The environmental impact of the production and consumption of food is seldom depicted to consumers. The footprint of food products provides a means for consumers to compare environmental impacts across and within product groups. In this study we apply carbon, nitrogen, and water footprints in tandem and present food labels that could help inform consumers about the environmental impacts of individual food products. The footprint factors used in this study are specific to the United States, but the concept can be applied elsewhere. We propose three methods of footprint calculations: footprint weight, sustainability measures, and % daily value. We apply the three footprint calculation methods to four example labels (stars label, stoplight label, nutrition label add-on, and a detailed comparison label) that vary in design and the amount of detail provided. The stars label is simple and easily understood but provides minimal detail about the footprints. At the other end of the spectrum, the detailed comparison label gives context in relative terms (e.g., carbon emissions for equivalent distance driven) for the food product. Implementing environmental impact food labels requires additional understanding of how consumers use footprint labels, and label suitability may vary for government organizations, retail and local grocers, and farmers.

Mitigation solutions are often evaluated in terms of costs and greenhouse gas reduction potentials, missing out on the consideration of direct effects on human well-being. Here, we systematically assess the mitigation potential of demand-side options categorized into avoid, shift and improve, and their human well-being links. We show that these options, bridging socio-behavioural, infrastructural and technological domains, can reduce counterfactual sectoral emissions by 40–80% in end-use sectors. Based on expert judgement and an extensive literature database, we evaluate 306 combinations of well-being outcomes and demand-side options, finding largely beneficial effects in improvement in well-being (79% positive, 18% neutral and 3% negative), even though we find low confidence on the social dimensions of well-being. Implementing such nuanced solutions is based axiomatically on an understanding of malleable rather than fixed preferences, and procedurally on changing infrastructures and choice architectures. Results demonstrate the high mitigation potential of demand-side mitigation options that are synergistic with well-being.