Introduction Climate governance is increasingly contested, with public acceptance of renewable energy projects such as wind farms often facing resistance. This study explores how different trust-building strategies, including science communication, co-creation, benefit sharing, and social media, affect public perceptions of wind energy across diverse socio-demographic groups in four European countries (Austria, Cyprus, Greece, and Spain). Methods Drawing on an experimental vignette-based survey developed within the EU-funded VERITY project, we assess the impact of these strategies on two contrasting demographic groups: Group 1 (young, urban, university-educated) and Group 2 (older, rural, without a university degree). Results Our findings reveal significant variations in trust and engagement, with Group 1 generally exhibiting more positive attitudes toward wind energy (mean score: 0.49), while Group 2 was neutral or slightly negative (−0.01). Benefit sharing emerged as the most universally effective strategy, improving perceptions across all groups, particularly among sceptical male respondents. Science communication was most effective among women, especially in Group 1, while social media showed minimal or negative impact. Discussion The study highlights the importance of tailoring trust-building strategies to different demographic contexts, emphasizing that a one-size-fits-all approach is inadequate for inclusive climate governance. These findings offer actionable insights for policymakers seeking to enhance public trust in renewable energy transitions, aligning local engagement strategies with broader climate diplomacy.

This study investigates how climate variability affects rural and urban electricity access differently and how these disparities influence agricultural transformation in the East African Community. Based on a panel dataset covering Kenya, Tanzania, Uganda, Rwanda, and Burundi from 2000 to 2024, we apply climate anomaly analysis, correlation assessment, and performance indexing to explore the links between climate shocks, infrastructure vulnerability, and development outcomes. The results show that rural electricity systems are consistently more sensitive to climate fluctuations than urban ones, with vulnerability indices ranging from 0.234 in Kenya to 1.234 in Burundi. Rather than narrowing, rural–urban electricity gaps widened in most countries, most notably by 23.5 percent in Tanzania and 14 percent in Burundi, while Kenya made substantial progress, reducing its gap by 15.2 percent. Countries with larger electricity access gaps also showed stronger negative correlations between climate variability and agricultural output, including −0.678 in Burundi, highlighting the importance of reliable electricity in reducing climate impacts. In contrast, Kenya’s near-zero correlation suggests that improved electricity access can help buffer agricultural systems from climate stress. These findings highlight a growing adaptation gap, where rural communities, despite facing greater exposure to climate risks, are often the least equipped to respond due to limited access to reliable electricity and enabling infrastructure. The study underscores the need to treat electricity access not only as a development priority but as a vital form of climate adaptation, and calls for spatially targeted, climate-resilient infrastructure strategies to promote equitable and sustainable rural transformation.

Arctic amplification caused by global warming is accelerating an unprecedented loss of Arctic sea ice due to thinning of multi-year sea ice and increased export through Fram Strait, which is the largest Arctic gateway for ice export. The transition to a thinner and younger Arctic ice cover has resulted in a steady surface albedo decline of 1.25–1.51% per decade, weakening the radiative cooling effect of sea ice by 0.04–0.05 W m – ² per decade. The Fram Strait ice export (FSIE) is a major sink in the Arctic ice mass balance, accounting for approximately 14% of the annual sea ice volume loss. As the ice becomes thinner, it drifts faster, leading to enhanced ice export. The annual and summer FSIE have increased by about 6% and 11% per decade, respectively, further accelerating Arctic sea ice decline. Surface Albedo Modification (SAM) has been considered among variety of climate intervention solutions to slow down the transition of the Arctic into a seasonally ice-free ocean by mid-century, in concert with the greenhouse emissions mitigation efforts. Using climate model simulations, we evaluate the impacts of SAM application on the Arctic radiation budget and ice cover in two deployment scenarios: Arctic-wide and regional in Fram Strait. We model such an increase in sea ice albedo as a perturbation to the present-day climate state. Our results show that enhancing the surface albedo by up to 20% Arctic-wide during summer reduces the absorbed radiation at the surface by 11.16 W/m² and increases outgoing radiation at the top of the atmosphere by 10.70 W/m². This results in surface cooling of –1.33°C and recovers approximately 10% of the present-day Arctic sea ice radiative cooling power. These findings suggest that large-scale surface albedo modification could offset Arctic warming and contribute measurably to global cooling. The regional targeted deployment in Fram Strait yields more spatially limited but dynamically significant responses. SAM in Fram Strait enhances surface albedo both locally and in adjacent regions (Barents, Kara Sea) through advection of thicker, more reflective ice. The resulting radiative cooling alters atmospheric circulation, strengthening the low-pressure system over the Barents–Kara sector and triggering a negative Arctic Dipole pattern. This reduces sea-ice export by 2.4% through Fram Strait via weakening the Transpolar Drift in addition to the local thickening and slowing of the ice in the FS region, supporting ice retention within the Arctic basin. Furthermore, the modified atmospheric circulation induces dynamically driven nonlocal ice growth in areas of Central Arctic which persist year-round. These results highlight the potential of Fram Strait albedo enhancement to support multi-year ice recovery and reduce its loss via the Fram Strait. While basin-wide SAM offers the greatest potential benefits, it remains logistically challenging and carries higher risks of unintended consequences. Targeted regional interventions—such as in the Fram Strait and marginal seas (Barents, Kara, and Beaufort)—present a more feasible and cost-effective alternative, with lower risks and the potential to induce basin-wide responses through coupled atmosphere–ice–ocean interactions. These regions are dynamically linked to major circulation centers, including the Barents–Kara Low and Beaufort High, making them promising leverage points for intervention. A strategy for Arctic climate intervention, where a coordinated, regionally targeted, and seasonally adaptive deployment—combining summer albedo enhancement with winter ice thickening—may offer the greatest potential to stabilize Arctic sea ice while minimizing risks.

Background Climate change presents mounting challenges to coffee systems globally, driving the search for resilient agricultural strategies. Agroforestry has emerged as a promising climate adaptation approach, yet its effectiveness across diverse outcomes and contexts remains uncertain. Objective To systematically review scientific literature on (i) Climate change impacts on coffee production and (ii) Effectiveness of agroforestry-based adaptation and mitigation strategies using qualitative synthesis and meta-analysis for sustainable coffee cultivation. Methods Conducted a comprehensive search across 13 databases, screening 3,357 records. Sixty-eight studies (2000–2024) met inclusion criteria, assessing agroforestry impacts under climate-related stressors. Data extraction followed PRISMA 2020 guidelines. A random-effects meta-analysis was conducted on 68 effect sizes categorized into pest/disease incidence, yield loss and quality degradation. Heterogeneity, bias and publication quality were assessed using ROBINS-I and GRADE-CERQual criteria. Results Agroforestry interventions reduced climate-related yield loss (OR = 0.67 [0.56–0.80], I 2 = 0%), pest and disease incidence (OR = 0.79 [0.67–0.95], I 2 = 0%) and quality degradation (OR = 0.74 [0.63–0.86], I 2 = 0%). The homogeneity across subgroups suggests consistent benefits across agroecological zones. However, most studies lacked PROSPERO registration and conceptual framing. Conclusion Agroforestry enhances adaptive capacity and farm resilience in coffee systems under climate stress. These effects are consistent across yield, pest and quality outcomes. To support theory-building, future studies should integrate resilience frameworks and improve methodological transparency. Findings provide actionable insights for climate-resilient coffee farming.

Several unknowns remain surrounding marine Carbon Dioxide Removal (mCDR) monitoring, reporting, and verification (MRV) practices and capabilities. Current in-situ sensor technology is limited (primarily pH and p CO 2 ), requiring calculations and assumptions to estimate changes in carbonate chemistry parameters, including total alkalinity (TA). Considering that cost, energy consumption, and accuracy of commercial sensors can vary by orders of magnitude, understanding how well existing sensors perform in an mCDR context is important for this emerging community. Likewise, documenting sensor limitations and how relatively simple models can optimize sensor deployments will improve MRV efforts and support protocol development. Here we (1) compare performance a variety of commercially available sensors in a blind mesocosm experiment simulating ocean alkalinity enhancement (OAE), and how sensor performance impacted carbonate chemistry estimates; (2) evaluate if sensors can distinguish the OAE signal from natural variability during a small scale OAE field test in Sequim Bay, WA, USA, and (3) use an idealized ocean biogeochemistry model to explore optimal sensor network design based on (1) and (2). Our mesocosm results indicate that correctly constraining pH uncertainty will be critical for accurate TA estimates with current sensor technology compared to the less impactful variation caused by uncertainty in p CO 2 (pH data that are presented throughout are reported on the total scale (pH T ) unless otherwise noted). Our pilot field test demonstrated that sensors were capable of distinguishing mCDR signatures from natural variability under optimal real-world conditions. Idealized modeling simulations of the field test showed that a range of sparse and dense (3 to 100) sensors sampling areas of detectable increases will underestimate the net change in surface pH by at least 35–55%, at both realistic and highly elevated alkalinity input levels. We also highlight the limitations of current sensing technology for MRV, and the importance of ocean biogeochemistry models as critical tools for predicting when and where mCDR signals will be detectable using available sensors. Overall, our findings suggest that commercially available p CO 2 sensors and some pH sensors will form an important backbone for mCDR MRV tasks, though complete MRV characterization will require these data to be used in combination with other tools.

This study examines the impact of oil price shocks on the stock performance of 73 listed banks—41 conventional and 32 Islamic—across dual banking systems in net oil-exporting and importing countries. Employing panel fixed-effects and two-stage least squares (2SLS) IV regressions, we address both endogeneity and unobserved heterogeneity. The results indicate that oil price fluctuations have a significant impact on bank stock returns, with a stronger negative effect during oil price declines, particularly those driven by demand-side shocks. Islamic banks are more sensitive to these fluctuations than their conventional counterparts, reflecting greater exposure to oil-dependent macroeconomic environments. Robustness checks confirm the presence of non-linear and asymmetric effects: bank stock returns respond more adversely to falling oil prices than to increases in oil prices. These responses differ systematically across bank types and levels of national oil dependency. Our findings underscore the importance of accounting for oil price risk in bank valuation and performance forecasting. For financial managers and investors, the results underscore the importance of incorporating oil-related risk factors into portfolio management, stress testing, and pricing models. For regulators and policymakers, the evidence supports the adoption of macroprudential tools such as countercyclical capital buffers and sector-specific supervisory frameworks to strengthen banking system resilience, particularly for Islamic banks operating in oil-dependent economies. Additionally, disclosure standards should be enhanced to improve transparency around oil price exposure, enabling better-informed decision-making across all stakeholder-dependent economies.

Climate change-related disasters represent nature’s response to the severe and cumulative damage generated by human activities. This article aims to examine such impacts by categorizing Latin American and Caribbean countries according to the number and type of natural hazard-induced disasters recorded between 2000 and 2022, and by assessing the correlation between disaster frequency and national greenhouse gas (GHG) emissions. The study adopts a documentary design with a quantitative and correlational approach. Data were obtained from the International Monetary Fund and Climate Watch Data. Analytical techniques include clustering, principal component analysis (PCA), and Pearson’s correlation coefficient. The clustering procedure identified five groups of countries, each characterized by distinct patterns in both the type and frequency of disasters. Findings reveal that Mexico, Brazil, and Colombia are the most affected countries. The PCA results highlight two principal dimensions: (1) hydrological events (floods, droughts, storms, and landslides) and (2) thermal phenomena (extreme temperatures and wildfires). Pearson’s correlation analysis demonstrates a moderate yet significant positive association between the incidence of climate change-related natural hazard-induced disasters and GHG emissions. This suggests that, although certain countries combine high levels of emissions with a high frequency of disasters, there are also countries with high disaster occurrence that are not among the largest GHG emitters.

This paper proposes to bridge the gap between traditional criminal law and environmental jurisprudence by redefining the harm principle proposed by Mill through the Environmental Harm and Human Risk Matrix. The Matrix classifies environmental harm and human risk as low, medium, and high impact, creating nine intersectional approaches to assess environmental harm based on its severity and irreversibility, the risk to human and non-human wellbeing, its intergenerational impact, and the ability to mitigate the impact. Through the Matrix, the paper identifies activities that should be assessed as violations with no criminal liability, harms that should have criminal liability and harms that are subject to interpretation by the executive and the judiciary thereby helping to understand environmental harm within the socioeconomic realities of the situation. The approach not only challenges anthropocentric legal paradigms but also the interpretation of the harm principle while treating the environment as a resource. The challenge to the anthropocentric legal paradigms integrates the socioeconomic realities, environmental harm to human and non-human beings and offers guidelines to differentiate violations requiring restorative approaches from crimes necessitating punitive action. The paper further argues that if environmental harm is purely perceived from the lens of the harm principle apportioning blameworthiness based on liability, culpability and accountability, then the entire human population commits environmental harm since the environment is a resource which is used/misused by all. The paper integrates both approaches while contextualizing the use/misuse of the environment as a resource and examines liability and culpability from the profit motive, wherein environmental harm is intergenerational, pervasive, long-term, and irreversible. However, social manifestations (order, disorder and strain in the society), behavior, culture and socioeconomic vulnerabilities on the utilization of the environment as a resource are imperative to understand environmental harm before affixing accountability. The paper develops a theoretical framework examining the relevant legal and criminological theories (deterrence, rational choice, etc.) and proposes a differential approach to assess environmental harm committed for profits and those committed by the marginalized and least advantaged members of society who invariably utilize environmental resources for survival and/or out of necessity. The paper further argues that sweeping punitive actions risk creating a ‘paradox of poverty’. The Matrix contributes to the current scholarship from the legal and sociological standpoint, arguing for a just, fair and equitable utilization of resources while ensuring an inclusive and sustainable policy to combat environmental violations and thus harm. The work contributes to global green criminology discourse urging transformative legal reforms to mitigate ecological violence and advance planetary justice.

Climate change impacts have driven initiatives like eco-village projects to implement Climate Change Adaptation (CCA) practices in vulnerable communities. However, their sustainability post-funding is uncertain. This study investigates how Relative User Satisfaction (RUS) and Critical Success Factors (CSF) influence CCA practice sustainability in Chamwino and Igunga agro-ecological zones, Tanzania. Using the Technology Acceptance Model (TAM) and Pinto’s Project Success Theory, we assessed RUS and CSFs’ comparative effects on sustainability. Data from 295 respondents implementing CCA practices were collected via using household surveys, Key Informant Interviews, and focus group discussion. Polychoric correlations, Multiple Correspondence Analysis, and multivariate ordered logit modeling evaluated sustainability (low, medium, high). Soil water conservation showed the highest sustainability (70.3%), followed by tree planting (66.3%), while energy-efficient cooking stoves had the lowest (48.7%). Strong correlations existed between soil water conservation, ox-drawn tillage, and tree planting ( p < 0.001), with weaker correlations for energy-efficient stoves ( p < 0.01). Perceived Image strongly influenced sustainability ( β = 0.912–1.198, p < 0.001), especially for tree planting, followed by Accountability ( β = 0.876–1.152, p < 0.001) and Transparency ( β = 0.567–0.784, p < 0.01). Self-efficacy ( β = 0.567–0.912, p < 0.05) and Usability ( β = 0.645–0.812, p < 0.001) also impacted sustainability, while Individual Performance had minimal effect. CSFs like Self-efficacy, Perceived Image, Accountability, and Transparency increased sustainability probability by 16.5–19.4%. Low sustainability reflects social and governance barriers. RUS and CSF significantly influenced CCA practice sustainability, enhancing resilience through user perceptions and institutional support. Policymakers should integrate RUS and CSFs into CCA strategies, prioritizing community engagement, institutional support, and targeted interventions like subsidies and training to enhance post-funding sustainability. These findings highlight the critical role of user-focused governance in sustaining CCA practices long-term.

Future climate projections indicate that Africa will experience significant increases in both mean and extreme temperature indices. These changes will be accompanied by notable shifts in precipitation patterns under a high-emission scenario (RCP8.5). Using climate simulations, this study assesses the potential impact of stratospheric aerosol injection (SAI) on projected mean and extreme temperature and precipitation across the continent. We analysed data from the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project, which simulates a set of SAI experiments under RCP8.5 emission scenarios with SO 2 injection into the tropical stratosphere at 22.8–25 km altitude (GLENS) and around 1 km above the tropopause (GLENS_low) and near the equator at around 20–25 km above ground (GLENS_eq). The results show that all SAI experiments (GLENS, GLENS_eq, and GLENS_low) exhibit substantial cooling effects, with GLENS_eq emerging as the most effective in reducing temperature extremes, particularly over Central and Southern Africa. However, despite successfully offsetting much of the RCP8.5-induced warming, the effectiveness of SAI varies across regions, leaving some regions, such as the Sahel and North Africa, with residual warming. In addition to its cooling effects, SAI could significantly alter precipitation patterns, introducing widespread drying and thereby reducing flood risks across the continent. While SAI could offset the projected increase in extreme precipitation under RCP8.5, it could simultaneously exacerbate drying trends over Central, Southern, and Northern Africa. These findings highlight critical trade-offs associated with SAI deployment, particularly for regions where agriculture and water resources depend heavily on rainfall, underscoring the need for regionally optimised geoengineering strategies that balance temperature moderation with hydrological stability. This study provides the first comparative analysis of tropical, equatorial, and low-altitude SAI impacts on the climate, revealing critical trade-offs for precipitation-dependent regions. The findings presented here are, however, specific to the SAI scenarios analysed (GLENS experiments), as a different SAI deployment scenario would lead to different conclusions.