Pilot Description & Climate Change application: Stakeholders need easily accessible climate effect applications and atlases of the Aa of Weerijs catchment. These are preferably built on spatial and temporal high-resolution data on climate and for relevant effects of Climate Change. There are some existing national and regional climate atlases, but they are not built on high-resolution data, and, secondly, they provide few, generic climate effect analyses. The proposed applications built with the support of GEOSS data will enhance stakeholder knowledge for designing climate adaptation measures and analyse these on their effects and degree of reducing/managing water shortages in drought conditions, and of GHGs mitigation (denitrification and carbon sequestration). Applications are as follows:
1. Hydrological / Water management model: Using combinations of data available locally and in GEOSS, comprehensive model(s) representing the hydrology in the catchment will be developed such that the adaptation measures can be represented and their effects analysed. These models need to provide results easily translated into potential actions by stakeholders on the ground, a task that will need to continue for a longer period. A mix of process-based models and AI-based models will be built, including sensitivity and uncertainty assessments. A hydrological and hydraulic model of the Aa of Weerijs catchment will be designed (including the subsurface), capable of representing adaptation measures (water storage, effective use, etc.) preferably at level of farm or property, under different climate scenarios. The value of GEOSS data will be tested also to assess conditions in the upstream part of the catchment in Belgium. Although the catchment is small (about 190 km2, of which 120 km2 is in Belgium), such analysis is valuable for replication / upscaling in other cross (trans) border catchments.
2. Soil carbon model: An integrated model of the catchment as a socio-ecological system will be built, representing the impact of adaptation measures on carbon sequestration. The model will be used to analyse some representative chrono-sequences of land use change (space‐for‐time substitution sites). To assess the impact of nature based solutions as adaptation measures on soil carbon storage, the application will model these impacts on processes, combining EO and in-situ data (from NB/waterboard), on changes in Soil Organic Matter (SOM), Soil Quality (topsoil depth, earthworms, drainage, retention etc.), Land Use Change (SDG 15.3). In addition to testing the effect on soil carbon sequestration locally, this application will enable assessing the impact on soil carbon at European Scale (EU Green Deal). This will be enabled using sub-basin spatial variability in drivers and retention processes of the Global News model (Global Nutrient Export from WaterSheds) with EU basins data.
3. Decision Support Application (web-based) that will allow presentation and testing of the adaptation measures in the Aa of Weerijs catchment by different stakeholders of the Pilot 1 Communities of Practice in a user-friendly manner. The effect of all proposed adaptation measures will be tested under Climate Change impact scenarios already developed in the climate impact atlases in NL11. Where needed, these atlases will be enhanced to assess impacts on local scales.

• Create a hydrological and water management model for the Aa of Weerijs catchment, for testing different nature-based solutions aiming at reducing and managing water shortages and droughts.
• Assess the value of GEOSS data for modelling water-related adaptation measures in cross-border catchments.
• Develop an integrated catchment model, capable of testing adaptation measures on soil carbon sequestration.
• Extend the soil carbon sequestration modelling for quick assessment at EU scale, using EU river basin data.
• Develop a DSS for collaborative decision making regarding selection of local climate adaptation measures.

Regional authorities and municipalities, Water Management Boards Land and Nature Managers, Agricultural organisations, Citizens councils (secondary).

6,13,15: SDG6 – Target 6.4: “…substantially increase water-use efficiency…”– addressed by adaptation measured identified, modelled and recommended for application in Aa of Weerijs, using indicators such as ‘Water Use Efficiency’ and local indicators identified by stakeholders; SDG6 – Target 6.6: “…protect and restore water-related ecosystems…” – addressed by promoting measures that create nature areas in Aa of Weerijs; SDG13 – Target 13.1: “…Strengthen resilience and adaptive capacity to climate-related hazards…” – addressed by all applications, specifically by the DS application for supporting stakeholders select adaptation measures in Aa of Weerijs; SDG15 – Target 15.3: “…combat desertification, restore degraded land and soil, including land affected by desertification, drought and floods,…” – addressed by adaptation measures identified, and modelled for the Aa of Weerijs, using indicators such as ‘Soil sealing index’ and local indicators identified by stakeholders.

Precipitation, Temperature, River discharge, LC/LU, Evaporation from land, Anthropogenic water use, Groundwater, Soil carbon, Soil moisture, Leaf Area Index.

EIFFEL, in a co-design process led by NPA, envisions to achieve short and long-term adaptation to Climate Change (e.g. carbon sequestration) and address environmental priorities of post-CAP 2020. This will be achieved thought A) the enhancement of EO services by leveraging on GEOSS and Copernicus data/products, as well as the distinct advantages of IACS/LPIS over other potential LULUCF data sources. The co-designing approach aims to B) enhance the reporting/monitoring of agricultural carbon emissions data by reaching Tier 3 modelling methodologies (IPCC guidelines), and C) assess recognized good practices (e.g. crop rotation) to the advent of Climate Change for current and future climatic conditions.
A) Enhanced spatial explicit agri-indicators: The aim is to provide detailed, next generation agricultural products for a robust assessment at micro-scales (i.e. field level based on IACS). The estimation of spatially distributed vegetative characteristics will be done leveraging GEOSS data (DEM, CLMS) and assimilating EO, in-situ and auxiliary spatial databases (LPIS). In this context, a monitoring tool will integrate both indirect predictions of Soil Organic Carbon (SOC) for grasslands through digital soil mapping techniques, and direct prediction for exposed soils (e.g. croplands), through imaging spectroscopy techniques. The accuracy of SOC prediction should meet the needs of users responsible for reporting on soils, and of policy makers designing and evaluating policies to increase SOC stocks. Given the rapid sensor developments (e.g. hyper-spectral PRISMA), the approach should evolve in the quality of SOC predictions and accommodate other soil properties (NO3-N). Existing EO data will be studied for their features, regulation needs and applicability in EIFFEL, while prominent integration strategies will be proposed assisted by XAI models, including uncertainty assessments.
B) Agricultural Carbon Hybrid model: With the need to move to higher tier methodologies, we will evaluate ensemble DL for building agricultural carbon meta-models and improve existing agricultural C storage and flux estimates in terms of spatiotemporal scale and completeness. The enhanced spatial explicit agri-indicators will be combined with global gridded crop models (GGCMs, e.g. EPIC), supporting scenario based calculations of crop biomass, soil C storage and C fluxes. The declaration of agricultural lands will be extended to provide additional information related to farm management practices (e.g. tillage). Then, spatiotemporal downscaling of GGCMs outputs will be performed by applying ensemble modelling on the large scale agronomic simulations as derived from the various GGCMs and applied to the region of interest at a finer spatial resolution. The approach will enable a meta-model training in a systematic way in order to simulate artificial combinations of atmospheric, soil, cultivar, and management conditions and the corresponding reporting of them.
C) Crop rotation: Crop rotation will answer where suitable areas are located, taking into account climate shifts from one area to another. Research will be conducted to build data driven algorithms to model the suitability of specific crops (e.g. Winter wheat, Winter rape, Winter rye, Winter triticale, Winter barley, Spring wheat, Spring rape, Spring barley, Peas, Oats, Beans) using yield data and EO variables (agriculture, environmental and weather). Then, specific IPCC climate scenarios will be used (e.g. RCP 2.6, 4.5, 8x.5) for the 2050s and 2100s, providing important agro-climatic indicators e.g. precipitation, air temperature, frost days, max consecutive dry/frost days etc. to assess the suitability of specific crops. The influence of climatic conditions and land changes (e.g crop mixes and extent of crop rotation) will be evaluated, using geospatial land suitability models for selected crops. A suitability analysis will be performed clustering land suitability parameters using XAI models.
On top of these, an in-depth validation exercise will be executed in the Lithuania (~400 farmers) stratified into landscapes unit based on the following criteria: agricultural land use (incl. nitrate vulnerable areas) and soil type. Additionally, socio-economic impacts will be roughly estimated taking into account the variability of farm income/subsidies% per region, as well as gender-age information.

• Support national GHG inventories by moving to higher Tier methodologies for LULUCF monitoring, reporting and verification via the development and utilization of a hybrid Cropland Carbon Monitoring System.
• Indirect predictions of Soil Organic Carbon (SOC) for grasslands through digital soil mapping techniques.
• Enhance the prediction of temporal variation (10%) and eliminate the uncertainty (-15%) for organic carbon estimations compared to the IPCC Tier 1 approach using state-of-the-art downscaling methods.
• Assess the value of IACS/LPIS and Copernicus Land Monitoring Service (CLMS) for LULUCF accounting purposes by EU member state.
• Develop operational commercial midstream agriculture EO services for monitoring practices that can reduce agricultural greenhouse gases (GHGs) emissions (e.g. diversification) as indicated in the reformed CAP.

Paying agencies, Agricultural policy makers (primary) Farmers, Agri-consultants, Agricultural Cooperatives (secondary), environmental agencies and scientific institutions.

2, 15. The pilot contributes to the SDG2.4 filling monitoring gaps for: crop yield and annual change in degraded arable land and forward an integrated approach for improving soil quality, in line with EU directives (CAP GAECS). Also, to SDG15.1 and 15.3 by enhancing the information, with positive impacts on diverse ecosystems, provide a reliable way to measure land degradation at a variety of landscapes.

Precipitation, Surface Temperature, anthropogenic water use, above ground biomass, LULC, Leaf area index, SOC.

BPA is gathering real time surface pollution data through a set of 25 in-situ stations distributed in the 5 ports area, that measure atmosphere parameters every 10 minutes, such as SO2, NO2, O3, CO, PM10, PM2.5 and weather observations (temperature, pressure and wind direction). Yet, this amount of data is not enough to build pollution patterns to produce reliable historical episodes of pollution or anomaly pollution predictions outside the port area, neither in the city nearby, where local and regional variability should be considered. This pilot will develop, through a co-design process, a port-oriented, atmospheric pollution monitoring web application addressed to port operators, cruise companies, city and other stakeholders for decision making and awareness. This application benefits from XAI, DL, data mining and geospatial techniques and is facilitated by EIFFEL tools. Real time in-situ observations will be combined with historical GEOSS data as well as external sources. The application will allow (i) integration with the cognitive search tool for data exploration, (ii) the calibration of EO surface pollution data in the port area, where land pollution stations data is available, (iii) the upscaling of pollution data in a regional level taking into account GEOSS and other open data sources, (iv) the real-time monitoring of abnormal pollution events detection, through the correlation of vessel activity (cargo and cruise ships), pollution, wind, and land traffic data in port area, city area and sea nearby, identifying the pollution origin and impact, (v) the temporal analysis of pollution indicators, in areas affected by navigation routes, (vi) the prediction of pollution patterns for supporting decision makers in optimising vessel traffic routes from/to the port area. The application will also provide a map viewer with temporal air quality maps (following OGC standards, INSPIRE), profile-tailored dashboards with pollution KPIs, notifications and reports for BPA, cruise companies and city authorities/citizens. This pilot will leverage datasets, results and collaboration with ongoing projects that share complementary objectives, e.g. PIXEL (H2020) and I2panema (ITEA3).

• Reduce the carbon footprint of the port; get closer to the Zero Emissions goal. The most polluting port activities will be identified and actions and investments proposed to reduce their impact (changing current machinery into ‘greener’ models or rewarding ships that use alternative fuel at a given dock or port).
• Determine if the origin of pollution events in port/city are caused by port activity; reduce the number of port-generated pollution episodes, through XAI-enabled decision making that targets the reduction of such events.
• Improve the reputation of the port authority as per their environmental policies towards the city, citizens, regional and national environmental institutions and Spain Ports Authority.
• Allow BPA to undertake initiatives towards the PA; Tangible Climate Change impact indicators will support BPA to commit more to PA goals, by enhancing accountability on the port-induced air pollution. It will support BPA in its efforts to follow the Katowice rulebook, cooperating with other stakeholders, and jointly providing mitigation plans.

Port Authority, Cruise companies, Shipping companies (primary) City Councils, citizens (secondary).

9,11,13,14. This pilot will support SDG 9.3, as BPA will upgrade its ICT infrastructure to make it sustainable. It will support SDG 9.4 with enhancing its Research and Innovation (R&I) activities and increase the number of such personnel at BPA. BPA will monitor emissions’ impact on the port-city areas and will make decisions to reduce the adverse per capita environmental impact of cities involved, in line with SDG 11.6. This will support ports and nearby cities in adopting and implementing integrated policies and plans towards Climate Change, in line with the SFDRR 2015-2030 (SDG 11.B). Improving awareness-raising and early warning by prediction of pollution episodes, is in line with SDG 13.3; it also significantly reduces marine pollution (SDG 14.1).

Precipitation, Surface radiation budget, Water vapour, Earth radiation budget, Ozone, Aerosols, Sea surface temperature, Sea level/ice/state, Ocean colour, Nitrous Oxide, Ocean Surface Heat Flux.

The Region of Attica (approx. 3.8M population) is the key stakeholder that will drive the co-design of a Climate Change application with other partners (NOA, Draxis). The application will enable the inspection of different GHG emissions' mitigation scenarios in three critical sectors:

(i) Building energy efficiency: Google Earth imagery classification and object features including buildings and shadows geometry integrated, with Eumetsat’s SAFNWC and Copernicus products (e.g. Urban Atlas 2012; Building Height 2012) will be used to map the footprint of buildings and their main geometry (e.g. height, roof-top area), in a selected Local Administrative Unit (LAU). In addition, the QGIS package with the LU/LC from the Greek Land Registry will help identify the potential areas for PV penetration. This data will be combined with national statistical data to compile a building stock model (BSM), leveraging EO and AI driven classification to map the building stock to specific building typologies. The concept from the EPISCOPE project along the lines of the TABULA Hellenic building typology and the updated version will enable scenario based calculation of GHG emission reduction. Further BSM improvement will be done by evaluating the above free data with Very High Resolution data for the building footprint (e.g. IKONOS), thermal envelope properties and local or central heat pumps (e.g. Sentinel-3 TIR). Complementary data through Cadastral and the energy performance certificate central registry will be used. BSM will allow assessing various renovation measures, modernization rates of the envelopes, technical installations, renewables etc. for the typical buildings and then projected to the region’s building stock. The vision is a systematic process for assessing energy savings and emissions abatement.

(ii) Photovoltaic penetration in urban areas: The solar energy system SENSE, developed through national (Aristotelis-Solar) and EU projects (GEO-CRADLE, e-shape) and applied at high resolution for the Attica region in SMURBS, will be used for assessing Rooftop PV (photovoltaic) systems penetration in urban areas. SENSE combines AI and high performance computing with CAMS solar and aerosol products and PV characteristics, to derive the energy potential of the region. Cadastral archives, inclination and orientation aspects and shadowing effects, will be used to calculate the solar energy availability at a building and neighbourhood level. A pilot study will be performed for the LAU of interest. Results will include assessing the carbon footprint reduction potential and estimating GHG emission abatement. The final product will be a detailed solar database and an interactive interface including: a) solar availability for a choice of PV orientations, available surface areas and PV materials b) a building scale database and interactive map of the LAU, providing the energy potential of the specific area.

(iii) Urban transport emissions and electromobility penetration: To calculate road transport emissions, the COPERT methodology, part of the EMEP/EEA air pollutant emission inventory guidebook, consistent with the 2006 IPCC Guidelines for calculating GHG emissions, will be deployed. Simulating from a single street to a full urban network, and selecting various fleet compositions (electric, LPG, CNG, hybrids), realistic scenarios will be studied to support policy decisions for achieving the desirable GHG emission reduction. The scenarios will be combined with the energy provided/saved by buildings, to infer on the feasibility of electric cars’ recharging. A city scale AQ model (e.g. EPISODE-Citychem) developed in SMURBS, will be used to study the effects of the scenarios in residential- and traffic-related emissions on the intra-urban concentration fields of basic air pollutants. The workflow will be fed with CLMS (Urban Atlas 2012 for proxies) and CAMS (emission inventory and regional reanalysis for boundary conditions) data. It will be assessed with AQ data from in-situ platforms and Sentinel-5p. Given the relation between climate forcing and air pollution emitters, the knowledge gained, not least with respect to black carbon, a critical climate forcer, will aim at developing sustainable and resilient cities, with citizens well-being the priority. The selected LAU is initially in Athens’ northern suburbs (e.g. municipalities of Penteli, Vrillisia, Kifissia), further refined upon co-design with Attica region and the availability of supplementary data.

Decision Support Application (DSA) for urban Climate Change mitigation measures: All the above will be combined into an interactive application comprising a user-friendly UI/UX, with the following features: capacity to use heterogeneous available data as input; visualization of different layers of the three components described above; simulation of policy scenarios and assessment of their effectiveness; support of the implementation of Climate Change policies.

• Produce a robust methodology to calculate, evaluate and scale up urban measures and their outcomes pursuing the National Plan for Energy and Climate targets by 2030, i.e. improving energy efficiency of buildings by 38%; increase in renewables penetration to >35% by 2030 (now 18%); transition of fleets to electric cars 30% share.
• Exploit the application’s results within the frame of the implementation of the Regional Plan for Adaptation to Climate Change of the Region (2022 onwards) providing knowledge and an easy to comprehend DS tool.
• Leverage EO for enhanced, beyond SotA BSM and solar energy potential database.
• Use city-scale modelling to translate GHG abatement scenarios in population exposure/health outcomes.
• Allow a unified exploration of urban GHG abatement measures (>10 scenarios to support carbon neutrality) w.r.t. three key policy sectors in a geographically scalable manner, i.e. from neighbourhood to city-wide.

Ministries of Environ. & Energy, Health, Develop. & Investments, Infrastructure (primary) Administrative authorities (i.e. prefectures, municipalities); Urban planners; Industry (e.g. renewables, building construction); Energy providers/distributors (i.e. PPC/PPCR, IPTO) (secondary).

3, 7, 11, 12, 13. Mortality and AQ indicators 3.4.1, 3.9.1 and 11.6.2 are addressed by offering quantified outcomes of GHG abatement scenarios on key urban pollutants that affect the population exposure to them. The application creates a knowledge base, for policy makers and citizens, to support the increase of the share as it targets two urban features ubiquitous to most citizens, i.e. the home and the car, addressing indicators 7.1.2, 7.2.1, 7.b.1 and 12.a.1 on reliance on clean fuels and renewable energy share. The enhancement of BSM through EO will allow more systematic methodologies to quantify indicator 11.1.1 on informal settlements, geospatially. Indicator 12.c.1 on fossil-fuel subsidies is also addressed as the DSA will quantify outcomes of fossil-fuel reduction measures, needed for monetization and subsidies cost/benefit analysis. The pilot will create an integrated knowledge base for urban sectors towards addressing indicator 13.2.2 on total annual GHG.

Surface and earth radiation budget (solar radiation/energy products), Carbon dioxide, methane and other GHG, Aerosols (BC in particular), Anthropogenic Greenhouse gas fluxes, LC/LU, Albedo.

The pilot will focus on the mapping of risks of droughts, forest fires and forest pests at regional and national scale in Finland. EIFFEL will integrate multiple data sources from GEOSS with national databases into a modelling framework to enhance existing drought and forest fire risk assessments and develop a new mapping tool for the risks of forest pests. The modelling framework will be applied to seasonal weather forecasts and climate projections up to 2050 and beyond. The pilot will bring together regional and national stakeholders to co-interpret the intermediate and final mapping of risks, followed by deliberation of alternative adaptation and mitigation measures. The WSFS model will be utilized to identify drought prone areas and to make seasonal and long-term drought forecasts. The potential improvement of drought forecast capabilities, based on satellite-observed soil moisture and vegetation characteristics as well as new drought indices, will be investigated. Forest fire indices calculated from meteorological variables, operationally in use in Finland to issues fire warnings, have also been applied to climate scenarios. WFSF and fire indices will be applied to construct impact response functions in a probabilistic framework to quantify the risk of drought and forest fire occurrences using similar approaches as in the Europe-wide analysis. Additionally, the benefit of satellite-observed soil moisture and vegetation condition and their integration in the assessment of forest fire risks will be evaluated. Building on previous work, predictive models that integrate in-situ observations from the Finnish moth monitoring scheme, climate variables and satellite-derived information from GEOSS and Copernicus will be used to forecast the occurrence and abundance of forest pest species. To this aim, GEOSS data will be investigated that can describe the phenological development of the host plants, drought effects on vegetation and forest damages. Stakeholders will be engaged in developing scenarios, data interpretation and utilization of the results. This will provide the project with empirical material and the stakeholders with support to their governance and decision-making processes. National scale risk assessments will be integrated as additional web-service based applications to national portals, such as the climate guide and the national portal for water resources information.

• Create an improved drought forecast for Finland and results presented in national portal.
• Develop a co-designed and co-communicated multi-hazard approach focusing on important forest disturbances which have so far been considered separately in Finland.
• Create new applications of moth database, not previously used to study forest pests.
• Present an overview of drought, fire and forest pests risk issues at stake, from environmental to socio-economic perspectives for policy, planning and management purposes.
• Provide recommendations for priority actions to reach an adequate strategy on adaptation and mitigation.
• Offer to Communities of Practices and external Climate Change stakeholders an enhanced capacity and competence for utilization of new/improved data sources and development of policies and management plans.

Ministry of Agriculture and Forestry, Forest Centres and management companies (primary), Regional authority for water resources governance; Rescue Services (secondary)

6, 11, 13, 15. The pilot contributes to SDG 6.4 by making future projections of water scarcity and providing the basis for adequate adaptation and mitigation measures at national and regional level. SYKE is responsible for reporting to Statistics Finland on the progress to the environment-related SDGs. EIFFEL will contribute to the assessment of the level of water stress (SDG indicator 6.4.2). In addition, the pilot supports SDG targets 11.5 (disaster reduction), 13.1 (strengthening of resilience and adaptive capacity) and 15.1 (sustainable use of ecosystems) and 15.2 (sustainable forest management). Forest fire, drought and pests risk maps and their dissemination to stakeholders and the wider public support implementing priorities 1 (“Understanding disaster risk”) and 2 (“Strengthening disaster risk governance to manage disaster risk”) of SFDRR.

Temperature, Precipitation, Snow, Land surface temperature, Soil Moisture, Leaf Area Index, Fire, Evaporation from land, Wind speed, Vapour pressure, Cloudiness, Radiation.