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The role of mixing between layers of different densities is key to how the ocean works and interacts with other components of the Earth's system. Correctly accounting for its effect in numerical simulations is therefore of utmost importance. However, numerical models are still plagued with spurious sources of mixing, originating mostly from the vertical advection schemes in the case of fixed-coordinate models. As the number of phenomena explicitly resolved by models increases, so does the amplitude of resolved vertical motions and the amount of spurious numerical mixing, and regional models are no exception to this. This paper provides a clear illustration of this phenomenon in the context of simulating the south-east Asian (SEA) seas along with a simple way to reduce its impact. This region is known for its particularly strong internal tides and the fundamental role they play in the dynamic of the region. Using the Symphonie ocean model, simulations including and excluding tides and using a pseudo-third-order upwind advection scheme on the vertical are compared to several reference datasets, and the impact on water masses is assessed. The high diffusivity of this advection scheme is demonstrated along with the importance of accounting for tidal mixing for a correct representation of water masses. Simultaneously, we present an improvement in this advection scheme to make it more suitable for use in the vertical. Simulations with the new formulation are added for comparison. We conclude that the use of a higher-order numerical diffusion operator greatly improves the overall performance of the model.

Abstract Graphene in water is electrically charged in most conditions. The level of charge can be large enough to stabilize single (or few) layer graphene colloidal dispersions in water, without the need of using any other additive. In this work, potentiometric titration, isothermal titration calorimetry, electrokinetic measurements, Density Functional Theory calculations, Raman Spectroscopy, and direct force measurements using Atomic Force Microscopy to investigate this charge and explore its origin are combined. The body of data collected suggests that this charge is a consequence of the interaction between water ions (hydroxide and hydronium) and graphene, and can be conveniently tuned (in magnitude and sign) by changing the pH of water.

Reusable glass bottles are experiencing a resurgence, driven notably by societal concerns and regulations. While single-use glass bottles generally have higher environmental footprint compared to plastic bottles, reusable systems could reduce both impacts related to single-use (e.g., climate change, energy consumption) and plastics (e.g., microplastic pollution). The environmental benefits of reusable bottles can vary across systems and this can be overlooked by stakeholders who rely on generic results for communication and a limited number of parameters to design their systems. This study addresses this gap by developing a systematic analysis of the variability of life cycle assessment results, within the specific case study of a new beverage. As a result, a list of key parameters to consider for the specific case study is set, enabling to propose targeted mitigation strategies. The commonly used generic key parameters are complemented with context-specific key parameters, empowering stakeholders to develop efficient systems and communicate their environmental performance accurately. Different configurations are likely to be influenced by other key parameters, and require specific mitigation strategies. In this perspective, stakeholders need assistance in: (1) designing context-specific strategies, and (2) translating – complex and plural – life cycle assessment results into actionable decisions.

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 β-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.

Abstract We are witnessing an acceleration of the global drive to converge consumption and production patterns towards a more circular and sustainable approach to the food system. To address the challenge of reconnecting agriculture, environment, food and health, collections of large datasets must be exploited. However, building high-capacity data-sharing networks means unlocking the information silos that are caused by a multiplicity of local data dictionaries. To solve the data harmonization problem, we proposed an ontology on food, feed, bioproducts, and biowastes engineering for data integration in a circular bioeconomy and nexus-oriented approach. This ontology is based on a core model representing a generic process, the Process and Observation Ontology (PO2), which has been specialized to provide the vocabulary necessary to describe any biomass transformation process and to characterize the food, bioproducts, and wastes derived from these processes. Much of this vocabulary comes from transforming authoritative references such as the European food classification system (FoodEx2), the European Waste Catalogue, and other international nomenclatures into a semantic, world wide web consortium (W3C) format that provides system interoperability and software-driven intelligence. We showed the relevance of this new domain ontology PO2/TransformON through several concrete use cases in the fields of process engineering, bio-based composite making, food ecodesign, and relations with consumer’s perception and preferences. Further works will aim to align with other ontologies to create an ontology network for bridging the gap between upstream and downstream processes in the food system.

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).

Consumers are increasingly interested in knowing the environmental impacts of foods. In addition, producers are interested in receiving recommendations to reduce their impacts. This faces two major challenges: (1) certain systems are not widely studied and (2) not all production stages are included in system boundaries (e.g. only the agricultural stage or the supply chain). Life Cycle Assessment was applied to a specific small-scale and low-input organic apple value chain. The system boundaries included the cultivation, processing and distribution. All transport and waste management were considered. The main contributors to environmental impacts are: cultivation, juice and applesauce production, retail and consumption. Compared to literature, cultivation is efficient. Processing and retail are respectively influenced by the use of glass packaging, the cold storage of fresh apples and the transport to stores. Consumption was influenced by the management of apple waste and the consumer trip. Literature survey and results confirm that the system was not represented in the literature and provides new insights into the entire value chain, as well as new proxy LCIs. Similar specific studies should be repeated in the future to cover the variability. It is an essential step towards applying the environmental footprint fairly to alternative systems.

In recent years, the food industry has expended considerable effort to design novel products that replace animal proteins with legumes; however, the actual environmental benefits of such products are often not quantified. Here, we performed Life Cycle Assessments (LCA) to evaluate the environmental performance of four new fermented food products based on different mixtures of animal (cow milk) and plant (pea) protein sources (100% Pea, 75% Pea-25% Milk, 50% Pea-50% Milk, 25% Pea-75% Milk). The system perimeter encompassed all stages from agricultural production of the ingredients to the creation of the final ready-to-eat products. Impacts were calculated for all environmental indicators included in the EF 3.0 Method in SimaPro software based on a functional unit of 1 kg of ready-to-eat product. Life cycle inventories included all of the flows analyzed by the LCA (raw materials, energy, water, cleaning products, packaging, transport, waste). Foreground data were acquired directly on the manufacturing site; background data were taken from the Ecoinvent 3.6 database. The dataset contains details on the products, processes, equipment, and infrastructure considered; mass and energy flows; Life Cycle Inventories (LCI); and Life Cycle Impact Assessment (LCIA). These data improve our understanding of the environmental impact of plant-based alternatives to dairy products, which is currently poorly documented.

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).

Human food consumption is responsible for significant environmental impacts, which in recent years have been the focus of an increasing amount of research. One of the major results of these efforts has been an appreciation for the ways in which impacts can differ among products. To date, though, relatively little is known about possible differences in the environmental performance of a single food product that is made or produced in different contexts. Furthermore, the influence of consumer practices, such as cooking time or cleaning method, has not yet been investigated. The goals of the study were therefore (i) to compare the environmental impacts of a single food product—in this case, pizza—that is produced in different contexts (industrial, homemade, and assembled at home) and (ii) to investigate the influence of real-world consumer practices on these impacts. Two study models were used: a ham-and-cheese pizza and a mixed-cheese pizza. The functional units (FU) examined were one pizza and 1 kg of ready-to-eat pizza. The system boundaries extended from the agricultural production of ingredients to the consumption of the pizza at home. All inventory data related to the steps occurring before purchase (including storage at the supermarket) came from databases or the literature, while inventory data related to the steps occurring after the sale were obtained from questionnaires answered by 69 consumers who prepared and consumed the six pizza preparation pathways (two recipes multiply three methods of preparation) at home. Background data were selected in the AGRIBALYSE 3.0 and Ecoinvent 3.6 databases. The environmental impacts of the six pizza preparation pathways were calculated by Life Cycle Assessment (LCA) using the characterization method ''EF 3.0 Method (adapted) V1.00 / EF 3.0 normalization and weighting set” in SimaPro software. To compare the environmental impacts of the six pizza preparation pathways, 69 LCAs were performed for each; to compensate for missing data from incomplete questionnaires, we performed random draws from the available data to generate the life cycle inventory for each assessment. The data obtained in this study can be used to make recommendations to consumers regarding more environmentally friendly food choices and practices.

In the food industry, there is currently a great deal of interest in the development of plant-based alternatives to dairy products. However, little is known about the ways in which differences in formulation and/or processing affect the potential environmental benefits of such products. In this study, we investigated the environmental performance of four new fermented products created using different mixtures of plant- (pea) and animal- (cow milk) derived protein sources and prepared using a cheese-technology process (Camembert production). Life cycle assessments (LCAs) were performed that included all steps from the agricultural production of ingredients to the generation of the final ready-to-eat product. The goals were to identify the hotspots of this production system and to compare the different products to each other as well as to other common fermented or legume-based products (Camembert, tofu, hummus). The LCA results revealed that the two main hotspots for the mixed products were milk production (when used) and the ripening stage. All four products were similar with respect to the environmental impacts related to processing. Instead, with regard to the impacts of agricultural production, the products made with a higher proportion of pea protein were superior, providing clear evidence of the potential environmental benefit of pea-milk fermented foods. Overall, though, the mixed products did not present any environmental benefit compared to Camembert, hummus, and tofu due to the complex and energy-intensive nature of the manufacturing process. It is therefore critical that these processing steps be simplified and optimized in order to realize the environmental potential of such pea-based products.

Graphene in water is electrically charged in most conditions. The level of charge can be large enough to stabilize single (or few) layer graphene colloidal dispersions in water, without the need of using any other additive. In this work, potentiometric titration, isothermal titration calorimetry, electrokinetic measurements, Density Functional Theory calculations, Raman Spectroscopy, and direct force measurements using Atomic Force Microscopy to investigate this charge and explore its origin are combined. The body of data collected suggests that this charge is a consequence of the interaction between water ions (hydroxide and hydronium) and graphene, and can be conveniently tuned (in magnitude and sign) by changing the pH of water. [ABSTRACT FROM AUTHOR]

The role of mixing between layers of different densities is key to how the ocean works and interacts with other components of the Earth's system. Correctly accounting for its effect in numerical simulations is therefore of utmost importance. However, numerical models are still plagued with spurious sources of mixing, originating mostly from the vertical advection schemes in the case of fixed-coordinate models. As the number of phenomena explicitly resolved by models increases, so does the amplitude of resolved vertical motions and the amount of spurious numerical mixing, and regional models are no exception to this. This paper provides a clear illustration of this phenomenon in the context of simulating the south-east Asian (SEA) seas along with a simple way to reduce its impact. This region is known for its particularly strong internal tides and the fundamental role they play in the dynamic of the region. Using the Symphonie ocean model, simulations including and excluding tides and using a pseudo-third-order upwind advection scheme on the vertical are compared to several reference datasets, and the impact on water masses is assessed. The high diffusivity of this advection scheme is demonstrated along with the importance of accounting for tidal mixing for a correct representation of water masses. Simultaneously, we present an improvement in this advection scheme to make it more suitable for use in the vertical. Simulations with the new formulation are added for comparison. We conclude that the use of a higher-order numerical diffusion operator greatly improves the overall performance of the model. [ABSTRACT FROM AUTHOR]

Abstract Tissue repair after injury in adult mammals, usually results in scarring and loss of function in contrast to lower vertebrates such as the newt and zebrafish that regenerate. Understanding the regulatory processes that guide the outcome of tissue repair is therefore a concerning challenge for regenerative medicine. In multiple regenerative animal species, the nerve dependence of regeneration is well established, but the nature of the innervation required for tissue regeneration remains largely undefined. Using our model of induced adipose tissue regeneration in adult mice, we demonstrate here that nociceptive nerves promote regeneration and their removal impairs tissue regeneration. We also show that blocking the receptor for the nociceptive neuropeptide calcitonin gene-related peptide (CGRP) inhibits regeneration, whereas CGRP administration induces regeneration. These findings reveal that peptidergic nociceptive neurons are required for adult mice tissue regeneration.

Abstract Tissue repair after lesion usually leads to scar healing and thus loss of function in adult mammals. In contrast, other adult vertebrates such as amphibians have the ability to regenerate and restore tissue homeostasis after lesion. Understanding the control of the repair outcome is thus a concerning challenge for regenerative medicine. We recently developed a model of induced tissue regeneration in adult mice allowing the comparison of the early steps of regenerative and scar healing processes. By using studies of gain and loss of function, specific cell depletion approaches, and hematopoietic chimeras we demonstrate here that tissue regeneration in adult mammals depends on an early and transient peak of granulocyte producing reactive oxygen species and an efficient efferocytosis specifically by tissue-resident macrophages. These findings highlight key and early cellular pathways able to drive tissue repair towards regeneration in adult mammals.

The prebiotics like FOS and GOS are receiving special attention in the food industry due to their potential health benefits. They can be produced by enzymatic synthesis by using disaccharides or other substrates as raw materials or by extraction and hydrolysis from different natural sources (roots, legumes). However the environmental footprints of these different production schemes are lacking. This dataset presents Life Cycle Assessment (LCA) of the production of FOS and GOS by enzymatic synthesis from glucose (to get FOS) or lactose (to get GOS) and hydrolytic production from extraction of yacon potato (to get FOS) or chickpea (to get GOS). A cradle-to-gate approach was considered in the two scenarios under assessment (the phases of use and/or final disposal of FOS/GOS were not considered). The functional unit was defined as 100 g of FOS/GOS produced. LCAs were performed using data collected at the laboratory scale during experiments, supplemented with data from technical and scientific literature. Ecoinvent database provided background data. SimaPro was used for the LCA modeling with the midpoint impact EF2.0 characterization method to calculate environmental impacts. For each scenario (FOS produced by synthesis, FOS produced by hydrolysis, GOS produced by synthesis, GOS produced by hydrolysis), the Life Cycle Inventory (LCI) and the Life Cycle Impact Assessment (LCIA) are provided. These data can be used (i) to identify the main environmental hotspots of the production process, (ii) to compare the different process alternatives between them and (ii) to suggest eco-design options to upscale these processes. They could also be re-used in other LCA studies which would include FOS and/or GOS in the production system.

Food production is associated with significant environmental impacts. To reduce these, it is first essential to better understand the environmental implications of production processes, and how these can vary among different products. Historically, most studies in this area have focused on comparing environmental impacts among different food categories, but here, we chose to investigate differences at a finer scale, among products belonging to the same category. Cheese was selected as our study model because it is one of the most popular types of food products around the world but is associated with significant environmental impacts. Specifically, we used Life Cycle Assessment (LCA) to evaluate the environmental impacts of 44 French cheeses that benefit from Protected Designation of Origin (PDO) certification. Our assessments took into account all steps from milk production to the end of the ripening period and the functional unit used was 1 kg of fully ripened cheese. Inventories for milk production were obtained from AGRIBALYSE 3.0. Data on cheeses production stage were collected using PDO specifications, technical datasheets, scientific literature, and three expert opinions. Background inventories (electricity mix, gas production, materials, transport, water, cleaning products) were obtained from the Ecoinvent 3.6 database. Simapro software was used to conduct all LCAs, using the characterization method ''EF 3.0 Method (adapted) V1.00 / EF 3.0 normalisation and weighting set''. Our final dataset contains details on products, life cycle inventories (LCI), and LCIA results. These data could be useful for cheesemakers seeking to improve the environmental performance of their products.

Most of the time, Life Cycle Assessments (LCA) of food products are performed only on one representative of a food category. This doesn't allow us to understand the possible variations of environmental impacts within a food product category and the responsible factors for these variations. For this reason, LCAs were conducted for 80 different industrial pizzas representative of the French retail market. The LCAs were performed using the “EF 3.0 Method (adapted) V1.00/EF 3.0 normalization and weighting set” on SimaPro software. Most of the data used were taken from the AGRIBALYSE 3.0 and Ecoinvent 3.6 databases. The system perimeter goes from the production of the ingredients to the pizza consumption. The functional unit used was 1 kg of ready-to-eat pizza. Life cycle inventories were made to include the different flows in the LCA (materials, transport, energy, water, waste, etc.). The dataset contains details on products, life-cycle inventories (LCI) and LCIA results. These data can enrich the discussion on the need to study the environmental impacts of different products belonging to the same food category and not only one representative in order to avoid erroneous conclusions.