Quantum computing (QC) has the potential to impact several industries and help achieve the United Nation’s sustainability goals.
If developed, QC models and ML algorithms can help boost food production, transform the healthcare industry, generate affordable energy, and ensure sustainable consumption patterns.
This paper discusses the possibilities quantum computing ignites, including how it could help reduce carbon dioxide in the atmosphere and move toward reaching net zero.
According to the Intergovernmental Panel on Climate Change (IPCC), to limit the global temperature rise up to 1.5 degree Celsius, the world has to achieve net zero by 2050.
Net zero refers to reduction of greenhouse gas emissions while balancing the levels of greenhouse gases in the atmosphere.
We know that the rise in carbon emissions, global warming, deforestation, and urban development have resulted in disturbances in the environment, including climate change. In addition, due to the advancement in technology and the post-pandemic need for digital transformation across industries, other issues such as data privacy and security have come into focus.
These issues, impacting humanity at large, could be resolved only through global partnerships, co-operation, and coordinated efforts. Bloomberg estimates that a third of environmental, social, and governance (ESG) assets under management—ESG-focused institutional investments—are to hit $53 trillion by 2025.
Quantum computing (QC) is considered a groundbreaking, disruptive technology based on the fundamental principles of quantum mechanics and the behavior of atomic and sub-atomic particles.
Scientists believe that QC is suitable for modeling natural phenomena and could play a major role in addressing key sustainability challenges.
The United Nations (UN) has outlined 17 Sustainable Development Goals (SDGs) that define a framework and practice standards, in line with the Paris Agreement of 2015, signed by 194 countries. Classifying the various problem areas from an ESG standpoint, quantum technology could help address all the 17 SDGs either directly or indirectly. In this paper, we will cover some of QC’s potential use cases across industries from an ESG perspective.
Zero hunger is a UN sustainability goal.
Currently practiced traditional farming techniques may not be able to meet the growing demand for food. Soil nutrients such as nitrogen, potassium, and phosphorous, absorbed in the form of nitrates, are essential to soil health, and require high fuel and temperatures to trigger the process of fixing nitrogen and output emissions. QC could help improve yields and suppress by-product generation through a better understanding of reactions and finding new catalysts.
For instance, QC could enable a more efficient and less energy-intensive way of fixing nitrogen for fertilizer production. It can also help better understand chemical reaction mechanisms to design improved catalysts and optimize process conditions.
Another UN SDG is good health.
One area within the healthcare industry where QC could make an impact is faster and cheaper drug development by in-depth research on complex, multifactorial diseases. The dynamic of chemical bonds is governed by Schrödinger’s equation, which on a classical computer is not feasible except for simple systems such as diatomic molecules. To overcome this limitation, quantum chemists usually rely on approximate methods to solve this equation.
The technology could help formulate new products and mixtures through an improved understanding of complex molecular-level processes involved by expanded modeling and computational capabilities of QC that can help identify the most effective molecular designs or structures before synthesizing a single molecule in the lab. In the case of a protein folding problem, QC algorithms can also predict the three-dimensional structure of a protein from its primary sequence of amino acids.
Predictive health using novel real-world evidence technologies, multi-omics methods, and smart technologies require exceedingly smart experimental designs to fully use. QC could ease interpretative burden by processing such vast volumes of data at much faster speeds. QC also has tremendous potential in tissue rejuvenation, regenerative medicine, molecular repair, gene therapy, pharmaceuticals, and organ replacement, as well as in early, accurate, efficient diagnosis, and data management and processing in the healthcare industry.
The expansion of hybrid distributed energy resources such as residential, commercial, and industrial rooftop photovoltaics batteries and the emergence of new load categories such as electric vehicles have exponentially increased the amount of data required for network maintenance, analysis, security, and communications infrastructure.
Due to the constant fluctuation in power demand, it’s important to take real-time decisions while minimizing operating cost.
QC could help minimize carbon footprint through an optimal route using a quantum approximate optimization algorithm or Ising Hamiltonian, and using the minimum variational quantum eigensolver optimizer.
In addition, batteries are key to decarbonizing both transport and the grid. Quantum technologies could make lithium-sulfur batteries a viable replacement for lithium-ion cells, with benefits including low costs, fast charging, high power and energy density, strong energy efficiency, and low flammability. QC could model the energy state of pulse electrolysis to optimize catalyst usage and produce hydrogen to develop clean emissions, and boost energy efficiency.
With fossil fuels fast depleting, industries are trying to decarbonize and remain relevant by carbon capture and storage.
QC could help boost the development of mineralization-based building materials for cost-effective carbon mineralization, wherein minerals naturally react with carbon dioxide (CO₂) and convert carbon in gas form into solid form. It could be a way to remove CO₂ from the atmosphere by skimming and extracting it in a concentrated stream, which can then be compressed, transported, and stored.
QC can help in the simulation of molecules for developing new catalysts that are likely to consume less energy, and enable scalable negative-emission solutions through direct air capture and reduce the cost of synthetic hydrocarbons. This captured CO₂ could be used in the production of metals, plastics, and concrete.
As we can see, QC could help organizations act on strategy, track metrics, and orchestrate results in line with their ESG goals.
Though its transformative potential may take many years to fully realize, early adoption can start improving environmental posture and real-world decision-making. Here are some steps your firm could take to meet the goals:
Creating awareness among businesses, governments, and the public on quantum computers to prepare and leverage the arbitrage potential and develop climate-friendly technological solutions.
Fostering an environment of low carbon-emitting technologies and bio-based technologies using QC, which has the potential to solve complex problems.
Engaging with relevant businesses and partners to identify potential use cases and develop quantum algorithms with higher quality solutions.
Optimization and simulation to uncover new materials, new catalysts for carbon capture, and large complex molecules to reduce greenhouse gas emissions.