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Executive Order No. 14008 mandated that U.S. federal agencies and departments develop Climate Change Adaptation Plans to enhance the nation's resilience to climate change. Invasive species are documented to reduce the effectiveness of climate adaptation and mitigation actions. In spite of this, only eight of the 26 federal plans directly reference invasive species, and just four meaningfully consider the reciprocal impact of invasive species on climate adaptation efforts. To ensure that climate adaptation planning and processes are effective with associated benefits for biodiversity conservation, a gap analysis of the Climate Change Adaptation Plans was conducted. Five key recommendations were developed that would transform how invasive species are considered within them. Examples of how invasive species have been included in some of the plans are provided, with suggestions for agencies that did not include invasive species on how they might do so, to illustrate that dedicated efforts in prevention, detection, and management of invasive species can safeguard carbon sequestration, protect communities and infrastructure, and minimize economic and biodiversity losses. Although developed based on U.S. federal plans, these recommendations can be used by state and local, as well as international, jurisdictions tasked with implementing climate‐adaptive policies to build resilience across multiple sectors. [ABSTRACT FROM AUTHOR]

Public support is crucial for the effectiveness of ambitious climate policies, and social norm interventions have been proven effective in fostering support. An open question is which norms should be communicated if support and estimated support for climate policies differ substantially between regions. In two studies, we investigate whether individuals accurately assess the existing support and then explore the impact of national and regional norms on public support. Our results show that the norm on climate policy support is generally misperceived, i.e., the norm is higher than expected. This misperception increases with policy ambition and varies substantially between sub-national regions. Information about the national norm increases support, mainly in regions with below or above-average support. In contrast, interventions with regional norms are ineffective and even backfire in low-support regions. This demonstrates that norm nudges need to consider the regional aspects of the reference and target groups. [ABSTRACT FROM AUTHOR]

This study aims to demonstrate the potential of assessing future land cover degradation status by combining the forecasting capabilities of the Cellular-Automata and Markov chain (CA-Markov) models in Idris Selva with the land cover degradation (LCD) model in the Trends.Earth module. The study focuses on the upper Zambezi Basin (UZB) in southern Africa, which is one of the regions with high rates of land degradation globally. Landsat satellite imagery is utilised to generate historical (1993–2023) land cover and land use (LCLU) maps for the UZB, while the global European Space Agency Climate Change Initiative (ESA CCI) LCLU maps are obtained from the Trends.Earth module. The CA-Markov chain model is employed to predict future LCLU changes between 2023 and 2043. The LCD model in the Trends.Earth module in QGIS 3.32.3 is then used to assess the historical and forecasted land cover degradation status. The findings reveal that land cover degradation maps produced from local LCLU classifications provide more detailed information compared to those produced from the global ESA CCI LCLU product. Between 2023 and 2043, the UZB is predicted to experience a net reduction of approximately 3.2 million hectares of forest cover, with an average annual reduction rate of − 0.13%. In terms of land cover degradation, the UZB is forecasted to remain generally stable, with 87% and 96% of the total land cover area expected to be stable during the periods 2023–2033 and 2033–2043, respectively, relative to the base years 2023 and 2033. Reduction in forest cover due to the expansion of grassland, human settlements, and cropland is projected to drive land cover degradation, while improvements in forest cover are anticipated through the conversion of grassland and cropland into forested areas. It appears that using locally produced LCLU with high-resolution images provides better assessments of land degradation in the Trends.Earth module than using global LCLU products. By leveraging the opportunities offered by models with capacity to predict LCLU such as the CA–Markov model and the capabilities of the LCD model, as evidenced in this study, valuable forecasted information can be effectively obtained for monitoring land cover degradation. This information can then be used to implement targeted interventions that align with the objective of realising the United Nations' land degradation neutral world target by 2030. [ABSTRACT FROM AUTHOR]

Frequent flooding in the central part of the Hindu Kush region, Nepal, results in substantial damage to lives and property, particularly in the plains. This study explores the catchment-scale flood hazard and vulnerability, generating flood risks under climate change scenario. Flood model was developed using HEC-RAS 2D rain-on-grid approach and CMIP6 projected climate data for SSP245 and SSP585 scenarios was used. Flood hazard, vulnerability and risk maps were generated delineating potential inundation scenarios for both 50-year, and 100-year return periods, under present and future climate scenarios. Hazard maps revealed a probable increase in flooding under future climate scenarios. Vulnerability assessments also demonstrated an anticipated escalation in future. Cropland dominates the land-use type in the study area, with agriculture vulnerability increasing by 22.14% (SSP245) and 29.322% (SSP585). The number of inundated buildings increases from 2967 in the existing scenario to 4601 (SSP245) and 5274 (SSP585). Similarly, road vulnerability areas are increased by 28.06% (SSP245) and 37.86% (SSP585). The impact of flooding is higher in SSP585 scenario as compared to SSP245 scenario. The catchment level outcomes have diverse applications, particularly in decision-making for flood management, integrating risk maps for effective strategies, and providing valuable insights into shape climate change adaptation policies. [ABSTRACT FROM AUTHOR]

Objective/context: In 2020, Ucayali was the Peruvian region with the highest loss of Amazonian forest (47,267 hectares). Measures have been taken regarding climate commitments and environmental governance, but the results continue without notoriety, and mitigation actions are limited. From a subnational approach, the article seeks to analyze the perceptions of brokers and actors involved about the implementation of forest policies in the Ucayali region. Methodology: Based on a qualitative strategy that included semi-structured interviews and a co-construction workshop to evidence the perceptions of the actors involved, with direct knowledge of the territory and implementation, and intermediary agents (brokers), the latter with the capacity to influence the decisions made regarding the formulation of action plans. Conclusions: The results demonstrate the existence of a structural difficulty in achieving short- or long-term change actions. There are institutional limitations but also a lack of support from civil society. Originality: Considering the type and limited number of studies on perceptions of climate change-oriented policies, the results obtained allow for generating relevant evidence for policy formulation processes and articulation between different levels of government. [ABSTRACT FROM AUTHOR]

The passage of the Inflation Reduction Act has been perceived as a substantial shift away from the history of more contentious climate politics in the US. We apply social network methods to interrogate an updated dataset that assesses the degree to which recent policy outcomes are a shift away from earlier policies and positions. We empirically test for homophily, a building block of polarisation, analysing four waves of survey data collected over 12 years from the community of political elites engaged in the issue of climate politics. Using Exponential Random Graph (ERG) modeling, we provide clear evidence that the stances of the top policy actors working on climate change have not shifted substantially. Instead, we document how the policy was successful due to its ability to combine the Administration's desire to support clean energy along with fossil fuel interests' aims of expanding extraction and profiting from a transition away from fossil fuels. [ABSTRACT FROM AUTHOR]

Today's ecological crises are entwined with inequality dynamics, yet prevailing techno-economic approaches in climate research and policy fall short in addressing the ecological crisis as distributional crisis. Recognising the limitations of techno-economism, focused on markets (price adjustments) and technology (efficiency gains), this contribution introduces sufficiency corridors as a concept, research field, and policy approach. Sufficiency corridors represent the space between a floor of meeting needs and a ceiling of ungeneralisable excess, i.e. within the sufficiency corridor everyone has enough (to satisfy needs) while no one has too much (to endanger planetary boundaries and need satisfaction). Establishing such corridors entails a process over time that continuously narrows the gap between floors and ceilings, lifting the former and pushing down the latter by strengthening forms of consumption and production that contribute to need satisfaction while shrinking those that do not. The article discusses the profound implications of this approach for how societal reality is reproduced and/or changed, highlighting the need for decisions that eliminate options between and within sectors and in the realms of consumption and production. After addressing questions of decision-making and the potential to realise corridors, the contribution concludes that the growing scientific consensus to complement techno-economic approaches with sufficiency measures remains inadequate. Instead, the possibility of a transformation by design hinges on embedding techno-economism within and subordinating it to a sufficiency framework. [ABSTRACT FROM AUTHOR]

Here, we investigate whether England's 152 local flood risk management strategies (LFRMSs) satisfy minimal legislative criteria and address the growing surface water flood (SWF) risk caused by climate change. A systematic audit was used to assess the alignment of the LFRMSs with national climate change legislation and other relevant national strategies. An objective method to identify inclusion of a range of factors that good strategies should include was applied. LFRMSs are mostly meeting their minimum statutory requirements. However, there is a widespread issue across most LFRMSs regarding inadequate consideration of increasing SWF risk from climate changes, which highlights the need for enhanced LFRMSs by improved planning and climate change adaptation plans. There is some evidence of good practice within the LFRMS portfolio, which is discussed in the context of the ongoing LFRMS update process. Beyond England, there are implications for developing FRM processes at a local level that can be objectively assessed against national requirements. Communities in England face inadequately managed SWF risk in the future because of the range in plan quality across the LFRMSs. This research contributes to the ongoing examination of the full suite of 152 LFRMSs and, therefore, builds towards a complete assessment of the SWF management approach in England. This will help inform local climate change adaptation strategies that cater to the escalating threat of SWF due to climate change. [ABSTRACT FROM AUTHOR]

Mandatory climate change reporting is suggested as a mechanism for mitigating firms' climate change impact and, in particular, their carbon emissions. Although extant literature provides evidence of a negative association between the introduction of carbon reporting regulation and firms' carbon emissions, the literature on real effects of climate change reporting regulation is still in its infancy and has yet to provide evidence of the channels through which reporting regulation affects firms' real climate change‐related activities. By adopting the theoretical framework of the targeted transparency action cycle, which describes the mechanism leading to the real effects of reporting regulation, we provide empirical evidence on how external pressures exerted on firms and internal policies adopted by them shape the effects of carbon reporting regulation on firms' actual carbon emissions. We take advantage of the 2013 amendments of the UK Companies Act 2006, which made the United Kingdom the first country in the world to require its listed firms to report carbon emissions in their annual reports, and we empirically show that, first, after the introduction of the new reporting regulation, firms exhibit significantly lower levels of carbon emissions; second, these effects are more prominent in firms under higher external pressure; and third, firms that engage with relevant climate change policies exhibit a much larger reduction of their carbon emissions after the regulation took effect. [ABSTRACT FROM AUTHOR]

Climate change is a confounding factor that affects food security in several ways. Although the analyses of earlier studies in this area were largely non-technical, new analytical techniques have been developed to comprehensively evaluate climate change patterns and their implications for food security. In this study, we use recent developments in panel econometrics, which consider cross-sectional dependence and parameter heterogeneity, to examine the effects of climatic conditions on cereal farming in Africa from 1970Q1 to 2017Q4. The results show that rainfall positively affects cereal crops, although average temperatures are typically unfavourable. In the country-specific scenarios, we observed significant variations in the influence of climatic conditions on cereal production. The causality test results show a two-way causal relationship between climatic conditions—rainfall and temperature—and cereal production. It is suggested that African governments and non-governmental organisations support farmers' adaptation to climate change by implementing policies that prioritise farmers' capacity building and ensure that extension service officers engage with farmers intensively. [ABSTRACT FROM AUTHOR]

In recent years, climate policy has experienced several episodes of crest and trough in the US, which has induced profound uncertainty. This climate policy uncertainty (CPU) may exert economic, social, and environmental impacts. Therefore, using the environmental Kuznets curve (EKC) framework, this study targets to probe whether CPU affects sectoral carbon dioxide emissions (COE) in the US. We make use of advanced econometric procedures such as the novel SOR unit root test (to probe the order of integration of the entire dataset) and the novel Fourier ARDL approach (to retrieve the long- and short-run estimates). The findings delineate that the EKC holds for the industrial, electric power, commercial, and residential sectors. In addition, CPU escalates COE in the residential, commercial, and electric power sectors in both the long- and short-run. Parallel to this, CPU affects industrial COE neither in the short-run nor in the long-run. Keeping in view the key findings, we propose a set of sector-specific policy implications to curb COE. [ABSTRACT FROM AUTHOR]

Industrial emissions are significant and need to be addressed in the fight against climate change. To achieve carbon emission reduction targets in line with climate change policies while maintaining the competitiveness of the industry, hard-to-abate sectors are exploring efficient carbon reduction technologies and striving to reduce associated costs. Carbon capture technology presents a large-scale CO2 reduction solution with immense potential. In promoting the application of carbon capture in hard-to-abate industries, it is essential to comprehensively analyze the feasibility and economics of carbon capture technology. This paper conducts a review of the technical feasibility and economics of carbon capture technologies in several industrial sectors, namely iron and steel, cement, and coal chemical industries. A vast amount of data on the costs of industrial carbon capture technologies has been gathered for comparison. This study also specifically addresses policy incentives that have been discussed and are currently being implemented to cut costs and promote industrial carbon capture projects. [ABSTRACT FROM AUTHOR]

Dissolved Organic Carbon (DOC) is the largest organic carbon pool in the ocean. Considering the biotic and abiotic factors controlling DOC processes, indirect satellite methods for open ocean DOC estimation can be developed, using conceptual, empirical or statistical models, driven by multiple satellite products. In this study, we infer a time series of global DOC from data of the European Space Agency's (ESA) Ocean Colour Climate Change Initiative (OC-CCI) in combination with a global database of in situ DOC observations. We tested empirical machine learning modelling approaches in which the available in situ data are used to train the models and to find empirical relationships between DOC and variables available from remote sensing. Of the tested methods, a random forest regression showed the best results, and the details of this model are further reported here. We present a time series of global open ocean DOC concentrations between 2010-2018 that is made freely available through the archive of the UK Centre for Environmental Data Analysis (CEDA). [ABSTRACT FROM AUTHOR]

Climate policy will inevitably lead to the stranding of fossil energy assets such as production and transport assets for coal, oil, and natural gas. Resource- rich developing countries are particularly affected, as they have a higher risk of asset stranding due to strong fossil dependencies and wider societal consequences beyond revenue disruption. However, there is only little academic and political awareness of the challenge to manage the asset stranding in these countries, as research on transition risk like asset stranding is still in its infancy. We provide a research framework to identify wider societal consequences of fossil asset stranding. We apply it to a case study of Nigeria. Analyzing different policy measures, we argue that compensation payments come with implementation challenges. Instead of one policy alone to address asset stranding, a problem-oriented mix of policies is needed. Renewable hydrogen and just energy transition partnerships can be a contribution to economic development and SDGs. However, they can only unfold their potential if fair benefit sharing and an improvement to the typical institutional problems in resource-rich countries, such as the lack of rule of law, are achieved. We conclude with presenting a future research agenda for the global community and academia. [ABSTRACT FROM AUTHOR]

Lakes are a crucial source of drinking water, provide ecological services from fisheries and aquaculture to tourism and are also a critical part of the global carbon cycle. Therefore, it is important to understand how lakes are changing over time. The ESA Ocean Colour Climate Change Initiative (OC-CCI) database allows to study changes in the largest lakes over 1997–2023 period. The Caspian Sea and ten next largest lakes were under investigation. Changes in the phytoplankton biomass (Chl-a), the concentration of particulate matter (bbp(555)), the colored dissolved organic matter, CDOM (adg(412)), and the light diffuse attenuation coefficient in water (Kd(490)) were analyzed. Both increasing and decreasing trends (or no significant trend at all) of studied parameters were observed in these lakes over the study period. In some of the Laurentian Great Lakes the changes in CDOM over the study period were found to be in accordance with the lake water level changes i.e. with the inflow from the catchment. There was difference between the trends of Chl-a and bbp(555) in lakes Michigan and Huron indicating that there may have been shift in phytoplankton community that took place around 2005. The study demonstrated that remote sensing products, like the ones created by ESA OC-CCI, are valuable tools to study behavior of large lakes ecosystems over time. [ABSTRACT FROM AUTHOR]

Droughts present substantial challenges to agriculture, food security, and water resources. Employing a drought index based on soil moisture dynamics is a common and effective approach for agricultural drought monitoring. However, the precision of a drought index heavily relies on accurate soil moisture and soil hydraulic parameters. This study leverages remote sensing soil moisture data from the Climate Change Initiative (CCI) series products and model-generated soil moisture data from the Variable Infiltration Capacity (VIC) model. The extended triple collocation (ETC) method was applied to merge these datasets from 1992 to 2018, resulting in enhanced accuracy by 28% and 15% compared to the CCI and VIC soil moisture, respectively. Furthermore, this research establishes field capacity and a wilting point map using multiple soil datasets and pedotransfer functions, facilitating the development of an enhanced Soil Water Deficit Index (SWDI) based on merged soil moisture, field capacity, and wilting points. The findings reveal that the proposed enhanced SWDI achieves a higher accuracy in detecting agricultural drought events (probability of detection = 0.98) and quantifying their severity (matching index = 0.33) compared to an SWDI based on other soil moisture products. Moreover, the enhanced SWDI exhibits superior performance in representing drought-affected crop areas (correlation coefficient = 0.88), outperforming traditional drought indexes such as the Standardized Precipitation Index (correlation coefficient = 0.51), the Soil Moisture Anomaly Percent Index (correlation coefficient = 0.81), and the Soil Moisture Index (correlation coefficient = 0.83). The enhanced SWDI effectively captures the spatiotemporal dynamics of a drought, supporting more accurate agricultural drought monitoring and management strategies. [ABSTRACT FROM AUTHOR]

Climate change has a significant impact on human economic and social life, and climate issues have rapidly emerged as a global hot topic. Using data from prefecture-level cities in China from 2005 to 2020 as a sample, this study explores the relationship between climate policy uncertainty (CPU) and urban green total factor energy efficiency (GTFEE). The results show that, first, the CPU can significantly improve urban GTFEE, and results are reconfirmed after various robustness tests. Second, the CPU promotes urban GTFEE by improving public environmental concerns and optimizing the energy consumption structure. Third, the promotion role of CPU in urban GTFEE is particularly significant in resource-based cities and economically developed cities. The results of this study provide a theoretical basis and practical enlightenment for the government to formulate forward-looking climate policies and promote the transformation of green development in cities. [ABSTRACT FROM AUTHOR]

Climate change is a very debated topic among academia, national and international institutions. Therefore, policies and tools for diminishing pollutant emissions are in place in a number of countries. Among them, taxation and renewable energy use seem to be among the most important. This paper aims at testing the impact of certain tools for climate change policy implementation, such as environmental taxes, renewable energy use, real productivity, employment rate taking into consideration the level of economic development and the GINI coefficient, on the greenhouse gas emissions in two important sectors of the economy: industry and commerce. Panel data analysis is used for a cluster of nine developing countries of the European Union that have the per capita GDP at purchasing power parity lower than 80% of the EU average, during 2008-2021. Similar to other studies, the results show a negative relationship between environmental taxation and greenhouse gas emissions in the industrial sector, and a positive one in the commercial sector. The latter is explained by the fact that transport, which is a main pollutant sector, is also one of the most difficult sectors to achieve green transition, given high associated costs. The analysis also shows that renewable energy use discourages the emissions of greenhouse gases, both in the industrial and commercial sectors, so that fostering investment in renewables is an important factor for addressing climate change and promoting a sustainable growth. [ABSTRACT FROM AUTHOR]

With the rapid proliferation of climate policies in both number and scope, there is an increasing demand for a global-level dataset that provides multi-indicator information on policy elements and their implementation contexts. To address this need, we developed the Global Climate Change Mitigation Policy Dataset (GCCMPD) using a semisupervised hybrid machine learning approach, drawing upon policy information from global, regional, and sector-specific sources. Differing from existing climate policy datasets, the GCCMPD covers a large range of policies, amounting to 73,625 policies of 216 entities. Through the integration of expert knowledge-based dictionary mapping, probability statistics methods, and advanced natural language processing technology, the GCCMPD offers detailed classification of multiple indicators and consistent information on sectoral policy instruments. This includes insights into objectives, target sectors, instruments, legal compulsion, administrative entities, etc. By aligning with the sector classification of the Intergovernmental Panel on Climate Change (IPCC) emission datasets, the GCCMPD serves to help policy-makers, researchers, and social organizations gain a deeper understanding of the similarities and distinctions among climate activities across countries, sectors, and entities. [ABSTRACT FROM AUTHOR]

In every Intergovernmental Panel on Climate Change (IPCC) Assessment cycle, a multitude of scenarios are assessed, with different scope and emphasis throughout the various Working Group reports and special reports, as well as their respective chapters. Within the reports, the ambition is to integrate knowledge on possible climate futures across the Working Groups and scientific research domains based on a small set of "framing pathways" such as the so-called representative concentration pathways (RCPs) in the Fifth IPCC Assessment Report (AR5) and the shared socioeconomic pathway (SSP) scenarios in the Sixth Assessment Report (AR6). This perspective, initiated by discussions at the IPCC Bangkok workshop in April 2023 on the "Use of Scenarios in AR6 and Subsequent Assessments", is intended to serve as one of the community contributions to highlight the needs for the next generation of framing pathways that is being advanced under the Coupled Model Intercomparison Project (CMIP) umbrella, which will influence or even predicate the IPCC AR7 consideration of framing pathways. Here we suggest several policy research objectives that such a set of framing pathways should ideally fulfil, including mitigation needs for meeting the Paris Agreement objectives, the risks associated with carbon removal strategies, the consequences of delay in enacting that mitigation, guidance for adaptation needs, loss and damage, and for achieving mitigation in the wider context of societal development goals. Based on this context, we suggest that the next generation of climate scenarios for Earth system models should evolve towards representative emission pathways (REPs) and suggest key categories for such pathways. These framing pathways should address the most critical mitigation policy and adaptation plans that need to be implemented over the next 10 years. In our view, the most important categories are those relevant in the context of the Paris Agreement long-term goal, specifically an immediate action (low overshoot) 1.5 °C pathway and a delayed action (high overshoot) 1.5 °C pathway. Two other key categories are a pathway category approximately in line with current (as expressed by 2023) near- and long-term policy objectives, as well as a higher-emission category that is approximately in line with "current policies" (as expressed by 2023). We also argue for the scientific and policy relevance in exploring two "worlds that could have been". One of these categories has high-emission trajectories well above what is implied by current policies and the other has very-low-emission trajectories which assume that global mitigation action in line with limiting warming to 1.5 °C without overshoot had begun in 2015. Finally, we note that the timely provision of new scientific information on pathways is critical to inform the development and implementation of climate policy. Under the Paris Agreement, for the second global stocktake, which will occur in 2028, and to inform subsequent development of nationally determined contributions (NDCs) up to 2040, scientific inputs are required by 2027. These needs should be carefully considered in the development timeline of community modelling activities, including those under CMIP7. [ABSTRACT FROM AUTHOR]

As enterprises look forward to new market share and supply chain opportunities, innovative strategies and sustainable manufacturing play important roles for micro-, small, and mid-sized enterprises worldwide. Sustainable manufacturing is one of the practices aimed towards deploying green energy initiatives to ease climate change, presenting three main pillars—economic, social, and environmental. The issue of how to reach sustainability goals within the sustainable manufacturing of pillars is a less-researched area. This paper's main purpose and novelty is two-fold. First, it aims to provide a hierarchy of the green energy indicators and their measurements through a multi-criteria decision-making point of view to implement them as an alliance strategy towards sustainable manufacturing. Moreover, we aim to provide researchers and practitioners with a forecasting method to re-prioritize green energy indicators through a linearity factor model. The CODAS–Hamming–Mahalanobis method is used to obtain preference scores and rankings from a 50-item list. The resulting top 10 list shows that enterprises defined nine items within the economic pillar as more important and one item on the environmental pillar; items from the social pillar were less important. The implication for MSMEs within the manufacturing sector represents an opportunity to work with decision makers to deploy specific initiatives towards sustainable manufacturing, focused on profit and welfare while taking care of natural resources. In addition, we propose a continuous predictive analysis method, the linearity factor model, as a tool for new enterprises to seek a green energy hierarchy according to their individual needs. The resulting hierarchy using the predictive analysis model presented changes in the items' order, but it remained within the same two sustainable manufacturing pillars: economic and environmental. [ABSTRACT FROM AUTHOR]

Beneficial influence of female representation in implementing environment-friendly policies have been documented in recent studies. However, presence of factors such as corruption and bureaucratic red tapes, known to hinder development initiatives, raises question about whether women legislators can achieve the desired level of success with environmental policies. Based on our empirical analysis using cross-sectional data for 83 countries, we find evidence that the positive impact of women in parliament on climate change policy outcomes is significant and most effective for countries with low levels of corruption. Depending on the model specification used, ranging from instrumental variable regressions to inclusion of controls to mitigate omitted variable bias, and matching models, we do find that the beneficial impact of women in parliament becomes insignificant and eventually might become negative with rising corruption. Thus, while women might be able to successfully propose a bill for and turn-into-law, environment-friendly policies in countries with low levels of corruption, the effort is nullified and might be reversed in case of countries with high corruption. We illustrate that the results are sensitive to model selection, and choice of controls. [ABSTRACT FROM AUTHOR]

India experienced several unprecedented floods in the recent decades. The increase in the extreme rainfall events (EREs) is the primary cause for these floods, manifesting its societal impacts. The daily downscaled and bias corrected (DBC) Coupled Model Intercomparison Project Phase 6 (CMIP6) rainfall and sea surface temperature (SST) are prepared for the Indian region and are utilized to examine the characteristics of EREs. The DBC products capture the characteristic features of EREs for the baseline period, which inspired us to assess the EREs over India in CMIP6 future projections. Consistent with the observations, DBC product shows ~ 8% of Indian land found to experienced extremely heavy rainfall associated with the long duration EREs in the baseline period. However, area and extreme rainfall thresholds are projected to increase by about 18(13)% and 58(50)%, respectively in the far future under SSP5-8.5 (SSP2-4.5) emission scenario relative to the baseline period. A two-fold-65(62)% increase in long-duration EREs compared to the short-duration EREs and substantial warming ~ 2.4(2.9) oC of Indian Ocean SSTs in the far future under SSP5-8.5 (SSP2-4.5) emission scenario compared to baseline period are reported. These findings may provide fundamental insights to formulate national climate change adaptation policies for the EREs. [ABSTRACT FROM AUTHOR]

Microbial communities play a crucial role in ocean ecology and global biogeochemical processes. However, understanding the intricate interactions among diversity, taxonomical composition, functional traits, and how these factors respond to climate change remains a significant challenge. Here, we propose seven distinct ecological statuses by systematically considering the diversity, structure, and biogeochemical potential of the ocean microbiome to delineate their biogeography. Anthropogenic climate change is expected to alter the ecological status of the surface ocean by influencing environmental conditions, particularly nutrient and oxygen contents. Our predictive model, which utilizes machine learning, indicates that the ecological status of approximately 32.44% of the surface ocean may undergo changes from the present to the end of this century, assuming no policy interventions. These changes mainly include poleward shifts in the main taxa, increases in photosynthetic carbon fixation and decreases in nutrient metabolism. However, this proportion can decrease significantly with effective control of greenhouse gas emissions. Our study underscores the urgent necessity for implementing policies to mitigate climate change, particularly from an ecological perspective. Zhang et al. propose the ecological status of the ocean by considering microbial diversity, structure, and biogeochemical potential. Ecological status of 32.44% surface ocean will change due to climate change in 2100, assuming no policy intervention. [ABSTRACT FROM AUTHOR]

Political polarization of Americans' support for climate policies often impedes the adoption of new, urgently needed climate solutions. However, recent polls suggest that younger conservatives favor adopting pro-climate policies to a greater degree than older conservatives, resulting in less political polarization among younger Americans relative to older Americans. To better understand these patterns, we analyzed Americans' support for various climate policies from 1982–2020, across 16 waves of historical, nationally representative survey data from the American National Election Studies (total N = 29,467). Regression models consistently show that, since 2012, younger Americans have been less politically polarized than older Americans on support for climate policies. Before 2012 and on non-climate policy topics, we did not find consistent statistical evidence for political polarization varying with age. These findings can inform policy debates about climate change and offer hope to environmentalists and policymakers who seek to build broad consensus for climate action at the policy level. [ABSTRACT FROM AUTHOR]

This paper presents a thorough examination of methane capture from Polish coal mines, contextualized within the framework of the European Union's (EU) climate policy objectives. Through a strategic analysis encompassing the interior of coal mines, the surrounding environment, and the macro environment, this study elucidates the complex dynamics involved in methane emissions and capture initiatives. The key findings include a declining trend in absolute methane emissions since 2008, despite fluctuations in coal extraction volumes, and a relatively stable level of methane capture exceeding 300 million m3/year since 2014. The analysis underscores the critical role of government support, both in terms of financial incentives and streamlined regulatory processes, to facilitate the integration of methane capture technologies into coal mining operations. Collaboration through partnerships and stakeholder engagement emerges as essential for overcoming resource competition and ensuring the long-term success of methane capture projects. This paper also highlights the economic and environmental opportunities presented by methane reserves, emphasizing the importance of investment in efficient extraction technologies. Despite these advancements, challenges persist, particularly regarding the low efficiency of current de-methanation technologies. Recommendations for modernization and technological innovation are proposed to enhance methane capture efficiency and utilization. [ABSTRACT FROM AUTHOR]

Background: Carbon (C) sink and stock are among the most important ecosystem services provided by forests in climate change mitigation policies. In this context, old-growth forests constitute an essential reference point for the development of close-to-nature silviculture, including C management techniques. Despite their small extent in Europe, temperate old-growth forests are assumed to be among the most prominent in terms of biomass and C stored. However, monitoring and reporting of C stocks is still poorly understood. To better understand the C stock amount and distribution in temperate old-growth forests, we estimated the C stock of two old-growth stands in the Dinaric Alps applying different assessment methods, including direct and indirect approaches (e.g., field measurements and allometric equations vs. IPCC standard methods). This paper presents the quantification and the distribution of C across the five main forest C pools (i.e., aboveground, belowground, deadwood, litter and soil) in the study areas and the differences between the applied methods. Results: We report a very prominent C stock in both study areas (507 Mg C ha− 1), concentrated in a few large trees (36% of C in 5% of trees). Moreover, we found significant differences in C stock estimation between direct and indirect methods. Indeed, the latter tended to underestimate or overestimate depending on the pool considered. Conclusions: Comparison of our results with previous studies and data collected in European forests highlights the prominence of temperate forests, among which the Dinaric Alps old-growth forests are the largest. These findings provide an important benchmark for the development of future approaches to the management of the European temperate forests. However, further and deeper research on C stock and fluxes in old-growth stands is of prime importance to understand the potential and limits of the climate mitigation role of forests. [ABSTRACT FROM AUTHOR]

Objective: Climate change is recognised as the biggest threat to global health of the 21st century and impacts on health and wellbeing through a range of factors. Due to this, the need to take action in order to protect population health and wellbeing is becoming ever more urgent. Methods: In 2019, Public Health Wales carried out a comprehensive mixed-method Health Impact Assessment (HIA) of climate change. Unlike other risk assessments, it appraised the potential impact of climate change on health and inequalities in Wales through participatory workshops, stakeholder consultations, systematic literature reviews and case studies. Results: The HIA findings indicate potential impacts across the wider determinants of health and wellbeing. For example, air quality, excess heat/cold, flooding, economic productivity, infrastructure, and community resilience. A range of impacts were identified across population groups, settings, and geographical areas. Conclusion: These findings can inform decision-makers to prepare for climate change plans and policies using an evidence-informed approach. The work has demonstrated the value of a HIA approach by mobilising a range of evidence through a transparent process, resulting in transferrable learning for others. [ABSTRACT FROM AUTHOR]

In the oceanic surface layer, particulate organic carbon (POC) constitutes the biggest pool of particulate material of biological origin, encompassing phytoplankton, zooplankton, bacteria, and organic detritus. POC is of general interest in studies of biologically-mediated fluxes of carbon in the ocean, and over the years, several empirical algorithms have been proposed to retrieve POC concentrations from satellite products. These algorithms can be categorised into those that make use of remote-sensing-reflectance data directly, and those that are dependent on chlorophyll concentration and particle backscattering coefficient derived from reflectance values. In this study, a global database of in situ measurements of POC is assembled, against which these different types of algorithms are tested using daily matchup data extracted from the Ocean Colour Climate Change Initiative (OC-CCI; version 5). Through analyses of residuals, pixel-by-pixel uncertainties, and validation based on optical water types, areas for POC algorithm improvement are identified, particularly in regions underrepresented in the in situ POC data sets, such as coastal and high-latitude waters. We conclude that POC algorithms have reached a state of maturity and further improvements can be sought in blending algorithms for different optical water types when the required in situ data becomes available. The best performing band ratio algorithm was tuned to the OC-CCI version 5 product and used to produce a global time series of POC between 1997-2020 that is freely available. [ABSTRACT FROM AUTHOR]

In the oceanic surface layer, particulate organic carbon (POC) constitutes the biggest pool of particulate material of biological origin, encompassing phytoplankton, zooplankton, bacteria, and organic detritus. POC is of general interest in studies of biologically-mediated fluxes of carbon in the ocean, and over the years, several empirical algorithms have been proposed to retrieve POC concentrations from satellite products. These algorithms can be categorised into those that make use of remote-sensing-reflectance data directly, and those that are dependent on chlorophyll concentration and particle backscattering coefficient derived from reflectance values. In this study, a global database of in situ measurements of POC is assembled, against which these different types of algorithms are tested using daily matchup data extracted from the Ocean Colour Climate Change Initiative (OC-CCI; version 5). Through analyses of residuals, pixel-by-pixel uncertainties, and validation based on optical water types, areas for POC algorithm improvement are identified, particularly in regions underrepresented in the in situ POC data sets, such as coastal and high-latitude waters. We conclude that POC algorithms have reached a state of maturity and further improvements can be sought in blending algorithms for different optical water types when the required in situ data becomes available. The best performing band ratio algorithm was tuned to the OC-CCI version 5 product and used to produce a global time series of POC between 1997-2020 that is freely available. [ABSTRACT FROM AUTHOR]

This paper presents an additive index on climate policy engagement at the municipal level, based on the three dimensions awareness, conception and implementation of climate change mitigation and adaptation. The distortion of the index is based on the self-perception and personal assessment of municipal decision-makers, which were collected and evaluated as part of a primary survey (postal survey). The index shows how strongly a municipality is committed to climate policy. Thus, it represents an extension of previous indices that either only consider climate mitigation or adaptation or are only based exclusively on secondary statistics. The second part of the paper describes the application of the index in three counties or 51 municipalities in Saxony, Saxony-Anhalt and Thuringia. The interpretation takes place in the context of structural characteristics of the municipalities concerned (number of inhabitants, share of votes of different parties, geographical location). The distribution of the index values shows a similar awareness in climate protection and climate change adaptation, but an increasing discrepancy in the implementation of adaptation-specific measures. [ABSTRACT FROM AUTHOR]

The amended German Climate Protection Act of 2021 is seen as an essential step towards fulfilment national climate protection targets and as a sign of mainstreaming climate protection in German politics. However, at the regional level, where many climate protection measures are implemented, there is a strong fragmentation in terms of priorities, policy instruments, actor constellations and resources. Moreover, the implementation of climate protectionmeasures is under increasing pressure in the face of crises, such as the management of the Covid 19 pandemic or the energy crisis. We therefore ask: Under what conditions does regional climate protection succeed in times of crisis? Drawing on the regional governance concept and a comparative analysis of ten German counties, we explain differences in subnational climate governance. For our study, very different, but always rural districts were selected, as the importance of rural regions is often neglected in the study of local climate policy. Based on a qualitative document analysis in combination with observations and interviewswith climate protectionmanagers, we identify factors for the success of climate protection activities in times ofmultiple crises. We argue that structural factors are central to the success of regional climate protectionmeasures in times of crisis, as they provide the framework conditions for the actions of actors. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

Dairy farming is highly vulnerable to climate change in Pakistan; therefore, productivity and earnings of small dairy farmers are at a higher risk. Dairy farmers can reduce the determintal impacts of climate change on productivity and earnings by adaptation to climate change. It is thus critical to understand the adaptation to climate change among dariy farmers and consequent impacts on productivity and earnings. Using cross-sectional data of 450 dairy farmers from three different agroecological zones of Punjab, Pakistan, study has employed the logistic regression to determine determinants of adaptation and to analyze the adaptation impact on farm productivity and on earnings of the farmers. Educated and large farm size farmers are highly probable to adopting more adaptation measures compared to their counterparts. Estimates of PSM reveal that milk productivity and earings of adapters are higher than non-adapters. Regular vaccination found to be the most widely adopted strategy, which provides greater returns in terms of sustained milk prodction and improved dairy income. The research makes significant recommendations for adapting policies to climate change in dairy farming for improving well-being of rural households. [ABSTRACT FROM AUTHOR]

Climate adaptation strengthens and builds the resilience of health systems to future climate-related shocks. Adaptation strategies and policies are necessary tools for governments to address the long-term impacts of climate change and enable the health system to respond to current impacts such as extreme weather events. Since 2011 South Africa has national climate change policies and adaptation strategies, yet there is uncertainty about: how these policies and plans are executed; the extent to which health policies include adaptation; and the extent of policy coherence across sectors and governance levels. A policy document analysis was conducted to examine how South African climate change, development and health policy documents reflect the health adaptation response across national and Western Cape levels and to assess the extent of coherence across key health and environment sector policy documents, including elements to respond to health-related climate risks, that can support implementation. Our findings show that overall there is incoherence in South African climate adaptation within health policy documents. Although health adaptation measures are somewhat coherent in national level policies, there is limited coherence within Western Cape provincial level documents and limited discussion on climate adaptation, especially for health. Policies reflect formal decisions and should guide decision-makers and resourcing, and sectoral policies should move beyond mere acknowledgement of adaptation responses to a tailored plan of actions that are institutionalized and location and sector specific. Activities beyond documents also impact the coherence and implementation of climate adaptation for health in South Africa. Clear climate risk-specific documents for the health sector would provide a stronger plan to support the implementation of health adaptation and contribute to building health system's resilience. [ABSTRACT FROM AUTHOR]

Drought has a paramount impact on global agriculture and food security. However, the study on future cropland areas that can incur drought is inadequate. This paper uses input parameters from 7 CMIP6 models for 7 future scenarios (SSP1‐1.9, SSP1‐2.6, SSP4‐3.4, SSP2‐4.5, SSP4‐6.0, SSP3‐7.0, and SSP5‐8.5) to measure South Asian cropland exposure to drought and its underlying factors. Some defined epochs such as 2021–2040 (near‐term), 2041–2060 (mid‐term), 2081–2100 (long‐term), and 1995–2014 (reference period) are designed to explore diverse outlooks of the change. The Standardized Precipitation Evapotranspiration Index and the Run theory methods are applied to detect drought. Results indicate an intensified cropland (under SSP4‐3.4, SSP3‐7.0, and SSP5‐8.5) in the Indo‐Gangetic Plain region of South Asia, where mostly the variation occurs among scenarios and periods. Notably, the future cropland exposed to drought will increase in the 2021–2040, and 2041–2060 periods, but it intends to decline during the 2081–2100. Relatively, the exposed cropland will upturn highest by 49.2% (SSP3‐7.0) in the mid‐term period and decrease by −8.2% (SSP5‐8.5) in the end future. Spatially, distributed cropland in the central, south‐west, and portion of the northeast of South Asia are subjective to be exposed largely, but it can drop greatly across the eastern part by the end future. Importantly, the climate change effect plays a grounding role in future exposure change over the region during the near to mid‐term periods, while the cropland change effect is predominant in the long‐term perspectives. However, these findings signify the urgency of policymaking focusing on drought mitigation to ensure food security. Plain Language Summary: Estimating drought‐induced cropland exposure is the pivotal aspect of agricultural risk assessment for drought impacts. The purposes of this study are to explore (a) how much of the cropland area would be exposed to drought under SSP scenarios; and (b) the degree to which climate change and cropland change effects contribute to changes in exposure. In this regard, we conducted a multi‐model and multi‐scenario‐based analysis to reveal variations in the cropland area exposed to drought in South Asia. Among the seven scenario combinations, the highest percentage of cropland exposed to drought was found at 49.2% (SSP3‐7.0) in the mid‐term epoch (2041–2060). The climate change effect seems to be the key contributor in the near‐term to mid‐term period, whereas it is the cropland change effect long‐term. To reduce drought risk, we recommend focusing on strong climate change mitigation policy development in the near‐ and mid‐term periods at a global scale and strict land‐use management policy interventions in the long‐term period at the regional level. Key Points: Larger cropland area will experience drought in the 2040–2060 period, while it will decline by the end of 21st centuryThe exposed cropland will increase by 49.2% under SSP3‐7.0 than that of historical timeThe climate change effect is the pivotal contributor in exposure changes over South Asia [ABSTRACT FROM AUTHOR]

Motivated by the growing attention on climate change acceleration, we examine the interrelationships among corporate governance disclosure index, bank ownership structures, and bank climate change initiatives through the lens of a multi‐theoretical framework. We conduct a fixed‐effects and dynamic two‐step system generalized method of moments models over an extensive dataset. Based on panel data of 220 banks (2,785 observations) from 16 Sub‐Saharan Africa emerging economies between 2007 and 2022, the study observes that banks with higher levels of corporate governance disclosure index engage in more climate change initiatives. The study shows that ownership by institutional and foreign investors is associated with more bank climate change initiatives, while government ownership reduces climate change initiatives. Further, we document that director ownership has no impact on climate change initiatives. The study documents that the association between bank ownership structures and bank climate change initiatives is positively moderated by the extent of the corporate governance disclosure index. This moderating impact improves for banks with high corporate governance mechanisms. Finally, we show that the bank ownership structures‐climate change initiatives linkage and the moderating effect of corporate governance mechanisms on this nexus vary significantly across banks' operating periods. We identify corporate governance disclosure as the potential channel through which bank ownership structures and climate change initiatives are interlinked. Our findings call for banks to adopt and implement good governance disclosure to improve climate change initiatives. The findings make significant theoretical and regulatory contributions. [ABSTRACT FROM AUTHOR]

This study theorizes and empirically tests whether firms' decisions to join multi‐stakeholder initiatives, targeting climate mitigation, lead to improved environmental performance. We focus on firms' participations in the Science Based Targets initiative, a multi‐stakeholder initiative meant to support firms in setting greenhouse gas (GHG) emission reduction targets in line with the thresholds defined by the Paris Agreement in 2015. The study hypothesizes that participation reduces firm's concerns about uncertainty and encourages investments in timeous internal climate change activities. We used the coarsened exact matching methodology to create a matched sample of European and North American listed firms participating in the initiative and comparable, non‐participating firms over a 3‐year period from 2015 to 2017. The results showed that firms' participation led to lower levels of GHG emissions compared to similar non‐participating counterparts, especially when they committed to the initiative with the intention to follow the proposed indications. [ABSTRACT FROM AUTHOR]

Copyright of Methaodos: Social Science Journal / Methaodos: Revista de Ciencias Sociales is the property of Departamento de Ciencias de la Comunicacion y Sociologia, Universidad Rey Juan Carlos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The European Union is committed to a 55% reduction in greenhouse gas emissions by 2030, as outlined in the Green Deal and Climate Law initiatives. In response to geopolitical events, the RePowerEU initiative aims to enhance energy self-sufficiency, reduce reliance on Russian natural gas, and promote hydrogen utilization. Hydrogen valleys, localized ecosystems integrating various hydrogen supply chain elements, play a key role in this transition, particularly benefiting isolated regions like islands. This manuscript focuses on optimizing a Centralized Green Hydrogen Production Facility (CGHPF) on the island of Crete. A mixed-integer linear programming framework is proposed to optimize the CGHPF, considering factors such as land area, wind and solar potential, costs, and efficiency. Additionally, an in-depth sensitivity analysis is conducted to explore the impact of key factors on the economic feasibility of hydrogen investments. The findings suggest that hydrogen can be sold in Crete at prices as low as 3.5 EUR/kg. Specifically, it was found in the base scenario that, selling hydrogen at 3.5 EUR/kg, the net profit of the investment could be as high as EUR 6.19 million, while the capacity of the solar and wind installation supplying the grid hydrogen facility would be 23.51 MW and 52.97 MW, respectively. It is noted that the high profitability is justified by the extraordinary renewable potential of Crete. Finally, based on our study, a policy recommendation to allow a maximum of 20% direct penetration of renewable sources of green hydrogen facilities into the grid is suggested to encourage and accelerate green hydrogen expansion. [ABSTRACT FROM AUTHOR]

Stratospheric aerosol injection is a potential method of climate intervention to reduce climate risk as decarbonization efforts continue. However, possible ecosystem impacts from the strategic design of hypothetical intervention scenarios are poorly understood. Two recent Earth system model simulations depict policy-relevant stratospheric aerosol injection scenarios with similar global temperature targets, but a 10-year delay in intervention deployment. Here we show this delay leads to distinct ecological risk profiles through climate speeds, which describe the rate of movement of thermal conditions. On a planetary scale, climate speeds in the simulation where the intervention maintains temperature are not statistically distinguishable from preindustrial conditions. In contrast, rapid temperature reduction following delayed deployment produces climate speeds over land beyond either a preindustrial baseline or no-intervention climate change with present policy. The area exposed to threshold climate speeds places different scenarios in context to their relative ecological risks. Our results support discussion of tradeoffs and timescales in future scenario design and decision-making. Hueholt et al. find that considering how the rate of temperature change contributes to ecosystem risk helps inform future hypothetical design of climate intervention scenarios [ABSTRACT FROM AUTHOR]

Globally, drought is occurring more frequently today, which is considerably affecting rural households' agricultural productivity and socioeconomic development. Understanding households' perceptions of drought is thus important for resilience-building work because people act based on their views, and the resilience of people is tied to their views, knowledge, culture, and attitudes. This study analyses the rural households' perceptions of drought occurrence and its influence on livelihood strategies in northeast Ethiopia. This was achieved through a mixed-methods approach with a concurrent research design. The quantitative data were collected from 354 randomly selected household heads, whereas the qualitative data were collected from purposefully selected household head focus group discussions (FGDs) and key informants. The quantitative data were analyzed using descriptive statistics, whereas the qualitative data were analyzed using thematic data analysis techniques. The results show that climate variability and drought occurrence were perceived by the households as decreasing rainfall, increasing temperature, variations in rainfall onset and cessation, variations in heat waves and cold waves, heavy rainfall events, changes in sporadic rain, a lesser coverage of clouds, and adverse weather events. Within the last 25 years, households have perceived the number of extreme, severe, or moderate droughts to be increasing. Household perceptions of temperature changes match meteorological records, but their perceptions of rainfall changes do not. The drought hampered income sources, brought food shortages, and threatened family well-being. It increased water stress, livestock morbidity and mortality, insect invasions, fire outbreaks, grazing resource depletion, abnormal migration, school dropout rates, and human health problems. The findings have important policy implications to mitigate drought risk, enhance drought adaptation, and develop pathways out of drought vulnerability, so it is worthwhile to harmonize the household perceptions with climate change policy. [ABSTRACT FROM AUTHOR]

On the third anniversary of the World Health Organization's declaration of a global pandemic, Gen Z's first congressional representative, Maxwell Alejandro Frost, advocated for a reduction in the Pentagon's budget to better serve local communities. This perspective underscores the economic and moral rationale for reallocating national defense funds to communities. The call for defunding the police has gained momentum, paralleling the advocacy for demilitarization. This Article emphasizes the overlooked impact of U.S. military carbon emissions on climate change and advocates for its inclusion in national carbon accounting systems globally. The U.S. Department of Defense has not been transparent about its carbon footprint, excluding significant military emissions from most official reports. Including military carbon emissions in national assessments can strengthen the U.S.'s stance in climate negotiations. Reallocating the Pentagon budget to support climate change initiatives would foster international cooperation and peace. This demilitarization could symbolize the U.S.'s commitment to disarmament, inspiring global stability, and resilience against climate-induced challenges. [ABSTRACT FROM AUTHOR]

This paper analyzed the importance of integrating disaster risk reduction and climate change adapting policies into the socio-economic development plans of coastal municipalities in Cuba. To this end, a literature review was carried out to locate the main theoretical and bibliographical sources on Disaster Risk Reduction, Climate Change Adaptation, coastal municipalities and government policies and triangulate them to create a four-phase integration tool. This tool will improve the territorial development plans and make them more effective while promoting an integrated vision of disaster risk reduction and adapting to climate change as a fundamental basis for the sustainability of development in Cuba. [ABSTRACT FROM AUTHOR]

GNSS Reflectometry (GNSS-R) is an emerging technique for the remote sensing of the environment. Traditional GNSS-R bio-geophysical parameter retrieval algorithms and deep learning models utilize observables derived from only the peak power of the delay-Doppler maps (DDMs), discarding the rest. This reduces the data available, which potentially hinders estimation accuracy. In addition, reflections from water bodies dominate the signal amplitude, and using only the peak power in those areas is challenging. Motivated by all the above, we propose a novel deep learning retrieval model for biomass estimation that uses the full DDM of surface reflectivity. Experiments using CYGNSS data have illustrated the improvements achieved when using the full DDM of surface reflectivity. Our proposed model was able to estimate biomass, trained using the ESA Climate Change Initiative (CCI) biomass map, outperforming the model that used peak reflectivity. Global and regional analysis is provided along with an illustration of how biomass estimation is achieved when using the full DDM around water bodies. GNSS-R could become an efficient method for biomass monitoring with fast revisit times. However, an elaborate calibration is necessary for the retrieval models, to associate GNSS-R data with bio-geophysical parameters on the ground. To achieve this, further developments with improved training data are required, as well as work using in situ validation data. Nevertheless, using GNSS-R and deep learning retrieval models has the potential to enable fast and persistent biomass monitoring and help us better understand our changing climate. [ABSTRACT FROM AUTHOR]

We investigate the effects of three events with major importance for climate policy on energy sector stocks: the Paris Agreement, the Trump election and presidency, and the Biden election. By combining event studies with impulse‐indicator saturation methods, we show that the Paris Agreement and the election of Mr. Biden benefited renewable industries, while the election of Mr. Trump had negative effects. For fossil fuel industries, the effects were largely the opposite. Despite Trump's efforts to eliminate environmental regulations, his presidency did however witness a decrease in both US coal production and consumption, while natural gas and oil consumption increased. [ABSTRACT FROM AUTHOR]

To align with climate initiatives, multiple reporting programs are transitioning from generic activity-based emission factors to site-specific measured emissions data to estimate greenhouse gas emissions at oil and gas facilities. This study contemporaneously deployed two top-down (TD) aerial methods across 14 midstream facilities, building upon previous research in the field. The methods produced multiple whole-facility estimates at each facility, resulting in 773 individual paired estimates (same facility, same day), and robust mean estimates for each facility. Mean estimates for each facility, aggregated across all facilities, differed by nearly 2:1 (49% [32% to 69%]). At 6 of 14 facilities, the methods produced mean estimates that differed by more than a factor of two. These data suggest that one or both methods did not produce accurate facility-level estimates at a majority of facilities and in aggregate across all facilities. The overall results are augmented with two case studies where TD estimates at two pre-selected facilities were coupled with comprehensive onsite measurements to understand the factors driving the divergence between TD and bottom-up (BU) emissions estimates. In 3 of 4 paired comparisons between the intensive onsite estimates and one of the TD methods, the intensive onsite surveys did not conclusively diagnose the difference in estimates. In these cases, our work suggests that the TD methods mis-estimate emissions an unknown fraction of the time, for unknown reasons. While two methods were selected for this study, it is unlikely that the issues identified here are confined to these two methods; similar issues may exist for other similar whole-facility methods on midstream and/or other facility types. These findings have important implications for the construction of voluntary and regulatory reporting programs that rely on emission estimates for reporting fees or penalties, or for studies using whole-facility estimates to aggregate TD emissions to basin or regional estimates. [ABSTRACT FROM AUTHOR]

The utilization of remote sensing soil moisture products in agricultural and hydrological studies is on the rise. Conducting a regional applicability analysis of these soil moisture products is essential as a preliminary step for their effective utilization. The triple collocation (TC) method enables the estimation of the standard deviation of errors in products when true soil moisture values are unavailable. It assesses data uncertainty and mitigates the influence of product errors on fusion, thereby enhancing product accuracy significantly. In this study, the TC uncertainty error analysis was employed to integrate Soil Moisture Active Passive (SMAP), the Advanced Microwave Scanning Radiometer 2 (AMSR-2), and the European Space Agency Climate Change Initiative (ESA CCI) active (ESA CCI A) and passive (ESA CCI P) products, with ground-based measurements serving as a reference. Traditional evaluation metrics, such as the correlation coefficient (R), bias, root mean square error (RMSE), and unin situed root mean square error (ubRMSE), were employed to evaluate the accuracy of the product. The findings indicate that SMAP and ESA CCI P products demonstrate strong spatiotemporal continuity within the research area and exhibit low uncertainty across various land types. The products derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) exhibit a high level of temporal and spatial continuity; however, there is a requirement for enhancing their accuracy. The products of ESA CCI A exhibit notable spatiotemporal disjunction, contributing significantly to their elevated level of uncertainty. After fusion with TC analysis, the correlation coefficient (R = 0.7) of the TC-2 product derived from the fusion of SMAP, AMSR-2, and ESA CCI P products is significantly higher than the correlation coefficient of the TC-1 product (R = 0.65) obtained from the fusion of SMAP, AMSR-2, and ESA CCI A products at a 95% confidence level. The integration of data can efficiently mitigate the challenges associated with spatiotemporal gaps and inaccuracies in products, offering a dependable foundation for the subsequent utilization of remote sensing products. [ABSTRACT FROM AUTHOR]

Copyright of Comparative Economic Research is the property of Wydawnictwo Uniwersytetu Lodzkiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Viticulture is an example of a socio-ecological system that poses serious challenges for sustainable soil management and pesticide use, with various interactions between winegrowers' decision-making and ecological consequences. This study introduces an agent-based model (ABM) on winegrowers' decision on inter-row management and pesticide use. The ABM builds upon an empirical study of winegrowers' decision-making in European viticultural landscapes and has been built for three case study regions: Leithaberg (Austria), Palatinate (Germany) and Târnave (Romania). The ABM allows for analysing potential effects of policy instruments including mandatory vegetation cover in the inter-rows, the reduction of fungicide use and ban of insecticides against Lobesia botrana. The effects of policies differ between the case study regions, indicating how important the local context is for effective policies. For example, policies aiming at higher inter-row vegetation cover had the strongest effects on vegetation cover, landscape aesthetics and soil loss in Târnave since many vineyards are currently intensively tilled and there exist no policies supporting inter-row vegetation cover in Romania. Highlights: We introduce an agent-based model suite for three European winegrowing regions. The model explores vegetation and pest management and their ecological consequences. The feedback loop between decision-making and ecological processes is closed. Each region is simulated under climate change and various policy instruments. Results show that context is important for effective policies. [ABSTRACT FROM AUTHOR]