Environmental Impacts of Mixed Dishes: A Case Study on Pizza

Modern diets are largely comprised of mixed dishes, a mixture of different ingredients with varying proportions. Environmental impacts of mixed dishes are not well studied since most research focuses on impacts associated with single-component food items (e.g. beef, milk etc.). We explore methods to deconstruct mixed dishes into “basic components” in order to estimate their environmental footprints by using a case study investigating the carbon footprint of pizza in the US diet, aiming to identify the strengths and limitations of each approach. We determined pizza consumption in the US diet using the What We Eat in America 2009–2012 dataset. We deconstructed pizza consumption into its “basic components” via three methods: food pattern categories (FP, 37 components), food commodities (FC, 300 components), and food ingredients (FI, 3,200 components). Using life cycle inventory (LCI) databases from Ecoinvent v3.2 and World Food LCA Database v3.1, we associated components to resource extraction and environmental releases. FCs and FIs are directly linked to LCI databases when possible while for FPs we averaged estimates from related LCI databases (Spatial preference: US>Canada>Global). We used the IPCC 2007 method to perform a climate change impact assessment. On average, the US consumer eats 31.4 gpizza/person-day containing 77 different food items and representing 4% of the total energy intake. The FP approach deconstructed pizza into 18 components, mainly grains (37%), cheese (27%), and vegetables (19%, Figure 1). This overestimated intake and individual food group (e.g. solid fats, dairy and grains) consumption by 5% and up to a factor of four, respectively, possibly due to converting FP serving equivalents to masses. The corresponding carbon footprint was 3.5 kg CO2 eq/kgpizza, largely due to cheese (43%), meat (21%), and solid fats (21%, Figure 2). The FP method could allow for a nutritional assessment of mixed dishes using the global burden of disease. The FC method identified 69 pizza components (95% intake coverage) through mainly vegetables (32%) and grains (32%). This resulted in 2.5 kg CO2 eq/kgpizza, mainly due to cheese (39%) and meat (36%). Dairy mixed dishes could be hard to study with this approach due to difficulties linking dairy FCs to LCI databases. However, the approach could be used for considering environmental impacts due to cooking and preparations of mixed dishes. The FI approach identified 64 pizza components (98% intake coverage), primarily vegetables (27%), grains (25%), and cheese (18%). This corresponded to a carbon footprint of 2.8 kg CO2 eq/kgpizza, largely due to meat (48%) and cheese (25%). The FI method introduces complexity to the analysis since “basic components” of the approach could be multi-ingredient that need further decomposition. Our analysis did not consider impacts due to losses, transportation, storage or cooking. We demonstrate three possible deconstruction methods to assess environmental impacts of mixed dishes by investigating the carbon footprint of pizza in the US diet. This case study suggests that deconstruction and component contribution to environmental impacts differs between methods. A comprehensive evaluation of the environmental impacts from mixed dishes could be achieved by combining the respective strengths of the different decomposition methods. In the future, we will test an alternative deconstruction method with a USDA retail commodities database and consider more environmental impact categories. Support or Funding Information Funding by an unrestricted grant of the Dairy Research Institute (DRI), part of Dairy Management Inc. (DMI) and the Dow Sustainability Fellows Program. Daily pizza consumption by deconstruction methods. Carbon footprint due to individual daily pizza consumption.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.