If we really want to help mitigate environmental damage, we need to explore and invest in technology rapidly – especially since there is still no cohesive, holistic solution – even if this means artificial intelligence (AI) consumes vast amounts of energy.
This is simply because AI and supercomputers may be the only way we get to a solution quickly.
Sure, there’s new technology such as carbon capture, utilisation and storage (CCUS), which gathers CO2, usually from large point sources like power generation or industrial facilities using fossil fuels or biomass and then uses it elsewhere.
According to the International Energy Agency, emissions, if not used on-site, are compressed and moved by pipeline, ship, rail, or truck, and deployed in othret56er areas, such as grid flexibility for power suppliers (now wouldn’t some extra grid capacity be nice here?) or injected into deep geological formations like depleted oil and gas reservoirs or saline aquifers.
ICT plays an important role here, enabling advanced monitoring, process optimisation and data analysis across capture, transportation and storage stages through sensors, AI and modelling programmes. While CCUS is growing as a greenhouse gas solution, the agency says deploying it alone won’t be enough to reach the Net Zero target by 2050.
All potential solutions are still at the ‘present a great opportunity’ stage for mitigating – if not eliminating – pollution.
While CCUS has potential, it cannot carry the full burden. That is why researchers are also turning to other solutions. There’s green hydrogen, which essentially turns fossil fuel into water using technology such as AI, machine learning and digital twin modelling. However, revolutionising global energy systems – as engineering firm EPCM Holdings notes – would require global hydrogen consumption to increase 15-fold by 2050 compared with 2020.
How about batteries? Progress is being made worldwide. This is crucial because we need to store energy generated from wind and solar sources so it can be used when the sun isn’t shining, and the wind isn’t blowing – especially here where we need the extra power.
A May 2024 paper in the Journal of Renewable Energy notes that chemical, mechanical, thermal, or magnetic energy storage techniques are viable. Much of this technology, however, is still in the lab phase, with researchers drawing equations on smart boards and using supercomputers to model scenarios. Examples such as solid-state and flow batteries are showing early promise, and AI-driven optimisation is already helping researchers simulate efficiency gains.
What else is there out there? When it comes to microplastics, research is exploring microbial enzymes as a solution. These proteins, which speed up biochemical reactions in cells, are a potential answer, according to a paper on the National Library of Medicine website. By 2023, researchers had demonstrated they could be used to tackle plastic pollution.
There is significant research in this area, mostly focused on recent trends. It’s not mainstream yet, but the early signs are promising. Before widespread use, enzymes need to be engineered for industrial applications – further supercomputer modelling will be required.
All potential solutions are still at the ‘present a great opportunity’ stage for mitigating – if not eliminating – pollution. A February 2024 paper in Environmental Technology & Innovation confirms this.
There is no single silver bullet. And maybe we shouldn’t be looking for one.
Rather, those of us in the technology field shouldn’t be sitting around as armchair coaches – to use a tired cliché – shouting at researchers for not doing enough. Given how critical technologies such as machine learning and supercomputing are to the fight against pollution, we should focus on improving calculation speeds and algorithms.
There are concerns that AI itself contributes to greenhouse gas emissions. I wrote about that here. And I’ve also written about what these companies are doing to limit how much they adversely affect the environment by using nuclear power.
While not minimising the need to do something about AI’s adverse influence on our planet, there is an argument to be made that AI can solve not only the problems it creates in terms of emissions but also help the globe reduce greenhouse gasses too.
And that’s not even considering the positive influence technology can have in other areas where pollution is a serious problem, such as microplastics.
We cannot sit around. We need to act, and we need to use the technology at our disposal to help move the globe to a space in which Net Zero is transformed from an aspiration into an achievable reality.
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