ALBERT

Description: Ground motion with strong‐velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering. However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood. In this study, we investigate moderate but damaging earthquakes (⁠Mw 6–7) and characterize ground‐motion pulses using the method of Shahi and Baker (2014) while considering the potential static‐offset effects. We confirm that the within‐event variability of the pulses is large. The identified pulses in this study are mostly from strike‐slip‐like earthquakes. We further perform simulations using the frequency–wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike‐slip earthquakes. We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations. Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect. We finally quantify and discuss within‐ and between‐event variabilities of pulse properties at short distances.

Description: The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation–maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motionmodeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motionmodels using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastías and Montalva (2016) with ∼2400 records from 319 events in the Chilean subduction zone. Our GMMwith the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.

Description: Surface heat flow is a geophysical variable that is affected by a complex combination of various heat generation and transport processes. The processes act on different lengths scales, from tens of meters to hundreds of kilometers. In general, it is not possible to resolve all processes due to a lack of data or modeling resources, and hence the heat flow data within a region is subject to residual fluctuations. We introduce the REgional HEAT-Flow Uncertainty and aNomaly Quantification (REHEATFUNQ) model, version 2.0.1. At its core, REHEATFUNQ uses a stochastic model for heat flow within a region, considering the aggregate heat flow to be generated by a gamma-distributed random variable. Based on this assumption, REHEATFUNQ uses Bayesian inference to (i) quantify the regional aggregate heat flow distribution (RAHFD) and (ii) estimate the strength of a given heat flow anomaly, for instance as generated by a tectonically active fault. The inference uses a prior distribution conjugate to the gamma distribution for the RAHFDs, and we compute parameters for a uninformed prior distribution from the global heat flow database by Lucazeau (2019). Through the Bayesian inference, our model is the first of its kind to consistently account for the variability in regional heat flow in the inference of spatial signals in heat flow data. Interpretation of these spatial signals and in particular their interpretation in terms of fault characteristics (particularly fault strength) form a long-standing debate within the geophysical community. We describe the components of REHEATFUNQ and perform a series of goodness-of-fit tests and synthetic resilience analyses of the model. While our analysis reveals to some degree a misfit of our idealized empirical model with real-world heat flow, it simultaneously confirms the robustness of REHEATFUNQ to these model simplifications. We conclude with an application of REHEATFUNQ to the San Andreas fault in California. Our analysis finds heat flow data in the Mojave section to be sufficient for an analysis and concludes that stochastic variability can allow for a surprisingly large fault-generated heat flow anomaly to be compatible with the data. This indicates that heat flow alone may not be a suitable quantity to address fault strength of the San Andreas fault.

Description: The European Commission's REPowerEU plan set the target of importing 10 million tonnes of 'green' hydrogen into the European Union (EU) by 2030. Against this backdrop, this paper sets out to assess a central question: which countries can be identified as suitable partners for European green hydrogen imports? Using Germany as a reference case, the article develops a quantitative sustainability and governance index (SGI), assessing five dimensions identified as central to ranking external partners: (i) the political will to scale up a green hydrogen sector; (ii) a country's integration with the EU/Germany; (iii) its commitment to international engagement and climate targets and policies; (iv) environmental regulatory effectiveness; and, (v) its governance performance. With this, the SGI offers a novel way of thinking about potential EU green hydrogen partnerships. Rather than focusing on the geography of renewables or cost structures underpinning a country's export potential, the present index captures the extent to which countries may be suitable for green hydrogen partnerships if judged by political and environmental factors. The empirical analysis suggests significant differences between a total of 113 assessed countries as per their overall index ranking, but also the individual dimensions composing the index. This allows drawing conclusions on the policy focus of potential partnerships, taking choices when facing trade-offs regarding individual dimensions, and prioritizing among the latter.

Description: This article examines limits to per capita living space (i.e. living smaller and/or sharing living space) as a measure for achieving sufficiency in housing. It studies the acceptance, motivation and side-effects of voluntarily reducing living space in five European Union countries: Germany, Hungary, Latvia, Spain and Sweden. Insights are derived from an extensive collection of qualitative empirical material collected from citizen and stakeholder ‘thinking labs’ across the five case countries. Overall, the data reveal an initial reluctance among citizens to reduce living space voluntarily. They also point to some major structural barriers: the housing market and its regulatory framework, social inequality, or dominant societal norms regarding ‘the ideal home’. Enhanced community amenities can compensate for reduced private living space, though contingent upon a clear allocation of rights and responsibilities. Participants also reported positive effects to living smaller, including increased time for leisure activities and proximity to services. This was often coupled with urbanization, which may also be part of living smaller in the future.

Description: A rapid and full decarbonisation of both energy and industry is essential to meet the targets in the Paris agreement, which brings coal- and carbon-intensive regions under significant pressure. Some regions have advanced in their transition and can provide insights in the system change processes. In this paper, we investigate the socio-economic transition processes of Essen and Duisburg as part of the wider structural change in the Ruhr Region/ Germany. We explore causes and effects of their trajectories in the last 30 + years and identify differences in outcome as a function of the interventions and/or contextual differences, while investigating whether either city crossed a tipping point in their transition process (yet). Therefore, we specifically evaluate the cities’ development trajectories by seeking evidence for “no”, “incremental” or “radical or tipping” changes in sets of qualitative and quantitative indicators. Our analysis shows that both cities experienced incremental changes in their demographic, economic and political trajectories but we found no evidence for either city to have crossed a tipping point in their transition process yet. However, distinct developments in the cities’ policy narratives and visions indicate qualitative changes while putting them on different development trajectories potentially leading to tipping points in the future. Our study shows that the sequence of interventions and timing are important factors for the trajectory of a region determining the quality of societal change. It also suggests that radical change and tipping are the exception rather than the rule, especially in the highly complex social systems of cities.

Description: Disasters and crises affect more people around the world than reported in official documents by national or international agencies. Meanwhile, climate change, the COVID-19 pandemic, several wars worldwide and other crises expose a large proportion of the entire population to substantial risks, as well as profoundly affecting human health globally. Many of these impacts remain unnoticed by governance authorities, since many coping strategies are based on bottom-up activities rather than top-down policies. This raises the question: how can we be adequately prepared for a next pandemic or other unforeseen extreme events? Social capital could provide some clues for resilient responses that could be integrated in risk planning and management practice. In this paper, a comprehensive review is provided based on bibliometric analysis. A total number of 2872 published articles were documented and classified. In addition, the geographic locations and the institutional affiliations were assessed and visualized. Four salient research themes were identified as follows: (1) Knowledge sources of the research domain; (2) Individual social capital and risky behaviors; (3) Disaster management and resilience building; and (4) Health issues in the COVID-19 Era. This study offered some practical insights for mobilizing and developing social capital in different phases of risk management. Nevertheless, more inter- and transdisciplinary research across domains is needed to articulate a more comprehensive view of the development of social capital in various risk situations.

Description: Solar energy is not only the most abundant energy on earth but it is also renewable. The use of this energy is expanding very rapidly mainly through photovoltaic technology. However, electricity storage remains a bottleneck in tackling solar resource variability. Thus, solar thermal energy becomes of particular interest when energy storage is required, as thermal energy storage is much cheaper than electricity storage. The objective of this paper is to make a short update on the CSP (Concentrated Solar Power) market as of the year 2023. It is based on the CSP-GURU database, which lists information on CSP power plants all over the world. Although this database is open, it is not easy to find UpToDate analysis. An overview of this expanding technology is presented and offers readable figures with the most important information. This includes the evolution of installed capacities worldwide along with upcoming projects (under construction) and technological trends. The evolution of storage capacities and operating temperatures is discussed. Investment costs and levelized cost of electricity are also provided to obtain reliable data for comparison with other energy technologies. Specific land requirements are highlighted, along with overall efficiency. Relevant examples are discussed in this paper. Eventually, it outlines the evolution of the CSP landscape with useful information for scientific and educational purposes.

Description: Based on a theoretical framework inspired by the Greed-Efficiency-Fairness-Hypothesis (GEF), it is argued that perceived effectiveness of climate policies, in addition to other policy beliefs (i.e. perceived personal and distributional consequences), influences perceived overall policy fairness and acceptance. However, links between these policy beliefs and perceived overall fairness as well as whether perceived overall fairness might mediate effects of these beliefs on acceptance remains understudied. This study addresses these gaps and extends the GEF-inspired framework: We add procedural fairness to the list of fairness-relevant beliefs and analyze whether perceived overall carbon pricing fairness integrates and mediates their effect on acceptance, using survey data representative of Germany (n = 4646). Additionally, we test whether adherence to the polluter-pays principle (a general fairness principle) moderates the effects of perceived distributional consequences and effectiveness on perceived overall fairness. Results showed that perceived personal consequences, distributional consequences, procedural fairness, as well as perceived effectiveness, all impact perceived overall fairness, and that the latter (partially) mediates their effects on carbon pricing acceptance. We also find weak evidence that the impact of perceived effectiveness and negative distributional consequences on perceived overall fairness is greater for polluter-pays adherents than for non-adherents. These results suggest that, additionally to perceived personal and distributional consequences as well as fair procedures, perceiving a policy to be effective increases its perceived overall fairness.

Description: Shared pooled mobility has been hailed as a sustainable mobility solution that uses digital innovation to efficiently bundle rides. Multiple disciplines have started investigating and analyzing shared pooled mobility systems. However, there is a lack of cross-community communication making it hard to build upon knowledge from other fields or know which open questions may be of interest to other fields. Here, we identify and review 9 perspectives: transdisciplinary social sciences, social physics, transport simulations, urban and energy economics, psychology, climate change solutions, and the Global South research and provide a common terminology. We identify more than 25 000 papers, with more than 100 fold variation in terms of literature count between research perspectives. Our review demonstrates the intellectual attractivity of this as a novel perceived mode of transportation, but also highlights that real world economics may limit its viability, if not supported with concordant incentives and regulation. We then sketch out cross-disciplinary open questions centered around (1) optimal configuration of ride-pooling systems, (2) empirical studies, and (3) market drivers and implications for the economics of ride-pooling. We call for researchers of different disciplines to actively exchange results and views to advance a transdisciplinary research agenda.