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）数据库是一套标准化整合的食品商品碳足迹（Carbon Footprint, CF）与水足迹（Water Footprint, WF）数值汇编库，其构建依托标准化方法流程：从同行评议论文与灰色文献（grey literature）中提取相关信息，并为各类食品分配最优的足迹数值与不确定性参数。本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。本数据库的核心基础与最细分的信息层级，源自对841篇文献（1998-2019年）中提取得到的3349组碳足迹数据，以及88篇文献（2005-2018年）中提取得到的937组水足迹数据进行的统一更新与整合汇编。研究团队采用严谨的统计学方法，构建了多组递进式的数据聚合层级：碳足迹数据共划分为85个大类、11个子类别，涵盖323个食品品类的相关数据；水足迹数据则划分为72个大类、9个子类别，涵盖320个食品品类的相关数据。此外，本数据库还搭建了一套创新的方法论框架，用于开展不确定性处理与数据质量管控，以确保为食品品类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学评估结果，均被整合为便于使用的数据集表格，可直接查询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及质量核查流程，本数据库易于部署与修改，可适配不同应用场景与专业水平需求，可为食品行业的从业者、管理者与科研人员提供一款灵活的科学化工具。