Discover CleanTech, Issue 4, August 2022

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Discover CleanTech

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Special Feature

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The Climate PI

The Climate PI: the organisation battling the climate crisis with big data The Climate PI (Planetary Intelligence) uses state-of-the-art AI to recommend which already existing policies, technologies and social solutions could be scaled and adapted to solve the specific challenges of new locations. Discover CleanTech learns how the firm harnesses big data to address some of the biggest challenges facing our planet and people. BY SUNNIVA DAVIES-ROMMETVEIT, MADE IN PARTNERSHIP WITH THE CLIMATE PI

All of the solutions that we need to reduce emissions, rejuvenating nature whilst improving living standards, are already out there,” explains Jennie-Marie Larsen, chief executive of The Climate PI, an organisation that uses machine learning to recommend climate solutions. “The problem is that all of these innovative solutions are fragmented around the world – stuck in silos – meaning that progress isn’t shared and scaled to other similar places around the globe. Getting to net zero before 2050 requires high-impact solutions and unprecedented international and intercorporate cooperation. Yet, knowing which solutions to apply, where and in which combination requires an understanding of not just climate science – complex in and of itself – but of the economical, political, sociologi20 |

Issue 04 |

August 2022

cal and psychological, real-world changes that such green transitions could evoke. As an example, Larsen points to recent well-meaning but mismanaged attempts to ‘green’ cities and transition away from fossil fuels. London’s Liveable Neighbourhoods scheme, which provided funding to London boroughs to implement green solutions, was recently paused due to backlash from some Londoners. “Some solutions simply weren’t workable for communities,” Larsen explains. “Many smaller streets in London became pedestrianised, but that simply meant a lot more traffic and pollution on London’s busier roads.” A similar situation happened in France, Larsen adds, when French president Emmanuel Macron raised Diesel prices in an attempt to discourage driving: those most hit were the poorest in society who can’t afford the slightest increase in cost of

living, and who don’t have access to public transport because they live in rural areas, and this led to country-wide protests. The reason for these strategic failures is that the vast majority of decision makers are unaware of many of the solutions available to help drive down the sources of emissions and increase the capacity of natural carbon sinks. The Climate PI will provide access to hundreds of climate solutions and, most importantly, associated data on the projected impact of each solution. Larsen explains: “We want to use local IoT and macro-environmental data combined with machine learning to understand which solutions are working, in which combination and in which types of environments – so that we can recommend a suite of the best-fit solutions for similar parts of the planet.”


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