Tackling the climate crisis requires a combined effort across science, business and governments of the likes that has never been seen before. However, while there are still many unknowns concerning AI, scientists and AI specialists around the world are actively working to maximize its usefulness, particularly when it comes to reducing greenhouse gas emissions. With increased funding from governments and the private sector, we can expect to see AI-driven climate solutions become more common place. It is without doubt that now is the time to act, and in this article we will demontrated just some of the ways AI is accelerating climate solutions in the race to avert the impending climate crisis.
With more and more new innovations in renewable energy sources coming onto the market every day, there is hope yet for a sustainable future. There are many ways that AI can be applied to climate solutions from measuirng emissions at the macro and micro levels, to reducing the effects of emissions and even removing emissions from the atmosphere.
For example, CO2 AI is an AI-powered solution to help companies accurately measure, simulate, measure, track and reduce their environmental impact at scale across their supply chain. Meanwhile, Permutable’s own AI has been trained to help improve our understanding of our carbon emissions trajectory by enabling more accurate predictions filling in the vast swathes of data reporting gaps.
Another important areas of application involves improving renewable energy efficiency – for example, AI systems can use forecasts for wind speed and irradiance to make predictions for short-term renewable power output in minutes rather than days ensuring grid stability and enabling the optimization of plant availability.
Modelling energy use
As of 2013, buildings were responsible for over 70% of global energy use and nearly 40% of its carbon emissions. So how can we reduce these numbers? One way is through artificial intelligence which has the potential to revolutionize the way buildings are designed, built, and operated.
Using AI, building systems can be modeled before construction begins in order to identify inefficiencies and operational vulnerabilities before it’s too late. This not only cuts down on waste but also saves money on energy bills by using less energy than a traditionally designed building would use.
For example, Brainbox AI uses self-adapting artificial intelligence technology to proactivey optimise the energy consumption of buildings, empowering building owners around the world to drastically reduce carbon emissions while generating significant savings.
The process of predictive analytics is to use past data and information in order to predict future events. In the case of advancing climate solutions, known climate change data it taken and used to predict the changes that will happen in the future. This helps plan ahead so government, countries and their inhabitants can prepare for what’s coming. For example, many countries are using this technique to help their farmers pick which crops they should grow and when they should plant them to adapt to a changing climate.
AI has helped researchers gain 89% to 99% percent accuracy in identifying tropical cyclones, weather fronts and atmospheric rivers, the latter of which can cause heavy precipitation and are often hard for humans to identify on their own (Columbia University Climate Institute). Meanwhile, Google has been using machine learning to “Nowcast” precipitation in high resolution, which enables almost instant prediction of weather patterns. This is particularly important with the advent of increasingly unpredictable weather patterns where being able to make predictions in a short period of time enables crisis management and avert all out catastrophe.
The climate crisis threatens all living beings on earth. Scientists predict that, by 2100, global warming will have increased earth’s temperatures by 3-5 degrees. The consequences of such a drastic increase in temperature will be devastating: rising sea levels and extreme weather patterns leading to higher rates of natural disasters, food shortages and massive population displacement.
Despite these terrifying predictions, there is still hope for us to create a sustainable future with less pollution and more renewable energy sources. Artificial intelligence can help us along the way by helping us to create climate solutions to address some of the biggest challenges we face today. In just three years, AI has already contributed to green innovations including safer nuclear power plants, better solar panel installation techniques and ways to reduce greenhouse gas emissions from refineries. With still more to come.
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