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The Role of AI in Combating Climate Change
To solve critical problems facing our environment and sustainable development needs, various AI techniques can be applied to long-term strategic planning, shorter-term infrastructure design and construction projects, and more.
5 Min Read
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July 2023 was the hottest month on record. Unfortunately, it is just another data point confirming the frightening pace of climate change. Since the mid-20th century, greenhouse gas emissions have been the most significant cause of global climate change.
Did you know infrastructure causes 79% of all greenhouse gas emissions? To effectively tackle climate change, we need to address infrastructure’s role in driving climate change, as well as explore how infrastructure can reduce its carbon footprint. One way to do that is by applying the latest technologies and innovations.
Artificial intelligence can be a powerful ally in combating climate change across the infrastructure lifecycle, from reducing an asset’s carbon footprint during design and construction to resilience planning for existing infrastructure. To solve critical problems facing our environment and sustainable development needs, various AI techniques can be applied to long-term strategic planning, shorter-term infrastructure design and construction projects, and more.
AI, Climate Change and Strategic Planning
For long-term strategic infrastructure planning, predictive AI techniques can help government agencies, relief organizations and other stakeholders to analyze past incidents or simulate natural disasters, the movement of people, and social unrest. They can forecast the impact on infrastructure as well as identify areas that need preventive safeguards. From these simulations, organizations can proactively implement solutions like fire breaks, levees, green zones and to establish disaster recovery plans that include communication trees, evacuation routes, and more.
A good example of the use of predictive AI is in Lagos, Nigeria. Experts believe that by 2050 rising sea levels could make half of Lagos unlivable, leaving 24 million residents with nowhere to go. By the end of the century, with no intervention, the entire metropolis will be unlivable, driving people to neighboring cities and towns, which are ill-equipped to deal with such rapid and immense population growth.
Using AI simulation technologies to predict future movements, the Nigerian government is planning for the changes with proactive programs and investments such as dredging, the construction of an 18-kilometer embankment, and multiple seawalls. Lagos is also creating better drainage systems and improving waste removal so that storm drains operate more efficiently in the event of flooding.
AI in the Near-Term Infrastructure Lifecycle
In the more immediate term, AI can be used across the infrastructure lifecycle to reduce an infrastructure asset’s carbon footprint and meet sustainable development goals.
During the design phase, AI can help create more sustainable, efficient, and resilient infrastructure. For example, generative design capabilities could combine reusable components, parametric design and AI to help practitioners plug in constraints and receive design options that meet the asset’s requirements. Such constraints could, for example, be maximum carbon output, ability to withstand high temperatures or sustained wind, local topology. While the designer would need to further hone the design, AI and parametric designing could speed up the process to deliver better outcomes.
The construction process undergoes several phases, starting with production and transportation of materials, which alone account for between 82% to 96% of the total CO2 emissions during the construction phase. Generative AI can help plan the most effective build process that minimizes environmental impact and produces the lowest carbon footprint.
AI can analyze and compare the emissions of oil, cement mortar, iron, steel, and concrete production and transportation, seeking materials with the lowest carbon footprint. With such powerful analysis, companies can pursue strategies to use alternative building materials, recycle construction waste, and promote alternative water resources to reduce emissions during construction. In addition, generative AI can use building design software and mixed and augmented reality to let owners and municipalities visualize projects before they’re built. This can minimize the environmental impact of infrastructure construction by reducing rework, material use, and energy consumption further helping to mitigate climate change.
AI can ensure that infrastructure operations minimize carbon and other emissions while staying safe and resilient. For example, AI-based systems can assist with predictive maintenance by analyzing sensor data on system components, including everything from environmental factors to structural elements. The analyzed data helps assess asset health, schedule repairs, and optimize maintenance, all of which can lead to lower emissions.
For example, if a wind turbine alerts the owner to a malfunction and there is scheduled maintenance on the next one within a reasonable time period, AI can identify and group these tasks, reducing the number of trips to the site. Finally, remote-controlled sensors can measure and monitor carbon releases in applicable industries such as oil and gas, and that data can project future output, so owners can adjust operations to reduce the impact on the environment.
Residents of the United States will remember the devastation caused by Hurricane Katrina, but levee breaches are certainly not unique to the US. Researchers at the University of New Orleans want to use AI to evaluate and detect potential deficiencies in the US floodwater control structures. The plan includes creating an automated program using unmanned aerial system imagery and other sensory data to assess the integrity and stability of that nation’s flood-control systems. The AI-based system evaluates deficiencies such as slope instability, cracks, sand boils, or seepage. Those could lead to failure, such as a levee collapse. The information will help stakeholders and emergency planners make rapid decisions, especially when infrastructure is at risk due to flooding or storm surges.
AI and Sustainable Infrastructure
As we seek to improve the health of the planet and the quality of life for people everywhere, it is critical that we reduce infrastructure’s contribution to climate change by exploring and investing in sustainability. This means building and maintaining infrastructure that adapts to future climate conditions; contributing to the decarbonization of the economy; protecting biodiversity; and minimizing pollution.
In many ways, it’s the early days for AI in the fight to combat climate change. However, with the right techniques and applications, AI has more than enough potential to drive outcomes that will greatly improve the design, construction, operations, and planning of sustainable infrastructure.
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