A key element in making our food systems more efficient is the reduction of food losses across the entire food value chain. Nevertheless, food losses are often neglected. This paper quantifies food losses in Switzerland at the various stages of the food value chain (agricultural production, postharvest handling and trade, processing, food service industry, retail, and households), identifies hotspots and analyses the reasons for losses. Twenty-two food categories are modelled separately in a mass and energy flow analysis, based on data from 31 companies within the food value chain, and from public institutions, associations, and from the literature. The energy balance shows that 48% of the total calories produced (edible crop yields at harvest time and animal products, including slaughter waste) is lost across the whole food value chain. Half of these losses would be avoidable given appropriate mitigation measures. Most avoidable food losses occur at the household, processing, and agricultural production stage of the food value chain. Households are responsible for almost half of the total avoidable losses (in terms of calorific content).

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Food production and consumption is known to have significant environmental impacts. In the present work, the life cycle assessment methodology is used for the environmental assessment of an assortment of 34 fruits and vegetables of a large Swiss retailer, with the aim of providing environmental decision-support to the retailer and establishing life cycle inventories (LCI) also applicable to other case studies. The LCI includes, among others, seedling production, farm machinery use, fuels for the heating of greenhouses, irrigation, fertilizers, pesticides, storage and transport to and within Switzerland. The results show that the largest reduction of environmental impacts can be achieved by consuming seasonal fruits and vegetables, followed by reduction of transport by airplane. Sourcing fruits and vegetables locally is only a good strategy to reduce the carbon footprint if no greenhouse heating with fossil fuels is involved. The impact of water consumption depends on the location of agricultural production. For some crops a trade-off between the carbon footprint and the induced water stress is observed. The results were used by the retailer to support the purchasing decisions and improve the supply chain management.

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Maintaining biotic capacity is of key importance with regard to global food and biomass provision. One reason for productivity loss is soil compaction. In this paper, we use a statistical empirical model to assess long-term yield losses through soil compaction in a regionalized manner, with global coverage and for different agricultural production systems. To facilitate the application of the model, we provide an extensive dataset including crop production data (with 81 crops and corresponding production systems), related machinery application, as well as regionalized soil texture and soil moisture data. Yield loss is modeled for different levels of soil depth (0-25cm, 25-40cm and >40cm depth). This is of particular relevance since compaction in topsoil is classified as reversible in the short term (approximately four years), while recovery of subsoil layers takes much longer. We derive characterization factors quantifying the future average annual yield loss as a fraction of the current yield for 100years and applicable in Life Cycle Assessment studies of agricultural production. The results show that crops requiring enhanced machinery inputs, such as potatoes, have a major influence on soil compaction and yield losses, while differences between mechanized production systems (organic and integrated production) are small. The spatial variations of soil moisture and clay content are reflected in the results showing global hotspot regions especially susceptible to soil compaction, e.g. the South of Brazil, the Caribbean Islands, Central Africa, and the Maharashtra district of India. The impacts of soil compaction can be substantial, with highest annual yield losses in the range of 0.5% (95% percentile) due to one year of potato production (cumulated over 100y this corresponds to a one-time loss of 50% of the present yield). These modeling results demonstrate the necessity for including soil compaction effects in Life Cycle Impact Assessment.

A Life Cycle Impact Assessment method was developed to evaluate the environmental impact associated with salinity on biodiversity in a Spanish coastal wetland. The developed characterization factor consists of a fate and an effect factor and equals 3.16 × 10(-1) ± 1.84 × 10(-1) PAF · m(3) · yr · m(-3) (PAF: Potentially Affected Fraction of species) indicating a "potential loss of 0.32 m(3) ecosystem" for a water consumption rate of 1 m(3) · yr(-1). As a result of groundwater consumption with a rate of 1 m(3) · yr(-1), the PAF in the lost cubic meter of ecosystem equals 0.05, which has been proposed as the maximum tolerable effect to keep the ecosystem intact. The fate factor was calculated from seasonal water balances of the wetland Albufera de Adra. The effect factor was obtained from the fitted curve of the potentially affected fraction of native wetland species due to salinity and can be applied to other wetlands with similar species composition. In order to test the applicability of the characterization factor, an assessment of water consumption of greenhouse crops in the area was conducted as a case study. Results converted into ecosystem quality damage using the ReCiPe method were compared to other categories. While tomatoes are responsible for up to 30% of the impact of increased salinity due to water consumption on ecosystem quality in the studied area, melons have the largest impact per tonne produced.

Food is one of the most energy and CO2-intensive consumer goods. While environmental data on primary agricultural products are increasingly becoming available, there are large data gaps concerning food processing. Bridging these gaps is important; for example, the food industry can use such data to optimize processes from an environmental perspective, and retailers may use this information for purchasing decisions. Producers and retailers can then market sustainable products and deliver the information demanded by governments and consumers. Finally, consumers are increasingly interested in the environmental information of foods in order to lower their consumption impacts. This study provides estimation tools for the energy demand of a representative set of food process unit operations such as dehydration, evaporation, or pasteurization. These operations are used to manufacture a variety of foods and can be combined, according to the product recipe, to quantify the heat and electricity demand during processing. In combination with inventory data on the production of the primary ingredients, this toolbox will be a basis to perform life cycle assessment studies of a large number of processed food products and to provide decision support to the stakeholders. Furthermore, a case study is performed to illustrate the application of the tools.