Extreme heat events are rising significantly, posing a growing threat to public health in cities worldwide. Heat Action Plans (HAPs) have emerged as a critical tool for cities to proactively prepare for, manage, and mitigate the impacts of extreme heat. This study offers the most comprehensive international assessment of HAPs to date. We analyze the content of local government HAPs worldwide and validate the findings with academic and practice-oriented guidance. We find that cities focus more on heat management strategies than heat mitigation, with emergency preparedness and heat education far outpacing urban greening or waste-heat-reduction measures. Our analysis also reveals heat governance as a third, and previously underemphasized, area of heat action, encompassing: research; planning, policy, and program development; leadership; funding; and community engagement. This study provides a robust evidence base to inform the next generation of HAPs and equips practitioners with actionable insights to refine and strengthen their design, implementation, and evaluation.
National Adaptation Plans (NAPs) are assuming a central role as a policy framework for adaptation, protecting from climate impacts if they thoroughly respond to risks. We present a comprehensive global review of all 60 NAPs submitted to the UNFCCC by developing country parties as of March 1st, 2025. Through the NAP-Good Practices Review Framework, plans are evaluated across the important dimensions of NAP-Coverage and NAP-Consistency. We find that, on average, NAPs contain three-quarters of the elements defining a good NAP—with higher scores for NAP-Consistency than NAP-Coverage. NAPs cover the factbase on vulnerabilities and risks well, followed by policies, goals, and implementation specifics. Developing robust monitoring and evaluation, participation, and finance components seems more difficult. We highlight good practices across all components of the NAP-GP framework, along with actionable, contextual policy recommendations to enhance the quality of NAPs, promote peer-to-peer exchange, and strengthen global adaptation efforts in alignment with the objectives of the Paris Agreement and its Global Goal on Adaptation.
Migration, whether of trees, animals or humans, is a universal ecological response to environmental change. Yet scientific and policy frameworks treat these processes in isolation, obscuring their shared temporal structure and coupled dynamics. Reframing migration as a temporally layered, cross-species phenomenon enables more coherent climate governance, more equitable policy, and more effective conservation across taxa, sectors, and regions. This reframing must, however, be grounded in legal authority to act.
Calls to co-produce climate adaptation research with communities are multiplying, yet engagement often remains shallow: communities are consulted, not granted shared authority over how problems are framed, findings are interpreted, and outputs are used. This Perspective distinguishes instrumental engagement from epistemic partnership, and argues that the main barrier to meaningful co-production is institutional rather than methodological. It offers insights for participation that is rigorous, ethical, and institutionally workable, structured around three stages of shared authority.
AI development’s current trajectory risks automating and amplifying the North-South divide in the global climate information system. Frontier models are built almost exclusively in the Global North, and this inequality continues through inputs, processes, and outputs, from biased training data to unrepresentative validation, disproportionately affecting vulnerable regions. Addressing these disparities requires a Climate Digital Public Infrastructure, evaluation metrics centring well-being, and knowledge co-production to foster resilience rather than inequity.
Abstract The net climate impacts of artificial intelligence (AI) depend largely on how its applications propagate through competing energy pathways. Predominant analyses examine the relationship between datacenter energy demand, renewables optimization, and demand-side efficiencies, but insufficiently address how AI also reshapes fossil fuel supply economics. We instead model AI as a bidirectional productivity amplifier in a global computable general equilibrium model, quantifying both enabled emissions from fossil fuel productivity gains and avoided emissions from renewables productivity gains. Under parallel adoption scenarios, net annual CO₂ emissions increase by 0.47–1.8 gigatonnes (1.2–4.8% of 2024 global energy-related CO₂ emissions). Enabled emissions exceed avoided emissions whenever fossil-sector gains are nonzero; net emissions reductions require renewables gains 4–5× greater than fossil fuel gains. Absent policy steering, AI’s modeled effects increase the carbon intensity of the global economy and reinforce fossil fuel incumbency—outcomes that current analytical and governance frameworks do not fully capture.
Urban climate action has shifted from agenda-setting to delivery, yet existing knowledge offers limited tools for comparing how interventions are implemented across cities. Governance theories are analytically rich but too abstract for implementation. Case studies and practitioner toolkits are practically useful, but they document delivery mechanisms and enabling conditions inconsistently. This paper addresses this ‘missing middle’ by proposing five climate delivery modes: recurring, non-exclusive delivery configurations defined by a core mechanism of change and an enabling bundle required to activate them.
Individual pro-environmental behaviours are often promoted as a pathway to broader climate engagement, yet critics argue they may divert attention from more impactful systemic solutions. Using four annual waves of longitudinal survey data from Australia (2021–2024; N = 2778), we examined whether everyday climate actions predict collective action and policy support, and whether climate change risk perception, efficacy beliefs, and personal norms moderate these associations. Multilevel models showed that individual actions were consistently associated with greater collective engagement and, to a lesser extent, stronger policy support within the same year. Moderation analyses indicated that individual actions more strongly predicted collective engagement among individuals higher in risk perception, efficacy, and personal norm. In contrast, the association with policy support weakened slightly at higher levels of these moderators, although these moderation effects were very small. Random-intercept cross-lagged panel models provided little evidence of systematic spillover across years, indicating that within-person changes in individual actions did not reliably predict subsequent changes in collective action or policy support. Overall, the findings challenged the crowding-out effect and suggested that increases in individual action do not undermine broader forms of climate engagement.
Addressing climate change with the necessary urgency will only be successful if climate policies are perceived as socially fair and equitable by the majority of the population. However, as recognised in the IPCC Sixth Assessment Report (AR6), energy and climate modelling still struggles to bring together detailed economic and inequality impacts of climate policies. To help reduce this gap, we link GCAM-Europe, a geographical expansion of a well-established integrated assessment model, with MEDUSA, a tool for high-resolution distributional analysis. Our analysis explores how different implementations of the European Union (EU)‘s climate policy portfolio affect various consumer groups across and within Member States. It finds that a general EU-wide carbon price, while cost-efficient, has regressive impacts, disproportionately burdening low-income Member States and households. In contrast, policies based on national plans (NECPs) are less regressive. Gender and the urban-rural dimension also play an important role, with man-headed and rural households being the most affected.
Did U.S. voters reward incumbents in the House of Representatives for the investments from the 2022 Inflation Reduction Act (IRA)? Using an instrumental variable (IV) approach, we examine changes in incumbents’ vote share in 349 contested districts between the 2022 and 2024 U.S. congressional elections. Voters could reward members for publicly claiming credit for IRA investment in their district, or for the economic growth the district might have experienced. We find that, after controlling for economic growth, incumbents in districts with higher IRA investments experienced a vote share gain, irrespective of party affiliation. Specifically, a 1% increase in the log IRA investment led to a 1.29% increase in the incumbents’ vote share. Results are more consistent with incumbents’ credit claiming around IRA investments rather than short-term economic growth that might have resulted from this funding. Also, not a single Republican supported the IRA, although in their 2024 campaigns, many took credit for IRA investments. Thus, voters rewarded incumbents not for their House vote on the IRA bill, but for the investments that emerged from the IRA. Our results suggest that voters may credit House members with the federal pork the district receives, rather than with the legislation they voted on.
Current Loss and Damage frameworks remain largely reactive, prioritising post-disaster response. We argue for better integration of ex-ante and ex-post approaches, including building back better strategies, to break recurring cycles of loss and recovery. Drawing on a scoping review, selected case studies, and expert consultations, we identify three enabling conditions- robust knowledge systems, inclusive governance, and flexible finance- to strengthen both short-term recovery and long-term resilience.
Climate change adaptation demands actionable knowledge to navigate complex, context-specific risks. Existing frameworks for climate literacy that rely on climate science awareness fall short of enabling effective adaptation. This article introduces climate change adaptation literacy as a distinct capability bridging the knowledge-to-action gap. Drawing on conceptual and empirical literature, we propose a five-pillar framework: understanding climate impact pathways, risk perception and interpretation, adaptation competencies, reflexive and learning capacities, and ethical and emotional engagement. We review global literacy patterns, sectoral applications, and barriers to adaptive action. Distinguishing adaptation literacy from climate literacy, we argue for a transformative approach that includes integrating diverse knowledge sources, participatory governance, and justice-oriented strategies. Strengthening adaptation literacy is essential for climate-resilient development and locally led adaptation. We outline research priorities for embedding adaptation literacy across education, policy, and professional practice.
The Intergovernmental Panel on Climate Change (IPCC) regularly publishes summaries for policymakers (SPMs) following the principle of policy-neutrality. As the urgency of climate change grows, there have been calls for IPCC assessments to be more solution-oriented, which means to assess policy instruments. Yet, there is a scholarly debate regarding whether and how it is possible to discuss policy instruments while staying policy-neutral. To inform this debate we conduct a content analysis of Working Group III SPMs on mitigation published in the last two decades. We find that the SPMs contain limited content on policy instruments with little change over time. This suggests that the SPMs have not yet become more solution-oriented while abiding by their policy-neutrality principle. On the other hand, we show that SPMs have shifted from emphasizing the cost-effectiveness of mitigation towards emphasizing projections of required emissions reductions. Thus, SPM content development is consistent with the evolution of ideas in global climate negotiations. Regardless of whether it chooses to amend its policy-neutrality principle, we recommend that the IPCC still strive to be more solution-oriented. For example, the IPCC could better support the growing ecosystem of national and local boundary organizations which can broker context-specific knowledge on policy instruments.
Climate change disproportionately affects persons with disabilities (PWDs), yet adaptation policies persistently neglect their specific needs. This study examines the integration of climate justice into adaptation policies affecting PWDs from 2011 to 2022, applying Schlosberg’s framework of distributional, procedural, and recognitional justice. Findings reveal critical gaps across all three dimensions: PWDs are systematically excluded from policy-making processes (procedural); no targeted resources are allocated for disability-specific adaptation (distributional); and PWDs are subsumed under broad “vulnerable groups” categories rather than recognized explicitly (recognitional). These omissions reinforce systemic inequalities and undermine inclusive climate resilience. The study argues that policymakers must adopt rights-based, inclusive approaches ensuring PWDs’ active participation, dedicating disability-specific funding, and strengthening disaggregated data collection to advance equitable and effective climate adaptation.
Climate adaptation excludes Disabled people from policymaking despite disproportionate exposure to climate harms. Recent scholarship identifies this as epistemic injustice but its mechanisms remain underexamined. We argue adaptation frameworks devalue Disabled people’s knowledge by categorising them as inherently vulnerable, presenting ableist perspectives as objective truth – a process operationalised through Integrated Assessment Models. Achieving epistemic justice requires rejecting false objectivity and co-producing adaptation scenarios with Disabled communities through iterative situated modelling.
Abstract Climate action is not constrained by a scarcity of options, but by how technologies, incentives, and power steer which innovations are scaled, which risks tolerated, and whose futures prioritised. Here, we apply a functional governance diagnostic to current popular experiments in ocean-based climate action. By systematically disentangling the functional dynamics shaping marine-climate governance, we identify strategic leverage points to responsibly navigate climate action in the ocean.
Organisations can drive the sustainability transition if employees and organisational culture are prepared to adopt sustainability-relevant changes. We present a multilevel framework that models the cognitive and emotional dimensions of readiness and resistance to sustainable changes in organisations. This framework is used to study change readiness for plant-based workplace lunches among 62 Danish organisations. Using multilevel latent class analysis, we identify three organisational clusters differing in change readiness. Higher change readiness correlates with reduced carbon footprints from workplace lunches. In ‘change-ready’ organisations, the carbon footprint is 28% (95% CI:16-40%) and 21% (95% CI:8-35%) lower than in ‘change-resistant’ and ‘mixed’ organisations, respectively. Additionally, an organisation’s change readiness level modifies when emotionally resistant employees engage in change-supportive behaviour. Our findings suggest that change agents must tailor sustainability goals to an organisation’s change readiness and resistance characteristics, and that academic scholars need to be alert to organisational heterogeneity when designing interventions.
Climate change and related health research increasingly informs global climate governance and health strategies, yet regional inequalities in scientific contribution, collaboration, leadership and scientific impact remain poorly understood. This study analyzes 53,978 publications on climate change and related health from a broader planetary health perspective encompassing human, environmental, and ecosystem health dimensions. We reveal that this field has become increasingly globalized and interconnected, shifting from an earlier Europe–North America dominance toward a more diversified structure co-led by Europe, Asia, and North America. However, substantial inequalities persist across continents. International collaboration remains dominated by North–North and North–South partnerships, whereas Africa and South America continue to contribute more often in supporting rather than leading roles. Inter-continental collaborations yield higher citation impact than intra-continental ones, and researchers from less-developed regions gain visibility largely through inclusion in networks anchored in the Global North. These findings reveal persistent structural asymmetries in global climate change and related health knowledge production and highlight the need for strengthening research capacity and promoting more equitable international collaboration to support global climate governance.
The EU's Corporate Sustainability Due Diligence Directive represents an ambitious regulatory experiment that transforms large corporations into gatekeepers of sustainable supply chains. This article provides a comprehensive governance analysis of the directive, drawing on regulatory theory and economic reasoning to reveal several overlooked incentive problems that may undermine its effectiveness. The article identifies environmental harm and human rights violations as "public bads" requiring intervention. However, the analysis demonstrates that the directive's enforcement mechanisms may produce perverse outcomes, creating risks of both over-deterrence and under-deterrence through its combination of regulatory fines and civil liability. The article explains why the EU's recent decision to deharmonise civil liability through the Omnibus Package does not resolve this problem. It further documents significant unintended consequences, including chilling effects on legitimate business activity and a statistical discrimination dynamic that may harm the very populations the directive aims to protect.
The global climate crisis demands innovative solutions, and artificial intelligence (AI), including large language models (LLMs), offers significant potential to improve efficiency and enable lower-carbon lifestyles. However, public concerns around data privacy may affect the use of AI-enabled, data-driven applications with potential climate benefits. Drawing on three empirical studies with a nationally representative UK sample (N = 2078), we show that heightened awareness of AI’s data collection practices reduces willingness to engage with such technologies - especially when perceived user benefits are low. We also find that data protection behaviours and greater familiarity with AI are associated with lower perceived risk, suggesting adaptive responses rather than disengagement. These behavioural dynamics highlight the importance of transparency, user agency and the integration of human and environmental dimensions into existing AI governance frameworks. Our results illustrate how public perceptions and everyday practices influence the social acceptance of digital innovations for sustainability.
