The agricultural sector in Sweden needs to cut GHG emissions and contribute to the climate goal of net-zero emissions by 2045. The GHG reduction goal for agricultural emissions is not quantified, but the Swedish climate policy framework states that ‘Swedish food production shall increase as much as possible with as little climate impact as possible’. Multiple key actors within the sector of food and agriculture have developed roadmaps or industry specific goals for reducing GHG emissions from the sector. Consequently, requirements for transparent GHG accounting and reporting are increasing within the agricultural sector, both on a national and international level. The purpose of the Agrosfär tool is to establish an automatic data driven climate calculator used to calculate GHG emissions from agricultural products and on a farm enterprise level. Automation and automatic data collection will save time, increase the accuracy of the calculations, and simplify updates of the tool to keep it aligned with the most recent climate data and climate reporting methodology. It will make it possible to continuously carry out follow-ups on climate performance indicators and measure improvements from climate measures taken. A working group consisting of agricultural life cycle assessment experts has developed the framework of the tool (e.g., setting system boundaries, selecting methodologies and input data). A technical team has developed algorithms, a digital interface and coupled the tool to other existing agricultural databases, providing farm specific information on crop and animal production data, soil characteristics, carbon footprints and amounts of purchased inputs etc. The tool and user interface have been developed based on input from farmers through prototyping and in-depth interviews. The priority guidelines on which the calculation model is based are the Product Environmental Footprint Category Rules (PEFCR), the International Dairy Federation (IDF)’s approach for carbon footprint for the dairy sector, and FAO Livestock Environmental Assessment and Performance guidelines (FAO LEAP). From the farm perspective, the Greenhouse Gas Protocol (GHG Protocol) Corporate Standard, GHG Protocol Agricultural Guidance (Scope 1 & 2) and GHG Protocol Corporate value chain (Scope 3) Accounting and Reporting Standard are guiding standards. Where standards have diverged or where assumptions have been required, the working group has made expert judgements on which method/guideline to follow or what assumptions to make. A first version of the tool, first described in report version 1, was developed as the basis for further development. The first version contains an animal and a crop module, and can calculate the carbon footprint of crops, milk and beef. This report (version 1.1) has been updated to include the most recent developments of the tool. The main change is that the tool can now also be used to calculate farm climate impact on a yearly basis. Future possibilities to develop the tool and calculation model are described in chapter 7, including suggestions for developing modules for more animal production types, deepening the integration between the crop and animal modules, expanding sources for automatic data collection, developing a carbon sequestration module, and other technical and methodological improvements to ensure alignment with important climate reporting standards. The report will be repeatedly updated as the tool develops, and new versions of the tool are released.

The agricultural sector in Sweden needs to cut GHG emissions and contribute to the climate goal of net-zero emissions by 2045. The GHG reduction goal for agricultural emissions is not quantified, but the Swedish climate policy framework states that ‘the Swedish food production shall increase as much as possible with as little climate impact as possible’ and multiple key actors within the sector of food and agriculture have developed roadmaps or industry specific goals for reducing GHG emissions from the sector. Consequently, requirements of transparent GHG accounting and reporting are increasing within the agricultural sector, both at national and international level. The purpose of the Agrosfär tool is to establish an automatic data driven climate calculator used to calculate GHG emissions from agricultural products and on farm enterprise level. The automation and automatic data collection will save time, increase accuracy of the calculations, and simplify updates of the tool to keep it aligned with the most recent climate data and climate reporting methodology. It will make it possible to continuously carry out follow-ups on climate performance indicators and measure improvements from climate measures taken. A working group consisting of Swedish agricultural life cycle assessment experts have developed the framework of the tool, e.g. setting system boundaries, selecting methodologies and input data. A technical team has developed algorithms, a digital interface and coupled the tool to other existing agricultural databases providing farm specific information on crop and animal production data, soil characteristics, carbon footprints and amounts of purchased inputs etc. The tool and user interface have been developed based on input from farmers through prototyping and in-depth interviews. For general guidelines on methodology the calculation model follows the Product Environmental Footprint Category Rules (PEFCR), the International Dairy Federation (IDF)’s approach for carbon footprint for the dairy sector and FAO Livestock Environmental Assessment and Performance guidelines (FAO LEAP). Where standards have diverged or where assumptions have been required the working group has made expert judgements on which method/guideline to follow or what assumptions to make. A first version of the tool, a so called minimal viable product (MVP) has been developed which will be the basis for further development. The MVP contains an animal and crop module and can calculate the carbon footprint of crops, milk and beef. Future development possibilities of the tool and calculation model is described in chapter 7, such as enabling climate calculations on enterprise level, develop modules for more animal production types, deepen the integration between the crop and animal modules, expand sources for automatic data collection, develop a carbon sequestration module and other technical and methodological improvements to ensure alignment with important climate reporting standards. The report will be repeatedly updated as the tool develops, and new versions of the tool are released.

RISE har på uppdrag av branschföreningen Svensk Fågel under våren beräknat klimatavtryck för svensk kyckling producerad av Svensk Fågels medlemmar. Analysen är genomförd enligt ISO 14067:2018 (ISO, 2018). Klimatavtrycket representerar traditionell uppfödning av kyckling som under hela uppfödningen utfodrats med kommersiella foderblandningar från svenska foderproducenter. RISE har fått tillgång till och baserar klimatberäkningen på primärinformation från de olika aktörerna i värdekedjan för kycklinguppfödning: foderföretag, uppfödare och slakterier. I denna publika rapport återges inte primärdata i de fall uppgiftslämnarna ansett data vara företagskänslig information. Klimatavtrycket har beräknats för 1 kg slaktvikt av kyckling. Slaktvikt är vikten på kycklingen då den är avblodad och fjädrar, huvud, fötter samt inkråm är borttaget. Medelslaktvikten som använts i analysen är 71,4 % av levandevikten av kycklingen.

Purpose: Pesticides are applied to agricultural fields to optimise crop yield and their global use is substantial. Their consideration in life cycle assessment (LCA) is affected by important inconsistencies between the emission inventory and impact assessment phases of LCA. A clear definition of the delineation between the product system model (life cycle inventory—LCI, technosphere) and the natural environment (life cycle impact assessment—LCIA, ecosphere) is missing and could be established via consensus building.

Methods: A workshop held in 2013 in Glasgow, UK, had the goal of establishing consensus and creating clear guidelines in the following topics: (1) boundary between emission inventory and impact characterisation model, (2) spatial dimensions and the time periods assumed for the application of substances to open agricultural fields or in greenhouses and (3) emissions to the natural environment and their potential impacts. More than 30 specialists in agrifood LCI, LCIA, risk assessment and ecotoxicology, representing industry, government and academia from 15 countries and four continents, met to discuss and reach consensus. The resulting guidelines target LCA practitioners, data (base) and characterisation method developers, and decision makers.

Results and discussion: The focus was on defining a clear interface between LCI and LCIA, capable of supporting any goal and scope requirements while avoiding double counting or exclusion of important emission flows/impacts. Consensus was reached accordingly on distinct sets of recommendations for LCI and LCIA, respectively, recommending, for example, that buffer zones should be considered as part of the crop production system and the change in yield be considered. While the spatial dimensions of the field were not fixed, the temporal boundary between dynamic LCI fate modelling and steady-state LCIA fate modelling needs to be defined.

Conclusions and recommendations: For pesticide application, the inventory should report pesticide identification, crop, mass applied per active ingredient, application method or formulation type, presence of buffer zones, location/country, application time before harvest and crop growth stage during application, adherence with Good Agricultural Practice, and whether the field is considered part of the technosphere or the ecosphere. Additionally, emission fractions to environmental media on-field and off-field should be reported. For LCIA, the directly concerned impact categories and a list of relevant fate and exposure processes were identified. Next steps were identified: (1) establishing default emission fractions to environmental media for integration into LCI databases and (2) interaction among impact model developers to extend current methods with new elements/processes mentioned in the recommendations.