Supplementary Data 2. Ranking of impacts by impact category and methods in the ten most commonly served commodities in NSLP.

Supplementary Data 2. Ranking of impacts by impact category and methods in the ten most commonly served commodities in NSLP. This table is provided as an excel file. To construct this table, we first identified the ten most commonly served commodities in the NSLP. We then assessed the environmental impacts of these commodities using various combinations of impact assessment methods and databases. A list of the methods and database combinations is available below as SI Table 7. We then ranked the impacts of each commodity from 1 to 10 within each of the methods/database combinations. For example, using the World Food LCA Database version 3.5 and Product Environmental Footprint (PEF) impact assessment methods in Simapro, we assessed the climate impacts of producing 1 kg of apples and 1 kg of beef. Rankings were determined for each food within a given method/database combination. For this example, the rank of apple for climate impact was 2 and the rank of beef was 10. Rankings were compared using the standard deviation of rankings for each commodity and across impact categories.

补充数据2：美国国家学校午餐计划（National School Lunch Program, NSLP）中十大最常供应食材基于影响类别与评估方法的影响排序。本表格以Excel文件形式提供。
本数据集的构建流程为：首先确定NSLP中十大最常供应的食材原料；随后采用多种影响评估方法与数据库的组合方案，对这些食材的环境影响开展评估。各类方法与数据库组合的详情可参见下文的补充表SI Table 7。
随后在每一组方法/数据库组合下，将每种食材的影响程度按1至10进行排序。举例而言，本研究借助Simapro平台中的世界食品生命周期评估数据库（World Food LCA Database）3.5版与产品环境足迹（Product Environmental Footprint, PEF）影响评估方法，对1千克苹果与1千克牛肉的生产气候影响进行了评估。在特定的方法/数据库组合下，为每种食材确定对应影响的排序结果；以本案例为例，苹果的气候影响排序为2，牛肉的气候影响排序为10。
研究通过计算每种食材在各影响类别下的排序标准差，对不同食材的排序结果进行对比分析。