Harnessing the Power of AI to Combat Climate Change

If nothing changes on the front of how we are treating the environment, by 2030 the global average temperature will rise to 1.5 degrees Celsius. While seemingly an insignificant number, the repercussions of this can be catastrophic with events like catastrophic heat waves, flooding, drought, crop failures and species extinction becoming significantly common.

We are living on our last chance where all the industrialized nations will have to join hands to slash greenhouse gasses by half of 2030 and then stop adding carbon dioxide to the atmosphere by the early 2050s. A delay by even some years will make the goal unattainable, assuring a hotter, more perilous future.

The situation is slowly getting out of human hands leading to a scope for adopting AI in climate change intervention.

In this article, we will look into two-sided facets of using artificial intelligence for climate change – one which highlights the need for technology to enter the cause and one which suggests otherwise. Ultimately, I will leave it up to you to decide the urgency of applying AI to the cause.

First thing first.

Why Should Your Business Care About Climate Change?

When it comes to tackling climate change, business as usual won’t work anymore. There are several compelling reasons why every business, yours included, should think about sustainability. Let us look at the top ones.

1. Customers are asking for it.

A research firm, Proedge, found that 78% of Americans would pay more for products with environmental/sustainable/charitable benefits. Increased media attention and public awareness about environmental issues have greatly influenced consumers’ buying habits. This has led to a situation where consumers are more likely to purchase from socially conscious companies.

2. Save on taxes or get tax breaks altogether.

The federal government offers multiple tax credits that prompt businesses to invest in renewable energy sources, like geothermal, solar, and wind. Your business might be eligible for a tax credit of up to 26% of the cost of solar energy system installation, using fuel cells with a capacity of 0.5 kilowatts or more, and setting up small-scale wind turbines with a capacity of 200 kilowatts and below. Other benefits can include – energy-efficient commercial buildings tax deduction and biodiesel income tax credit.

3. Investors are expecting it.

Companies which tend to prioritize sustainability have more potential to attract investments from ESG-driven funds and socially conscious investors. According to a study by Harvard Business Review, companies that focus on sustainability tend to have better financial performance and lower cost of capital, attracting more investors. It has also been found that ESG performers enjoy higher valuations by a margin of 20%.

4. It is impacting your supply chains

Climate change affects the supply chain in two ways – brings in long-lasting, severe weather events that can damage facilities, cut off resources, and disrupt travel. It also leads to rising sea levels which is highly used by global supply chains, so much so that climate change is known to cause $7.6 billion in losses for ports every year.

Reasons like these encourage businesses to look at technology, particularly AI to implement climate action in their processes. In response, several AI products and startups have entered the market, such as –

• ClimateAI – An enterprise climate platform to help companies reduce, monitor, and adapt to physical climate risks
• Gro Intelligence – Analyzes trillions of data points from multiple sources – crop forecasts, satellite images, topography – to give forecasts into unique agricultural products.
• Climavision – A forecasting solution that proactively updates businesses on weather events which might impact sales and business operations.

The Applications of AI in Climate Change

Possible delay or even mitigation of a dire situation will require fast-forwarded efforts towards immediate crisis response to long-term planning. AI climate change solutions are best suited for this because of their capacity to collect, construct, and interpret large, complex data fields on climate impact, emissions,  and more. This will ultimately support stakeholders in taking an informed and data-driven strategy to address carbon emissions and create a greener society. Let us look at some of the applications of Artificial Intelligence in climate change in detail below:

Climate Modeling

Global warming experts have been long using climate models to understand the complexity of interactions between the different components of the earth’s system so that the potential impact of climate change can be predicted accurately. AI climate change tools help enhance the efficiency and accuracy of the models by integrating a vast amount of data sets and processing them accurately. Moreover, machine learning can be applied to find patterns in the gathered data sets which may not appear to human researchers.

Energy Efficiency

Optimization of energy consumption and waste reduction is critical for making development sustainable. To address this, the industry is experimenting with an AI-powered smart grid management system that would manage the creation, distribution, and consumption of electricity efficiently.

This part of climate change AI can help with analyzing real-time data from multiple sources such as smart meters and sensors to identify patterns and predict energy demands accurately. The result? Better optimization of energy resource allocation, which doesn’t just reduce waste but also ensures that supply meets demand.

Also Read: Building Energy Management Systems for Carbon Neutrality

Carbon Capture

It is an approach which involves capturing carbon dioxide emissions released by energy and industry-related sources before their release into the environment. With the main intent being the minimization of CO2 release in the environment, AI is being used for the optimization of the operation and design of these carbon capture technologies so that they become more cost-effective and efficient.

Disaster Forecast

Climate scientists and meteorologists are utilizing artificial intelligence to predict and eliminate the climate-related natural disasters’ effects. With the technology on their side, they can analyze a massive amount of datasets to find trends which indicate the chance of impending disasters, following which they can build and deploy an early warning system to minimize the loss of property and life.

Ecosystem Tracking

A critical part of measuring the impact of climate change is tracking the shift in natural resources and biodiversity. AI use in climate change can be seen in using tools that would process massive amounts of data coming in from drone footage, satellite imagery, and other sources. Conservationists can also utilize machine learning algorithms to find patterns in changing land covers and species distribution.

Fast Fashion

The fast fashion industry is a powerful contributor to the climate crisis, liable for as much as 10% of global carbon dioxide emissions. Noting its global reach and size, unsustainable practices within the fashion industry can have long-lasting impacts on the environment. This is where AI climate change solutions come into the picture. Machine learning and artificial intelligence can help with the optimization of the supply chain to lower waste, promote sustainable manufacturing, and track resource consumption.

Agriculture Optimization

Another emission-heavy sector, agriculture, leads to 22% of global greenhouse gas emissions. From small-scale farmers to big corporations, the issues of water scarcity, unpredictable weather events, and land degradation are similar across the sector. AI for climate change can help with this through smart grids. These grids can efficiently balance supply and demand, enabling the integration of renewables in energy systems and lowering the dependency on fossil fuels.

Methane Detection

The heavily potent pollutant, which gets released by agriculture, energy, and landfill sectors is the second biggest contributor to global warming, constantly competing with carbon dioxide for the first spot. Companies are merging AI and climate change to help interpret massive amounts of satellite images that track global methane emissions on an everyday basis.

The technology comes aligned with the growing nations-wide focus on methane monitoring with dedicated regulations being passed such as by – the U.S. Environmental Protection Agency and the European Union.

Green Tech Mining

Climate-focused solutions right from electric vehicles to solar panels need a massive amount of minerals such as lithium, cobalt, and copper. However, the current supplies are far from meeting the growing demand.

To take charge of this situation, researchers, governments, and companies are using artificial intelligence and climate change to find critical minerals. It has been found that there is a lot of data present on what is under the earth’s surface. Utilizing AI to look into those datasets will not just minimize uncertainty but also save billions of dollars that are spent looking for profitable areas to extract.

Also Read: How AI, IoT, and AR/VR Technologies are Helping Companies Achieve Their Sustainability Goals

These are only surface-level uses and roles of AI in climate change, the entire scope, while up to the imagination, generally lies among five elements –

• To collect and complete complex datasets on climate effects, emissions, and more
• To strengthen decision-making and planning
• To optimize operations
• To support collective ecosystems
• To encourage climate-positive events

BCG has done an amazing job at categorizing the role of artificial intelligence for climate change into a framework.

Now that we have looked at the wide-ranging applications of AI in climate change, some things are clear. The sector is ready for technological intervention leading to a situation where demand for climate-focused smart tools and queries like how to develop an AI platform like climateGPT or CO2 AI is on the rise.

However, this optimism from the technology is in no way a sign of the perilous situation coming under control. Humans and institutions will still play the biggest role in bringing the efforts back on track when it comes to meeting the targets set by the National Climate Task Force.

Taking the conversation on AI in climate change benefits ahead, let us look into an infographic that lists down the real-world applications of artificial intelligence in climate change.

This would give you an idea of the initiatives that are being taken towards combining the technology with the cause.

Up until this point, we have looked into the benefits of AI in climate change and companies that are using the technology to turn these benefits into reality that changemakers can utilize. But does this mean we are ignoring the computing power and electricity the AI system needs to run?

OpenAI GPT-3 and Meta’s OPT were found to emit over 500 and 75 metric tons of carbon dioxide. What is worse is that the precise effect AI would have on the climate crisis is impossible to calculate, even if the focus is kept on the greenhouse gas emission amount. This is because there are many different types of artificial intelligence – such as an AI and ML model that spots trends in research data, a vision program that helps self-driving cars avoid obstacles or a large language model (LLM) that enables a chatbot to talk naturally – all with different amounts of computing power requirements to train and run.

Another angle to look at here is if the technology is helping one side of the coin, it has also been built to empower the environment perpetrators. In 2019, for example, Microsoft announced a partnership with ExxonMobil, mentioning that the company will use Microsoft’s cloud-computing platform, Azure. The oil giant stated that by this partnership, which relied on using AI for certain tasks such as performance analysis, it could optimize its mining operations and, by 2025, increase the oil production by 50,000 oil-equivalent barrels per day.

Balancing this equation ultimately falls on the responsibility of policymakers, companies using AI, and the companies building artificial intelligence development services.

Appinventiv’s Bit in Making AI Greener

At Appinventiv, we consider ourselves to be one of the most carbon neutrality-focused organizations. When we build applications we work with a millstone around emissions we will leak out into the environment.

Some of the practices we follow with augmenting AI and climate change throughout our SDLC include –

• Using existing large generative models
• Using energy-conserving computational methods like TinyML and microcontrollers
• Fine-tuning generative models
• Using tools like ML CO2 Impact Calculator for measuring the level of carbon dioxide generated during the machine learning models’ training.

For us, the AI software development approach is always around how we can utilize existing models to their full capacity. Forcing ourselves to look at energy-conserving limitations, ultimately drives us towards new and creative AI innovations.

FAQs

Q. How can AI help climate change?

A. The answer to whether AI solves climate change lies in the hows. Here are some ways that AI can help with climate change. Climate Modeling, Energy Efficiency, Carbon Capture, Disaster Forecast, Ecosystem Tracking, Fast Fashion, Agriculture Optimization, Methane Detection, and Green Tech Mining.

Q. What is Green AI?

A. Green AI is about algorithm development that uses less data and computational resources. As a result of this, the need for energy-intensive computations gets lowered without any significant impact on the AI model’s efficiency.

Q. How can companies lower AI model’s carbon emissions?

A. There are a number of ways companies can build greener AI –

• Upgrade or fine-tune the existing models.
• Use less energy-heavy computational methods.
• Design the IT architecture for sustainability.
• Monitor energy consumption, hardware utilization, and data storage to find opportunities for becoming more energy efficient.

THE AUTHOR

Sudeep Srivastava

Co-Founder and Director