those reported in the
Accepted: June 9, 2025
companies’ official corporate literature. In an era of rapid AI adoption, establishing
Published online: June 24, 2025 reliable environmental metrics is essential for informed decision-making and
Copyright: © 2025 Author(s). responsible technology use.
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution Keywords: Carbon footprint; Smartphone; Large language models; Environmental
License, permitting distribution, sustainability; ChatGPT; Digital healthcare; Artificial intelligence
and reproduction in any medium,
provided the original work is
properly cited.
Publisher’s Note: AccScience
Publishing remains neutral with 1. Introduction
regard to jurisdictional claims in
published maps and institutional The healthcare sector significantly contributes to carbon dioxide (CO ) emissions from
2
affiliations. hospitals, clinics, operating rooms, and surgeries (Eckelman & Sherman, 2016). This is

Volume 3 Issue 3 (2025) 273 https://doi.org/10.36922/ghes.8359