Life cycle inventory and life cycle impact assessment datasets of an industrial-scale milk fractionation process generating 5 co-products: Cream, casein, lactose and two whey-protein ingredients enriched in α-lactalbumin or ß-lactoglobulin.

Food plays a significant role in the environmental impacts of human activities. However, many agro-industrial processes are multi-product systems and their impacts need to be distributed between the different co-products in order to properly address two major issues: (1) prevention of food spoilage and food losses and (2) the eco-design of food systems, from processing up to recommendations for changes in Western diets. As a culturally and nutritionally central component of most human diets, milk is critical because processing is a preservation issue and most dairy products follow from separations, thereby generating co-products. Life Cycle Assessment (LCA) is a reference and standard method that allows quantification of the potential environmental impacts of a manufactured product throughout its life cycle. Application of the method requires foreground information on the system considered, as well as input and output flows that feed and exit the system. This data paper provides data related to the fractionation of milk into cream, casein, lactose and two whey protein ingredients at industrial scale, using up-to-date technologies used in French dairy factories in years 2000-2010s. Cleaning is included. Transcription of these input and output flows into a selection of processes in the Agribalyse 3.0.1 and Ecoinvent 3.8 databases is also provided. Application of the LCA method in its attributional approach leaves methodological choices up to the practitioner, such as subdivision of the system, allocation of the environmental burden where subdivision is not applied or not possible, and aggregation of the impacts. Therefore, this data paper also provides the allocation factors that are necessary to apply mass, dry matter, protein or economic allocation at every separation operation throughout the processing itinerary. Using the characterization method EF 3.0, this data paper provides the potential environmental impacts of the 5 co-products obtained with an initial input of 600 tons of raw milk, i.e., 63 tons of cream, 183 tons of wet casein, 90 tons of lactose, 1.7 ton of dried ß-lactoglobulin and 0.3 ton of dried α-lactalbumin. The respective shares of the 5 co-products are calculated for each allocation rule. Finally, this data paper provides the potential environmental impacts for the manufacture of 1 kg of α-lactalbumin enriched ingredient, as the co-product with the longest process itinerary, with details of all intermediate input contributions as well as two possible aggregation rules: by step or by input type. The dataset participates in providing often confidential industrial-scale LCI data to the public. It will be helpful for the eco-design of future itineraries. In particular, it contributes to taking the fate of the co-products into account when using LCA for such eco-design.

Datasets for the environmental assessment of an apple value chain including fresh fruits, juice and applesauce from an organic low-input production farm.

Due to societal concerns, assess the environmental impacts, address the issues and provide labelling to the consumer are growing issues for the agri-food sector. In this context, provide datasets specific to alternative systems is crucial to be able to take into account the variability between systems then address their issues and label them appropriately. This data paper compiles all the data used to produce the life cycle assessment (LCA) environmental of an organic low-input apple value chain including the cultivation of apples at farm, the transformation of a part into juice and applesauce, the retail and the consumption stages. The raw data have mostly been obtained through interviews of the farmer and complemented by literature. They have been used to build a life cycle inventory (LCI), using Agribalyse 3.0 and Ecoinvent 3.8 as background databases. The dataset also compiles the life cycle impact assessment (LCIA) using the characterization method EF3.0. As discussed in an associated scientific paper, this dataset participates in filling two gaps: integrate the variability between systems in the discussion and link upstream (at farm) and downstream (transformation, retail, consuming) impacts. This is done by (1) covering the entire value chain from cradle to grave when most papers found in literature focusses on one stage (e.g. the cultivation of apples) and (2) applying LCA to a system that present specificities not well covered by LCA literature (e.g. low-input cultivation with no fertilization up to now).

Datasets on the nutritional and environmental (including biodiversity) characteristics of food products consumed in France.

Analysing the nutritional and environmental impacts of our current diets and promoting sustainable dietary shifts require quantified data on the characteristics of foods. We have jointly studied environmental and nutritional performances of more than 200 generic foods consumed in France, by combining and completing different databases. Several environmental issues calculated by Life Cycle Assessment (LCA) were selected, including impacts on biodiversity. This required to (1) model diets for given subpopulations; (2) adapt the LCA database of food products, Agribalyse 3.0, to link selected food and environmental inventories (3) compile characterization factors to assess impacts on biodiversity. Additionally, modifying Agribalyse 3.0 required to also modify the characterization method on Land Competition. This data paper compiles all the data used to obtain the results presented in the companion article entitled: Environmental trade-offs of fulfilling nutritionally adequacy with reduced animal protein share for French adult populations[1]; i.e. (i) the characterization methods used, (ii) the modifications made to Agribalyse 3.0 and (iii) the nutrient content and quantities consumed of generic foods (iv) the optimized quantities of simulated diets reaching nutrient recommendations with low share of animal-based proteins. It also comprises (iv) Life Cycle Impact Assessment for all Agribalyse 3.0 processes of food having a CIQUAL code (2,497 processes).

Life cycle inventory and life cycle impact assessment datasets of PDO Feta production in Stymfalia region, Greece.

Considering and reducing the environmental impacts has become one of the main concerns of agri-food systems. More specifically, the agri-food sector is increasingly confronted to the necessity of quantifying environmental impacts, e.g., to eco-design their products or to inform the consumers. Literature shows a high variability in environmental impacts between existing systems, as for example between cheeses and the necessity of more case studies to validate statements. In this context, this data paper provides some data related to Feta production in Greece, based on 8 farms of a cooperative (7 sheep livestock and one goat livestock). Feta cheese is PDO (Protected Designation of Origin), composed solely of goat's milk and sheep's milk under specific percentages (at least 70% sheep). More specifically, the data paper displays all the data used to obtain environmental impacts (calculated by using life cycle assessment (LCA)) of the production of Feta, from cradle to consumer. It includes the - sheep and goat - milk productions, the transformation into cheese, the packaging and the transport to wholesalers, then stores and then consumers. The raw data have mostly been obtained through interviews and surveys with the cheese and milk producers and complemented by literature. Data were used to build a life cycle inventory (LCI). For the milk production, the LCI was modeled using MEANS InOut software. For the whole LCI, Agribalyse 3.0 and Ecoinvent 3.8 were used as background databases, with modifications to reflect Greek context. The dataset also compiles the life cycle impact assessment (LCIA). The characterization method used is method EF3.0. This dataset participates in filling two gaps: (1) providing data to represent the variability between Feta cheese production systems and (2) providing data linking impacts of farm, transformation, retail and transport in a value chain perspective. This is done by (1) enlarging the perimeter when most studies found in literature focus on one stage (e.g. the production of milk) and (2) applying LCA to data specific to a regional production (Stymfalia in Greece).

Allocation factors for meat coproducts: Dataset to perform life cycle assessment at slaughterhouse.

The sharing of total environmental impacts between the different products of a multi-output system is crucial in Life Cycle Assessment. ISO standards recommend subdivision then substitution methods when possible. Sometimes, allocations rules are necessary. They consist of allocating the total impact to the different products in proportion to a value that characterize the products. They can be based on physical parameters (such as mass, protein, dry matter, etc.) or the economic value of coproducts can be used as a proxy. As they are based on various type of parameters, allocation rules can lead to significantly different environmental impact results. Then a consensus is difficult to reach between stakeholders as for example in meat sector. To make the debate going further, Chen et al. (2017) proposed a new allocation method based on biophysical parameters (Chen et al., 2017). Adapted from previous methods, they propose to allocate impacts in proportion to the energy needed for the growth, the maintenance and the activity of each tissue. The method has been judged as scientifically viable but also particularly difficult to apply due to the amount of necessary data and to the complexity of the calculation model. In a recent project, we developed a freeware to easily calculate biophysical allocation factors as well as mass and economic factors to allow a fair comparison: MeatPartTool. We also collected data to create a dataset of mass, economic and biophysical allocation factors for a large range of beef (132 individuals), calf (54 individuals) and lamb (14 individuals) at the slaughterhouse stage. This data paper provides both primary data and calculated allocation factors.