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Artificial Intelligence Tools in Misinformation Management during Natural Disasters
Get PDFEnsuring accurate information during natural disasters is vital for effective emergency response and public safety. Disasters like earthquakes and hurricanes often trigger misinformation, complicating response efforts and endangering lives. Historical events, such as Hurricane Katrina and the COVID-19 pandemic, illustrate the harmful impact of false information. Artificial intelligence (AI), with technologies like natural language processing and machine learning, offers promising solutions for detecting and mitigating misinformation. This paper explores AI’s role in managing misinformation during disasters, highlighting its potential to improve disaster response, enhance public trust, and strengthen community resilience
Tracing inclusivity at UNFCCC conferences through side events and interest group dynamics
Get PDFInclusivity and transparency are the foundations of procedural justice in climate governance. However, concerns persist around the influence of business interest groups at United Nations Framework Convention on Climate Change (UNFCCC) Conferences of Parties (COPs). COPs have increased in size and complexity, obscuring agendas and organizational relationships. Here we analyse the discourse and networks of actors at COP side events from 2003 to 2023 using machine learning-based topic modelling and social network analysis. We trace how discussions on energy, food and forests have evolved. Focusing on energy topics, we show that fossil fuel lobbyists gain COP access through developed-country business non-governmental organizations (NGOs) and developing-country governments. Their nominators focus on renewable energy and system approaches but are peripheral in the anti-fossil fuel discourse which grew from a collaborative network of environmental NGOs. Despite data availability challenges, systematically tracing the inclusivity of COP processes can uncover power dynamics at the highest levels of climate governance
Twelve research agendas for advancing the peace-sustainability nexus
Get PDFThe world's social and environmental systems are currently experiencing an increase in the number of conflicts and irreversible human-induced changes. While destabilizing, these changes offer opportunities to advance the science involved to promote peace and sustainability. This forum outlines 12 key research agendas essential for advancing our understanding of the peace-sustainability nexus: global challenges (including the Anthropocene, disasters, and migration); socio-ecological systems (such as oceans, water, and heritage); policy solutions (focused on cities, food, and geoengineering); and guiding principles for peace and sustainability (emphasizing gender, justice, and plurality). Each agenda echoes the normative elements of peace and sustainability as processes while situating them within specific contexts. This approach works within limitations when mobilizing capacities to minimize unintended negative impacts of well-intentioned solutions. Beyond examining how each area either strengthens or weakens the relationship between peace and sustainability, this forum also encourages future research to explore the interconnections that might illuminate pathways for meaningful action. The brief overview of research trends and knowledge gaps can support future work in considering the capacities, constraints, and contexts underpinning the peace-sustainability nexus
Prioritizing involuntary immobility in climate policy and disaster planning
Get PDFGlobally, populations are increasingly located in areas at high risk of climate change impacts. Some populations lack the agency to move out of harm’s way, leading to involuntary immobility. The climate risks these populations face are insufficiently addressed in climate policy and disaster planning. While policy and planning should be data-informed, the lack of appropriate data should not limit governments and institutions from taking action to reduce the risk of involuntary immobility. Incorporating involuntary immobility within the broader sustainable development goals of climate action and safe, orderly, and regular migration may substantially reduce the risk of involuntary immobility
Informal and formal long-term care utilization and unmet needs in Europe: examining socioeconomic disparities and the role of social policies for older adults
Get PDFThe rising number of older adults with limitations in their daily activities has major implications for the demands placed on long-term care (LTC) systems across Europe. Recognizing that demand can be both constrained and encouraged by individual and country-specific factors, this study explains the uptake of home-based long-term care in 18 European countries with LTC policies and pension generosity along with individual factors such as socioeconomic status. Using data from the Survey of Health, Ageing and Retirement in Europe conducted in 2019, we apply a two-part multilevel model to assess if disparities in use of LTC are driven by disparities in needs or disparities in use of care when in need. While individual characteristics largely affect the use of care through its association with disparities in need, country-level characteristics are important for the use of care when in need. In particular, the better health of wealthier and more educated individuals makes them less likely to use any type of home-based personal care. At the country level, results show that the absence of a means-tested benefit scheme and the availability of cash-for-care benefits (as opposed to in-kind) are strongly associated with the use of formal care, whether it is mixed (with informal care) or exclusive. LTC policies are, however, shown to be insufficient to significantly reduce unmet needs for personal care. Conversely, generous pensions are significantly associated with lower unmet needs, underscoring the importance of considering the likely adverse effects of future pension reforms
A methodology to compile multi-hazard interrelationships in a data-scarce setting: an application to Kathmandu Valley, Nepal
Get PDFThis paper introduces a multifaceted methodology to identify and compile single natural hazards and multi-hazard interrelationships within the context of data-scarce urban settings, exemplified by Kathmandu Valley, Nepal. This approach integrates (i) five blended types of evidence to support a more nuanced and holistic understanding of a hazardscape where data are scarce and (ii) a 2-hour stakeholder workshop with seven participants to provide greater context to the hazards, consider their impacts through the co-production of multi-hazard interrelationship scenarios, and how this methodology could support more people-centred disaster risk reduction (DRR) strategies. We use blended evidence types, including academic literature, grey literature, media, databases, and social media, to systematically search for exemplars of single hazards and multi-hazard interrelationships that have influenced or could potentially influence Kathmandu Valley. We collated 58 sources of evidence for single hazards and 21 sources of evidence for multi-hazard interrelationships. Using these sources, our study identified 21 single hazard types across six hazard groups (geophysical, hydrological, shallow Earth processes, atmospheric, biophysical, and space/celestial hazards) and 83 multi-hazard interrelationships (12 that have direct case study evidence of previous influence in Kathmandu Valley) that might influence Kathmandu Valley. These exemplars are collated into two databases that accompany this paper. We supplement these exemplars with multi-hazard interrelationship scenarios and multi-hazard impacts developed by stakeholders engaged in DRR research and practice in Kathmandu Valley. The results illustrate the complexity of the hazard landscape, with many single hazards and multi-hazard interrelationships potentially influencing Kathmandu Valley. The research emphasises the importance of inclusive DRR strategies that recognise disaggregated impacts experienced by different social groups. This knowledge can inform the development of dynamic risk scenarios in planning and civil protection, thus strengthening multi-hazard approaches to DRR in “Global South” urban areas such as Kathmandu Valley
Improving accuracy, complexity and policy relevance: a literature survey on recent advancements of climate mitigation modeling
Get PDFProcess-based Integrated Assessment Models (IAMs) play a crucial role in climate agenda-setting and progress monitoring. They advise climate negotiations, inform nationally determined contributions (NDCs), and help create scenarios for central banks. Recent developments have enhanced IAMs' policy scope and accuracy, including the incorporation of industrial policies, improved sectoral details, and modeling of consumer behavior. Despite these advancements, challenges remain, particularly in improving spatio-temporal and sectoral resolution, adapting to fast-changing sector-specific policies, and addressing complex dynamics beyond the traditional techno-economic cost-minimization framework. This literature review explores Directed Technical Change (DTC) growth models, Agent-Based Modeling (ABM), and game theory to complement mainstream IAM approaches, especially in integrating political economy considerations. DTC emphasizes the role of public research and development (R&D) investment in supporting early-stage mitigation technologies. ABM highlights the decision-making processes and behaviors of heterogeneous agents, while game theory examines market dynamics, such as newcomer vs. incumbent competition, strategic pricing, and resource extraction. While these models cannot replace IAMs, they can broaden the scenario design space and improve the complexity and policy relevance of IAM-based mitigation modeling
Breaking Barriers with Patterns: New Tools for Integrating Distributional Justice into Global Mitigation Scenarios
No full textGlobal mitigation scenarios allocate resources in ways that align with specific climate targets under varying assumptions. These allocations inevitably raise questions of distributional justice. With scenarios becoming a major tool for global climate policy, the distributional implications of global mitigation scenarios are increasingly central to international political debates and negotiations. However, the scenario community lacks tools to systematically and transparently incorporate considerations of distributional justice in scenario development. This research addresses this gap by operationalizing philosophical concepts of distributional justice, referred to as justice patterns.
The justice patterns examined in this study include Aggregate Utilitarian (core idea: everyone benefits), Egalitarian (equal outcomes for all), Prioritarian (priority to those worst-off), Sufficientarian (ensuring everyone reaches a minimum threshold), and Limitarian (ensuring no one exceeds a maximum threshold). With two concrete applications we demonstrate that these justice patterns provide a useful framework for integrating distributional justice considerations in scenario development.
First, we quantify justice patterns to analyse the distributional logic of energy service access in scenarios from the AR6 database. Our findings reveal that Prioritatrian and Egalitarian patterns are the most prominent in AR6 scenarios, while Sufficientarian and Limitarian patterns remain underexplored, leaving a gap in the scenario space.
Second, we introduce an open-source web application that visualizes justice patterns as idealized trajectories, allowing stakeholders to explore and express their preferences for justice patterns in varying contexts. We demonstrate the tool’s potential to guide scenario development in a small pilot study.
We conclude by advocating for future scenario studies to systematically incorporate diverse justice patterns to examine potential conflicts between mitigation strategies and justice considerations. Furthermore, we recommend extending assessments beyond energy services to encompass non-material dimensions critical to socially acceptable futures, such as freedom and power. By operationalizing justice patterns, this research establishes a foundation for comprehensive scenario assessments on distributional justice and systematic stakeholder engagement
Cascading droughts: Exploring global propagation of meteorological to hydrological droughts (1971–2001)
Get PDFAn understanding of the spatiotemporal behaviour of Meteorological drought (MD) and Hydrological drought (HD) is crucial for analysing how drought propagation occurs. Here, drought events were treated as three-dimensional grid structures spanning space (latitude and longitude) and time. 31 years (1971–2001) of global MD and HD events were analysed for evidence of propagation, and the most severe 20 MD events explored in detail. From the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) data archive, precipitation data was used for identifying MD events and an ensemble of simulated runoff from several global hydrological models used for detecting HD events. A technique was developed based on overlapping of the spatial and temporal coverage of MD and HD events, to establish propagation, and to calculate several propagation features. In three dimensions, the transformation from MD to HD was characterised based on delayed instigation, elongated duration, and dampened intensity of the HD event. Additionally, pooling of MD events that resulted in one or multiple branched HD events were identified. Results indicate that minor MD events with short durations and small areas generally do not exhibit propagation. The frequency of HD events with drought duration of 6–12-months is higher than that of MD events with 6–12-month duration. Out of 1740 extreme MD events identified for the 31-year period, 272 events propagated and resulted in 395 extreme HD events. Propagation features for the 20 most severe MD events show substantial variation based on geographical location highlighting the influence of regional climatic and hydrological conditions. This study advances the understanding of global drought propagation mechanisms by addressing key methodological challenges and providing a structured framework for future large-scale drought assessments
Modeling impacts of food and fertilizer trade disruptions on global food security
Get PDFGeopolitical tensions are increasingly affecting global trade in food and essential agronomic inputs such as fertilizers. This imperils food production and security in import-dependent countries. Major disruptions, such as armed conflicts or the formation of isolated political blocs, are expected to further disrupt bilateral trade as countries tend to save resources for their own populations or because of the destruction of trade infrastructure. Countries not directly involved in such conflicts may also choose to stop exporting and start stockpiling products as a precautionary measure. This will create a situation where the global trade network will be fragmented.
This study estimates the consequences of such trade disruptions on fertilizer supply and food security through network analysis and statistical modeling using global data on food and fertilizer trade, fertilizer inputs, and crop yields. We consider several hypothetical scenarios, including a military conflict between major military alliances, political separation into major (emerging) blocs, economic scenario, where the world is divided into Global North and Global South, and stochastic scenarios that model probable division into groups based on the structure and intensity of historical trade between partners through community detection in graphs. A first prototype considers major staple crops: rice, wheat, maize, potato, and cassava.
The results demonstrate that in the event of a political, military, or economic separation that disrupts trade, Non-Aligned and Global South countries will experience dramatic reductions in the availability of certain critical crops and fertilizers, with losses of more than 25 percent compared to uninterrupted supplies in 2022. In the military scenario, Non-Aligned nations will be most sensitive to the decline in maize, wheat, and fertilizer, while in the political scenario, access to maize, potatoes, rice, and wheat will be problematic. The economic scenario shows drops in availability of maize, rice, cassava, wheat, and fertilizer for the Global South block. Military alliances, political blocs, and Global North countries have limited supplies of at least two critical crops in every scenario, but their losses are less disruptive (excluding cassava, which is expected to decline by 95 percent in the Global North). For all groups of countries, the drops in food supply are compounded by a further reduction in expected agricultural output due to the loss of fertilizer supplies. Stochastic network simulations generally provide more balanced scenarios as they are based on interwoven historical trade data. Further research will refine the results using process-based crop modeling and explore scenarios for improving the resilience of the global food system