The Power of AI in Reducing Energy Consumption
Imagine a future where the fight against climate change is fortified by artificial intelligence. Lei Xing, a lecturer in chemistry and chemical engineering at the University of Surrey, and his team, have developed a groundbreaking AI model system to enhance the efficiency of CO2 capture from power plants.
Applying Innovative “Enhanced Weathering”
Xing revealed that the traditional method of CO2 capture involves bubbling the flue gas through water containing limestone, which reacts with the CO2 to produce harmless bicarbonate in a process known as “enhanced weathering.” However, the energy requirements were inefficient, especially in calm weather.
The Role of AI in Predictive Efficiency
With the integration of AI technology, the researchers were able to teach the model system to predict CO2 levels and renewable energy availability. This allowed for optimization in water pumping, reducing the need for energy from the grid during periods of low CO2 capture or renewable energy availability.
Broader Applications and Environmental Impact
The potential impact of this AI technology extends far beyond enhanced weathering. Xing emphasized that their findings could revolutionize CO2 capture across industries, easing the burden on energy consumption and positively contributing to UN Sustainability Goals.
Making Strides Towards a Sustainable Future
Xing expressed optimism about the broader implications, stating, “Our model could help anybody trying to capture and store more CO2 with less energy – whatever the process they’re using.” Their work provides a glimpse into an era where AI is a key ally in the global effort to combat climate change.
