How artificial intelligence can accelerate the reduction of CO2 emissions

2023-05-23 15:43:00

Globally, the construction industry accounts for 11% of CO2 emissions, a figure that rises to 39% if the operational energy consumption of buildings is included. To meet the target set by the Paris Climate Agreement, emissions from the construction industry must be halved by 2030, and zero by 2050… A greening that the sector will in any case have to borrow constrained and forced following the proliferation of regulations, as in France the Agec law 2020.

To do this, the options are fortunately numerous, from cement produced without limestone to the reuse of materials, through the use of green hydrogen to manufacture steel. However, these methods, as promising as they are, require a complete rethinking of the functioning of the industrial fabric, and therefore cannot be deployed massively in the very short term. However, the sector is racing once morest time. This is why a growing number of players are also betting on the recent and dazzling progress of artificial intelligence to optimize existing production processes.

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Reducing cement-related energy consumption with AI

Carbon Re, a British start-up, is using this technology to reduce emissions from cement production. The latter is indeed an extremely polluting product, of which 4.6 billion tonnes are consumed each year (the equivalent of Mount Everest) on a global scale. If the cement industry were a continent, it would be the third in the world in terms of CO2 emissions. Difficult, therefore, to green the construction industry without tackling this big piece.

To do this, Carbon Re relies on artificial intelligence to optimize energy consumption.

« Producing cement notably involves firing limestone at very high temperatures, and the energy used to reach this temperature is responsible for around 40% of emissions. says Sherif Elsayed-Ali, co-founder and CEO of the company.

« However, obtaining an optimal temperature is very complicated, you have to juggle with a large amount of data, such as the type of fuel used, the raw materials involved, the degree of humidity in the air… But artificial intelligence is very good at this type of optimization problem. By sifting plant data through our algorithms, we are therefore able to reduce the amount of energy needed “, he summarizes.

For the time being, the solution of the young shoot, which sells its software in the form of a subscription to cement manufacturers, makes it possible on average to reduce fuel consumption by 8%. Artificial intelligence algorithms are constantly learning and improving, and ultimately aims to reach 20%

From steel to the energy consumption of buildings

In addition to cement, steel is also one of the leading materials in the construction sector, and a major emitter of CO2. THE middle class German is a big consumer: not surprising, therefore, that a young shoot from across the Rhine is trying to decarbonize its production, also betting on artificial intelligence. Like those of Carbon Re, the algorithms of Smart Steel Technologies make it possible to optimize the temperature during the production process to limit the energy bill. But also to increase the quality of the steel produced and to limit the quantity of waste. It works in particular with ArcelorMittal and Marienhütte, an Austrian steel manufacturer.

Finally, the energy consumption of buildings alone accounts for 28% of global CO2 emissions. To improve this carbon footprint, it is not enough to rely on new, more energy-efficient buildings, insofar as 80% of the buildings that will be standing in 2050 have already been built. It is therefore also and above all necessary to improve the efficiency of existing buildings. Again, artificial intelligence can save money. This is the bet of Mortar IO, another young London shoot that relies on artificial intelligence to quickly perform an energy audit of a building stock and provide simple ways to optimize their efficiency.

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The Vinci group has also deployed pilot projects which have reduced the energy efficiency of buildings by up to 40%. Singapore, which is striving to rapidly reduce the energy footprint of its building stock to achieve net zero emissions by 2050, has started retrofitting buildings to optimize lighting and temperature through artificial intelligence to save energy, but also perform predictive maintenance to extend the life of buildings.