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Rapid urbanization and land use/land cover (LULC) changes have become global phenomena, significantly impacting ecosystems and climate, which are key concerns in eco-climatology. Focusing on Riyadh, the rapidly growing capital of Saudi Arabia, this study investigated the spatiotemporal dynamics of ecosystem service values (ESVs) in response to LULC changes using an eco-climatological modeling approach. Support vector machine algorithms were employed on Google Earth Engine to classify Landsat imagery and map LULC in Riyadh for 1993, 2003, 2013, and 2023. ESVs were quantified using global coefficients to assess the impact of LULC changes on the eco-climatological system. Results revealed substantial LULC changes during 1993–2023, with built-up areas expanded by 330.79% (777.76 km²), vegetation by 114.30% (32.14 km²), and waterbody areas by 888.89% (7.20 km²). Conversely, barren soil and cropland areas declined by 9.41% (727.90 km²) and 84.40% (89.14 km²), respectively. These LULC changes led to significant alterations in ESVs, with barren soil and cropland losses resulting in ESV reductions of $591.56 million and $555.91 million, respectively. However, increased vegetated areas contributed to $750.40 million ESV rise. Spatially, western Riyadh experienced the most pronounced ESV declines due to rapid urbanization. Overall, total ESV decreased by $206.37 million over the 30-year, with supporting and cultural service values declining by $174.04 million and $39.91 million, respectively. Provisioning and regulating services increased by $3.58 million and $4.02 million. The eco-climatological modeling approach effectively captured the complex interactions between LULC dynamics, ecosystems, and ESVs in this arid environment, highlighting the need for sustainable land management strategies that balance urban growth, ecosystem preservation, and climate change adaptation and mitigation. This study contributes to eco-climatology by demonstrating advanced modeling techniques for assessing spatiotemporal ESV dynamics in response to LULC changes, informing future research and policy in rapidly urbanizing regions. [ABSTRACT FROM AUTHOR]

Purpose: The choice of characterization model has the potential to profoundly influence LCA results and conclusions. It is therefore a requirement of ISO 14044:2006 that the selection of characterization model shall be both justified and consistent with goal and scope. The purpose of this article was to examine current practices regarding the characterization of GHG emissions and reporting as CO2 equivalent emissions. Methods: A survey of practice was conducted across articles recently published in the International Journal of Life Cycle Assessment. Each article was examined using seven predetermined questions covering reporting of CO2 equivalent emissions and justification of climate metric used, interpretation of results in relation to climate measures or goals, and the implications of choosing an alternative climate metric. Results and discussion: Of the sample of 85 articles, more than half reported GHG emissions as CO2 equivalent emissions. Of these, 81% unambiguously reported the climate metric used. Most often, there was no justification for the choice of a characterization model. Where a justification was given, the most common reason was alignment with the requirements of a program or PCR document. In some cases, the choice of characterization model was determined by the choice of impact assessment method (e.g., CML, ReCiPe). In other cases, the choice of characterization model was based on the desire to compare results to other studies. It is noted that none of the abovementioned reasons is scientific justification related to a stated climate objective. Not surprisingly, most studies made no attempt to interpret results reported as CO2 equivalent emissions in relation to climate measures or goals, and most did not discuss the potential implications of alternative climate metrics. For almost half of the articles, the choice of climate metric was assessed as potentially having major implications for decision-making or comparison to alternative systems. Conclusions: Based on this survey, it is evident that key aspects of ISO 14044:2006 are routinely not being followed. When GHG emissions are aggregated into a single impact category indicator result, there is a loss of transparency about climate impacts over time and the potential to unknowingly trade short-term climate benefits against the exacerbation of the difficulties of achieving long-term climate stabilization. As such, whenever GHG emissions are reported as CO2 equivalent emissions, it is imperative that the choice of characterization model is unambiguously reported and justified, that results are interpreted in relation to environmental outcomes, and that the potential implications of selecting alternative models are discussed. [ABSTRACT FROM AUTHOR]

Food production is known to have significant environmental impacts, with the main contributors residing in the farming and transportation life cycle phases. Of the various food products transported around the world, avocados have increasingly gained attention as a high-commodity superfood. Avocados require specific climatic and agricultural conditions for farming, with the most fertile land and conditions located outside Europe. Consequently, most avocados consumed in Europe are imported over vast geographical distances, with little information available to quantify the environmental impacts of this imported superfood. This paper aims to present the most detailed life cycle assessment results of an avocado cultivated, grown and harvested in the Limpopo Province of South Africa and exported to the European market for sale and consumption. A life cycle assessment was developed for the farming, harvesting, handling, packaging, ripening, transportation, and carbon sequestration potential of the avocado, and it was used to conduct a holistic life cycle assessment. Input data was obtained through an 18-month data collection campaign across the relevant stakeholders. A baseline 'business-as-usual' scenario is focused on throughout this study, and scope for optimisation is identified for each life cycle phase where applicable, accompanied by uncertainty analyses. Results show a total carbon input of 904.85 kg CO2e/tonne. Mitigating this, 521.88 kg CO2e/tonne is offset, resulting in a net carbon footprint of 382.97 kg CO2e/tonne with uncertainty ranges of −23.22 to +58.69 kg CO2e/tonne, normalised to 57.45 g CO2e/avocado grown in South Africa and sold in Europe. The environmental impacts of the avocado industry under consideration are largely mitigated by the "nature first" philosophy of the farming and logistics enterprises, which have made significant investments in reducing emissions. Sensitivity analyses indicate that implementing large-scale renewable energy, using alternative packaging instead of cardboard, and selling avocados unripened could further enable the farming enterprise to achieve Net Zero objectives. These measures could reduce baseline emissions from 382.97 kg CO2e/tonne to a theoretical −68.54 kg CO2e/tonne, representing a 117.9% decrease. Although this study does not quantify climate change impacts, qualitative analyses suggest that climate change will have a net negative effect on the avocado industry in South Africa. These regions, typically located in micro-climates, are projected to become wetter and warmer, adversely affecting crop phenology, pest control, road conditions, management complexity, farmer livelihoods, and food security. The study recommends large-scale implementation of the optimisation strategies identified to achieve Net Zero objectives and the development of proactive climate change mitigation strategies to enhance the resilience of avocado supply chains to future stressors. These insights are crucial for policymakers, industry stakeholders, and consumers aiming to promote sustainability in the avocado market. [ABSTRACT FROM AUTHOR]

The role of universities in addressing climate change is often discussed, but one crucial aspect tends to be overlooked: their potential contribution to carbon sequestration. Many universities around the world possess significant tracts of land, often featuring substantial forested areas. These landscapes represent an underutilised opportunity for nature-based solutions that facilitate carbon sequestration. This paper discusses the current trends and status of university-owned forests, highlighting some of the largest and most ecologically significant forests managed by academic institutions across different regions worldwide. It explores their capacity for carbon sequestration, their biodiversity value, and the potential they hold for contributing to global climate change mitigation efforts. Furthermore, the article examines how these university forests can serve as dynamic, living laboratories for research, education, and conservation, as well as spaces for community engagement. In addition to their environmental benefits, these green spaces can enhance human health and well-being. Based on this analysis, the paper offers recommendations for universities on how to optimise their forested lands as carbon sinks and enhance their role in advancing sustainable practices, research, and education. Article Highlights: Presents an agenda-setting synthesis on measures universities can deploy to enhance their forested landscapes as carbon sinks and in situ living labs for research and education. Illustrates the manifold benefits of university forests through twelve case studies spanning five continents. Demonstrates how university forests may be harnessed for conservation, health, and well-being. Spotlights an under-recognised area in higher education, presenting opportunities for universities that may inspire similar initiatives beyond the featured cases. [ABSTRACT FROM AUTHOR]

Does prompting people to volunteer for the climate spur or hamper further environmental engagement? We address this question in an online experiment with 10,670 German respondents. First, respondents read a text explaining how to help scientists fight climate change. Second, participants choose whether to do a real-effort task, like the behavior emphasized in the text. Third, respondents can sign a petition against climate change. In Study 1, we manipulate the narrative of the texts. We compare narratives condemning inaction or praising climate action against a neutral narrative (control) and an unrelated article (placebo). In Study 2, we investigate how the difficulty of the first behavior moderates behavioral spillovers. In Study 3, we test if the similarity between the domains of the two behaviors (e.g., environment, health) moderates spillover effects. None of our narratives increase the uptake of the real-effort task. Doing the real-effort task does not increase the likelihood of signing the petition either. Difficulty and domain-similarity do not moderate these effects. Protocol registration The stage 1 protocol for this Registered Report was accepted in principle on January 1, 2023. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/JPT8G. [ABSTRACT FROM AUTHOR]

Achieving net-zero climate targets requires some level of carbon dioxide removal. Current assessments focus on tonnes of CO2 removed, without specifying what form these removals will take. Here, we show that countries' climate pledges require approximately 1 (0.9–1.1) billion ha of land for removals. For over 40% of this area, the pledges envisage the conversion of existing land uses to forests, while the remaining area restores existing ecosystems and land uses. We analyse how this demand for land is distributed geographically and over time. The results are concerning, both in terms of the aggregate area of land, but also the rate and extent of land use change. Our findings demonstrate a gap between governments' expected reliance on land and the role that land can realistically play in climate mitigation. This adds another layer to the observed shortcomings of national climate pledges and indicates a need for more transparency around the role of land in national climate mitigation plans. Achieving net-zero climate targets requires substantial land for carbon dioxide removal. This paper quantifies the land area in countries' climate pledges at approximately 1 billion hectares, often involving the conversion of existing land uses to forests. [ABSTRACT FROM AUTHOR]

Background: Understanding the drivers of variations in carbon stocks is essential for developing the effective management strategies that contribute to mitigating climate change. Although a positive relationship between biodiversity and the aboveground carbon (AGC) has been widely reported for various Brazilian forest types, representing a win–win scenario for climate change mitigation, this association has not been commonly found in Brazilian subtropical forests. Therefore, in the present study, we aimed to evaluate the effects of Araucaria angustifolia, stand structure and species diversity in shaping AGC stocks in Brazilian subtropical mixed forest. We hypothesized that the effects on the AGC of stand structure and diversity would be mediated by A. angustifolia. We also evaluated the expectation of higher carbon stocks in protected forest as a result of their positive correlation with biodiversity conservation. Results: We found that stand structure, followed by A. angustifolia, played the most important role in shaping the AGC stock. Our hypothesis was partially confirmed, the indirect effects of A. angustifolia on stand structure being found to have shaped the AGC. Similarly, our expectation was partially supported, with the higher AGC in the protected area being related not to diversity, but rather to the presence of larger trees, denser stands, and a greater abundance of A. angustifolia. Conclusion: Although the win–win strategy between diversity conservation and carbon storage is not a peculiarity of Araucaria forests, we highlight the potential of these forests as a nature-based climate solution, maintaining high levels of carbon storage in harmony with the provision of keystone socio-economic resources. [ABSTRACT FROM AUTHOR]

Climate action requires differentiated mitigation and adaptation strategies tailored to the national circumstances of countries worldwide. The first global stocktake (GST) and the nationally determined contributions (NDCs) submitted by parties to the Paris Agreement (PA) have clarified the pathways for global climate action. These submissions indicate that building the capacity of developing countries, as stated in Article 11, is a prerequisite for conducting assessments related to climate finance under Article 9 and technology development and transfer under Article 10 of the PA. This suggests that the approach to carbon reduction in developing countries differs from that in developed countries. Developed countries need to implement immediate mitigation actions while supporting developing countries in avoiding a carbon-intensive development path as they advance their less-developed sectors. Although global climate actors have significantly focused on climate finance and technology transfer, efforts to build the capacity of developing countries to access these resources have been inadequate. Therefore, capacity building in developing countries is essential for collective progress toward achieving the PA goal. The upcoming Conference of the Parties (COP29) should prioritize a capacity-building framework to strengthen the global response to climate change. [ABSTRACT FROM AUTHOR]

Forest ecosystems play a crucial role in regulating greenhouse gas (GHG) emissions and mitigating climate change. This research aimed to evaluate the GHG emissions of various sources within forested ecosystems and assess their respective contributions to global warming potential (GWP), vital for developing more targeted strategies to mitigate climate change, shaping climate policies, carbon accounting, sustainable forest management, and advancing scientific comprehension of ecosystem-climate dynamics. The study comprehensively analysed carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions EDGAR data of deforestation, fires, and natural processes such as organic soil decomposition within forested ecosystems. The assessment quantified the CO2 equivalent emissions for each category from 1990 to 2022 and forecasted till 2030. Our forecast shows that CO2 emissions from deforestation could reach between 3,990 and 4,529 metric ton (Mt) by 2030, with forest fires contributing an additional 750 Mt. Forestland CO2 absorption is expected to decline to -5134.80 Mt by 2030. There is uncertainty surrounding the forecasts for Organic soil CO2 (829.78 Mt) and Other land CO2 (-764.53 Mt). In addition, deforestation was a significant contributor to CO2 emissions, with a GWP ranging from 4000 to 4500, highlighting the complex interplay between natural processes and human activities in shaping atmospheric warming patterns. Additionally, forest fires emit a complex mix of GHGs. The potency of these gases in warming the planet varies considerably, with CH4 exhibiting a GWP range of 500 to 700 Mt CO2 equivalent, and CO2 ranging from 900 and 1350 Mt. These variations depend on fire intensity and its overall impact on the climate system. Forestland acts as powerful carbon sink, capturing atmospheric CO2 with negative GWP values between -7000 and -6000. Researchers suggest a multifaceted strategy such as stricter enforcement of sustainable forestry regulations, investing in projects that promote carbon sequestration, and reforestation. Additionally, advancements in drone technology, satellite imagery, remote sensing and advanced data analytics can aid in detecting and mitigating climate change impacts, ultimately paving the way for carbon neutrality. Highlights: • Deforestation exacerbates CO2 emissions, with the additional threat of fires compounding the issue. • Forest CO2 sink weakens to -5,135 Mt by 2030. Soil stores 829.78 Mt, and Other land -764.53 Mt. • Deforestation's GWP (4,000–4,500 Mt) shows complex human and nature impact on CO2. • Varying fire emissions (methane 550–650t, CO2 900–1,350t) highlight need for sustainable land use. [ABSTRACT FROM AUTHOR]

The mental health impacts of climate change are increasingly documented; however, less research has investigated the relationship between climate change-related psychological distress and engagement with the issue. The results from two national probability samples of U.S. adults show that 16% report at least one feature of climate change psychological distress and that certain groups have higher levels of distress than others (e.g., Hispanic/Latinos, lower income adults, younger adults). Importantly, people experiencing distress are more likely to engage in collective action on climate change or express a willingness to do so, even when controlling for several correlates of environmental behavior (e.g., political ideology, collective efficacy beliefs). These findings highlight that many Americans are experiencing psychological distress from climate change, and those who do are more involved in collective climate action. People experiencing such distress may benefit from resources to support mental health and engagement with climate change. [ABSTRACT FROM AUTHOR]

'People' are central both to populism, an ideology in which 'people' are pitted against corrupt elites, and to climate science and policy, which advocate 'people-centred' climate action. Our Brief Communication explores references to climate change and 'people' on Twitter (now X). Populist tropes (the people against corrupt elites) were not restricted to climate-sceptical tweets; they extended to tweets that recognised climate change was real but expressed mistrust about climate actions. [ABSTRACT FROM AUTHOR]

Climate change can evoke intergenerational conflict. Structural inequalities and their unequal impact on generations can increase perceptions of collective victimhood among the younger generation (< 30 years) and bear the risk of social tensions between the young and the elderly. An experimental study (N = 434) showed that younger people perceived an increased risk of future victimhood. In line with a needs-based approach, the young reported an increased desire to pursue agentic intergroup goals, indicating a heightened need for agency. However, when the young received empowering messages that affirmed their ingroup agency, their willingness to reconcile with the old generation increased, whereas informing them about non-agentic ingroup behavior did not affect reconciliation (between-subjects manipulation). While empowering messages from the outgroup ("Grannies for Future") that directly affirmed the young generations' agency for climate change mitigation as well as empowering messages from the ingroup that indirectly affirmed ingroup agency in domains unrelated to climate change both addressed the need for agency, only outgroup empowerment promoted intergenerational reconciliation. However, empowerment did not affect support for collective climate action. We discuss empowerment as an avenue for resolving intergroup conflict in the context of climate change and possible consequences for climate action and social change. [ABSTRACT FROM AUTHOR]

In this review, we discuss current research on forest carbon risk from natural disturbance under climate change for the United States, with emphasis on advancements in analytical mapping and modeling tools that have potential to drive research for managing future long-term stability of forest carbon. As a natural mechanism for carbon storage, forests are a critical component of meeting climate mitigation strategies designed to combat anthropogenic emissions. Forests consist of long-lived organisms (trees) that can store carbon for centuries or more. However, trees have finite lifespans, and disturbances such as wildfire, insect and disease outbreaks, and drought can hasten tree mortality or reduce tree growth, thereby slowing carbon sequestration, driving carbon emissions, and reducing forest carbon storage in stable pools, particularly the live and standing dead portions that are counted in many carbon offset programs. Many forests have natural disturbance regimes, but climate change and human activities disrupt the frequency and severity of disturbances in ways that are likely to have consequences for the long-term stability of forest carbon. To minimize negative effects and maximize resilience of forest carbon, disturbance risks must be accounted for in carbon offset protocols, carbon management practices, and carbon mapping and modeling techniques. This requires detailed mapping and modeling of the quantities and distribution of forest carbon across the United States and hopefully one day globally; the frequency, severity, and timing of disturbances; the mechanisms by which disturbances affect carbon storage; and how climate change may alter each of these elements. Several tools (e.g. fire spread models, imputed forest inventory models, and forest growth simulators) exist to address one or more of the aforementioned items and can help inform management strategies that reduce forest carbon risk, maintain long-term stability of forest carbon, and further explore challenges, uncertainties, and opportunities for evaluating the continued potential of, and threats to, forests as viable mechanisms for forest carbon storage, including carbon offsets. A growing collective body of research and technological improvements have advanced the science, but we highlight and discuss key limitations, uncertainties, and gaps that remain. [ABSTRACT FROM AUTHOR]

To guide climate change mitigation efforts, we identify and characterize the different types of mitigation strategies countries adopted over the last two decades. The analysis exploits the novel and rich policy repository of the OECD's Climate Actions and Policies Measurement Framework (CAPMF), covering more than 120 policy variables and 50 countries over 2000–2020. All countries in the dataset increased the number of climate policy instruments and their stringency over the past two decades, but at a different pace and using different policy instruments. Using statistical cluster analysis, we identify four distinct types of mitigation strategies, which differ in the composition and stringency of mitigation policies. Regression results show that emissions are negatively associated with the overall stringency of the country's mitigation strategies. Evidence also supports the hypothesis that this relationship is stronger for mitigation strategies comprising a more diverse set of instruments, pointing to possible policy synergies. [ABSTRACT FROM AUTHOR]

Background: Renewable energy and climate change are vital aspects of humanity. Energy is needed to sustain life on Earth. The exploration and utilisation of traditional fossil-based energy has led to global warming. The exploration and use of fossil-based energy have significantly contributed to global warming, making the shift to renewable energy crucial for mitigating climate change. Renewable energies offer a sustainable alternative that does not harm the environment. This review aims to examine the role of machine learning (ML) in optimising renewable energy systems and enhancing climate change mitigation strategies, addressing both opportunities and challenges in this evolving field. The vital significance of renewable energy and measures to circumvent climate change in modern civilisation is first contextualised in the review. It draws attention to the difficulties encountered in these fields and describes the exciting potential of ML to solve them. Important discoveries highlight how ML can improve renewable energy technology scalability, dependability and efficiency while enabling more precise climate change projections and practical mitigation strategies. Simultaneously, issues including ethical considerations, interpretability of models and data quality demand attention. Method: This review conducted a systematic literature analysis on the application of ML in renewable energy and climate change mitigation. It involved a comprehensive search, selection, and analysis of recent studies, focusing on ML's role in energy forecasting, predictive maintenance, and climate modelling. The review synthesised key developments, challenges, and future directions, emphasising the need for ongoing transdisciplinary research to fully realise ML's potential in advancing sustainable energy solutions. Result: The review found that machine learning significantly enhances renewable energy system efficiency, scalability, and climate change mitigation through improved forecasting, predictive maintenance, and climate modelling. However, challenges like ethical concerns, model interpretability, and data quality persist. Ongoing research is essential to fully leverage ML's potential in these areas. Short conclusion: The paper highlights how machine learning can be used to revolutionise the energy and climate change mitigation industries for sustainable futures. It promotes ongoing transdisciplinary research and innovation to fully realise ML's synergistic potential and tackle urgent global issues. In the end, the review advances our knowledge of how to use ML to hasten the transition to a future that is more robust and sustainable. [ABSTRACT FROM AUTHOR]

Biochar application to soil is a potential climate change mitigation strategy. In addition to long-term sequestration of the carbon content of the biochar itself, its application may reduce the emissions of other greenhouse gases (GHGs) from the soil. However, the reported effects of biochar application on soil GHG fluxes exhibit inconsistent results. Prediction of such effects is an important gap that needs to be addressed in biochar research. In this study, rule-based machine learning models were developed based on rough-set theory. Data from the literature were used to generate the rules for predicting the effects of biochar application on soil GHG (CO2, N2O, and CH4) fluxes. Four rule-based models for CO2 fluxes, two rule-based models for N2O fluxes, and three rule-based models for CH4 fluxes were developed. The validity of these models was assessed based on both statistical measures and mechanistic plausibility. The final rule-based models can guide the prediction of changes in soil GHG fluxes due to biochar application, and thus serve as a decision-support tool to maximize the benefits of biochar application as a negative emission technology (NET). In particular, mechanistically plausible rules were identified that predict triggers for GHG fluxes that can offset carbon sequestration gains. This knowledge allows biochar application to be calibrated to local conditions for maximum efficacy. Highlights: • Biochar interaction with soil affects net CO2 removal. • Rough set-based machine learning was used to find patterns in biochar literature data. • Rule-based models for CO2, N2O, and CH4 fluxes were developed. • The final rule-based models show both good statistical performance and mechanistic plausibility. [ABSTRACT FROM AUTHOR]

While democratic societies experience intense conflicts about topics such as migration and climate action, there is no sound theory of democratic conflict. Agonistic theories emphasize the importance of conflict for democracy, but disregard conflict dynamics. Conflict sociology has focused on international or violent conflicts and neglects democratic conflicts. This article shows how this lacuna can be overcome. First, it develops an innovative, empirically informed processual approach to democratic conflicts. To this end, it draws on a broad range of scholarship from sociology and social psychology, and integrates relevant insights into a processual framework for analyzing democratic conflicts that explores mechanisms of escalation, de-escalation, and reconciliation. Second, the article illustrates how this approach can ground a more elaborated democratic theory of conflict that concretizes how and when conflicts are beneficial to democracy, and explores the practices and institutions that democracies employ to cope with different conflict dynamics. [ABSTRACT FROM AUTHOR]

Seaweed cultivation, including kelp species, is rapidly expanding in many regions. A widely assumed co-benefit of seaweed farming is increased local carbon sequestration rates (thereby contributing to climate change mitigation), although direct field-based measurements of carbon assimilation and release are largely lacking. We quantified growth, erosion and dislodgement rates of farmed Saccharina latissima in Porthallow Bay (Cornwall, UK) throughout a typical cultivation season to provide insights into the carbon sequestration potential of small-scale kelp farms. Blade elongation rates increased from ~ 1.3 cm day−1 to ~ 2.3 cm day−1 in March–April, before declining to 1.4 cm day−1 by May. Meanwhile, erosion rates remained low, ranging from ~ 0.5 to ~ 0.8 cm day−1. Dislodgement rates decreased from 20% of plants in January–February to 5% in April–May. Rates of carbon accumulation and loss increased from January to May, related to an increase in standing stock. Conservative first-order estimates suggest that the farm captures 0.14 t C ha−1 y−1, of which up to 70% is released into the environment as particulate organic carbon. Based on previous estimates of carbon burial and storage rates, the farm may sequester 0.05 t CO2e ha−1 y−1. These values suggest that scaling-up European kelp farming should be motivated by other co-benefits, such as low-carbon product alternatives, job creation and potential biodiversity gains, and not be solely driven by a perceived meaningful increase in carbon sequestration. Importantly, further information needs to be obtained from a variety of cultivation sites to develop a better understanding of carbon dynamics associated with kelp farms. [ABSTRACT FROM AUTHOR]

Most people in rural sub-Saharan Africa lack access to electricity and rely on traditional, inefficient, and polluting cooking solutions that have adverse impacts on both human health and the environment. Here, we propose a novel integrated agroforestry-bioenergy system that combines sustainable biomass production in sequential agroforestry systems with biomass-based cleaner cooking solutions and rural electricity production in small-scale combined heat and power plants and estimate the biophysical system outcomes. Despite conservative assumptions, we demonstrate that on-farm biomass production can cover the household's fuelwood demand for cooking and still generate a surplus of woody biomass for electricity production via gasification. Agroforestry and biochar soil amendments should increase agricultural productivity and food security. In addition to enhanced energy security, the proposed system should also contribute to improving cooking conditions and health, enhancing soil fertility and food security, climate change mitigation, gender equality, and rural poverty reduction. [ABSTRACT FROM AUTHOR]

Sustainable livestock management plays a crucial role in food production, climate change mitigation, and cultural preservation. Our study aimed to identify and analyse the diversity of social–ecological conditions that characterize extensive livestock systems in southern Patagonia. We integrated data collected from interviews and secondary sources and analysed data using hierarchical cluster analysis and non-metric multidimensional scaling to identify distinct ranching types. A qualitative analysis of key informant interviews identified key social–ecological changes for each type. The results emphasize the impact of administration, production, and biophysical factors on shaping different livestock ranching schemes. Further, we identified three significant social–ecological changes driving the dynamics of these systems, including shifts from (1) sheep to cattle ranching, (2) domestic to feral cattle ranching, and (3) landowners to tenant land managers. These findings have implications for policymakers seeking to develop strategies tailored to diverse realities, ensuring the sustainability of livestock systems in Tierra del Fuego. [ABSTRACT FROM AUTHOR]

Although accelerated urbanization has led to economic prosperity, it has also resulted in urban heat island effects. Therefore, identifying methods of using limited urban spaces to alleviate heat islands has become an urgent issue. In this study, we assessed the spatiotemporal evolution of urban heat islands within the central urban area of Fuzhou City, China from 2010 to 2019. This assessment was based on a morphological spatial pattern analysis (MSPA) model and an urban thermal environment spatial network constructed using the minimum cumulative resistance (MCR) model. Optimization measures for the spatial network were proposed to provide a theoretical basis for alleviating urban heat islands. The results show that the heat island area within the study area gradually increased while that of urban cold island area gradually decreased. The core area was the largest of the urban heat island patch landscape elements with a significant impact on other landscape elements, and represented an important factor underlying urban heat island network stability. The thermal environment network revealed a total of 197 thermal environment corridors and 93 heat island sources. These locations were then optimized according to the current land use, which maximized the potential of 1599.83 ha. Optimization based on current land use led to an increase in climate resilience, with effective measures showing reduction in thermal environment spatial network structure and function, contributing to the mitigation of urban heat island. These findings support the use of current land use patterns during urban heat island mitigation measure planning, thus providing an important reference basis for alleviating urban heat island effects. [ABSTRACT FROM AUTHOR]

The two main goals of peatland restoration are habitat improvement and climate change mitigation by reducing greenhouse gas emissions from damaged peatlands and providing a net carbon sink. The biodiversity of specialist peatland species is threatened because of habitat destruction and the large heath butterfly Coenonympha tullia has become a flagship species for peatland ecosystem restoration, with a species reintroduction programme currently underway on a peatland restoration site within Chat Moss, Greater Manchester, UK. The aim of this study was to improve our quantitative understanding of C. tullia habitat resource requirements to optimise habitat restoration for further reintroduction attempts. We monitored butterfly micro-distribution and dispersal during the first three flight seasons (2020, 2021 and 2022) of the reintroduction using high-accuracy GPS, combined with a distance-bearing protocol. Analysis of butterfly flight points and rest points in relation to plant species distribution and abundance, identified the most important habitat resources. Using logistic regression, treatment-response curves were constructed, enabling us to identify critical thresholds for the abundance of these important habitat resources. The break of slope near the top of the logistic curve was identified using segmented regression, giving an estimate of the near-optimal abundance; fourteen Eriophorum vaginatum tussocks per 2 m quadrat and 13.4% Erica tetralix cover. Implications for insect conservation: During ecosystem restorations, prior to the reintroduction of species with specialist habitat requirements, it is necessary to have a clear understanding of the abundance of the important habitat resources that need to be provided. The quantitative approach we describe defines the most significant environmental factors and habitat resources, then uses segmented regression to estimate the near-optimal habitat resource requirements; increasing the likelihood of reintroduced populations thriving and reintroduction programmes achieving long-term success. [ABSTRACT FROM AUTHOR]

This paper examines whether or not public support for climate change mitigation policy can be affected by salient events such as natural disasters. We test this hypothesis using detailed, county-level data from the 2018 Yale Climate Opinion Maps, which documents both the degree to which residents of a county support climate change policy. We show that while natural disasters lead to statistically significant increases in both the share of a county's population that support climate change mitigation policy and/or believe that climate change is happening, the magnitude of these estimated effects are economically small and perhaps not robust to hidden bias. As a result, and even assuming our results are in fact causal, the magnitude of our findings suggest that support as a policy objective by targeting agent's beliefs about the risks climate change poses may ultimately be an ineffectual approach at achieving policymakers' goals. [ABSTRACT FROM AUTHOR]

Climate change mitigation is a pressing global challenge that requires reducing CO2 emissions without hindering economic growth. Using an extended Kaya identity, Logarithmic Mean Divisia Index (LMDI), and Tapio decoupling indicator, this paper investigates the spatio-temporal variations, drivers, and decoupling of CO2 emissions from economic growth in 150 countries from 1990 to 2019, considering regional disparities and income-based inequalities. The findings reveal increasing CO2 emissions between 1990 and 2019, with notable fluctuations in certain 5-year intervals. CO2 emission growth varied significantly by region, with countries like China, the USA, India, and Japan experiencing rapid increases. Economic growth emerged as the primary driver of CO2 emission growth, and its impact strengthened over time. Population growth also contributed significantly to CO2 emissions, particularly in middle- and low-income countries. The study identifies energy and carbon intensity as crucial mitigating factors that weaken CO2 emissions, offering hope for effective climate change mitigation. Furthermore, the degree of decoupling between economic growth and CO2 emissions varied among countries in the same region, with high-income countries demonstrating stronger decoupling compared to upper-middle-income countries, which accounted for 71% of global CO2 emission increase. These findings underline the imperative of accounting for income levels and regional differences in formulating CO2 emission mitigation strategies. Also, the study emphasizes the pressing necessity for cohesive global coordination to facilitate the transition toward a low-carbon economy. Such collaborative endeavors are paramount in our collective pursuit to combat climate change effectively, safeguarding the well-being and sustenance of our planet for future generations. As policymakers, it is imperative to integrate these insights into decision-making processes to chart a sustainable and resilient course forward. [ABSTRACT FROM AUTHOR]

Climate change is currently one of humanity's greatest threats. To help scholars understand the psychology of climate change, we conducted an online quasi-experimental survey on 59,508 participants from 63 countries (collected between July 2022 and July 2023). In a between-subjects design, we tested 11 interventions designed to promote climate change mitigation across four outcomes: climate change belief, support for climate policies, willingness to share information on social media, and performance on an effortful pro-environmental behavioural task. Participants also reported their demographic information (e.g., age, gender) and several other independent variables (e.g., political orientation, perceptions about the scientific consensus). In the no-intervention control group, we also measured important additional variables, such as environmentalist identity and trust in climate science. We report the collaboration procedure, study design, raw and cleaned data, all survey materials, relevant analysis scripts, and data visualisations. This dataset can be used to further the understanding of psychological, demographic, and national-level factors related to individual-level climate action and how these differ across countries. [ABSTRACT FROM AUTHOR]

This study explores the impact of environmental policies on trade and innovation, utilizing an expanded dataset sourced from the WTO Environmental Database (EDB). It makes two contributions to the literature: First, employing advanced text analysis algorithms, we extracted valuable information from the EDB, enhancing its usefulness for future research and policy analysis. Second, we leverage this augmented dataset to evaluate the impact of environmental measures on trade and green innovation. Our empirical findings suggest that environmental policies not only elevate demand for environmental goods and stimulate imports but also bolster competitiveness and amplify exports of environmental goods. Additionally, these policies appear to stimulate green innovation. [ABSTRACT FROM AUTHOR]

In this research, we document knowledge gaps between consumers and experts about what consumer actions most effectively help mitigate climate change. We then identify three sources for lack of consumer knowledge on greenhouse gas emissions associated with consumption: carbon emissions labeling, awareness of indirect versus direct emissions, and orders of magnitude differences in carbon intensity across behaviors. We further propose that this lack of knowledge and several cognitive and motivational biases lead consumers away from effective climate actions, including the tendency to focus on first- versus second-order effects of "green" behaviors, motivated reasoning that easier, more accessible actions are more impactful, and a focus on individual behavior versus systemic changes. We close with a research agenda designed to address the lack of knowledge and biases we identify, while acknowledging that shifting marketers and consumers to focus on systemic changes may be both most challenging and most impactful. [ABSTRACT FROM AUTHOR]

Compliance with green requirements is becoming increasingly important in assessing the performance of companies. The new CSRD legislation requires a wider range of companies to produce sustainability reports and their content is influenced by the EU's taxonomy regulation setting out the framework for sustainable finance. The disclosure of information affects the perception of companies' sustainability performance, which will affect their access to financial resources and development opportunities. The main question is, both in theory and in practice, how companies can comply with the legislation in the future. It is essential for the competitiveness of Hungary's food industry to keep pace with future environmental sustainability requirements, so we examined the sustainability reporting practices of the sector's key companies in terms of their contribution to the environmental objectives set out in the taxonomy regulation. The research fits well with the EU's overall green transition regulatory procedure and our study is gap-filling at macro-regional and sectoral levels. The sustainability reports were assessed by content analysis using a scoring method. The results show that the sustainability reporting practices of food processing companies in Hungary differ significantly. Furthermore, greater emphasis must be placed on reporting and the credibility of the reports to meet future expectations. Foreign-owned companies and companies with more than 500 employees attribute greater importance to reporting. In the food processing sector, the disclosure of information and data under the taxonomy objectives of mitigation of climate change, sustainable use of water and marine resources, and transition to a circular economy was most common. [ABSTRACT FROM AUTHOR]

Urgent climate action, especially carbon emissions reduction, is required to achieve sustainable goals. Therefore, understanding the drivers of and predicting emissions is a compelling matter. We present two global modeling frameworks—a multivariate regression and a Random Forest Regressor (RFR)—to hindcast (until 2021) and forecast (up to 2035) emissions across 117 countries as driven by 12 socioeconomic indicators regarding carbon emissions, economic well-being, green and complexity economics, energy use and consumption. Our results identify key driving features to explain emissions pathways, where beyond-GDP indicators rooted in the Economic Complexity field emerge. Considering current countries' development status, divergent emission dynamics appear. According to the RFR, a −6.2% reduction is predicted for developed economies by 2035 and a +19% increase for developing ones (referring to 2020), thus stressing the need to promote green growth and sustainable development in low-capacity contexts. [ABSTRACT FROM AUTHOR]

Science should drive policies and regulations to ensure a sustainable (environmentally, socially, and economically) green transition to a Net-Zero / Net-Negative circular economy. Since 2015, which saw COP21 in Paris, Net Zero has been a global target that must be rapidly accompanied by a Net Negative strategy to mitigate climate change. Accordingly, biochar's role as a durable carbon removal method is gaining attention and increasing. In this work, we discuss the durability of the carbon in biochar and the need for analytical techniques to support stakeholders on a project level. The different ecologically relevant groups of carbon forms contained in biochar are presented, and possible project-based methods to assess the quality and durability of the product versus the regulatory requirements for the permanence of carbon removals are summarized. Biochar is today one of the CDR technologies with the highest technology readiness level (TRL 8–9) that can ensure permanent removals for time frames relevant to climate change mitigation projects, combined with co-benefits that are gaining relevance in terms of mitigating climate impacts in agricultural soils. Biochar comprises different carbon forms, for which permanence is discussed here. Biochar can deliver cost-effective long-term Carbon Dioxide Removal (CDR), which is possible to deploy at large scale. Project-level Biochar Carbon Removal (BCR) can be verified by analytical techniques and third-party certification. Certified BCR can be accounted towards nation-wide climate targets. Site-specific co-benefits can be generated, supporting the shift to more sustainable and climate-resilient agriculture [ABSTRACT FROM AUTHOR]

A series of energy-econometrics techniques were employed for a 5-year time span between 2016 and 2020. The tests of Environmental Kuznets Curve (EKC) hypothesis were conducted essentially to examine the significance of economic growth (GDP), energy consumption (EC), with energy intensity (EI), and on-road passenger vehicles (PV) as related to economic development on the mitigation of carbon emissions (CO2-eq) in the transportation industry of South Africa. The findings from the prevailing research imply that, with respect to South Africa's transportation industry, CO2-eq emissions increased in the course of early phases of economic growth while it tends to decline at certain levels of economic threshold. Though the nation maintains the edge of turning points in both the industrial and circular economy. The results further indicate a nexus between GDP and EC, which consequently affect the CO2-eq emissions. The findings proffer the needs to monitor the EC from the long-run impacts alongside the short run impacts of the forecast. The per capita GDP from the short-run impacts of t-stat—(4.928) to the long run effects of t-stat—(5.033) rises, indicating its improper influence in the industry. To limit the use of fossil-based fuels, as demonstrated in the negative signal of EI for long-run impacts of a p-value (0.2835), then to the short run effects which possess a significant p-value. It also highlights the directional correlation surfacing between EC, EI and South Africa's on-road PV. In the computation context, the series was determined to be stationary at its first differences, as evident by the R2 combined with the R2 (Adjusted) values of 0.9837 and 0.9827, respectively, for both long-run and short-run assessments. The indication of the research among others further reveals that public transportation systems of road and rail options, which have the potentials to incorporate alternative energy sources, can be the required efforts to mitigate climate change and global warming effects in the transportation industry. [ABSTRACT FROM AUTHOR]

Background: Understanding the complex relationship between vegetation dynamics and land surface temperature (LST) is crucial for comprehending ecosystem functioning, climate change impacts, and sustainable land management. Hence, this study conducts a temporal analysis of leaf area index (LAI) and LST data derived from Sentinel-2 and Landsat Operational Land Imagery (OLI) in the Mille River Basin, a tropical region in Ethiopia. LAI data were generated using Sentinel-2 imagery processed with the Sentinel Application Platform (SNAP) toolbox, an open-access earth observation analysis tool, while Landsat OLI collection 2 level 2 data were utilized for precise LST retrieval. The Mann–Kendall test was used to detect trends in the time series data. Results: The trends in the mean LAI were statistically significant at P values of 0.05 and 0.10 for the annual and seasonal trends, respectively. The mean LST trends were insignificant throughout the study period except for the summer season, for which the P value was 0.07. The correlation between the LAI and LST was weak (R2 = 0.36) during the crop-growing seasons (summer and spring) but moderate in winter (R2 = 0.46) and autumn (R2 = 0.41). Conclusion: The findings of this research clarify the complex relationships between variations in surface temperature and vegetation growth patterns, providing insight into the environmental mechanisms driving the dynamics of localized ecosystems. The study underscores the implications of these findings for informed decision-making in sustainable land management, biodiversity conservation, and climate change mitigation strategies. [ABSTRACT FROM AUTHOR]

Biochar, produced from the thermochemical conversion of biomass waste, has various applications owing to its broad utility and advantageous properties. This study employs a scientometric approach to comprehensively assess the advancements in biochar application from 2022 to 2023. Utilizing 13,357 bibliographic records sourced from the Web of Science Core Collection with the search term "biochar", the analysis focuses on authorship, national contributions, and keyword trends. Findings demonstrate a continual rise in annual publications since 2009, albeit with a moderated growth rate in 2023. China leads in publication outputs, followed by USA and India, with Hailong Wang emerging as a prominent figure in biochar research. Keyword co-occurrence analyses identify key research themes such as biochar's role in climate change mitigation, easing salinity and drought stress, immobilizing toxic metals, degrading organic pollutants, serving as additives in anaerobic digestion, and functioning as electrodes in microbial fuel cells. Among these, biochar's application for global climate change mitigation gains significant attention, while its utilization as electrodes in microbial fuel cells emerges as a promising research frontier, indicating the growing need for sustainable energy sources. The study also outlines critical research gaps and future priorities for enhancing biochar application. Overall, it highlights the diverse applicability of biochar and offers valuable insight into research progression and forthcoming directions in biochar studies. Highlights: Utilization of bibliometric review for keyword analysis. Examination of recent developments in biochar application. The emerging focus on biochar's effectiveness as electrodes in microbial fuel cells (MFCs). Suggested future research directions and priorities for sustainable biochar application. [ABSTRACT FROM AUTHOR]

The way in which climate change-related information is framed can influence not only cognitive outcomes but also emotional responses. This web-based experiment (n = 331) investigated the effects of strategy framing and issue framing on emotions and online climate action intentions in the context of climate relationship between China and the United States. Results indicated that strategy framing increased negative emotions (i.e., anxiety and anger), whereas issue framing triggered more positive emotions (i.e., pride and excitement). No significant difference was observed regarding climate action intentions between two groups. Additionally, anxiety and anger mediated the effects of message framing on online climate action intentions. Habitual worry about climate change and attitude toward China-U.S. climate collaboration moderated the effects of strategy framing and issue framing on discrete emotions. The findings offer theoretical insights regarding emotional responses to strategy framing and practical implications on climate communication. [ABSTRACT FROM AUTHOR]

The Nigeria Government through the Energy Commission of Nigeria has been promoting biomass as one of the renewable energy sources with little emphasis on biogas technology. These efforts were meant to encourage the adoption of alternate sources of energy and shift from traditional forms of energy like firewood which have devastating effects on the environment. A policy reviewed of was conducted and identified that Nigeria's Energy Policy has no technology listed to aggregate and deploy biogas as a tool for Nigeria's climate goals and enhance energy access. This study aims to investigate through scientific and policy review of how biogas technology penetration could be legislated in the Nigeria energy policy. Works of literatures reviewed (over 70 scientific articles) revealed that policy among other factors is prominent as the main caveat that limits the penetration of biogas technology in many developing countries including Nigeria. Social acceptance, awareness and availability of feedstock are also regarded as part of the challenges facing adopting biogas technology as an alternative clean energy source. The current study has also presented a strategic policy framework that could be considered for biogas policy adoption. In addition, the study has revealed that identification and appropriate stakeholder consultation is key to enhance achieving a holistic policy that fully supports biogas technology in Nigeria. The study has provided robust policy recommendations for deploying biogas technology in the Nigeria energy policy. [ABSTRACT FROM AUTHOR]

In March 2020, an extreme rainfall in Baixada Santista, Brazil, led to a series of landslides affecting more than 2800 people and resulting losses exceeding USD 43 million. This attribution study compared extreme rainfall in two large ensembles of the UK Met Office Hadley Centre HadGEM3-GA6 model that represented the event with and without the effects of anthropogenic climate change. Antecedent rainfall conditions on two different timescales are considered, namely extreme 60-day rainfall (Rx60day) which relates to the soil moisture conditions and extreme 3-day rainfall (Rx3day) which represents landslide triggering heavy rainfall. In the scenario including both natural and human-induced factors the antecedent 60 day rainfall became 74% more likely, while the short-term trigger was 46% more likely. The anthropogenic contribution to changes in rainfall accounted for 20–42% of the total losses and damages. The greatest economic losses occurred in Guarujá (42%), followed by São Vicente (30%) and Santos (28%). Landslides were responsible for 47% of the homes damaged, 85% of the homes destroyed, all reported injuries, and 51% of the deaths associated with heavy rainfall. Changes in land cover and urbanization showed a pronounced increase in urbanized area in Guarujá (107%), São Vicente (61.7%) and Santos (36.9%) and a reduction in farming area. In recent years, the region has experienced an increase in population growth and a rise in the proportion of irregular and/or precarious housing in high-risk areas. Guarujá has the highest number of such dwellings, accounting for 34.8%. Our estimates suggest that extreme precipitation events are having shorter return periods due to climate change and increased urbanization and population growth is exposing more people to these events. These findings are especially important for decision-makers in the context of disaster risk reduction and mitigation and adaptation to climate change. [ABSTRACT FROM AUTHOR]

This study uses a state-of-the-art regional climate model (RCM) to examine how tropical deforestation affects the meteorology of the Indian Summer Monsoon (ISM). Incorporating insights from existing research on deforestation by climate scientists, alongside evidence of environmental deterioration in semi-arid, hilly and tropical regions of Southeast Asia, this research seeks to elucidate the critical influence of anthropogenic reasons of climate change on the hydroclimate of ISM. Employing "tropical deforestation" design experiments with the ICTP-RegCMv4.4.5.10 RCM the study evaluates the effects on meteorological parameters including precipitation, circulation patterns and surface parameters. This experimental design entails substituting vegetation type in the land use map of RegCMv4.4.5.10 model, such as deciduous and evergreen trees in Southeast Asia with "short grass" to mimic tropical deforestation. Findings reveal that deforestation induces abnormal anti-cyclonic circulation over eastern India curtails moisture advection, diminishing latent heat flux and moisture transport, leads to a decrease in precipitation compared to control experiment scenario. Alterations in albedo and vegetation roughness length attributable to deforestation impact temperature, humidity, precipitation, consequently exacerbating drought and heatwave occurrences. Additionally, the study also explores deforestation-induced feedback on ISM precipitation variability. The study concludes that deforestation substantially alters land-surface characteristics, water and energy cycle, and atmospheric circulation, thereby influencing regional climate dynamics. These findings offer foundational insights into comprehending land-use and land-cover changes and their implications for climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

Biomass is a clean and green renewable energy source that can address the energy needs of rural India. This paper is a case study of three villages—Ranoli, Pranpura, and Kishanpur—in Bawal tehsil of Haryana, India, assessing the biomass resource and power generation potential, greenhouse gas emissions (GHGs), and climate impact. The results show that study area can produce 2.13 kt of biomass annually, equivalent to 258.6 kW of power, with biomass resource density ranging between 0.167 and 0.205 kt/km2. The estimated emissions from biomass power generation are 453.91 t of CO 2 , 1.79 t of CH 4 , and 0.174 t of N 2 O . The global temperature change potential (GTP) climate metric is used to estimate the impacts of biomass power emissions on global surface temperature, showing that the first year's emissions would increase the global temperature by 0.27, 1, and 0.54 nK for biomass, coal, and natural gas-based power, respectively. The study highlights the potential of biomass in climate change mitigation and identifies challenges, such as spatio-temporal distribution, low power density, and competing uses, that need to be addressed for its large-scale adoption. Overall, this study contributes to the understanding of biomass energy potential and its role in sustainable development. [ABSTRACT FROM AUTHOR]

Climate change presents a substantial global threat to human health and wellbeing. Planetary health, an emerging field, provides a comprehensive framework to comprehend the intricate interplay between ecological stability, human health, and ecosystems, particularly within the context of climate change. This study investigates the planetary health perspective on climate change by exploring global knowledge. The Scopus database is used as the source of data. The analysis encompassed a performance evaluation aimed at scrutinizing both quantitative and qualitative indicators. Visualization techniques utilizing VOSviewer software were deployed to analyze collaboration patterns, co-citation links among prominent knowledge-sharing platforms, and key topics derived from keyword co-occurrence matrices. Additionally, using SciMAT software, the study conducted thematic evolution and intellectual analyses to identify both driving and emerging themes, while also examining coherence among different themes across various periods. The study also explores policy implications, and the relevance of COVID-19 in the context of planetary health and climate change. Through this analysis, 261 relevant publications are identified, with the United States being the leading contributor (90 documents; 34.5% of publications). At the institutional level, the Australian National University secured the top position, representing 4.6% of the total with 12 documents. The Lancet Planetary Health journal was the most prolific source, contributing 15 documents (5.7%). In terms of impact, The Lancet journal held a central position as the most cited source. The primary funding organization was the Wellcome Trust, based in the United Kingdom. Motor themes shaping the future of this field include vector-borne diseases, human demographics, informal settlements, air pollution, carbon footprint of animal-based foods, and pro-environmental attitudes and behaviors. The study underscores the significance of leveraging the momentum surrounding infectious diseases like COVID-19 and the impacts of climate change to advance planetary health concepts. Integration of the social sciences and enhanced multidisciplinary cooperation are crucial for progress. Additionally, increased funding for developing countries, and legislative empowerment are essential to foster further research. Article Highlights: Planetary health and climate change global knowledge is analyzed using performance analysis and visualization mapping. Stimulating collaboration to advance the principles of planetary health is fundamental for effectively combating climate change. Managing the socioeconomic determinants of equity and health deserves to be the top priority of climate change initiatives. [ABSTRACT FROM AUTHOR]

This study takes a unique approach to analyzing the sustainability and climate planning in major Hungarian cities. It conducts a qualitative analysis, examining the selected cities' sustainability and climate strategy objectives/goals. The aim is to comprehensively assess the extent of harmony between these objectives and identify potential hindering factors. An impact series with six distinct levels (+ + , + , 0, NR, −, –) was established for this analysis, from which positive (+ + , +), neutral (0, NR), and negative (−,–) categories were formulated. The main result of the study presents the efficiency score of the sustainability and climate goals, in which only the ratio of the positive impacts are covered. The findings reveal that the impacts of sustainability objectives show significant differences among the cities, particularly concerning positive and neutral effects. However, climate objectives present a more modest discrepancy regarding positive, neutral, and negative effects observed among the cities. There was no clear regional pattern in terms of sustainability and climate planning efficiency; on the other hand, Budapest, Győr, and Nyíregyháza emerged with outstanding performances. [ABSTRACT FROM AUTHOR]

Moso bamboo (Phyllostachys edulis), an ecologically and economically important forest species in East Asia, plays vital roles in carbon sequestration and climate change mitigation. However, intensifying climate change threatens moso bamboo survival. Here we generate high-quality haplotype-based pangenome assemblies for 16 representative moso bamboo accessions and integrated these assemblies with 427 previously resequenced accessions. Characterization of the haplotype-based pangenome reveals extensive genetic variation, predominantly between haplotypes rather than within accessions. Many genes with allele-specific expression patterns are implicated in climate responses. Integrating spatiotemporal climate data reveals more than 1050 variations associated with pivotal climate factors, including temperature and precipitation. Climate-associated variations enable the prediction of increased genetic risk across the northern and western regions of China under future emissions scenarios, underscoring the threats posed by rising temperatures. Our integrated haplotype-based pangenome elucidates moso bamboo's local climate adaptation mechanisms and provides critical genomic resources for addressing intensifying climate pressures on this essential bamboo. More broadly, this study demonstrates the power of long-read sequencing in dissecting adaptive traits in climate-sensitive species, advancing evolutionary knowledge to support conservation. Moso bamboo is a critical species for carbon sequestration and mitigating climate change. This study presents a haplotype-based pangenome that uncovers substantial genetic diversity associated with climate adaptation and enables predictions of genetic vulnerability under future emission scenarios. [ABSTRACT FROM AUTHOR]

In the last two decades, an exponentially growing number of meta-analyses (MAs) synthesize thousands of peer-reviewed studies on the environmental impacts of farming practices (FPs). This paper describes the iMAP-FP evidence library, a comprehensive dataset on the effects of 34 categories of FPs (such as agronomic practices, cropping and livestock systems, land management options and mitigation techniques) on 34 impacts including climate mitigation, soil health, environmental pollution, water use, nutrients cycling, biodiversity, and agricultural productivity. Through systematic screening, 570 MAs published since 2000 were selected and categorized according to the type of FP. We assessed their impacts, the geographic regions covered, and their quality. We extracted 3,811 effects and their statistical significance associated with sustainable FPs (intervention) compared to a control (typically conventional agriculture) across 223 different intervention-control pairs. Our dataset is accompanied with an online free-access library, which includes a catalogue of synthetic reports summarizing the available evidence on each evaluated FP. [ABSTRACT FROM AUTHOR]

Given the urgency of climate change action and the significant climate impact of household emissions, understanding the drivers of individuals' sustainable behavior patterns is more important than ever. Consequently, we investigate whether different clusters of individual users can be distinguished regarding sustainability-related values, attitudes, and intentions. If these diverse clusters exist, we can explore tailored approaches to promote sustainable behavior patterns among them based on their unique needs and targets. For this purpose, we employ a mixed-method approach combining qualitative interviews with a quantitative survey. The obtained insights help us identify core factors that drive sustainable behavior, develop representations of different user groups, and suggest individualized interventions for supporting sustainable behavior patterns. The qualitative part comprised interviews with ten participants, resulting in the development of qualitative personas. Emerging differences could subsequently be used to select validated psychological scales for the quantitative part to confirm the differences. Applying data-driven clustering, we identify five intention-based clusters that vary regarding factors such as belief in climate change, collaboration, or skepticism concerning sustainability. Building on both qualitative and quantitative insights, five validated personas are created for research and practical use. These personas include Socially Sustainable, Responsible Savers, Unconcerned Spenders, Comfort-Oriented, and Skeptical Consumers. Individuals corresponding to the selected persona may, for example, respond positively to sustainability benefits, while others may be more receptive to hedonistic benefits. Addressing related varying motivational factors raises the demand for individualized interventions. These could be achieved by incorporating the personas' needs with more individualized products and services to promote sustainable behavior. [ABSTRACT FROM AUTHOR]

Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems, maintaining general planning, and accounting for resources. Various sensors bring together heterogeneous data, and advanced machine learning methods enable their automatic handling in wide territories. Key forest properties usually under consideration in environmental studies include dominant species, tree age, height, basal area and timber stock. Being proxies of stand productivity, they can be utilized for forest carbon stock estimation to analyze forests' status and proper climate change mitigation measures on a global scale. In this study, we aim to develop an effective machine learning-based pipeline for automatic carbon stock estimation using solely freely available and regularly updated satellite observations. We employed multispectral Sentinel-2 remote sensing data to predict forest structure characteristics and produce their detailed spatial maps. Using the Extreme Gradient Boosting (XGBoost) algorithm in classification and regression settings and management-level inventory data as reference measurements, we achieved quality of predictions of species equal to 0.75 according to the F1-score, and for stand age, height, and basal area, we achieved an accuracy of 0.75, 0.58 and 0.56, respectively, according to the R2. We focused on the growing stock volume as the main proxy to estimate forest carbon stocks on the example of the stem pool. We explored two approaches: a direct approach and a hierarchical approach. The direct approach leverages the remote sensing data to create the target maps, and the hierarchical approach calculates the target forest properties using predicted inventory characteristics and conversion equations. We estimated stem carbon stock based on the same approach: from Earth observation imagery directly and using biomass and conversion factors developed for the northern regions. Thus, our study proposes an end-to-end solution for carbon stock estimations based on the complexation of inventory data at the forest stand level, Earth observation imagery, machine learning predictions and conversion equations for the region. The presented approach enables more robust and accurate large-scale assessments using limited annotated datasets. [ABSTRACT FROM AUTHOR]

Background: Dry Afromontane forests play a vital role in mitigating climate change by sequestering and storing carbon, as well as reducing greenhouse gas emissions. Despite previous research highlighting the importance of carbon stocks in these ecosystems, the influence of canopy cover and environmental factors on carbon storage in dry Afromontane forests has been barely assessed. This study addresses this knowledge gap by investigating the effects of environmental factors and vegetation cover on carbon stocks in Desa'a forest, a unique and threatened Afromontane dry forest ecosystem in northern Ethiopia. Data on woody vegetation, dead litter, grass biomass, and soil samples were collected from 57 plots. A one-way analysis of variance (ANOVA) was performed at a 95% confidence level (α = 0.05) to examine the influence of canopy cover and environmental factors on the carbon stocks of various pools. Results: Among the 35 woody species identified, Juniperus procera was the most dominant, while Carissa edulis Vahl and Eucalyptus globulus were the least dominant. The average total carbon stock was 92.89 Mg ha−1, with contributions from aboveground carbon, below-ground carbon, litter carbon, grass carbon, and soil organic carbon. Among the carbon pools, soil organic carbon had the highest carbon stock, accounting for 76.8% of the total, followed by above-ground biomass carbon at 17.7%. Significant variations in carbon stocks were found across altitude class and canopy level but not slope and aspect factors. Conclusions: In summary, altitude and canopy level were found to significantly influence carbon stocks in Desa'a forest, providing valuable insights for conservation and climate change mitigation efforts in dry Afromontane forests. Forest intervention planning and management strategies should consider the influence of different environmental variables and tree canopy levels. [ABSTRACT FROM AUTHOR]

The rapid growth of offshore wind farms (OWFs) is driven by concerns for energy security and climate change mitigation. However, their impact on marine environments remains poorly understood due to limited research. This study analyzes the effects of an OWF along China's Jiangsu Coast on seawater quality using data from different development phases. Results show the major pollutants were different across phases. Heavy metal pollution reached alert levels during construction compared to the safe levels observed in the pre-construction and operational phases, mainly due to increases in Pb, Cd, and Hg concentrations. Eutrophication was mild throughout all periods but exhibited a continuous decrease, primarily attributed to reductions in PH and COD concentrations. As a result, the comprehensive pollution level during construction was increased, but it was improved to a clean level during the operational phase. Besides, significant variations were observed in the spatial distribution patterns of major pollutant indices across different scenarios. These changes may stem from a combination effect of land-based pollution, aquaculture, OWF-induced disturbances to atmosphere and hydrodynamics, OWF-related drain and leakage contamination, and marine management policies. Understanding these effects informs OWF optimization, rational wind resource utilization, and marine ecology protection. [ABSTRACT FROM AUTHOR]

This paper presents a collection of datasets holding information on the energy and climate action plans of 6,850 municipalities, taking part in the transnational initiative of the Global Covenant of Mayors (GCoM). This collection includes commitments for reducing net GHG emissions by at least 20% by 2020, 55% by 2030 and becoming climate neutral by 2050. The signatories commit to addressing any of the three pillars of the initiative, namely climate change mitigation, adaptation and energy access. Following two previous releases, the third release of the GCoM collection is introduced, with closing date September 2022. The datasets include information on the action plans and monitoring reports as they are self-reported by signatories, undergoing a quality-harnessing procedure before publication. Additionally, an external comparison is developed with the Emissions Database for Global Atmospheric Research (EDGAR v7), controlling for comparable sources and activity sectors, ensuring the usability of the GCoM datasets for relevant research on local policies and their effects on reducing the impact of climate change. [ABSTRACT FROM AUTHOR]

Flash droughts, characterized by rapid onset and development, present significant challenges to agriculture and climate mitigation strategies. Operational drought monitoring systems, based on precipitation, soil moisture deficits, or temperature anomalies, often fall short in timely detection of these events, underscoring the need for customized identification and monitoring indices that account for the rapidity of flash drought onset. Recognizing this need, this paper introduces a global flash drought inventory from 1990 to 2021 derived using the Soil Moisture Volatility Index (SMVI). Our work expands the application of the SMVI methodology, previously focused on the United States, to a global scale, providing a tool for understanding and predicting these rapidly developing phenomena. The dataset encompasses detailed event characteristics, including onset, duration, and severity, across diverse climate zones. By integrating atmospheric variables through their impact on soil moisture, the inventory offers a platform for analyzing the drivers and impacts of flash droughts, and serves as a large, consistent dataset for use in training and evaluating flash drought prediction models. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel for Climate Change has over the past decade repeatedly warned that we are heading towards inevitable and irreversible climate change, which will negatively affect the lives, livelihoods, and well-being of millions of people around the world, both at present and in the future. In fact, many people, especially vulnerable and marginalized communities in low- and middle-income countries, already live with the effects of climate change in their daily lives. While adaptation – along with mitigation and compensation for loss and damage as a consequence of climate change – was identified as the central pillars of a just climate policy in the Paris Agreement it is unclear whether this entails a right to adaptation – that some people are owed, as a matter of justice, to have the ability to adapt to climate change – and, if so, what such a right would look like. In this paper, I argue that individuals and communities who are or will be negatively affected by climate change through no fault of their own should have the right to adaptation. I argue that the right to adaptation should be specified through four questions: (i) who has a right to adaptation; (ii) what is it a right to; (iii) how much is it a right to; and (iv) who has the duty to uphold the right to adaptation? [ABSTRACT FROM AUTHOR]

The massive deployment of clean energy technologies plays a vital role in the strategy to attain carbon neutrality by 2050 and allow subsequent negative CO2 emissions in order to achieve our climate goals. An emerging challenge, known as 'From Emissions to Resources,' highlights the significant increase in demand for critical raw materials (CRMs) in clean energy technologies. Despite the presence of ample geological reserves, ensuring sustainable access to these materials is crucial for the successful transition to clean energy, taking into account the environmental and social impacts. The commentary centers on four renewable energy technologies namely solar photovoltaics, wind turbines, Li-ion batteries, and water electrolysers. Four pathways for mitigation are quantitatively examined to assess their potential in reducing the vulnerability of the CRM supply chain for these four clean energy technologies: (i) Enhancing material efficiency, (ii) employing substitutivity strategies, (iii) exploring recycling prospects, and (iv) promoting relocalisation initiatives. It is important to note that no single mitigation lever can completely eliminate the risk of CRM supply, rather the accelerated adoption of all four levers is necessary to minimize the CRM supply risk to its absolute minimum. Hence, the study underscores the significance of increased research, innovation, and regulatory initiatives, along with raising social awareness, in effectively addressing the challenges faced by the CRM supply chain and contributing to a sustainable energy transition. [ABSTRACT FROM AUTHOR]