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）中十大常见供应食材按影响类别与评估方法划分的影响排序。本表格以Excel文件形式提供。为构建本表格，研究团队首先筛选出该计划中十大最常供应的食材；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。方法与数据库组合的完整清单详见下文补充表7（SI Table 7）。随后在每一组方法/数据库组合下，将每种食材的影响得分按1至10进行排序。例如，本研究依托Simapro平台，采用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开展评估。在指定的方法/数据库组合下，为每种食品单独确定影响排序；以本示例为例，苹果的气候影响排序为2，牛肉的气候影响排序为10。最后通过计算每种食材在各影响类别下的排序标准差，对所有食材的排序结果开展对比分析。