ALBERT

Description: The IRGC risk governance framework refers to an integrated concept on how to deal with a variety of physical, environmental and social risks characterized by complex, uncertain and ambiguous impacts. The framework has been informed by interdisciplinary research drawing from sociological and psychological research, including investigations about regulatory styles, institutional regimes and public participation. The notion of governance pertains to the many ways in which all relevant actors, individuals and institutions, public and private, deal with interventions that impact nature and human societies. It includes formal institutions and regimes as well as informal arrangements for including stakeholders and the public at large.

Description: Risk and uncertainty communication of often directed towards addressing the relevance and meaning of probability distributions over negative outcomes and statistical confidence intervals. As much as a professional handling of complex mathematical operations is needed, this will cover only a fraction of what uncertainty communication needs to addres. In those cases where estimates of uncertainty come close to educated guesses, simple beliefs or even total ignorance, other important cues may be more important than formal expertise in risk assessments. These include trust in the risk management agencies or other influential actors, personal experience, indigenous or community-based knowledge, common sense and argumentative or persuasive power. Once the full range of uncertainty is in the focus of risk managemem and communication institutions, an interdisciplinary, inclusive and demand-driven communication strategy needs to be developed. As recommended in the paper by Lofstedt and Bouder, such a targeted approach to risk and uncertainty communication requires interdisciplinary expertise, competence in the social and natural sciences, and practical experience in designing public discourses.

Description: In recent years, bottom–up civil society initiatives have advanced urban transformation processes in Berlin. Following previous research suggesting that bottom–up participation could have a positive impact on community resilience (CR), we analyse the impact of engagement on Berlin–based civil society initiatives. Whilst a positive effect on resilience can be found, we identify governance processes that would be necessary to enable the full potential of bottom–up participation for CR. Resilience, understood as the capacity of a community to thrive in times of change and uncertainty, is becoming increasingly important for the functioning of (urban) communities; hence, finding ways of strengthening it is deemed necessary.

Description: In the light of the major global crises such as pandemics, war, climate change and inequality, scientific research faces new challenges and targets. Scientific studies are supposed to provide background knowledge, to facilitate the desired transformation towards a sustainable future and to offer assistance for resolving complex problems that accompany societies in transition. Concepts such as transformative, transdisciplinary or co-creative research elucidate the direction in which scientific research finds its new role(s). Based on the discussion of these concepts and their different roots, the entry analyzes a new modular concept for a transdisciplinary scientific approach combining and integrating classic curiosity-driven research with goal oriented (advocacy) knowledge and catalytic, process-oriented expertise. In particular it emphasizes the role and function of curiosity-driven research for a comprehensive design of transdisciplinarity and transformative research. There is no doubt that society needs better transformative knowledge to facilitate actions towards sustainability but such knowledge rests on evidence-based insights from disciplinary and interdisciplinary research efforts. The entry provides an orientation of how this classic research outcomes can effectively be integrated into a transdisciplinary context.

Description: Cities and other human settlements are major contributors to climate change and are highly vulnerable to its impacts. They are also uniquely positioned to reduce greenhouse gas emissions and lead adaptation efforts. These compound challenges and opportunities require a comprehensive perspective on the public policy of human settlements. Drawing on core literature that has driven debate around cities and climate over recent decades, we put forward a set of boundary objects that can be applied to connect the knowledge of epistemic communities and support an integrated urbanism. We then use these boundary objects to develop the Goals-Intervention-Stakeholder-Enablers (GISE) framework for a public policy of human settlements that is both place-specific and provides insights and tools useful for climate action in cities and other human settlements worldwide. Using examples from Berlin, we apply this framework to show that climate mitigation and adaptation, public health, and well-being goals are closely linked and mutually supportive when a comprehensive approach to urban public policy is applied. © The Author(s) 2024.

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.