AI Helps Business Become Greener To Fight Climate Change
Global climate change is accelerating, leading to floods, droughts, anomalous wildfires, marine heat waves affecting entire ecosystems, and dirty air choking cities and towns.
Author:Elisa MuellerReviewer:James PierceOct 25, 202230 Shares586 Views
Global climate change is accelerating, leading to floods, droughts, anomalous wildfires, marine heat waves affecting entire ecosystems, and dirty air choking cities and towns.
In 2021, the UN issued a dire warning that the "internationally agreed threshold of 1.5 degrees above pre-industrial levels of global heating was perilously close.” Transformational change is needed to prevent the worst impacts, it said.
Climate tech powered by artificial intelligence (AI) is seen by many as the answer we need at this juncture.
As different forms of AI are evolving, including machine learning, big data, and computer vision, companies have rushed for artificial intelligence consulting helpto become more sustainable.
In this blog, we will look at how business is exploiting opportunities offered by AI innovations to join the battle against climate change.
Why companies leverage AI for sustainability
Apart from stepping in to bolster collective action on climate change, organizations across sectors enjoy immediate benefits from embracing ML and other AI solutions for sustainability. These include:
- Tax breaks and other financial incentives for carbon footprint reduction
- Positive impact on brand reputation, attracting more consumers and driving stock returns
- Readiness for future regulation addressing climate change
Sustainable business practices are good not only for the planet. Companies that put them at the heart of their operations also improve efficiency, which leads to a better bottom line.
How companies incorporate AI to address climate change
AI can process immense volumes of structured data and unstructured data, including images, graphs, and maps, with ease, at scale, and at speed to uncover patterns and make predictions.
In the climate change context, this means that AI can enhance climate predictions, improve decarbonization decision-making at the level of entire industries and individual companies, identify risk factors, and work out a better response to them.
Capgemini Research Instituteforecasts that AI can help companies across industry verticals achieve up to 45% of the Paris Agreement targets by 2030 while reducing greenhouse gas (GHG) emissions by 16%.
Below are a few examples of how AI already enables companies to achieve green transition:
Reduction of emissions
Through the use of artificial intelligence and machine learning solutions, organizations can efficiently monitor, predict, and manage their carbon footprint.
For instance, the leading oilfield services provider NESRuses an AI platform in combination with IoT technology to continuously monitor gases in remote fields in real time. For the same purpose, VL Energyhas built predictive emissions monitoring systems that power predictive models based on combustion equipment operating parameters to measure air emissions.
Beyond the energy sector, data centers are also leveraging AI-based carbon accounting tools to analyze data on their energy consumption and gauge their carbon emissions.
Waste management
Efficient waste management has long been a top-of-the-mind priority for municipalities and organizations alike. Many of them are now embracing AI-based innovations for optimizing and automating collection, separation, and recycling processes.
Novel solutions range from smart bins that sort waste at the point of disposal to complex recycling systems combining AI, computer vision, and robotics. One example is a sensor-based robot gripper arm built by the Alba Groupfor sorting packaging at its lightweight packaging plant in a German city. Another illustration is an AI-powered computer vision system developed by London’s startup Greyparrotthat has trained a number of ML models to enable its system to distinguish between glass, paper, cardboard, newspaper, plastics, and other sorts of waste.
Research projects are also underway to exploit AI for improving waste processing. One of them, AI-Waste Projectlaunched by the European research center Know-Center, is projected to increase the recycling share by at least 10% by using image recognition and data analysis.
Supply chains
Supply chains are a main contributor to GHG emissions, accounting for an average of 5.5 times of direct emissions attributed to big companies (as reported by CDP). Leading organizations are embracing AI and automation technologies to improve supply chain sustainability and resilience.
Integrating ML and adding new sources of data, AI systems help better match supply and demand, reducing perishable waste in the food and retail industries and allowing manufacturers to avoid unnecessary transportation and production costs. Accurate forecasting is also key to optimizing inventory through adjusted shipment frequencies or the bundling of freights with other supplies. Such measures ultimately help reduce carbon emissions across the supply chain.
Precision agriculture
According to MarketsandMarkets, investments into AI in agriculture are expected to increase fourfold in 2026 from $1 billion in 2020.
Agricultural businesses already use AI tools to improve crop management for better yields and sustainability. For instance, an AI-based disease and pest detection system helps NatureSweet not only increase its tomato yields but also protect the environment.
By monitoring and analyzing temperature, soil composition, expected precipitation, and other data, AI enables farmers to save resources such as water, fertilizers, and electricity and contribute to the fight against climate change.
More efficient transportation
Accounting for roughly a quarter of CO2 emissions globally, the transportation sector faces a serious decarbonization challenge. AI is poised to play a key role in making the sector greener.
From powering autonomous vehicles, including shared transportation systems, to preventing traffic jams, AI is already reshaping transportation for a cleaner environment. Using sensors and cameras, smart systems analyze complex data to offer drivers more optimal routes or adjust traffic lights to cut idling. The city of Pittsburg, for instance, has cut down travel time by 25% and traffic jams by 40% percent using smart traffic technology and AI for recognizing traffic activity.
Concluding thoughts
Artificial Intelligence can be a game-changing tool that we have at our disposal in the 21st century to solve climate change. We don’t even need superintelligent AI systems for that. Adding up smaller-scale and cheaper AI solutions to climate change in different sectors can create a huge cumulative effect.
Elisa Mueller
Author
James Pierce
Reviewer
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