AFRY (Austria)

Enhanced weathering is under active consideration as a permanent carbon dioxide removal pathway, but its agronomic and biogeochemical outcomes remain insufficiently constrained under field conditions. We report a two-year field trial with four treatments: (i) basalt, (ii) control, (iii) manure, and (iv) basalt + manure, conducted on grassland in the Austrian Alps.Soil water was sampled continuously at 40 cm depth using suction plates to capture high‑resolution dynamics in pH, alkalinity, and dissolved ion composition. Soil measurements were conducted at the start and end of the experiment. Nutritional quality of forage was analyzed after each cut. The aim of the experiment was to quantify CO2 drawdown from weathering and potential agronomic benefits in the context of typical regional farming practice.Basalt addition did not lead to a detectable increase in alkalinity in soil water over the study period, highlighting the slow dissolution rates under temperate field conditions. However, basalt application resulted in a measurable increase in biomass production compared to the control, suggesting potential agronomic co-benefits.We present further observed geochemical and biological responses and discuss implications for monitoring, verification, and the design of future trials.

Bedrock mapping is essential for understanding seismic amplification, particularly in sediment-filled valleys or basins. However, this can be hard in urban environments. We conducted a geophysical investigation of the sediment-filled Bolzano basin in Northern Italy, where three valleys converge. This study uses low-impact, single-station geophysical methods suitable for urban areas to address the challenges of mapping in such environments. A dataset of 574 microtremor and gravity measurements, along with three seismic reflection lines, allows for the inference of the basin’s deep bedrock morphology, even without direct stratigraphic data. The dataset facilitates a detailed analysis of the spatial patterns of resonance frequencies and amplitudes, revealing 1D and 2D characteristics of the resonances. Notably, 2D resonances predominate along the Adige valley, i.e., the deepest part of the basin with depths up to 900 m. These 2D resonances, which cannot be interpreted through simple 1D frequency-depth relationships, are better understood by integrating gravity data to develop a depth model. The study identifies resonance frequencies ranging from 0.27 to over 3 Hz in Bolzano, affecting different building types during earthquakes. Maximum resonance amplitudes occur at lower frequencies, specifically at 2D resonance sites, therefore primarily impacting high structures. The 2D resonances are directional, with the most significant amplification occurring longitudinally along the valley axes. The resulting 3D bedrock model aids in seismic site response modeling, hydrogeological studies, and geothermal exploration and provides insights into the geological history of the basin, highlighting the role of the Adige Valley as a major drainage pathway.

Abstract In 2004, ÖBB‐Infrastruktur AG started the first studies for the construction of a pumped‐storage hydro power plant between the two largest reservoirs of the existing Stubach Valley power plant group in Salzburg's Pinzgau region. Two reversible pump‐turbine units including a full converter with a total capacity of 170 MW and a maximum flow of 80 m3/s are planned. The construction of the 335 million. euro project started in 2020 and will be completed by autumn 2025. In addition to a 50,000 m3 cavern, an 11.5 km tunnel system including the access tunnels and the power water ways have been built. Most of the 11.5 km tunnel system is situated in stable gneiss. A greater challenge is the construction of the two inlet and outlet structures in the high mountain region during the winter season, when the lakes can be held on the lowest reservoir level. Since the remaining construction work is also carried out at an altitude of 1500 to 2250 m above sea level in alpine terrain, the construction company has been facing recurring problems such as snow, cold, wind, mudslides and the associated logistical difficulties. Despite these challenges, the excavation work was completed in summer 2022. The main focus is currently placed on the concrete works in the cavern, which is scheduled to be completed in autumn 2023. This will be followed by the installation of mechanical and electrical equipment as well as the control systems.

Abstract Die Bauindustrie zählt zu den einflussreichsten Branchen hinsichtlich des anthropogenen Ressourcen‐ und Energieverbrauchs sowie des anfallenden Feststoffmülls (≥ 38 %). Die Entwicklung und Verwendung von Bauweisen und Baustoffen mit minimalem Umwelteinfluss über den gesamten Lebenszyklus ist somit von höchster Relevanz. Um den ökologischen Einfluss von Bauweisen und Baustoffen quantifizieren zu können, muss eine faktenbasierte Ökobilanzierung durchgeführt werden. Gegenwärtig ist dies meist nicht der Fall und objektive Vergleiche fehlen. Im Hochbau haben besonders Deckensysteme großen Einfluss auf die Gesamtbilanz der Tragstruktur. Deswegen widmet sich dieser Beitrag dem ökologischen Vergleich von unterschiedlichen Deckensystemen im Hochbau in Anlehnung an die EN 15804 und die EN 15978. Die Systemgrenzen sind mit den Lebenszyklusphasen Cradle‐to‐Gate und Cradle‐to‐Grave festgelegt worden. Insgesamt werden neun unterschiedliche Deckenarten aus Holz, Stahl, Beton wie auch deren Kombinationen im Rahmen unterschiedlicher statischer Systeme betrachtet. Alle Systeme wurden nach gängiger Ingenieurpraxis für die gegebenen Randbedingungen nach den aktuell gültigen Normen (ÖNORM, Eurocode) möglichst effizient dimensioniert. Die Ergebnisse zeigen, dass mit allen betrachteten Materialien ökologisch konkurrenzfähige Systeme umgesetzt werden können. Zentral sind jeweils ein Einsatz der Materialien entsprechend deren Eigenschaften und die Optimierung der Struktur sowie des Tragsystems.

<p>Production of a large ensemble of climate simulations suitable for impact assessments is an attempt to enhance our knowledge about the associated uncertainties in future projections. However, the actual quantification of the change in the climate and its impact relies on the ensemble of models selected, particularly given the wide availability of climatic simulations from various initiatives, i.e. CMIP5, CORDEX.</p><p>Here, we hypothesize that historical streamflow observations contain valuable information to investigate practices for the selection of climate model ensembles. We apply eight selection methods (based on democracy, diversity of GCM, diversity of RCM, maximum information minimum redundancy, best performing hindcasted climate depiction, best performing hydrological model, simple climate model averaging and reliable ensemble average) to subset an ensemble available from 16 combinations of Euro-CORDEX GCM-RCM by comparing observed to simulated streamflow shift of the Danube from a reference period (1960–1989) to an evaluation period (1990–2014). Simulations are carried out with the well-performing Upper Danube COSERO hydrological model, spanning a calibration and evaluation period of more than 100 years. Comparison against no selection shows that an informed selection of ensemble members improves the quantification of climate change impacts where methods that maintain the diversity and information content of the full ensemble are favourable. In addition, the method followed allows the assessment which individual climate models perform best, where only three of 16 models were able to correctly reproduce the direction of streamflow change in each season.</p><p>Prior to carrying out climate impact assessments, we propose splitting the long-term historical data and using it to test climate model performance, sub-selection methods, and their agreement in reproducing the indicator of interest, which further provide the expectable benchmark of near- and far-future impact assessments. This test can further be applied in multi-basin experiments to obtain a better understanding of uncertainty propagation and uncertainty reduction in hydrological impact studies.</p>

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors—a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90‐m digital‐elevation model by using the GRASS‐GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land‐use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1–93.2 and 0.61–0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can have consistently high evaluation scores while mapped predictions differ significantly and are highly contingent on the underlying subcatchment size. We encourage building freshwater SDMs across multiple catchment sizes, to assess model variability and uncertainties in model outcomes emerging from the MAUP.