An electronic product carbon footprint dataset for question answering

The embodied carbon of computing systems constitutes a significant portion of their overall greenhouse gas (GHG) emissions. To support environmental initiatives and meet evolving standards, many companies now disclose product carbon footprints in sustainability reports, often with detailed breakdowns. Yet these reports appear in diverse and unstructured formats—text, tables, and graphs embedded in PDFs—creating major challenges for extracting and analyzing component-specific emissions data. This lack of standardization limits comparative assessments and opportunities for targeted reductions. To address this, we introduce a carbon question-answering (QA) dataset designed to enable the extraction and analysis of data from real-world carbon reports of computing products. The dataset features annotated metadata, numerical reasoning tasks, and structured derivations to ensure accurate processing of fragmented information. This work establishes a foundation for training advanced language models to automate aggregation and standardization of emissions data, enabling deeper analysis and integration into downstream applications, such as carbon analysis tools, to evaluate and optimize the footprint of Information and Communication Technology (ICT) systems.