Austrian Case Study Research Articles

Creating an indicator system for the United Nations Sustainable Development Goals in communities and municipalities: Application and analysis in an Austrian case study

Sustainability indicators should implement the United Nations Sustainable Development Goals (UN SDGs). Indicators in literature often consider large sets of actions and are thus complex in application. Therefore, this work derives energy- and resource-related SDG indicators for communities and municipalities with low complexity. Moreover, this work analyzes three different policy paths to promote SDG contribution. The policy paths consider SDG target settings and two different incentive schemes in the form of penalties and investment subsidies. The indicators and policy actions are applied in two case studies for communities and municipalities in Austria. Therefore, an optimization model that considers the case study setups, SDG targets and policy actions is developed. The modeling approach shows applicability and positive contribution to sustainable development by indicators. Moreover, the results show the applicability of the three policy paths. Implementing the target-setting path directly leads to the desired SDG targets and provides insights into the costs for target achievement. The incentive scheme paths also lead to selected targets, but they require a cost assessment of the provided incentive schemes. A combination of both incentive schemes leads to the lowest costs. However, policymakers should implement a workflow that considers all three policy paths for policy action settings.

Network analysis of pig movement data as an epidemiological tool: an Austrian case study

Animal movements represent a major risk for the spread of infectious diseases in the domestic swine population. In this study, we adopted methods from social network analysis to explore pig trades in Austria. We used a dataset of daily records of swine movements covering the period 2015–2021. We analyzed the topology of the network and its structural changes over time, including seasonal and long-term variations in the pig production activities. Finally, we studied the temporal dynamics of the network community structure. Our findings show that the Austrian pig production was dominated by small-sized farms while spatial farm density was heterogeneous. The network exhibited a scale-free topology but was very sparse, suggesting a moderate impact of infectious disease outbreaks. However, two regions (Upper Austria and Styria) may present a higher structural vulnerability. The network also showed very high assortativity between holdings from the same federal state. Dynamic community detection revealed a stable behavior of the clusters. Yet trade communities did not correspond to sub-national administrative divisions and may be an alternative zoning approach to managing infectious diseases. Knowledge about the topology, contact patterns, and temporal dynamics of the pig trade network can support optimized risk-based disease control and surveillance strategies.

Bridging Disciplinary Divides through Computational Social Sciences and Transdisciplinarity in Tourism Education in Higher Educational Institutions: An Austrian Case Study

Grand societal issues such as climate change and technological disruption challenge all industry sectors, including tourism. To cope with these challenges, new sustainable business models that not only rely on data-driven technologies but also require new ways of collaboration beyond disciplines and sectors by facilitating the overall conception of transdisciplinarity are essential. One potential way to combine all these requirements is computational social sciences. As a discipline-crossing approach, it should be anchored within tourism education to train the future workforce and experts necessary to realize the needed transformation. Thus, this study explores the status quo of tourism curricula in higher educational institutions in Austria through the lens of computational social sciences. In doing so, a set of core modules of computational social sciences content was developed as an analytical framework. The results show that there is still a significant gap between the demands of the tourism industry and the offered educational programs in Austria. The article concludes with insights on how to close the existing gap and some suggestions for possible foundational steps to support the transformation.

Competences That Foster Digital Transformation of Public Administrations: An Austrian Case Study

Digitalisation has changed society, and, as a result, public administrations are required to undergo significant changes to satisfy emergent societal needs. These changes impact all areas of the public sector, including the development and provision of digital services, the design of processes, and the development of policy. To implement the digital strategies and transformation requirements, public administrations must rethink the competences that their workforce as well as the external stakeholders may need. To understand how one nation implements its digital strategy and upskills its civil servants, we conducted a qualitative analysis of 41 Austrian expert interviews. The research shows that different stakeholders require a variety of competences to participate in the digital transformation of its processes and services. The results demonstrate the high level of diversity and the need for a holistic approach to tackle the complexity of the digital public sector, where leadership plays the most important role. In addition, the study shows that the use of competence frameworks for measurement and monitoring needs to be adapted to the local context.

Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)

Abstract. The assessment of uncertainties in landslide susceptibility modelling in a changing environment is an important, yet often neglected, task. In an Austrian case study, we investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In June 2009, extreme events of heavy thunderstorms occurred in the Styrian Basin, triggering thousands of landslides. Using a storyline approach, we discovered a generally lower landslide susceptibility for the pre-industrial climate, while for the future climate (2071–2100) a potential increase of 35 % in highly susceptible areas (storyline of much heavier rain) may be compensated for by much drier soils (−45 % areas highly susceptible to landsliding). However, the estimated uncertainties in predictions were generally high. While uncertainties related to within-event internal climate model variability were substantially lower than parametric uncertainties in the landslide susceptibility model (ratio of around 0.25), parametric uncertainties were of the same order as the climate scenario uncertainty for the higher warming levels (+3 and +4 K). We suggest that in future uncertainty assessments, an improved availability of event-based landslide inventories and high-resolution soil and precipitation data will help to reduce parametric uncertainties in landslide susceptibility models used to assess the impacts of climate change on landslide hazard and risk.

The Usage of GIS Tools on Vintage Aerogeophysical Data for Simple and Fast Processing with a Focus on Fault Interpretation: An Austrian Case Study

The reuse of vintage datasets which were acquired in the 20th century can pose challenges for modern geophysical modeling due to missing detailed preprocessing information, significant uncertainties, or lack of precise tracking, etc. Nevertheless, they are often the only available datasets in a target region. We explore here the potential of such vintage airborne geophysical datasets (magnetics, AEM, radiometrics) to detect the location and dip direction of geological faults, using a non-modeling interpretation approach based on multiple GIS tools. We apply our approach in a geologically well-known region where four different types of faults are mapped. The applicability of the tools used in this study depend on the geological setting of each fault and is evaluated based on the comparison with geological and—where available—with modeling data. In general, the GIS tools, especially used on a combination of datasets, show reliable results concerning the location and strike of faults, and even seem to be able to predict the dip direction of a fault.

Modelling soil emissions and precision agriculture in fertilization life cycle assessment - A case study of wheat production in Austria

The environmental assessment of using optical crop sensors for variable rate nitrogen application (VRNA) has been limited by the lack of a robust method to quantify site- and technology-specific impacts. This study aimed to (1) present a comparative life cycle assessment (LCA) of a conventional winter wheat production system with and without using a crop sensor for VRNA applied to an Austrian case study. Special emphasis was placed on simulating site-specific field emissions with the DeNitrification-DeComposition (DNDC) biogeochemical soil model; (2) assess the environmental impacts of only the fertilization process; and (3) compare soil emissions simulated by the DNDC with soil emissions coming from a benchmark ecoinvent wheat production process. Three nitrogen fertilization schemes – one conventional and two VRNA – were modeled. Two functional units were used – 1 ha of cultivated winter wheat and 1 kg of winter wheat produced. The system boundary includes tillage, seeding, plant protection, nitrogen fertilization, and harvesting processes. Information communication technologies (ICT) – manufacturing of the sensor, internet and computer manufacturing and usage – were also included within the boundary. Local and global environmental impacts attributed to nitrogen emissions due to fertilization were evaluated in this LCA, including climate change (CC), fine particulate matter formation (FPMF), freshwater eutrophication (FE), freshwater ecotoxicity (FET), terrestrial acidification (TA), marine eutrophication (ME), and human noncarcinogenic toxicity (HTnc). The CC of the fertilization process was 1,662.8 kg CO2 eq./ha with conventional nitrogen application versus 1,518.8 kg CO2 eq./ha as the lower of the two VRNA results, an 8.6% reduction due to less fertilizer applied. Fertilization was found to be responsible for more than 80% of the total emissions that impact CC, 55% of the FET, 44% of the HTnc, 96% of the FE and 96% of the TA. The largest greenhouse gas (GHG) emitters were soil N emissions as simulated by the DNDC, followed by the fertilizer manufacturing process in all of the impacts, except for FET and HTnc, where fertilizer production was the highest contributor. ICT components contributed less than 1% to all of the impacts assessed. The amount of applied N fertilizer has a greater influence on NH3 and NO3 indirect soil emissions than on direct N2O emissions. This study demonstrates that using optical crop sensors for VRNA could have a limited but positive environmental impact and highlights the importance of applying site-specific soil models to estimate field emissions.

Climate neutrality strategies for energy-intensive industries: An Austrian case study

The industry is responsible for 24% of anthropogenic emissions and a quarter of total energy consumption worldwide. Accelerating the action plan for climate neutrality for the industry, particularly the energy-intensive industrial subsectors, which are responsible for about 70% of the sector's emissions and energy consumption, is crucial to achieving the climate change goals. Iron and steel, pulp and paper, nonmetallic minerals emphasizing cement and nonferrous metals focusing on aluminum are the four energy-intensive industrial subsectors investigated in this study. We evaluate the benefits and obstacles of various mitigation methods for each subsector over two time horizons: short/medium-term emission reductions and long-term emission reductions. Actions that have already been implemented in some industrial sites and do not require extensive infrastructural upgrades are generally considered in the short/medium term. This group covers boosting energy efficiency by retrofitting plants and adopting the best available or best practice technologies in existing process stages, as well as substituting fossil fuels as energy sources with bioenergy, hydrogen, or electricity (low-emission electricity). This strategy can reduce emissions in the shortest possible timeframe; nevertheless, the reduction is insufficient, and additional efforts are required to transition the industry to a low-carbon economy by 2050. These further efforts are viewed as long-term reductions that broadly address mitigation alternatives connected to process emissions, which are an inherent part of the production processes of industrial subsectors across a more extended period. The frontline technologies studied in this category are fossil fuel feedstock change to non-fossil gases such as hydrogen, carbon capture usage and storage, a higher degree of electrification and increased use of secondary raw material. By evaluating the conditions for each subsector, this study also analyses the industrial landscape along the industrial value chain, showing that all of these four technology groups need to be implemented in a sector-specific approach to close the ambitious net-zero emissions gaps. In this essay, Austrian energy-intensive industrial subsectors are assessed as case studies using a comprehensive approach that includes influencing factors such as the subsector's current energy and emissions intensity, energy infrastructure, future national and international policies, and related decarbonization techniques. Transitioning from fossil fuels to emission-free fuels as raw materials (in the iron and steel subsector) and energy sources, as well as circular economy paths, have more potent effects on decarbonizing the Austrian industry. When these strategies are integrated with CO₂ capture solutions for the cement industry and energy efficiency improvements for relevant subsectors, Austrian industrial emissions can be reduced by more than 65% compared to the current level.

Barn or building lot? A cross-case comparison viewing the role of agricultural interests in Austria’s local spatial planning processes

Due to ongoing urbanisation processes, farmland and the number of farms in Europe are declining. In the regions affected, spatial planning plays a substantial role in securing agricultural production requirements. The extent to which planning decision-makers actually consider agricultural interests, however, has been little investigated so far. Based on two Austrian case studies, this paper explores the presence of agricultural interests within local spatial planning as well as potential preconditions for their perception and implementation.A systematic case study selection through a weighted linear combination (WLC) brought up the two agro-structurally contrasting municipalities Aderklaa and Leopoldsdorf, located at the Viennese city border. Problem-centred interviews with 27 local spatial planning actors, supplemented by the analysis of planning documents, provided insights into the local spatial planning processes. The Institutional Analysis and Development (IAD) framework served as the conceptual basis for the qualitative data analysis and the subsequent cross-case comparison.Aderklaa has preserved its rural characteristics in the past decades. Almost 90 % of the municipal area is used as farmland; there are about 25 farms in the village of 196 inhabitants. Leopoldsdorf, on the other hand, experienced an urbanisation of its former village structure. Farmland makes up 50 % of Leopoldsdorf’s area. The municipality has 5230 inhabitants; three farms still exist today. Regarding the integration of agricultural interests into local spatial planning, the municipalities show significant differences: While Aderklaa aligns its spatial planning policy to a large extent with the interests of local farmers, this is not the case in Leopoldsdorf. The study was able to identify the political commitment of local farmers as crucial for the integration of agricultural interests into local spatial planning and to confirm the impact of spatial planning decisions on agriculture.

PeakTrace: Routing of hydropeaking waves using multiple hydrographs—A novel approach

AbstractHydropeaking is known for its adverse impacts on river ecosystems. However, the implementation of mitigation measures is still largely pending due to conflicting priorities of ecology and economics, which require scenario building to assess trade‐offs. Therefore, widely applicable and standardized tools are needed to analyze hydropeaking hydrology in affected rivers to expedite mitigation efforts. Here, we present a novel empirical approach—PeakTrace—that can (a) detect and follow source‐specific hydropeaking waves in the downstream direction by using multiple hydrographs and (b) describe how to flow metrics of hydropeaking waves change along a river's course. In detail, PeakTrace first identifies associated flow events and then models translation and retention processes between neighboring hydrographs. Finally, the models can be combined to establish a non‐linear hydropower plant‐specific model. We demonstrate the PeakTrace method's usability in 16 Austrian case studies. The results underline the high performance of PeakTrace, describing the longitudinal development of flow metrics with high model accuracy up to 25 km or more. Ecologically‐relevant metrics, such as rate of change or amplitude, decrease with distance from the hydropower outlet regarding down‐ramping events; the same pattern can be observed for up‐ramping events too, except for the rate of change for which an intensity increase may be observed, probably due to slope and the roughness difference between base flow and peak flow. Overall, this paper underlines the usability of PeakTrace as a basis to assess hydropower plant‐specific hydro‐ecological impacts and evaluate hydropeaking mitigation measures, especially by incorporating critical flow thresholds of river biota and life stages.

Fostering social learning through role-play simulations to operationalize comprehensive climate risk management: Insights from applying the RESPECT role-play in Austria

This paper describes an analytical-deliberative process, centered around the RESPECT role-play simulation, conducted to foster the operationalization of comprehensive climate risk management (CRM) in Lienz, southern Austria, a city that is representative of many alpine regions. We hypothesize that fostering social learning via participatory stakeholder engagement processes aids closing prevailing science–policy–implementation gaps in CRM, which are often a result from insufficiently clear roles and responsibilities, diverging stakeholder interests, priorities and risk perceptions, and inexistent or incipient cooperation mechanisms. To test this hypothesis, we co-developed and conducted a role-play simulation centered on riverine-flood risk—the most pressing climate-related risk in the Lienz case-study region. Based on our analysis of qualitative data gathered ex ante and ex post the intervention, we found role-play simulations to have a high potential for fostering social learning in CRM. After taking part, the diverse societal stakeholders were found to better understand: i) the interacting dimensions and drivers of riverine-flood risks; ii) the diverging risk perceptions; and iii) each other’s interests and needs in addressing such risks at the individual and institutional level. Role-play simulations are a promising transdisciplinary method for engaging societal stakeholders beyond traditional policy- and decision-making communities in informed and inclusive public debate around challenges and solutions to CRM. The methodological and practical insights gained in this Austrian case study may be transferred to the management of other climate-related risks.

Exergy as criteria for efficient energy systems – Maximising energy efficiency from resource to energy service, an Austrian case study

The EU aims for complete decarbonisation. Therefore, renewable generation must be massively expanded, and the energy and exergy efficiency of the entire system must be significantly increased. To increase exergy efficiency, a holistic consideration of the energy system is necessary. This work analyses the optimal technology mix to maximise exergy efficiency in a fully decarbonised energy system. An exergy-based optimisation model is presented and analysed. It considers both, the energy supply system and the final energy application. The optimisation is using Austria as a case study with targeted renewable generation capacities of 2030.The results show, that despite this massive expansion and the maximum exergy efficiency, about half of the primary energy still be imported. Overall exergy efficiency can be raised from today's 34% (Sejkora et al., 2020) to 56%. The major increase in exergy efficiency is achieved in the areas of heat supply (via complete excess heat utilisation and heat pumps) and transport (via electric and fuel cell drives). The investigated exergy optimisation results in an increase of the final electrical energy demand by 44% compared to the current situation. This increase leads to mainly positive residual loads, despite a significant expansion of renewable generation. Negative residual loads are used to provide heat and hydrogen.

Towards the Use of Land Use Legacies in Landslide Modeling: Current Challenges and Future Perspectives in an Austrian Case Study

Land use/land cover (LULC) changes may alter the risk of landslide occurrence. While LULC has often been considered as a static factor representing present-day LULC, historical LULC dynamics have recently begun to attract more attention. The study objective was to assess the effect of LULC legacies of nearly 200 years on landslide susceptibility models in two Austrian municipalities (Waidhofen an der Ybbs and Paldau). We mapped three cuts of LULC patterns from historical cartographic documents in addition to remote-sensing products. Agricultural archival sources were explored to provide also a predictor on cumulative biomass extraction as an indicator of historical land use intensity. We use historical landslide inventories derived from high-resolution digital terrain models (HRDTM) generated using airborne light detection and ranging (LiDAR), which are reported to have a biased landslide distribution on present-day forested areas and agricultural land. We asked (i) if long-term LULC legacies are important and reliable predictors and (ii) if possible inventory biases may be mitigated by LULC legacies. For the assessment of the LULC legacy effect on landslide occurrences, we used generalized additive models (GAM) within a suitable modeling framework considering various settings of LULC as predictor, and evaluated the effect with well-established diagnostic tools. For both municipalities, we identified a high density of landslides on present-day forested areas, confirming the reported drawbacks. With the use of LULC legacy as an additional predictor, it was not only possible to account for this bias, but also to improve model performances.

Overview and Main Findings for the Austrian Case Study

As part of a project investigating in the potential greenhouse gas mitigation effect of the increased use and production of mass timber worldwide, a comparative study was carried out to show the potential benefit of mass timber use in buildings in central Europe. After designing a mass timber building functionally equivalent to an existing conventional building, cradle to grave life cycle assessments (LCA) were calculated. The reference is an eight-story building with mixed use in Vienna, originally built in reinforced concrete. Global Warming Potential (GWP) is defined as the central parameter of interest. Calculated life cycle phases are A1–A3 (resource to production), A4 and A5 (transport to site and construction, respectively), B4 (replacement in the use phase), and C1–C4 (End of Life), as well as D (benefits and loads beyond the building life). It can be shown that the total mass of the timber building is 47% lower than of the concrete building. Considering life cycle phases A1 to A5, the timber building shows 18% less embodied carbon. Taking the whole building life cycle and the operational energy use (B6) into account, differences in GWP are much lower, as the heating system, though equipped with high efficiency and clean Austrian electricity grid mix, has much higher impact than the other phases.

Techno-economic analysis of combined heat pump and solar PV system for multi-family houses: An Austrian case study

With the increasing amount of building renovations in Austria, the potential increases for replacing conventional national gas heating systems with heat pumps (HP) and thereby reduce CO2 emissions particularly when combined with solar photovoltaics (PV). The Austrian subsidization scheme for HP and PV systems are different for every state, creating confusion and inconstancy for potential adopters. This study provides a parametric techno-economic analysis of PV + HP systems to identify the critical economic parameters on profitability and make policy recommendations. A case study in Vienna is modelled using demand from the Building Model Generator and black box efficiency models for the HP and PV simulated with hourly time steps. The results show that both air-source and ground source heat pumps are currently profitable with PV under current subsidy schemes. The benefit-to-cost ratio (BCR) is highly influenced by capital costs and subsidies, however natural gas prices have the greatest influence. Increasing natural gas prices by 0.01 €/kWh, or 17%, is enough to replace all other complicated subsidies for both HP and PV. This is equivalent to a carbon emissions price of 33 €/ton and could result in a reduction of CO2 emissions in multi-family houses by approximately 45%–60%.

Supporting decision-making for heating and distribution systems in a new residential district - An Austrian case study

A new residential district will be built in Innsbruck, Austria. The energy and environmental impact are considered during the decision-making procedure. A complete and comprehensive simulation study was performed to develop a decision support tool with respect to a) which type of heating system i.e. heat pumps, connection to district heating, or natural gas boilers, b) which level of centralization of the heating system i.e. from one central solution for the entire district up to decentral systems located in each flat, c) which type of heat distribution system and d) the corresponding pipe insulation level. To compare the aforementioned combinations, various key performance indicators were calculated, using two different calculation methods: one with annual and one with monthly conversion factors. The results show that the use of heat pumps or district heating instead of gas boilers decreases the carbon emissions by a maximum of 75% and 52%, respectively. The choice of the appropriate key performance indicator and calculation method had a minor influence on the ranking of the investigated solutions but a significant influence on the quantitative results.

Going local – Providing a highly detailed Green Infrastructure geodata set for assessing connectivity and functionality

Green Infrastructure (GI) defined as a strategically planned network of natural and semi-natural areas is a key strategy in the European biodiversity strategy and the landscape connectivity agenda. To implement this approach in Central Europe’s (CE) landscape planning policies the Interreg project MaGICLandscapes (ML) tried to operationalise the GI concept in CE as well as in nine case studies, to provide land-managers, policy makers and communities with tools and knowledge, at different spatial levels.
 Based on the example of the Austrian case study area, the aim of this paper is to present an easy to use approach, as implemented in ML, for producing a highly-detailed regional GI database to overcome the difficulty of realising comprehensive biotope mapping surveys as well as the rather coarse resolution of CORINE Land Cover (CLC). By compiling regional cadastral and agricultural information, highly detailed data on the water network as well as Pan-European High Resolution Layers (HRL), this detailed representation of the regional GI network allows to enhance the regional applicability and acceptance of GI initiatives and provides a crucial foundation for assessing GI connectivity and functionality to develop evidence-based strategies and action plans through stakeholder involvement to direct future actions and investment in GI.

Citizen Participation to Finance PV Power Plants Focused on Self-Consumption on Company Roofs—Findings from an Austrian Case Study

Despite large amounts of available roof space, long pay-back periods for investments in photovoltaic (PV) power plants often hinder PV installations in industrial parks. Photovoltaic citizen participation initiatives (PV-CPI) are an alternative way of financing PV power plants that add non-financial benefits to these investments. This paper analyzed the feasibility of the installation of PV power plants focused on high rates of self-consumption financed by citizen participation initiatives on the roofs of five companies located in the Austrian Ennshafen industrial business park based on the net present value and the discounted pay-back period and compared it to a standard financing scheme, assuming a predetermined interest rate for participants as well as economies of scale with respect to the specific installation costs due to a joint purchase of the PV power plants. To calculate the feasibility, site-specific data and literature input have been used. The results show that despite an interest rate above the current interest rates of conservative forms of investments provided to (small-scale) investors, a payback-period of 17–23 years can be reached while the joint purchase can lead to a competitive feasibility of the PV-CPI compared to an individual purchase of PV power plants.

Labour Market Profile, Previous Employment and Economic Integration of Refugees: An Austrian Case Study

In 2015, large numbers of forced migrants crossed the borders to the European Union and the influx of new arrivals has led to the important question of implications for the host societies. This article assesses the labour market profile and previous employment of the recent inflows of displaced persons, mainly coming from Syria, Iraq and Afghanistan. Moreover, sectoral unemployment rates and trends in job openings in different economic branches in the host society are compared to the profiles of the refugee population. Analyses are based on two unique datasets on displaced persons in Austria: DiPAS (a social survey among asylum seekers) and competence checks (information on occupational and transferable skills). Results indicate that the labour supply provided by refugees’ roughly corresponds to the labour demand in Austria. In terms of a potential impact on the Austrian labour market, this match might be regarded as favourable.

Religionszugehörigkeiten in Österreich auf Bundesländerebene: Schätzungen für Vorarlberg, 2001–2018

Religionszugehörigkeiten in Österreich auf Bundesländerebene: Schätzungen für Vorarlberg, 2001–2018