According to Climate-KIC, even though we're still emitting 17% less CO2 than in 2019, our current greenhouse gas emissions still exceed the normal rate by 80%. And this is one of the most significant drops we've had in recent years. If this situation continues, the economic damage resulting from climate change will equate to sustaining one COVID-like pandemic every ten years.
Fortunately, AI can significantly impact climate change by helping different sectors minimize their carbon footprint. Many organizations are already racing to deploy artificial intelligence as a service on their journey to becoming more sustainable.
So, can technology save us from climate change?
This article will help you discover how to apply AI in climate change reversing practices and make sure your algorithms don't cause excess pollution on their own.
A company from any sector can use artificial intelligence and its subtypes or other technology to fight climate change and reap the rewards. The benefits range from financial incentives to compliance to gaining a “green” status. Could AI solve global warming? Probably not by itself, but research shows that AI technology could help cut greenhouse gas emissions by 4% by 2030.
Governments support companies in their journey towards sustainability. The EU Innovation Fund pledged to provide €10 billion of support for companies that invest €7.5 million in sustainable technology between 2020 and 2030.
The US is also concerned with climate change. One of the first actions of the Biden administration was to rejoin the Paris Agreement. In November 2021, the House of Representatives passed a large spending bill of $2.2 trillion aiming to slow global warming. This bill features substantial tax benefits. For instance, it allocates $320 billion in tax incentives for producers and consumers of wind, solar, and nuclear power. Additionally, President Biden has a strong view of AI and wants America to lead the AI race.
Here are some of the main perks of embracing sustainability:
Waste processing is a challenging task as waste composition and quantity vary depending on seasons and regions. Therefore, fixed rules that human employees follow when gathering and processing waste are often inadequate. Installing climate tech, such as intelligent garbage beans and IoT sensors, can help municipalities adjust the garbage collection routes and frequency of waste gathering.
Governments and technology startups are working towards improving the current waste management and recycling systems. One example comes from Austria. The Graz Climate Fund and the Styrian Future Fund financed AI-Waste research project that is expected to deliver actionable recommendations on optimizing waste processing. The project commenced in 2021, and after two years, it expects to increase waste recycling by 10%.
To fight climate change, London-based startup Greyparrot, trained machine learning algorithms to recognize different types of waste to make recycling more efficient. The company claims that less than 1% of waste is currently being audited, and it wants to improve this situation. Recycling companies can install Greyparrot’s hardware-agnostic application into their facility to ensure waste is adequately sorted and recycled. The company obtained nearly $2.2 million in seed funding in 2020.
AI can rapidly analyze dynamic data, such as obtained from weather forecasting systems and create a simulation that scientists use for decision-making. This being said, machine learning-based weather forecast enables scientists to identify extreme conditions, such as hurricanes, with 89% to 99% accuracy.
Researchers at Montreal Institute for Learning Algorithms (MILA) are making the effects of climate change more visible to ordinary people. MILA’s team built an application that would let users see how their neighborhoods will look in the future given different climate change scenarios. Anyone can visit thisclimatedoesnotexist.com to apply realistic filters of flooding, fire, etc., and view how their selected locations will look (not all locations worldwide are available).
Here are a few heartbreaking images:
Another example comes from Japan. The Japanese government partnered with Accenture to launch an AI-powered system that will send disaster alerts to citizens’ smartphones. Subscription to this service is voluntary, and citizens can choose to opt-in when they are ready. The question of data privacy has been raised, but Accenture addressed it promptly.
Here is what Shojiro Nakamura, Co-lead of Accenture Innovation Center Fukushima said in this regard, “Most smart city data derives from citizens' activities - energy usage, healthcare, etc. - and the owner of the data is the citizen, even if it is held by companies or clinics. So it is critical that citizens have control over the degree to which their data is accessible.”
Another application of AI in climate stems from using drones to monitor the environment. Drones provide the easiest way to gather data on remote regions. Machine learning algorithms can analyze climate data from drone images, enabling scientists to monitor vegetations over large land areas for a prolonged period to understand how climate change impacts these locations.
AI can also analyze satellite images and predict changes. For example, Orbital Insight, an AI startup based in California, deploys convolutional neural networks to process radar data and identify virgin forests being destroyed and replaced with buildings and roads. This initiative is a part of the Global Forest Watch’s real-time forest monitoring efforts.
In another instance, a Canadian startup 3vGeomaticsn monitors thawing permafrost across the Canadian Arctic by processing satellite images. Permafrost is mainly found in Arctic regions. It contains ice and some organic material. It encapsulates around 1,500 billion tons of carbon, which is released into the atmosphere as permafrost melts. With this AI-powered technology, the startup can deliver timely insights regarding permafrost’s state.
AI-powered climate change solutions enable companies to measure their carbon footprint by setting a dependable emission baseline and monitoring progress. An AI startup from Finland, Aeromon, tracks industrial emissions in real-time. It can quantify emissions and visualize various gases and other matter.
AI-based climate technology can also accurately measure power plant emissions. Google offered a $1.7 million grant to Carbon Tracker to use its satellite-based technology to hold power plants accountable for their environmental impact. As a part of this grant, Carbon Tracker was expected to study emissions of around 4,000 power plants and make the results public if needed.
Oceans regulate our climate and generate half of the oxygen we breathe. But with global warming, they can turn into a threat. Think of storms and rising sea levels, which can displace up to 187 million people by 2100 if the ice continues to melt at the same rates. Climate change technologies can help us understand what’s happening with the oceans and prevent deterioration. Here is how Ronan Fablet, professor at IMT Atlantique, France, one of the winners of AI for Earth EU Ocean award, puts this:
“Data can help tell us about the health of our oceans, including temperature and rising sea levels. But we need technology’s help to capture this vast amount of data and convert it into actionable intelligence. Fundamentally, AI can accelerate our ability to observe ocean dynamics and how they are changing at a global scale”
When it comes to data, oceans are heavily underrepresented. There are 35 billion sensors positioned on land to gather data, while there are less than 10,000 sensors located in the ocean. Ocean Data Alliance uses IoT and AI to collect and analyze ocean data to build a digital twin ocean and understand what happens above, on, and below the ocean’s surface. This information enables decision-makers to monitor aspects, such as fishing, ocean mining, and the outbreak of marine disease.
The supply chain is an essential aspect of every business but also a costly one. Studies show that emissions resulting from a corporation’s supply chain are on average 5.5 times higher than that corporation’s direct emissions. The traditional approach to supply chain management doesn’t necessarily take demand into account, shipping excess items that will not serve any purpose. This results in extra costs and harms the environment. Artificial intelligence helps businesses fight climate change by accurately forecasting demand, allowing companies to only supply what will be consumed.
Another example of using AI to improve supply chain sustainability is to analyze how environmentally friendly your partners are. Audi has been piloting such an AI-powered application to assess its supply chain. This AI tool evaluates various environmental and social factors, including water pollution and waste problems. When the car manufacturer spots a violation, it demands immediate adjustments or terminates the contract.
Scientists are looking for new materials that would harvest, store, and use energy efficiently. AI can accelerate this tedious process. It can help discover new chemical structures and evaluate them against desirable properties. It can identify materials that absorb carbon dioxide or absorb and hold sunlight energy.
Researchers at the University of Liverpool developed a tool that uses neural networks to examine relationships between different existing materials and spot the most promising combinations that could potentially lead to forming new substances. With the help of this tool, the team recently discovered four previously unknown materials.
The United States Environmental Protection Agency revealed the sectors responsible for greenhouse gas (GHG) emission in the US. The transportation industry is leading the pack, followed closely by electricity and the industrial sectors. Below we will address these three sectors that contribute the most to polluting our atmosphere.
Everyone knows that vehicles cause emissions. But not everyone is aware that idle vehicles waiting for a traffic light or in a traffic jam waste over 6 billion gallons of diesel and gasoline annually.
AI technology can reduce climate change by facilitating traffic and minimizing shipment trips. It can:
Connect vehicles with the help of IoT technology, and allow them to communicate with each other and the infrastructure to avoid traffic jams and natural hazards. Together with computer vision, AI can identify traffic patterns and make intelligent recommendations regarding optimum routes
Analyze and bundle shipments together in such a way as to minimize the total number of trips, which would reduce emissions. Statistics show that around 30% of transport is running partially empty due to poor planning
Improve battery energy efficiency in electronic vehicles to increase the mileage the car can traverse on one charge, reducing “range anxiety”
Enhance vehicle design to increase its lifetime
Prevent accidents as machine learning for climate change can detect transport hazards, such as unstable vehicles and overloaded trucks, and mitigate accidents that would cause traffic congestion, which in turn results in more emissions
The city of Pittsburg, Pennsylvania, has pioneered using AI-powered traffic control technology. This tool operates traffic lights and communicates with autonomous vehicles that are being tested in the city. With the help of AI, Pittsburg cuts traffic jams by 40% and travel time by 25%.
The traditional method of electricity generation occurs in thermal power plants, which produce electricity by burning coal and its derivatives. Here is how AI technology can help combat climate change:
AutoGrid, an energy company headquartered in California, uses AI-powered applications to deliver insights on power usage. The company works with clients from ten countries and makes around a million predictions every minute. The company analyzes customer behavior and can spot fluctuating demands and inform its clients to adjust their supply.
Another example of a company working in this field is DeepMind, a Google subsidiary. It uses machine learning to analyze wind power and predict its output 36 hours ahead of the actual power generation. These calculations come in handy as wind power is highly unstable and unpredictable at times.
The industrial sector includes activities, such as manufacturing and food production, which uses fossil fuel to generate heat and facilitate chemical processes, emitting greenhouse gases. AI has numerous applications in manufacturing, and here is what it can do to help reduce pollution (these points were elaborated above):
Subaru’s Indiana division achieved an honorable zero-landfill status. The company turned to AI to categorize different materials used in manufacturing and make sure they are all properly recycled.
Chicago-based Uptake developed an AI-driven software that allows manufacturers to study their production data and make informed decisions to reduce their carbon footprint and increase product quality.
AI technology can impact climate change, but AI has its implementation challenges and the technology itself causes its share of pollution. Studies show that training a large algorithm emits approximately 626,000 pounds of carbon dioxide, which is five times higher than what an average car can produce throughout its lifetime. The more powerful and accurate the algorithm is, the higher is its resulting pollution. It’s a challenge to estimate the amount of emissions a particular algorithm can generate. It depends on various factors, such as the number of mathematical operations to be performed to train the model, the type of computer hardware used, and the physical data storage and cooling requirements.
Here are some practices that you can follow to reduce your algorithm’s carbon footprint:
Are you concerned with your company’s carbon footprint? Get in touch! ITRex AI experts will develop a solution that will help you redesign your processes in a way that reduces emissions.