Stockholm Environment Institute (SEI)
Leading Tasks
T1.1: Breaking new ground: overcoming spatial and temporal limitations in agricultural production data
Lead: SEI (10PM).
Effort by contributors: ETHZ (10PM), UOY (6PM), DDS (2PM), NILU (0.5PM). Timing: M1-19. Mapping of the subnational (municipality, district, province) agricultural production of all key global crops, including their tonnage, area and yield. The higher accuracy and spatial-explicitness of this dataset allows important improvements in all following other analyses, particularly on resource and energy use, and as well as on environmental impacts of food production. We will build upon the current research of this consortium that developed the GSAP (Global Subnational Agricultural Production) database, covering the subnational regions of the vast majority of countries. Remaining agricultural products will be modelled based on other datasets and research of consortium members, such as the HESTIA.earth database, Cropgrids, and MapSPAM. Contributes to:
D1.1 (M18).
This task is linked to the following milestones: MS1.1 (M18).
Responsible For Deliverables
Deliverable D1.1 — Sub-national crop dataset
| Deliverable Number | D1.1 | Lead Beneficiary | SEI |
| Deliverable Name | Sub-national crop dataset | ||
| Type | DATA | Dissemination Level | PU |
| Due Date (month) | M18 | Work Package No | 1 |
| Description | |||
| Not available |
Deliverable D1.4 — Trade and transport model
| Deliverable Number | D1.4 | Lead Beneficiary | SEI |
| Deliverable Name | Trade and transport model | ||
| Type | OTHER | Dissemination Level | PU |
| Due Date (month) | M40 | Work Package No | 1 |
| Description | |||
| Not available |
Contributions in WP1
Contributing 9PM to:
T1.4: Modelling domestic and international trade and transport modes and emissions
Lead: ULEI (0PM).
Effort by contributors: ETHZ (9PM), SEI (9PM), UOY (5PM), NILU (1PM), DDS (1PM). Timing: M10-48. This task develops a comprehensive spatially explicit approach to analyse the supply chains and footprint of agricultural products. This integrated approach will involve analysing subnational commodity flows combining Trase for selected high-impact crops with FABIO/MRIO for full coverage of all international trade flows. About 85% of all traded products are transported by sea, a number that increases for the specific case of staple foods given their bulky nature. We will model global maritime transport of food trade and assess associated maritime shipping emissions. For all other transportation modes, we will develop a detailed multi-modal transport model, incorporating assessment of greenhouse gas and particulate matter emissions. Regarding IPR, the Trase data is all open, however some input data may be restricted. While the data product used to obtain results might not be shared, the final outputs that are part of the project will be freely shareable as long as we make sure they are not traceable back to the input data. Contributes to:
D1.4 (M40).
Contributing 5PM to:
T1.2: Providing new-generation quantification of resource and energy use and eutrophying emissions in crop production
Lead: ETHZ (10PM).
Effort by contributors: SEI (5PM), ULEI (3PM), UOY (3PM), NILU (0.5PM). Timing: M6-36. Based on Task 1.1, we develop a detailed crop growth model using remote sensing based information in combination with growth and yield statistics for establishing more accurate inventory flows of crop production for key processes and biosphere exchanges. This allows us to add details on land use and land use change, with a special focus on tropical deforestation associated with food imports. Based on the detailed land use data, we will enhance water consumption estimates through an irrigation model (with increased level of detail based on previous work of the consortium). We will close the gap of detailed nutrient use and emission inventories, by enhancing fertiliser application models, differentiating artificial and organic fertiliser (for organic production) and model related N and P emissions. This also allows better estimating energy use in food supply chains due to fertiliser application. We extend model greenhouse / vertical farming production models to provide detailed information on land use, water consumption, heat and electricity demand, and material use. Contributes to:
D1.2 (M36).
Contributions in WP2
Contributing 2PM to:
T2.1: Generate a centralised repository of food-linked data
Lead: ETHZ (5PM).
Effort by contributors: UOY (5PM), ZHAW (4PM), SEI (2PM), COOL (2PM). Timing: M3-12. ata on the environmental impacts of food is scattered. Here, we will gather and interrogate existing food-related datasets (LCA, IO-based/footprinting, production and processing, nutritional, supply-chain management-linked, geospatial/remote-sensing and trade resources) encompassing information and datasets linked to production, processing, consumption and end-of-life/waste stages of the food system. The purpose of this review is to support standardization efforts and help build a roadmap for how to move from the current state of the art to robust PEF standards. The purpose of the review is not distil knowledge, i.e. it is not to get a robust understanding of food system impacts. The purpose is simply to support standardization efforts. We will centrally and systematically record key components of the data. We will document the scope of information being provided (e.g. supply chain stage covered, indicators specified/available, commodity coverage, specificity/resolution, time-series etc), the management of the data by data-owners (e.g. ownership, periodicity of uptake, project resourcing and marketing etc), examples of use-cases and applications (e.g. impactful case studies, known utilisation in policy or private-sector decision making) and availability to end-users (openness, licensing, availability of meta-data and methodology materials, investment in training materials etc). Contributes to:
D2.1 (M21).
Contributing 2PM to:
T2.2: Targeted investments for FAIRness and PEF compliance
Lead: UOY (6PM).
Effort by contributors: ULEI (3PM), DDS (3PM), SEI (2PM), COOL (2PM). Timing: M12-21. Data uptake grossly lags behind data availability. We will assess datasets (including those resources developed/owned by the project team, but also external parties) for technological ‘readiness’. Initial triage (based on Task 2.1 datasets) will identify those most important in providing (or having the potential to provide) actionable information to private sector and policy decision maker needs. Key criteria will include the development status of datasets (i.e. maturity as a product and potential longevity etc), uniqueness (i.e. ability to fill gaps in knowledge), levels of impact (i.e. existing uptake in practice, demonstrable use-cases), and scientific quality, including reported uncertainties. Triage will identify datasets which span the breadth of food sustainability issues (environmental domains, supply chain stages, end-users targeted etc) with the most ‘valuable’ use cases. For this subset of ‘most valuable products’ we will undertake assessment of adherence to FAIR principles and Product Environmental Footprint standards; systematically identifying weaknesses. For the latter, we will benchmark data provision and documentation against PEF guidance from the perspective of dataset readiness to provide information to the sixteen core environmental footprints, plus the optional ‘further environmental information’ aspects of PEF implementation. Best practice examples will be collated across the tools and datasets. Contributes to:
D2.1 (M21), D2.5 (M42).
This task is linked to the following milestones: MS2.1 (M15).
Contributing 2PM to:
T2.3: Improve the technological readiness of key datasets
Lead: UOY (5PM).
Effort by contributors: NILU (5PM), CNRS (3PM), DDS (3PM), ZHAW (3PM), ULEI (2PM), SEI (2PM), ETHZ (2PM), COOL (2PM). Timing: M22-34. To enhance uptake, we will develop recommendations for each tool/data provider based on the assessment of weaknesses and best practice examples (T2.2). We will actively disseminate findings to data providers, who will be invited to attend one-to-one discussion meetings with the project team. We will also host two workshops across multiple partners (covering the same topic, but split to allow attendance from more parties and deeper interaction) to encourage further sharing of best practice and ‘challenges’ in responding to recommendations. An academic publication will also be produced to share outcomes openly. For tools provided by project partners we will, via project funding, implement selected recommendations. This task contributes to D2.2 (M24), D2.3 (M32) and D2.4 (M34). Milestone: M2.2 (M28) Stakeholder workshops (M28); M2.3 (M28): Assessment of which internal tool/data provider recommendations will be implemented (M28). Contributes to:
D2.2 (M24), D2.3 (M32), D2.4 (M34).
This task is linked to the following milestones: MS2.2 (M28), MS2.3 (M28).
Contributing 2PM to:
T2.5: Launch an AI conversational agent (AICA) for food LCA supply chain and environmental impact info
Lead: INTEC (24PM).
Effort by contributors: ARBO (22PM), UOY (2PM), SEI (2PM), NILU (1PM), ULEI (1PM), ETHZ (1PM), CNRS (1PM), DDS (1PM). Timing: M26-46. We will develop a prototype AICA that answers user-posed questions in natural language about the impacts of the EU’s food system. It will utilise food linked LCA, footprint and other data developed within and outwith the project (incl. sources developed in WP1 and assessed in WP2), collated into a central structured database. Quantitative data will be complemented by information derived from research outputs (including outputs from WP3 and WP4) and other assessments. Training of the AICI will take place via development of common questions inspired by the EU’s policy context and the guidance received via stakeholders (WP5). We will undergo a thorough validation process, drawing on expertise from across the consortium. Iteration of the model based on feedback from the experts will take place before final production launch towards the end of the project. Contributes to:
D2.6 (M42), D2.7 (M42).
This task is linked to the following milestones: MS2.4 (M30), MS2.5 (M32), MS2.6 (M34).
Contributions in WP3
Contributing 6PM to:
T3.2: Benchmark actor-level environmental footprints in European food system
Lead: ULEI (16PM).
Effort by contributors: SEI (6PM), ETHZ (2PM), INTEC (2PM). Timing: M9-23. To harmonise impact and actor-level data, LCIs generated in WP1 and validated in WP2 will be aligned by concordance to sectors present within the chosen MRIO database(s). The contribution of food consumption and production groups to the environmental impacts of EU food systems (e.g. climate, pollution and biodiversity) will be benchmarked at regional (NUTS-2), national, EU and global scales. The nutritional quality and socio-economic impacts of diets will also be evaluated to assess synergies and trade-offs with environmental sustainability. Network analysis will complement ranking of groups’ (actors and regions) impacts to identify existing best practices and key targets for improvement actions.
This task is linked to the following milestones: MS3.1 (M23).
Contributions in WP6
Contributing 1PM to:
T6.1: Management of financial legal and administrative requirements
Lead: NILU (9PM).
Effort by contributors: NILUAB (2PM), UOY (2PM), ETHZ (1PM), GLOBE (1PM), SEI (1PM), UOXF (1PM), ARBO (1PM), COOL (1PM), CLIMCO (1PM), ULAT (1PM), BUW (1PM), DDS (1PM), ZHAW (1PM), ULEI (0.5PM), INTEC (0.5PM). Timing: M1-49. In this task we will manage and coordinate all financial and administrative activities in the project, including monitoring and maintaining the overall adherence to the financial budgets. T1.1 will deliver a project toolbox to ensure a smooth communication and cooperation between the project partners. This task will forward the EU contribution according to the work plan, the Consortium Agreement and the decisions made by the consortium. The administrative and financial monitoring of the project will be done by the project coordinator in cooperation with the Project Management Board (coordinator and WP leaders).
Contributing 1PM to:
T6.4: Exploitation strategies and business cases
Lead: NILU (9PM).
Effort by contributors: UOY (2PM), ULEI (1PM), SEI (1PM), UOXF (1PM), ZHAW (1PM), INTEC (0.5PM). Timing: M1-49. GREENGROCER has a distinct set of exploitable outcomes. In this task, we will develop the initial exploitation routes for data products, tools, methodologies, and standardisation activities. Starting out from key exploitation routes, we will develop business model canvases for each of the GREENGROCER outcomes, starting by identifying target markets (e.g. science to science, science to business, B2B or B2C), value propositions, and potential value capture models (e.g. freemium, SaaS -models). For data products developed under an open source licence, this task has clear links with the Data management and open science practices (T6.5) and communication and dissemination strategies. Contributes to:
D6.2 (M9), D6.7 (M46).