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Carbon Mark

Do you know the accurate CO2 footprint of a single thing around you? The table and chairs in front of you, the computer you sit at, your shoes perhaps?

The answer is almost certainly ‘no’, as currently there is no adequate way for anyone whose goal is sustainable purchasing – consumers, procurement professionals or manufacturers – to instantly assess and rank the CO2 emissions of the goods they buy and sell. Nor is there a mechanism that companies can utilise to benchmark against one another in a way that is immediately visible to consumers, and which enables companies to gain a significant marketplace advantage when they improve the sustainability of their products and the way they transact business.

We cannot expect consumers and industry to move towards a less carbon-intensive economy if they cannot judge the impact of their purchasing decisions. To address this, Imperial College London has devised a ground-breaking method – using Big Data and Machine Learning – to calculate the carbon emission of all consumer goods, incorporating their full-life cycle and enabling ranking comparable goods accordingly. Product life-cycle assessment is one of the keys to curbing global carbon emissions, as both the consumer products and services sectors account for 60% of all CO2 emission globally. The project, named Carbon Mark, is primed to create the capability to instantly calculate the carbon footprints of all consumer products worldwide.

Led by Professor Nilay Shah, with Professor Martin Siegert, Dr Eva Sevigne Itoiz and Dr Antonio Del Rio Chanona.


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