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The defossilization of industry has far-reaching implications regarding the future demand for hydrogen and other forms of energy. This paper presents and applies a fundamental bottom-up model that relies on techno-economic data of industrial production processes. Its aim is to identify, across a range of scenarios, the most cost-effective low-carbon options considering a variety of production systems. Subsequently, it derives the hydrogen and electricity demand that would result from the implementation of these least-cost low-carbon options in process industries in Germany. Aligning with the German government's target year for achieving climate neutrality, this study's reference year is 2045. The primary contribution lies in analyzing which hydrogen-based and direct electrification solutions would be cost-effective for a range of energy price levels under climate-neutral industrial production and what the resulting hydrogen and electricity demand would be. To this end, the methodology of this paper comprises the following steps: selection of the relevant industries (I), definition of conventional reference production systems and their low-carbon options (II), investigation and processing of the techno-economic data of the standardized production systems (III), establishment of a scenario framework (IV), determination of the least-cost low-carbon solution of a conventional reference production system under the scenario assumptions made (V), and estimation of the resulting hydrogen and electricity demand (VI). According to the results, the expected industrial hydrogen consumption in 2045 ranges from 265 TWh for higher hydrogen prices in or above the range of onshore wind-based green hydrogen supply costs, to up to 473 TWh for very low hydrogen prices corresponding to typical blue hydrogen production costs. Meanwhile, the direct electricity consumption of the process industries in the results ranges from 147 TWh for these rather low hydrogen prices to 338 TWh for the higher hydrogen prices in the region of or above the hydrogen supply costs from the electrolysis of energy from an onshore wind farm. Most of the break-even hydrogen prices that are relevant to the choice of low-carbon options are in the range of the benchmark purchase costs for blue hydrogen and green hydrogen produced from offshore wind power, which span between €40 per MWh and €97 per MWh. [Display omitted] • Derivation of the future hydrogen and power demand of the process industry in Germany. • Bottom-up, process-level model to find the least-cost low-carbon production method. • Reference year is 2045, and the achievement of climate-neutral production is assumed. • Model determines the hydrogen and power demand under varying hydrogen prices. • Expected hydrogen use between 265 TWh and 473 TWh, depending on scenario assumptions. [ABSTRACT FROM AUTHOR]

Integrating enormous quantities of wind energy into the electrical system requires precise planning and forecasting. This paper presents a novel framework for wind power forecasting, which establishes a new standard for accuracy and reliability. It uses advanced deep neural networks and a stacking ensemble mechanism to make probabilistic forecasts. These forecasts address wind speed volatility and variability, which continue to be key issues in producing consistently accurate wind power forecasts despite advances in deep learning. Base learners generate forecasts that include lower and upper bounds, as well as median prediction intervals. The Huber regressor, also known as the Meta-learner, combines projections from many models to reduce susceptibility to extreme values. Expanding window cross-validation is used in performance evaluation, with a focus on Mean Absolute Error, Mean Squared Error (MSE), Symmetric Mean Absolute Percentage Error, Prediction Interval Coverage Probability, and Average Interval Width for one, two, and three step ahead predictions. The model's stability is measured by the standard deviation of MSE throughout each validation window. Additionally, the Diebold–Mariano test is used to validate the Meta-learner's predictive accuracy in contrast to other advanced models and the seasonal naïve benchmark. This study found that the meta model outperformed all other models in eight of the nine forecasts tested, indicating its effectiveness in medium-range forecasting. In Germany, it exceeded Temporal Fusion Transformer by two and three steps ahead, with 22% and 34% improvements, respectively. Indeed, this study not only provides a reliable prediction tool, but also lays foundations for efficient and effective energy management and policy planning in the renewable energy industry. • Deep neural network architectures are applied to probabilistic wind power forecasting. • Transformer and artificial neural network approaches combined with conformal prediction intervals is proposed. • A window cross-validation scheme on wind power forecasting is evaluated. • Wind power data from Germany, the UK, and the Netherlands are used for forecasting purposes. • SHAP and LIME analyses perform the explanatory analysis of the variables in the meta-learner's predictions. [ABSTRACT FROM AUTHOR]

The electricity market transitions from a market clearing in which flexible generation meets inflexible demand to one in which inflexible generation meets flexible demand. Consequently, new types of flexibility are needed to balance generation and demand. This paper mainly aims to analyse competition and synergy between various flexibility options in the electricity market. The developed European electricity market model maximises the joint socio-economic welfare of the electricity and the hydrogen market. Transmission grid,- storage expansion, electric vehicle demand side flexibility and hydrogen sector coupling are flexibility options. This work examines the implementation of different flexibility options in the bidding zones Austria and Germany. Austria, with a very high storage capacity in the alpine arc and Germany, with massive wind turbine capacities serve as representative case study. Results show that the storage location heavily influences the corresponding socio-economic welfare increase. Hence, location-dependent synergy and competition between storage and transmission line expansion can occur. In contrast, sector coupled hydrogen production and storage expansion compete with each other as both will reduce very low electricity prices. Demand-side flexibility primarily benefits end-users while producer surplus reduces. In combination with storage expansion, further positive synergistic effects for end-users occur. The combination of storage expansion and demand-side flexibility can replace transmission line expansion and vice versa if used comprehensively. Further efforts could address the evaluation of these effects if the individual flexibility providers aim for something other than a system-wide but individual optimum. • Implementation of several flexibility options into the European electricity market. • Storage location and transmission capacity have a huge influence on the results. • Consumers benefit from combined storage and demand-side flexibility use. • Additional electricity demand by sector coupling increases renewable energy revenue. • Storage and sector coupling compete with each other as both reduce price volatility. [ABSTRACT FROM AUTHOR]

The additive manufacturing of concrete components has made significant progress in the last 10 years. The increasing application of 3D printing in practice now also requires a categorization of the quality of the printed concrete surfaces that remain visible after printing. The quality of visible surfaces of additively manufactured components can be assessed according to the quality of formwork-exposed concrete surfaces. A suitable basis for this assessment is provided by the applicable regulations for exposed concrete surfaces in Germany and other international standards. In this publication, characteristics and requirements of individual concrete filaments as well as printed components are developed. These evaluate geometric, optical and structural properties of printed concrete surfaces. These can be used as a basis for further standardization of quality requirements for 3D-printed surfaces and for automated algorithms, fully automated manufacturing and monitoring of printed concrete components. • New perspectives for civil engineering, concrete technology, contract and site management are considered. • Good information base for the topic of exposed concrete. • The paper introduces a classification of quality levels for 3DCP surfaces, enhancing their visibility and evaluation. • Overview of surface design options for printed wall structures. • The effects of printing technologies on quality and basics for automated QA-/QC-processes are explained. [ABSTRACT FROM AUTHOR]

The transformation process in the building sector towards future city concepts requires changes in our society that aim for significant emission reduction until 2045. Currently, buildings in Germany are constructed and operated in such a way that no changes need to be made to them for decades. Therefore, any upcoming changes that do not achieve the climate goals must be avoided immediately. However, making the optimal decision for a change is complex due to (a) multi-domain (e.g., design and control), (b) multi-scale (e.g., single-family building and urban energy system), (c) multi-stakeholder (e.g., users and practice), and (d) long-term implications (up to decades). Conventional testing facilities and methods do not account for the integration of (a)-(d). Therefore, their technology readiness level is limited by 6. This paper introduces an approach that aims at (1) a multi-domain and multi-scale approach by applying process systems engineering to the building sector and that aims at (2) stakeholder integration already in the research process by applying the living lab approach. We combine the two methods, yielding a field test in the lab infrastructure pushing the technology readiness level to 7–8. In all, it consists of five test benches (Refrigerant Cycle Lab, FlexFass, RT-Lab, Raumklimalabor, and InFis). This work focuses on the Refrigerant Cycle Lab. Its concept is based on two further Hardware-in-the-Loop test benches which are extended by a safety system that ensures automated operation dedicated to heat pumps with flammable refrigerants. In two case studies, we show that field tests in the lab allow multi-domain and multi-scale testing. Both aspects support accelerating the transformation process towards a defossilized building sector. In the next step, the combination of test benches at different locations is promising to reduce the need to set up identical experiments at different locations. In the long term, the laboratory is designed to include external stakeholders to avoid time-consuming iterations and can, therefore, save resources, time, and money for our complex transformation process. [Display omitted] • Hardware-in-the-Loop environments for heat pumps handling flammable refrigerants are key for field tests in the lab. • Experiments under quasi-field test conditions push the technology readiness level of conventional testing methods (4–6) towards field tests in the lab (7-8). • Capturing the design and control domain and potential stakeholder interactions in early development stages unlocks the full research potential. • Using pre-defined interfaces, the field test in the lab concept can be used to conduct decentral experiments which safe resources, money, and time. [ABSTRACT FROM AUTHOR]

In many industries, low-carbon hydrogen will substitute fossil fuels in the course of the transformation to climate neutrality. This paper contributes to understanding this transformation. This paper provides an overview of energy- and emission-intensive industry sectors with great potential to defossilize their production processes with hydrogen. An assessment of future hydrogen demand for various defossilization strategies in Germany that rely on hydrogen as a feedstock or as an energy carrier to a different extent in the sectors steel, chemicals, cement, lime, glass, as well as pulp and paper is carried out. Results indicate that aggregate industrial hydrogen demand in those industries would range between 197 TWh and 298 TWh if production did not relocate abroad for any industry sector. The range for hydrogen demand is mainly due to differences in the extent of hydrogen utilization as compared to alternative transformation paths for example based on electrification. The attractiveness of production abroad is then assessed based on the prospective comparative cost advantage of relocating parts of the value chain to excellent production sites for low-carbon hydrogen. Case studies are provided for the steel industry, as well as the chemical industry with ethylene production through methanol and the production of urea on the basis of ammonia. The energy cost of the respective value chains in Germany is then compared to the case of value chains partly located in regions with excellent conditions for renewable energies and hydrogen production. The results illustrate, that at least for some processes – as ammonia production – relocation to those favorable regions may occur due to substantial comparative cost advantages. • Industry transformation: fossil fuels to hydrogen as feedstock and energy carrier. • Case study on Germany with hydrogen demand for industry. • Value chains: steel production, ethylene with methanol, and urea with ammonia. • Comparative cost advantage in value chains for locations with different renewable costs. [ABSTRACT FROM AUTHOR]

The EU has established the world's first cross-border emission-trading systems (ETS) for greenhouse gas (GHG) emissions, currently covering aviation, emission-intensive sectors, and electricity (EITE). The EU Commission has offered to apply emissions trading in new sectors where emissions from maritime transport will be incorporated into the current EU ETS, while a separated emissions trading system will cover emissions from road transport and the building sector. This paper employs a multi-regional multi-sectoral computable general equilibrium (CGE) model with two simultaneous international emission permit markets. After examining the abatement costs for the EU regions, various policy scenarios are implemented to study the welfare effects of forming an ETS covering the sectors other than EITE (NEIT) and its linking with the EITE sectors under two different baselines and four emission reduction targets. The results provide several important insights: (i) Marginal abatement costs in Germany and the Eastern European Union region (EEU) are significantly lower than in the rest of the EU regions. (ii) The carbon price in the emission permit market covering NEIT is significantly higher than the carbon price in the emission permit market covering EITE. (iii) Germany and EEU appear as notable suppliers of emission permits in both markets. (iv) There is a significant aggregate welfare gain under the scenario in which the ETS covering NEIT co-exists parallel with the ETS covering EITE. (v) The aggregate welfare in the EU under the full integration of EITE and NEIT may fall below its value under the scenario with two parallel emission permit markets. [ABSTRACT FROM AUTHOR]

In this paper are presented results of tests and analyses of complex dynamic loads carried out on the bucket-wheel excavator SchRs 650/5 × 24 Krupp, as well as assessment of service life of vital welded structures of a bucket-wheel excavator boom subjected to cyclic loading with a variable amplitude through the use of experimental tests carried out in order to determine operational strength and growth of a fatigue crack for one structural part. Bucket-wheel excavator was built by "Thyssen Krupp" company, Germany. Outer loads, or in other words digging forces for the overburden and coal have been calculated on the basis of measured values of actual current intensity of the bucket-wheel drive and recorded output values of changeable loads. Correlations between the power of the bucket-wheel drive system and adequate hourly production, depending on the overall digging resistance which affects the stress condition of the bucket-wheel, were also determined. Results of the theoretical and experimental analysis of natural and forced oscillations of the support structure for various exploitation conditions are presented in first part of the paper. Deformations ε i determined by tensometric measurements on the rotating shaft of the bucket-wheel were converted into tangential stresses through the introduction of the modulus of elasticity and Poisson's ratio, which, along with the polar moment of inertia of the cross-section, define the moment of rotation on the bucket-wheel shaft. Through the use of the load - strength comparison method (maximization of the ratio of load and strength indicators) the application factor of the gear with the largest number of turns K A has been determined. In the second part of the paper methodological approach for the assessment of service life of vital welded structures of a bucket-wheel excavator boom was presented. Assessment was done in order to determine operational strength and growth of a fatigue crack, through the use of experimental tests. Realized researches and results presented in this paper offer great possibilities for the analyses of behaviour of vital welded structures of the bucket-wheel boom. By the application of the measurement device with 8 channels for registration and processing of electric signals HBM Spider 8 and measurement tapes HBM 6/350 × XY31 deformations were measured at vital welded structures of the boom in the area of the bucket-wheel. The objective of the test is to determine if there is a possibility of occurrence of plastic deformations or initial cracks due to fatigue at vital welded structures and to obtain data which define crack growth. • Specific digging resistances per knife at highest loads are 20% higher than the average value for overall measurements. • Hourly production N(Q e) show that the bucket-wheel excavator during operation cannot reach the designed capacity of Q t =4212 [m3/h]. • Determined application factor K A =1.6 is smaller than the one prescribed in standards for the gearbox of the excavator drive (K A =1.75-2.0). • In exploitation there is a possibility of the occurence of resonance due to their matching, and therefore of the occurence of damaging of critical cross-sections. • Fracture mechanics parameters have shown that the service life of the welded structure if a new edge crack occuris 4.55 years. [ABSTRACT FROM AUTHOR]

Pedestrian permeability is a key aspect of the accessibility of urban environments. In particular, high permeability increases the walkability of cities, which is advocated by sustainable urban design practices. Previous research on pedestrian permeability has predominantly focused only on single and very specific, characteristic, and homogenous urban morphologies but investigations at a broader scale have not been conducted up to now. In this paper, we apply the concept of Individual Walkable Neighbourhoods (IWN) to measure local urban pedestrian permeability for all large cities in Germany with more than 100,000 inhabitants. Our results reveal great differences in intra- and inter-urban pedestrian permeability, and based on examples, we explore various factors that influence local permeability, such as topography or structural types. Furthermore, the large-scale analysis is used to identify characteristic patterns of high (e.g., urban centers) or low (e.g., neighbourhoods of single-family detached houses) permeability for German cities. • Permeability is dependent on morphological urban patterns. • There is a strong permeability-gradient between urban centers and the periphery. • Topography has a strong influence on permeability. • Barriers such as railways can half the range of movement without connections. [ABSTRACT FROM AUTHOR]

In this paper, we explore the possibility of connecting decentralized biogas plants via a pipeline network to terminals that upgrade biogas into biomethane. We present a mixed-integer linear program that forms subnetworks of such plants, decides on suitable terminal locations, and establishes pipeline connections to maximize profit. We apply this model to a real-world scenario in Northern Germany. The results show a much higher total profit for the optimized network compared to the benchmark solutions where each plant upgrades biogas into biomethane on its own. Therefore, plants can increase their profitability by collaborating with other (neighboring) plants. However, the collaboration requires a fair profit-sharing model as network participation is not individually profitable for all plants, especially small ones. • We explore network designs for a profitable upgrading of biogas into biomethane. • We introduce a Mixed Integer Programming model to determine optimal plant networks. • A real-world application for biogas plants in Northern Germany is presented. • Results reveal higher profits for the networks compared to stand-alone upgrading. • Fair profit-sharing mechanisms are important for plant collaborations. [ABSTRACT FROM AUTHOR]

This paper examines the emergence of 1,072 solar initiatives (268 associations and 804 cooperatives operating photovoltaic systems) from 2006 to 2018 in Germany. The study draws on organizational ecology theory to identify factors that influence the likelihood of establishing a solar initiative by investigating the impacts of two opposing effects: legitimation effects and competition effects. We show that the density of medium-scale photovoltaic installations in a district negatively affects the likelihood of establishing a solar initiative, suggesting that competitive dynamics prevail between different market entrants, dampening the emergence of solar initiatives. By contrast, we find that the founding of a solar initiative in a district has a positive effect on the probability of founding other solar initiatives in the same district, confirming legitimacy effects. Further, we show that solar initiatives are more likely to be founded in rural areas, especially in densifying rural areas. • Citizens collectively install PV systems where there are fewer similar systems present. • Initiatives are more likely to emerge in districts with existing initiatives. • Initiatives emerge primarily in densified rural areas. • Enhancing organizational rather than technological knowledge is important. [ABSTRACT FROM AUTHOR]

In this paper, a multi-step framework to design flexible power-to-methane processes is presented. The approach considers all crucial parts of the power-to-methane process, including the renewable energy source. The aim is to provide a design that allows for feasible operation under the fluctuating conditions induced by the renewable energy source at all times. For each part of the process, the operating windows are analyzed and optimized under different site-specific constraints, and recommendations for actions regarding the technical implementations are provided. The impact of the carbon dioxide source is scrutinized, and subsequent scheduling optimization is performed to determine necessary storage capacities. The framework is demonstrated on two carbon dioxide availability scenarios where the renewable energy source is a wind turbine coupled to a polymer exchange membrane electrolyzer that produces hydrogen, which is then converted to methane in a fixed-bed reactor. The results show that the feasible operation of the system strongly depends on the site-specific conditions. In particular, the availability of carbon dioxide impacts the flexibility of the methanation reactor. When the stochiometric ratio between hydrogen and carbon dioxide cannot be sustained, the operating window of the reactor deteriorates significantly. However, it is shown that appropriate integration and scheduling of storage capacities debottlenecks the reactor and enables the utilization of all electricity generated by the wind turbine. • A framework for the design of flexible power-to-methane systems is introduced. • Optimization approaches for each step of the framework are provided. • A dynamic optimization approach for storage integration is given. • The impact of the carbon dioxide provision flexibility is investigated. • The framework is tested in a case study with an onshore wind turbine in Germany. [ABSTRACT FROM AUTHOR]

• Soil reflectance composites were generated with Sentinel-2 L2A data. • A multi-channel CNN learning framework for soil organic carbon prediction is proposed. • A dual input deep learning architecture improves the predictions. • The framework produced results that can be interpreted. The Copernicus Sentinel-2 multispectral imagery data may be aggregated to extract large-scale, bare soil, reflectance composites, which enable soil mapping applications. In this paper, this approach was tested in the German federal state of Bavaria, to provide estimations for soil organic carbon (SOC). Different temporal ranges were considered for the generation of the composites, including multi-annual and seasonal ranges. A novel multi-channel convolutional neural network (CNN) is proposed. By leveraging the advantages of deep learning techniques, it utilizes complementary information from different spectral pre-treatment techniques. The SOC predictions indicated little dissimilarity amongst the different composites, with the best performance attained for the six-year composite containing only spring months (RMSE = 12.03 g C · kg−1, R2 = 0.64, RPIQ = 0.89). It has been demonstrated that these outcomes outperform other well-known machine learning techniques. An ablation analysis was accordingly performed to evaluate the interplay of the CNN's different components to disentangle the advantages of each aspect of the proposed framework. Finally, a DUal inPut deep LearnIng architecture, named DUPLICITE, is proposed, which concatenates deep spectral features derived from the CNN mentioned earlier, as well as topographical and environmental covariates through an artificial neural network (ANN) to exploit their complementarity. The proposed approach was demonstrated to provide an improvement in the overall prediction performance (RMSE = 11.60 gC · kg−1, R2 = 0.67, RPIQ = 0.92). [ABSTRACT FROM AUTHOR]

To mitigate climate change, individual greenhouse gas emissions need to decline substantially. This paper empirically explores the relationship between individual carbon footprints and carbon literacy as well as socio-economic and attitudinal factors. To operationalize carbon literacy, we distinguish between carbon knowledge and carbon engagement. Our econometric analysis uses widely representative survey data for 1000 individuals in Germany and distinguishes between components of an aggregate carbon footprint and of carbon footprints related with electricity consumption, heating, motorized individual transport, aviation, and dietary choices. We find a negative and sizeable correlation between carbon engagement and the aggregate footprint, as well as the footprints related to electricity consumption and diet. For example, a one-unit increase in our index reflecting carbon engagement corresponds to a decrease in the aggregate carbon footprint of about 4%. Furthermore, for carbon knowledge we find a negative correlation with the carbon footprint from diet. We also find significant correlations between the carbon footprints and gender, age, income, education, environmental preferences, and policy orientation, which generally exhibit the intuitively expected signs, but differ somewhat across activities. Overall, our findings support the notion that fostering carbon engagement represents a more effective strategy for reducing individuals' carbon footprints than enhancing carbon knowledge. • We study the relationship between carbon literacy and carbon footprints. • We break down carbon literacy into carbon knowledge and carbon engagement. • Individual-level carbon footprints calculated from representative data in Germany. • Carbon footprints calculated for electricity use, heating, transport, and diet. • Econometric findings stress role of carbon engagement for carbon footprints. • Carbon footprints are correlated with socio-economic factors and policy orientation. [ABSTRACT FROM AUTHOR]

Caroli Disease (CD) and Caroli Syndrome (CS) are rare disorders presenting with dilation of the intrahepatic bile ducts. CD/CS are associated with cholangiocarcinoma (CCA). However, the true incidence of CCA is still unclear, although it may serve as an indication for surgery. In this paper, we analyzed (I) the incidence of CCA in German centers, (II) reviewed our single center population together with its clinical presentation and (III) performed a thorough literature review. 17 large HPB-centers across Germany were contacted and their patients after surgical treatment due to CD/CS with histopathology were included. Medline search for all studies published in English or German literature was performed. Patients who underwent surgery at our department between 2012 and 2020 due to CD or CS were analyzed. In the multicenter study, 79 patients suffered from CD and 119 patients from CS, with a total number of 198 patients. In 14 patients, CCA was found (Overall: 7,1%; CD: 6,3%, CS 7,6%). Between 2012 and 2020, 1661 liver resections were performed at our department. 14 patients underwent surgery due to CD or CS. Histological examination showed synchronous cholangiocarcinoma in one patient. The literature review revealed a CCA-rate of 7,3% in large series, whereas in case reports a rate of 6,8% was found. There is risk of malignant transformation and patients with CD might also benefit from resection due to improvement of symptoms. Therefore, resection is strongly advised. As certain patients with CS require transplantation, treatment should not be guided by the relatively low rate of CCA but by the concomitant diseases that come along with hepatic failure. [ABSTRACT FROM AUTHOR]

• Travel demand generator for anywhere in Germany. • Open-source and requires only OpenStreetMap data as input. • Output is wholly disaggregated spatially and temporally. • Validated with household travel survey data. • Architecture designed for transferability to other regions. This paper introduces OMOD (OpenStreetMap Mobility Demand Generator), a new open-source activity-based mobility demand generation tool. OMOD uses a data-driven approach, calibrated with household travel survey data, to generate a population of agents with detailed daily activity schedules that state what activities each agent plans to conduct, where, and for how long. The temporal aspect of the output is wholly disaggregated, while the spatial aspect is given on the level of individual buildings. In contrast to other existing models, OMOD is freely available, open-source, works out-of-the-box, can be applied to anywhere in Germany with the ambition to widen the scope to other countries, and only requires freely available OpenStreetMap (OSM) data from the user. With OMOD, it is easy for non-experts to create realistic mobility demand, which can be used in transportation studies, energy system modeling, communications system research, et cetera. This paper describes OMOD's architecture and validates the model for three cities ranging from 200,000 to 2.5 million inhabitants. [ABSTRACT FROM AUTHOR]

Increasing the efficiency of production is the basis for decoupling economic growth from resource consumption. In agriculture, more efficient use of natural resources is at the heart of sustainable intensification. However, technical improvements do not directly translate into resource savings because producers and consumers adapt their behaviour to such improvements, often resulting in a rebound effect, where part or all of the potential resource savings are offset. In extreme cases, increases in efficiency may even result in higher, instead of lower, resource consumption (the Jevons paradox). Rebound effects are particularly complex in agricultural land and soil management, where multiple resources are used simultaneously and efficiency gains aim to lower the need for farmland, water, energy, nutrients, pesticides, and greenhouse gas emissions. In this context, quantification of rebound effects is a prerequisite for generating realistic scenarios of global food provision and for advancing the debate on land sparing versus land sharing. However, studies that provide an overview of rebound effects related to the resources used in agriculture or guidelines for assessing potential rebound effects from future innovations are lacking. This paper contributes to closing this gap by reviewing the current state of knowledge and developing a framework for a structured appraisal of rebound effects. As a test case, the proposed framework is applied to emerging technologies and practices in agricultural soil management in Germany. The literature review revealed substantial evidence of rebound effects or even Jevons' paradox with regard to efficiency increases in land productivity and irrigation water use. By contrast, there were few studies addressing rebound effects from efficiency increases in fertilizer use, pesticide application, agricultural energy use, and greenhouse gas emissions. While rebound effects are by definition caused by behavioural adaptations of humans, in agriculture also natural adaptations occur, such as resistance of pests to certain pesticides. Future studies should consider extending the definition of rebound effects to such natural adaptations. The test case revealed the potential for direct and indirect economic rebound effects of a number of emerging technologies and practices, such as improved irrigation technologies, which increase water productivity and may thereby contribute to increases in irrigated areas and total water use. The results of this study indicated that rebound effects must be assessed to achieve realistic estimates of resource savings from efficiency improvements and to enable informed policy choices. The framework developed in this paper is the first to facilitate such assessments. [ABSTRACT FROM AUTHOR]

Abstract Having a noticeable role in CO 2 sequestration and O 2 production, microalgae as precious sources of the third-generation biofuel, offer various advantages for energy efficient architecture. Although biofuel production from microalgae biomass has a considerable research background, integrating microalgae culture system with building façade is in its infancy. It is mainly due to the fact that there is only one real building named BIQ house adopting the bioreactor façade technology constructed in Germany, 2013. Hence, there are various challenges associated with this newly emerged technology. This paper aims to detect and estimate the probable causes of damage to microalgae photobioreactor panels integrated with building façade known as SolarLeaf. In order to realize the paper key objective, by comprehensively studying the literature review, surveying and interviewing with the experts, the factors causing damage to bioreactors were recognized and categorized. Based on the results, the main damages are classified as internal and external. Internal causes include bio/chemical and structural factors, while external ones involve climatic and operational/constructional ones. These are the fundamental damage categories of microalgae façade systems that architects and engineers should get familiar with in order to meet and consider the defects developed in the bioreactor panel structure during the design and construction process. Highlights • Microalgae as precious sources of the third-generation biofuel, offer various advantages for energy efficient architecture. • This paper aims to detect and estimate the probable causes of damage to microalgae photobioreactor panels integrated with building façade known as SolarLeaf. • The main damages are classified as internal and external. Internal causes include bio/chemical and structural factors, while external ones involve climatic and operational/constructional ones. • Architects and engineers should get familiar with in order to meet and consider the defects developed in the bioreactor panel structure during the design and construction process. [ABSTRACT FROM AUTHOR]

Abstract Our society faces a carbon dilemma whereby there is an imbalance between our need for carbon and the dark side of its utilization. Unlike electricity, heat and mobility sectors where a transition towards renewable energy sources is possible, the chemical industry has no alternative to carbon sources for its production. This paper carried out a case analysis of the German chemical industry. The objective is to identify challenges posed by the human dimension for its carbon transition from a dependence on imported carbon resources towards cleaner and sustainable production using domestic primary and secondary carbon feedstock alternatives. Findings from a representative survey study carried out in Germany in October 2017 showed widespread public misconceptions regarding what are carbon sources and a lack of mental associations regarding the use of domestic biomass, coal, waste and CO 2 as feedstock alternatives for chemical production. Furthermore, significant regional difference in support/resistance for coal-to-chemicals as a carbon transition route is also observed. This paper represents a first effort to bridge the gap between transition and circular economy research to facilitate the early identification of human-related barriers to a carbon transition for the chemical industry. Highlights • A carbon transition for the chemical industry from a dependence on imported carbon resources to using domestic carbon feedstock alternatives. • Case analysis of the German chemical industry. • Overview of biomass, coal, waste and CO 2 as domestic chemical feedstock alternatives and policy drivers and obstacles for different options. • Public awareness, perception and acceptance of domestic carbon resources as feedstock alternatives for the chemical industry. • Early identification of human-related barriers to a carbon transition for the chemical industry. [ABSTRACT FROM AUTHOR]

Germany remains the only large country in the world without a general speed limit on highways. One of the main arguments for this policy is that lower speeds represent a travel time cost that is not outweighed by benefits, such as a reduction in greenhouse gas emissions. As transport decision making in the European Union is based on cost-benefit analysis (CBA), this paper compares the value of travel time, fuel consumption, infrastructure, crashes, carbon dioxide (CO 2), and air pollution. Results suggests that, at the low end of the estimate, a 130 kph speed limit will generate welfare gains in the order of 950 million Euro per year. The 'no speed limit' policy consequently represents a subsidy forwarded to fast drivers. The paper also discusses the views of the public vis-à-vis automobile lobbies, and the relevance of Germany's climate change mitigation law, mandating that transport systems be decarbonized. The CBA suggests that a 130 kph speed limit is a policy field where environmental concerns, positive economic effects, and public opinion can be aligned. [ABSTRACT FROM AUTHOR]

This study assesses alternative energy technologies (i.e., PV and battery systems, electric heat pumps, hybrid gas heating with solar thermal energy) in terms of profitability and CO 2 emissions, for the case of two simulated typical households living in detached houses in Germany. Under the status-quo regulatory framework, the energy transition in the heating sector is fostered through grants for replacing old heating systems, whereas PV generation is fostered by feed-in tariffs and indirect subsidies for self-consumption. This study considers an alternative regulatory scenario with a more market-oriented approach, finding that a CO 2 -oriented reform of energy surcharges and taxes, as well as a reform of network charges, can support a more cost-efficient energy transition in the residential sector. The paper concludes with a discussion of the consistency, cost efficiency and effectiveness of past and current policies underpinning the energy transition in the residential sector. • Assessment of home energy systems across 2 households and 2 regulatory scenarios. • Consideration of PV, batteries, heat pumps and hybrid gas-solar heating systems. • Comparison of subsidies and flat energy tariffs vs. cost-reflective, dynamic tariffs. • Market-oriented approach incentivizes far more cost-efficient CO 2 emission reduction. • The German residential energy sector needs a consistent regulatory framework. [ABSTRACT FROM AUTHOR]

A key policy instrument to conserve biodiversity in agricultural landscapes are agri-environment schemes (AES). AES typically incentivise specific conservation measures which are independent of a specific state of an ecosystem or a species. In this paper we take up the idea of state-dependent conservation measures which means that in each period of interest the decision about the design of the conservation measure is made dependent on the state of the ecosystem or the species of interest. We develop a modelling framework to compare the cost-effectiveness of AES which incentivise state-dependent conservation measures (AES-SD) with AES which incentivise state-independent conservation measures (AES-SI). We apply the framework to a case study of meadow bird conservation through specific mowing regimes in the Aller river valley in Germany, and compare an AES-SI with fixed mowing dates and an AES-SD with mowing dates depending on the phenological start of spring. We find that AES-SD substantially outperforms AES-SI. Cost-effectiveness gains arise as the connection of mowing dates to phenological events increase the breeding success of the meadow birds but also as farmers accept slightly lower compensation payments as mowing in dependence of the state of the grassland reduces fluctuations in their fodder yields. • We analyse the cost-effectiveness of state-dependent AES. • The design of state-dependent AES depends on the state of the ecosystem. • State-dependent conservation is known in conservation planning but new to AES design. • We design a state-dependent AES for meadow bird conservation in Germany. • We show that cost-effectiveness gains of a state-dependent AES can be substantial. [ABSTRACT FROM AUTHOR]

Organic food contributes to environmental sustainability and is becoming increasingly popular worldwide, although it is generally more expensive than conventionally produced food. Rather different sets of values and motivations are driving consumers' purchase intentions in mature compared with emerging organic food markets. To inquire about similarities and differences in consumers' motives our qualitative, comparative study employs a series of in-depth interviews with organic-food-store clients in Germany and Thailand from February to May 2021. The analysis applied means-end chain (MEC) theory to map the mental decision-making processes. Results were interpreted and compared referring to the Schwartz Theory of Basic Human Value (STV). The findings show a rather similar values base of both samples in terms of the relevance of 'quality of personal life' and 'personal well-being'. Substantial differences emerged in the Germans high emphasis on the values 'health of environment' and 'social responsibility' which were absent in Thailand, while Thais put great importance on the 'responsibility for family'. Focusing on the five most important values in each country, we conclude a more personal-focused value system in Thailand, respectively a rather social-focused one in Germany. This paper contributes to the literature as it is one of the few qualitative studies on organic food purchase intention using MEC and STV and the first one conducted in Thailand. The findings provide valuable insights for producers and marketers to better address German and Thai consumers' needs to influence their purchase intention towards organic food consumption. • Germans have a more social-focused value system when buying organics. • Thais have a more personal-focused value system when buying organics. • Similar values base: 'quality of personal life' and 'personal well-being'. • Germans emphasize 'health of environment' and 'social responsibility'. • Thais prioritize 'responsibility for family'. [ABSTRACT FROM AUTHOR]

This paper presents a new service development process model for transport services for the inclusion of wheelchair users. In line with the principles of Universal Design, the new model aims to develop services for the widest possible range of users, including people using wheelchairs. The model is based on existing models, case studies in Brazil and Germany, and complemented with specific support material regarding wheelchair users, ultimately devised to guide the development of services that include such users. The paper illustrates a demonstration of the model in a real situation in Germany, with the development of a service for wheelchair users where early consideration of their needs results in clear benefits. [ABSTRACT FROM AUTHOR]

Low carbon transitions have been predominantly analysed using quantitative methods, mostly building on present and forecasted data of social metabolism. This paper addresses both the economic and social dimensions of low carbon emissions by analysing the presence of socio-environmental conflicts in Germany. These conflicts appear to be a consequence of unsustainable policies targeting firms' planning and behaviour, mainly based on neoclassical economic thinking and various stakeholder groups that oppose carbon intensive businesses. By applying a Delphi Method with 18 experts, the authors analyse 117 socio-environmental conflicts (e.g. derived from extractive activity, energy production, and infrastructure projects) in Germany. Most of these conflicts include the struggle of various society groups to achieve a low carbon economy but also a more equitable society. The analyses presented in this paper shows that Germany provides both the best and the worse of achieving low carbon paths: a significant investment into renewable energy, but also a strong dependency on lignite which supplies the most polluting power stations of Europe. By addressing the problem from a historical perspective, the authors demonstrate how carbon intensive extractive activity has been one of the major causes for environmental activism and protest in both socialist and capitalist societies. [ABSTRACT FROM AUTHOR]

Finding alternative phosphorus sources is imperative to address negative environmental and societal impacts caused by its current inefficient use. However, the direct use of phosphorus in sewage sludge in agriculture is controversial. This paper uses Denmark, Germany, and Spain as case examples to assess relevant legislation and boundary conditions in agricultural production to identify opportunities and barriers for the utilisation of recycled phosphorus from wastewater in agriculture on a regional level. Only five out of 22 phosphorus recycling technologies considered were in full compliance with legislation across all three countries, and these five were then assessed for their potential to supply phosphorus to major crops within countries. We considered the application of technologies across four scenarios: 1) struvite; 2) vivianite as iron supply; 3) vivianite for calcium phosphate precipitation; and 4) ashes for calcium phosphate precipitation. The most suitable scenario identified for Denmark was vivianite for calcium phosphate precipitation, whereas in Spain vivianite as iron supply was identified as most suitable, and ashes for calcium phosphate in Germany. We found that in 2018, the potential phosphorus supply from recycling technologies was on average 0.38, 0.29 and 0.05 kg of phosphorus per capita for Danish, German, and Spanish regions. These quantities could meet 9.1, 21.7, and 10.0 percent of the phosphorus required to produce major cereals in each country (specifically wheat, barley, and rye). Given current legal constraints, wastewater treatment plant connections and agronomic context, the potential contribution of recycled phosphorus is non-negligible in many sub-national regions. Still, to access the full potential of phosphorus circularity clear product specifications and transport and logistics among regions will be necessary. [ABSTRACT FROM AUTHOR]

Digital Twins (DTs) provide a promising solution for the maintenance and operation of bridges, thanks to their ability to mirror physical/structural conditions. A bridge DT generally consists of a geometric-semantic model whose creation, however, requires extensive manual effort. This paper presents an automated framework to generate the parametric model of bridges from their segmented point clouds. Following the concept of reverse engineering with parametric modeling, Parametric Prototype Models (PPMs) are proposed as tools to extract parameter values from point clouds. A local and global optimization problem is defined to adjust and assemble PPMs into an integrated model. The proposed approach has been validated by applying it to the point cloud of bridge components as well as point clouds captured from six concrete bridges in Bavaria, Germany. The results show that the proposed approach can generate the parametric model of bridges with a mean absolute error (MAE) of 8.71 cm. • A reverse engineering approach is proposed for the parametric modeling of bridges. • Parametric Prototype Models (PPMs) are introduced to describe bridge point clouds. • Local and global optimization problems are defined to adjust and assemble PPMs. • Metaheuristic optimization algorithms are utilized to derive parameter values. • The method is validated with the point cloud of six bridges in Bavaria, Germany. [ABSTRACT FROM AUTHOR]

The increase of electric vehicles (EVs) in the power system, in addition to environmental benefits, also has economic advantages. Charging parking lots can perform better economically through aggregators the benefits of participating in energy markets and developing different charging programs. The main challenge for participating in the electricity market for parking lots is the uncertainties in the behavior of EV owners and the day-ahead market (DAM) price. Therefore, this paper proposes a deep learning-based framework for day-ahead optimal charging scheduling, which is in three stages. In the first stage, the parameters of charging sessions are modeled using the proposed Copula generative adversarial network (CopulaGAN). In the second stage, the DAM price is forecasted using the time series multi-input nonlinear autoregressive neural network for 24 h ahead. In addition, in the proposed framework, the balancing energy market (BEM) is used to keep the charging power balance on the implementation day of the optimal charging program. In the third stage, optimal day-ahead EV scheduling is performed. The simulation is carried out using Grey Wolf Optimization (GWO) based on the Caltech charging sessions dataset and the Germany energy market dataset. The simulation results show that using the proposed deep learning framework reduces the charging cost for the parking lots compared to the fixed price approaches, the use of the BEM, the time of use (TOU) program, and using normal distribution modeling about 19.94 €, 159.97 €, 14.27 €, and 114.03 € respectively. • Presenting a deep learning framework for modeling day-ahead scheduling. • The proposed framework is applied to Caltech and the German energy market dataset. • Results show a 15% reduction in charging costs compared to conventional methods. [ABSTRACT FROM AUTHOR]

With its strong ties to the European Union, Germany is well-positioned to assist many countries achieve sustainability goals. Therefore, the main objective of this paper is to examine how renewable energy intensity and renewable energy share improve environmental sustainability, the load capacity factor (LCF) in Germany from 1970 to 2018. To this end, the study uses the autoregressive distributed lag model, with the effects of the Kyoto Protocol included as a dummy variable. The study contributes to the literature by considering and testing for the first time the impact of renewables on the LCF in terms of intensity and share for Germany. The empirical results show that (i) economic growth lowers the LCF faster in the early stages of economic development than in later periods; therefore, the environmental Kuznets curve hypothesis is valid in Germany. (ii) A 1% upsurge in renewable energy intensity has no statistically significant effect on the LCF, while a 1% rise in the share of renewables in the total energy mix increases LCF by 0.48%. (iii) A 1% rise in urbanization reduces the LCF by 6.52%. (iv) A 1% augment in human capital enhances the LCF by 3.49%. These outcomes suggest that the German government should use human capital development and increasing the share of renewable energy as policy instruments to achieve the sustainable development goals. [Display omitted] • The EKC hypothesis is valid for Germany. • Renewable energy intensity has no influence on the load capacity factor. • A higher renewable share in the energy mix is associated with an improvement in LCF. • Human capital plays a key role in solving environmental challenges. • The urbanization process has a devastating effect on the environment. [ABSTRACT FROM AUTHOR]

• Economic efficiency of various imported e-fuels for heavy-duty transport in different scenarios for the year 2035 has been evaluated. • E-fuels considered are Fischer-Tropsch diesel, methanol, and hydrogen transported as cryogenic liquid or in form of liquid organic hydrogen carriers. • We develop a mathematical model that covers the entire process chain. • The choice of production site has a major impact on the mobility cost using the respective fuels. The transformation of economies worldwide towards climate neutrality will require not only renewable electricity but also climate-neutral energy carriers such as hydrogen and its derivatives. The production cost of electric fuels (e-fuels) are to a large extent driven by the energy-intensive electrolytic water splitting. The option of producing e-fuels in highly industrialized countries, as Germany, competes with production at international locations, with excellent conditions for renewable energies and thus very low levelized cost of green hydrogen and its derivatives. In this paper, we examine the economic efficiency of various imported e-fuels that are under consideration in different scenarios for the year 2035: Fischer-Tropsch diesel, methanol, and hydrogen transported as cryogenic liquid or in form of liquid organic hydrogen carriers. We develop a mathematical model that covers the entire process chain, from the production of the e-fuels at various excellent locations worldwide to the energetic utilization of the fuels in a heavy duty vehicle. We find that the choice of production site has a major impact on the mobility cost using the respective fuels. Under the selected boundary conditions and assumptions, methanol, cryogenic hydrogen, and liquid organic hydrogen carriers are the most favourable options for all seven locations examined. Which e-fuel is cheapest varies with the production site. Especially in case of diesel, the levelized cost of electricity determined by the full load hours of the applied renewable energy source have a huge impact. An LOHC-based system is shown to be less dependent on electricity source compared to other technologies due to its comparatively low electricity consumption. The length of the transportation route and the price of the filling station infrastructure, however, increase mobility cost for LOHC and LH 2. [ABSTRACT FROM AUTHOR]

• Imported green e-H 2 is more expensive than e-H 2 produced in Germany and Finland. • Local supply of e-H 2 found to be more economical across all scenarios and years. • Transportation costs constitute 29–63% of the total imported e-H 2 cost. • Pipeline transmission may be cheaper than shipping for distances of 2000–2500 km. Widely available and low-cost solar photovoltaics and wind power can enable production of renewable electricity-based hydrogen at many locations throughout the world. Hydrogen is expected to emerge as an important energy carrier constituting some of the final energy demand; however, its most important role will be as feedstock for further processing to e-fuels, e-chemicals, and e-steel. Apart from meeting their own hydrogen demand, countries may have opportunities to export hydrogen to countries with area limitations or higher production costs. This paper assesses the feasibility of e-hydrogen imports to Germany and Finland from two case regions with a high availability of low-cost renewable electricity, Chile and Morocco, in comparison to domestic supply. Special attention is paid to the transport infrastructure, which has a crucial impact on the economic viability of imports via two routes, shipping and pipelines. This study has found that despite lower e-hydrogen production costs in Morocco and Chile compared to Germany and Finland, additional transportation costs make imports of e-hydrogen economically unattractive. In early 2020s, imported fuel costs are 39–79% and 34–100% higher than e-hydrogen produced in Germany and Finland, respectively. In 2050, imported e-hydrogen is projected to be 39–70% more expensive than locally produced e-hydrogen in Germany and 43–54% in the case of Finland. e-Hydrogen may become a fuel that is mostly produced domestically and may be feasible for imports only in specific locations. Local e-hydrogen production may also lower dependence on imports, enhance energy security, and add jobs. [ABSTRACT FROM AUTHOR]

This paper attempts to benchmark the municipal solid waste (MSW) management performance of the NUTS 2-regions in the EU by constructing a composite indicator. In order to account for commensurability, weighting and aggregation issues of the performance indicators in regional waste and materials' management, this paper advocates a conditional directional distance version of the Benefit-of-the-Doubt weighting technique. In addition, the waste management hierarchy defined by the EU is strongly embedded in the construction of our composite indicator. The results reveal considerable differences in the aggregate performance of the regions, even within Member States. In general, waste sectors of the NUTS 2-regions in Austria, Belgium, and Germany generally do well in terms of MSW management. Our results also reveal that some differences in the operating environment of the regions, such as the number of tourist overnight stays, are related to the aggregate performance of the regions. However, the observation that other conditions are not significantly related to the performance on a regional level is interesting as many policy makers frequently argue that the level of performance in their regions cannot be compared to that in other regions precisely due to this difference in operating conditions. [ABSTRACT FROM AUTHOR]

This paper concerns the net effects of promoting renewable energies on value added and disposable income in Germany, as well as their distribution among regions and income brackets. Since its entry into force, the German Renewable Energy Sources Act (EEG) has stimulated tremendous investments in renewable energy capacities by guaranteeing investors a fixed price per kWh as well as a preferred feed into the grid over electricity from conventional sources. The policy measures are financed by a surcharge on electricity prices. In recent years, a controversy has arisen about potentially negative regional and social distribution effects. In this paper, multiregional price and quantity input-output models with endogenous heterogeneous households are used to trace the indirect impacts of the EEG on value added and disposable income through the complex network of regional value chains. Our findings suggest that the generation of electricity from renewable sources itself leads to small positive impacts on industries, but leads to a significant drain on household income and has regressive distributive effects. However, investment in new capacities may possibly transform these negative impacts into a positive direction for the majority of households. [ABSTRACT FROM AUTHOR]

Tackling societal challenges relating to sustainability requires both an understanding of the underlying complex socio-ecological systems and participation of scientists as well as relevant stakeholders, such as practice experts, decision makers, and citizens. This paper introduces the Decision Theatre Triangle, a method which combines empirical information, mathematical modelling and simulation, and a format for dialogue between scientists and stakeholders. While it builds on previous Decision Theatre work, the new structuring into these three elements emphasizes what is needed for setting up a Decision Theatre for a given challenge. Based on experience with a specific example – sustainable mobility in Germany – it is argued that agent-based models are particularly suitable for Decision Theatres and that the method is useful not only for decision support but also for science communication and co-creation of a deeper knowledge of the system under discussion. As a step towards facilitating a broader use of the Decision Theatre Triangle method, the paper then sketches research needs for each of its three elements, with a focus on mathematical modelling and simulation. [Display omitted] • The Decision Theatre Triangle combines data, models, and stakeholder dialogues. • It enables decision support, science communication and co-production of research. • Agent-based modelling shows benefits in the Decision Theatre Triangle method. • Setting up Decision Theatre Triangles for societal challenges needs model structures. [ABSTRACT FROM AUTHOR]

The paper concerns fault-tolerant control of a real battery assembly system which is under a pilot implementation at RAFI GmbH Company (one of the leading electronic manufacturing service providers in Germany). The proposed framework is based on an interval analysis approach, which along with max-plus algebra, allows describing uncertain discrete event system such as the production one being considered in this paper. Having a mathematical system description, a model predictive control-based fault tolerant strategy is developed which can cope with both processing, transportation and mobile robot faults. In particular, it enables tolerating (up to some degree) the influence of these faults on the overall system performance. As a result, a novel robust predictive fault-tolerant strategy is developed that is applied to the advanced battery assembly system. The final part of the paper shows the implementation and experimental validation of the proposed strategy. The proposed approach is tested against single as well as simultaneous faults concerning processing, transportation and mobile robots. [ABSTRACT FROM AUTHOR]

• Multi-modal energy system planning approach to support political decision makers. • Energy sector coupling enables efficient transition pathway to achieve climate goals. • Main drivers: electrification of heat and mobility sectors and use of synthetic fuels. • High impact of the electricity exchange on the operation and costs of the system. In order to reach the goals of the United Nations Framework Convention on Climate Change, a stepwise reduction of energy related greenhouse gas emissions as well as an increase in the share of renewable energies is necessary. For a successful realization of these changes in energy supply, an integrated view of multiple energy sectors is necessary. The coupling of different energy sectors is seen as an option to achieve the climate goals in a cost-effective way. In this paper, a methodical approach for multi-modal energy system planning and technology impact evaluation is presented. A key feature of the model is a coupled consideration of the sectors electricity, heat, fuel and mobility. The modeling framework enables system planners to optimally plan future investments in a detailed transition pathway of the energy system of a country, considering politically defined climate goals. Based on these calculations, in-depth analyses of energy markets as well as electrical transmission and distribution grids can be performed using the presented optimization models. Energy demands, conversion and storage technologies in households, the Commerce, Trade and Services (CTS) area and the industry are modeled employing a bottom-up modeling approach. The results for the optimal planning of the German energy system until 2050 show that the combination of an increased share of renewable energies and the direct electrification of heat and mobility sectors together with the use of synthetic fuels are the main drivers to achieve the climate goals in a cost-efficient way. [ABSTRACT FROM AUTHOR]

• Off-grid Power-to-Fuel systems fit demands for implementing at early market stages. • Excellent wind park sites yield methanol costs of 1.28–1.73 €/l Gasoline Equivalent. • Future electrolyzer costs have high impact on costs, but are still highly uncertain. • Suitable regulatory framework can promote implementing Power-to-Fuel technology. In this paper the integration of systems for the production of electrofuels for a market entrance scenario from a short-term perspective is examined. A model was built to optimize the design parameters and simulate the yearlong operation of an off-grid power-to-fuel system, consisting of a wind park, electrolyzer, hydrogen storage, a CO 2 source and synthesis plant. In this manuscript, the regional focus is Germany; however, the results as well as the methodology can be applied to other regions. Successively, the production costs for the designed system were calculated on the basis of the model results. Various cases for different operational modes and sites have been analyzed. In addition, a sensitivity analysis was made to test the influence of single economic assumptions. Calculations demonstrate that the proposed off-grid systems are a viable option for implementation in a short-term scenario. The results include net production costs of 1.73 €/l GE (GE = gasoline equivalent) for methanol production in the reference case. For optimal wind farm sites, the calculated production costs can drop to 1.32 €/l GE. [ABSTRACT FROM AUTHOR]

Data centers are estimated to have the fastest growing carbon footprint from across the whole information and communication technology (ICT) sector. Evaluating the performance of data centers in terms of energy efficiency and sustainability is becoming an increasingly important matter for organizations and governments (e.g., for regulation or reputation purposes). It nonetheless remains difficult to achieve such evaluation, as data centers imply to take into consideration a wide range of dimensions and stakeholders. Even though a wide range of sustainability performance indicators exist in the literature, there is still a lack of frameworks to help data center stakeholders (spanning from data center owners, governmental regulators to engineers/field operators) to evaluate and understand how a data center performs in terms of sustainable development/behavior. Our research work proposes such a framework, whose originality lies in the combination of state-of-the-art sustainability metrics with the biomimicry commandments of eco-mature system, which enables holistic sustainability assessment of data centres. From a theoretical perspective, the proposed model is designed based on a benefit-cost analysis using the Analytic Hierarchy Process (AHP) technique. This approach allows data center stakeholders for specifying their own preferences and/or expertise in the comparison process, whose practicability is demonstrated in this paper considering three data center candidates, which are respectively located in France, Germany and Sweden. • A new model for comparing data center sustainability performance is proposed. • The model makes use of state-of-the-art sustainability metrics together with biomimicry lessons. • The model is designed based on a benefit-cost approach using the AHP technique. • A comparison study is carried out with three distinct data center candidates. [ABSTRACT FROM AUTHOR]

• Status of MITICA facility. • SPIDER experimentation started. • First scan of plasma light and spectroscopic signals vs RF power and filter field. • SPIDER short-term planning. To reach fusion conditions and control plasma configuration in ITER, a suitable combination of additional heating and current drive systems is necessary. Among them, two Neutral Beam Injectors (NBI) will provide 33 MW hydrogen/deuterium particles electrostatically accelerated to 1 MeV; efficient gas-cell neutralisation at such beam energy requires negative ions, obtained by caesium-catalysed surface conversion of atoms inside the ion source. As ITER NBI requirements have never been simultaneously attained, a Neutral Beam Test Facility (NBTF) was set up at Consorzio RFX (Italy), including two experiments. MITICA is the full-scale NBI prototype with 1 MeV particle energy. SPIDER, with 100 keV particle energy, aims at testing and optimising the full-scale ion source: extracted beam uniformity, negative ion current density (for one hour) and beam optics (beam divergence <7 mrad; beam aiming direction within 2 mrad). This paper outlines the worldwide effort towards the ITER NBI realisation: the main results of the ELISE facility (IPP-Garching, Germany), equipped with a half-size source, are described along with the status of MITICA; specific issues are investigated by small specific facilities and by joint experiments at QST and NIFS (Japan). The SPIDER experiment, just come into operation, will profit from strong modelling activities, to simulate and interpret experimental scenarios, and from advanced diagnostic instruments, providing thorough plasma and beam characterisation. Finally, the results of the first experiments in SPIDER are presented, aimed at a preliminary source plasma characterisation by plasma light detectors and plasma spectroscopy. [ABSTRACT FROM AUTHOR]

The increasingly efficient use of scarce resources is a central theme in the gradual transition towards a circular economy. Hazardous materials represent a category of resources that is often difficult—and potentially risky—to transport, store, or neutralize. As a result, hazardous materials are rarely included in closed material loops. The present paper analyzes HorsePower, a business concept centered around an innovative way of utilizing horse manure. Horse manure is generated in millions of tons in horse-rich countries such as the UK, Germany, and France. It is a hazardous resource, as it may spread diseases, and cannot be disposed of or landfilled economically. The content analysis of 21 semi-structured interviews carried out with different business actors participating in the HorsePower business network reveals that the success of HorsePower stems from its ability to combine the complementary capabilities and material needs of a relatively complex network of business actors including stables, sawmills, logistical service providers, and heat and power plants. Each actor receives added value; the benefits from participation are greater than the sacrifices of participation. Furthermore, the findings show that certain types of hazardous resources, when combined with resources produced by another actor, may be burned efficiently and safely in specific power plants, reducing the need for other types of fuel. The observations imply that novel approaches for effectively sharing ideas and resource needs across organizational boundaries are needed to facilitate the development of additional innovative CE business concepts, leveraging both actor-specific capabilities and intra-actor resource dependencies. [ABSTRACT FROM AUTHOR]

Affecting millions of Europeans, energy poverty is increasingly high on the political agenda. This paper compares space and water heating demand at household level in Germany and in the United Kingdom (UK) between 1991 and 2015. The elasticities of consumption of space and water heating with respect to price, income and heating degree days (HDD) are examined using non-parametric models. Domestic heating consumption is highly elastic with HDD in both countries and HDD elasticities are found to be higher in the UK. From a certain income threshold, heating demand decreases as income increases in German households whereas demand rises with higher incomes in the UK. High price elasticities indicate that UK households are very responsive to energy conservation measures, therefore implying that a pricing policy will effectively reduce heating consumption. However, in Germany, the impact of pricing policies is unclear. Thus, the most effective policy measure to decrease domestic heating consumption in Germany in the long-run should be one which targets improvements of building envelope performance levels. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We used an indicator-based approach to assess river landscape aesthetic quality. • We provide maps and distribution curves for Germany. • Results are compared with other landscape types. • Insights can inform river landscape management and planning. Abstract River ecosystems are widely considered to be of high value for nature conservation. This judgment has been validated for biodiversity and regulating ecosystem services. However, little is known about the role of landscape aesthetic quality (LAQ) of river landscapes compared to other landscapes. The objective of this paper is to assess river landscape aesthetic quality (RLAQ), with an indicator-based approach, and to investigate whether river landscapes deserve special protection because of their attractiveness. We compare RLAQ with the aesthetic quality of other landscapes and explore specific indicators of RLAQ by using GIS and descriptive statistics. The results demonstrate that river courses and adjacent recent floodplains achieve higher LAQ scores than other landscapes of Germany, whereas LAQ of historical riparian zones is rated lower than in other landscapes. This is, mainly, due to the large modification of historical riparian zones. Areas with high RLAQ scores are mostly characterized by rare land cover types and, particularly, high relief diversity. In contrast, low RLAQ scores are found in agglomerations and in intensively cultivated historical riparian zones. RLAQ is an important contribution to multifunctional river landscape development as it supports the public acceptance of renaturation measures. [ABSTRACT FROM AUTHOR]

Abstract Facilitated by the environmental goals set by the government, wind turbines will be one of the main pillars of the future electricity production in Germany. In this paper, a comprehensive assessment of the future metallic raw material requirements for the development of the German wind energy sector was conducted, which is closely based on the current and future market conditions. Copper and dysprosium are identified as the most critical materials since they face the possibility of supply bottlenecks while being fundamental to the functionality of wind turbines. While the cumulative demand for copper may require 0.2% of the current known reserves, the demand for dysprosium may reach up to 0.6% of the reserve levels. Both metals clearly exceed the allocations for renewable energy technologies in Germany and would face strong competition from other sectors in securing raw materials. Although recycling is able to reduce the bottleneck risks, it does not completely mitigate them. More efforts are therefore required to improve material efficiency by means of alternative turbine designs, efficient production techniques, highly reliable components and material substitution. [ABSTRACT FROM AUTHOR]

• Techno-economic analysis of battery storage systems providing frequency control. • A stochastic, data-driven optimisation algorithm to optimise the battery controller. • Use of frequency data and detailed, yet computationally efficient battery models. • Case study of Germany shows the highest margins for a battery rated at 1.6 MW/1.6 MWh. • Calendar ageing drives battery degradation, while cycle ageing has less impact. Optimal investment in battery energy storage systems, taking into account degradation, sizing and control, is crucial for the deployment of battery storage, of which providing frequency control is one of the major applications. In this paper, we present a holistic, data-driven framework to determine the optimal investment, size and controller of a battery storage system providing frequency control. We optimised the controller towards minimum degradation and electricity costs over its lifetime, while ensuring the delivery of frequency control services compliant with regulatory requirements. We adopted a detailed battery model, considering the dynamics and degradation when exposed to actual frequency data. Further, we used a stochastic optimisation objective while constraining the probability on unavailability to deliver the frequency control service. Through a thorough analysis, we were able to decrease the amount of data needed and thereby decrease the execution time while keeping the approximation error within limits. Using the proposed framework, we performed a techno-economic analysis of a battery providing 1 MW capacity in the German primary frequency control market. Results showed that a battery rated at 1.6 MW, 1.6 MWh has the highest net present value, yet this configuration is only profitable if costs are low enough or in case future frequency control prices do not decline too much. It transpires that calendar ageing drives battery degradation, whereas cycle ageing has less impact. [ABSTRACT FROM AUTHOR]

Highlights • A new approach for the calculation of quarter-hourly CO 2eq intensity is presented. • Effects of charging strategies on the environmental impact of BEVs are derived. • Large amounts of CO 2eq emissions are saved by optimizing the charging time. • The temporal variation of CO 2eq intensity in winter is small compared to summer. • The CO 2eq savings potential is significantly greater during the day than at night. Abstract In many countries, the replacement of internal combustion engine vehicles (ICEVs) with battery electric vehicles (BEVs) offers an opportunity to reduce CO 2 equivalent (CO 2eq) emissions in traffic. BEVs have significantly greater energy conversion efficiency from energy storage to wheel (tank-to-wheel [TTW]) and zero tailpipe emissions; these features are in stark contrast to the environmental burdens posed by vehicle production and electricity generation (well-to-tank [WTT]). Since CO 2eq emissions from vehicle use of BEVs account for the majority of the entire life cycle emissions, it is important to closely examine the CO 2eq intensity of electricity generation, which varies based on the sources of energy in the electricity mix of each country and time of day. This paper compares the environmental impact of diesel and electric buses in the city of Aachen throughout their life cycles and analyzes the effects of electricity generation with reference to variation in charging time. Based on recorded driving profiles, the vehicle dynamics of the longitudinal motion are simulated, and the energy demand as a function of the altitude profile and ambient temperature is calculated. The calculation of the quarter-hourly CO 2eq intensity is combined with the vehicle life cycle model in order to examine the effects of electricity generation on BEV life cycle emissions. To analyze the correlation between charging time and BEV environmental impact, different charging scenarios are defined, and CO 2eq savings from replacing ICEVs with BEVs are estimated. Scenario analyses are conducted over both short- and long-term time scales to predict the future environmental and economic benefits and costs of BEVs compared to ICEVs. The results demonstrate a significant dependency of BEV environmental impact on charging time, which varies by time of day and season. At night, the contribution of renewable energies to the electricity mix is low, and the variation in CO 2eq intensity is limited; therefore, the environmental impact of charging time is lower compared to charging at noon. The larger CO 2eq emissions of BEV production are compensated for all scenarios within the first year of operation. However, if BEVs are charged with electricity generated exclusively by lignite-fired power plants, more CO 2eq emissions are released over their lifetimes compared to ICEVs; this scenario also holds when ICEVs are fueled with biodiesel. Overall, the positive environmental balance of BEVs is not based on a low CO 2eq intensity, but on the greater energy conversion efficiency and the possibility of recuperating braking energy. These properties are particularly advantageous in urban traffic. [ABSTRACT FROM AUTHOR]

Abstract In recent years the need to consider the social dimension of sustainability within life cycle thinking has been increasing, catalysing the development of many different social life cycle assessment approaches (sLCA). The demand to assess potential social effects has been strengthened further, due to the implementation of national bioeconomy strategies. The RESPONSA framework (REgional SPecific cONtextualised Social life cycle Assessment) has been developed to assess the social effects associated with wood-based bioeconomy products from Germany (Siebert et al., 2018a; Siebert et al., 2018b). However, a characterisation approach, based on a context-specific benchmark which is easy to understand and interpret, is still missing. In general, characterisation approaches provide meaning to social indicator values (i.e., the inventory data). However, there is no standardised sLCA characterisation method yet. Therefore, the aim of this paper is to outline a characterisation method based on context-specific performance reference points (PRPs), which can effectively reflect the social conditions influencing the various organisations involved in producing a specified product. Such PRPs should also qualify whether the social indicator values collected from the organisations in the production system corresponds to a negative (worse than sector average) or positive performance (better than sector average). Therefore, we considered the classification of economic sector of the assessed organisation and in some cases the size of the organisation as factors influencing the potential social effects related to our particular context. These were then applied to define context-specific PRPs, which relate the social indicators calculated in the inventory phase, to those benchmarks, thus generating relative social performance scores for producers of a wood-based product in Germany. Highlights • A context-specific social LCIA approach was developed for assessing wood-based products from bioeconomy regions. • It considers the organisation's economic sector and size as factors influencing social performance. • Context-specific performance reference points were defined as benchmarks for the social indicators. [ABSTRACT FROM AUTHOR]

In the context of climate change mitigation and sustainable energy infrastructure development, this paper focuses on the successful implementation of microgrids supplied by renewable energies in very diverse environments. Taking into account the challenges of reaching economies of scale, this paper is targeted at identifying success factors for microgrid implementation. The success factors are derived from case study analyses of microgrids implemented in the Global South and in communities of Germany. The goal of the research is to develop a mutual understanding of common values and so support future developments. The analysis covers the categories of ownership and participation; technology and system design; and policy and financing. The results show that microgrids in the Global South and renewable-energy-based communities in Germany share a number of success factors. The results demonstrate that a high share of ownership by users and the flexibility to expand the microgrid with user needs are particularly promising features. To verify the application of the identified success factors, the latter are applied to analyze the microgrid concept of “swarm electrification”. The analysis concludes that the concept of swarm electrification is consistent with the success factors, making it a high-potential approach for renewable-energy-based electrification. [ABSTRACT FROM AUTHOR]

The approach to integrate a fourth-party logistics service provider in the German Agricultural Bulk Logistics sector marks a new concept that aims at achieving sustainable development goals in transportation, i. e., by realising full truck loads. Against the background of steadily growing transport volumes, it is of paramount importance to develop sustainability concepts in order to mitigate the impacts on the environment. At present, the processes in the domain of the German Agricultural Bulk Logistics sector are characterised by bulk transports, small and medium sized actors and paper-based processes, which offers high potential for process optimizations in terms of sustainability. Therefore, the German Agricultural Bulk Logistics sector currently explores the approach of including a fourth-party logistics service provider into its transport processes in order to render these more sustainable and reduce costs. The objective of this paper is to present the general idea of implementing a fourth-party logistics service provider into a transportation (planning) process, to clarify the different functions of the participating parties and to introduce the modified transportation planning process as artefact. By means of a mixed method approach, we deliver qualitative insights based on semi-structured interviews and quantitative insights based on simulations. Effects and benefits of the approach are identified by means of a case study. Involving the fourth-party logistics service provider as well as the associated transportation planning process in the mentioned logistics area can lead to cost savings up to 38%, helps to reduce environmental pollution and mitigates social barriers in form of existential fears. The results demonstrate the applicability of the fourth-party logistics service provider approach in the sector and underline that this approach supports the achievement of sustainable development goals in transportation. Furthermore, we identify sustainable characteristics and present the mixed method approach which functions as an assessment framework for the fourth-party logistics service provider approach. Furthermore, by adopting the documented features of sustainable supply chain management in the fourth-party logistics service provider approach, an additional value is generated. [ABSTRACT FROM AUTHOR]

Target 2, Action 5 of the EU Biodiversity Strategy requests member states “to map and assess ecosystems and their services” (Mapping and Assessment of Ecosystems and their Services – MAES initiative). The objective of this paper is to present and discuss the preliminary outcomes of the approach taken to define indicators for implementing MAES in Germany. The paper introduces the requirements for using indicators from a perspective of nature conservation policy, in particular the need to discern the demand and supply of ecosystem services, including their potentials, actual and future use, as well as the natural contributions and human inputs to the generation of ecosystem services. An adapted, differentiated, ecosystem services terminology is presented and a first set of indicators is introduced and explained. The paper closes with an estimate of potential benefits of information produced by implementation of a national MAES for various fields of policy (e.g. local and regional landscape planning) and proposes some recommendations for further research and practical exploration. [ABSTRACT FROM AUTHOR]

Today's methods for data acquisition usually involve a considerable amount of manual work and, depending on the level of detail, must find a compromise between accuracy and workload. As a result, various typologies of building stocks have been developed. These typologies provide engineers and architects with rough descriptions for classifying buildings into certain periods and construction types. However, real-world applications lack objective decision-making, as these classifications are usually conducted by manual investigations of buildings. To overcome this subjective approach and to ensure the reproducibility of data acquisition, this paper proposes an image-based classification using Deep Learning (DL) methods. We present the acquisition of ground truth and describe the training and testing routines on a dataset of 5,307 images obtained in the city of Weimar (located in the Free State of Thuringia, Germany), a mid-sized city representative of eastern Germany. All building images are linked to an existing building typology, allowing a classification of buildings in ten predefined and acknowledged periods. These periods are ranging from pre-1859 to post-2002. As a benchmark, an expert human baseline is acquired, showing a lower prediction accuracy than the results obtained by DL methods. Our results highlight the potential for automation in image analysis and beneficial impacts for Building Energy Modeling (BEM) on urban scale. Thus, a trustworthy data acquisition regarding the building age holds benefits for various stakeholders in BEM (engineers, architects, policymakers as well as customers). • Two CNN-architectures (ResNet50 and AlexNet) are used for image-classification. • Extraction of annotated image-patches facilitates an enhancement of the image set. • Quantity of training images and applied optimizer significantly influence results. • CNN-based estimations successfully linked to existing and popular building typology. • Accuracies of CNN-based estimation of building age outperform the human baseline. [ABSTRACT FROM AUTHOR]