Bavaria Research Articles

Individual right to clean air including compensation for health damage – comment on JP v Ministre de la Transition écologique, C-61/21

Abstract On the one hand, the EU member states are to manage ambient air quality in line with the Air Quality Directive (dir. 2008/50/EC) provisions that put forward local air quality targets. On the other hand, EU citizens have their right to demand that their local authorities pass ‘air quality plans’ for towns or districts where air quality standards were below the so-called limit values. In 2008, in the Janecek Judgement of the Court of Justice of 25.07.2008, C-237/07 Dieter Janecek v. Freistaat Bayern EU:C:2008:447. case the Court of Justice of the EU (the CJEU) for the first time recognised the direct effect of Articles 13 and 23 of this directive, and in this way granted rights to individuals to challenge local air quality plans for their inefficiency. The main point of this article is to prove that EU citizens have a subjective, justiciable right to clean and healthy air, and to examine whether this right entitles them to compensation for health damage due to air pollution, as was the subject matter of the commented case: JP v Ministre de la Transition écologique. Therefore, it is necessary to examine the three conditions of the Francovich rule for state liability established in the Brasserie du Pêcheur case: ‘1. the rule of law infringed must be intended to confer rights on individuals; 2. the breach must be sufficiently serious, 3. and there must be a direct causal link between the breach of the obligation resting on the state and the damage sustained by the injured parties’ Judgement of the Court of Justice of 5.03.1996, C-46/93 and 48/93 Brasserie du Pêcheur EU:C:1996:79. .

Students’ perspectives on climate change—unveiling gender–interest associations in climate change beliefs

Climate change is one of humanity’s key problems. Younger generations’ beliefs about and perceptions of climate change are thus of particular importance, as these generations have to tackle the problem in the present and will have to do so even more in the future. Against this background, 4627 high school students in the federal state of Bavaria in Germany were surveyed in a quantitative questionnaire-based study. The analysis shows high values and gender differences for the four general climate change beliefs examined: (1) general perception of climate change as a problem, (2) possible solutions to the problem, (3) contributions to climate protection, and (4) effects on one’s own home. However, mediation analyses suggest that differences are more complex and are to some extent connected to gender differences in interest in climate change.

What if … there were no special schools?

AbstractInclusive education is a human right that involves restructuring the school system and closing special schools. However, there is uncertainty about whether all or only some students in an inclusive system should attend regular primary schools and whether all or only some special schools should be closed. This question is usually only discussed in terms of the best possible care and education and the challenge of transportation to school and travel distances is neglected. This article attempts to take both into account. The federal state of Bavaria in Germany does not yet have a fully developed inclusive school system. Using school statistics data for the entire Bavarian primary school population in 2020 (N > 445,000) and geographical data, we simulate deterministically what the Bavarian primary school system could look like with various underlying inclusion models. We analyse the resulting student numbers, support rates of primary schools and school travel distances of former special school students in an urban-rural comparison in four different simulated inclusion models. The results show that all models are potentially feasible. The student numbers at each primary school resulting from the closure of special schools would in most cases not change significantly, whereas the support rate (i.e., the percentage of students with SEN per primary school) would. Schooling close to home favours students in rural areas in particular and significantly reduces their journeys to school by up to 30 km, while for students in urban areas, all inclusive models would be possible. The pedagogical and systemic consequences of the simulated inclusion models are discussed.

First Evidence of Leishmania infantum Antibodies in Sheep (Ovis aries) from Southern Germany.

In Europe, Leishmania infantum is the most prevalent Leishmania species, and this protozoan is transmitted by phlebotomine sandflies. A recent publication has shown that sheep harbor L. infantum antibodies. This raises questions about the epidemiological role of small ruminants. Therefore, sera from small ruminants located in two southern German federal states, Baden-Wuerttemberg (BW) and Bavaria (BAV), were analyzed with an ELISA to determine the presence of L. infantum antibodies. The species, sex and age (gimmer vs. ewe) were recorded, and a univariate analysis was conducted to determine possible associations. In total, seven sheep flocks (274 sheep/10 goats) from BW and seven sheep flocks (277 sheep/78 goats) from BAV were examined. In BW, four sheep from three flocks tested positive for L. infantum antibodies. In BAV, the same number of positive sheep were detected but in four flocks. The total seropositivity rate in sheep was 1.45%. All goats tested negative. No significant association (p > 0.05) was detected between Leishmania seropositivity and the variables evaluated. Our study reveals the exposure of sheep to L. infantum in a non-endemic area. Further investigation is needed to determine whether sheep can be used as sentinels to identify new phlebotomine habitats and Leishmania risk areas.

Selectively closing recycling centers in Bavaria: Reforming waste‐management policy to reduce disparity

AbstractRecycling centers sort and process collected waste in the interest of the environment, but also lead to damaging climate effects via released emissions and pollutants in their operation. Consequently, governments are closing such centers to fulfill climate and carbon neutrality goals. However, such closures risk populations being forced to travel further to facilities that collect waste, and can cause an unfair burden on the remaining open centers, thereby reducing participation in recycling. Using a facility location optimization model and mobility survey data within the state of Bavaria in Germany, we show how selective closures of these centers can still lead to high levels of recycling access. Our analysis ensures that even when 20% of facilities are closed smartly, the median travel distance by residents to their assigned recycling center increases by only 450 m. Additionally, we find Bavaria suffers from disparity in recycling patterns in rural and urban regions, both in terms of motivation to recycle and the locations of the facilities. We promote a policy that favors retention of recycling centers in rural regions by reserving 75% of open facilities to be in rural areas, while selectively closing facilities in urban regions, to remove these regional differences. Success of recycling campaigns depends on public perception of closures of such facilities and also on their ease of access. As policymakers gradually implement further closures, such data‐driven strategies can assist in being more transparent to the public thereby increasing the willingness to participate in such recycling programs.

Quadratic Optimization Models for Balancing Preferential Access and Fairness: Formulations and Optimality Conditions

Typically, within facility location problems, fairness is defined in terms of accessibility of users. However, for facilities perceived as undesirable by communities hosting them, fairness between the usage of facilities becomes especially important. Limited research exists on this notion of fairness. To close this gap, we develop a series of optimization models for the allocation of populations of users to facilities such that access for users is balanced with a fair utilization of facilities. The optimality conditions of the underlying nonconvex quadratic models state the precise balance between accessibility and fairness. We define new classes of fairness and a metric to quantify the extent to which fairness is achieved in both optimal and suboptimal allocations. We show that a continuous relaxation of our central model is sufficient to achieve a perfect extent of fairness, while a special case reduces to the classical notion of proportional fairness. Our work is motivated by pervasive ecological challenges faced by the waste management community as policymakers seek to reduce the number of recycling centers in the last few years. As a computational case study, applying our models on data for the state of Bavaria in Germany, we find that even after the closure of a moderate number of recycling centers, large degrees of access can be ensured, provided that the closures are conducted optimally. Fairness, however, is impacted more, with facilities in rural regions shouldering larger loads of visiting populations than those in urban regions. History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis. Funding: Computer resources and support provided by the Erlangen Regional Computing Center are gratefully acknowledged. B. Singh was partially financially supported by the Bavarian State Ministry for Science and Art (Bayerisches Staatsministerium für Wissenschaft und Kunst) under the Competence Network for Scientific High Performance Computing in Bavaria. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0308 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0308 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Mapping of very shallow geothermal potentials in rural areas of Bavaria

Climate change is a rising issue which strongly influences contemporary society. Therefore, the utilization of sustainable non-fossil energy sources is one of the most important goals in order to reduce greenhouse gas emission. Utilization of geothermal energy for heating and cooling buildings or residential units is one of the significant steps in providing sustainable and renewable energy supply. This paper presents very Shallow Geo-thermal Potentials (vSGP) of German federal state Bavaria, with special focus on rural are-as. Main goal of the study was to analyze the potentials for utilization of very shallow geo-thermal systems in terms of thermal conductivity and heat extraction. High-resolution soil maps containing information of grain size conditions served as an area-wide data basis for the research, while the analysis and visualization of the results were conducted by GIS software. Thermal conductivity as well as system-specific heat extraction were calculated depending on soil texture and climate conditions. Thermal conductivity results are intend-ed to be further used as the basic parameter for planning and installing horizontal geo-thermal heating and cooling systems.

Strategic Alignment in Times of Crisis: Voting at the Dawn of a Global Pandemic

Natural disasters are likely to increase in the near future. How does the emergence of such events influence voting behavior? While the literature has focused on the electoral repercussions after disaster has already struck, we investigate whether imminent disaster influences vote choice. We study the effect of the onset of the COVID-19 pandemic on electoral choice in a setting that allows for causal identification: the local elections in Germany’s southern state Bavaria in March 2020, where, at the time of the elections, only an as-if random sample of localities had recorded cases of COVID-19. We find that initial local outbreaks favored the political party governing at the state level and hurt the far right. These findings are most likely driven by a ‘strategic alignment’ mechanism, whereby voters choose the party or candidate they believe is best placed to help them through the crisis.

Investigation and Comparison of Spatial–Temporal Characteristics of Farmland Fragmentation in the Beijing–Tianjin–Hebei Region, China, and Bavaria, Germany

Farmland fragmentation has emerged as the primary manifestation of global land use changes during the last century. Following the economic reform and opening up in China from the 1980s, the Beijing–Tianjin–Hebei (BTH) region has witnessed continuous farmland fragmentation. Understanding the spatial–temporal dynamics of farmland fragmentation is crucial for formulating sustainable land use management strategies. However, the specific causes and locations of farmland fragmentation remain unclear, as do potential significant differences or similarities across different countries. Given this quandary, this study empirically analyzes the spatial–temporal characteristics of farmland fragmentation in two different contexts: the BTH region in China and Bavaria in Germany. The study utilizes multiple theoretical models for temporal and spatial farmland fragmentation, applying the comprehensive index method, landscape pattern analysis, and the magic cube model. The results indicate that the farmland fragmentation index (FFI) value in BTH and Bavaria first increased or remained stable, but afterwards, both decreased and increased again. Moreover, the spatial analysis demonstrated high significance values for the FFI in the northern and western BTH region and in northern and southern Bavaria. There are, furthermore, significant differences in the FFI in different macro landforms. The FFI in the mountain regions is significantly higher than that of the plains. Finally, the results also demonstrate that a decreasing FFI relates to the overall low values within an FFI region. The theoretical framework in this study appears to align with empirical results, and thus provides a reference for future policy measures to protect farmland.

Rumänische Suffixnamen auf -ean(u) in Deutschland

This study aims to document Romanian surnames in Germany derived with the suffix -ean(u), starting from the telephone database of Deutsche Telekom from 2005. The morphological contrast between the variants that take an article and the ones that do not shows their similar distribution on the map, specifically in southern and western Germany, in the states of Bavaria, Baden-Württemberg, Hessen and North Rhine-Westphalia, in the areas of important industrial and university centres such as Munich, Nuremberg, Augsburg, Ingolstadt, Stuttgart, Freiburg, Mannheim and Frankfurt. This picture of the spread of Romanian surnames derived with the suffix -ean(u) is similar to that of the surnames ending in -escu, as well as to that of other foreign surnames, such as the Turkish, Italian, Portuguese or Greek ones, which proves the settlement of immigrants in the same highly industrialized areas of Germany. The most frequent surnames ending in -ean(u) in Germany are Muntean(u) (88+80), Ardelean(u) (65+14), Mărginean (23), Ungurean(u) (21+31), C(î|â)mpean(u) (18+11), Oltean(u) (12+22). Historically, the Romanian names derived with the suffix -ean(u) appear in the 15th century (e.g. Coman Făgărășanul 1437–1446), are derived from toponyms and indicate the place of origin of the first named. The onomastic suffix -ean(u), of Slavic origin, is present in all historical Romanian provinces, theform -ean, with no article, being much more frequent in Transylvania.

Impact of the COVID-19 pandemic on the care of major trauma patients: analysis from the TraumaRegister DGU®

The treatment of major trauma patients requires intensive care capacity, which is acritical resource particularly during the coronavirus disease 2019 (COVID-19) pandemic. Therefore, the aim of this study was to analyze the impact on major trauma care considering the intensive care treatment of COVID-19 positive patients. Demographic, prehospital, and intensive care treatment data from the TraumaRegister DGU® of the German Trauma Society (DGU) in 2019 and 2020 were analyzed. Only major trauma patients from the state of Bavaria were included. Inpatient treatment data of COVID-19 patients in Bavaria in 2020 were obtained using IVENA eHealth. In total, 8307 major trauma patients were treated in the state of Bavaria in the time period investigated. The number of patients in 2020 (n = 4032) compared to 2019 (n = 4275) was not significantly decreased (p = 0.4). Regarding COVID-19 case numbers, maximum values were reached in the months of April and December with more than 800 intensive care unit (ICU) patients per day. In the critical period (> 100patients with COVID-19 on ICU), aprolonged rescue time was evident (64.8 ± 32.5 vs. 67.4 ± 30.6 min; p = 0.003). The length of stay and ICU treatment of major trauma patients were not negatively affected by the COVID-19 pandemic. The intensive medical care of major trauma patients could be ensured during the high-incidence phases of the COVID-19 pandemic. The prolonged prehospital rescue times show possible optimization potential of the horizontal integration of prehospital and hospital.

Varying growth response of Central European tree species to the extraordinary drought period of 2018 – 2020

Droughts have intensified in Central Europe and will likely become a major driver of forest ecosystem change in the future. Regional studies are needed to understand drought impacts on forests and to provide guidance for adaptive management. In this study, we have investigated the effects of an extraordinary drought period in 2018 – 2020 on tree growth in the State of Bavaria (Germany). We (i) assessed overall changes in tree growth compared to pre-drought conditions, (ii) mapped the spatial configuration of drought and its impact on growth across ecoregions, (iii) quantified the standardized drought effect for the most abundant tree species, and (iv) analyzed the inter- and intraspecific variability in growth responses to drought.Covering a large environmental gradient, we compared 3,462 tree basal area growth records at 200 inventory plots with the pre-drought period of 2006 – 2017. We analyzed drought impacts on tree growth using nonparametric randomization tests and linear quantile mixed models (LQMMs).Median annual tree growth declined by 41.3% during drought. Decreases in growth were statistically significant for 13 out of 20 species. Growth reductions were most distinct in northwestern ecoregions of Bavaria. After controlling for other covariates of tree growth, the most abundant conifers, Picea abies [Karst.] and Pinus sylvestris [L.], were overall more susceptible than the common broadleaves, Fagus sylvatica [L.], Quercus robur [L.], and Quercus petraea [Matt.]. Yet, all species exhibited a high intraspecific variation in drought response.Altering tree species composition is a key strategy to adapt forest ecosystems. Our study reveals high potential to mitigate future drought impacts by admixing P. abies- and P. sylvestris-dominated forests with more drought-adapted broadleaved tree species. In addition, the high intraspecific variability in drought susceptibility indicates potential to promote provenances or individuals with low drought sensitivity to reduce the local loss of tree species.

Impact of STARFM on Crop Yield Predictions: Fusing MODIS with Landsat 5, 7, and 8 NDVIs in Bavaria Germany

Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km2), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R2 of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R2 of yearly synthetic NDVIs and N) and −0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R2 of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R2 = 0.88) and OSR (R2 = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R2 of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.

Seroprevalence of Brucella Infection in Wild Boars (Sus scrofa) of Bavaria, Germany, 2019 to 2021 and Associated Genome Analysis of Five B. suis Biovar 2 Isolates

Brucella species are highly pathogenic zoonotic agents and are found in vertebrates all over the world. To date, Germany is officially declared free from brucellosis and continuous surveillance is currently limited to farm ruminants. However, porcine brucellosis, mostly caused by B. suis biovar 2, is still found in wild boars and hares. In the present study, a three-year monitoring program was conducted focusing on the wild boar population in the state of Bavaria. Serologic screening of 11,956 animals and a direct pathogen detection approach, including a subset of 681 tissue samples, was carried out. The serologic incidence was 17.9%, which is in approximate accordance with previously published results from various European countries. Applying comparative whole genome analysis, five isolated B. suis biovar 2 strains from Bavaria could be assigned to three known European genetic lineages. One isolate was closely related to another strain recovered in Germany in 2006. Concluding, porcine brucellosis is endemic in Bavaria and the wild boar population represents a reservoir for genetically distinct B. suis biovar 2 strains. However, the transmission risk of swine brucellosis to humans and farm animals is still regarded as minor due to low zoonotic potential, awareness, and biosafety measures.

Atlas of ticks (Acari: Argasidae, Ixodidae) in Germany: 1st data update

The first data update of the atlas of ticks in Germany published in 2021 is presented here. This atlas provides maps based on georeferenced tick locations of 21 species endemic in Germany as well as three tick species that are regularly imported to Germany. The data update includes the following numbers of newly georeferenced tick locations: 17 Argas reflexus, 79 Carios vespertilionis, 2 Dermacentor marginatus, 43 Dermacentor reticulatus, 4 Haemaphysalis concinna, 3 Haemaphysalis punctata, 3 Hyalomma rufipes, 3 Ixodes apronophorus, 9 Ixodes arboricola, 1 Ixodes ariadnae, 30 Ixodes canisuga, 3 Ixodes frontalis, 80 Ixodes hexagonus, 3 Ixodes lividus, 497 Ixodes ricinus/inopinatus, 1 Ixodes rugicollis, 17 Ixodes trianguliceps, 14 Ixodes vespertilionis, and 45 Rhipicephalus sanguineus sensu lato. Old and new tick findings were mapped, such as the northernmost occurrence of D. marginatus in Germany observed in 2021, but also the historical records from the first descriptions of I. apronophorus and I. arboricola, which were georeferenced here for the first time. The digital dataset of tick locations available for Germany is supplemented by 854 new tick locations. These records increase the number of tick species mapped in the federal states Bavaria, Brandenburg and Mecklenburg Western Pomerania by five each, those in Berlin and Schleswig-Holstein by four each, those in Hamburg by three, those in Baden-Wuerttemberg, Bremen, Lower Saxony, Northrhine-Westphalia, Rhineland Palatinate and Thuringia by two each, and those in Hesse, Saxony and Saxony-Anhalt by one each. Thus, the first data update of the tick atlas in Germany and the underlying digital dataset significantly improve our knowledge of the distribution of these tick species and helps to investigate the effects of climate change and habitat changes on them.

Vergleich der Genauigkeit zweier Methoden zur Kariesdetektion in einer epidemiologischen Feldstudie

Aim: In the course of the 6th nationwide epidemiological schoolchildren's oral health study, examination standards in caries diagnosis in Bavaria had to be adapted to the specifications of the German Working Group for Promotion of Youth Dental Care (Deutsche Arbeitsgemeinschaft für Jugendzahnpflege, DAJ). However, it was questionable whether the recorded data would be comparable with earlier examination outcomes. The present study therefore aimed to investigate whether different specifications from Bavaria (BA) and Germany (DAJ) lead to different DMF-T/S values. Methods: From the representative sample provided by the GESIS Leibniz Institute in Mannheim, Germany, 965 Bavarian sixth graders from 50 schools were assessed twice and independently between October 15, 2015 and June 20, 2016. All investigators qualified via online calibration (κ ≥0.65). Control investigators (CI; n=3) underwent an additional local briefing. Pupils were investigated independently by two investigators. Study investigators (SI; n=21) used conventional DAJ equipment (WHO probe, mirror, 20 W lamp, cotton dental rolls); CI used enhanced BA equipment (50 W lamp, stream of air, magnifying loops). The DMF-T/S values were recorded, initial caries screened, and the Significant Caries (SiC) index was computed. Two-sample comparisons were carried out using the t-test, and the analysis of variance was used for multiple sample analyses.Results: In all, 53.4% (CI) and 63% (SI) of children (average age 12.3 years) were caries-free. Mean DMF(T) was 1.65 (DMFS=2.33) for the CI group and 0.89 (DMFS=1.31) for the SI group. Calculated SiC-DMF(T) value of CI was 4.18, while SI was 2.54. The calculated SiC-DMF(S) values were also different (CI: 6.15/SI: 3.78). CI found significantly more initial caries (2.04) than SI (1.16). The data analysis showed that control examiners detected significantly higher experience of caries compared to the study investigators.Conclusion: The results show a discrepancy in the detection of caries in 11- to 14-year-old Bavarian pupils, with the better-equipped control examiners detecting a significantly greater caries experience than the study examiners. Consequently, the equipment used by investigators in epidemiological studies has a significant impact on the accuracy of caries diagnosis. Therefore, this should be taken into account for the planning of further epidemiological studies

Ecologically and biophysically optimal allocation of expanded soy production in Bavaria, Germany

A debate about cultivation and trading of soy has emerged among scientists, policymakers, and the public in recent years. Export-orientated soy production in regions of South America is associated with large-scale ecosystem destruction. Since soy is an important source of animal fodder, policymakers are developing schemes to support and enhance sustainable domestic soy cultivation, especially in the EU. Expanded soy cultivation should ideally provide high yields and at the same time promote environmental benefits. For this purpose, we applied a multi-objective optimization algorithm that selects areas with maximum soy suitability, minimum erosion risk, need for low fertilizer input due to water quality issues, and need for diversification of monotonous crop rotations. We use the state of Bavaria in Germany as a case study, modeling full self-sufficiency of soy. The results of the optimization indicate synergies between plantation suitability with need for low fertilization input and crop variation, which implies that the environmental benefit of nitrogen fixation and rotation diversification from soy plants can easily be reconciled with food productivity. However, slight trade-offs occur between erosion risk and the three other objectives, i.e., locations with better soy production might be more prone toward erosion risk. As a potential consequence of expanded soy cultivation in Bavaria, we identified winter wheat, grain maize, potatoes, and sugar beet as those crops that have the highest share of displaced cultivation area. To reduce such land use conflicts and ensure self-sufficiency in relevant crops, we recommend to limit the use of soy as animal feed. Nevertheless, we propose to explicitly incorporate the local need for the environmental benefits of soy cultivation in the planning for soy expansion. In doing so, domestic soy can turn into a real sustainable alternative to imported plant protein.

Identification of undocumented buildings in cadastral data using remote sensing: Construction period, morphology, and landscape

Buildings are the predominant objects that characterize the urban structure. For many cities, local governments establish building databases for administration as well as urban planning and monitoring. However, newly constructed buildings are often only included with a considerable time delay in the official digital cadastral maps due to processes in the acquisition of data, so-called undocumented buildings. In this regard, detecting undocumented buildings using remote sensing techniques would support the construction of update-to-date building databases with complementary information. In-depth studies on undocumented buildings and their number and location, however, are scarce. Therefore, we exploit a deep learning-based framework to detect undocumented buildings in remote sensing data and propose to derive 2D and 3D morphological parameters as well as landscape metrics., which are capable of depicting the physical forms and spatial structures of undocumented buildings. Furthermore, we exemplify the variabilities of undocumented buildings across space by the differences in morphology and landscape metrics between high and low building density regions. Upon analysis of undocumented buildings in 15 cities in the state of Bavaria, Germany, both state- and city-scale results reveal that most undocumented buildings are located in lower dense regions. This reveals that fragmentation of the landscape by building structures in the state of Bavaria is probably greater than official geospatial data currently documented.

Techno-economic optimization of large-scale deep geothermal district heating systems with long-distance heat transport

Geothermal energy can play an important role in decarbonizing the heating sector, however, a limiting factor is that heat demand in urban areas does not usually coincide spatially with geological settings favorable to the extraction of geothermal energy. Long-distance heat transport could enable the direct use of geothermal resources even in areas with low or no geothermal potential. This paper proposes the cost-optimal coordinated deployment of geothermal heating plants together with heat transport and distribution networks to simultaneously supply geothermal heat to multiple urban areas. To this end, a holistic approach comprising the mapping of geothermal potential for direct-use, the estimation of district heating potential, and a two-step optimization model to calculate cost-optimal large-scale geothermal district heating systems, is presented and applied to the Free State of Bavaria in Germany. As a result, heat supply costs can be reduced by 15% if fewer geothermal wells are drilled in more geologically favorable areas at greater distances from heat sinks. Calculated levelized costs of heat without local distribution networks of 33–39 €/MWh show that geothermal energy could transition from a local to a regional use if utilized in in scenarios with high full-load hours. The proposed methodology can be adapted to develop expansion strategies for deep geothermal energy in other similar regions worldwide.

The influence of state politics on solar energy auction results

In this paper, we analyze the impact of policy-induced opportunity costs and restrictions on the outcomes of auctions to subsidize ground-mounted photovoltaic (PV) systems in Germany since 2015. First, we examine the incidence of opportunity cost reductions for some suppliers in a simple theoretical auction model. Second, we descriptively study the volumes and prices in PV auctions in Germany. Finally, we analyze a quasi-experiment: the opening of auctions for farmland in disadvantaged areas in some German states from 2017. We show that policy-induced opportunity cost reductions lead to greater success in PV auctions only in the state of Bavaria, which has more generous quantity restrictions and is generally expected to be more supportive of solar power suppliers after 2017. As a result, there is an interregional redistribution in favor of a single state that enables and administratively effectively implements support for disadvantaged areas.