A Green Future: 10 Ways to Achieve Carbon Neutrality with AI
Carbon neutrality is the most talked-about subject and also the focal point behind innovations and decisions that most of the tech giants (read Apple, Meta) are making today. Protecting our environment, and reducing carbon emissions, is not a man’s job; it is a collective effort by leaders, organizations, governments, and industries.
A lackadaisical approach towards climate change from any of them can seriously jeopardize the entire ecosystem to an extent we can’t imagine. To genuinely combat climate change, we need to stop thinking about global warming as a bane of our existence, and instead, aggressively find measures to get a handle on it.
And, the first and the most logical answer is to work alongside machines, i.e. leverage AI to achieve a green future and a healthier environment. Artificial intelligence can help to create a healthier environment and reduce carbon footprints.
According to Capgemini Research Institute modeling, AI is expected to help businesses in a variety of sectors, including consumer goods, retail, automotive, and more, achieve up to 45% of the Paris Agreement targets by 2030. And, there are good chances that AI will lend a helping hand to reduce GHG emissions by 16%.
The Paris Agreement
Let’s take a little recap of the Paris Agreement when the basic step towards a carbon-neutral future was taken in 2015 by the European Union and its member states. The international treaty on climate change aims to keep global warming below 2 degrees Celsius by bringing forth economic and social transformations.
Defining Carbon Footprint
A carbon footprint can be defined as the total amount of greenhouse gas emissions by anybody or anything – it could be a person, an event, a product, or an organization. Greenhouse gases refer to the gases in the atmosphere which primarily cause global warming and climate change.
To put it in simple terms, an individual who uses his own car every day to commute to work will have a bigger carbon footprint than someone who carpools with his colleagues or uses public transport to travel to work.
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Carbon Footprint – Lifestyle Causes
But the question remains, how and where to begin the process of reversing the adverse effects our environment has seen already? How can we decrease our effect by identifying the aspect of our lifestyle that has the biggest impact? Will a switch over to veganism help? Will waste reduction be of any help?
The numbers below may surprise you:
- Compared to cereals or vegetables, meat products have larger carbon footprints per calorie. This is due to the fact that animals including cattle, sheep, and goats produce large amounts of methane gas.
- The carbon footprint fact sheet compiled by the Center for Sustainable Systems at the University of Michigan indicated that cattle generated around 170 million metric tons of CO2e of methane in 2016.
- On average, a single American household produces 8.1 metric tons of CO2e in one year just from eating.
- 83% of emissions are caused by the production of food, while 11% are caused while transporting it.
- The Center for Sustainable Systems explains that you can save 1,200 pounds of CO2e every time there is a 10% reduction in waste.
- And this not just applies to recycling, but also to buying products that have less packaging.
- NuEnergy states that the two components that constitute 67% of generated electricity are fossil fuels and coal. Think out loud when you leave the switch on next time.
- And last but not the least; big corporations are accountable for the biggest carbon footprints. A report by environmental non-profit CDP, in collaboration with the Climate Accountability Institute revealed that 100 companies contribute to more than 70% of the world’s emissions.
As shocking and revelatory as these numbers may be, are these basic minuscule lifestyle changes help to attain the carbon neutrality we all envision? Will it be enough for the bigger picture aka the Paris Agreement? We need to partner up with technology to get accurate facts, numbers, and analysis.
AI’s Role in Achieving Carbon Neutrality
From reporting earthquakes and reducing road accidents to streamlining parking woes and contributing towards smart cities‘ sustainability goals, artificial intelligence has been the strong scaffolding across industries and our daily lives too. In the current time, when climate change has become a pressing point across the world, artificial intelligence plays a crucial role in enhancing the climate change strategy, limiting greenhouse gas effects, and bringing forth equilibrium in our ecosystem.
Let’s take a look at some of the most promising ways that artificial intelligence will contribute towards carbon neutrality and climate change strategy.
1. Monitoring Plastic Pollution
Combating plastic pollution is an urgent matter courtesy of the history of overuse which has now resulted in full-blown plastic pollution. Plastic is everywhere – in seas, oceans, space stations, medical equipment, stationeries, etc. And do you know what’s worse? There’s something called ‘an island of plastic,’ which is, unfortunately, thriving. That’s because, annually, oceans get a whopping 12 million tons of plastic resulting in these gyres.
A non-profit organization called The Ocean Cleanup, whose sole mission is to make oceans plastic-free, and remove ‘90% of floating ocean plastic by 2040.’ This ambitious goal is backed by AI’s object detection algorithm which detects floating macro plastic litter. This is, obviously, way better than manual data-collection efforts, which are enormously time-consuming. This tool helps to create maps and identify hotspots that need working.
Though most plastics are anticipated to persist for decades or centuries after usage, those that do disintegrate turn into tiny plastic particles that are eaten by fish and other marine life and swiftly enter the world’s food supply. Here are some facts revealed by the UN.
- Every year, 500,000,000,000 plastic bags are used.
- Every year, 13,000,000 tons of plastic leak into the ocean.
- Every minute, 1,000,000 plastic bottles are bought.
- Every year, 100,000 marine animals are killed.
2. Predicting Deforestation
In order to forecast deforestation in unaffected areas, Deloitte and WWF launched the Deloitte Impact Foundation project. Deloitte uses satellite photography to make it feasible to assess the likelihood of deforestation based on details like the distance to towns, water sources, and other important considerations.
By using artificial intelligence to forecast where illegal deforestation will occur using satellite imagery (radar technology) and other geographic information, this technique stops illicit deforestation.
Sulabh Soral, a leader at the UK Deloitte AI Institute, states that,
“The route to sustainability is really building machine learning algorithms and pipelines that are more energy efficient. I think we have to be very choosy, clear, and deliberate in how we design these systems and how we leverage what’s already existing smaller or simpler algorithms.”
3. Optimizing Clean Energy
Hydropower dams are known to provide significant amounts of electricity with carbon footprints comparable to those of solar and wind energy. However, some dams produce hazardously high levels of greenhouse gases due to their structure, endangering sustainability objectives.
Traditionally, developers of Hydropower dams built in the Amazon basin did not have very clear long-term planning. To optimize this process, a group of ecologists, computer scientists, and researchers from Cornell University took it upon themselves to look for the safest and best locations ideal for building hundreds of hydropower dams that are likely to produce the lowest amounts of GHG emissions.
The AI model identified a more intricate and unexpected set of factors than had ever been taken into account for reducing GHG emissions. The model allows the researchers to determine which set of dams, given a target energy output, would result in the least amount of greenhouse gas emissions. Currently, there are over 150 hydropower dams, and another 350 are proposed for the Amazon basin.
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4. Monitoring Agricultural Input
Agriculture is as much a contributor to the climate change situation as plastic or fossil fuels. Presently, the agricultural sector is responsible for 19–29% of global greenhouse gas (GHG) emissions. And if appropriate steps are not taken, that percentage might significantly increase as other industries cut their emissions.
The Bangalore-based startup, Brahm Works is leveraging AI to decarbonize India’s agriculture sector. They use artificial intelligence to track and optimize fertilizer nutrition for improved yield and lower greenhouse gas emissions for farmers. The brand’s story began with exploring and discovering the one major issue in the agricultural sector – excessive manure usage which constituted higher amounts of Greenhouse gas (GHG) emissions. This eye-opener of the situation pushed them to come up with an AI-driven precision fertilizer and nutrient feeding. This solution enhanced yield, lowered GHG emissions, and maintained soil health.
5. Scaling up Energy Efficiency
When we think of carbon neutrality, one of the most vital aspects of it is to fuse business and sustainability goals. One organization that is strictly adhering to this is IBM. The tech behemoth is assisting its customers to achieve their sustainability goals with its data-driven developing solutions. One example is employing AI for enhanced energy efficiency in data centers and IT operations.
The organization is making use of tools such as IBM LinuxONE and IBM Instana for Observability, to empower its clients to track as well as bring down data center energy consumption in real time. LinuxONE is a sustainable and highly secure Linux server, designed for companies of all sizes.
In the next five years, improved company results will be driven by sustainability initiatives, according to more than 80% of CEOs. Although 86% of businesses have a sustainability plan, just 35% have implemented it.
- Reduce your energy, space, and CO2 footprint.
- Discover opportunities for greenhouse gas reductions.
- Power monitoring at the partition level.
- Monitor sustainable factors.
- The personalized total cost of ownership estimate along with sustainability goals.
6. Natural Disaster Forecasting
Sipremo, a startup is utilizing AI to ensure cities are clean, safe, and at the same time sustainable. They have created an AI that can tell users where, when, and what kind of disaster or climate change event is likely to happen in the future, giving them a huge window of time to take action before the events take place. This further helps in avoiding the negative environmental impact the catastrophic event was likely to have.
The brand’s website clearly states that they are an ‘AI-driven solution for proactive resilience building, reducing reactivity in natural disaster management, and empowering intelligent decision-making to deal with climate change for businesses and governments.”
7. Predicting Climate Change
Deep learning is a part of AI that uses a machine-learning technique that mainly works with patterns in data. A startup named Kettle uses deep learning to predict the negative effects of climate change. With a smarter reinsurance model, Kettle can better protect the communities and ecosystem by predicting the catastrophic effects.
Did you know that hurricanes, extreme temperatures, and wildfires caused 2.98 trillion in losses and around 1 billion climate catastrophes increased three times? And out of these, Kettle predicted 89% of them accurately. The machine learning algorithms work with more than ‘seven billion lines of weather and ground truth data’. The top 20% of risk locations for wildfires were correctly forecasted by their most recent fire model.
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8. Adopting large-scale, renewable energy
Did you know that 71% are okay with paying a price to become a sustainable brand?
Watershed, a company established in California, is working to hasten the uptake of clean, renewable energy and power desalination. They offer comprehensive solutions that cover everything from early-stage market analysis to technological deployment. Watershed reveals to businesses the origin of every kilogram of carbon. It analyses Scope 3 emissions using granular information on particular suppliers, compares them to the market, and finds high-emitting vendors and categories. Watershed focuses on measuring, reporting, and bringing down your emissions in a span of a few weeks. With the help of a panel of climatic experts, policymakers and professors, and consultants, Watershed’s carbon data engine at Watershed examines emissions for each line item in your company.
9. Optimizing the Biggest Energy Consumer
The United Nations recently revealed that building and construction CO2 emissions reached a new high, putting the industry off course to decarbonize by 2050.
Brainbox AI, a Montreal-based company with a passion to heal the planet and helping communities attain their decarbonization goals states that 20% of GHG emissions are produced by buildings. The self-adapting artificial intelligence technology is used to proactively optimize one of the biggest energy consumers and GHG emitters in the world: buildings. Jean-Simon Venne, Co-founder & CTO confidently asserts that Brainbox’s state-of-the-art technology has the capacity to remove 2 gigatons of CO2.
10. Streamlining Waste Management
The World Bank predicts that from 2020 to 2050, yearly waste handling would increase by 73%, reaching around 3.88 billion tons.
AI has a huge part to play when it comes to collecting, processing, transporting, and sorting all kinds of waste. One of the easiest and simplest ways to modify the way the climate is affecting the planet is through effective waste management. As waste management gets more complex, robotics combined with AI and machine learning have improved worker health conditions and the quality of the process.
Let’s take a look at how smart recycling bins work.
When waste is being disposed of, a smart recycling container keeps track of and separates it. Smart Recycling bins use artificial intelligence, computer vision, robots, and machine learning to efficiently and accurately sort garbage.
- The camera scans the waste and sends details to servers.
- AI and computer vision classify waste under different categories.
- Robotic automation puts the waste in appropriate bins.
- Sends a notification when the bin is full.
Be it predicting wildfires or the effects of natural disasters, streamlining waste management, or contributing towards greener buildings, there are numerous areas where AI has shown significant potential in decreasing carbon emissions. Needless to say, machine learning and artificial intelligence are equipped with sophisticated tools and enormous potential to gather, complete, and interpret huge amounts of data on climate change and carbon emissions and these can help individuals and companies support carbon neutrality.
Addressing climate change is complicated but with AI-driven hardware and software solutions there’s a silver lining and we, by all means, achieve carbon neutrality within our lifetimes.
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