Sustainability-aware food recommender systems require environmental impact signals at the ingredient and recipe level to reason about the consequences of personalized meal suggestions. Yet large-scale food recommendation corpora rarely provide carbon and water footprint estimates that can be robustly aligned with recipe ingredients, limiting comparability and reproducibility. GreenFoodLens is a dataset resource that enriches the …