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The development of geothermal energy is below the European National Renewable Energy Action Plans' anticipated trajectory. For deep geothermal energy projects in particular, multiple sources of uncertainty in combination with high upfront investment costs result in a major investment risk, hampering the mobilization of required capital (Compernolle et al., 2019). The uncertainty sources include market uncertainty, uncertainty regarding new technologies and uncertainty inherent to working with subsurface data. The objectives of the DESIGNATE project for deep geothermal systems in Belgium, including applications in abandoned mines are two folds. First, to create tools for integrated forecasts under uncertainty and second to set-up a methodological framework for territorial Life Cycle Analysis (LCA) considering surface and subsurface impacts. To do so, analytical reservoir models will be developed to assess the effect of uncertainties about geological data and concepts on the performance and impact of the geothermal applications. These will be coupled with a techno-economic analysis in combination with a territorial, environmental life cycle analysis. To evaluate the impact of different policy measures, the techno-economic analysis consists of a Monte Carlo simulation model that integrates both market and geological uncertainties and a project developers' option to wait or abandon the geothermal project development at different steps in the development of the project (Welkenhuysen et al., this conference). As a preliminary step, the influence of the rollout time of a heat network on the risk and on the profitability is investigated. At the start often only a part of the district heating network is in place at the time of commissioning and the geothermal plant operates at much lower capacity. Part of the capacity is foreseen for district heating networks linked to residential districts expected to be built or renovated in the near future. In this research, the change in income of a project considering a stepwise rollout of a district heating network compared to a full load from the start, in combination with a reduced maximum capacity of the geothermal plant compared to the expected output is calculated. This is done with a simplified spreadsheet techno-economic model, limiting variability to the rollout scenarios. For the calculation, data provided by the project developer HITA of the Turnhout NW geothermal project is used. In the next section the four cases used to evaluate the risk and profitability linked to the changes in the rollout time of a heat network are described. In the first case, the base case, the production plant is assumed to work at full capacity once the construction of the geothermal plant is achieved. Full capacity means that the production plant will be working at 100% during the heating season. Additional production for cooling or for heat storage in summertime are not taken into account. The second case considers that the maximum production capacity is 20% lower than in the first case due to lower-than-expected reservoir temperature or flow rate. In the third case, the full capacity is equal to the one of the base case but will be reached in three steps, simulating a growing demand by adding new district heating networks. The demand is expressed as a percentage of the expected maximum production capacity of the geothermal plant. At the start of production, the geothermal plant runs at 50%. After 5 years this is increased to 75% and after 10 years full capacity is reached. The fourth and last case is similar to the third case, with a stepwise increase of the demand, but the maximum production capacity is, as in second case, 20% lower. Because the demand is lower than the total capacity in the first 10 years, the production plant will however be able to supply the required energy. Only after 10 years when the demand rises to the expected maximum production capacity, only 80% of the required energy can be delivered without additional investments. As such, the income of the project will be the same the first 10 years compared to the third case. In a best-case scenario, demand and rollout of a district heating network will be fast and the production plant will run at full capacity during the heating season from the start (case 1). This is however unlikely and assuming this to be the base case will result in many projects not reaching predetermined targets, as the income of the project will be lower during the first years of production. In this respect, the third case or a similar scenario is a better option to use as a base case. This will put more stringent conditions on the expected output parameters of the production well to ensure an economic viable project, and hence provide a more realistic outlook. When using case 3 as the base case this also has the complementary benefit of reducing the risk related to the maximum production capacity. If the real maximum production capacity is lower than expected, the reduction of income will be lower than the decrease in the maximum production capacity. In other words, a reduction of 20% of the maximum production capacity will not lead to a reduction of 20% of the income, but will be between 0 and 20%, depending on the interest rate and on the time frame to reach full capacity. Acknowledgments This research is carried out under the DESIGNATE project, which receives funding from the BELSPO BRAIN-be 2.0 research programme under contract nr B2/191/P1/DESIGNATE. HITA kindly provided input for the development for this case study. References Compernolle, T., Welkenhuysen, K., Petitclerc, E., Maes, D. & Piessens, K., 2019. The impact of policy measures on geothermal energy investments. Energy Economics, 84, 104524. https://doi.org/10.1016/j.eneco.2019.104524 Welkenhuysen, K., Compernolle, T., Kaufmann, O., Laenen, B., Meyvis, B., Piessens, K., Gousis, S., Dupont, N., Harcouet-Menou, V. & Pogacnik, J., this conference. Decision support under uncertainty for geothermal applications: case selection and concept development.

In order to meet climate goals and provide energy security, geothermal energy can play an important part in Belgium’s energy production portfolio. The current implementation of geothermal energy in Belgium is very limited, making accurate forecasts about the economic potential difficult. In the DESIGNATE project, tools and workflows are developed to investigate the potential of deep geothermal energy and geothermal applications in abandoned mines in Belgium, considering uncertainties at reservoir, technology and economic level. The goal of this project is to make forecasts about the role of these geothermal applications in the Belgian energy portfolio and provide support for strategic planning of subsurface activities by: explicitly considering uncertainties in modelling non-standard geothermal resources; creating tools for integrated forecasts under uncertainty; setting up a methodological framework for territorial LCAs considering surface and subsurface impacts; and analysing interferences and their consequences for geothermal energy deployment in Belgium. These workflows will be developed for and applied to five real and theoretical case studies throughout Belgium, in different geological settings. A first case is the Balmatt deep geothermal project, a deep geothermal research project led by VITO in Mol, of which two wells are operational as a doublet. To allow for a realistic economic assessment, this case takes the basic structure and development of the Balmatt project, but as if it would be a commercial doublet project at the same location and in the same Carboniferous strata. A second case is a deep doublet system in NW Turnhout, currently under development by the geothermal development company HITA. This project allows supplying heat to part of the city of Turnhout’s residential and tertiary sector’s buildings. A third case involves the application of a novel single-well technology for geothermal heat extraction To compensate for the unknowns of the new technology, a more uniform and predictable reservoir type was chosen for this application: the Cretaceous deposits in the Campine Basin. The fourth case will investigate a new deep geothermal doublet in the Mons Basin, the Deep Mons project. At Porte de Nimy, close to a hospital, two wells of about 2.5km depth are planned to reach the Carboniferous. A fifth and last case is the application of an open geothermal system in former coal mine galleries. Preliminary, the Péronnes-lez-Binche coal mines were selected, as the structural separation of the galleries in a shallower colder part and a deeper warmer part allows for several applications such as seasonal use of heat and cold. Because a portfolio of methods will be developed to analyse different aspects of these projects, a solid common base is needed across all methods. These “project concepts” start from a decision tree, listing the major decision steps for each case, such as seismic exploration, well drilling, and the potential use cases. Additionally, options for waiting and abandoning the project are also included. Other data such as duration and cost are tied to this framework. Figure 1 shows a flow chart of such a decision tree for the Balmatt case. Because of their flexibility and speed, analytical solutions will be developed from numerical models for simulating the reservoir behavior and predict the evolution of temperature and pressure. The project uses an innovative approach by stepping away from simple well designs and homogeneous reservoirs, and introducing uncertainty. These analytical models will provide direct input for a geological techno-economic assessment (G-TEA), a territorial life cycle assessment (LCA), and a new version of the PSS simulator. Project development is simulated considering the analytical reservoir models as resource, the technical and economic aspects of project development, heat transport, energy demand, environmental impact, energy market and the policy framework. Acknowledgements This research is carried out under the DESIGNATE project, which receives funding from the BELSPO BRAIN-be 2.0 research programme under contract nr B2/191/P1/DESIGNATE.

In order to reach greenhouse gas emission reduction targets, atmospheric CO2 emissions from all industrial sectors need to be avoided. Globally, the cement production industry emits 2.4 Gt CO2 per year, or 7% of all CO2 emissions (IEA). While about a third of this could be reduced by using renewable energy sources, the remainder are process emissions from the calcination process. Lime or CaO is produced by heating limestone (CaCO3), emitting CO2. The Australian company Calix has developed a direct separation technology for capturing these process emissions; a pilot-scale installation is operational at the Lixhe cement plant in Belgium (Figure 1). The EU H2020-funded LEILAC2 project (Low Emission Intensity Lime and Cement 2: Demonstration Scale) upscaling and integrating a novel type of carbon capture technology. This technology aims to capture, at low cost, unavoidable process emissions from cement and lime plant. This large-scale capture plant will be installed at the Heidelberg Cement’s plant in Hannover, Germany, capturing 20% of a typical cement plant’s CO2 emission. Apart from the physical installation and operation of the capture unit, a business case will be developed for the downstream components of transport, use and geological storage for the captured CO2. In order to develop a business case, a very large number of options, combinations and scenarios for each these components need to be evaluated, taking into account the intricacies of for example dealing with geological data in economic calculations. The PSS suite of geo-techno-economic simulators has been developed by the Geological Survey of Belgium, specifically for creating forecasts on the deployment of CO2 capture and geological storage (CCS) technologies (Welkenhuysen et al., 2013). In PSS, investment decisions for the full CCS chain are simulated as a forecast in a non-deterministic way, considering uncertainty and flexibility. Especially for matching storage, these elements are essential. While capture in this demonstration project is a given, several scenarios will be analyzed: the current demo-scale, full-scale capture, and CO2-network integration. Due to its location, several CO2 transport options can be considered at the Hannover plant: from low-volume truck, railway or barge transport, up to ships and pipelines. Special attention is given to possible connections with ongoing and planned initiatives for infrastructure and hub development such as the Porthos project in the port of Rotterdam or the Northern Lights project offshore Norway. In the wider area around the capture location, North-Western Europe including the North Sea offshore area, there are many potential storage options available. Offshore storage options will be the primary targets for assessment, with many (nearly) depleted hydrocarbon fields and saline aquifers that are present in the southern North Sea. Storage aspects are treated as stochastic parameters, with for example storage capacity and injectivity of the reservoirs represented by probability density functions. In order to compare storage options, the degree of knowledge, uncertainty and economic and practical development feasibility of such a storage location needs to be assessed. An analysis of such storage classification systems is created by Tovar et al. (this conference). With the above-mentioned PSS method and CCS project development options, source-sink matching is performed to create forecasts on project and network development. Results will provide insight in the probability of preferred storage option development for steering exploration and development efforts, preferred transport modes and routes, the optimal timing of investments, and the influence of market parameters, such as the ETS price of CO2 emissions. Acknowledgments This research is carried out under the LEILAC2 project, which receives funding by the European Union’s Horizon 2020 research and innovation program under grant agreement number 884170. The LEILAC2 consortium consists of: Calix Europe SARL, HeidelbergCement AG, Ingenieurbüro Kühlerbau Neustad GmbH (IKN), Centre for Research and Technology Hellas (CERTH), Bundesanstalt für Geowissenschaften und Rohstoffe (BGR), Politecnico di Milano (POLIMI), Geological Survey of Belgium (RBINS-GSB), ENGIE Laborelec, Port of Rotterdam, Calix Limited, CIMPOR-Indústria de Cimentos SA and Lhoist Recherche et Development SA. References IEA, 2020. Energy Technology Perspectives 2020. https://www.iea.org/reports/energy-technology-perspectives-2020 Tovar, A., Piessens, K. & Welkenhuysen, K., this conference. Ranking CO2 storage capacities and identifying their technical, economic and regulatory constraints: A review of methods and screening criteria. Welkenhuysen K., Ramírez A., Swennen R. & Piessens K., 2013. Strategy for ranking potential CO2 storage reservoirs: A case study for Belgium. International Journal of Greenhouse Gas Control, 17, 431-449. http://dx.doi.org/10.1016/j.ijggc.2013.05.025

Numerous naturally CO2-rich mineral water springs, locally called ‘pouhons’, occur in southeast Belgium. These are oversaturated in CO2 (up to 4g/L) and have attracted economic, touristic and scientific interest for centuries. Water sources occur within Palaeozoic rocks of the Rhenohercynian deformation zone, a fold-and-thrust belt at the north of the Variscan orogeny in central Europe. Many occurrences are concentrated in the Cambro-Ordivician Stavelot-Venn massif. A widely accepted model, supported by H-O isotopic signatures, is that sources are primarily fed by meteoric water, which infiltrates through Quaternary sediments, then reaching Lower Palaeozoic rocks to meet the mineral and CO2 source at unknown depth. Different ideas for the origin of CO2 are grouped in two main hypotheses: a) generation by dissolution of carbonate rocks and/or nodules, and b) volcanic degassing related to the neighbouring Eifel area in Germany. These well-known interpretations are mostly based on geochemical studies that are dispersed and poorly accessible. These have now been gathered in the light of new sampling campaigns, allowing to revisit and compare the views of earlier authors. We also for the first time include the geotectonic setting of the region. Carbonate rocks in the region are represented by Lower Carboniferous and Middle Devonian limestones. Depending on the assumed structural evolution for this foreland fold-an-thrust belt, these may occur at >2 km depth below the Stavelot-Venn massif. Carbonate nodules are present in other formations, but their limited volume is unlikely to originate high and long-lived quantities of CO2. Springs enriched in CO2 are also common in the volcanic Eifel area, with presence of mantle CO2 well established. The supposed extension of the Eifel plume would allow for a magmatic CO2 source below the Stavelot-Venn massif from degassing of the plume (>50 km deep), or of an unknown shallower magmatic reservoir. Available stable and noble isotopes point to a mixed carbonate-magmatic origin. If considering the presence of limestones at depth, meteoric water should infiltrate at least 2 km. Known deep-rooted faults are thought to act as preferential groundwater pathways. However, such deep circulation is incompatible with the low temperatures of springs (~10oC), unless the ascent is slow enough to fully dissipate heat prior to resurfacing. Another possibility is that meteoric water does not infiltrate as deep, with CO2 being transported upwards to meet groundwaters at shallower depths. The presence of CO2 surface leaks, locally called ‘mofettes’, could be evidence of such relatively shallow availability of CO2. The evaluation of existing hypotheses highlights complex subsurface processes that involve water infiltration, CO2 assimilation and water resurfacing in southeast Belgium (Figure 1). As such, this review is an important guide for the newly launched sampling campaigns. Acknowledgements This work is part of two research projects: GeoConnect³d-GeoERA that has received funding by the European Union’s Horizon 2020 research and innovation programme under grant agreement number 731166, and ROSEAU project, as part of the Walloon program «Doctorat en Entreprise», co-funded by the SPW Région Wallonne of Belgium and the company Bru-Chevron S.A. (Spadel group), under grant number 7984. References Barros, R., Defourny, A., Collignon, A., Jobé, P., Dassargues, A., Piessens, K. & Welkenhuysen, K., 2021. A review of the geology and origin of CO2 in mineral water springs in east Belgium. Geologica Belgica, 24 (1-2), p.17-31. https://doi.org/10.20341/gb.2020.023

PSInSAR analyses across Belgium using ERS 1-2, ENVISAT, TerraSAR-X and Sentinel 1 allowed to follow several ground movements areas during the last three decades. Several areas of regional importance are affected by land subsidence processes that have been observed during this period (i.e. the alluvial plain of the Schelde estuary in Antwerpen, a large area in the West Flanders province and one around Merchtem area). Other land subsidence areas associated to old coal mining both in Flanders (Campine basin) and Wallonia (Hainaut and Liège province) are affected by progressive uplifting conditions linked to the mining aquifer piezometric rebound. It is extremely important to follow the spatio-temporal behavior of these phenomena to forecast their influences and their effects on the urban developments.

A land subsidence affecting several towns at the joining limits of the Belgian Provinces of East Flanders, Antwerp and Flemish Brabant is followed during the last three decades. ERS 1–2, ENVISAT, TerraSAR-X and Sentinel-1A satellites SAR scenes were processed from 1992 till October 2020 to map the land subsidence evolution. The subsidence corresponds to a surface area of 220 km 2 during the ERS 1/2 time interval distributed over three distinct subsidence bowls. During the ENVISAT and TerraSAR-X time interval, only one residual subsidence bowl was mapped affecting a surface area of about 70 km 2 . Several towns (Londerzeel and Steenhuffel) remained in the center of the subsidence bowl. The annual average negative velocity values range between −5.99 and −0.5 mm/year. During the Sentinel-1A period, the subsidence bowl has lost half of its surface reaching 36 km 2 . The LOS velocity values have also decreased during the period 2016–2020.