Emissions and resource use are influenced by soil and climate as well as by farm management. In addition, characterisation factors (CFs) used in life cycle assessment (LCA) to translate emissions and resource use into environmental impacts also depend on the location. The purpose of this study was to evaluate how regional differences in emissions, resource use, and CFs influence the variability of the environmental impacts of agricultural products from the perspective of an LCA practitioner. We examined four databases—AGRIBALYSE®, SALCA, WFLDB, and Agri-footprint®—differentiating both emissions/resource uses and their environmental impacts at the country level. Only the Agri-footprint® database had data from at least ten different countries considered sufficient for a statistical analysis. The country-specific environmental impacts of the products in Agri-footprint® were calculated according to the Swiss Agricultural Life Cycle Assessment (SALCA) method using Brightway and analysed for seven spatially explicit impact categories: water use, land occupation, terrestrial acidification, eutrophication, water scarcity, soil quality, and biodiversity. Spatial differences in emissions, resources, and CFs contributed to the spatial variability of environmental impacts at the product level. For nutrient-related impacts, such as eutrophication and acidification, the spatial variability of the contributing emissions had a stronger influence than the variability of the CFs. This is evident for marine and freshwater eutrophication, where characterisation is assumed to be uniform across all countries. For biodiversity the variability in CFs was more dominant. Most of the impact categories showed more significant positive than significant negative correlations between agricultural land occupation and the impact score. A higher yield per area thus generally leads to lower impacts per product unit. In summary, a spatial differentiation is needed if the parameters driving the impacts show high spatial variability or have a strong influence on the emission, and this emission has an important contribution to the impact. Our analysis highlighted that emission fluxes and CFs significantly influence the spatial variability of midpoint-level environmental impacts. Inventory flows exhibited greater variability than CFs, except for the land-use-related impact categories. Most impacts correlated positively with agricultural land occupation, showing a strong effect on yield levels. Our results underlined the importance of accounting for the spatial variability of emissions and CFs to adequately reflect the environmental impacts of agricultural products. The results are primarily representative of European conditions and temperate regions, as Agri-footprint® mainly includes products cultivated in Europe.

Social life cycle assessment has become an important tool for systematically including the social component in the sustainability assessment of value chains. However, the exclusion of non-human animals from social life cycle assessment (S-LCA) is problematic and essentially speciesist. This paper addresses this problem by developing strategies towards a non-speciesist S-LCA. This is a conceptual contribution in which we discuss the rationale and identify the methodological options for considering the well-being and rights of both human and non-human animals in social life cycle analysis. When applying the methodological options in practice, researchers may face challenges stemming from the current socioeconomic structures and speciesist values dominating society. However, we argue that approaches attentive to including non-human animals in a social life cycle assessment should take the well-being of animals as seriously as that of humans. To advance the methodology of social life cycle assessment, the range of impacts on the well-being of all sentient beings as well as their severity and duration should be considered as far as possible based on the available data and scientific literature. This should include issues of longevity and allow for a comparison of animal production and crop production. Thereby, it should allow for different ethical perspectives, like utilitarian and rights-based approaches, rather than following one particular route. S-LCA researchers who take up this challenge will inform the transformation of the agri-food sector towards greater sustainability, help to align the practice of S-LCA with recent developments in philosophy and science, and better prepare us for addressing future changes to the social demands placed on animal agriculture.

Ecolabels and novel environmental assessment methods are increasingly being used to evaluate the environmental impacts of food items. Some ecolabels build on life cycle assessment, a standardised method for the environmental impact assessment of products over their entire life cycle. The major challenges of life cycle assessment include its complexity in application and result communication, as well as its data intensity. The aim of this study was to compare the methods behind ecolabels to traditional life cycle assessments for evaluating the environmental impacts of food products. To this end, we (1) categorised ecolabels, (2) identified criteria describing the suitability of existing ecolabels in evaluating the environmental impacts of food labels, (3) identified main challenges of the methods underlying ecolabels, and (4) evaluated the challenges based on the criteria to answer the research question. Among the challenges, we found that merging results obtained by different methods, such as life cycle impact assessment and bonus/malus point systems, to build a composite score can risk double counting. Furthermore, certain agricultural production methods are sometimes assumed to be more environmentally friendly than others without evidence. Environmental labels focusing on one or a few selected aspects of sustainability while ignoring other relevant issues can lead to burden shifting and should be avoided. Based on our findings, we conclude that ecolabels help consumers make more sustainable purchasing decisions and create business cases for companies as an incentive to mitigate impacts, while complex research questions should be addressed based on life cycle assessment.

CONTEXT National and international agendas are focusing on reducing pesticides due to their detrimental effects on flora, fauna, and human health, which has led to the introduction of agri-environmental programmes aimed at reducing the risk of pesticides. Pesticide reduction in agriculture can have an impact on labour time requirements and profitability. OBJECTIVE We used winter wheat, sugar beet, and potatoes as examples to analyse the changes in profitability and working time requirements, including management tasks. METHODS For the calculations, we used five different production schemes for each crop: reference; (A) reduction of herbicides; (B) reduction of growth regulators, fungicides, and insecticides; combination of schemes (A) and (B); and organic production. The working time requirements for fieldwork and farm management work were modelled for each scheme and crop. The respective partial costs and benefits of the schemes were calculated for each crop. RESULTS AND CONCLUSIONS Based on the model assumptions, scheme (B) appears favourable in terms of working time requirements, and profitability of winter wheat and sugar beet. Scheme (A) offers synergies between the same parameters for potato production. Economic analysis shows that crop production with reduced pesticide use may even experience an increase in financial viability if the yield is not severely jeopardised, and farmers can be compensated through premiums and direct payments. SIGNIFICANCE Our results can support policy-making, since the labour time requirement and profitability of pesticide-reduced crop production can affect the success of voluntary agri-environmental programmes for the reduction of the risks from pesticide use in agriculture.

Purpose Agricultural production, which dominates the environmental impacts of the food sector, has specific characteristics that need to be considered in life cycle assessment (LCA) studies. Agricultural systems are open, difficult to manage and control, strongly depend on natural resources and their impacts are highly variable and influenced by soil, climate and farm management. A specific framework, efficient methods and tools are thus needed to adequately assess the environmental impacts of agricultural systems. Methods We present the Swiss Agricultural Life Cycle Assessment (SALCA) concept and method, developed for a detailed and specific analysis of agricultural systems. It comprises rules for the definition of system boundaries, functional unit and allocation, emission models, a life cycle inventory (LCI) database, calculation tools, impact assessment methods and concepts for analysis, interpretation and communication. This paper focuses on emission models for gaseous N, nitrate leaching, P emissions to water, soil erosion, pesticides, heavy metals, emissions from animal production and impact assessment methods for soil quality and biodiversity. The models are calculated at the crop, field, animal group and farm levels and are integrated in a consistent and harmonised framework, which is ensured by exchanging intermediate results between models. Results and discussion The SALCA concept has been applied in numerous LCA studies for crops and crop products, cropping systems, animal husbandry systems and animal products, food and feed products, farms and product groups, the agrifood sector and food systems. The SALCA methodology has also been a backbone of the LCI databases ecoinvent, AGRIBALYSE and the World Food LCA database. The strengths of SALCA lie in its comprehensiveness, specificity to agriculture, harmonisation, broad applicability, consistency, comparability, flexibility and modularity. The extensive data demand and the high complexity, however, limit the application of SALCA to experts. The geographical scope is limited to Central and Western Europe, with a special focus on Switzerland. However, due to the modular and flexible design, an adaptation to other contexts is feasible with reasonable effort. Conclusions SALCA enables answering a wide range of research questions related to environmental assessment and is applicable to various goals and scopes. A further development would be the inclusion of the social and economic dimensions to perform a full sustainability analysis in the SALCAsustain framework.

This paper presents a scientifically sound set of environmental indicators for comprehensive description of farm environmental impact within a policy-driven framework that aims at achieving Swiss agri-environmental policy goals. The indicator system covers the following key environmental areas: greenhouse gas (GHG) and ammonia emissions, nitrate and phosphorus leaching, biodiversity, plant protection products, soil erosion, and humus accumulation. Novel indicators were developed through reviewing existing indicators and intensive consultation with experts. To provide a flexible and suitable indicator-based system, three systems of varying complexity (simple, medium, detailed) were developed. In-depth evaluation revealed specific advantages and disadvantages of the three novel indicator systems at different complexity levels. The simple system benefited from a low administrative burden, but may suffer from limited acceptance owing to its low flexibility regarding farmers’ scope for action. The detailed system may be very demanding to implement in terms of data acquisition, but benefited from more accurate representation of the key driving processes. Successful implementation of the system will require broad acceptance promoted through sufficient support and advice, good communication between participating stakeholders, a secure and simple data acquisition process, and a high degree of transparency.

Indicator-based frameworks for assessing farms’ environmental performance have become a resource for environmental knowledge regarding the impacts of agricultural practices. The present study explores whether a novel indicator-based direct payment system, which focuses on the farms’ environmental impact, could better target Swiss agricultural policy and help achieve its environmental goals. The system covers the environmental topics of biodiversity, nutrients and climate, plant protection products, and soil. Despite high direct payments, simulations with an agent-based agricultural sector model show that such indicator-based payments have a limited impact. For example, the decrease in the animal population is only moderate. Though direct payments alone can hardly lead to the desired reduction in Switzerland's environmental pollution, they could help make important contributions to a more targeted distribution of environmentally oriented direct payments and steer agricultural production in a more environmentally friendly way.

A sample of 239 farm year observations of Swiss farms was assessed at the product group level for analyzing the relationship between environmental and economic performance and correlations between product groups (Milk, Cattle, Cereal, Beets, and Potatoes). The farms cover the production regions valley, hill and mountains and practice organic production or proof of ecological performance (PEP), the Swiss standard production.The environmental dimension was covered by nine impact categories calculated by the Swiss Agricultural Life Cycle Assessment method (SALCA). The impacts were aggregated using a data envelopment analysis (DEA). The economic dimension is assessed by the family workforce income per product group calculated from a full cost data set from the Swiss farm accountancy data network (FADN). Hereby, all indirect costs, which cannot be directly attributed to the product groups, were allocated using standard costs.We also included productivity as a third dimension in our analysis, quantified as output per area for crop products and output per animal livestock unit for the animal product groups.No trade-offs between the environmental efficiency and the economic performance were identified. On the contrary, for Cattle and Milk we found significant synergies (1.5 times more observations show synergies than no effect or trade-offs).Furthermore we found that productivity correlated positively with environmental efficiency for Milk (coef-ficient = 0.27), Cattle (coefficient = 0.38) and Cereals (coefficient = 0.30), but only for Cattle (coefficient = 0.17) and Potatoes (coefficient = 0.47) it correlated with economic performance.For all product groups except Cereals, the organic farming system had 5% to 10 higher environmental effi-ciency and 5%-26% higher economic performance than the PEP farms. Although the differences were not sig-nificant, a consistent decrease up to-20% in environmental performance and productivity was observed between the valley/hill and the mountain region.Our results show no indication that farmers maximize their productivity or economic performance at the cost of environmental efficiency. However, the large variability suggests that there is a) room for improvement in several dimension simultaneously, and b) that maximizing productivity does not seem to be a necessity for these improvements.

The online version of the original article can be found at https://doi.org/10.1007/s11367-020-01790-0

In recent decades, many sustainability indicators and methods have been developed at farm level, but a validated set of quantitative and scientifically-sound indicators covering all three dimensions of sustainability is still needed. For this reason, the sustainability method SALCAsustain was developed in order to estimate the environmental impact and economic and social situation of farms using a manageable number of indicators. The primary aim of this study was to assess the feasibility, explanatory power, and acceptability to farmers of the SALCAsustain methodical framework. To achieve this goal, SALCAsustain was applied for the first time to selected Swiss farms. In-depth personal feedback interviews were conducted to gain more insights into the feasibility and farmers’ acceptance of the method. The results showed that SALCAsustain is a feasible, acceptable and robust method for assessing farm sustainability based on a set of indicators. Correlation analysis demonstrated that the number of environmental indicators can be reduced due to high correlation, but that the correlation between environmental impact and socioeconomic indicators was generally low. Evaluation of responses to questionnaires and semi-structured interviews with farmers revealed that the majority would adjust their medium and long-term planning to achieve higher sustainability scores. Additional efforts are needed to speed up data collection and to refine plausibility checks, through exploiting the increasing digitalisation in agriculture. Recommendations and instructions on actions for more sustainable farm management are also needed.

Periodized nutrition is necessary to optimize training and enhance performance through the season. The Athlete’s Plate (AP) is a nutrition education tool developed to teach athletes how to design their plates depending on training load (e.g., volume × intensity), from easy (E), moderate (M) to hard (H). The AP was validated, confirming its recommendations according to international sports nutrition guidelines. However, the AP had significantly higher protein content than recommended (up to 2.9 ± 0.5 g·kg−1·d−1; p < 0.001 for H male). The aim of this study was to quantify the environmental impact (EnvI) of the AP and to evaluate the influence of meal type, training load, sex and registered dietitian (RD). The nutritional contents of 216 APs created by 12 sport RDs were evaluated using Computrition Software (Hospitality Suite, v. 18.1, Chatsworth, CA, USA). The EnvI of the AP was analyzed by life cycle assessment (LCA) expressed by the total amount of food on the AP, kg, and kcal, according to the Swiss Agricultural Life Cycle Assessment (SALCA) methodology. Higher EnvI is directly associated with higher training load when the total amount of food on the plate is considered for E (5.7 ± 2.9 kg CO2 eq/day); M (6.4 ± 1.5 kg CO2 eq/day); and H (8.0 ± 2.1 kg CO2 eq/day). Global warming potential, exergy and eutrophication are driven by animal protein and mainly beef, while ecotoxicity is influenced by vegetable content on the AP. The EnvI is influenced by the amount of food, training load and sex. This study is the first to report the degree of EnvI in sports nutrition. These results not only raise the need for sustainability education in sports nutrition in general, but also the urgency to modify the AP nutrition education tool to ensure sports nutrition recommendations are met, while not compromising the environment.

Agricultural life cycle analysis (LCA) provides information about the environmental footprint of farming. Life cycle sustainability assessment (LCSA) includes social and economic indicators. As a contribution to LCSA, we developed an indicator measuring the impact of individual farms on visual landscape quality based on state-ofthe-art theory for landscape aesthetic assessment and conforming to general LCA principles. The indicator is a composite consisting of two independent sub-indicators, the aggregated diversity indicator (ADI) and the area-weighted preference value (AWPV). Both sub-indicators are based on the preference values of the Swiss population for the most frequent crop types and farmland features. The two sub-indicators were calculated when the land-use types with an available preference value represented 75% of a farms' utilised agricultural area. Following this rule, we were able to evaluate 91% of Swiss farms. The ADI measures a farm's contribution to land-use diversity and to seasonal diversity, while the AWPV measures a farm's contribution to perceived naturalness. The two sub-indicators are combined to form the composite landscape indicator (CLI). The two sub-indicators were computed from Swiss farm structure data for 2015 without additional data collection. Two scenarios were defined to test the independence of the two sub-indicators from each other and the response of the CLI against landscape changes. The first scenario enriched the crop diversity of the farms to test the response of the ADI. The second scenario increased the number of standard trees on farms to test the AWPV. The results showed that the two sub-indicators complement one another by responding to different changes in landscape quality. In both cases, the CLI showed on average increasing values after enriching crop diversity or increasing the number of standard trees on selected farms. The solid conceptual grounding of the two sub-indicators in landscape aesthetic theory combined with LCA principles renders them reproducible and independent of the observer.

Describing the impact of farming on soil quality is challenging, because the model should consider changes in the physical, chemical, and biological status of soils. Physical damage to soils through heavy traffic was already analyzed in several life-cycle assessment studies. However, impacts on soil structure from grazing animals were largely ignored, and physically based model approaches to describe these impacts are very rare. In this study, we developed a new modeling approach that is closely related to the stress propagation method generally applied for analyzing compaction caused by off-road vehicles. We tested our new approach for plausibility using a comprehensive multi-year dataset containing detailed information on pasture management of several hundred Swiss dairy farms. Preliminary results showed that the new approach provides plausible outcomes for the two physical soil indicators “macropore volume” and “aggregate stability”.

Trois methodes developpees en Suisse sont disponibles pour evaluer la durabilite au niveau de l’exploitation: RISE, SMART et SALCAsustain. Le present article compare les trois methodes a l’aide d’un catalogue de criteres et de quelques exemples concrets afin d’aider le lecteur a choisir l’outil le mieux adapte a son application specifique et a son groupe cible. Les trois methodes couvrent toutes les dimensions de la durabilite et les resultats obtenus permettent de deduire des mesures d’amelioration et des decisions concretes pour les groupes d’interet concernes. Les arguments exposes montrent que SALCAsustain convient pour repondre a des questions de recherche et analyser differentes strategies de gestion d’exploitation. La force de RISE reside dans sa souplesse, qui permet de l’utiliser pour le conseil, l’enseignement et la comparaison d’exploitations et de groupes d’exploitations. SMART permet un examen rapide de la durabilite a l’echelle de l’exploitation et fournit des resultats qui peuvent egalement etre compares entre les exploitations et facilement communiques a des tiers. Le choix de la methode appropriee depend donc de la problematique en jeu et du groupe cible.

There are three methods available for evaluating sustainability at farm level that were developed in Switzerland: RISE, SMART and SALCAsustain. In this article, the three methods are compared by means of a list of criteria and several concrete examples with the aim of making it easier for readers to decide which tool is best suited for their own specific application and target group. All three methods cover sustainability comprehensively, and concrete measures for improvement and decision-making can be derived for the relevant interest groups from the results. The details show that SALCAsustain is suitable for answering research queries as well as analysing different farm-management strategies. RISE's strength is its flexible applicability which allows for its use in extension and teaching, and in the comparison of farms and groups of farms. SMART enables rapid screening of farm sustainability and provides results which also allow for inter-farm comparisons and which can easily be communicated to third parties. The choice of the appropriate method therefore depends on the question posed as well as on the target group.

The integration of ecosystem services (ESS) in life cycle assessment (LCA) poses two main challenges: (1) how to integrate ESS within LCA, and (2) how to quantify the delivery of ESS. Several approaches have been proposed to integrate ESS in LCA: using multiple functional units, allocation to ESS, system expansion and introducing additional indicators. Some ESS are already directly or indirectly covered in LCA impact categories, while others remain to be added. The methods SALCA-biodiversity, SALCA-soil quality and the newly developed SALCA-landscape aesthetics will be applied to assess the environmental impacts and ESS from three grassland-based dairy production systems in Switzerland.