Environmental Impact of Generative AI: Carbon and Water Footprint

Generative AI technologies, such as ChatGPT, have measurable environmental impacts primarily from electricity consumption and freshwater usage at data centers. An individual AI query emits roughly 4.3 grams of CO₂ and uses around 10 milliliters of freshwater. In comparison to common everyday tasks, AI's carbon footprint is small, significantly lower than driving or showering but higher than simple digital activities like web browsing.At scale, however, generative AI contributes notably to global energy and water demands. AI data centers consume tens of terawatt-hours (TWh) of electricity annually, with major companies reporting rapid increases in energy use due to expanding AI capabilities. Freshwater use at these centers is similarly substantial, reaching billions of gallons annually.Though concerns regarding AI's environmental impacts are supported by data, significant mitigation is achievable through energy-efficient designs, renewable energy sourcing, and enhanced operational transparency.

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Publication Details

Journal
AI-EDU arxiv.
Published
2025-03-21
DOI
https://doi.org/10.36851/ai-edu.vi.5448
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

Environmental Impact of Generative AI: Carbon and Water Footprint

Alexander M. Sidorkin
2 links
AI-EDU arxiv.
Engineering Education and Technology
article

Environmental Impact of Generative AI: Carbon and Water Footprint

Alexander M. Sidorkin
article en

Abstract

Generative AI technologies, such as ChatGPT, have measurable environmental impacts primarily from electricity consumption and freshwater usage at data centers. An individual AI query emits roughly 4.3 grams of CO₂ and uses around 10 milliliters of freshwater. In comparison to common everyday tasks, AI's carbon footprint is small, significantly lower than driving or showering but higher than simple digital activities like web browsing.At scale, however, generative AI contributes notably to global energy and water demands. AI data centers consume tens of terawatt-hours (TWh) of electricity annually, with major companies reporting rapid increases in energy use due to expanding AI capabilities. Freshwater use at these centers is similarly substantial, reaching billions of gallons annually.Though concerns regarding AI's environmental impacts are supported by data, significant mitigation is achievable through energy-efficient designs, renewable energy sourcing, and enhanced operational transparency.

AI-EDU arxiv.
California State University, Sacramento (US)
Openalex Percentile: Top 93%
Engineering Education and Technology
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