ALBERT

Beschreibung: Monsoon systems transport water and energy across the globe, making them a central component of the global circulation system. Changes in different forcing parameters have the potential to fundamentally change the monsoon characteristics as indicated in various paleoclimatic records. Here, we use the Atmosphere Model developed at the Geo- physical Fluid Dynamics Laboratory (GFDL-AM2) and couple it with a slab ocean in order to analyze the monsoon’s sen- sitivity to changes in different parameters on a planet with idealized topography (varying land position, slab depth, atmospheric CO2 concentration, solar radiation, sulfate aerosol concentration, and surface albedo). This Monsoon Planet concept of an aquaplanet with a broad zonal land stripe allows us to reduce the influence of topography and to access the relevant meridional monsoon dynamics. In simulations with monsoon dynamics, a bimodal rainfall distribution develops during the monsoon months with one maximum over the tropical ocean and the other one over land. The intensity and ex- tent of the monsoon depend on the relative height of a local maximum in the surface pressure field that is acting as a bar- rier and is determining the coastward moisture transport. Changes in the barrier height occur during the course of one year but can also be induced when varying different parameters in the sensitivity analysis (e.g., the increase of atmospheric CO2 reduces the barrier height, resulting in an increase of rainfall, while aerosols have the opposing effect). This bimodal rainfall structure separated by a pressure barrier is also present in reanalysis data of the West African monsoon.

Beschreibung: Weather extremes are challenging the achievement of Sustainable Development Goal (SDG 2) – Zero Hunger globally and, most notably, in West Africa where it is further aggravated by rapid population growth. Here we present a stylized stochastic food production model to show how optimal crop allocations change depending on food security risk targets. To guarantee stable livelihoods for farmers, we examine the viability of a contingency fund that supports farmers in the event of low crop yields. Applied to the West African context, accounting for weather variability can substantially improve the reliability of the food supply and boost the fiscal sustainability of a contingency fund. Yet, setting reliability targets for food security is costly and leaves high residual risk in certain regions. Spatial risk-sharing through regional cooperation at the West African scale can eliminate the risk of insufficient food supply and further enhance the fund solvency.

Beschreibung: Rising seas are a threat to human and natural systems along coastlines. The relation between global warming and sea level rise is established, but the quantification of impacts of historical sea level rise on a global scale is largely absent. To foster such quantification, here we present a reconstruction of historical hourly (1979–2015) and monthly (1900–2015) coastal water levels and a corresponding counterfactual without long-term trends in sea level. The dataset pair allows for impact attribution studies that quantify the contribution of sea level rise to observed changes in coastal systems following the definition of the Intergovernmental Panel on Climate Change (IPCC). Impacts are ultimately caused by water levels that are relative to the local land height, which makes the inclusion of vertical land motion a necessary step. Also, many impacts are driven by sub-daily extreme water levels. To capture these aspects, the factual data combine reconstructed geocentric sea level on a monthly timescale since 1900, vertical land motion since 1900 and hourly storm-tide variations since 1979. The inclusion of observation-based vertical land motion brings the trends of the combined dataset closer to tide gauge records in most cases, but outliers remain. Daily maximum water levels get in closer agreement with tide gauges through the inclusion of intra-annual ocean density variations. The counterfactual data are derived from the factual data through subtraction of the quadratic trend. The dataset is made available openly through the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) at https://doi.org/10.48364/ISIMIP.749905 (Treu et al., 2023a).

Beschreibung: A potential shutdown of the Atlantic meridional overturning circulation (AMOC) is commonly recognised to have a significant impact on the Northern hemispheric climate, notably in Northern Europe. The collapse of the northbound heat transport by the AMOC is supposed to cool down surface air temperatures at the Scandinavian coast by up to 6 K accompanied by a concomitant nutrient starvation of phytoplankton in Subarctic and Arctic regions. However, besides local and regional impacts, tipping the AMOC into a weaker state by anthropogenic carbon dioxide (CO2) and associated freshwater forcing could also have surprising remote effects. In order to investigate possible long-term impacts of an AMOC shutdown on ocean biogeochemistry, we employ an Earth system model of intermediate complexity using idealised scenarios of century-scale atmospheric 2×CO2 and 4×CO2 pulses combined with North Atlantic freshwater forcing. The results show a continued increase in primary production, in particular in the Eastern equatorial Pacific, due to a decrease in iron limitation following the AMOC shutdown. Tracer simulations indicate that bioavailable dissolved iron brought by aeolian dust into the subtropical gyres of the Atlantic Ocean is transported to the Southern Ocean and from there enters the Indian Ocean and the Pacific. Thereby, the additionally introduced iron fertilises the phosphate-rich high-nutrient, low chlorophyll waters, giving a lasting boost to phytoplankton growth, especially in the Eastern equatorial Pacific.

Beschreibung: Investigating the correlations between time series is a fundamental approach to reveal the hidden mechanisms in complex systems. However, the estimated correlations often show time-dependent behaviors, which may create uncertainty for decision-making in various scenarios. Thus, forecasting the evolution of these varying correlations may be helpful, but it is still unsolved entirely. We bridge this gap by proposing a data-driven framework: (a) we first embed all the pairwise correlations within a complex system into multivariate correlation-based series by sliding windows; (b) we then identify two different low-dimensional representations of multivariate correlation-based series through delay embedding and dimensionality reduction; (c) finally, multistep ahead predictions of varying correlations can be achieved by training a mapping between two low-dimensional representations. Both model and real-world systems are used to illustrate our framework, including finance, neuroscience, and climate. Our framework is robust and has the potential to be used for other complex systems. Hopefully, forecasting the evolution of correlations in complex systems can be a useful complementary, since existing works mainly focus on the predictions of components within the systems.

Beschreibung: Crop models are essential tools for assessing the impact of climate change on national or regional agricultural production. Starting from meteorology, soil and crop management, fertilization and irrigation practices, they predict the yield of specific crop varieties. For long term assessments, climate models are the source of primary information. To make climate model results usable in a specific time frame context, bias adjustment (BA) is required. In fact, climate models tend to deviate from day-to-day values of the physical parameters while conserving the climate variability signal. BA brings the climatic signal to the actual values observed in a specific location and period, and to be representative of a specific period in absolute terms. BA techniques come in different flavours. The broadest categorization is univariate and multivariate methods. Multivariate methods adjust the variables considering possible cross-correlations while univariate methods treat the variables one by one without accounting for possible dependence on one another.

Beschreibung: The emergence of the evolutionary game on complex networks provides a fresh framework for studying cooperation behavior between complex populations. Numerous recent progress has been achieved in studying asymmetric games. However, there is still a substantial need to address how to flexibly express the individual asymmetric nature. In this paper, we employ mutual cognition among individuals to elucidate the asymmetry inherent in their interactions. Cognition arises from individuals’ subjective assessments and significantly influences their decision-making processes. In social networks, mutual cognition among individuals is a persistent phenomenon and frequently displays heterogeneity as the influence of their interactions. This unequal cognitive dynamic will, in turn, influence the interactions, culminating in asymmetric outcomes. To better illustrate the inter-individual cognition in asymmetric snowdrift games, the concept of favor value is introduced here. On this basis, the evolution of cognition and its relationship with asymmetry degree are defined. In our simulation, we investigate how game cost and the intensity of individual cognitive changes impact the cooperation frequency. Furthermore, the temporal evolution of individual cognition and its variation under different parameters was also examined. The simulation results reveal that the emergence of heterogeneous cognition effectively addresses social dilemmas, with asymmetric interactions among individuals enhancing the propensity for cooperative choices. It is noteworthy that distinctions exist in the rules governing cooperation and cognitive evolution between regular networks and Watts–Strogatz small-world networks. In light of this, we deduce the relationship between cognition evolution and cooperative behavior in co-evolution and explore potential factors influencing cooperation within the system.

Beschreibung: We study three different strategies of vaccination in an SEIRS (Susceptible–Exposed–Infected–Recovered–Susceptible) seasonal forced model, which are (⁠ ⁠) continuous vaccination; (⁠ ⁠) periodic short-time localized vaccination, and (⁠ ⁠) periodic pulsed width campaign. Considering the first strategy, we obtain an expression for the basic reproduction number and infer a minimum vaccination rate necessary to ensure the stability of the disease-free equilibrium (DFE) solution. In the second strategy, short duration pulses are added to a constant baseline vaccination rate. The pulse is applied according to the seasonal forcing phases. The best outcome is obtained by locating intensive immunization at inflection of the transmissivity curve. Therefore, a vaccination rate of of susceptible individuals is enough to ensure DFE. For the third vaccination proposal, additionally to the amplitude, the pulses have a prolonged time width. We obtain a non-linear relationship between vaccination rates and the duration of the campaign. Our simulations show that the baseline rates, as well as the pulse duration, can substantially improve the vaccination campaign effectiveness. These findings are in agreement with our analytical expression. We show a relationship between the vaccination parameters and the accumulated number of infected individuals, over the years, and show the relevance of the immunization campaign annual reaching for controlling the infection spreading. Regarding the dynamical behavior of the model, our simulations show that chaotic and periodic solutions as well as bi-stable regions depend on the vaccination parameters range.

Beschreibung: Operating within safe and just Earth system boundaries requires mobilizing key actors across scale to set targets and take actions accordingly. Robust, transparent and fair cross-scale translation methods are essential to help navigate through the multiple steps of scientific and normative judgements in translation, with clear awareness of associated assumptions, bias and uncertainties. Here, through literature review and expert elicitation, we identify commonly used sharing approaches, illustrate ten principles of translation and present a protocol involving key building blocks and control steps in translation. We pay particular attention to businesses and cities, two understudied but critical actors to bring on board.

Beschreibung: Oscillatory instability emerges amidst turbulent states in experiments in various turbulent fluid and thermo-fluid systems such as aero-acoustic, thermoacoustic and aeroelastic systems. For the time series of the relevant dynamic variable at the onset of the oscillatory instability, universal scaling behaviors have been discovered in experiments via the Hurst exponent and certain spectral measures. By means of a center manifold reduction, the spatiotemporal dynamics of these real systems can be mapped to a complex Ginzburg–Landau equation with a linear global coupling. In this work, we show that this model is able to capture the universal behaviors of the route to oscillatory instability, elucidating it as a transition from defect to phase turbulence mediated by the global coupling.

Beschreibung: Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analysed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models’ sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models.

Beschreibung: Flood losses have steadily increased in the past and are expected to grow even further owing to climate and socioeconomic change. The reduction of flood vulnerability, for example, through adaptation, plays a key role in the mitigation of future flood risk. However, lacking knowledge about vulnerability dynamics, which arise from the interaction between floods and the ensuing response by society, limits the scope of current risk projections. We present a socio-hydrological method for flood risk assessment that simulates the interaction between society and flooding continuously, including changes in vulnerability through collective (structural) and private (non structural) measures. Our probabilistic approach quantifies uncertainties and exploits empirical data to chart risk dynamics including how society copes with flooding. In a case study for the commercial sector in Dresden, Germany, we show that increased adaptation is necessary to counteract the expected four-fold growth in flood risk due to transient hydroclimatic and socioeconomic boundary conditions. We further use our holistic approach to identify solutions for effective long-term adaptation, demonstrating that integrated adaptation strategies (i.e., combined structural and non structural measures) can reduce the average risk by up to 60% at the study site. Ultimately, our case study highlights the benefit of the model for robust flood risk assessment as it can capture unintended, adverse feedbacks of adaptation measures such as the levee effect. Consequently, our socio-hydrological method contributes to a more systemic and reliable flood risk assessment that can inform adaptation planning by exploring the possible system evolutions comprehensively including unlikely futures.

Beschreibung: Despite their importance, wetland ecosystems protected through the Ramsar Convention on Wetlands are under pressure from climate change and human activities. These drivers are altering water availability in these wetlands, changing water levels or surface extent, in some cases, beyond historical variability. Attribution of the effects of human and climate activities is usually focused on changes within the wetlands or their upstream surface and groundwater inputs. However, the reliance of wetland water availability on upwind atmospheric moisture supply is less understood. Here, we assess the vulnerability of 40 Ramsar wetland basins to precipitation changes caused by land use and hydroclimatic changes occurring in their upwind moisture-supplying regions. We use moisture flows from a Lagrangian tracking model, atmospheric reanalysis data, and historical land use change data to assess and quantify these changes. Our analyses show that historical land use change decreased precipitation and terrestrial moisture recycling in most wetland hydrological basins, accompanied by decreasing surface water availability (precipitation minus evaporation) in some wetlands. The most substantial effects on wetland water availability occurred in the tropical and subtropical regions of Central Europe and Asia. Overall, we found wetlands in Asia and South America to be especially threatened by a combination of land use change-driven effects on runoff, high terrestrial precipitation recycling, and recently decreasing surface water availability. This study stresses the need to incorporate upwind effects of land use changes in the restoration, management and conservation of the world’s wetlands.

Beschreibung: The Anthropocene is characterized by accelerating change and global challenges of increasing complexity. Inspired by what some have called a polycrisis, we explore whether the human trajectory of increasing complexity and influence on the Earth system could become a form of trap for humanity. Based on an adaptation of the evolutionary traps concept to a global human context, we present results from a participatory mapping. We identify 14 traps and categorize them as either global, technology or structural traps. An assessment reveals that 12 traps (86%) could be in an advanced phase of trapping with high risk of hard-to-reverse lock-ins and growing risks of negative impacts on human well-being. Ten traps (71%) currently see growing trends in their indicators. Revealing the systemic nature of the polycrisis, we assess that Anthropocene traps often interact reinforcingly (45% of pairwise interactions), and rarely in a dampening fashion (3%). We end by discussing capacities that will be important for navigating these systemic challenges in pursuit of global sustainability. Doing so, we introduce evolvability as a unifying concept for such research between the sustainability and evolutionary sciences.

Beschreibung: Renewable power generation is the key to decarbonizing the electricity system. Wind power is the fastest-growing renewable source of electricity in the United States. However, expanding wind capacity often faces local opposition, partly due to a perceived visual disamenity from large wind turbines. Here, we provide a US-wide assessment of the externality costs of wind power generation through the visibility impact on property values. To this end, we create a database on wind turbine visibility, combining information on the site and height of each utility-scale turbine having fed power into the U.S. grid, with a high-resolution elevation map to account for the underlying topography of the landscape. Building on hedonic valuation theory, we statistically estimate the impact of wind turbine visibility on home values, informed by data from the majority of home sales in the United States since 1997. We find that on average, wind turbine visibility negatively affects home values in an economically and statistically significant way in close proximity (5 miles/8 km). However, the effect diminishes over time and in distance and is indistinguishable from zero for larger distances and toward the end of our sample.

Beschreibung: The construction sector makes a considerable contribution to global greenhouse gas emissions. Considering the ongoing urbanization trends and climate change urgency, the exploration of alter- native construction techniques should be a mandate. 3D-printing represents an emergent technol- ogy and more and more specimen are being built. We collect data of raw material use for houses that have already been built using 3D-printing. Assessing the construction related emissions, we find that, the four examples for which we could obtain the data, do have less emissions per square meter than conventionally built houses (10 international examples). We argue that 3D-printing represents an interesting alternative, but further research is necessary, not just in terms of environ- mental implications but also to better understand the social implications, e.g. health and safety or labor.

Beschreibung: This paper considers the exponential output synchronization of complex networks with output coupling (CNOC) based on the intermittent event-triggered control (IE-TC) strategy. Unlike existing intermittent control strategies, the proposed IE-TC strategy is event-triggered instead of time-triggered during the control intervals. Moreover, the average control rate is adopted for intermittent control, which makes the results less conservative. A new Lyapunov function is proposed to simplify the proof, which does not require the traditional mathematical induction method for intermittent control. Based on the Lyapunov method and inequality technique, sufficient conditions for achieving exponential output synchronization of CNOC for undirected graph and digraph topologies are given, respectively. Moreover, the Zeno phenomenon can be excluded. Finally, an example with simulations is provided to verify the feasibility of the theoretical results.

Beschreibung: This paper analyzes the implications of investors’ short-term oriented asset holding and portfolio decisions (or short-termism), and its consequences on green investments. We adopt a dynamic portfolio model, which contrary to conventional static mean-variance models, allows us to study optimal portfolios for different decision horizons. Our baseline model contains two assets, one asset with fluctuating returns and another asset with a constant risk-free return. The asset with fluctuating returns can arise from fossil-fuel based sectors or from clean energy related sectors. We consider different drivers of short-termism: the discount rate, the nature of discounting (exponential vs. hyperbolic), and the decision horizon of investors itself. We study first the implications of these determinants of short-termism on the portfolio wealth dynamics of the baseline model. We find that portfolio wealth declines faster with a higher discount rate, with hyperbolic discounting, and with shorter decision horizon. We extend our model to include a portfolio of two assets with fluctuating returns. For both model variants, we explore the cases where innovation efforts are spent on fossil fuel or clean energy sources. Detailing dynamic portfolio decisions in such a way may allow us for better pathways to empirical tests and may provide guidance to some online financial decision making.

Beschreibung: Humanity is modifying the atmospheric water cycle, via land use, climate change, air pollution, and weather modification. Given the implications of this, we present a theoretical framing of atmospheric water as an economic good. Historically, atmospheric water was tacitly considered a ‘public good’ since it was neither actively consumed (rival) nor controlled (exclusive). However, given anthropogenic changes, atmospheric water is becoming 'common-pool’ (rival, non-excludable) or 'club’ (non-rival, excludable). Moreover, advancements in weather modification presage water becoming a 'private’ good (i.e. rival, excludable). In this research, we explore the implications of different economic goods framings using story-based scenarios of human modifications of the atmospheric water cycle. We blend computational text analysis with expert perspectives to create science fiction prototypes of the future. The economic goods framing highlights that social choices play an enormous role in how the future will unfold with regard to human interaction with the atmospheric water cycle. The narrative scenarios serve two purposes. First, they provide creative artifacts for the investigation of future interactions with the atmospheric water cycle, that are rooted in a scientific evidence base. Second, they articulate trajectories of our coupled social-hydrological world that require deeper interrogation and anticipation in the present.

Beschreibung: Climate impacts on economic productivity indicate that climate change may threaten price stability. Here we apply fixed-effects regressions to over 27,000 observations of monthly consumer price indices worldwide to quantify the impacts of climate conditions on inflation. Higher temperatures increase food and headline inflation persistently over 12 months in both higher- and lower-income countries. Effects vary across seasons and regions depending on climatic norms, with further impacts from daily temperature variability and extreme precipitation. Evaluating these results under temperature increases projected for 2035 implies upwards pressures on food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per-year respectively on average globally (uncertainty range across emission scenarios, climate models and empirical specifications). Pressures are largest at low latitudes and show strong seasonality at high latitudes, peaking in summer. Finally, the 2022 extreme summer heat increased food inflation in Europe by 0.43-0.93 percentage-points which warming projected for 2035 would amplify by 30-50%.

Beschreibung: Tree regeneration is a key process in forest dynamics, particularly in the context of forest resilience and climate change. Models are pivotal for assessing long-term forest dynamics, and they have been in use for more than 50 years. However, an assessment of their ability to accurately represent tree regeneration is lacking. We assess how well current models capture the overall abundance, species composition, and mortality of tree regeneration. Using 15 models built to capture long-term forest dynamics at the stand, landscape, and global levels, we simulate tree regeneration at 200 sites representing large environmental gradients across Central Europe. The results are evaluated against comprehensive data from unmanaged forests. Most of the models overestimate regeneration levels, which is only compensated in some models by high simulated mortality rates in the early stages of individual trees dynamics. Simulated species diversity of regeneration matches the observed ranges. Models simulating higher species diversity at the stand level do not feature higher regeneration diversity. The effect of light availability on regeneration levels is captured better than the effect of temperature and soil moisture, but patterns are not consistent across models. Increasing complexity in the tree regeneration modules of the models is not related to higher accuracy of simulated tree regeneration. Furthermore, individual model design is more important than scale (stand, landscape, global) and approach (empirical, process-based) for accurately capturing tree regeneration. Despite considerable mismatches between simulation results and data, it is remarkable that most models capture the essential features of the highly complex process of tree regeneration, while not having been parameterized with such data. We conclude that much can be gained by evaluating and refining the modeling of regeneration processes. This has the potential to render long-term projections of forest dynamics under changing environmental conditions that are much more robust.

Beschreibung: There has been fierce controversy in the literature over the long-run efficiency of the energy-only market (EOM) design ever since its inception. In this paper, we provide novel insights to illuminate this historical controversy, and we revisit it with a focus on contemporary issues and the profound changes brought about by the energy transition. Specifically, we develop an analytical and modeling framework to quantitatively investigate how EOM outcomes hinge on the underlying behavioral, informational and structural assumptions. We apply our framework to a case study calibrated on Californian fundamentals that captures the key features of energy systems under deep decarbonization. We characterize how EOM outcomes can substantially deviate from the long-run optimum as soon as one assumption is relaxed compared to theoretical requirements. This leads to pathways with higher electricity prices, lower security of supply and delayed decarbonization. In particular, we highlight how market price signals alone are prone to a dynamic entry-exit coordination problem between investment in low-carbon assets and the phaseout of fossil-fired assets. This calls for a market design reform to complement price signals that accounts for realistic assumptions.

Beschreibung: This study examines the impact of drought on the land ownership rights of smallholder farmers in Uganda. Three waves of the Uganda National Panel Survey are combined with an indicator for drought, the Standardized Precipitation Evapotranspiration Index. Using a household fixed effects approach, we exploit spatial and temporal variation in drought conditions to identify its effect on households’ self-reported willingness to acquire land ownership rights, both at the extensive and intensive margins. Results show that exposure to drought lowers households’ intentions to purchase land and substantially reduces the price households are willing to pay for land. The effects persist over time and are robust to different specifications. Our findings suggest that drought exposure limits the operating space for farmers wishing to purchase land.

Beschreibung: The term “polycrisis” appears with growing frequently to capture the interconnections between global crises, but the word lacks substantive content. In this article, we convert it from an empty buzzword into a conceptual framework and research program that enables us to better understand the causal linkages between contemporary crises. We draw upon the intersection of climate change, the covid-19 pandemic, and Russia’s war in Ukraine to illustrate these causal interconnections and explore key features of the world’s present polycrisis.

Beschreibung: Climate policy increasingly requires carbon dioxide removal (CDR). We describe its role, characterize optimal flows for non-permanent removals and describe optimal pricing regimes under different information and liability conditions. Non-permanent removal – though to a certain extent optimal – creates liabilities that warrant careful risk management. Thus, seemingly cheap land-based technologies can become expensive. We discuss possibilities for integrating CDR in the EU policy architecture and define four tasks: managing the emission cap; R&D support; quality certification of removals; management of liabilities from non-permanent CDR. We propose three institutions for these tasks: a European Carbon Central Bank, a Carbon Removal Certification Authority and a Green Leap Innovation Authority.

Beschreibung: Measuring complexity allows to characterize complex systems. Existing techniques are limited to simultaneously measure complexity from short length data sets, detect transitions and periodic dynamics. This paper presents an approach based on ordinal pattern positioned slopes (OPPS). It considers exclusively OPPS group occurrences to compute the complexity from OPPS (COPPS) as the average number of patterns and applies to short data series. The COPPS measure was successfully applied to simulation data for measuring complexity, detecting transition phases and regular dynamics, distinguishing between chaotic and stochastic dynamics; and to real-world data for detecting arrhythmia ECG beats.

Beschreibung: The rapid growth of clean energy technologies is driving a rising demand for critical minerals. In 2022 at the 15th Conference of the Parties to the Convention on Biological Diversity (COP15), seven major economies formed an alliance to enhance the sustainability of mining these essential decarbonization minerals. However, there is a scarcity of studies assessing the threat of mining to global biodiversity. By integrating a global mining dataset with great ape density distribution, we estimated the number of African great apes that spatially coincided with industrial mining projects. We show that up to one-third of Africa’s great ape population faces mining-related risks. In West Africa in particular, numerous mining areas overlap with fragmented ape habitats, often in high-density ape regions. For 97% of mining areas, no ape survey data are available, underscoring the importance of increased accessibility to environmental data within the mining sector to facilitate research into the complex interactions between mining, climate, biodiversity, and sustainability.

Beschreibung: Disruptive events and calamities can have major consequences for households in the predominantly agrarian communities of Eastern Africa. Here, we analyze the impacts of environmental and non-environmental shocks on migration in Tanzania using panel models and longitudinal data from the Tanzania National Panel Survey between 2008 and 2013. Shocks are defined as events that lead to losses in income, assets, or both. We find shocks resulting from changes in environmental conditions to be positively related to migration over time with more recent shocks exerting the strongest impact. According to our estimates, the probability of having a household member absent increases by 0.81% with each additional environmental shock encountered in the past 12 months. Different types of shocks have differential effects on migration with the strongest effects being observed for shocks with an immediate impact on household livelihoods, including through livestock losses and crop damage. Households in the sample are differently affected with rural, agriculturally dependent, and poor households without alternative income sources showing the strongest changes in their migration behavior in response to shocks. Our study adds important insights into the relationship between disruptive events and migration in Eastern Africa considering a broad time window and the compounding influence of different shock types. Our findings have a range of policy implications highlighting the need for a comprehensive perspective on household responses in times of distress that considers the interplay of different shock types as well as the role of context in shaping mobility patterns.

Beschreibung: Climate stabilization is crucial for restabilizing the Earth system but should not undermine biosphere integrity, a second pillar of Earth system functioning. This is of particular con- cern if it is to be achieved through biomass-based negative emission (NE) technologies that compete for land with food production and ecosystem protection. We assess the NE con- tribution of land- and calorie-neutral pyrogenic carbon capture and storage (LCN-PyCCS) facilitated by biochar-based fertilization, which sequesters carbon and reduces land demand by increasing crop yields. Applying the global biosphere model LPJmL with an enhanced representation of fast-growing species for PyCCS feedstock production, we calculated a land-neutral global NE potential of 0.20–1.10 GtCO2 year−1 assuming 74% of the biochar carbon remaining in the soil after 100 years (for + 10% yield increase; no potential for + 5%; 0.61–1.88 GtCO 2 year−1 for + 15%). The potential is primarily driven by the achiev- able yield increase and the management intensity of the biomass producing systems. NE production is estimated to be enhanced by + 200–270% if management intensity increases from a marginal to a moderate level. Furthermore, our results show sensitivity to process- specific biochar yields and carbon contents, producing a difference of + 40–75% between conservative assumptions and an optimized setting. Despite these challenges for making world-wide assumptions on LCN-PyCCS systems in modeling, our findings point to dis- crepancies between the large NE volumes calculated in demand-driven and economically optimized mitigation scenarios and the potentials from analyses focusing on supply-driven approaches that meet environmental and socioeconomic preconditions as delivered by LCN-PyCCS.

Beschreibung: Given growing concerns about climate tipping points and their risks, it is important to investigate the capability of identifying robust precursor signals for the associated transitions. In general, the variance and short-lag autocorrelations of the fluctuations increase in a stochastically forced system approaching a critical or bifurcation-induced transition, making them theoretically suitable indicators to warn of such transitions. Paleoclimate records provide useful test beds if such a warning of a forthcoming transition could work in practice. The Dansgaard–Oeschger (DO) events are characterized by millennial-scale abrupt climate changes during the glacial period, manifesting most clearly as abrupt temperature shifts in the North Atlantic region. Some previous studies have found such statistical precursor signals for the DO warming transitions. On the other hand, statistical precursor signals for the abrupt DO cooling transitions have not been identified. Analyzing Greenland ice core records, we find robust and statistically significant precursor signals of DO cooling transitions in most of the interstadials longer than roughly 1500 years but not in the shorter interstadials. The origin of the statistical precursor signals is mainly related to so-called rebound events, humps in the temperature observed at the end of interstadial, some decades to centuries prior to the actual transition. We discuss several dynamical mechanisms that give rise to such rebound events and statistical precursor signals.

Beschreibung: Eastern Africa and Arabia were major hominin hotspots and critical crossroads for migrating towards Asia during the late Pleistocene. To decipher the role of spatiotemporal environmental change on human occupation and migration patterns, we remeasured the marine core from Meteor Site KL 15 in the Gulf of Aden and reanalyzed its data together with the aridity index from ICDP Site Chew Bahir in eastern Africa and the wet-dry index from ODP Site 967 in the eastern Mediterranean Sea using linear and nonlinear time series analysis. These analyses show major changes in the spatiotemporal paleoclimate dynamics at 400 and 150 ka BP (thousand years before 1950), presumably driven by changes in the amplitude of the orbital eccentricity. From 400 to 150 ka BP, eastern Africa and Arabia show synchronized wet-dry shifts, which changed drastically at 150 ka BP. After 150 ka BP, an overall trend to dry climate states is observable, and the hydroclimate dynamics between eastern Africa and Arabia are negatively correlated. Those spatio-temporal variations and interrelationships of climate potentially influenced the availability of spatial links for human expansion along those vertices. We observe positively correlated network links during the supposed out-of-Africa migration phases of H. sapiens. Furthermore, our data do not suggest hominin occupation phases during specific time intervals of humid or stable climates but provide evidence of the so far underestimated potential role of climate predictability as an important factor of hominin ecological competitiveness.

Beschreibung: Climate change–induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nw with nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.

Beschreibung: This paper presents an extension of industry modelling within the REMIND integrated assessment model to industry subsectors and a projection of future industry subsector activity and energy demand for different baseline scenarios for use with the REMIND model. The industry sector is the largest greenhouse-gas-emitting energy demand sector and is considered a mitigation bottleneck. At the same time, industry subsectors are heterogeneous and face distinct emission mitigation challenges. By extending the multi-region, general equilibrium integrated assessment model REMIND to an explicit representation of four industry subsectors (cement, chemicals, steel, and other industry production), along with subsector-specific carbon capture and sequestration (CCS), we are able to investigate industry emission mitigation strategies in the context of the entire energy–economy–climate system, covering mitigation options ranging from reduced demand for industrial goods, fuel switching, and electrification to endogenous energy efficiency increases and carbon capture. We also present the derivation of both activity and final energy demand trajectories for the industry subsectors for use with the REMIND model in baseline scenarios, based on short-term continuation of historic trends and long-term global convergence. The system allows for selective variation of specific subsector activity and final energy demand across scenarios and regions to create consistent scenarios for a wide range of socioeconomic drivers and scenario story lines, like the Shared Socioeconomic Pathways (SSPs).

Beschreibung: The death toll and monetary damages from landslides continue to rise despite advancements in predictive modeling. These models’ performances are limited as landslide databases used in developing them often miss crucial information, e.g., underlying movement types. This study introduces a method of discerning landslide movements, such as slides, flows, and falls, by analyzing landslides’ 3D shapes. By examining landslide topological properties, we discover distinct patterns in their morphology, indicating different movements including complex ones with multiple coupled movements. We achieve 80-94% accuracy by applying topological properties in identifying landslide movements across diverse geographical and climatic regions, including Italy, the US Pacific Northwest, Denmark, Turkey, and Wenchuan in China. Furthermore, we demonstrate a real-world application on undocumented datasets from Wenchuan. Our work introduces a paradigm for studying landslide shapes to understand their underlying movements through the lens of landslide topology, which could aid landslide predictive models and risk evaluations.

Beschreibung: Anthropogenic climate change drives extreme weather events, leading to significant consequences for both society and the environment. This includes damage to road infrastructure, causing disruptions in transportation, obstructing access to emergency services, and hindering humanitarian organizations after natural disasters. In this study, we develop a novel method for analyzing the impacts of natural hazards on transportation networks rooted in the gravity model of travel, offering a fresh perspective to assess the repercussions of natural hazards on transportation network stability. Applying this approach to the Ahr valley flood of 2021, we discovered that the destruction of bridges and roads caused major bottlenecks, affecting areas considerably distant from the flood’s epicenter. Furthermore, the flood-induced damage to the infrastructure also increased the response time of emergency vehicles, severely impeding the accessibility of emergency services. Our findings highlight the need for targeted road repair and reinforcement, with a focus on maintaining traffic flow for emergency responses. This research provides a new perspective that can aid in prioritizing transportation network resilience measures to reduce the economic and social costs of future extreme weather events.

Beschreibung: We propose to explore the sustainability of climate policies based on a novel commitment metric. This metric allows to quantify how future generations’ scope of action is affected by short-term climate policy. In an example application, we show that following a moderate emission scenario like SSP2-4.5 will commit future generations to heavily rely on carbon dioxide removal or/and solar radiation modification to avoid unmanageable sea level rise.

Beschreibung: It is unclear how CO2 emissions in the German electricity sector will develop until 2030. On the one hand, the amendment in the Climate Change Act (as of August 2021) aims to tighten the emission reduction targets, fostering the pathway towards a decarbonised energy system. On the other hand, the complex interplay between the main instruments used to mitigate carbon emissions, fuel prices and the latest energy scarcity as a result of Russia’s war in Ukraine generates pressure for increased emissions. Using an energy system model parametrised to reflect the 2021 energy market situation i.e., before Russia’s attack, our study investigates the possibility that Germany will meet its 2030 climate targets. We then provide a qualitative analysis on how results can change in light of recent events. We suggest establishing a carbon price floor that can be dynamically changed in response to the evolution of other market forces and policies. This instrument would institutionalize a more credible path towards decarbonization and offer investors certainty.

Beschreibung: Paleoclimate proxies reveal abrupt transitions of the North Atlantic climate during past glacial intervals known as Dansgaard-Oeschger (DO) events. A central feature of DO events is a sudden warming of about 10°C in Greenland marking the beginning relatively mild phases termed interstadials. These exhibit gradual cooling over several hundred to a few thousand years until a final abrupt decline brings the temperatures back to cold stadial levels. As of now, the exact mechanism behind this millennial-scale variability remains inconclusive. Here, we propose an excitable model to explain Dansgaard-Oeschger cycles, where interstadials occur as noise-induced state space excursions. Our model comprises the mutual multi-scale interactions between four dynamical variables representing Arctic atmospheric temperatures, Nordic Seas’ temperatures and sea ice cover, and the Atlantic Meridional Overturning Circulation. The model’s atmosphere-ocean heat flux is moderated by the sea ice, which in turn is subject to large perturbations dynamically generated by fast evolving intermittent noise. If supercritical, perturbations trigger interstadial-like state space excursions during which all four model variables undergo qualitative changes that consistently resemble the signature of interstadials in corresponding proxy records. As a physical intermittent process generating the noise we propose convective events in the ocean or atmospheric blocking events. Our model accurately reproduces the DO cycle shape, return times and the dependence of the interstadial and stadial durations on the background conditions. In contrast to the prevailing understanding that DO variability is based on bistability in the underlying dynamics, we show that multi-scale, monostable excitable dynamics provides a promising alternative to explain millennial-scale climate variability associated with DO events.

Beschreibung: Drought risk threatens pastoralism in rangelands, which are already under strain from climatic and socioeconomic changes. We examine the future drought risk (2031–2060 and 2071–2100) to rangeland productivity across Eurasia (West, Central, and East Asia) using a well-tested process-based ecosystem model and projections of five climate models under three shared socioeconomic pathway (SSP) scenarios of low (SSP1−2.6), medium (SSP3−7.0), and high (SSP5−8.5) warming relative to 1985–2014. We employ a probabilistic approach, with risk defined as the expected productivity loss induced by the probability of hazardous droughts (determined by a precipitation-based index) and vulnerability (the response of rangeland productivity to hazardous droughts). Drought risk and vulnerability are projected to increase in magnitude and area across Eurasian rangelands, with greater increases in 2071–2100 under the medium and high warming scenarios than in 2031–2060. Increasing risk in West Asia is caused by longer and more intense droughts and vulnerability, whereas higher risk in Central and East Asia is mainly associated with increased vulnerability, indicating overall risk is higher where vulnerability increases. These findings suggest that future droughts may exacerbate livestock feed shortages and negatively impact pastoralism. The results have practical implications for rangeland management that should be adapted to the ecological and socioeconomic contexts of the different countries in the region. Existing traditional ecological knowledge can be promoted to adapt to drought risk and embedded in a wider set of adaptation measures involving management improvements, social transformations, capacity building, and policy reforms addressing multiple stakeholders.

Beschreibung: The decarbonization of India's economy will have different effects across income groups. As India is in the middle of the transformation process from an agriculture-based economy towards an industry- and service-based economy, called economic structural change, the extent of income distribution across households strongly depends also on the speed of economic transformation. While a number of recent studies have analyzed the distributional effects of carbon pricing, the specific role of structural change across sectors has not been in the focus of the related literature. Our study contrasts distributional effects from climate policy with distributional effects from structural change in India and asks how far carbon pricing supports or hinders structural change and development. We develop and apply a comprehensive model framework that combines economic growth and international trade dynamics related to structural change with detailed household income and expenditure data for India. Our study shows that changes in income and inequality due to carbon pricing vary with the changes in the sectoral structure of economies. Our results indicate that carbon pricing tends to delay economic structural change by retarding the reallocation of economic activities from the agricultural sector to the manufacturing sector. Furthermore, the results emphasize that the increase in inequality due to structural change is substantially stronger than due to carbon pricing. Consequently, socially sensitive policies supporting the process of structural transformation appear to be more important for poor households than lowering climate policy ambitions.

Beschreibung: "There are no scientifically justified obstacles to protecting biodiversity in all its beauty and diversity. There are only six years left to achieve the biodiversity targets by 2030. We must work together now to get there in time." In the 10 Must Knows from Biodiversity Science 2024, 64 scientists have further developed their well-founded and diverse findings and recommendations from the 10MustKnows22. The content of the ten selected key areas of the Earth-human system is supplemented by relevant publications from 2022 and 2023 and linked to the 23 global goals of the Kunming-Montreal Global Biodiversity Framework (GBF) adopted in December 2022. The authors are aware that the next six years until 2030 are essential for achieving an ecologically sustainable and socially just life on our planet in the medium and long term. With the 10MustKnows24, they want to actively contribute to accelerating the socio-ecological transformation by providing scientifically sound recommendations for politics and society.

Beschreibung: Non-traditional and transnational actors have become essential for environmental and climate change governance. One of these actors, the Climate and Clean Air Coalition (CCAC), has taken over a lead role in the governance of SLCPs. Since 2012, the CCAC has been pushing for an increased political dialogue on the one hand, and fostering technical expertise, projects, and a knowledge network on the other hand. This voluntary alliance is an interesting research subject because it brings together a mix of over 150 governmental, intergovernmental, NGO, and scientific members, who closely work on reducing global near term-warming as well as improving air quality, health, and further aspects of sustainable development. This chapter focuses on the CCAC’s role in the international policy landscape and on what it can contribute to SLCP governance. It describes the CCAC’s structure, modus of operation, and activities, and then scrutinizes its potential and challenges for SLCP governance. Furthermore, this text seeks to provide a perspective on the CCAC in the global climate and environmental policy landscape.

Beschreibung: Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts (CCI) due to interdependencies between coupled natural and social systems. However, current decision-making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi-sector CCI of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary or even convergent roles for analyses based on quantitative (e.g., data-mining, systems modeling) and qualitative methods (e.g., mental models, qualitative storylines). The data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes.

Beschreibung: Net-zero energy system configurations can be met in numerous ways, implying diverse economic effects. However, what is usually ignored in techno-economic and economy-wide analysis are the distinct social-political drivers and barriers, which might constrain certain elements of future energy systems. We thus apply a model ensemble that defines social-political storylines which constrain feasible net-zero configurations of the European energy system. Using these configurations in a macroeconomic general equilibrium model allows us to explore economy-wide effects and ultimately the cost-effectiveness of different systems. We find that social-political storylines provide valuable boundary conditions for feasible net-zero designs of the energy system and that the costliest energy sector configuration in fact leads to the highest European-wide welfare levels. This result originates in indirect effects, particularly positive employment effects, covered by the macroeconomic model. However, adverse public budget effects on the transition to net-zero energy may limit the willingness of policymakers who focus on shorter time-horizons to foster such a development. Our results highlight the relevance of considering the interaction of energy system-changes with labor, emission allowance and capital markets, as well as considering long-term perspectives.

Beschreibung: The Corona pandemic was one of the most challenging political events of the last decades in Europe in which many important political issues had to be decided within a very short space of time. Deliberative, sortition-based formats offer new approaches to strengthen democracy in times of crisis but have so far mainly been used for fundamental issues that have been under discussion for a long time. In Germany, four Corona Citizens’ Councils were organized at different levels to deal with the highly dynamic pandemic situation. The first was on local level and took place in the city of Augsburg, the next and most prominent one in the state of Baden-Wurttemberg (‘Bürgerforum Corona’), being held monthly over a period of 13 months. Another one was organized in the state of Saxony, a fourth one in Thuringia. The article examines the background, the methodological quality and the outcomes of three Corona Citizens’ Councils in Germany. The article compares the three Citizens’ Councils and draws conclusions about the crisis-management capacities of deliberative formats in dealing with pressing political issues in highly dynamic situations.

Beschreibung: Background This article asks the following question: how well are coal regions, affected by phase-out plans, represented in mediating commissions, to what extent do local communities participate in the decision-making process and how are the political negotiations perceived by the communities? We look at the case of the German lignite phase-out from a procedural justice perspective. Informed by literature on sociotechnical decline and procedural justice in energy transitions, we focus first on aspects of representation, participation and recognition within the German Commission on Growth, Structural Change and Employment (“Coal Commission”). Second, we analyze how to exnovate coal in two regions closely tied to the coal- and lignite-based energy history in Germany: Lusatia and the Rhenish Mining District. Results Based on interview series in both regions, we connect insights from local communities with strategies for structural change and participation programs in the regions. We find significant differences between the two regions, which is primarily an effect of the challenging historical experiences in Lusatia. Participation within existing arrangements is not sufficient to solve these problems; they require a comprehensive strategy for the future of the regions. Conclusions We conclude that the first phase-out process was a lost opportunity to initiate a community-inclusive sustainable transition process. As the phase-out process is not yet concluded, additional efforts and new strategies are needed to resolve the wicked problem of lignite phase-out.

Beschreibung: The transport sector and especially private cars pose environmental, economic, and social challenges. For this reason, cargo bikes and shared mobility are considered viable alternatives for road transport. In order to understand the potential and barriers of alternative transport modes, it is essential to analyze underlying motives. Moreover, comparing sustainable alternatives (such as public transport) to cars in terms of motives has been established as a research approach (Steg, 2003). Despite increasing interest in cargo bikes and cargo bike sharing, research on this topic is relatively rare. Particularly, there exists a lack of research addressing the impact of cargo bike sharing on car ownership. Against this background, this study quantifies the car ownership reduction effect of cargo bike sharing. In addition, it is investigated how cargo bikes differ from cars with regard to the underlying motives of users which also helps understanding potential barriers. To answer these research questions, this study is based on a large-scale survey with n = 2,590 cargo bike sharing users. The results imply that cargo bike sharing has a notable impact on car ownership. In general, cargo bikes are rated superior in regard to affective, symbolic, and environmental motives as well as on flexibility and price. However, discrepancies to cars do exist in terms of other instrumental aspects (traffic safety, travel speed, comfort, weather-independence). Notably, users who reduced car ownership tend to rate cargo bikes superior compared to car-dependent users. The results imply that cargo bikes can play a marked role in reducing car dependency. Improving infrastructure and cargo bike technology as well as stimulating favorable social norms for cargo bikes have been identified as beneficial conditions that could help to leverage this potential.

Beschreibung: In sustainability transitions research, the deliberate destabilisation of socio-technical regimes is increasingly recognised as a central intervention point. Absent, however, are granular approaches for assessing whether regime destabilisation actually occurs in processes of systemic change. We propose to assess regime destabilisation through shifts in the institutionalisation of field logics. Methodologically, we employ Socio-Technical Configuration Analysis to map changes over time in the composition and alignment of institutional and technological concepts embedded in sectoral policy. Empirically, we assess the extent to which post-Brexit agricultural policy reform in the United Kingdom marks the destabilisation of an unsustainable regime. Assessing legislative debate transcripts, we find that the previously dominant regime is only partly destabilised, as pre-existing development trajectories along established configurations of field logics, policy goals and instruments remain. These findings support the validity of our conceptual approach. Moreover, they nuance expectations about large-scale policy change as windows of opportunity for regime shifts.

Beschreibung: Where annual layers are found in stalagmites, these can be used to provide insights into palaeoclimate. Sebastian F.M. Breitenbach and Norbert Marwan present a low-cost and high-resolution method for acquisition and analysis of greyscale data from speleothems by means of the free open-source ImageJ software.

Beschreibung: Climate models are vital for understanding and projecting global climate change and its associated impacts. However, these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections. Addressing these challenges requires addressing internal variability, hindering the direct alignment between model simulations and observations, and thwarting conventional supervised learning methods. Here, we employ an unsupervised Cycle-consistent Generative Adversarial Network (CycleGAN), to correct daily Sea Surface Temperature (SST) simulations from the Community Earth System Model 2 (CESM2). Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole mode, as well as SST extremes. Notably, it substantially corrects climatological SST biases, decreasing the globally averaged Root-Mean-Square Error (RMSE) by 58%. Intriguingly, the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies, a common issue in climate models that traditional methods, like quantile mapping, struggle to rectify. Additionally, it substantially improves the simulation of SST extremes, raising the pattern correlation coefficient (PCC) from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32. This enhancement is attributed to better representations of interannual, intraseasonal, and synoptic scales variabilities. Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Beschreibung: We utilize a global warming level (GWL) lens to evaluate global and regional patterns of agricultural impacts as global surface temperature increases, providing a unique perspective on the experience of stakeholders with continued warming in the 21st century. We analyze crop productivity outputs from 11 crop models simulating 5 climate models under 3 emissions scenarios across 4 crops within the AgMIP/ISIMIP Phase 3 ensemble. We categorize regional productivity changes (without adaptation) into 9 characteristic climate change response patterns, identifying consistent increases and decreases as well as non-linear (peak or dip) responses indicative of inflection points reversing trends as GWLs increase. Many maize regions and pockets of wheat, rice and soybean show peak decrease patterns where initial increases may lull stakeholders into complacency or maladaptation before productivity shifts to losses at higher GWLs. Although the GWL perspective has proven useful in connecting diverse climate models and emissions scenarios, we identify multiple pitfalls that recommend proceeding with caution when applying this approach to climate impacts. Chief among these is that carbon dioxide (CO2) concentrations at any GWL depend on a climate model's transient climate response (TCR). Higher CO2 concentrations generally benefit crop productivity, so this leads to more pessimistic agricultural projections for so-called “hot” models and can skew multi-model ensemble results as models with high TCR are disproportionately likely to reach higher GWLs. While there are strong connections between many climatic impact-drivers and GWLs, vulnerability and exposure components of food system risk are strongly dependent on development pathways.

Beschreibung: Chapter 6 presents an introduction and sections on: earth system analysis from a nonlinear physics perspective; physics fields with relevance for energy technologies; towards green cities: the role of transport electrification; environmental safety; understanding and predicting space weather

Beschreibung: Residential buildings directly contribute 11% to local greenhouse gas emissions and up to 40% of total emissions when accounting for energy use for electricity generation. In order to achieve the climate targets in line with the Federal Climate Protection Act, increased ambition level of climate policy instruments is required in this sector. In this research, we are interested in the governance of this sector and the role of evaluation: the government-mandated processes used to evaluate policy in terms of the actors, organisations and ministries involved in executing and coordinating these processes; and the metrics and methods as well as the scope and granularity of evaluations.

Beschreibung: Real-world labs make the mobility transition tangible for residents. However, these experiences are not always positive, and often local conflicts arise. Based on in-depth interviews, the authors show that perceived procedural unfairness as well as the redistribution of space are the main drivers of a sceptical attitude towards redesign projects. Real-world labs (RwLs) are often used to explore and foster the mobility transition. Many RwLs dealing with mobility transition temporarily reallocate public spaces from motorized to active transport or to leisure activities. While some residents accept and enjoy the changes, others react with scepticism, rejection, or protest. This can lead to conflicts. Controversial perceptions and conflicts among residents make a permanent redesign rather challenging for the administration and the politicians. In this paper the authors investigate the related conflict types and counterarguments by studying the case of a temporary redesign of an intersection in Berlin. Based on in-depth interviews, they untangle procedural, distributional, and identity conflicts which might underlie the critical and ambivalent perceptions of residents. An abundance of conflict issues pertaining to procedural and distributional conflicts are revealed and emphasize the role of the RwL process.

Beschreibung: In order to avoid dangerous climate change and to satisfy the global energy needs energy systems have to change. Hopes are especially high in countries of the Global South for the low-carbon transition to propel sustainable development. Yet, while the energy transition provides opportunities, it also raises questions on how to avoid new global inequalities. This study presents the first quantitative approach to measure the extent to which the energy transitions in the Global South incorporate elements of energy justice. In doing so, this study builds on a rich literature on energy justice that differentiates between distributional, recognition, and procedural justice, thus taking into account social and development objectives such as affordability and accessibility of energy, the inclusion of marginalised parts of society, as well as broader community involvement and participation. Though much important conceptual and qualitative work has been done, what has been lacking so far is a quantitative measure of the degree to which the energy transition lives up to the imperative of energy justice, going beyond the much-studied Global North. The proposed energy justice index is designed and applied to select countries from Southeast Asia (Malaysia), sub-Saharan Africa (Kenya), the MENA region (Jordan), and Latin America (Chile). The index stands the test of the empirical application and demonstrates significant variation between countries along the different dimensions of energy justice. The study also emphasizes the importance of further testing and of improving data quality for informed policy making of energy justice issues in the Global South.

Beschreibung: Net zero targets have rapidly become the guiding principle of climate policy, implying the use of carbon dioxide removal (CDR) to compensate for residual emissions. At the same time, the extent of (future) residual emissions and their distribution between economic sectors and activities has so far received little attention from a social science perspective. This constitutes a research gap as the distribution of residual emissions and corresponding amounts of required CDR is likely to become highly contested in the political economy of low-carbon transformation. Here, we investigate what function CDR performs from the perspective of sectors considered to account for a large proportion of future residual emissions (cement, steel, chemicals, and aviation) as well as the oil and gas industry in the EU. We also explore whether they claim residual emissions to be compensated for outside of the sector, whether they quantify these claims and how they justify them. Relying on interpretative and qualitative analysis, we use decarbonization or net zero roadmaps published by the major sector-level European trade associations as well as their statements and public consultation submissions in reaction to policy initiatives by the EU to mobilize CDR. Our findings indicate that while CDR technologies perform an important abstract function for reaching net zero in the roadmaps, the extent of residual emissions and responsibilities for delivering corresponding levels of negative emissions remain largely unspecified. This risks eliding pending distributional conflicts over residual emissions which may intersect with conflicts over diverging technological transition pathways advocated by the associations.

Beschreibung: The Paris Agreement requires countries to break away from carbon lock-in, a particular challenge for traditional oil and gas producers. How can these countries overcome path-dependencies to shift from a fossil fuel heavy system to one relying on renewable energy? Malaysia epitomizes this challenge: the country is the second-largest oil producer in Southeast Asia whilst the fossil fuel energy sector takes up nearly 80 % of total greenhouse gas (GHG) emissions, with coal energy occupying the largest share. To identify leverage points of energy transitions, we model the structural components influencing the Malaysian energy system and assess the dynamics of interrelating factors. Based on stakeholders' input, we identify main factors influencing Malaysia's energy transition, explore their interactions, and use Cross Impact Balances (CIB) to create scenarios. Our analysis reveals the need to simultaneously disperse the centralized political power to a more diverse set of actors whilst introducing green growth recovery packages to break the carbon lock-in. Whilst focused on Malaysia, the findings contribute more generally to our understanding how fossil fuel reliant emerging economies can break path-dependencies inhibiting the clean energy transition.

Beschreibung: The topic of greenhouse gas emissions embodied in products is gaining in prominence and the possibilities for measuring and verifying them are improving. This provides fertile ground for those who demand that climate policy should address such embodied emissions. There are different design options for policies targeting embodied emissions. Such differences affect which groups can be mobilized in their favour. This paper shows that procurement standards which target intermediate products can mobilize the support of relatively low carbon producers of high carbon materials, while product standards which target final products can mobilize the support of producers of relatively low carbon materials and knowledge-intensive service providers.

Beschreibung: Germany is known for its ambitious climate policy targets. By 2045, the country seeks to achieve climate neutrality. As an intermediate step, the government has determined emission thresholds for different economic sectors through the year 2030. The industrial sector has so far not been a frontrunner in Germany's emission reduction efforts. Much of the country's success in this context is owed to the successful ramp-up of renewables in the electricity sector. For German industries, this means that they have little time left to undergo a substantial climate-friendly transformation by 2030. But how can this be achieved? This chapter introduces five different building blocks of Germany's climate strategy for its emission-intensive industrial sector: (1) The expansion of renewable energy for electricity production; (2) electrification and energy efficiency improvements; (3) the establishment of a green hydrogen economy; (4) the transformation towards a circular economy; and lastly (5) carbon capture and storage (CCS) and carbon capture and utilization (CCU). In an in-depth case study, the chapter reviews the particular role of CCU as a strategic component, discussing its potential as a climate strategy, its regulatory and legal framework, as well as insights on the broader societal acceptance of this technological approach.

Beschreibung: Dataset of recurrence plot bibliography. Scripts to retrieve additional data (paper citations and authors' affiliations) and to perform some statistical bibliometric and bibliographic analysis of the recurrence plot bibliography. Scripts are forPython and MATLAB.

Beschreibung: MATLAB scripts and functions used to create spatial recurrence plots to study circular structures in higherdimensional data fields, and to reproduce the figures of M. Riedl, N. Marwan, J. Kurths: Extended generalized recurrence plot quantification of complex circular patterns, European Physical Journal B, 90(58), 1–9 (2017). DOI:10.1140/epjb/e2017-70560-7

Beschreibung: A transition to healthy diets like the EAT-Lancet Planetary Health Diet could considerably reduce GHG emissions. However, the specific contributions of dietary shifts for the feasibility of 1.5°C pathways remain unclear. Here, we use the open-source Integrated Assessment Modeling (IAM) framework REMIND-MAgPIE to compare 1.5°C pathways with and without dietary shifts. We find that a flexitarian diet increases the feasibility of the Paris Agreement climate goals in different ways: The reduction of GHG emissions related to dietary shifts, especially methane from ruminant enteric fermentation, increases the 1.5°C-compatible carbon budget. Therefore, dietary shifts allow to achieve the same climate outcome with less carbon dioxide removal (CDR) and less stringent CO2 emission reductions in the energy system, which reduces pressure on GHG prices, energy prices and food expenditures.

Beschreibung: Photovoltaics (PV) and wind are the most important energy-conversion technologies for cost-efficient climate change mitigation. To reach international climate goals, the annual PV module production must be expanded to multi-terawatt (TW) scale. Economic and resource restraints demand the implementation of cost-efficient multi-junction technologies, for which perovskite-based tandem technologies are highly promising. In this work, the resource demand of the emerging perovskite PV technology is investigated, considering two factors of supply criticality, namely, mining capacity for minerals and the production capacity for synthetic materials. Overall, the expansion of perovskite PV to a multi-TW scale may not be limited by material supply if certain materials, especially indium, can be replaced. Moreover, organic charge-transport materials face currently unresolved scalability challenges. This study demonstrates that, besides the improvement of efficiency and stability, perovskite PV research and development also need to be guided by sustainable materials choices and design-for-recycling considerations.

Beschreibung: Forests, critical components of global ecosystems, face unprecedented challenges due to climate change. This study investigates the influence of functional diversity—as a component of biodiversity—to enhance long-term biomass of European forests in the context of changing climatic conditions. Using the next-generation flexible trait-based vegetation model, LPJmL-FIT, we explored the impact of functional diversity on long-term forest biomass under three different climate change scenarios (video abstract: https://www.pik-potsdam.de/~billing/video/2023/video_abstract_billing_et_al_LPJmLFIT.mp4). Four model set-ups were tested with varying degrees of functional diversity and best-suited functional traits. Our results show that functional diversity positively influences long-term forest biomass, particularly when climate warming is low (RCP2.6). Under these conditions, high-diversity simulations led to an approximately 18.2% increase in biomass compared to low-diversity experiments. However, as climate change intensity increased, the benefits of functional diversity diminished (RCP8.5). A Bayesian multilevel analysis revealed that both full leaf trait diversity and diversity of plant functional types contributed significantly to biomass enhancement under low warming scenarios in our model simulations. Under strong climate change, the presence of a mixture of different functional groups (e.g. summergreen and evergreen broad-leaved trees) was found more beneficial than the diversity of leaf traits within a functional group (e.g. broad-leaved summergreen trees). Ultimately, this research challenges the notion that planting only the most productive and climate-suited trees guarantees the highest future biomass and carbon sequestration. We underscore the importance of high functional diversity and the potential benefits of fostering a mixture of tree functional types to enhance long-term forest biomass in the face of climate change.

Beschreibung: The question of how science can become a lever in achieving the Sustainable Development Goals permeates most recent sustainability research. Wide-ranging literature calling for a transformative approach has emerged in recent years. This ‘transformative turn’ is fueled by publications from fields such as sustainability science, social-ecological research, conservation science, sustainability transitions, or sustainability governance studies. However, there is a lack of a shared understanding specifically of what is meant for research to be transformative in this developing discourse around doing science differently to tackle sustainability problems. We aim to advance transformative research for sustainability. We define transformative research and outline six of its characteristics: (1) interventional nature and a theory of change focus; (2) collaborative modes of knowledge production, experimentation and learning; (3) systems thinking literacy and contextualization; (4) reflexivity, normative and inner dimensions; (5) local agency, decolonization, and reshaping power; (6) new quality criteria and rethinking impact. We highlight three tensions between transformative research and traditional paradigms of academic research: (1) process- and output-orientation; (2) accountability toward society and toward science; (3) methodologies rooted in scientific traditions and post-normal methodologies. We conclude with future directions on how academia could reconcile these tensions to support and promote transformative research.

Beschreibung: Dominant ways of doing research are not enough to achieve the UN Sustainable Development Goals. The typical response of science to dealing with the current local and global sustainability crises is to produce and accumulate more knowledge. Transformative research seeks to couple knowledge production with co-creating change. This paper defines the transformative way of doing research to pro-actively support society's fight against pressing societal and environmental problems. We present six characteristics of transformative research. We reflect on the challenges related to implementing these characteristics in scientific practice and on how academia can play its part.

Beschreibung: Strategies for mitigating climate change today include plans for removing carbon dioxide from the atmosphere through “Negative Emissions Technologies” (NETs). NETs create new opportunities for scientific research, technology development, and the development of financial products, but also new conceptual possibilities, for example of declaring one’s ambition to become “climate neutral.” NETs thus constitute a novel frontier in climate science and politics whose conditions of possibility, characteristics, and consequences can be studied by social scientists and humanists. For environmental sociologists, NETs pose numerous opportunities for engaging with questions around future-making, imaginaries, promises, expertise, markets, infrastructure, justice, publics, and generally, the shape and role of science and technology in a form of social life that is increasingly organized around “planetary” concepts.

Beschreibung: CrossGov D2.1 EU and international policy landscape - Mapping EU policies and Green Deal objectives: general observations for policy coherence in the marine domain aims to provide a mapping of the European Green Deal policy landscape relevant to the marine domain and the CrossGov project. It also offers a general introduction into how policy coherence, embedded within the design of (selected) EU policies, supports or impedes progress towards the EGD’s objectives in the marine domain. A total of 36 policies were selected and mapped against five EGD strategies, namely the 2030 Climate Target Plan, the EU Climate Change Adaptation Strategy, the Biodiversity Strategy for 2030, the Zero Pollution Action Plan, and the Sustainable Blue Economy Strategy. These five strategies lay out a total of 25 specific objectives to implement the vision of the EGD, identified as relevant to the marine domain and the focus of the CrossGov project – i.e. climate change, biodiversity loss, and pollution.

Beschreibung: The PermaGov Deliverable focuses on exploring the EU policy landscape within the context of the European Green Deal (EGD), structured around four regime complexes: marine life, marine plastics, marine energy, and maritime transport. These complexes provide a framework for analysing the EU's approach to achieving the EGD's vision for sustainable marine governance. This report aims to offer a descriptive overview of marine EU policies relevant to the PermaGov project, focusing on policies identified as relevant to the overarching goals set forth in the EGD. It also considers relevant initiatives at global and regional levels. The marine life regime sees the EU Biodiversity Strategy for 2030 as its overarching strategy, essential for the EGD’s element of preserving and restoring ecosystems and biodiversity. Tackling the challenges of marine waste pollution, the marine plastics regime is guided by the EU Circular Economy Action Plan and the EU Action Plan: Towards Zero Pollution for Air, Water, and Soil, targeting the EGD’s elements of a mobilising industry for a clean and circular economy and a zero-pollution ambition for a toxic-free environment. The marine energy regime is shaped by the European Climate Law and the Offshore Renewable Energy Strategy, which are the overarching instruments that contribute to the EGD’s elements of increase the EU’s climate ambition for 2030 and 2050 and ensure the supply of clean, affordable, and secure energy. Lastly, the maritime transport regime sees the 'Fit for 55' Package and the 'Sustainable and Smart Mobility Strategy' as the two main instruments to achieve the EGD’s elements of increase the EU’s climate ambition for 2030 and 2050 and Accelerating the Shift to Sustainable and Smart Mobility. An additional aspect of this report is an initial screening of institutional barriers through the lens of policy documents. This is intended to be a starting point for the case studies of the PermaGov project, which will be further investigated in more depth later in the project. Institutional barriers are understood as obstacles within the structure and processes of governance systems that hamper decision-making processes and policy implementation. These barriers often arise from established rules, norms, and practices. The report considers the analytical framework developed by Oberlack (2017), focusing on attributes of institutions such as actor eligibility, responsibility, control, social connectivity, conflict, social learning, accountability, temporal and spatial scale, adaptiveness, and formality. These attributes describe the characteristics of how institutions are organised and operate, providing insights into potential challenges in policy design and implementation. The report provides a mapping of instruments relevant to the PermaGov four regime complexes and concludes by identifying potential institutional barriers, underlining the importance of conducting further detailed research in upcoming tasks of the PermaGov projects to effectively address the challenges of sustainable marine governance in line with the EGD’s ambitions.

Beschreibung: In this discourse, we present the unveiling of an open-source software package designed to facilitate engagement with the atmospheric model, Aeolus 2.0. This particular iteration stands as a self-contained model of intermediate complexity. The model's dynamical core is underpinned by a multi-layer pseudo-spectral moist-convective Thermal Rotating Shallow Water (mcTRSW) model. The pseudo-spectral problem-solving tasks are handled by the Dedalus algorithm, acknowledged for its spin-weighted spherical harmonics. The model captures the temporal and spatial evolution of vertically integrated potential temperature, thickness, water vapour, precipitation, and the intricate influence of bottom topography. It comprehensively characterizes velocity fields in both the lower and upper troposphere, employing resolutions spanning a spectrum from the smooth to the coarse, enabling the exploration of a wide range of dynamic phenomena with varying levels of detail and precision.

Beschreibung: We study the impact of California’s cap-and-trade system on carbon emissions in the electricity and industrial sectors. We use US state-level panel data covering the period 2005–2019 and apply the synthetic control method to construct an optimal counterfactual for per capita emissions in each sector. In our experiment, emissions in the power sector fall below counterfactual emissions by 48%. In the industrial sector, the state’s emissions are 6% higher than those of the synthetic control unit by the end of the observation period. Thus, cap-and-trade failed to deliver decarbonization across both sectors. While the abatement in the power sector was facilitated by complementary policies and driven by a switch from natural gas to renewables, California’s policy mix has disincentivized emission reductions in the industrial sector.

Beschreibung: Human activities have had a significant impact on Earth's systems and processes, leading to a transition of Earth's state from the relatively stable Holocene epoch to the Anthropocene. The planetary boundaries framework characterizes major risks of destabilization, particularly in the core dimensions of climate and biosphere change. Land system change, including deforestation and urbanization, alters ecosystems and impacts the water and energy cycle between land surface and atmosphere, while climate change can disrupt the balance of ecosystems and impact vegetation composition and soil carbon pools. These drivers also interact with each other, further exacerbating their impacts. Earth system models have been used recently to illustrate the risks and interacting effects of transgressing selected planetary boundaries, but a detailed analysis is still missing. Here, we study the impacts of long-term transgressions of the climate and land system change boundaries on the Earth system using an Earth system model with an incorporated detailed dynamic vegetation model. In our centennial-scale simulation analysis, we find that transgressing the land system change boundary results in increases in global temperatures and aridity. Furthermore, this transgression is associated with a substantial loss of vegetation carbon, exceeding 200 PgC, in contrast to conditions considered safe. Concurrently, the influence of climate change becomes evident as temperatures surge by 2.7–3.1 °C depending on the region. Notably, carbon dynamics are most profoundly affected within the large carbon reservoirs of the boreal permafrost areas, where carbon emissions peak at 150 PgC. While a restoration scenario to reduce human pressure to meet the planetary boundaries of climate change and land system change proves beneficial for carbon pools and global mean temperature, a transgression of these boundaries could lead to profoundly negative effects on the Earth system and the terrestrial biosphere. Our results suggest that respecting both boundaries is essential for safeguarding Holocene-like planetary conditions that characterize a resilient Earth system and are in accordance with the goals of the Paris Climate Agreement.

Beschreibung: The majority of signatories to The United Nations Climate Change Conference in 2021 (COP26) made a declaration to end deforestation by 2030. Here, we quantify future changes in land use and associated CO2 emissions to examine the impact of ending deforestation by 2030 on global land dynamics and emissions using an open-source land-use model. We show that if the COP26 declaration to end deforestation is fully implemented globally, about 167 Mha of deforestation could be avoided until 2050, compared to a baseline scenario which does not have extended forest protection. However, avoided deforestation and associated emissions come at the cost of strongly increased conversion of unprotected non-forested land to agricultural land, while land-use intensification in most regions is similar compared to a baseline scenario. Global initiatives are needed to facilitate a common dialogue on addressing the possible carbon emissions and non-forest leakage effects due to the expedited loss of non-forested land under a policy aimed at halting deforestation by 2030.

Beschreibung: As the Earth system is exposed to large anthropogenic interferences, it becomes ever more important to assess the resilience of natural systems, i.e., their ability to recover from natural and human-induced perturbations. Several, often related, measures of resilience have been proposed and applied to modeled and observed data, often by different scientific communities. Focusing on terrestrial ecosystems as a key component of the Earth system, we review methods that can detect large perturbations (temporary excursions from a reference state as well as abrupt shifts to a new reference state) in spatio-temporal datasets, estimate the recovery rate after such perturbations, or assess resilience changes indirectly from stationary time series via indicators of critical slowing down. We present here a sequence of ideal methodological steps in the field of resilience science, and argue how to obtain a consistent and multi-faceted view on ecosystem or climate resilience from Earth observation (EO) data. While EO data offers unique potential to study ecosystem resilience globally at high spatial and temporal scale, we emphasize some important limitations, which are associated with the theoretical assumptions behind diagnostic methods and with the measurement process and pre-processing steps of EO data. The latter class of limitations include gaps in time series, the disparity of scales, and issues arising from aggregating time series from multiple sensors. Based on this assessment, we formulate specific recommendations to the EO community in order to improve the observational basis for ecosystem resilience research.

Beschreibung: Global flood impacts have risen in recent decades. While increasing exposure was the dominant driver of surging impacts, counteracting vulnerability reductions have been detected, but were too weak to reverse this trend. To assess the ongoing progress on vulnerability reduction, we combine a recently available dataset of flooded areas derived from satellite imagery for 913 events with four global disaster databases and socio-economic data. Event-specific flood vulnerabilities for assets, fatalities and displacements reveal a lack of progress in reducing global flood vulnerability from 2000—2018. We examine the relationship between vulnerabilities and human development, inequality, flood exposure and local structural characteristics. We find that vulnerability levels are significantly lower in areas with good structural characteristics and significantly higher in low developed areas. However, socio-economic development was insufficient to reduce vulnerabilities over the study period. Nevertheless, the strong correlation between vulnerability and structural characteristics suggests further potential for adaptation through vulnerability reduction.

Beschreibung: Simulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77-0.87 and RMSE values between 16.3 mu g m3 and 20.6 mu g m- 3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes.

Beschreibung: Transdisciplinary processes deal with transdisciplinary problems that are (i) complex, (ii) societally relevant, (iii) ill-defined, and (iv) real-world problems which often show a high degree of ambiguity resulting in contested perceptions and evaluations among and between scientists and practitioners. Therefore, they are susceptible to multiple trade-offs. Transdisciplinary processes construct socially robust orientations (SoROs) particularly for sustainable transitioning. The integration of science and practice knowledge on equal footing (1) is considered the core of transdisciplinary processes. Yet other forms of knowledge integration contribute essentially to construct SoROs. Individuals may (2) use different modes of thought; (3) refer to various cultures with diverse value and belief systems; and (4) problems are perceived and prioritized based on roles and interests. Coping with transdisciplinary problems, (5) purposeful differentiation and integration and (6) an integration of evolutionary evolving codes of representing knowledge are necessary. Finally, (7) what systems to integrate requires consensus-building among participating scientists and practitioners. This paper is Part I of a two-part publication. It provides a conceptualization of the different types of knowledge integration. Part II analyzes tasks, challenges, and barriers related to different types of knowledge integration in five transdisciplinary processes which developed SoROs for sensitive subsystems of Germany affected by the irresponsible use of digital data.

Beschreibung: Transdisciplinary problems are complex, ill-defined, societal real-world problems with high ambiguity that are contested and require multiple trade-offs. Part I of this paper showed that transdisciplinary processes include seven types of knowledge integration: system (ontological), epistemological, cultural, cognitive, social conflict, evolutionary (levels of representation), and complexity-theory-based types of knowledge integration. The epistemological integration of the different modes of reasoning from science and practice is a unique selling point of the transdisciplinary process. Part II presents five transdisciplinary processes for the responsible use of digital data in different vulnerable/sensitive subsystems of Germany (mobility, health, agriculture, SME, and social media). Between 10 and 18 participants (equally representing science and practice in each group) synchronously constructed socially robust orientations as pillars of a white book. We elaborate that outcomes of a transdisciplinary process can be improved, and barriers diminished by reflecting on which of the seven types of knowledge integration are applied (see Part I). This is done for the six phases of a transdisciplinary process: (1) triggering, (2) initiation, (3) preparation, (4) planning, (5) core, and (6) post-processing. We particularly address researchers and practitioners who seek insights into how the production and integration of knowledge can be improved by transdisciplinary processes.

Beschreibung: Introduction Current urban and transport planning practices have significant negative health, environmental, social and economic impacts in most cities. New urban development models and policies are needed to reduce these negative impacts. The Superblock model is one such innovative urban model that can significantly reduce these negative impacts through reshaping public spaces into more diverse uses such as increase in green space, infrastructure supporting social contacts and physical activity, and through prioritization of active mobility and public transport, thereby reducing air pollution, noise and urban heat island effects. This paper reviews key aspects of the Superblock model, its implementation and initial evaluations in Barcelona and the potential international uptake of the model in Europe and globally, focusing on environmental, climate, lifestyle, liveability and health aspects. Methods We used a narrative meta-review approach and PubMed and Google scholar databases were searched using specific terms. Results The implementation of the Super block model in Barcelona is slow, but with initial improvement in, for example, environmental, lifestyle, liveability and health indicators, although not so consistently. When applied on a large scale, the implementation of the Superblock model is not only likely to result in better environmental conditions, health and wellbeing, but can also contribute to the fight against the climate crisis. There is a need for further expansion of the program and further evaluation of its impacts and answers to related concerns, such as environmental equity and gentrification, traffic and related environmental exposure displacement. The implementation of the Superblock model gained a growing international reputation and variations of it are being planned or implemented in cities worldwide. Initial modelling exercises showed that it could be implemented in large parts of many cities. Conclusion The Superblock model is an innovative urban model that addresses environmental, climate, liveability and health concerns in cities. Adapted versions of the Barcelona Superblock model are being implemented in cities around Europe and further implementation, monitoring and evaluation are encouraged. The Superblock model can be considered an important public health intervention that will reduce mortality and morbidity and generate cost savings for health and other sectors.

Beschreibung: In academia and political debates, the notions of ‘degrowth’ has gained traction since the dawn of the 21st century. While some uncertainty around its exact definition remains, research on degrowth revolves around the idea of reducing resource and energy throughput as a unifying theme. We employ a mixed-methods design to systematically review the scientific peer-reviewed English literature from 2008 to 2022 that refers to ‘degrowth’ or ‘post-growth’ in title, keywords or abstract (N = 951). We find a lack of concrete distributional and monetary policy proposals in the sample analyzed, and a low overall degree of collaboration among authors in relation to degrowth's age and size. The scientific peer-reviewed literature analyzed can be grouped into seven clusters along two major gradients, one along methodology (qualitative-quantitative) and the other along scale-of-analysis (individual-societal). We conclude that the academic literature about degrowth would benefit from a more prominent discussion of the political implications of its ideas and proposals, and that in particular the debate about distributional policy implications of degrowth should be more prominent and concrete, with a stronger focus on distributional policies in a degrowing economy.

Beschreibung: The Yangtze River Delta (YRD) region frequently experiences ozone pollution events during the summer and autumn seasons. High-concentration events are typically related to synoptic weather patterns, which impact the transport and photochemical production of ozone at multiple scales, ranging from the local to regional scale. To better understand the regional ozone pollution problem, studies on ozone source attribution are needed, especially regarding the contributions of sources at different vertical heights based on tagging the region or time periods. Between September 3 and 8, 2020, an episode of ozone concentration anomaly high was observed in Hefei through ground-based stations and ozone Lidar. The mechanism behind this event was uncovered through synoptic weather pattern analysis and using the Weather Research and Forecasting Chemistry model (WRF-Chem). Because an approaching typhoon caused variable wind direction, the O3-rich air masses (ORMs) arising from the YRD region were transported to Hefei via the nocturnal residual layer and descended to the ground through horizontal advection and vertical mixing processes the next day. Based on geographic source tagging, the anthropogenic NOx emissions (ANEs) from local and regional sources were the main contributors to the heavy ozone pollution over Hefei on September 6. Furthermore, the intra-regional transported ozone from southern Jiangsu (SJS), southern Anhui (SAH), and Zhejiang (ZJ) in the YRD was the main driving factor of the surface and upper atmosphere ozone pollution. Based on time period tagging, The ozone generated due to ANEs from September 3 to 5 significantly contributed to this episode. It is important to pay attention to the impact of ANEs on September 5 on the surface peak ozone concentration the following day (i.e., September 6). Our findings provide significant insights into the regional ozone transport mechanism in the YRD and optimization of measures to prevent and control heavy ozone pollution on spatiotemporal scales.

Beschreibung: In this paper, the authors discuss the role of China in the emerging geopolitics of hydrogen. It begins with a review of China's external energy policy and its evolution over the past decades, highlighting China's transition to a net-energy importer as an important inflection point in that process. It then goes on to describe the main pillars of China's national hydrogen policy. Building on this the paper provides and overview of China's external hydrogen policy and how this aligns with both its broader energy foreign policy and its hydrogen policy objectives. The paper finds that China’s hydrogen strategy – both internal and external – are still at an emergent stage. National targets remain modest, and policy remains ambiguous regarding the preferred production pathway. China’s long-term vision clearly emphasizes the role of renewable hydrogen to help balance an energy system dominated by wind and solar energy. However, current policy provides ample space for the promotion of other forms of hydrogen production. Rather, than a strong, centralized policy approach, local and provincial governments along with SOEs have been driving investment and policy experimentation in the sector, which includes efforts to boost fossil-based hydrogen production.

Beschreibung: As a variant of Support Vector Machine (SVM), Large Margin Distribution Machine (LDM) has been validated to outperform SVM both theoretically and experimentally. Due to the inevitable noise in real applications, the credibility of different samples is not necessarily the same, which is neglected by most existing LDM models. To tackle the above problem, this paper first introduces fuzzy set theory into LDM, and proposes a Fuzzy Large Margin Distribution Machine (FLDM) with better robustness and performance. Considering the noise and uncertainty in datasets, sample points farther from the center of homogenous class are less reliable. Therefore, a fuzzy membership function based on the distance to the class center is utilized to characterize the confidence of each sample, i.e., the degree to which the sample belongs to a certain category. Furthermore, different strategies are developed to obtain class centers for linearly separable and linearly inseparable problems. Experiments conducted on both artificial and UCI datasets verified the superiority of FLDM from different perspectives.

Beschreibung: The problem of network disintegration, such as suppression of an epidemic spread and destabilization of terrorist networks, possesses extensive applications and has lately been the focus of growing interest. Many real-world complex systems are represented by spatial networks in which nodes and edges are spatially embedded. However, existing disintegration approaches for spatial network disintegration focus on singular aspects such as geospatial information or network topography, with insufficient modeling granularity. In this paper, we propose an effective and computationally efficient virtual node model that essentially integrates the geospatial information and topology of the network by modeling edges as virtual nodes with weights. Moreover, we employ Kernel Density Estimation, a well-known non-parametric technique for estimating the underlying probability density function of samples, to fit all nodes, comprising both network and virtual nodes, to identify the critical region of the spatial network, which is also the circular geographic region where disintegration occurs. Extensive numerical experiments on synthetic and real-world networks demonstrate that our method outperforms existing methods in terms of both effectiveness and efficiency, which provides a fresh perspective for modeling spatial networks.

Beschreibung: Bioenergy with carbon capture and storage (BECCS) can help stabilize the climate by extracting carbon dioxide from the atmosphere while producing renewable energy. However, biomass availability would limit the potential of BECCS, and biomass cropland expansion may threaten biodiversity, food security, and water supply. Replacing land-intensive foods can help unlock sustainable biomass production. Here, we estimated BECCS energy and negative emissions using biomass grown on freed-up land when replacing animal-source foods. Biomass production excludes agricultural expansion to protect biodiversity, ensures enough food supply globally to safeguard food security, and constrains irrigation to secure water for people and ecosystems. Negative emissions consider supply chain emissions and the forgone sequestration from natural revegetation. Results show that replacing 50% of animal products by 2050 could release enough land for BECCS to generate 26.4–39.5 EJelec/year, the scale of coal power today, while removing 5.9–9.3 GtCO2e/year from the atmosphere, almost what coal power emits today.

Beschreibung: We investigated the influence of the El Niño-Southern Oscillation (ENSO) on inter-annual precipitation variability in the far-eastern Pacific (FEP) and northern South America (NSA) using an approach based on phase synchronization (PS). First, we carried out a detailed analysis of observational data to define the inter-annual variability, eliminate the seasonal residual frequencies in hydro-climatic anomalies, and assess the statistical significance of PS. Additionally, we characterized the seasonality of regional patterns of sea surface temperature, surface pressure levels, low-level winds and precipitation anomalies associated with the ENSO states. We found that the positive (negative) precipitation anomalies experienced in the FEP and NSA differ from those previously reported in the literature. In particular, the Guianas (northeastern Amazon) and the Caribbean constitute two regions with negative (positive) rainfall anomalies during El Niño (La Niña), separated by a zone of non-significant anomalies along the Orinoco Low-level Jet corridor. Moreover, we showed that the ENSO signal is phase-locked with inter-annual rainfall and low-level wind variability in most of the study regions. Furthermore, we found consistency in the PS between the Central and Eastern Pacific El Niño indices and hydroclimatic anomalies over the Pacific. However, some areas exhibited PS, although they did not show significant precipitation anomalies, suggesting that the influence of ENSO on tropical climatology manifests not only in terms of the magnitude of anomalies but also in terms of the phases only. Our approach advances the understanding of climatic anomalies in tropical regions and provides new insights into the non-linear interactions between ENSO and hydroclimatic processes in tropical Americas.

Beschreibung: Lack of nitrogen limits food production in poor countries while excessive nitrogen use in industrial countries has led to transgression of the planetary boundary. However, the potential of spatial redistribution of nitrogen input for food security when returning to the safe boundary has not been quantified in a robust manner. Using an emulator of a global gridded crop model ensemble, we found that redistribution of current nitrogen input to major cereals among countries can double production in the most food insecure countries, while increasing global production of these crops by 12% with no notable regional loss or reducing the nitrogen input to the current production by one third. Redistribution of the input within the boundary increased production by 6–8% compared to the current relative distribution, increasing production in the food insecure countries by two thirds. Our findings provide georeferenced guidelines for redistributing nitrogen use to enhance food security while safeguarding the planet.

Beschreibung: Oil seed crops are the second most important field crops after cereals in the agricultural economy globally. The use and demand for oilseed crops such as groundnut, soybean and sunflower have grown significantly, but climate change is expected to alter the agroecological conditions required for oilseed crop production. This study aims to present an approach that utilizes decision-making tools to assess the potential climate change impacts on groundnut, soybean and sunflower yields and the greenhouse gas emissions from the management of the crops. The Decision Support Tool for Agrotechnology Transfer (DSSAT v4.7), a dynamic crop model and the Cool Farm Tool, a GHG calculator, was used to simulate yields and estimate GHG emissions from these crops, respectively. Four representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), three nitrogen (0, 75, and 150 kg/ha) and phosphorous (0, 30 and 60 P kg/ha) fertilizer rates at three sites in Limpopo, South Africa (Ofcolaco, Syferkuil and Punda Maria) were used in field trials for calibrating the models. The highest yield was achieved by sunflower across all crops, years and sites. Soybean yield is projected to decrease across all sites and scenarios by 2030 and 2050, except at Ofcolaco, where yield increases of at least 15.6% is projected under the RCP 4.5 scenario. Positive climate change impacts are predicted for groundnut at Ofcolaco and Syferkuil by 2030 and 2050, while negative impacts with losses of up to 50% are projected under RCP 8.5 by 2050 at Punda Maria. Sunflower yield is projected to decrease across all sites and scenarios by 2030 and 2050. A comparison of the climate change impacts across sites shows that groundnut yield is projected to increase under climate change while notable yield losses are projected for sunflower and soybean. GHG emissions from the management of each crop showed that sunflower and groundnut production had the highest and lowest emissions across all sites respectively. With positive climate change impacts, a reduction of GHG emissions per ton per hectare was projected for groundnuts at Ofcolaco and Syferkuil and for sunflower in Ofcolaco in the future. However, the carbon footprint from groundnut is expected to increase by 40 to 107% in Punda Maria for the period up to 2030 and between 70-250% for 2050, with sunflower following a similar trend. We conclude that climate change will potentially reduce yield for oilseed crops while management will increase emissions. Therefore, in designing adaptation measures, there is a need to consider emission effects to gain a holistic understanding of how both climate change impacts on crops and mitigation efforts could be targeted.

Beschreibung: The planetary boundaries framework defines a safe operating space for humanity. To date, these boundaries have mostly been investigated separately, and it is unclear whether breaching one boundary can lead to the transgression of another. By employing a dynamic global vegetation model, we systematically simulate the strength and direction of the effects of different transgression levels of the climate change boundary (using climate output from ten CMIP6 models for CO2 levels ranging from 350 ppm to 1000 ppm). We focus on climate change-induced shifts of Earth’s major forest biomes, the control variable for the land-system change boundary, both by the end of this century and, to account for the long-term legacy effect, by the end of the millennium. Our simulations show that while staying within the 350 ppm climate change boundary co-stabilizes the land-system change boundary, breaching it (〉450 ppm) leads to its critical transgression with greater severity, the higher the ppm level rises and the more time passes. Specifically, this involves a poleward treeline shift, boreal forest dieback (nearly completely within its current area under extreme climate scenarios), competitive expansion of temperate forest into today’s boreal zone, and a slight tropical forest extension. These interacting changes also affect other planetary boundaries (freshwater change and biosphere integrity) and provide feedback to the climate change boundary itself. Our quantitative process-based study highlights the need for interactions to be studied for a systemic operationalization of the framework.

Beschreibung: Ecosystems are under multiple stressors and impacts can be measured with multiple variables. Humans have altered mass and energy flows of basically all ecosystems on Earth towards dangerous levels. However, integrating the data and synthesizing conclusions is becoming more and more complicated. Here we present an automated and easy to apply R package to assess terrestrial biosphere integrity which combines 2 complementary metrics: The BioCol metric quantifies the human colonization pressure exerted on the biosphere through alteration and extraction (appropriation) of net primary productivity, whereas the EcoRisk metric quantifies biogeochemical and vegetation structural changes as a proxy for the risk of ecosystem destabilization. Applied to simulations with the dynamic global vegetation model LPJmL5 for 1500–2016, we find that presently (period 2007–2016), large regions show modification and extraction of 〉25 % of the preindustrial potential net primary production, leading to drastic alterations in key ecosystem properties and suggesting a high risk for ecosystem destabilization. In consequence of these dynamics, EcoRisk shows particularly high values in regions with intense land use and deforestation, but also in regions prone to impacts of climate change such as the arctic and boreal zone. The metrics presented here enable global-scale, spatially explicit evaluation of historical and future states of the biosphere and are designed for use by the wider scientific community, not only limited to assessing biosphere integrity, but also to benchmark model performance. The package will be maintained on GitHub and through that we encourage application also to other models and data sets.