SU-EATABLE LIFE: a comprehensive database of carbon and water footprints of food commodities

The Su-EATABLE LIFE (SEL) database is a harmonised compilation of carbon (CF) and water (WF) footprint values of food commodities, based on a standardized methodology to extract information and assign optimal footprint values and uncertainties to food items, starting from peer-reviewed articles and grey literature. SEL database is organized in different levels of information suitable for different users and purposes. An updated and harmonized compilation of 3349 carbon footprint values extrapolated from 841 publications (1998-2019) and 937 water footprint values extrapolated from 88 publications (2005-2018) represents the solid basis of the database and the most disaggregated level of information. Using a rigorous statistical approach we have created additional levels of data information which represent increasing level of CF and WF data aggregation, summarized into 85 typologies, 11 sub-typologies, 323 items data of CF and 72 typologies, 9 sub-typologies, 320 items data of WF. Moreover we have implemented an innovative methodological framework for uncertainty treatment and data quality assurance to attribute robust and statistically significant footprint values to food commodities. The complex sets of statistical evaluations, done for each informative level, are summarized into an easy to use datasheet reporting values of CF and WF of food items. Thanks to its multilevel approach and to the transparent procedure for data analysis and quality check, the database can be easily implemented and modified, fits different purposes and levels of expertise and provides a flexible science based tool operators, managers and researcher in the food sector.

Su-EATABLE LIFE（SEL）数据库是食品商品碳足迹（Carbon Footprint, CF）与水足迹（Water Footprint, WF）数值的统一汇编数据集，其基于标准化方法学从同行评议文献与灰色文献中提取信息，并为各类食品分配最优足迹值与不确定性参数。该数据库按照多信息层级进行组织，以适配不同用户群体与应用场景。本次更新的统一汇编数据集包含3349条碳足迹数值（源自841篇1998-2019年的文献）与937条水足迹数值（源自88篇2005-2018年的文献），构成了数据库的核心基础，同时也是信息粒度最精细的层级。研究团队采用严谨的统计方法构建了多组拓展数据层级，对应碳足迹与水足迹数据的逐步聚合程度，最终归纳为85个大类、11个子类、323条碳足迹条目，以及72个大类、9个子类、320条水足迹条目。此外，本研究还创新性地提出了不确定性处理与数据质量保障的方法论框架，可为各类食品赋予稳健且具备统计学显著性的足迹数值。针对每个信息层级开展的复杂统计评估结果，均被整理为易于使用的数据表单，列明各类食品的碳足迹与水足迹数值。得益于其多层级架构与透明化的数据分析与质量核查流程，该数据库易于部署与修改，可适配不同应用场景与专业水平，为食品行业的从业者、管理者与研究者提供了一款灵活的、基于科学依据的工具。