While researchers in both industry and academia are racing to build Quantum Computing (QC) platforms with viable performance and functionality, the environmental impacts of this endeavor, such as its carbon footprint, e-waste generation, mineral use, and water and energy consumption, remain largely unknown. A similar oversight occurred during the semiconductor revolution and continues to have disastrous consequences for the health of our planet. As we build the quantum computing stack from the ground up, it is crucial to comprehensively assess it through an environmental sustainability lens for its entire life-cycle: production, use, and disposal. In this paper, we highlight the need and challenges in establishing a QC sustainability benchmark that enables researchers to make informed architectural design decisions and celebrate the potential quantum environmental advantage. We propose a carbon-aware quantum computing (CQC) framework that provides the foundational methodology and open research questions for calculating the total life-cycle carbon footprint of a QC platform. Our call to action to the research community is the establishment of a new research direction known as, sustainable quantum computing that promotes both quantum computing for sustainability-oriented applications and the sustainability of quantum computing.
While researchers in both industry and academia are racing to build Quantum Computing (QC) platforms with viable performance and functionality, the environmental impacts of this endeavor, such as its carbon footprint, e-waste generation, mineral use, and water and energy consumption, remain largely unknown. A similar oversight occurred during the semiconductor revolution and continues to have disastrous consequences for the health of our planet. As we build the quantum computing stack from the ground up, it is crucial to comprehensively assess it through an environmental sustainability lens for its entire life-cycle: production, use, and disposal. In this paper, we highlight the need and challenges in establishing a QC sustainability benchmark that enables researchers to make informed architectural design decisions and celebrate the potential quantum environmental advantage. We propose a carbon-aware quantum computing (CQC) framework that provides the foundational methodology and open research questions for calculating the total life-cycle carbon footprint of a QC platform. Our call to action to the research community is the establishment of a new research direction known as, sustainable quantum computing that promotes both quantum computing for sustainability-oriented applications and the sustainability of quantum computing.
While researchers in both industry and academia are racing to build quantum computing (QC) platforms with viable performance and functionality, the environmental impacts of this endeavor, such as its carbon footprint, e-waste generation, mineral use, and water and energy consumption, remain largely unknown. A similar oversight occurred during the semiconductor revolution and continues to have disastrous consequences for the health of our planet. As we build the quantum computing stack from the ground up, it is crucial to comprehensively assess it through an environmental sustainability lens for its entire lifecycle: production, use, and disposal. In this article, we highlight the need and challenges in establishing a QC sustainability benchmark that enables researchers to make informed architectural design decisions and celebrate the potential “quantum climate advantage.” We propose a carbon-aware quantum computing (CQC) framework that provides the foundational methodology and open research questions in calculating the total life-cycle carbon footprint of a QC platform. Our call to action to the research community is the establishment of a new research direction known as sustainable quantum computing (SQC) that promotes quantum computing for both sustainability-oriented applications and the sustainability of quantum computing itself.
As quantum computing progresses from theory to practical systems, its environmental and economic sustainability remains underexplored.This paper analyzes both the carbon footprint and cost implications of quantum computing technologies, with attention to their alignment with global sustainability goals.Key contributors to energy consumption, emissions, and operational costs are identified across the quantum computing lifecycle: hardware manufacturing, cryogenic cooling, runtime power demands, and quantum circuit simulation.The study employs a qualitative methodology, integrating a comprehensive review of scientific literature, environmental assessments, cost analysis reports, and benchmarking frameworks.It further presents a comparative analysis of quantum and classical high-performance computing (HPC), evaluating energy efficiency, environmental impact, and cost-effectiveness across realistic scenarios.By addressing both sustainability and economic dimensions, this research provides new insights for developers and policymakers, supporting the advancement of greener and more costeffective quantum technologies.
Quantum computing's environmental footprint remains poorly understood relative to classical infrastructure, and as quantum computing moves toward cloud delivery, Quantum Cloud Service (QCS) providers lack actionable guidance beyond platform-level carbon-accounting frameworks. Objective: This study extends the carbon-aware quantum computing (CQC) framework from a platform-level to a service-level model that translates empirical life cycle assessment (LCA) findings of a superconducting quantum computer into guidance for QCS providers. Method: We modeled the CQC framework via service-level embodied-carbon allocation, load-independent and load-proportional operational decomposition, and a workload-resolved application offset on the basis of results acquired through a cradle-to-grave LCA of a superconducting quantum platform. Results: The five-year footprint is 583 t CO2e (GKP) and 10,570 t (surface-code), dominated by embodied carbon (77.3-85.2%), with operational-embodied parity not reached until 17.0-28.7 years versus 2.7 years for classical comparators. This reorders provider levers: utilisation yields the largest gain (19.7x), followed by service life extension (59.9%) and electricity supply (6.5x), while operational efficiency and renewable procurement offer limited leverage. Conclusion: Superconducting quantum computers are structurally embodied-carbon-dominated, inverting classical sustainability intuition and motivating direct power measurement and cross-architecture validation as quantum infrastructure scales.
The rapid advancements in quantum computing hold transformative potential for addressing critical global challenges and achieving sustainable development. This paper presents a conceptual framework that aligns quantum computing innovations with the United Nations Sustainable Development Goals (SDGs). It explores key areas such as renewable energy optimization, smart city infrastructure, and climate change mitigation. The study also emphasizes sustainability challenges, including environmental impacts, ethical concerns, and socio-economic considerations like workforce transitions and digital equity. A novel Carbon-aware Quantum Computing model is introduced to minimize the environmental footprint of quantum systems. Finally, the paper proposes a roadmap for ethical and scalable adoption of quantum technologies, ensuring inclusive and resilient societal growth.
Quantum computing (QC) offers a pathway to solving certain problems that classical computers struggle with, such as advanced drug discovery, secure cryptography, and the design of new materials. While these capabilities are promising, the field also raises serious sustainability concerns. Running quantum processors demands significant amounts of energy, rare elements, and specialized infrastructure, often without clear guidelines for environmentally responsible design. This paper reviews the environmental impact of QC by examining inefficiencies in energy use, cooling, and hardware manufacturing. The findings indicate that integrating renewable energy sources, adopting energy-efficient quantum hardware designs, and developing optimized, low-power quantum algorithms are the most effective strategies for reducing QC’s environmental footprint. In addition, a set of potential sustainability metrics is proposed to guide future research and implementation. The discussion points to one clear message: if sustainability is not embedded into quantum technology now, we risk repeating the environmental mistakes made in past computing revolutions.
Abstract With the demonstrated ability to perform calculations in seconds that would take classical supercomputers thousands of years, quantum computers namely hold the promise of radically advancing sustainable IT. However, quantum computers face challenges due to the inherent noise in physical qubits, necessitating error correction for reliable operation in solving industrial-scale problems, which will require more computation time, energy, and electronic components than initial laboratory-scale experiments. Yet, while researchers have modeled and analyzed the environmental impacts of classical computers using Life cycle assessment the environmental performance of quantum computing remains unknown to date. This study contributes to filling this critical gap in two ways: (1) by establishing an environmental profile for quantum computers based on superconducting qubits; and (2) by comparing it to a functionally equivalent profile of a state-of-the-art supercomputer. With the comparison based on the problem size, the paper shows how the usage time can drive an environmental advantage for quantum computers under specific scaling conditions and quantum error correcting codes. The results emphasize that quantum error correction hardware has a substantial environmental impact due to the numerous electronic components needed to achieve 100 logical qubits. This paper can serve as a basis for designing more environmentally friendly quantum computers and for establishing their environmental profiles, as well as those of the human activities that will use them.