The anticipated expansion of photovoltaic (PV) energy production is likely to have major impacts on ecosystems globally. PV arrays alter the spatiotemporal availability of abiotic drivers, such as light and precipitation, creating discrete microenvironments. Plant responses to PV-induced environmental heterogeneity are increasingly well studied, suggesting spatially explicit patterns of phenology, photosynthesis, productivity, and community composition; however, potential differences in soil microbial processes across these microenvironments are relatively unknown.

To determine how PV arrays influence soil microbial processes, we leveraged an established single-axis tracking photovoltaic array in Colorado, United States, where agriculture and PV energy production are co-located. We conducted our experiment in a portion of the array dominated by a C3 grass (Bromus inermis) to investigate soil physiochemical properties, microbial community structure, and function across microclimates. Soil samples were collected during the growing season from each panel edge (i.e., east & west), beneath panels, between panels, and outside of the array. Soil physiochemical properties generally did not differ across microclimates, although organic matter was highest on the east panel edge, where aboveground productivity is consistently greatest. Soil microbial biomass C & N were highest beneath panels, while substrate induced respiration rates were highest on the east panel edge. Soil microbial community structure differed greatly between microclimates within the array and plots outside the array, with unique bacterial & fungal genera dominating each microclimate (e.g., the fungi, Xylaria, on the east panel edge). Hence, the presence of PV arrays will generate microclimates that alter soil microbial community structure and function in grassland ecosystems, potentially shifting carbon cycling and other ecosystem processes.

How to cite: Siggers, J. A., Sturchio, M., Smith, M., and Knapp, A.: Environmental heterogeneity imposed by photovoltaic array alters grassland soil processes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1130, https://doi.org/10.5194/egusphere-egu25-1130, 2025.

A significant barrier to the planning and installation of large solar power plants is the reduction of arable farmland and the potential despoiling of areas of outstanding natural beauty in the countryside with solar PV panels. Bi-facial Photovoltaics (PV) allow continuing use of land for farming whilst providing an additional income to farmers from royalties associated with solar power production. The ESA GTIF (Green Transition Information Factory) programme initiated three kickstarter projects in 2024 following a successful demonstrator over Austria (gtif.esa.int). The UK-Ireland-France (gtif-uk-ireland-france.net) kickstarter covers 5 different applications (called capabilities) including mapping of PM2.5 at 10m, drought prediction at 10m, urban heat island mapping at 30m and mapping of methane emission plumes at 20m and the mapping of potential areas for the development of solar bi-facial PV (solar bPV) farms over arable and grassland in the 3 aforementioned areas. To select areas of potential development using solar bPV requires knowledge of high resolution spectral albedo, LULC (Land Use Land Cover), topography, and understanding of the solar power equation and Global Horizontal Irradiance (GHI). Spectral albedo is mapped from 10m spectral albedo derived using the ESA HR-Albedo retrieval system [1,2] which was operationalised by the EU Copernicus Sentinel Global Mosaic (https://s2gm.land.copernicus.eu); Global Horizontal Irradiance is taken from both MERRA-2 at 50km and from the UN Solar Atlas at 250m (https://globalsolaratlas.info/map); LULC from the ESA World Cover 2021(https://worldcover2021.esa.int/) and exclusion zones such as Areas of Outstanding Natural Beauty, National Parks and Sites of Special Scientific Interest). Losses due to PV, distance to grid and different seasonal changes are mapped and will be demonstrated for GB and Ireland. The GTIF-UKIF project is now being rolled out across France with the potential to be rolled out across Europe and Africa.

Cited references
[1] Muller, J-P., Song, R., Francis, A.N., Gobron, N., Peng, J., Torbick, N., 2022. Assessment of 10m spectral and broadband surface albedo products from Sentinel-2 and MODIS data. DOI: 10.5194/egusphere-egu22-12092 
[2] Muller J.P., Song R. Brockley D., Whillock M., 2023. Sentinel-2 Global Mosaic HR-Albedo Algorithm Theoretical Basis Document S2GM-UCL-ATBD-v3.1 https://s2gm.land.copernicus.eu/help/documentation

How to cite: Muller, J.-P., Song, R., and Griffiths, P.: Bi-facial PV solar power systems for mixed use of arable and grassland, an evaluation over GB and Ireland taking into account environmental exclusion areas., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18951, https://doi.org/10.5194/egusphere-egu25-18951, 2025.

In Germany, about 23% of the total final energy is consumed for the heat supply (space heating and warm water) of residential buildings (as of 2022) (UBA 2024a, 2024b). Approximately three million older medium-sized multi-family houses with 3 to 12 residential units are responsible for a significant portion of CO₂ emissions in the building sector. To achieve climate goals, the number of renovations would need to increase from the current approximately 4.1 million to 13–16 million buildings by 2045. The dynOpt-San project (BMWK, 2024) supports the achievement of these goals by developing standardized renovation concepts and efficiently integrating innovative photovoltaic-thermal systems in combination with phase-change material storages (PVT-PCM systems). Additionally, a self-learning energy management system with integrated operational monitoring is being developed to optimize and monitor the operation of multi-family houses and districts.

In this contribution, we showcase a prototypical version of such energy management system as well as cloud-based monitoring tools, and we present initial results and lessons learned from first real demonstrator buildings. The predictive energy management relies on a two-level architecture to coordinate energy flows at both the building and district levels with minimal effort. To model the energy system components, we utilize the open-source python framework oemof to formulate mixed-integer linear problems. To facilitate predictive optimization, we incorporate information about future electricity prices, weather forecasts, as well as energy consumption forecasts on residential level, generated with machine learning approaches. The objectives of the energy management system include reducing costs and CO₂ emissions, achieving an optimal self-consumption rate within the buildings, and promoting grid-friendly behavior of the district.

BMWK (2024):  Project dynOpt-San:  Digital unterstützte und modulare Sanierung von Mehrfamilienhäusern in Quartieren mit PVT-PCM-Wärmepumpensystemen und selbstlernendem Energiemanagement, 1/2024 – 12/2026, funded by German Federal Ministry BMWK, funding code 03EN6024A-G, https://www.dynopt-san.de/, last accessed: January 13, 2025

UBA (2024a), Energieverbrauch privater Haushalte, https://www.umweltbundesamt.de/daten/private-haushalte-konsum/wohnen/energieverbrauch-privater-haushalte, last accessed: January 7, 2025

UBA (2024b), Endenergieverbrauch nach Energieträgern und Sektoren, https://www.umweltbundesamt.de/daten/energie/energieverbrauch-nach-energietraegern-sektoren, last accessed: January 7, 2025

How to cite: Wunsch, A., Wallner, S., Hörter, T., and Bernard, T.: Predictive Two-Level Energy Management for the Energetic Optimization of Multi-Family Houses and Districts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5485, https://doi.org/10.5194/egusphere-egu25-5485, 2025.

Multi-energy systems (MESs) integrate a variety of technologies and energy carriers into a unified framework, offering flexible and efficient solutions to the challenges of modern energy systems. These include the urgent need for decarbonization, greater integration of renewable energy sources, and a push for decentralization and energy market independence. However, long-term planning for MESs is becoming increasingly complex in a rapidly changing world, where socio-economic, technological, and climatic shifts can quickly render obsolete solution previously considered optimal. These challenges are particularly acute for vulnerable systems, such as those in small, isolated island communities.

This study focuses on identifying robust future configurations for the energy-water systems of Italian minor islands, which face significant challenges in energy and water supply. The aim is to increase energy independence and promote decarbonization. The analysis explores the integration of desalination plants and rooftop photovoltaic systems as replacements for fossil fuel generators and water transport via tanker ships, together with the expansion of the islands’ water storage capacity. The study incorporates various sources of uncertainty—technological, climatic, and economic—into a multi-objective analysis to evaluate their individual and combined impacts on optimized configurations.

A novel optimization framework is presented, which combines Multi-Objective Evolutionary Algorithms (MOEAs) with the multi-energy system planning model CALLIOPE. This approach identifies trade-off solutions for energy-water system configurations under conflicting objectives. The process is iterated across several scenarios, each defined by a unique combination of uncertainties. Sensitivity indexes and probabilistic analyses are employed to assess variations in performance metrics and the robustness of optimized configurations to each uncertainty source.

The results reveal that the optimal configurations include substantial integration of photovoltaic systems and desalination plants, effectively reducing CO₂ emissions and energy costs. The analysis also highlights the significant role of uncertainty in influencing system performance, particularly the impact of technology-specific parameters like ship tanker emission factors. and desalination plants efficiency. In most scenarios, especially for the island further away from the coast, the replacement installation of desalination plants coupled with renewable technologies proves to be both cost-effective and environmentally sustainable, demonstrating the robustness of the proposed configurations.

This work provides a new decision-making tool for multi-energy system planning, which emphasise the critical role of uncertainty analysis in ensuring resilient planning under fluctuating resource availability and demand. It explores multiple options for the implementation of renewable energy solutions in isolated and vulnerable regions, contributing to a sustainable and resilient energy transition.

How to cite: Tangi, M. and Amaranto, A.: Multi-objective Optimization and Uncertainty Analysis Reveal Resilient Water-Energy System Configurations on Small Islands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10757, https://doi.org/10.5194/egusphere-egu25-10757, 2025.

The transition to a bioeconomy aims to reduce dependence on finite fossil resources, mitigate climate change, and promote sustainable development. Forest biomass plays a key role in the bioeconomy, contributing significantly to bio-based materials and energy production. The transition to the bioeconomy implies the acceleration and upscaling of biomass production and use. However, increasing demand for forest biomass may drive substantial changes in land use and forest management, resulting in environmental impacts, such as, alterations in carbon balances.

Despite the growing emphasis on the bioeconomy, studies quantifying spatially and temporally explicit environmental impacts of increased forest biomass demand are limited. Existing assessments use aggregated and static models, which overlook spatiotemporal variations in land-use, land-management, and environmental outcomes. Addressing this gap is critical to quantify impacts of bio-based systems along value chains and to understand the trade-offs associated with increased woody biomass demand for bio-based products. Accounting for spatial and temporal variation of environmental impacts of the biobased economy requires an integrated modelling approach which includes economic modelling, land-use change and land management change simulation, environmental impact analysis, and approaches to allocate impacts outcomes to bio-based products.

This study aims to quantify the spatial and temporal variation in environmental impacts of bio-based products, driven by land-use and land-management changes resulting from increased forestry biomass feedstock demand in Europe up to 2050. By addressing impacts at both the land level and the bio-based product level, the study provides a comprehensive evaluation of the trade-offs associated with forest biomass sourcing, filling critical gaps in existing assessments. This research adopts an ex-ante and spatiotemporally explicit approach to assess these impacts, focusing on the impacts on carbon balances. More specifically, the approach consists of the following steps:

• Biomass-demand scenarios development using a partial equilibrium forestry economic model: Scenarios of biomass demand for bio-based materials, energy, and other applications. These scenarios, disaggregated by biomass types, form the basis for analysing future land-use changes and linking impacts to bio-based products.
• Spatio-temporal land-use change modelling with the partial equilibrium forestry economic model: Projections of land-use allocation across land use types (e.g., cropland, managed forests, and natural vegetation) while capturing competition among sectors.
• Carbon balance modelling with a forest resource allocation model: Simulation of the impacts of afforestation, deforestation, and forest management practices on carbon emissions and removals under alternative and standard forest management practices.
• Allocating biomass supply to demand with a spatially-explicit techno-economic model: Biomass-demand scenarios outputs are downscaled to a spatially-explicit techno-economic model for bio-based product-level allocation, allocating biomass supply to demand. This step helps making the link of environmental impacts to specific bio-based products.

The results offer an integrated framework to quantify spatial and temporal variations in environmental impacts of bio-based products. By focusing on product-level impacts and spatiotemporal variations, this research supports sustainable forest biomass sourcing strategies, identifies trade-offs, and informs evidence-based policymaking to align bioeconomic growth with long-term environmental sustainability goals.

How to cite: Rondon Villabona, M. A., Duden, A., and van der Hilst, F.: Environmental impacts of increased biomass demand for bio-based products in the bioeconomy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13261, https://doi.org/10.5194/egusphere-egu25-13261, 2025.

Air source heat pumps are one of the most promising solutions for decarbonising domestic heating in the UK. However, the extent of their decarbonisation potential is dependent on a number of factors. This study aims to explore the greenhouse gas reduction capabilities of a  heat pump uptake, in the houses currently using gas boilers for specific local authorities. Three different regions in England and Wales were chosen for this study: South Wales, North East England and South England. Furthermore, within each of these regions, at least one predominantly urban local authority was selected. This is to account for the difference in housing characteristics such as floor area. Therefore, local authorities selected were Powys, Cardiff, Vale of Glamorgan, Newcastle upon Tyne, Northumberland, Reading West Berkshire.

In this study, three different house models, including terraced, semi-detached and detached were created within each local authority for calculating heat demand and % reduction in carbon emissions. The annual heating demand for each local authority was then estimated using modelling techniques, alongside temporal, housing and heat flow data. For households with natural gas boilers, the annual greenhouse gas emissions were calculated using typical boiler efficiency (84%). For households with heat pumps, the annual carbon emissions were computed using regional carbon intensity data.

The heating load for the year 2022 (in GWh) for local authorities was calculated as 210 for West Berkshire, 180 for Reading, 680 for Northumberland, 410 for Newcastle, 170 for Powys, 230 for Vale of Glamorgan, and 450 for Cardiff. Seasonal performance factor was observed in close range of 2.3 for all the local authorities in the same year. Finally, the carbon emissions reduction for replacement of 5% of boilers with heat pumps was noted to vary from 2.2 to 2.6% for all the local authorities.

Furthermore, this study revealed that the Carbon Reduction of a local authority was linearly related to the overall heating demand in that local authority, which is an expected result. When considering the base model conditions, the biggest factors influencing the heating demand between different local authority were the number of houses, the split of houses (between detached, semi-detached and terraced) and the average outside temperature. The local authority which performed best on both metrics mentioned was Northumberland, which had many of the prior factors working in its favour. However, it was also determined that other strategies should be implemented to reduce heating demand, alongside the deployment of heat pumps, such as insulation or demand side reduction.

The preliminary results for this work were obtained as part of the ‘Barocaloric materials for zero carbon heat pumps’ project funded by the Engineering and Physical Sciences Research Council (EP/V042262/1).

How to cite: Mehta, N., Burges, W., Hehar, R., Fender, T., and Radcliffe, J.: Evaluating carbon emissions reduction due to the uptake of heat pumps, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20257, https://doi.org/10.5194/egusphere-egu25-20257, 2025.

Clean hydrogen will play an indispensable role in decarbonizing “hard-to-abate” sectors. However, it is not a “one-size-fits-all” solution because clean hydrogen production currently entails low energy efficiency, high costs, limited supply and risks of leakage.  U.S. policy efforts to date have focused on the supply of clean hydrogen.  However, prioritizing demand applications that maximize environmental and economic benefits is critical. Here we evaluate clean hydrogen’s decarbonization potential in a variety of energy-intensive sectors in the U.S. circa 2035.  We identify oil refining, ammonia production, and steelmaking as “no-regret” sectors, whereas on-road transport and trains fall into the “do-not-use” category. We compare the implications of policymakers GHG mitigation objectives and stakeholder profit maximizing objectives and find that current supply-side subsidies are insufficient to ensure optimal clean hydrogen allocation. Sector-specific demand-side policies are required to align priorities of policymakers and stakeholders to maximize the potential benefits of clean hydrogen.

How to cite: Mauzerall, D., Wu, Y., Atouife, M., Cheng, F., Luo, Q., Perera, A., and Jenkins, J.: Prioritizing demand-side applications for clean hydrogen to maximize environmental and economic benefits, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13911, https://doi.org/10.5194/egusphere-egu25-13911, 2025.

Background: The need to address the dual challenges of climate change and biodiversity loss is pressing and requires collective efforts in both land-use and energy sectors. However, the interactive impacts between mitigation and biodiversity conservation measures, especially the indirect impacts through the energy-land nexus, have not been comprehensively investigated. The question arises as to whether and what levels of synergies or trade-offs exist between mitigation and biodiversity targets, and what are the implications on energy system decarbonization pathways and corresponding mitigation costs.

Methodology: By applying and comparing two modelling frameworks that link integrated assessment models (AIM, MESSAGEix-GLOBIOM) and biodiversity models (Figure 1), we explore the system-wide synergies and trade-offs between the ambitious climate and biodiversity targets included in the Paris Agreement and Kunming-Montreal Global Biodiversity Framework (KMGBF). Four forward-looking policy scenarios with different mitigation and biodiversity conservation ambitions are simulated for the period 2010-2070 to quantify the land-use dynamics, greenhouse gas emissions, biodiversity indicators, as well as energy transformation pathways under different policy targets. Additional sensitivity analysis and decomposition analysis allow us to explore the implications of alternative mitigation pathways on the key findings, and to disentangle the effects of individual policy measures within the mitigation and biodiversity portfolios.

Results: Scenario results show that despite biodiversity synergies from stringent mitigation measures for the 1.5°C target, area-based biodiversity conservation measures are not enough to revert the declining trends of biodiversity. Biodiversity losses can be halted or decelerated with combined mitigation and biodiversity efforts, but until 2070 global biodiversity cannot restore its 2010 levels. On the other hand, due to the energy-land nexus, deploying biodiversity conservation measures can double the carbon price in line with the 1.5°C target and increase global gross domestic product loss by 0.7% by 2070. However, the availability of alternative negative emission technologies and increased pasture production efficiency can act as enablers to reduce the additional costs to achieve 1.5°C-mitigation induced by the biodiversity target. Besides, the large land demand for co-achieving stringent mitigation and biodiversity targets can increase the global average price of agricultural products by 35-53% in 2070 and reduce food consumption. Avoiding the potential negative implications on food security would entail substantial food system transformation efforts. Our results indicate that the challenges of co-achieving the 1.5°C and KMGBF targets can be amplified via cross-sectoral impacts on the energy system and be greater than previously thought. This calls for more careful policy design to simultaneously address the two targets while limiting the trade-offs with food security or the economic feasibility of decarbonization.

Figure 1. Overview of research design

How to cite: Wu, Y., Frank, S., Tsuchiya, K., Leclère, D., Fricko, O., Fujimori, S., Gusti, M., Hasegawa, T., Lessa Derci Augustynczik, A., Krisztin, T., Rouet-Pollakis, S., Wögerer, M., van Meijl, H., van Zeist, W.-J., Hirata, A., Krey, V., Ohashi, H., Takahashi, K., Riahi, K., and Havlík, P.: Challenges and enablers of co-achieving ambitious global climate and biodiversity targets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14971, https://doi.org/10.5194/egusphere-egu25-14971, 2025.

World and Europe’s climate emergency and renewable electricity production are a central topic for present and future energy security and carbon emission strategies, requiring strong efforts to governments and industries for their achieving.

Diversification in the mix of sources providing electricity is getting more crucial day after day. Among the many possibilities, offshore generation has seen an outstanding increase in the last twenty years, in particular in those areas where wind, solar and wave data performance enables to reach high capacity factors and where landuse is a sensitive topic for protected onshore areas and biodiversity, especially for the islands.

In particular, floating generation in the last few years has dragged the attention of investors and governments for its potential and positive implications, from technical, economic and employment perspectives. Floating Offshore Wind Farms (FOWF), after years of studies and prototypes, are now an actual feasibile source, showing tens of projects under development and approval phases in the Mediterranean areas and in the Nordic regions, showing their great potential. Furthermore, the coupling of these technologies with other energy generation forms, like solar photovoltaic and wave kinds, and storages, as electrochemical and hydrogen ones, could contribute to reach a more complete, stable and economically efficient system.

In this context, Iceland’s energy systems relies on about 70% out of its total electricity generation from hydroelectric plants, followed by almost 30% from geothermal source, and less than 1% from wind, solar and fossil-fuel production. Moreover, it is the European country with the highest share of renewables in final energy consumption, scoring a value around 82%. Nevertheless, grid shortages, blackouts, houses not connected to the national grid, peaks of demand from energy-intensive factories, unpredicable events, force the use of carbon-based fuels to cope with lacks of electricity, mainly diesel ones. This requires an improvement in the variety of sources of generation and storage, aiming at a 100% renewable scenario. Focus of this work is to analyze the Icelandic energy mix and investigate the possibility of implementation of offshore electricity generation and storages, and the expected effects on this energy self-sufficient island. Furthermore, the study considers the environmental impacts and the grade of public acceptance towards these technologies. Eventually, a comparison with the Mediterranea island of Malta provides more completeness to the research work.

How to cite: Cappellari, M., Lorenzoni, A., Finger, D. C., and Guðlaugsson, B.: Offshore electricity generation potential and its integration into the energy system of an energy self-sufficient island: a case study of Iceland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16495, https://doi.org/10.5194/egusphere-egu25-16495, 2025.