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International organizations like the EU and IUCN are advocating for nature-based solutions (NBSs) as green alternatives for climate change adaptation and mitigation, especially in disaster risk reduction and urban planning. The H2020 OPERANDUM project was designed to address the major hydro-meteorological risks (floods, droughts, landslides, storm surge, and coastal erosions) through the deployment and assessment of NBSs in different contexts and areas affected by specific hazards. Despite growing research and funding, NBSs are still in the early stages of mainstream adoption and face challenges in acceptance and dissemination. Although designed to benefit both social and ecological systems, they remain a niche area with low perceived effectiveness among technicians and decision-makers. Their uptake requires a paradigm shift that includes a change in cultural-cognitive institutions, a different and wider set of knowledge than traditional engineering (ecological, social), and an adaptive management approach, missing within the current governance system. Using a qualitative case study research method, this paper aims to identify barriers in mainstreaming NBSs for DRR (disaster risk reduction) in the Emilia-Romagna region—influenced not only by individual beliefs but also by variables tied to technical culture and local procedural norms—and emphasizing the importance of combining social and ecological indicators in socio-ecological system analysis. [ABSTRACT FROM AUTHOR]

The potential of the environmental impact assessment (EIA) process to respond to climate change impacts of development projects can only be realized with the support of policies, regulations, and actors' engagement. While considering climate change in EIA has become partly mandatory through the EU revised Directive in Europe, African countries are still lagging. This paper assesses Tanzanian policies, laws, regulations, and EIA reports to uncover consideration of climate change impacts, adaptation, and mitigation measures, drawing from the transformational role of EIA. The methodology integrates content analysis, interpretive policy analysis, and discourse analysis. The analyses draw from environmental policy, three regulatory documents and three EIA reports in Tanzania using a multi-cases study design. The aim was to understand how considering Climate Change issues in EIA has played out in practice. Results reveal less consideration of climate change issues in EIA. The policy, laws, and regulations do not guide when and how the EIA process should consider climate change-related impacts mitigation and adaptation. The practice of EIA in the country is utterly procedural in line with regulations provisions. Consequently, environmental impact statements only profile the climatology of the study area without conducting a deeper analysis of the historical and future climate to enhance the resilience of proposed projects. The weakness exposed in the laws and regulations contributes to the challenges of responding to the impacts of climate change through the EIA process. It is possible to address climate change issues throughout the project life cycle, including design, approval, implementation, monitoring, and auditing, provided the policy and regulations guide how and when the EIA process should consider climate change issues. Additionally, increasing stakeholders' awareness and participation can enhance the EIA process's potential to respond to the impacts of climate change. [ABSTRACT FROM AUTHOR]

This study analyses macroeconomic trends in Southeast Asian countries and their implications for climate change, focusing on urbanisation, GDP per capita, energy intensity, FDI, inflation, and trade. Using panel data from 1970 to 2020, we investigate climate change drivers across Indonesia, Malaysia, the Philippines, Singapore, and Thailand through panel ARDL with PMG and MG analyses, along with Hausman tests. Our results highlight the need for tailored urbanisation policies for sustainability, as the consistent positive correlation between GDPs per capita and emissions, underscores the challenge of decoupling economic growth from emissions. Urbanisation's varying impact calls for proactive planning, and mixed FDI results suggest nuanced investment approaches aligned with sustainability. Inflation's negative impact hints at environmental benefits during price increases, necessitating integrated economic and climate policies. The positive relationship between trade openness and emissions emphasises the need for eco-conscious trade agreements to mitigate emissions from industrial activity. Our study stresses the importance of considering macroeconomic heterogeneity in crafting climate policies. Policymakers must adopt multifaceted approaches that prioritise sustainability across economic growth, energy efficiency, technology adoption, and trade to balance development with environmental preservation. This approach enables Southeast Asian countries to contribute effectively to global climate change mitigation. [ABSTRACT FROM AUTHOR]

The growing global population causes more anthropogenic carbon dioxide (CO2) emissions and raises the need for forest products, which in turn causes deforestation and elevated CO2 levels. A rise in the concentration of carbon dioxide in the atmosphere is the major reason for global warming. Carbon dioxide concentrations must be reduced soon to achieve the mitigation of climate change. Forest management programs accommodate a way to manage atmospheric CO2 levels. For this purpose, we considered a nonlinear fractional model to analyze the impact of forest management policies on mitigating atmospheric CO2 concentration. In this investigation, fractional differential equations were solved by utilizing the Atangana Baleanu Caputo derivative operator. It captures memory effects and shows resilience and efficiency in collecting system dynamics with less processing power. This model consists of four compartments, the concentration of carbon dioxide C(t), human population N(t), forest biomass B(t), and forest management programs P(t) at any time t. The existence and uniqueness of the solution for the fractional model are shown. Physical properties of the solution, non-negativity, and boundedness are also proven. The equilibrium points of the model were computed and further analyzed for local and global asymptotic stability. For the numerical solution of the suggested model, the Atangana-Toufik numerical scheme was employed. The acquired results validate analytical results and show the significance of arbitrary order ffi. The effect of deforestation activities and forest management strategies were also analyzed on the dynamics of atmospheric carbon dioxide and forest biomass under the suggested technique. The illustrated results describe that the concentration of CO2 can be minimized if deforestation activities are controlled and proper forest management policies are developed and implemented. Furthermore, it is determined that switching to low-carbon energy sources, and developing and implementing more effective mitigation measures will result in a decrease in the mitigation of CO2. [ABSTRACT FROM AUTHOR]

This comprehensive systematic review explores the multifaceted impacts of electric vehicle (EV) adoption across technological, environmental, organizational, and policy dimensions. Drawing from 88 peer-reviewed articles, the study addresses a critical gap in the existing literature, which often isolates the impact of EV adoption without considering holistic effects. Technological advancements include innovations in the battery technology and energy storage systems, enhancing EV performance and mitigating range anxiety. The environmental analysis reveals substantial reductions in greenhouse gas emissions, with lifecycle assessments showing significant reductions for EVs compared to internal combustion engine vehicles, particularly when charged with renewable energy sources. Key comparisons include lifecycle emissions between mid-size battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), and global average lifecycle emissions by powertrain under various policy scenarios. The organizational implications are evident, as businesses adopt new models for fleet management and logistics, leveraging EVs for operational efficiency and sustainability. Policy analysis underscores the crucial role of government incentives, regulatory measures, and infrastructure investments in accelerating EV adoption. The review identifies future research areas such as efficient battery recycling methods, the potential impact of EVs on grid stability, and long-term economic implications. This study offers insights for stakeholders aiming to foster sustainable transportation and achieve global climate goals. [ABSTRACT FROM AUTHOR]

Under the best circumstances, achieving or sustaining optimum ecological conditions in estuaries is challenging. Persistent information gaps in estuarine data make it difficult to differentiate natural variability from potential regime shifts. Long-term monitoring is critical for tracking ecological change over time. In the United States (US), many resource management programs are working at maximum capacity to address existing state and federal water quality mandates (e.g., pollutant load limits, climate impact mitigation, and fisheries management) and have little room to expand routine sampling efforts to conduct periodic ecological baseline assessments, especially at state and local scales. Alternative design, monitoring, and assessment approaches are needed to help offset the burden of addressing additional data needs to increase understanding about estuarine system resilience when existing monitoring data are sparse or spatially limited. Research presented here offers a pseudo-probabilistic approach that allows for the use of found or secondary data, such as data on hand and other acquired data, to generate statistically robust characterizations of ecological conditions in estuaries. Our approach uses a generalized pseudo-probabilistic framework to synthesize data from different contributors to inform probabilistic-like baseline assessments. The methodology relies on simple geospatial techniques and existing tools (R package functions) developed for the US Environmental Protection Agency to support ecological monitoring and assessment programs like the National Coastal Condition Assessment. Using secondary estuarine water quality data collected in the Northwest Florida (US) estuaries, demonstrations suggest that the pseudo-probabilistic approach produces estuarine condition assessment results with reasonable statistical confidence, improved spatial representativeness, and value-added information. While the pseudo-probabilistic framework is not a substitute for fully evolved monitoring, it offers a scalable alternative to bridge the gap between limitations in resource management capability and optimal monitoring strategies to track ecological baselines in estuaries over time. [ABSTRACT FROM AUTHOR]

This study investigates the application of Artificial Intelligence (AI) in monitoring and managing marine ecosystems to address the impacts of climate change on Kenya's Blue Economy. It aims to assess the threats posed by climate change to these ecosystems and explore the potential of AI solutions to enhance adaptation and resilience. The research employs a comprehensive review of secondary data sources, including academic publications, reports from reputable institutions, and other relevant materials. The study analyzes existing literature on AI applications in marine ecosystem management and climate change mitigation, focusing on the specific context of Kenya's Blue Economy. The study reveals that climate change poses significant threats to Kenya's marine ecosystems, including coral bleaching, ocean acidification, sea-level rise, and disruptions to ocean currents. AI technologies offer promising solutions for monitoring and managing these impacts, with applications in predictive modeling, resource optimization, and decision support. The research highlights the need for further exploration into specific AI applications tailored to Kenya's unique coastal challenges and the importance of incorporating diverse stakeholder perspectives. Additionally, it emphasizes the necessity for longterm impact assessments of AI technologies in the context of climate change mitigation. This study contributes to the growing body of knowledge on AI applications in environmental management, particularly within the context of Kenya's Blue Economy. By identifying the potential of AI to enhance resilience and sustainability in marine ecosystems, the research offers valuable insights for policymakers, researchers, and practitioners involved in climate change mitigation and adaptation efforts. [ABSTRACT FROM AUTHOR]

Purpose: This study builds on the panarchy theory by viewing the supply chain as a socio-ecological system and further expands it by considering the within-level linkages internal to the supply chain level. Three types of linkages are considered: the two cross-level linkages with the planetary and the political-economic levels and the supply chain within-level linkages. The research questions are addressed using the data gathered by the Carbon Disclosure Project within its Supply Chain Programme. Design/methodology/approach: This work aims to study, applying the lens of panarchy theory, how the planetary and the political-economic levels affect the supply chain within-level linkages for sustainability. Furthermore, the difference in how these cross-level linkages influence focal firms and first-tier suppliers is explored. Findings: The results show that considering the planetary-supply chain linkage, climate change risk exposure is likelier to foster within-level linkages with buyers than with suppliers. Further, climate change mitigation investments have different roles in the different tiers: focal firms are pushed to strengthen the linkages with their suppliers when they lose efficacy in improving their carbon performance, whereas first-tier suppliers exploit investments to gain legitimacy. Discussing the political-economic level effect, perceptions from first-tier suppliers could be two-fold: they could perceive a mandating power mechanism or exploit policymakers' knowledge to advance their capabilities. Originality/value: The results contribute to the sustainable supply chain management literature by providing empirical evidence of the cross-level linkages theorised by the panarchy theory. Moreover, the concept of within-level linkages is proposed to apply the theory in this field. [ABSTRACT FROM AUTHOR]

We present a framework for strategic dam planning under uncertainty, which includes GHG emissions mitigation as a novel objective. We focus on the Mekong River Basin, a fast‐developing region heavily relying on river‐derived ecosystem services. We employ a multi‐objective evolutionary algorithm to identify strategic dam portfolios for different hydropower expansion targets, using process‐related and statistical models to derive indicators of sediment supply disruption and GHG emissions. We introduce a robust optimization approach that explores variations in optimal portfolio compositions for more than 5,000 state‐of‐the‐world configurations, regarding sediment origins and trapping and GHG emissions. Thus, we can rank dam projects' attractiveness based on their frequency of inclusion in optimal portfolios and explore how uncertainty affects these rankings. Our results suggest that developing dams in the upper Mekong would be a more robust option for near‐term development than, for example, the lower Mekong and its tributaries, for both environmental and energy objectives. Our work presents a novel approach to better understand the basin‐scale cumulative impacts of dam development in high‐uncertainty, data‐scarce contexts like the Mekong Basin. Plain Language Summary: Hydropower is considered an important energy source to meet many climate mitigation targets. Its negative impacts are however often underestimated, including the emission of greenhouse gases (GHG) from reservoirs. This study introduces a framework for planning dams strategically in the Mekong River Basin, a region heavily dependent on river‐related services. The framework considers uncertainties and incorporates greenhouse gas emissions mitigation and sediment transport disruption as new objectives. Using a multi‐objective evolutionary algorithm, the research identifies optimal dam portfolios for different hydropower expansion goals. To consider uncertainties in the results, the analysis employs a robust optimization approach to assess over 5,000 state‐of‐the‐world configurations. Results indicate that developing dams in the upper Mekong is a more robust option for both environmental and energy goals in the near term. These conclusions showcase the approach's usefulness in understanding dams' cumulative impacts in data‐scarce and uncertain contexts like the Mekong Basin. Key Points: We identify optimal dam portfolios which balance hydropower expansion, sediment supply disruption, and GHG emissions in the MekongWe extracted optimal portfolios under multiple state‐of‐the‐world configurations, to extract robust indicators of project attractivenessResults suggest that near‐term dam development should focus more on the upper Mekong, compared to the lower Mekong and its tributaries [ABSTRACT FROM AUTHOR]

Developing countries, including Small Island Developing States (SIDSs) and Least Developed Countries (LDCs), are exceptionally vulnerable to climate change due to their distinct geographical and environmental characteristics. Escalating sea levels and heightened salinity levels imperil freshwater reserves, while warmer ocean temperatures and acidification disrupt water demand, tourism, health services, and fisheries. Concurrently, these countries bear the brunt of water shortages, flooding, and declining water quality. However, significant barriers such as limited financing capacities to fund water security initiatives, exacerbated by a growing debt crisis marked by escalating interest rates and inflation, hinder developmental progress and investments in climate adaptation and mitigation endeavors. Consequently, there arises a critical necessity to harness innovative financial mechanisms to transform these debts into opportunities that support effective climate action. This paper explores the potential of debt-for-climate swaps as a catalyst for advancing transformative wastewater projects, focusing on their strategic deployment to underpin critical initiatives. Through case studies and empirical evidence, the paper elucidates how debt-for-climate swaps can enhance sustainable wastewater management systems in developing countries and delineates best practices for leveraging these mechanisms and the roles and responsibilities of key stakeholders, including governments, policymakers, the private sector, communities, and climate financial institutions. Combining theoretical insights with tangible examples, this paper furnishes a comprehensive framework for harnessing debt-for-climate swaps to enhance water security and resilience in developing countries. It offers actionable strategies for policymakers, practitioners, and stakeholders to navigate the complex terrain of climate change and engender sustainable development. [ABSTRACT FROM AUTHOR]

Within the "dual carbon" framework, sustainable agriculture is pivotal for climate change mitigation and long-term agricultural health. To explore the environmental effects of agricultural trade, this study assesses the carbon emissions from agriculture using information from 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan due to a lack of available data) from 2001 to 2021. Then, we analyzed the impact of agricultural trade on agricultural carbon emissions and tested for the possible existence of mechanisms. Finally, we validate the synergistic effects of agricultural trade on pollution and carbon abatement. The findings were as follows: (1) Agricultural trade significantly suppresses agricultural carbon emissions. (2) Agricultural technological progress and the rationalization of the structure of the agricultural industry are the two influencing mechanisms. (3) The inhibitory effect of agricultural trade on agricultural carbon emissions is more pronounced in southern regions and regions with lower degree of topographic relief and higher agricultural industrial agglomeration. (4) Agricultural trade fosters the collaborative advancement of mitigating agricultural pollution and reducing carbon emissions. As a result, this study confirms that agricultural trade has a role in reducing carbon emissions and that giving full play to the environmental effects of trade in agricultural products contributes to the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Turfgrass systems hold significant climate change mitigation value, but their management often negates the beneficial effects due to the intense adoption of external inputs. The research objective in this paper was to assess the nitrogen fertilization rate able to maintain the ideal esthetic characteristics of Zoysia turfgrass, reducing the environmental impacts associated with greenhouse gas (GHG) emissions. A two-year open field experiment was conducted. Nitrogen was added to the soil at six rates (0, 50, 100, 150, 200, and 250 kg ha−1). The GHG emissions were monitored using a portable gas analyzer and the static chamber methodology. Cumulative environmental impacts were calculated from the inclusion of CO2, CH4, and, N2O using the Global Warming Potential (GWP). The quality assessment of the turf was assessed through a visual and instrumental approach. Higher CO2 and N2O fluxes were linked to high nitrogen rates, ranging from 83.55 to 87.50 and from 0.046 to 0.047 g N-N2O ha−1 day−1 for 200 and 250 kg N ha−1, respectively. CH4 emissions were not correlated to nitrogen rates. Higher GWP impacts were linked to high N rate treatments. A rate of 100 kg N ha−1 is recommended as the best strategy to reduce GHG emissions while maintaining high turf quality. [ABSTRACT FROM AUTHOR]

There is an increasing interest in achieving global climate change mitigation targets that target environmental protection. Therefore, electric vehicles (as linear metros) were developed to avoid greenhouse gas emissions, which negatively impact the climate. Hence, this paper proposes a finite set-model predictive-based current control (FS-MPCC) strategy of linear induction motor (LIM) for linear metro drives fed by solar cells with a beta maximum power extraction (B-MPE) control approach to achieve lower thrust ripples and eliminate a selection of weighting factors, the main limitation of conventional model predictive-based thrust control (which can be time consuming and challenging). The B-MPE control approach ensures that the solar cells operate at their maximum power output, maximizing the energy harvested from the sun. Considering a single cost function of primary current errors between the predicted values and their references in αβ-axes, the proposed method eliminates the need for weighting factor selection, thus simplifying the control process. A comparison between the conventional and the presented control method is conducted using MATLAB/Simulink under different scenarios. Comprehensive simulation results of the presented system on a 3 kW LIM prototype revealed that the introduced system based on FS-MPCC surpasses the conventional technique, resulting in a maximum power extraction from solar cells and a suppression of the thrust ripples as well as an avoidance of weighting factor tuning, leading to fewer computational steps. [ABSTRACT FROM AUTHOR]

In the context of a global shift towards renewable energies and climate change mitigation, the market for electric vehicles has experienced a remarkable upswing, with battery electric vehicles (BEVs) leading this transformative wave. The appeal of BEVs lies in their ability to significantly curtail CO2 emissions by supplanting the traditional internal combustion engine (ICE) with an electric motor. This pivotal change in vehicular technology extends its influence to various subsystems, including automotive lighting. Headlights are particularly sensitive to the thermal environment they operate in, which can profoundly affect their functionality and durability. The removal of an ICE in BEVs typically results in a reduction in heat exposure to headlight components, prompting a potential reevaluation of their design. This article presents a comprehensive analysis of temperature distributions within headlight units, comparing BEVs and ICE vehicles. The study encompasses a robust dataset of nearly 30,000 vehicles from around the globe, taking into account the impact of ambient temperature on headlight operation. The investigation delineates the distinct thermal behaviors of the two vehicle categories and offers strategic recommendations for conceptual modifications of headlights in BEVs. These adjustments are aimed at enhancing headlight efficacy, prolonging lifespan, and furthering the sustainability objectives of electric mobility. [ABSTRACT FROM AUTHOR]

Despite the widespread recognition of the significance of long-term sustainability, there is as yet a relative paucity of evidence on what factors account for sustainability performance. In an effort to close the apparent gap in knowledge, this study contributes new empirical evidence to this discussion by considering the role of economic policy uncertainty. Inconsistent economic policy may undermine sustainability efforts as it creates a more complex and volatile operating environment, which, in turn, affects the behaviour of economic entities in the system. Drawing primarily on environmental management literature, this study aims to investigate the relationship between economic policy uncertainty and sustainability performance in the Asian regions between 2012 and 2020. With country-level annual data, this study estimates the model using a system generalised method of moments approach to address the possible biases resulting from serial correlation of random errors, simultaneity, and unobserved heterogeneity. Therefore, the estimates of this study will be consistent and asymptotically unbiased. The empirical analysis reveals that sustainability performance in Asia is adversely affected by economic policy uncertainty. The sustainability sub-components results are broadly in line with the main results that a higher economic policy uncertainty index is detrimental to the protection of natural capital and the development of social capital. This study concludes that ongoing economic policy uncertainty and disturbance could have serious repercussions for local economies, thereby hindering sustainability development. Overall, the findings of this study suggest that the establishment of sustainability development frameworks in areas of climate goals, social justice, and good governance would need to pay close attention to uncertainty in economic policy. [ABSTRACT FROM AUTHOR]

Bamboo forests in Colombia and the Andean region of South America represent high-value ecosystems that provide ecological and economic benefits with local and global impacts. One of the ecosystem services provided by these forests is associated with their capacity to store carbon. In this study, data collected from monitoring plots were used to estimate the carbon content in different pools. Bamboo biomass (Bba), tree biomass (Btree), litter (Cli) and soil organic carbon (SOC) were assessed. The approximate total ecosystem carbon stock (TECaprox) ranged from 198.4 Mg C ha−1 to 330.9 Mg C ha−1 and bamboo carbon Cba represents approximately 50%. In addition, considering the relevance of developing tools to facilitate bamboo inventory and biomass estimates, allometric equations (AE) to estimate bamboo aboveground biomass (AGB) were fitted using the diameter of culms at breast height (dbh) and the total culm length (l) as predictor variables. The fitted AEs included the weighted linear, weighted log-transformed and weighted nonlinear fixed effect models. To compliance the additivity of biomass components a simultaneous systems of biomass equations (seemingly unrelated regressions) were also fitted. The precision and accuracy were assessed considering the residual diagnostic plots and statistics, such as the root-mean-square error (RMSE), RMSE percentage error (RMSEPE) and the Furnival's index (Fln) for weighted log-transformed models and cross-validation. The performance of the models was similar with an RMSE of approximately 10 kg and 26% of RMSEPE, with slightly lower error for the weighted log-transformed model for the fitting and validation phases. A proper performance was also evidenced for the simultaneous approach for predicting AGB. Bamboo forests showed high relevance as carbon sinks and therefore might be considered strategic tropical ecosystems for climate change mitigation. On the other hand, the fitted AE exhibited proper performance and therefore provided reliable possibilities for estimating the AGB of bamboo during inventories. For practical reasons, the use of models with dbh as a predictor variable is recommended. [ABSTRACT FROM AUTHOR]

In response to the climate goal of achieving carbon neutrality by 2050, efficient electrochemical energy conversion devices are garnering increasing attention. However, the enhancement of electrochemical performance using noble metal electrocatalysts, along with cost reduction and electrode fabrication, remain significant challenges. Noble metal hybrid nanostructures, possessing multiple surface functionalities, lead to outstanding electrocatalytic performances and low‐cost potential. Strain effects can bolster the bonding strength between the noble metal layers and the substrate or core layers, while simultaneously affecting electrocatalytic performance through tuning the binding strength between catalytically active sites and reactants, including intermediates. This review encapsulates the research efforts directed towards improving the performance of noble metal electrocatalysts and provides an overview of the latest advancements in controlling the surface state of noble metals by incorporating a secondary component. We discuss systematic approaches to adjusting surface strain effects on noble metals, characterization techniques, and application case studies, while extracting key design indicators for readers to consider from a macroscopic perspective. Further, we outline the challenges encountered and current solutions when advancing noble metal catalysts from theoretical mechanisms to practical use. Finally, the perspectives on the future research of noble metal surface layer control techniques were also provided. [ABSTRACT FROM AUTHOR]

The EU faces two economic challenges: managing non-performing exposures (NPEs) and climate change. This paper analyzes the relationship between the NPEs of domestic banking groups and climate risks, including macroeconomic variables such as the GDP growth rate, unemployment rate (UnEmp), and the voice and accountability percentile (VCA) and the interaction variable between the GHG and the Rule of Law Percentile (GhGRLP). The estimation uses ordinary least squares with time-fixed and individual effects. Physical and transition risks significantly affect NPEs, showing that both adverse climate events and the transition to a low-carbon economy worsen the financial situation of European banking institutions. The analysis also revealed that increased levels of VCA lead to a rise in NPEs, while an increase in GhGRLP reduces NPEs. In contrast, financial institutions tend to recognize and report NPEs more accurately in contexts with greater transparency and accountability. In comparison, UnEmp negatively affects NPEs, suggesting that economic support measures during high unemployment can reduce NPEs in the subsequent period. In conclusion, climate risk management represents a crucial challenge for the financial stability of banking institutions. Policymakers and financial institutions must continue to develop and implement climate change mitigation and adaptation strategies to preserve financial system stability amid growing climate uncertainties. [ABSTRACT FROM AUTHOR]

The article presents carbon capture and storage, CCS, as a climate change mitigation method. Many industrial processes, such as the manufacture of cement, the metallurgical industry, and the production of electricity from fossil fuels, produce large CO2 quantities. Carbon capture and storage is a method for these industrial areas to become carbon neutral for the environment. To combat climate change, the EU wants to achieve climate neutrality by 2050, and this goal, along with an intermediate goal of reducing emissions by 55% by 2030, is enshrined in the European Climate Law. The EU has launched various initiatives to achieve these goals, one of which is the 'Fit for 55' legislation. The first step that countries wanting to apply these technologies must take is the evaluation of the underground CO2 storage potential. The potential for CO2 storage in the depleted hydrocarbon reservoirs in Oltenia, one of the eight regions of Romania, makes it possible to develop safe long-term storage projects for the neighboring power plants currently producing energy from burning coal or hydrocarbons. The results of dynamic simulations of CO2 storage in one of these geological structures, Bradesti, which hosts depleted hydrocarbon reservoirs, using a numerical simulator are successfully presented for the neighboring Isalnita Power Plant. In this case, the impact on the environment and climate will be minimal and in alignment with the European Union's long-term objectives. Our study also opens the path for future similar analyses. [ABSTRACT FROM AUTHOR]

Taiwan's unique geographic environment combined with climate change leaves it particularly vulnerable to water shortage issues. A new water resource recycling system that adheres to a Low Impact Development (LID) concept and utilizes existing permeable pavement techniques to mitigate water scarcity is presented in this study. The design routes water at the base and subbase layers of a permeable pavement toward a planter box in the median divider island or box culvert below the median divider island. Once the runoff has flowed into the bottom of the planter box or box culvert, it is available for plants via soil capillary action. Through evaporation or transpiration, the water is then returned to the atmosphere and integrated into the water cycle for localized microclimates. This study used a 3D printer to create a small-scale model of the proposed design. Using this small-scale 3D model, a series of capillary experiments were conducted to evaluate the permeable pavement water recycling system. Because the small-scale model is not suitable for long-duration tests, soil column experiments were also used. The soil was compacted to different relative compactions for a 3D model and the soil column experiments were used to evaluate the capillary rise height of the soil. The results showed that when using a silt with low plasticity soil (ML), under low relative compaction, the capillary water can reach the rooting level of appropriately selected plants. Therefore, if the soil around vegetation is correctly compacted, the vegetation's roots will have access to stored water. The proposed permeable pavement water recycling system represents a practical approach to managing stormwater runoff and achieving water conservation objectives. This innovative design not only aims to conserve and protect water resources but also supports sustainable water management practices, thereby helping to mitigate the impacts of climate change. [ABSTRACT FROM AUTHOR]

Accurate subsurface soil moisture (SM) estimation is critical for vegetation growth, drought monitoring, and climate change mitigation, yet remains a significant challenge. Previous data assimilation (DA) approaches are limited to only surface SM assimilation. In this study, we utilized the proxy subsurface SM estimated via the exponential filter method (ExpF) as another assimilation variable in our 2‐dimensional DA. Meanwhile, the dual updating DA scheme was implemented to simultaneously update model parameters and states. The two DA pathways were incorporated into the proposed framework (DA_1E_D), which enhanced the subsurface SM accuracy, with the effects of 2‐dimensional assimilation being more significant. Under 2‐dimensional DA, the information transfer between layers was more accurately characterized, leading to overall improvements with unbiased root‐mean‐square error (ubRMSE) reductions of 0.015 and 0.005 m3 · m−3, and Kling–Gupta efficiency (KGE) increases of 0.248 and 0.067 for surface and subsurface SM, respectively, across five SM networks. The soil thickness (d2) and hydraulic conductivity exponent (expt2) are the most influential parameters affecting subsurface SM dynamics through model propagation. DA_1E_D also outperformed ExpF in subsurface SM accuracy, particularly in SM networks with weak surface‐subsurface correlation, achieving an average ubRMSE reduction of 0.003 m3 · m−3 and an average KGE increase of 0.202. It was also applied to Soil Moisture Active Passive data at regional scale, demonstrating significant improvements. The model surface‐subsurface SM coupling was adjusted toward the actual coupling after subsurface assimilation and dual updating. This study may provide new insights into the diagnosis and refinements of the model representation of surface‐subsurface processes. Plain Language Summary: Soil moisture (SM) is a key variable in the fields of hydrology, ecology, and agriculture, and in characterizing Earth's climate. Particularly, accurate subsurface SM estimation remains challenging for the Earth science community. Here, we used the empirical subsurface SM estimates derived from an exponential filter method (ExpF) as another assimilation variable, in combination with the data assimilation (DA) technique which updates model states and parameters simultaneously, to constrain the model estimates. We found these two pathways lead to significant improvements in subsurface SM estimation. The accuracy of subsurface SM was improved with biases (ubRMSE) significantly reduced by 0.005 m3 · m−3 on average over the modeling grid cells, due to the assimilation of empirical subsurface SM. The effects of parameter updating were relatively smaller but also positive. The proposed DA framework demonstrated superior accuracy to ExpF, with an average ubRMSE reduction of 0.003 m3 · m−3 and an average KGE increase of 0.202. This framework was also applicable to regional scale using satellite products. Moreover, both pathways proved effective in adjusting the physical surface‐subsurface correlation in the land surface model toward actual coupling. Our analysis has important implications for future studies on estimating subsurface SM using land surface models at larger spatiotemporal scales. Key Points: A 2‐dimensional data assimilation (DA) framework which accounted for a dual state‐parameter updating scheme was proposedThe accuracy of subsurface soil moisture (SM) was improved by assimilating empirical subsurface estimates and dual updatingThe proposed DA framework can also be applied to Soil Moisture Active Passive data to improve subsurface SM estimation at regional scale [ABSTRACT FROM AUTHOR]

The world is facing grand challenges in energy security, environmental pollution, and sustainable use (and re‐use) of resources. Electrochemical processes, incorporating electrosynthesis, electrochemical catalysis, and electrochemical energy storage devices, provide pathways to address these challenges via green chemistry. However, the applicability of electrochemical processes for these systems is limited by the required energy input, the "electrons" in electrochemistry. Electrocatalysis as a subset of electrochemistry is set to underpin many of the United Nations Sustainable Development Goals, including "Affordable and Clean Energy" through the production of future fuels and abatement of carbon emissions; "Responsible Consumption and Production" through recycling and degradation of waste; and "Climate Action" through CO2 (and other greenhouse gas) remediation. The rise of green photovoltaic power has lowered the carbon cost of these electrons, making electrocatalysis an even more viable, green(er), chemical conversion pathway. This perspective highlights the need for comprehensive understanding of catalyst structure via in situ and operando analysis to complement device design considerations. The challenges faced by the field of electrocatalysis in data reporting, elimination of electrochemical artifacts, catalyst stability, and scaling to industrial relevance, along with opportunities, emerging tools, are discussed with a view to achieve the maximum 'potential' of electrocatalysis. [ABSTRACT FROM AUTHOR]

This research conducts a comprehensive analysis of the relationship between green finance and the Sustainable Development Goals (SDGs), particularly focusing on SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). Utilizing a novel SDG index based on United Nations criteria, the study evaluates the effect of green finance on sustainability across OECD economies between 2000 and 2020. Employing advanced econometric methods, including Driscoll–Kraay standard errors, FMOLS, DOLS, and the method of moments quantile regression, the findings reveal that green finance, along with environmental governance, fiscal policy, and population growth, significantly contributes to the advancement of SDGs. However, the study also highlights the detrimental impact of elevated geopolitical risks, which can hinder progress toward these goals and partially negate the benefits of green finance initiatives. These insights are vital for policymakers striving to develop effective strategies to promote the SDGs amidst current global uncertainties. [ABSTRACT FROM AUTHOR]

The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenic Vibrio spp. The waterborne pathogen, Vibrio vulnificus can invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination of V. vulnificus need to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll‐a (chl‐a) in locations with reported V. vulnificus infections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2‐month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl‐a values, was statistically linked to higher odds of V. vulnificus infection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations. Plain Language Summary: Our study focused on Vibrio spp., a group of bacteria in warm, slightly salty water. One of these, Vibrio vulnificus, is especially dangerous and can cause severe illness with a high risk of death. The spread of this pathogen in humans is becoming more of a concern due to climate change. We aimed to understand what environmental conditions influence occurrence of the disease caused by this bacterium. The main factor linked to the rise of V. vulnificus is sea surface temperature (SST). However, other factors like chlorophyll also play a role. We used satellite data to monitor SST and chlorophyll levels and statistically associated this data with the number of people getting sick from V. vulnificus. Our findings indicate a pattern: when 2 months prior SST and 1‐month prior chlorophyll levels are higher than their monthly average, the chance of V. vulnificus infections is higher. By using this pattern, we aim to predict better when and where infections might happen, helping identify at‐risk areas and potentially stop outbreaks before they occur. Key Points: Likelihood of Vibrio vulnificus infections is influenced by elevated Sea Surface Temperature and chlorophyll of previous monthsSea Surface Temperature, chlorophyll, and V. vulnificus cases occurrence showed increasing trends during the study periodStatistically significant difference was observed between overall chlorophyll levels and the levels recorded during increased cases of V. vulnificus [ABSTRACT FROM AUTHOR]

Forest restoration is critical for meeting global objectives related to climate change mitigation, biodiversity conservation and sustainable livelihoods.Recently, new technologies such as unmanned aerial vehicles (hereafter drones) have been promoted to support activities across the planning, implementation, monitoring and maintenance stages of forest restoration. Yet, there is little empirical data on how the development and application of drones are perceived by restoration managers and stakeholders and how drones intersect with existing forest social–ecological systems (SESs).Here, we investigate how drone tree planting initiatives in Australia can support ecosystem restoration. Through interviews and focus groups with key actors, we examine the opportunities and challenges that have been experienced or are foreseen with drone use.Opportunities included the ability of drones to access degraded sites that are difficult or unsafe to access on foot, for example, following bushfires, floods or landslides. They were also perceived to ease the labour shortage of bush regenerators in Australia. Drones were considered particularly useful when operating at scales of around 20–100 ha.Challenges included restrictive flying regulations that prohibit use of artificial intelligence to plot courses through complex terrain, their unproven ability to control or eradicate weeds and the uncertain supply, germination and survival rates of seeds—upon which drone‐based restoration relies. Drone use may also reduce the emotional, spiritual and cultural connections of people to the land, as compared to hand‐planting seeds or seedlings.We conclude by conceptualising how drone‐assisted restoration can be embedded within a forest SESs management framework. Ultimately, we argue that drones offer a 'boutique' restoration approach that supports, rather than replaces, traditional forest restoration techniques. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

This study aims to monitor the implications of climate change on savanna ecosystem drought using time series data from the Landsat 8 sensor, spanning from 2013 to 2022. We employed a remote sensing computational approach with the Semi-Automatic Classification Plugin (SCP) in the open-source QGIS software. Specifically, we utilized channels from the Operational Land Imager (OLI), including Band 4 Red (0.636 – 0.673 µm) and Band 5 Near-Infrared (0.851 – 0.879 µm), as well as Thermal Infrared Sensor (TIRS) channels Band 10 TIRS-1 (10.60 - 11.19 µm) and Band 11 TIRS-2 (11.50 - 12.51 µm). These channels were used to calculate the Vegetation Health Index (VHI) using the raster calculator, followed by data reclassification with specific thresholds to compare drought-affected areas. Our findings reveal a significant impact of climate change on savanna ecosystem drought over the decade, with the most extreme conditions observed in 2015 and 2019, where drought coverage reached 42.74% and 26.58%, respectively. Other years exhibited relatively low drought dynamics, affecting less than 3% of the area. This period aligns with the El Niño-Southern Oscillation (ENSO) phenomenon, particularly the transition from El Niño to La Niña, known to cause global weather variations, and significantly influenced by the positive phase of the Indian Ocean Dipole (IOD). The novelty of this research lies in two main aspects: firstly, the use of Landsat satellite sensors for this specific region has not been extensively studied before; secondly, the discovered impacts of drought in relation to global climate change phenomena are particularly noteworthy. A limitation of this study is the relatively short investigation period of just one decade, which does not fully capture the long-term impacts of climate change. Future research is recommended to utilize imagery with higher temporal resolution over extended periods to better represent extreme climate events and derive drought patterns over durations exceeding one decade.

Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation. Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural intensification, which are two key parameters in the Shared Socioeconomic Pathways (SSPs). Datasets mapping future land dynamics under different SSPs and climate change mitigation targets stem from different scenario assumptions, land data and modelling frameworks. This study aims to determine the role that these three factors play in the estimates of the evolution of cropland and pastureland in future SSPs under different climate scenarios from four main datasets largely used in the climate and land surface studies. The datasets largely agree with the representation of cropland at present-day conditions, but the identification of pastureland is ambiguous and shows large discrepancies due to the lack of a unique land-use category. Differences occur with future projections, even for the same SSP and climate target. Accounting for CO2 sequestration from revegetation of abandoned agricultural land and CO2 emissions from forest clearance due to agricultural expansion shows a net reduction in vegetation carbon stock for most SSPs considered, except SSP1. However, different datasets give differences in estimates, even when representative of the same scenario. With SSP1, the cumulative increase in carbon stock until 2050 is 3.3 GtC for one dataset, and more than double for another. Our study calls for a common classification system with improved detection of pastureland to harmonize projections and reduce variability of outcomes in environmental studies.

Abstract Background The National Health Service (NHS) has pledged to reach carbon net-zero by 2040. In alignment with this goal, a London hospital’s anaesthesia department is actively reducing desflurane use and transitioning towards total intravenous anaesthesia (TIVA) as a sustainable alternative, contributing to environmentally responsible practices within the healthcare sector. Methods We conducted a rapid qualitative appraisal through online interviews with 17 anaesthetic practitioners to explore their perspectives regarding this climate change mitigation strategy. Data analysis was undertaken through the use of rapid appraisal sheets and a framework analysis method. Results Participants highlighted the disadvantages of TIVA, including the increased effort, heightened monitoring requirements, operational challenges, and a lack of clinical confidence associated with its use. Despite these reservations, participants acknowledged TIVA’s potential to reduce postoperative nausea. There were perceptions that senior staff members might resist this change due to habits and scepticism over its impact on climate change. To facilitate greater TIVA adoption, participants recommended enhanced training, the implementation of a dashboard to raise awareness of greenhouse gas (GHG) emissions, and the presence of strong climate change leadership within the department. Participants believed that a shift to TIVA should be followed by specific measures such as addressing waste management which is crucial for GHG reduction, emphasising the perceived link between waste and emissions. Conclusions The evaluation examines stakeholder attitudes, perceptions, and behaviours, focusing on transitioning from desflurane to TIVA. The study highlights the importance of staff engagement, organisational support, and underscores the crucial role that healthcare practitioners and leadership play in fostering sustainability within the healthcare sector.

Abstract Background Grasslands are essential for providing vital resources in the livestock sector and delivering invaluable ecosystem services such as biodiversity and soil carbon (C) sequestration. Despite their critical importance, these ecosystems face escalating threats from human disturbances, human degradation, and climate change, compromising their ability to effectively stock C. Restoring degraded grasslands emerges as a pragmatic and cost-effective approach to tackling climate change. However, the successful implementation of grassland management toward this goal, faces significant challenges. A systematic mapping approach will help to compile a comprehensive global inventory of studies investigating the impact of differing grassland management practices on soil carbon. In addition, the potential for trade-offs with other greenhouse gas emissions further underlines the value of a systematic assessment. This approach aims to identify knowledge clusters (i.e., well-represented subtopics that are amenable to full synthesis) for potential systematic reviews and pinpoint knowledge gaps requiring further primary research efforts, all contributing to a better understanding of the evidence surrounding this topic. Methods Following systematic evidence synthesis standards, we developed the question to address in the systematic map protocol using the PICO framework. We established a preliminary search string by combining search terms for the Population (Grasslands), Intervention (management) and Outcome (soil carbon) categories, as well as with one additional group (Study types—to focus on farm and field experiments). We will conduct a comprehensive literature search of relevant peer-reviewed and grey literature using Web of Science, Scopus, CABI platforms, Google Scholar, and specialised websites (e.g., Agrotrop). Searches will be conducted in the English, Spanish, Portuguese, French, German, and Mongolian languages, as per the linguistic capabilities of the research team. The comprehensiveness of the search will be assessed by comparing the literature collected to a test-list of forty relevant articles. The repeatability of the literature screening process will be ensured by a list of inclusion/exclusion criteria and inter-reviewer consistency statistical tests. Data extraction will be organised into four complementary sections (article information, PICO categories, study characteristics, measurable parameters), on which we will perform queries to produce the tables, figures and evidence maps that will compose the systematic map. The results will identify and describe knowledge gaps and clusters.

The growing global population causes more anthropogenic carbon dioxide $ (CO_2) $ emissions and raises the need for forest products, which in turn causes deforestation and elevated $ CO_2 $ levels. A rise in the concentration of carbon dioxide in the atmosphere is the major reason for global warming. Carbon dioxide concentrations must be reduced soon to achieve the mitigation of climate change. Forest management programs accommodate a way to manage atmospheric $ CO_2 $ levels. For this purpose, we considered a nonlinear fractional model to analyze the impact of forest management policies on mitigating atmospheric $ CO_2 $ concentration. In this investigation, fractional differential equations were solved by utilizing the Atangana Baleanu Caputo derivative operator. It captures memory effects and shows resilience and efficiency in collecting system dynamics with less processing power. This model consists of four compartments, the concentration of carbon dioxide $ \mathcal{C}(t) $, human population $ \mathcal{N}(t) $, forest biomass $ \mathcal{B}(t) $, and forest management programs $ \mathcal{P}(t) $ at any time $ t $. The existence and uniqueness of the solution for the fractional model are shown. Physical properties of the solution, non-negativity, and boundedness are also proven. The equilibrium points of the model were computed and further analyzed for local and global asymptotic stability. For the numerical solution of the suggested model, the Atangana-Toufik numerical scheme was employed. The acquired results validate analytical results and show the significance of arbitrary order $ \delta $. The effect of deforestation activities and forest management strategies were also analyzed on the dynamics of atmospheric carbon dioxide and forest biomass under the suggested technique. The illustrated results describe that the concentration of $ CO_2 $ can be minimized if deforestation activities are controlled and proper forest management policies are developed and implemented. Furthermore, it is determined that switching to low-carbon energy sources, and developing and implementing more effective mitigation measures will result in a decrease in the mitigation of $ CO_2 $.

In the evolving landscape of global energy dynamics, Malaysia stands as a pivotal example of a nation actively transitioning towards renewable energy and sustainable development. This paper provides a comprehensive analysis of Malaysia's energy sector transformation, underpinned by the government's commitment to reducing carbon emissions and mitigating the impacts of climate change. The objective of this research is to delve into the intricacies, opportunities, and challenges of steering Malaysia towards a greener future, with a particular focus on the shift from reliance on fossil fuels to the adoption of renewable energy sources such as solar, wind, and biomass. Employing a mixed-method approach, this study synthesizes existing literature, policy documents, and case studies to examine the current state and historical context of energy use in Malaysia, analyze government initiatives and policy frameworks, explore technological advancements, and assess the environmental and socioeconomic impacts of the energy transition. Results indicate that despite facing challenges such as financial investment, technological advancement, and public acceptance, collaborative efforts between the government, private sector, and communities have led to significant progress in promoting renewable energy. The paper concludes that Malaysia's energy transition represents a critical step towards achieving a balance between economic growth and environmental preservation, setting a precedent for sustainable development in the Southeast Asian region. This transition is not only essential for climate change mitigation but also presents opportunities for economic diversification, energy security, and social inclusivity. The study ultimately calls for continued innovation, supportive policies, and international cooperation to overcome remaining barriers and fully realize the potential of renewable energy in Malaysia.

The European Commission has proposed a Carbon Border Adjustment Mechanism (CBAM) to reduce carbon leakage and create a level playing field for its domestic products and imported goods. Nevertheless, the effectiveness of the proposal remains unclear, especially when it triggers threats of retaliation from trading partners of the European Union. We apply a Computable General Equilibrium model - Global Trade Analysis Project - to assess the economic and environmental impacts of different CBAM schemes. Here we show that the effectiveness of the CBAM to address carbon leakage risks is rather limited, and the CBAM raises concerns over global welfare costs, Correct to Gross Domestic Product (GDP) losses, and violation of equality principles. Trade retaliation leads to multiplied welfare losses, which would mostly be borne by poor countries. Our results question the carbon leakage reduction effect of a unilateral trade policy and suggest that climate change mitigation still needs to be performed within the framework of international cooperation.

Global impervious surface area (ISA) has more than doubled over the last three decades, but the associated carbon emissions resulting from the depletion of pre-existing land carbon stores remain unknown. Here, we report that the carbon losses from biomass and top soil (0–30 cm) due to global ISA expansion reached 46–75 Tg C per year over 1993–2018, accounting for 3.7–6.0% of the concurrent human land-use change emissions. For the Annex I countries of UNFCCC, our estimated emissions are comparable to the carbon emissions arising from settlement expansion as reported by the national greenhouse gas inventories, providing independent validation of this kind. The contrast between growing emissions in non-Annex I countries and declining ones in Annex I countries over the study period can be explained by an observed emerging pattern of emissions evolution dependent on the economic development stage. Our study has implications for international carbon accounting and climate mitigation as it reveals previously ignored but substantial contributions of ISA expansion to anthropogenic carbon emissions through land-use effects. Terrestrial carbon emissions from global expansion of impervious surface area have been long overlooked in global carbon budget assessments. Qiu et al. report that these emissions account for up to 6.0–12.9% of those from human land use change. [ABSTRACT FROM AUTHOR]

Climate change leading to Climate extremes in the twenty-first century is more evident in megacities across the world, especially in West Africa. The Greater Accra region is one of the most populated regions in West Africa. As a result, the region has become more susceptible to climate extremes such as floods, heatwaves, and droughts. The study employed the Coupled Model Intercomparison Project 6 models in simulating climate extreme indices under the Shared Socioeconomic Pathway scenarios (SSPs) over West Africa between 1979 and 2059 as exemplified by the Greater Accra region. The study observed a generally weak drought in the historical period and expected to intensify especially under SSP585 in Greater Accra. For instance, continuous dry days (CDD) reveal an increasing trend under the SSPs. Similarly, the overall projected trend of CDD over West Africa reveals an increase signifying a more frequent and longer drought in the future. The flood indices revealed a surge in the intensity and duration of extreme precipitation events under the SSPs in the region. For instance, R99pTOT and Rx5days are expected to significantly increase under the SSPs with intensification under the SSP245, SSP370, and SSP585. A similar trend has been projected across West Africa, especially along the Guinean coast. The study foresees a gradual and intensifying rise in heatwave indices over the Greater Accra region. The warming and cooling indices reveal an increasing and decreasing trend respectively in the historical period as well as under the SSPs particularly within urban centers like Accra and Tema. Most West African countries are projected to observe more frequent warm days and nights with cold nights and days becoming less frequent. Expected effects of future climate extreme indices pose potential threats to the water, food, and energy systems as well as trigger recurrent floods and droughts over Greater Accra. The findings of the study are expected to inform climate policies and the nationally determined contribution of the Paris Agreement as well as address the sustainable development goal 11 (Sustainable cities) and 13 (Climate action) in West Africa. [ABSTRACT FROM AUTHOR]

Subsurface gas storage is crucial for achieving a sustainable energy future, as it helps to reduce CO2 emissions and facilitates the provision of renewable energy sources. The confinement effect of the nanopores in caprock induces distinctive thermophysical properties and fluid dynamics. In this paper, we present a multi‐scale study to characterize the subsurface transport of CO2, CH4, and H2. A nanoscale‐extended volume‐translated Cubic‐Plus‐Association equation of state was developed and incorporated in a field‐scale numerical simulation, based on a full reservoir‐caprock suite model. Results suggest that in the transition from nanoscale to bulk‐scale, gas solubility in water decreases while phase density and interfacial tension increase. For the first time, a power law relationship was identified between the capillary pressure within nanopores and the pore size. Controlled by buoyancy, viscous force and capillary pressure, gases transport vertically and horizontally in reservoir and caprock. H2 has the maximum potential to move upward and the lowest areal sweep efficiency; in short term, CH4 is more prone to upward migration compared to CO2, while in long term, CH4 and CO2 perform comparably. Thicker caprock and larger caprock pore size generally bring greater upward inclination. Gases penetrate the caprock when CH4 is stored with a caprock thickness smaller than 28 m or H2 is stored with a caprock pore size of 2–10 nm or larger than 100 nm. This study sheds light on the fluid properties and dynamics in nanoconfined environment and is expected to contribute to the safe implementation of gigatonne scale subsurface gas storage. Plain Language Summary: Aiming at the ambitious targets of net‐zero emission and global energy transition, effective technologies need to be developed and deployed with huge efforts. Subsurface gas storage is expected to play a critical role in reducing CO2 emission and providing large‐scale renewable energy. However, unforeseen gas leakage can cause potential environmental risks and energy efficiency concerns. Despite its importance, the mechanisms governing gas transport and distribution within caprocks, particularly under nanoconfinement conditions, are poorly understood. From nano‐scale and bulk‐scale thermodynamic properties predictions to field‐scale numerical simulations, this work carried out a comprehensive multi‐scale analysis to evaluate the storage security of CO2, CH4, and H2. Relationships between VLE, phase density, interfacial tension, capillary pressure and pore size, temperature, pressure and wettability were discussed, offering novel perspectives on the mechanisms governing gas leakage. Furthermore, loss potentials of different gases were compared and evaluated and the impacts of caprock thickness and pore size were examined, providing valuable insights for screening eligible storage sites. Overall, this work contributes to the development of secure and reliable gas storage techniques, supporting the goals of climate change mitigation and facilitating the transition to a net‐zero energy future. Key Points: A multi‐scale analysis is carried out to assess the loss potential of CO2, CH4, and H2 during subsurface storageMigration and distribution characteristics of gases in the caprock are investigatedShort‐term and long‐term gas storage security are analyzed and compared [ABSTRACT FROM AUTHOR]

Climate change mitigation necessitates increased investment in green sectors. This study proposes a methodology to predict green finance growth across various countries, aiming to encourage such investments. Our approach leverages time-series Conditional Generative Adversarial Networks (CT-GANs) for data augmentation and Nonlinear Autoregressive Neural Networks (NARNNs) for prediction. The green finance growth predicting model was applied to datasets collected from forty countries across five continents. The Augmented Dickey-Fuller (ADF) test confirmed the non-stationary nature of the data, supporting the use of Nonlinear Autoregressive Neural Networks (NARNNs). CT-GANs were then employed to augment the data for improved prediction accuracy. Results demonstrate the effectiveness of the proposed model. NARNNs trained with CT-GAN augmented data achieved superior performance across all regions, with R-squared (R2) values of 98.8%, 96.6%, and 99% for Europe, Asia, and other countries respectively. While the RMSE for Europe, Asia, and other countries are 1.26e+2, 2.16e+2, and 1.16e+2 respectively. Compared to a baseline NARNN model without augmentation, CT-GAN augmentation significantly improved both R2 and RMSE. The R2 values for the Europe, Asia, and other countries models are 96%, 73%, and 97.2%, respectively. The RMSE values for the Europe, Asia, and various countries models are 2.24e+2, 7e+2, and 2.07e+2, respectively. The Nonlinear Autoregressive Exogenous Neural Network (NARX-NN) exhibited significantly lower performance across Europe, Asia, and other countries with R2 values of 74%, 52%, and 86%, and RMSE values of 1.11e+2, 3.63e+2, and 1.8e+2, respectively. [ABSTRACT FROM AUTHOR]

The Wof‐Washa Natural State Forest (WWNSF) in Ethiopia harbors remarkable biodiversity but faces threats from local communities, climate change, and a lack of awareness regarding its preservation. Although numerous studies exist, the economic value of the forest's ecosystem services (FESs) has been largely overlooked. Thus, the purposes of this study were to identify FESs, estimate their total economic value, and assess challenges with possible strategies for sustainable forest management. The research employed Google Earth to estimate forest area and socioeconomic surveys with field visits to gather data from 368 participants for analyzing the FESs, monetary values, and challenges with possible strategies. Analyses included descriptive statistics, total economic valuation (TEV), and an ordinary least squares regression model. The study revealed that the WWNSF provides crucial provisioning services (timber, honey, water, and firewood), regulating services (soil erosion control and climate change mitigation), and supporting services (soil formation and nutrient cycling). The forest's annual contribution to sampled households averaged $1152.30, with regulating and cultural services valued at $14,112 and $622.00, respectively. The study also revealed that male‐headed households, larger families, and those having limited farmland and off‐farm income depended more heavily on the forest. Therefore, farmland scarcity, settlements, and tree harvesting for firewood, timber, and agricultural tools, as well as the lack of employment opportunities, were the main challenges encountered in the study area. This suggests that despite degradation and reduction in size due to human pressures, the WWNSF remains a significant source of socioeconomic and ecological benefits, supporting local livelihoods and biodiversity. To ensure the forest's restoration, prioritizing community participation, promoting family planning, providing alternative income opportunities especially for youth, and balancing resource use with conservation efforts are possible strategies that should be taken into account. [ABSTRACT FROM AUTHOR]

The climate commitment to achieving carbon neutrality before 2060 in China has been announced recently. In the context of pursuing carbon neutrality, sharing similar sources as greenhouse gases, aerosol particle and precursor emissions are projected to substantially decrease in China, which can potentially have a great impact on climate. Here, we investigate the effects of future aerosol reductions, because of achieving carbon neutrality, on solar and wind energy in China by using an earth system model. We show that significant reductions in aerosol emissions, particularly in eastern China, lead to increases in the surface downwelling shortwave radiation, surface air temperature and wind speed, which can further enhance the potential of solar and wind energy production. The findings underline that the pursuit of carbon neutrality can yield co‐benefits of not only mitigating climate change and air pollution but also fortifying the stability of renewable energy sources. Plain Language Summary: In response to China's commitment to achieve carbon neutrality by 2060, our study examines the potential impact of reducing aerosol emissions and greenhouse gases on solar and wind energy generation. Employing an earth system model, we observe significant reductions in aerosols, particularly in eastern China, resulting in increases in surface downwelling shortwave radiation, surface air temperature, and wind speed. These changes have promising implications for enhancing solar and wind energy production. Our research underscores the interconnected benefits of pursuing carbon neutrality, encompassing climate change mitigation, air quality improvement, and the enhancement of renewable energy reliability. Key Points: The effects of future aerosol reductions in China due to achieving carbon neutrality on solar and wind energy are investigatedAerosol emission reductions, especially in eastern China, increase surface downwelling shortwave radiation, temperature and wind speedClimate changes resulting from emission reductions under carbon neutrality enhance the potential of solar and wind energy [ABSTRACT FROM AUTHOR]

The European Green Deal (EGD) represents the response of the European Union (EU) to the climate crisis and a strategy to mitigate against climate change and the associated environmental degradation. European Climate Law supports the EGD by setting the legally binding target of climate neutrality for the EU on a time horizon of 2050 and mandates that member states develop and implement their own Climate Action Plans (CAP), which are strategic roadmaps outlining steps to reduce greenhouse gas (GHG) emissions and adapt to the impacts of climate change. Within the Irish context, the CAP focuses on six specific sectors, three of which, namely the energy grid, the built environment and transportation are considered in this research. This policy proposes the retrofitting of all residential buildings in the country to a B2 energy performance certificate (EPC), all public transport and 60% of private vehicles electrified and the full decarbonisation of the electrical grid by 2050. This study aims to implement the targets and goals outlined within CAP 2021 in an urban area of Ireland, specifically a historical city centre. The research leverages digital twin technology developed by IES to model the carbon emissions associated with the built environment, while also incorporating GHG emissions associated with transportation and the grid. Furthermore, CAP scenarios are applied systematically and strategically, prioritising building retrofits based on buildings with similar characteristics, typologies and performance. This study has assessed the performance of CAP about two future grid scenarios (1) business as usual and (2) a decarbonised grid. In both scenarios, CAP was not sufficient to achieve the targets set out, resulting in a shortfall of between 25 and 33%. Based on this outcome it may be concluded that any decarbonisation targets specified should be tested and validated before their implementation in policy. Moreover, current state-of-theart digital twin technologies can facilitate the rapid holistic appraisal of complex multi-sectoral policy at the urban scale, which, depending on data availability, could prove useful in future iterations of CAP at both national and international levels. [ABSTRACT FROM AUTHOR]

Salt marshes provide many important ecosystem services, key among them being carbon sequestration. However, a large degree of uncertainty remains in salt marsh carbon budgets, particularly during colder months of the year when salt marsh microbial and vegetative activity is assumed to dormant. We also lack data on urban systems. In this study, we used an easily portable carbon dioxide sensor package to directly measure net carbon dioxide (CO2) fluxes throughout the winter in a temperate, urban salt marsh. We sampled across the dormant season both on normal (cold) temperature days and on days that were anomalously warm (defined here as air temperatures 2.8°C above the long-term average). We demonstrated that median (±mad) daytime CO2 fluxes doubled on the warm days, compared to cold days (1.7 ± 2 mmol m-2 h-1, 0.7 ± 1.3 mmol m-2 h-1, respectively). We also show that net CO2 emissions scaled with soil temperature. The high day-to-day variability, however, implies that infrequent or sparse measurements cannot sufficiently capture the temporal dynamics of dormant season salt marsh net CO2 fluxes. The magnitude of the net CO2 source from our sampling during the dormant season leads us to hypothesize that, as mean annual temperatures continue to increase, dormant season CO2 emissions from salt marshes will increasingly offset growing season carbon dioxide uptake. This change compromises the carbon sequestration capacity, and therefore the climate mitigation potential of these ecosystems. Future studies should focus on quantifying the impact of dormant season CO2, and other greenhouse gases on salt marsh carbon budgets. [ABSTRACT FROM AUTHOR]

Climate dynamics management plays a crucial role in safeguarding the environment from a global to local scale. Land degradation poses a significant threat to the livelihoods of millions of people living in drylands. Arid regions are particularly vulnerable when it comes to finding suitable habitats for ecological processes. Various global initiatives have been developed to restore degraded drylands. In addition, exclosures have important implications in arid areas for regulating environmental services. However, there is a lack of systematic studies on the biomass improvement and climate change mitigation effects of exclosures. A study was carried out in the Sekota district of northern Ethiopia to evaluate the impact of exclosures on biomass production and carbon stock. Three sites—Gateno, Jinqaba, and Mildam—were chosen for the pilot study. Data was collected from 27 quadrats, with different sizes used for sampling saplings, seedlings, litter, and soil. Soil samples were taken at depths of 0–20 cm and 0–40 cm. The data was analyzed using Excel and R Studio, and a linear mixed-effect model was used to determine the differences between land uses. The results indicated significant variations in above-ground biomass carbon, soil organic carbon, and total carbon stock between the two land uses. Furthermore, the observational perspective of exclosures in the Sekota district reveals a sustainable and suitable environment for interested parties. Exclosures prove to be effective in the restoration of degraded lands, as well as in enhancing biomass accumulation and carbon sequestration. [ABSTRACT FROM AUTHOR]

All over the world, waste and its disposal are becoming a more prominent issue, as landfills swell up and growing evidence points to its contribution to climate change and environmental degradation. In the developing world, waste pickers sort through solid waste and sell it to vendors, who will recycle the product into something consumable. The work they do is vital to climate change mitigation, as well as urban cleanliness. In a way, waste pickers, especially in India, are vehicles of environmental justice, but they are often discriminated against and subjected to inhumane working conditions. In this environment, the pandemic hit, making waste pickers' already precarious life even worse. This paper attempts to fill the gap in the academic literature by compiling a systemized literature review of the impacts of COVID-19 on waste-pickers' lives using an environmental justice perspective. The review also uses a Feminist Political Ecology perspective to illuminate the double jeopardy that female waste pickers face in the era of COVID-19, which academia often ignores. Ultimately, this paper shows that COVID-19 exacerbated the preexisting injustices that the waste picker community face and created an immense burden on women. This paper will show that it is important to notice the differentiation between female and male waste picker challenges, especially at the crux of the COVID-19 pandemic. This paper has important policy implications as well as research considerations for both environmental justice and feminist political ecology scholars. [ABSTRACT FROM AUTHOR]

Factors such as extreme temperatures, light radiation, and nutritional condition influence the physiological, biochemical, and molecular processes associated with fruit development and its quality. Besides abiotic stresses, biotic constraints can also affect fruit growth and quality. Moreover, there can be interactions between stressful conditions. However, it is challenging to predict and generalize the risks of climate change scenarios on seasonal patterns of growth, development, yield, and quality of fruit species because their responses are often highly complex and involve changes at multiple levels. Advancements in genetic editing technologies hold great potential for the agricultural sector, particularly in enhancing fruit crop traits. These improvements can be tailored to meet consumer preferences, which is crucial for commercial success. Canopy management and innovative training systems are also key factors that contribute to maximizing yield efficiency and improving fruit quality, which are essential for the competitiveness of orchards. Moreover, the creation of habitats that support pollinators is a critical aspect of sustainable agriculture, as they play a significant role in the production of many crops, including fruits. Incorporating these strategies allows fruit growers to adapt to changing climate conditions, which is increasingly important for the stability of food production. By investing in these areas, fruit growers can stay ahead of challenges and opportunities in the industry, ultimately leading to increased success and profitability. In this review, we aim to provide an updated overview of the current knowledge on this important topic. We also provide recommendations for future research. [ABSTRACT FROM AUTHOR]

In response to escalating global climate change and its increasing impacts worldwide, this study investigates the consequences of extreme weather events, focusing on the unprecedented 2022 monsoon season in the Swat River basin of Pakistan. Record-breaking rainfall, exceeding the 1960–2021 averages by 7–8 %, triggered catastrophic debris flows and floods, aggravating low-income communities' challenges. The resulting financial instability severely affected millions, causing extensive damage to homes, crops, and transportation. The study employs a multidisciplinary approach, combining field investigations, remote sensing data interpretation, and numerical simulations to identify the factors contributing to debris flow incidents. Analysis of land cover changes reveals a decrease in grasslands and an increase in barren land, indicating the adverse effects of deforestation on the region. Topography and gully morphology are crucial in initiating debris flows, with steep gradients and shallow slope failures predominant. Numerical simulations show that debris flows reached high velocities of 18 m/s and depths of 40 m within 45 minutes. Two debris flows resulted in the formation of dams along the Swat River, intensifying subsequent floods. The study emphasizes the interplay of extreme rainfall and deforestation during the rainy season, rendering the region susceptible to debris flows and hindering restoration efforts. The findings underscore the urgent need for comprehensive disaster mitigation strategies. Recommendations include climate change mitigation, reforestation initiatives, and discouraging construction activities in flood-prone and debris flow-prone regions. The study advocates for enhanced early warning systems and rigorous land use planning to protect the environment and local communities, highlighting the imperative of proactive measures in the face of escalating climate challenges. Additionally, the study investigates the spatial distribution of various events and their consequences, including potential hydro-meteorological triggers, and how such events initiate processes that change mountain landscapes. It also assesses the degree to which the 2022 monsoon can be classified as abnormal. The combination of empirical evidence and practical insights presented in this study highlights research gaps and proposes routes toward attaining a comprehensive comprehension of monsoon-triggered geological hazards and consequences. [ABSTRACT FROM AUTHOR]

In today's industry, H2 is mostly produced from fossil fuels such as natural gas (NG), oil, and coal through various processes. However, all these processes produce both carbon dioxide (CO2) as well as H2, making them questionable in terms of climate change mitigation efforts. In addition to efforts to increase the conversion efficiency of green H2 technologies, work is also underway to make H2 production from fossil fuels more environmentally friendly by reducing/avoiding CO2 emissions. In this framework, these technologies are combined with geologic carbon storage. In a further step, the use of depleted hydrocarbon reservoirs for in situ H2 production is being investigated, with the co-generated CO2 remaining permanently in the reservoir. The objective of this paper is to provide a brief overview of the technologies that can be used to produce H2 from depleted and depleting hydrocarbon reservoirs (DHRs) in various ways. We evaluate the required processes from a reservoir engineering perspective, highlighting their potential for H2 generation and their technology readiness level (TRL) for applications. We also investigate the possibility of permanently storing the co-produced CO2 in the reservoir as a means of mitigating emissions. In addition, we provide a preliminary cost analysis to compare these methods with conventional hydrogen production techniques, as well as an assessment of operational risks and associated cost estimates. [ABSTRACT FROM AUTHOR]

In the context of the rapidly growing demand for green investments and the need to combat climate change, this study contributes to the emerging literature on green investments by exploring the time–frequency connectedness between green bonds (GBs) and green equities. Specifically, we examine the degree of connection between GBs and green equities, the extent to which these markets influence each other, and which one is the primary net transmitter versus the net receiver of shocks under diverse market conditions. To accomplish these objectives, we use the wavelet-based Quantile-on-Quantile (QQ), dynamic conditional correlation (DCC), portfolio implications, and Quantile VAR approaches. The results show that GBs and green equities have a strong positive connection, depending on time and frequency domains. However, a negative association between GBs and green equities is observed during periods of crisis, highlighting GBs' ability to hedge green equity portfolios. The portfolio strategies demonstrate that investors require to invest in the Green Economy equity and S&P GB portfolio to reach the highest level of hedging effectiveness. The findings further imply that the Global Water Equity Index transmits the highest spillover to other green assets, while the Green Economy Equity Index receives the most spillover from other assets. The pairwise volatility connectivity reveals that most pairs have minimal quantile dependence, indicating the potential for diversification across the GB and green equity pairs. These findings have significant implications for investors and policymakers concerned with green investments and climate change mitigation. [ABSTRACT FROM AUTHOR]

The EU Biodiversity Strategy 2030 aims to better protect natural ecosystems with high biodiversity and climate change mitigation potential. To achieve this goal, it is crucial to identify forests worth protecting, such as those characterized by long continuity and old age. Here, we propose a robust approach that combines historical maps from the mid‐19th century with remote sensing data to identify areas that have been forested for over 150 years, aiming to reduce the need for detailed and time‐consuming field investigations in potential conservation areas. We tested this approach in a 20,000 km2 region in the Polish Carpathians, an area likely containing many unprotected forests of high conservation value, where historical maps from the mid‐19th century are representative of much of Central Europe. Our results showed that an area of approximately 4200 km2 has been continuously forested since at least the mid‐19th century. Currently, 50% of these forests are outside protected areas, representing an important conservation opportunity. More generally, our approach can support the identification of valuable forests worth protecting before they are lost and provide useful insights for policymakers and stakeholders in the ongoing debate on the challenges of improving forest conservation in the Carpathians, and Europe more widely. [ABSTRACT FROM AUTHOR]