Editorial Feature

Quantum Computing to Monitor CO2 Emissions

Image Credits: Yurchanka Siarhei/shutterstock.com

Quantum computing promises to usher in an exponential growth in computer processing power by replacing the binary digits (bits) used in classical electronic computing with quantum bits (qubits).

Quantum Supremacy

While the technology is not there yet, once quantum supremacy (the theoretical state in which quantum computers can be shown to perform any task faster than classical computers) is reached then computers will be able to enhance and speed up any function that can be programmed or, through machine-learning, self-programmed into machines.

This could have a significant impact on humans’ ability to monitor – and therefore limit – emissions of carbon dioxide (CO2). In the Industrial Revolution in the eighteenth and nineteenth centuries in Europe and the west, new technologies like the steam engine harnessed the carbon stored in fossil fuels (beginning with coal and then oil) by burning it to produce usable energy. This resulted not only in untapping previously unimaginable amounts of energy to fuel rapid technological and societal developments but also in the release of CO2 into the atmosphere at unprecedented levels.

Increased Atmospheric CO2 Contributes to Global Warming

These unprecedented levels of CO2 emissions could not be converted by vegetable photosynthesis into breathable oxygen fast enough, and the ability of vegetation to take CO2 out of the atmosphere has concurrently been reduced significantly by mass deforestation. Since the start of the Industrial Revolution 250 years ago, the concentration of CO2 in the atmosphere has increased by 43%, and 50% of the CO2 emissions caused by humans has been dissolved in the ocean.

The increase in the atmospheric concentration of CO2 has resulted in global warming, which is altering planetary weather systems, reducing rainfall and making parts of the world uninhabitable. Meanwhile, CO2 dissolved in the oceans is causing ocean acidification and rises in the ocean’s surface temperature, which is killing marine plant and animal life and altering the marine ecosystem.

Key to reducing emissions of CO2 into the atmosphere – and subsequently, carbon dissolved in the oceans – is accurately monitoring and reporting on them. However, this is an incredibly difficult task. This is due to the vast number of individual points of emission, which can at best only be estimated. Emitters of CO2 include power generators that burn fossil fuels to convert into electricity for electric grids, industrial facilities that burn fossil fuels to power their various processes, and exhaust fumes from all kinds of transportation including airplanes, trains, cars and ships, generators of onsite power for buildings. As such, gathering and monitoring accurate emissions data from these sources around the world is practically impossible for any organization today.

Quantum Computing for Monitoring CO2 Emissions

This is where quantum computing could drastically improve the situation. Quantum computers could accurately model all of these sources of CO2 emissions around the world due to their potential for superior processing power, something that current classical computing is unable to achieve. Such a model of the CO2 emissions network could identify target areas for reduction through machine-learning and artificial intelligence (AI) – technologies themselves significantly enhanced by quantum computing. This could be done even without cooperation from CO2 emitters, as a quantum computing model would be able to take inputs from multiple sources including local atmospheric monitoring and`satellites to build an accurate picture.

Recent Developments

As more and more cars and commercial vehicles including airplanes and ships are fitted with smart technology, they can be linked into a global network of CO2 emitters – a feature of the Internet of Things (IoT). Such a network would comprise of a vast amount of nodes, all different, which would require significant computing processor power to monitor: this is what quantum computing can offer.

Quantum computing could also automate large parts of the energy cycle to maximize energy efficiency and reduce CO2 emissions. As well as this, machine-learning and AI-powered by quantum computers could improve technologies to reduce or eventually eliminate our reliance on fossil fuel combustion for energy supply.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ben Pilkington

Written by

Ben Pilkington

Ben Pilkington is a freelance writer who is interested in society and technology. He enjoys learning how the latest scientific developments can affect us and imagining what will be possible in the future. Since completing graduate studies at Oxford University in 2016, Ben has reported on developments in computer software, the UK technology industry, digital rights and privacy, industrial automation, IoT, AI, additive manufacturing, sustainability, and clean technology.


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Pilkington, Ben. (2019, August 28). Quantum Computing to Monitor CO2 Emissions. AZoCleantech. Retrieved on June 24, 2024 from https://www.azocleantech.com/article.aspx?ArticleID=941.

  • MLA

    Pilkington, Ben. "Quantum Computing to Monitor CO2 Emissions". AZoCleantech. 24 June 2024. <https://www.azocleantech.com/article.aspx?ArticleID=941>.

  • Chicago

    Pilkington, Ben. "Quantum Computing to Monitor CO2 Emissions". AZoCleantech. https://www.azocleantech.com/article.aspx?ArticleID=941. (accessed June 24, 2024).

  • Harvard

    Pilkington, Ben. 2019. Quantum Computing to Monitor CO2 Emissions. AZoCleantech, viewed 24 June 2024, https://www.azocleantech.com/article.aspx?ArticleID=941.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.