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Optimizing Resilience in Sports Science Through an Integrated Random Network Structure: Harnessing the Power of Failure, Payoff, and Social Dynamics
Get PDFThis study focuses on understanding risk-aversion behaviours in sports science by examining system dynamics and network structures. Various network models for real-world sports were analyzed, leading to the development of a comprehensive computational algorithm that captures the interactive properties of networked agents. This algorithm dynamically estimates the likelihood of systemic risk propagation while optimizing principles related to failure, reward, and social learning within the network. The findings suggest that despite the inherent risks in sports-centric network structures, the potential for protection can be enhanced through strategically developed, interconnected methods that emphasize appropriate investment. Strong social learning interactions were found to reduce the probability of failure, whereas weaker interactions resulted in a broader distribution of eigenvector centrality, increasing the risk of failure propagation. The study highlights key conceptual and methodological advancements in applying system dynamics to sports science. Furthermore, advanced agent-based network simulations offer deeper insights into the protective potential of interconnected management strategies, offering solutions to mitigate instability and cascading risks in sports
Closing the gap: Integrating behavioral and social dynamics through a modular modelling framework for low-energy demand pathways
Get PDFDemand-side pathways play a key role in achieving the 1.5-degree target and enhancing human well-being. Achieving this requires establishing a systematic bridge between social sciences and climate-energy-economy assessment tools, such as models. The IPCC's sixth assessment report faced challenges in providing robust demand-side scenarios, primarily due to the intricate nature of this challenge and existing knowledge gaps. Nevertheless, it emphasizes the urgent need for a more thorough examination of demand-side pathways. Policymakers and stakeholders are in dire need of improved decision support tools capable of anticipating demand-side interventions, especially behavioral and social interventions, and guide the planning of low-energy demand pathways. In this perspective, we comprehensively assess the drivers of change in the transition toward low-energy demand. We categorize these drivers into behavioral and socio-cultural factors, technological and infrastructural design and adoption, and institutional settings. Moreover, we propose a modular architecture and a complementary modelling framework that facilitates nuanced, policy-relevant scenario exploration. Such exploration is essential for translating scientific insights into actionable measures. Additionally, we call for a comprehensive community effort to co-create and co-develop this modular and complementary modelling platform
Robust Assessments of Lithium Mining Impacts Embodied in Global Supply Chain Require Spatially Explicit Analyses
No full textLithium is a critical material for the energy transition, but its mining causes significant environmental impacts that will intensify due to surging global demand. Here, we conduct a mining site-specific environmental impact assessment of lithium on a global scale, focusing on greenhouse gas (GHG) emissions, water use, and land use. We then track the production and international trade flows of all lithium-containing commodities to assess how lithium mining impacts are distributed across global supply chains. Results indicate that environmental impact intensities of battery-grade Li2CO3 production from various mine sites differ between 4 times for GHG emissions to 2885 times for land use. 56-68% of environmental impacts generated in the mining countries were embodied in internationally traded lithium flows. On the production side, China, Australia, and Chile were the top 3 countries, accounting for 91-94% of environmental impacts. Regarding final demand, China was the major consuming region, inducing 46-47% of the environmental impacts of global lithium mining, followed by Korea (17-18%) and the EU-27 (9%). Our findings reveal the need for spatially explicit information to accurately assess the environmental impacts of lithium mining and highlight that mitigation requires cooperation between major producer and consumer countries
Filling the Gaps: Tracing 12 Types of Non-commodity Plastics in China’s Plastic Socioeconomic Metabolism
No full textRecent plastic flow research has largely focused on commodity plastics (PE, PP, PVC, PS, ABS), yet a sizable share of other polymer types remains understudied. These non-commodity plastics suffer from inconsistent definitions, complex classifications, and data gaps, which hinder accurate assessment of their production, use, and end-of-life management. This study develops dynamic material flow analysis to investigate 12 key "non-commodity" plastics in China─including PET, PU, seven engineering plastics, and three thermosetting plastics─and addresses these knowledge gaps. Our results show that in 2022, China produces approximately 85 million tonnes of these polymers, a volume comparable to commodity plastics, with 35% used in plastic products and the remainder in non-plastic applications (e.g., fibers, rubber). PET is predominantly employed in short-lifespan packaging, whereas PU, engineering plastics, and thermosetting plastics find use in longer-lifespan applications, underscoring the need for targeted recycling strategies─particularly chemical recycling for PU and thermoset products. Revisiting the scope of "plastics" using scientific criteria can help mitigate definitional ambiguities and guide more effective policymaking. By improving data availability and tracking this underexplored non-commodity category, our study lays the groundwork for more accurate assessments and interventions to reduce plastic pollution
Using net-zero carbon debt to track climate overshoot responsibility
Get PDFCurrent emissions trends will likely deplete a 1.5 °C consistent carbon budget around the year 2030, resulting in at least a temporary exceedance, or overshoot. To clarify responsibilities for this budget exceedance, we consider “net-zero carbon debt,” a forward-looking measure of the extent to which a party is expected to breach its “fair share” of the remaining budget by the time it achieves net-zero carbon emissions. We apply this measure to all vetted mitigation scenarios assessed in the Intergovernmental Panel on Climate Change’s Sixth Assessment Report and two scenarios that model current policies and pledges, using an illustrative equal per capita allocation of a remaining 1.5 °C carbon budget starting in 1990. The resulting regional carbon debt estimates inform i) the scale and pace of regional carbon drawdown obligations necessary to address budget exceedance and ii) relative regional responsibilities for increased lifetime exposure to extreme heatwaves across age cohorts due to budget exceedance. Our work strengthens intergenerational equity considerations within an international climate equity discourse and informs the implementation of effort-sharing mechanisms that persist beyond the exhaustion of a rapidly dwindling remaining carbon budget
The breadth and potential of systems analysis across Africa
No full textSystems analysis is a multidisciplinary scientific approach that examines complex entities and dynamics by "perceiving and understanding the whole", which emerges from the properties and interactions of the individual parts and processes involved. For instance, the collapse of many ecosystems or entire cultures can only be explained by accounting for the interplay of crucial components (such as species, sectors, and norms) with each other and their natural or social environments. Therefore, systems analysis, which employs advanced cognitive tools such as complexity science, simulation modeling or AI-based pattern recognition, is often the best option for addressing the global challenges we currently face or will face in the near future, including global warming, extreme climate and weather events, biodiversity loss, food security, soil quality degradation, water scarcity and quality, social inequality, and technological disruption
Citizen science for data-informed, resilient cities
Get PDFNature-based solutions are crucial for addressing urban environmental challenges by enhancing climate resilience, improving biodiversity, and promoting mental well-being. However, their effective implementation requires a Nexus-driven, integrated approach that bridges ecological, social, and governance dimensions. The Urban ReLeaf project exemplifies this paradigm by fostering citizen science as a process for cross-sectoral collaboration, ensuring that data-driven greenspace policies align with broader sustainability objectives.
In six European cities - Athens, Cascais, Dundee, Mannheim, Riga, and Utrecht - citizen science plays a pivotal role in resource management by generating critical, multi-dimensional datasets that inform policy interventions. Athens is advancing participatory urban greening through a community-supported tree registry, strengthening urban ecosystem governance. Through map-based surveys Cascais incorporates citizen-reported perceptions into climate-responsive greenspace planning, while Dundee co-develops strategies with socially vulnerable communities gathering perceptions of greenspace and nature whilst exploring far-future 'what if...' scenarios.’ Mannheim integrates citizen-collected data on urban tree conditions into greenspace management, ensuring evidence-based decision-making. In Riga, collaborative air pollution monitoring fosters interdisciplinary insights into the air quality and urban greenspace relationship, supporting urban resilience strategies. Utrecht mobilizes local groups to assess microclimatic variables using wearable sensors in green-deprived neighborhoods, reinforcing the need for data-driven mitigation strategies in climate adaptation.
Urban ReLeaf illustrates how citizen science, data-informed policy innovation, and integrated urban planning can break down sectoral silos and drive sustainable resource management. The presentation will highlight the transformative potential of citizen science in operationalizing the Nexus approach, fostering collaborative governance and ensuring that urban ecosystems serve both environmental and societal needs
Climate change impacts on two European crop rotations via an ensemble of models
Get PDFContinuous long-term simulations of an ensemble of nine crop models covering the 1961–2080 period was employed to assess the expected impacts of climate change on the crop yield and water use for distinct crop rotations (CRs) in Europe. In this study, the likelihood of changes in two differently managed CRs (conventional and alternative) involving four important field crops (winter wheat, spring barley, silage maize, and winter oilseed rape) was assessed. The conventional agricultural practice (CR1) included only mineral fertilization with the removal of crop residues after harvest. The alternative agricultural practice (CR2) included cover crops and the application of mineral and organic fertilizers, with crop residues retained in the field. The simulations covered six sites in five European countries (Mühldorf and Müncheberg in Germany, Ukkel in Belgium, Ødum in Denmark, Milhostov in Slovakia and Lednice in Czechia) based on two distinct soil profiles (universal soil and site-specific soils). The universal soil was the same across all the sites, while the site-specific soils were typical of each region. Eight transient climate change scenarios (4 general circulation models (GCMs) under representative concentration pathways (RCPs) 2.6 and 8.5) were used to capture the possible evolution of future climatic conditions. Compared with those during the 1962–1990 period, the ensemble projections for the 2051–2080 period indicated average increases in the annual yields of all crops of 0.7 t/ha (RCP 2.6) and 0.8 t/ha (PCP 8.5) under both CRs and soil types. Under most climate change scenarios, the crop model ensemble projections of the winter wheat and winter oilseed rape yield increases agreed for CR2 but not for CR1. For spring barley, the simulated increase was more sporadic, with no significant difference between CR1 and CR2. In regard to silage maize, the changes in the simulated yields depended on site-specific climatic conditions. If the same varieties were planted in the future, yield reductions would be expected, except at the Ødum site, where the silage maize growth conditions would remain satisfactory, regardless of the CR and soil type. The results indicated greater cover crop biomass production, which could affect the long-term soil water balance and groundwater replenishment. The crop model ensemble further indicated a greater spatial variability in the yield can be expected, which is likely caused by the expected increase in the air temperature and not by the expected increase, or even decrease, in the total precipitation and increases in the actual evapotranspiration under climate change at all sites. This trend was greater under CR2 and could affect the long-term soil water balance and soil regime in the case of rainfed agriculture
The association of temperature extremes, ecosystem resilience, with child mortality: Novel evidence from India
No full textThe present study investigates how ecosystem resilience affects children's health and acts as a protective shield against high temperature exposure. Ecosystem resilience is the ability of an ecosystem to absorb anthropogenic or climatic shocks and recover from those shocks. The study used various data sources to estimate the impact of temperature extremes on child mortality in India. Data on neonatal mortality (NMR) and infant mortality (IMR) were obtained from the National Family Health Survey (NFHS-5) conducted between 2019 and 2021. Satellite data were used to assess extreme heat and ecosystem resilience. Univariate and bivariate Local Indicator of Spatial Autocorrelation (LISA) analysis were applied to examine the spatial association of high temperature, ecosystem resilience, and NMR, IMR. Further, a multivariate Cox hazard model, taking into account the censored data, was used to estimate mortality risk in high temperatures and non-resilient ecosystems. The spatial regression model reveals a significant association between higher temperatures and higher NMR (β: 1.78) and IMR (β: 1.79). The cox-proportional hazard models show elevated risks for neonatal and infant deaths due to high temperatures and non-resilient ecosystems. The resilience of the ecosystem plays an important role in exerting a positive effect on children's health, though, at its current state, resilience fails to moderate the high temperature impact on mortality. The present study, the first of its kind in India, highlights the exposure to high temperatures leading to neonatal and infant deaths when reliance imparts limited protective effect to offshoot the impact of high temperature on excess mortality
A critical review of heat pump adoption in empirical and modeling literature
Get PDFHousehold electrification is an important pillar of decarbonization in the US and requires the rapid adoption of electric heat pumps. Household energy models that project adoption rates do not represent these decisions well. To what extent are they limited by fundamental knowledge gaps, or is there scope to incorporate insights from the social science literature? We review the energy modeling and social science literature on heating equipment adoption to synthesize our understanding of adoption decisions, to identify best practices on representing decision-making behavior among energy models, and to suggest model improvements. At the most aggregated level, market allocation models divide market shares among different technologies by considering a single representative household, ignoring heterogeneity among the actors. Energy-system models and agent-based models can include some disaggregation. Adoption decisions include two stages, one to retire existing equipment, and to select the preferred technology. Equipment breaking down, price shocks, and moving to a new house promote entering the first stage, but these factors are not widely explored in surveys. The empirical literature reveals considerable heterogeneity in what matters to people in choosing technology. Even cost considerations, which are the most widespread, vary in the components and the manner in which they enter decisions. Other considerations include comfort and reliability; whether decision-makers are urban, young and educated; and how adopters perceive novel technologies. However, the relative strengths of these factors and how they vary across the US population are not known. Modelers can make incremental structural improvements such as separating the two decision stages, differentiating household groups, and incorporating changing household perceptions with market maturation. However, they cannot ground these in reality without considerable new fieldwork on decision-making processes and their variation across the population