1. Department of Environmental Engineering, College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China 2. Engineering Laboratory of Low-Carbon Unconventional Water Resources Utilization and Water Quality Assurance, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China 3. Zhejiang Province Key Laboratory for Water Pollution Control and Environmental Safety, Hangzhou 310058, China 4. Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan 314100, China
The boosting development of artificial intelligence (AI) is contributing to rapid exponential surge of computing power demand, which results in the concerns on the increased energy consumption and carbon emission. To highlight the environmental impact of AI, a quantified analysis on the carbon emission associated with AI systems was conducted in this study, with the hope of offering guidelines for police maker to setup emission limits or studies interested in this issue and beyond. It has been discovered that both industry and academia play pivotal roles in driving AI development forward. The carbon emissions from 79 prominent AI systems released between 2020 and 2024 were quantified. The projected total carbon footprint from the AI systems in the top 20 of carbon emissions could reach up to 102.6 Mt of CO2 equivalent per year. This could potentially have a substantial impact on the environmental market, exceeding $10 billion annually, especially considering potential carbon penalties in the near future. Hence, it is appealed to take proactive measures to develop quantitative analysis methodologies and establish appropriate standards for measuring carbon emissions associated with AI systems. Emission cap is also crucial to drive the industry to adopt more environmentally friendly practices and technologies, in order to build a more sustainable future for AI.
Yang Yu,Jiahui Wang,Yu Liu, et al. Revisit the environmental impact of artificial intelligence: the overlooked carbon emission source?[J]. Front. Environ. Sci. Eng.,
2024, 18(12): 158.
Fig.1 Training compute of AI systems from 2010 to 2024. Data from: Epoch AI (2024).
Fig.2 Top 20 AI systems in terms of carbon emission for a single training run.
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