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<p>The deployment of 5&#xa0;G networks has generated significant debate regarding its environmental implications, particularly concerning carbon emissions. Although 5&#xa0;G technology offers improved energy efficiency per bit transmitted, concerns persist due to potential rebound effects and the significant carbon footprint associated with infrastructure deployment and baseline energy consumption. This paper presents a bottom-up approach combining a detailed radio load model and spatial distribution of users to precisely estimate the energy usage and carbon emissions of 5&#xa0;G networks using the 3.5 GHz band. Although the model is valid for other regions, we focus specifically on the city of Lyon in France, providing a detailed assessment of current emissions (2021–2024) and projections up to 2050, incorporating traffic growth and national energy decarbonization scenarios. At the base station scale, our results show that emissions generated by hardware manufacturing and baseline energy consumption constitute the dominant contributors to the overall carbon footprint, compared with emissions induced by traffic load. As a result, our projections indicate that an increase in traffic demand does not significantly impact the carbon footprint unless it necessitates the deployment of additional base stations. By 2050, infrastructure-related emissions could constitute up to 70% of total network emissions, highlighting a major challenge in the management of network growth to avoid rebound effect. The study demonstrates that decarbonizing electricity and enhancing energy efficiency alone are insufficient.</p>

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Carbon footprint of urban 5 G traffic in Lyon based on real-world data and analytical modeling

  • 期刊论文

  • 发表日期：

    2026年2月27日

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  • Mériem Ghali,
  • Anthony Busson,
  • Marceau Coupechoux

摘要

The deployment of 5 G networks has generated significant debate regarding its environmental implications, particularly concerning carbon emissions. Although 5 G technology offers improved energy efficiency per bit transmitted, concerns persist due to potential rebound effects and the significant carbon footprint associated with infrastructure deployment and baseline energy consumption. This paper presents a bottom-up approach combining a detailed radio load model and spatial distribution of users to precisely estimate the energy usage and carbon emissions of 5 G networks using the 3.5 GHz band. Although the model is valid for other regions, we focus specifically on the city of Lyon in France, providing a detailed assessment of current emissions (2021–2024) and projections up to 2050, incorporating traffic growth and national energy decarbonization scenarios. At the base station scale, our results show that emissions generated by hardware manufacturing and baseline energy consumption constitute the dominant contributors to the overall carbon footprint, compared with emissions induced by traffic load. As a result, our projections indicate that an increase in traffic demand does not significantly impact the carbon footprint unless it necessitates the deployment of additional base stations. By 2050, infrastructure-related emissions could constitute up to 70% of total network emissions, highlighting a major challenge in the management of network growth to avoid rebound effect. The study demonstrates that decarbonizing electricity and enhancing energy efficiency alone are insufficient.