How Does Artificial Intelligence Help Fight Climate Change?

Did you know a study by PricewaterhouseCoopers estimated that AI applications in energy systems can reduce global greenhouse gas emissions by up to 4% by 2030?

If 4% seems like a small fraction, consider this: the world currently emits approximately 53 billion metric tons of greenhouse gases annually. Even a 4% reduction would eliminate emissions equivalent to those produced by 460 million oil-powered cars, substantially impacting global carbon levels.

AI’s potential extends far beyond theoretical applications, emerging as a crucial ally in the escalating fight against climate change, with Los Angeles forest fires being a recent example.

From real-time monitoring and early detection of shifting weather patterns to predicting natural disasters and optimizing energy consumption in vehicles, factories, and buildings, AI offers practical, impactful solutions. These advances bolster environmental resilience and promote sustainable agriculture, paving the way for a greener, more secure future.

While many political and technological challenges remain, advancing AI and advocating for AI adoption can accelerate global efforts to combat climate change effectively.

How Can AI Save the Environment?

What we know of the global economy exists in four sectors -agriculture, transport, energy, and water. Together, these sectors form the four pillars of sustaining human life and economic growth, but climate change may pose a significant hurdle.

Climate change may directly or indirectly impact the four pillars.

1. In agriculture, rising temperatures, unpredictable rain, and extreme weather changes may threaten crop yields.
2. In transport, frequent and severe storms can damage infrastructure like roads, bridges, and ports.
3. As for energy, less rainfall means reduced hydropower capacity, heat waves can strain power grids, and less sunlight may inhibit solar power.
4. Lastly, water seems scarce or unpredictable in many regions. Droughts and floods can destroy human lives, forests, farmlands, and infrastructure.

While governments, organizations, and individuals have worked on these challenges for years, progress remains slow. So, where can we find a faster, more effective solution? Artificial Intelligence is the answer!

For example, the UN Environment Program uses AI tools to detect when oil and gas installations vent methane, one of the major greenhouse gases, foreboding possible disaster.

AI for Climate Monitoring and Prediction

AI algorithms and tools can significantly enhance climate monitoring by analyzing photos and data from satellites, sensors, and environmental agencies to detect changes in temperature, weather patterns, and vegetation.

They are packed with machine learning models and feed real-time data, helping display current and possible future scenarios much faster than a human would.

• Google’s AI-powered Environmental Insights Explorer (EIE) is a freely available tool that helps measure carbon emission sources using satellite imagery. Just type in the city and check the building and transportation emissions.
• Space agencies and institutes can leverage AI to analyze satellite images to monitor ice cap melting, rising sea levels, and deforestation. The University of Leeds has designed an AI model to map large Antarctic icebergs in satellite images in one-hundredth of a second.
• IBM's The Weather Company uses AI analytics to provide more precise local forecasts and climate predictions.
• Similarly, the RFCx Guardian device uses AI and machine learning to constantly gather data on the surrounding environment to detect threats of poaching and deforestation.

AI for Renewable Energy Optimization

Transitioning to renewable energy is crucial for reducing carbon emissions and ensuring a better future for all.

Fortunately, tech agencies have already trained AI models to track fluctuations in weather conditions, such as predicting wind patterns and cloud directions to optimize energy management.

• DeepMind and Google’s AI-powered wind energy forecasting system allows engineers to optimize wind farm output by predicting wind power output 36 hours in advance, maximizing the efficiency of wind farms.
• IBM's AI-driven smart grids track energy output and distribution from solar panels to reduce possible energy wastage and optimize electricity distribution.

AI for Sustainable Agriculture and Food Production

Did you know agriculture contributes 25% of global greenhouse gas emissions

The future of humankind lies in sustainable agriculture and food production to ensure optimal crop yields and protect existing crops from diseases.

• AI apps like PEAT by Plantix can monitor crop health and growth, detect early signs of diseases and stress, and predict rainfall and temperature in the coming days to give farmers a heads-up.
• John Deere's Mobile Farm Manager can help with resource optimization, such as determining water requirements by monitoring soil moisture levels, identifying nutrient deficiency through soil samples, and reducing reliance on chemical inputs by favoring other options. Enabling AI in farming can help prevent the risk of deforestation, detect methane emissions from livestock, and improve inefficient farming practices.

AI for Reducing Carbon Emissions

Transportation alone is responsible for 20% of global carbon emissions, while the petroleum industry contributes an additional 15% to the total greenhouse gases.

Any chance of reducing these emissions can considerably sustain climate in the coming years, drastically reducing the risk of unpredictable weather patterns like less or more rainfall, droughts, and warming temperatures.

• Many environmental agencies have adopted Google Maps and Waze to monitor traffic and infrastructure systems to optimize traffic flow.
• Smart traffic management systems like those used in Pittsburgh, USA, have reduced traffic congestion by 40%, reducing emissions from idling vehicles.
• Companies like Tesla and Waymo are leveraging AI to develop more efficient vehicles to reduce fossil fuel usage.

AI for Predicting Climate Disaster

Climate disasters globally are common occurrences lately, causing human fatality and billions in loss. AI-aided systems can predict these disasters to provide early warning.

The state of Los Angeles had pre-warnings about forest fires but was pretty slow to act on them. However, that does not mean AI failed. AI is critical in mitigating, managing, and responding to climate disasters by providing early, data-driven insights.

A company called Sipremo in Brazil uses AI to predict where and when climate disasters will occur. It gathers public, private, and international data to forecast and generate operational insights to guide decision-making.

Therefore, AI and machine learning software can help a great deal in natural disaster management or at least forewarn people to prepare themselves.

AI for Cleaning Up the Ocean

Litter buildup in the ocean has become a stark threat to aquatic biodiversity, increasing the risk to the dwindling marine animals.

Plastic waste often causes entanglement, ingestion of microplastics, and toxic buildups, leading to habitat destruction and effects on biogeochemical cycling.

Cleaning the ocean isn’t easy, but AI can accelerate the process by monitoring plastic waste through satellite and aerial imagery, deploying autonomous drones to remove debris, and intercepting trash in rivers before it reaches open waters.

Sensor networks connected to AI platforms can monitor where waste is likely to accumulate, and smart buoy systems powered by AI analytics can detect plastics and microplastics, notifying local authorities for quicker response.

Challenges in Adopting AI

AI has the potential to supercharge climate action. Yet, it requires strict ethical oversight, a proactive stance from government and agencies, and the development of greener tech to prevent escalating inequalities down the line.

1. Regulatory and Policy Barriers:  Lengthy bureaucratic procedures, funding gaps, and a lack of willingness from any party to share data and resources can stall progress, undermining the potential impact of AI-driven initiatives.

For AI adoption to succeed, governments, private sectors, and environmental agencies must collaborate, supported by endorsements from top public offices and firm commitments from private stakeholders.

2. Ethical and Safe Use of AI for Climate Action: While AI for climate action is designed to benefit humanity, competing corporate interests can sometimes overshadow these broader objectives.

Strong regulatory oversight is therefore essential to ensure that technology, data, and resources are used responsibly at every step. Equally important is transparent communication through regular public updates, which helps maintain trust and demonstrates that AI-driven climate initiatives are focused on the greater good.

3. Ethical and Bias Concerns: AI systems can inadvertently introduce or amplify biases, mainly when incomplete or skewed climate data.

The authority should maintain thorough documentation of data sources, model assumptions, and processes while conducting regular audits to identify and correct biases.

4. Talent Shortage and Skill Gaps: AI and climate science each demand specialized expertise, and the shortage of interdisciplinary experts can often delay critical projects, especially in developing countries.

One solution is to start training climate scientists to learn and use AI, and vice versa, or recruit experts from leading tech companies or abroad, thereby forming a competent interdisciplinary team of climate-focused AI professionals.

5. Energy-intensive and Carbon Footprint: Training and running AI models can be highly energy-intensive, potentially increasing the carbon emissions AI aims to reduce.

One solution is to invest in energy-efficient hardware and algorithms and consider renewable energy sources (e.g., solar, wind energy, or hydro) to power data centers.

However, these measures may raise the project cost significantly, requiring multiple funding streams or a foolproof, long-term plan to ensure financial sustainability.

Conclusion

Despite the numerous obstacles governments and environmental agencies encounter—from funding shortfalls to ethical concerns—the drive to integrate AI for climate action must persist.

By embracing strategic partnerships for funding, investing in skill development, and ensuring responsible data use, stakeholders can overcome these hurdles and harness AI’s transformative potential to fight climate change.

Contact Iowa 4 Tech, your tech partner, to learn how AI-driven solutions can revolutionize your next project and propel your business toward innovation.