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Shared Digital Product Passport for holistic lifecycle assessment

CO2 Calculation with the Product AAS


Publikationsform: Fachartikel
Artikelnummer: 03654_2024_04_01
Zeitschrift: Shared Digital Product Passport for holistic lifecycle assessment
Erscheinungsdatum: 01.04.2024
Autor: Manuel Reif, Mohammad Hossein Rimaz, Christiane Plociennik, Martin Ruskowski, Alexander David,
Verlag: Vulkan-Verlag GmbH
Seiten: 9
Publikationsformat: PDF


As AI models become more and more common in process industry applications, it is important to understand their carbon footprint. Recent papers have shown that it can be quite big, i.e., the training of a single high-end model can result in emissions of more than 500t of CO2eq. In this paper we discuss the factors that influence the carbon footprint of AI models, explore what impact different decisions have, and show how the footprint can be reduced. We also evaluate different models to validate or challenge theoretical assumptions from the literature. Two experimental examples using process industry data show the impact on providers of industrial analytics in particular.

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