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Climate change represents one of the most pressing societal and scientific challenges of our time. While much of the current research on climate change focuses on future prediction, some of the strongest signals of warming can already be seen in Arctic and alpine areas, where temperatures are rising faster than the global average, and in the oceans, where the combination of rising temperatures and acidification due to increased CO2 concentrations has had catastrophic consequences for sensitive marine organisms inhabiting coral reefs. The scientific papers highlighted as part of this anniversary issue represent some of the most impactful advances in our understanding of the consequences of anthropogenic climate change. Here, we reflect on the legacy of these papers from the biotic perspective. [ABSTRACT FROM AUTHOR]

Recent research has indicated high economic and environmental costs of human paper usage. Technologies have been developed to reduce consumers' paper use behavior, including mechanical dispensers that institute a delay between opportunities to obtain each consecutive unit. However, there is no empirical evidence that these dispensers or delays reduce paper use. In Experiment 1, implementing a delay between paper-unit deliveries using mechanical dispensers in a university café resulted in a significant decrease in units per person, material per person, and cost per person, compared to free-access dispensers. In Experiment 2, a relatively long delay was more effective than a short delay in reducing paper consumption in a laboratory experiment using mechanical dispensers. These results indicate that delays could be used to decrease paper use in many contexts on a larger scale. More research is necessary to determine the underlying behavioral mechanisms responsible for the observed reduction and the cost–benefit relationship under different circumstances. [ABSTRACT FROM AUTHOR]

Tick-borne diseases are a public health issue. To predict vector tick abundance and activity, it is necessary to understand the driving factors for these variables. In this study, the activity of Ixodes ricinus was investigated in forest and meadow habitats in Germany with a focus on abiotic factors. Ixodes ricinus adults, nymphs and larvae were caught by flagging over a period of 2 years. Microclimatic and weather conditions were recorded at the collection sites. Statistical models were applied to describe correlations between abiotic factors and tick activity in univariable and multivariable analyses. Tick activity was observed in a broad range of air temperature between 3 and 28 °C, and air humidity varied between 35 and 95%. In general, tick activity of nymphs and larvae was higher in forest habitats than that in meadows. With the exception of a single specimen of Dermacentor reticulatus, all ticks were Ixodes ricinus, most of them nymphs (63.2% in 2009 and 75.2% in 2010). For the latter, a negative binomial mixed-effects model fitted best to the observed parameters. The modelling results showed an activity optimum between 20 and 23 °C for air temperature and between 13 and 15 °C for ground temperature. In univariable analyses, the collection site, month, season, ground and air temperature were significant factors for the number of ticks caught and for all life stages. In the multivariable analysis, temperature, season and habitat turned out to be key drivers. Ixodes ricinus positive for RNA of tick-borne encephalitis virus was only found at a single sampling site. The results of this study can be used in risk assessments and to parameterise predictive models. [ABSTRACT FROM AUTHOR]

V.M. Fedorov has published comments regarding my paper on the new astronomical theory of climate change developed by us and the appendix to it. In this paper, I disagree with his objections and briefly substantiate my disagreement. The new theory is based on solving problems of the evolution of orbital and rotational motions of the Earth under the influence of the Sun, planets, and the Moon. All components of the theory have been published, and the methods, programs, and calculation data are freely available. [ABSTRACT FROM AUTHOR]

Six planetary boundaries have already been exceeded, including climate change, loss of biodiversity, chemical pollution, and land-system change. The health research sector contributes to the environmental crisis we are facing, though to a lesser extent than healthcare or agriculture sectors. It could take steps to reduce its environmental impact but generally has not done so, even as the planetary emergency worsens. So far, the normative case for why the health research sector should rectify that failure has not been made. This paper argues strong philosophical grounds, derived from theories of health and social justice, exist to support the claim that the sector has a duty to avoid or minimise causing or contributing to ecological harms that threaten human health or worsen health inequity. The paper next develops ideas about the duty’s content, explaining why it should entail more than reducing carbon emissions, and considers what limits might be placed on the duty. [ABSTRACT FROM AUTHOR]

Peatlands cover only 3–4% of the Earth's surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity. [ABSTRACT FROM AUTHOR]

In Ethiopia, large-scale agricultural investment (LAI) is promoted to foster adaptation to climate change among smallholder farmers by improving farming conditions and productivity. However, little has been known about this condition so far. Therefore, the aim of this paper is to study the implications of LAI for the capacity for climate change adaptation among smallholder farmers, based on a study conducted in Merti district in the Central Rift Valley of Ethiopia. An asset-based approach was used to measure the adaptive capacity of smallholders, via data collected from a household survey, undertaken among smallholder households who had, or had not, benefited, from LAI, and supported by key informant interviews and focus group discussions. Descriptive and inferential statistics and qualitative thematic analysis methods were used to analyze the data. The study found that the adaptive capacity of smallholder households was improved under the influence of LAI. LAI motivated and prompted farmers to use technologies that fostered climate change adaption, including the use of irrigation, improved crop varieties, chemical fertilizer, and engagement in alternative sources of income, which improved their food security status. But this technology and knowledge transfer mainly occurred through observation (learning by doing), not by capacity-building. However, both group of smallholders (within and without contact with the LAI) received similar benefits through government rural extension services. Therefore, the paper concludes that scaling up these technologies and alternative income sources could enhance the adaptive capacity of smallholders, but that LAIs should contribute actual technical and financial support as part of benefit-sharing or corporate responsibility. [ABSTRACT FROM AUTHOR]

Climatic and geographic factors characterizing local conditions, as well as the ecological state of the external environment, have a direct effect on human health, morbidity, and life expectancy. The paper considers the basic concepts of medical ecology, a pathogenetic role of environmental atmospheric pollution in the development of environmentally induced and environmentally dependent diseases associated with exposure to meteorological factors. In addition to the major hygienic risk factors affecting the public health (a level of air, water, and soil pollution), the levels of acoustic and electromagnetic background, the type of human nutrition, architectural and planning conditions of human life are of significant importance. Global climate warming causes numerous environmental changes, primarily an increase in surface air temperature, which in turn entails global changes in weather conditions that lead to various weather anomalies. Human health is directly dependent on environmental conditions and a degree of adaptation to them. The paper highlights the issues of diagnosing environmentally induced diseases and measures to counteract their spread. Based on the system diagnosis using physiological indicators of human health and the integration of the adaptation and nosological approaches, a hardware-software complex has been developed and introduced into medical practice. Corrective technologies of regenerative medicine that are used for ecologically dependent pathologies are described. Their application in the process of the complex sanatorium and resort treatment is most effective. [ABSTRACT FROM AUTHOR]

Vulnerability to climate change is a complex, multi-dimensional construct influenced by multiple interacting factors. Several methods and approaches have been developed over the past three decades, yet there are no standard methods for assessing vulnerability (Connelly et al. in State of the art report (4) vulnerability assessment: definitions, indicators and existing assessment methods (issue 4), 2015). The vulnerability assessment studies differ in conceptualization, methodology, sectors affected, exposure to specific hazards, regional factors, and the scale of impact. Assessment of climate vulnerability and identification of indicators to measure it are significant problems. This paper provides a comprehensive and systematic review of indicator-based vulnerability assessment studies from 1990 to 2020. We analyse 84 studies to understand various aspects of vulnerability assessment—concept and approach, dimensions and indicators, and assessment methods. Though multi-dimensional assessments represent the overall vulnerability of an area, only 29.8% of the studies assessed more than one dimension. Analysis shows that 68.8% (75 of 109) of the identified indicators belong to the socioeconomic dimension. Socioeconomic vulnerability is the most assessed, and environmental vulnerability is the least assessed dimension, possibly attributed to ease of data availability. Due to the lack of methodological differences, there has been confusion associated with index-based and indicator-based studies in the literature (Ramieri et al. in Methods for assessing coastal vulnerability to climate change. ETC CCA Tech Paper 1/2011 (issue January), 2011. 10.13140/RG.2.1.1906.9840). Therefore, we develop a taxonomy of the existing vulnerability assessment methods based on their methodological approach. To avoid ambiguity, we denote all methods that employ indicators as indicator-based vulnerability assessment methods and classify them into index-based, clustering-based, and GIS-based methods. Finally, we discuss the advantages and disadvantages of each vulnerability assessment method and the open challenges in this research area. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for developing a social Cumulative Effects Assessment (CEA) which analyses the impacts of climate change on maritime crime and maritime insecurities. The use of a CEA methodology, including the use of the Effect to Impact Pathway will enable mapping the relationships between certain ‘Activities’ (e.g. human-induced emissions of greenhouse gasses), the ‘Pressure’ engendered (e.g. warming sea temperatures) and their ‘Impacts’ (e.g. food shortages) via ‘Receptors’ (e.g. fishing communities) on specific sectors of society (in this case maritime migration and maritime crime, e.g. illegal fishing). This paper provides a Proof of Concept (PoC) for using such a methodology and shows the applicability of a multidisciplinary approach in understanding causal chains. In this PoC, the authors are generating a Non-Geographic Assessment Map that investigates the ‘Impacts’ that the human-induced greenhouse gas emissions have on maritime security. The proposed analytical tool can then be applied in further studies to assess the dependencies and synergies between climate change and the occurrence of maritime insecurity. [ABSTRACT FROM AUTHOR]

Nature-Based Solutions concepts and practices are being used worldwide as part of attempts to address societal challenges but have also been criticised for not dealing with deeper transformations needed to face urgent issues including biodiversity loss, climate change and inclusion. In this paper, we explore how an inclusive, integrated and long-sighted approach, emphasising a more radical integration of nature within cities, might support the transformations needed to endure major contemporary challenges. Addressing important emerging critiques of Nature-Based Solutions, we consider the potential of a more incisive form of Nature-Based Thinking (NBT) in cities, based on more holistic perspectives. The paper draws on a reflective and iterative research process that engaged both the research and practice communities through a symposium and a series of futures workshops that together explored the potential of NBT to develop future nature-cities relations in Europe and Latin America. The results of the reflective process suggest that notions of nature with people—not for people— new organisational structures, and the intention and capacity to apply long-term perspectives, are needed when planning for NBS interventions aimed at sustainable urban development. This includes developing a cultural-structural change based on new and inclusive understandings of human–nature relations, and novel governance paradigms that allow cross-sectoral coordination and engagement of local stakeholders beyond formal organisational structures. [ABSTRACT FROM AUTHOR]

Atmospheric extreme events cause severe damage to human societies and ecosystems. The frequency and intensity of extremes and other associated events are continuously increasing due to climate change and global warming. The accurate prediction, characterization, and attribution of atmospheric extreme events is, therefore, a key research field in which many groups are currently working by applying different methodologies and computational tools. Machine learning and deep learning methods have arisen in the last years as powerful techniques to tackle many of the problems related to atmospheric extreme events. This paper reviews machine learning and deep learning approaches applied to the analysis, characterization, prediction, and attribution of the most important atmospheric extremes. A summary of the most used machine learning and deep learning techniques in this area, and a comprehensive critical review of literature related to ML in EEs, are provided. The critical literature review has been extended to extreme events related to rainfall and floods, heatwaves and extreme temperatures, droughts, severe weather events and fog, and low-visibility episodes. A case study focused on the analysis of extreme atmospheric temperature prediction with ML and DL techniques is also presented in the paper. Conclusions, perspectives, and outlooks on the field are finally drawn. [ABSTRACT FROM AUTHOR]

This paper begins with a recognition that questions of climate change, environmental degradation, and our relations to the natural world are increasingly significant and requiring of a response not only as philosophers of education but also as citizens of the planet. As such the paper explores five of the key journals in philosophy of education in order to identify the extent, range, and content of current discussions related to the environment. It then organizes and summaries the articles that were located while seeking to identify the extent, possibilities, and limitations of current discussions relating to the environment in the philosophy of education community. The hope is that ultimately this work is an invitation to anyone, regardless of tradition, orientation, and expertise, to contribute to the expansion and deepening of both theory and practice in the face of this most serious of challenges. [ABSTRACT FROM AUTHOR]

This paper assesses the robustness of the "natalist bias" of pollution control in de la Croix and Gosseries (J Environ Econ Manage 63:271–287, 2012), according to which taxing emissions encourage agents to shift from production to procreation, further deteriorating the environment and gradually impoverishing the next generations. We relax the assumptions that human capital does not depend on environmental quality and that society does not allocate resources to pollution control. Using a similar Overlapping Generations (OLG) growth model, our findings indicate that taxation does not necessarily encourage agents to permanently shift away from production because living under better environmental conditions enhances productivity through human capital formation. As the government increases the emissions price, agents reduce consumption and education spending, hurting output in the short term. However, in the long run, the reduction in emissions that follows taxation more than compensates for the initial adverse effects, provided that the sensitivity of human capital accumulation to environmental degradation is strong enough. Furthermore, as we increase the coefficient capturing such pollution externality, a Neimark–Sacker bifurcation occurs, making the system compatible with persistent endogenous fluctuations. [ABSTRACT FROM AUTHOR]

Sustainability in cotton production is inevitable because producing more cotton means more employment, economic acceleration, and industrial expansion. India, China, the United States, Brazil, and Pakistan contribute 74% of worldwide cotton production. Pakistan is contributing only 5%, despite the high potential of cotton. The average yield of cotton in Pakistan is stagnant at 570.99 kg hm−2, whereas it entails the highest cost of production among all other crops. The yield obtained in Pakistan is less than the potential, profitability is drastically lessening, and farmers are abandoning cotton for alternative kharif crops. Some traditional quantitative studies have unveiled different factors that affect cotton production. However, an in-depth qualitative study has never been conducted in Pakistan to explore the root causes of growing cotton crop failure. Following Moustakas's traditional phenomenological guidelines, this phenomenological study was conducted in the district of Rahim Yar Khan in the core cotton zone of Punjab province. A total of 10 interviews were conducted with purposively selected cotton growers based on a criterion: (i) having more than 10 years of cotton growing experience, (ii) being a cotton grower, and (iii) having at least 10 years of formal schooling. Interviews were conducted face to face on an interview guide. One interview lasted 45–50 min, and responses were recorded and analyzed using a thematic analysis approach. A total of 6 themes emerged from the collected data, including (i) climate change, (ii) varietal problems, (iii) pesticide usage, (iv) sense of institutional services, (v) attitude of farmers and (vi) soil health and environment. These six merging themes contributed to cotton crop failure and yield decline. The deep exploration further summarized that researchers, extensionists, and farmers need to seriously consider variety, sowing time, and the environment to revive cotton crops. The detailed recommendations and policy guidelines are presented in this paper, highlighting the cotton sector's research, development and investment areas. [ABSTRACT FROM AUTHOR]

The Paris Agreement created an institutionalized role for non-state actors through voluntary cooperation. Many international NGOs (INGOs) are particularly active in these "Paris partnerships," often working with multinational corporations to reduce emissions and promote decarbonization. Though there is ample work on both the effectiveness of the Paris partnerships and on the role of INGOs in the global climate regime, much of this work focuses "outward" – on how INGOs contribute to climate mitigation and adaptation, or influence norms, discourse and policy. Yet, there is considerably less work that focuses "inward" – examining who INGOs work with in order to achieve their policy goals. This paper provides a descriptive analysis of key INGOs in the United Nations Framework Convention on Climate Change (UNFCCC) process, as a first step in a larger research agenda to understand the incentives and opportunities that drive INGO behavior. Specifically, it uses network analysis to identify the "climate establishment" – which I define as the insider INGOs working within the multilateral process and with large corporations to influence rulemaking, soft law and firm behavior. Measures of network centrality demonstrate that two INGOs – WWF and the World Resources Institute – are by far, the most authoritative members of the climate establishment. They participate in the largest number of partnerships, and have "important" friends, as measured by eigenvector centrality. The data also indicate that the climate establishment sees carbon pricing as a key strategy, and it often cooperates with banks that are large funders of fossil fuel projects. The descriptive analysis of the climate establishment and its partners raises important questions for future research about why INGOs choose to partner with F100 companies, and how such cooperation might influence INGO behavior. [ABSTRACT FROM AUTHOR]

Wildfires pose a severe threat to the ecosystem and economy, and risk assessment is typically based on fire danger indices such as the McArthur Forest Fire Danger Index (FFDI) used in Australia. Studying the joint tail dependence structure of high-resolution spatial FFDI data is thus crucial for estimating current and future extreme wildfire risk. However, existing likelihood-based inference approaches are computationally prohibitive in high dimensions due to the need to censor observations in the bulk of the distribution. To address this, we construct models for spatial FFDI extremes by leveraging the sparse conditional independence structure of Hüsler–Reiss-type generalized Pareto processes defined on trees. These models allow for a simplified likelihood function that is computationally efficient. Our framework involves a mixture of tree-based multivariate generalized Pareto distributions with randomly generated tree structures, resulting in a flexible model that can capture nonstationary spatial dependence structures. We fit the model to summer FFDI data from different spatial clusters in Mainland Australia and 14 decadal windows between 1999 and 2022 to study local spatiotemporal variability with respect to the magnitude and extent of extreme wildfires. Our proposed method fits the margins and spatial tail dependence structure adequately and is helpful in providing extreme wildfire risk estimates. Our results identify a significant increase in spatially aggregated fire risk across a substantially large portion of Mainland Australia, which raises serious climatic concerns. Supplementary material to this paper is provided online. [ABSTRACT FROM AUTHOR]

As one of the major greenhouse gases, CO2 is significantly influencing global climate change. Efficient utilization of CO2 is considered an important approach to address the current environmental and energy challenges. In particular, using CO2 as a raw material for the production of hydrocarbons is an attractive strategy for reducing carbon emissions while ensuring a stable energy supply. In this study, fluorine (F) doped ZnLa layered double hydroxide (F-ZL-LDH) and F-doped ZnCe layered double hydroxide (F-ZC-LDH) were prepared using a hydrothermal synthesis method. The materials' structural composition and morphology were analyzed using X-ray diffractometry (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The research results demonstrate that both catalysts exhibit abundant active sites, high selectivity, and excellent electrocatalytic performance for CO2RR to generate CO, with Faradaic efficiencies reaching 89.29% and 89.87% for F-ZL-LDH and F-ZC-LDH, respectively. The doping of fluorine results in the presence of numerous defects and pore structures on the surfaces of F-ZC-LDH and F-ZL-LDH, increasing the surface active area and enhancing charge transfer rates. Meanwhile, F doping facilitates CO2 adsorption and mass transfer on the electrode surface. Moreover, F doping in the catalysts also restricts the adsorption and desorption of *H during the competing hydrogen evolution reaction (HER) process. The effective management and rapid conversion of CO2 to various organic compounds and chemical fuels to facilitate carbon cycle and reduce atmospheric CO2 concentration have become a hot topic in current technological advances worldwide. Among the various electrocatalytic CO2 reduction reaction (CO2RR) products, carbon monoxide (CO) is the product with the highest kinetic accessibility. In this paper, F-ZL-LDH and F-ZC-LDH composite materials were prepared using a hydrothermal synthesis method. Based on preliminary studies, a molar ratio of M2+:M3+ of 3:1 was determined to provide better catalytic performance,and ammonium fluoride content of 30% of the cation molar ratio of M2+ + M3+. The introduction of fluorine (F) improves the catalytic performance of both materials, with a greater enhancement observed for ZL-LDH. At − 1.3V vs. RHE potential, The research results demonstrate that both catalysts exhibit abundant active sites, high selectivity, and excellent electrocatalytic performance for CO2RR to generate CO, with Faradaic efficiencies reaching 89.29% and 89.87% for F-ZL-LDH and F-ZC-LDH, respectively. the fluorination treatment of ZC-LDH and ZL-LDH catalysts significantly enhances their electrocatalytic activity for the CO2 reduction reaction, particularly for the production of CO. These findings contribute to the development of efficient catalysts for CO2 electrochemical reduction and hold promise for advancing the field of CO2 utilization and renewable energy conversion. [ABSTRACT FROM AUTHOR]

Tropical storms are among the most devastating natural disasters in the USA. Climate change is projected to make them even more destructive, and the number of people and properties at risk has steadily increased over the past several decades. Migration is often seen by scholars as an adaptation strategy to reduce exposure to future natural disasters. However, studies of migration after tropical storms have led to inconsistent results and have not analyzed post-storm migration from the viewpoint of exposure to future events. This paper adopts an innovative approach to estimate “excess migration” associated with tropical storms using Bayesian hierarchical models, and decomposes migration by risk of exposure to natural disasters of the origin and destination to understand whether migrants move to safer areas or rather riskier ones. Findings indicate that excess migration after tropical storms is rare and generally fails to reduce the number of people at risk of experiencing future natural disasters. Only the most destructive tropical storms are associated with significant excess migration. Finally, findings further suggest that neither the amount of post-disaster assistance nor the socio-demographic characteristics of the affected counties are strongly associated with excess migration. [ABSTRACT FROM AUTHOR]

Biodiversity reserves are a crucial in-situ method to conserve biodiversity hotspots as they are sensitive to climate change. The Nanda Devi Biosphere Reserve (NDBR) in the western Himalayas is enriched with diverse endemic flora and fauna and endorses the second-highest mountain peak in the world. However, in the recent decade, this region has potentially warmed at an alarming rate. With 36 temperature and precipitation indices from high-resolution 40-year data from ERA5 reanalysis and CHIRPS, this paper assesses the state of warming and extreme climatic events. Apart from the indices, Landsat (NASA/USGS, USA) and QuickSCAT (ISRO, India) were utilized to assess the region's response to climate change. An increase of 0.73ºC in the last decade for minimum, 0.26°C for maximum temperatures was observed, with the highest anomaly of 1.7°C in 2016. The reserve's vegetation pattern has changed with the vegetative region's dispersal towards the north and higher elevations. In the year 2000, the area without any vegetation covered 79% of the total area, which declined to a mere 23.8% in the year 2020, equivalent to a 70% decline in the area. Similarly, the area with very dense region covered only 0.02% of the total area in the year 2000, and in the year 2020, it increased to 109%. Snow cover seems to be worst affected in the region with dense snow cover declining maximum by 2020. From coverage of 12.3% of the total area of the reserves, it was reduced to a mere 0.02%, showing a decline of nearly 100% in the region. Our findings show that although protected areas are meant to be resilient to external anthropogenic intrusions, they are highly susceptible to the intrinsic forces of induced climate change. We suggest that reserve managers enable robust measures to identify the distribution of vulnerable species and introduce new methods to preserve the pristine hotspot region. [ABSTRACT FROM AUTHOR]

Timely and accurate agricultural drought monitoring and drought-driven mechanism analysis in karst basins in the context of global warming are highly important for drought disaster monitoring and sustainable ecological development in a basin. In this study, based on MODIS data, meteorological and topographic data and land use data from 2001 to 2020, we used the Sen slope, the Mann–Kendall test and a geographic detector to explore the driving mechanisms of agricultural drought caused by climate change and human activities in the karst basin of southern China from 2001 to 2020. The results showed that (1) the spatial distribution of the TVDI in the karst basin in southern China has obvious regional characteristics, showing a decreasing trend from west to east. (2) According to the interannual trend of drought, the degree of drought in the South China karst basin exhibited a weakening trend over the last 20 years, with the most severe drought occurring in 2003. Regarding the seasonal change in the TVDI, drought in spring, summer and autumn exhibited a decreasing trend, while that in winter exhibited an increasing trend, and the drought intensity decreased in the following order: spring (0.58) > autumn (0.53) > summer (0.5) > winter (0.48). (3) Single-factor detection the results showed that rainfall, temperature and elevation were the main factors driving aridification in the study area; multifactor coupling (mean) drove drought in descending order: rainfall (q = 0.424) > temperature (q = 0.340) > elevation (q = 0.219) > land use (q = 0.188) > population density (q = 0.061) > slope (q = 0.057). Therefore, revealing the mechanism of agricultural drought in karst basins through the study of this paper has important theoretical significance and provides technical guidance for drought relief in karst areas. [ABSTRACT FROM AUTHOR]

The impacts of climate change increasingly show themselves in many forms in our everyday lives such as heatwaves and droughts. Drought is one of the critical events today for increasing drought frequency. This study focuses on meteorological drought because it directly affects other drought types. Hence, this study focuses on how the future drought conditions will vary under climate change effects in the Mediterranean basin (Turkey). In doing so, this study utilizes precipitation data from three General Circulation Models (GCMs) and three Regional Circulation Models (RCMs). The GCMs are CNRM-CM6, GFDL-CM4, and MPI-ESM1, while the RCMs are (RCA4)-CNRM-CM5, (Reg CM4)-GFDL-ESM2M, and (RCA4)-MPI-ESM-MR. Mitigating biases of the climate models, this study utilizes four statistical downscaling methods (SD), linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), and distribution mapping (DM). Here, the study has two purposes. The main aim of the paper here is to compare the performance of SD methods in improving the representation of observed climate variables in climate models. In addition, the study shows how different methods will affect the spatial drought distribution in the area under the SSP2 4.5 and SSP5 8.5 scenarios. Consequently, the study uses the standardized precipitation index (SPI) and Z-score index (ZSI) to quantify future drought conditions and reaches the following results. The study reveals that mild drought conditions are prevalent in the basin for future periods, and drought indices go down to − 0.55. The study also shows that different SD methods affect the results obtained by each climate model diversely. For example, while the LS method causes the most drought conditions on the results based on CNRM-CM5 and CNRM-CM6, the DM method has a similar impact on outcomes based on GFDL-CM4 and GFDL-ESM2M and causes the most drought conditions. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that occurred in Central Europe in the past, but it is becoming a more serious problem due to the changes in its occurrence and intensity related to climate change. The main aim of this paper was to determine changes in air temperature and precipitation amounts in Slovakia from 1931 to 2020 and to identify changes in drought occurrence and intensity using the Standardised Precipitation and Evapotranspiration Index (SPEI). Cluster analysis was used to determine regions with similar drought occurrences. For each of the identified five clusters, drought characteristics were determined and compared between two reference periods 1961–1990 and 1991–2020. While a decrease in the number of months with SPEI-1 below − 1 was observed in autumn, spring and summer months showed a drying tendency. Overall, we can say that we observed a shift in drought occurrence from autumn and winter months to spring and summer months. This is an important finding for the agriculture or forestry because it affects work management and planning. The clearest tendency in drought events was observed in the western part of Slovakia covering areas with agriculturally intensive land use. Besides prolonging drought events, there was also a higher accumulated deficit for each event. The increase in drought intensity was not spatially consistent over the cluster area, mostly reaching a slight decline of about − 0.1 to − 0.3, which means slight intensification of drought periods in 1991–2020. [ABSTRACT FROM AUTHOR]

Research has focused on the threat of global warming-induced climate change to modern human civilization. Carbon dioxide (CO2) is a primary greenhouse gas that causes global warming. Current efforts have focused on using CO2 as a raw source for producing value-added chemicals. Among the different CO2 conversion processes, the Sabatier process, also known as "CO2 methanation," is an effective approach, particularly if H2 is generated by renewable energy sources. In this process, methane (CH4) and water (H2O) are produced from CO2 and H2 using different transition-metal-based catalysts. Although numerous studies have been conducted to assess the significance of CO2 methanation, quantitative analysis of the publication trends in this research field is still lacking. This review presents the global research landscape of CO2 methanation over the last 20 years (2000–2022). The Web of Science (WoS) database was used to extract 1657 publications, and the VOSviewer software was used for bibliometric investigations. Bibliometric analysis revealed that 77.53% of the papers were published within the past 5 years (2018–2022). The International journal of hydrogen energy is leading journal publishing research articles about CO2 methanation followed by Applied Catalysis B. This study conducted a statistical analysis on the influence of leading countries, institutions, journals, authors, and top keywords in the field of CO2 methanation. Additionally, future research directions and findings of the most cited publications are discussed. Because the CO2 methanation reaction requires a highly stable and active catalyst, a brief introduction and major challenges of these catalysts are also reviewed. We hope that bibliometric findings will help scholars to understand this field of research more effectively and comprehensively. [ABSTRACT FROM AUTHOR]

In northern regions, the long-term serviceability of infrastructure founded on frozen ground is adversely affected by climate warming. Rates of change in temperature, which are not identical spatially and temporally, can remarkably dictate the magnitude and evolution of permafrost degradation. Investigating such impacts requires a non-isothermal rate-dependent geomechanical constitutive model for ice-contained geomaterials. In this paper, a critical-state thermo-elasto-viscoplastic (TEVP) constitutive model is developed for modeling time- and temperature-dependent behavior of frozen soils using the concepts of thermo-elasticity and thermo-viscoplasticity. Solid phase stress (defined as the excess of total stress over fluid pressure), in addition to the cryogenic suction, are considered as the two independent stress state variables to establish the model. The proposed model is able to satisfactorily capture the rate-dependent behavior of frozen soils observed in the experimental tests reported in the literature. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of transition risk on a firm's low-carbon production. As the world is facing global climate change, the Intergovernmental Panel on Climate Change (IPCC) has set the idealized carbon-neutral scenario around 2050. In the meantime, many carbon reduction scenarios, known as Shared Socioeconomic Pathways (SSPs) have been proposed in the literature for different production sectors in a more comprehensive socio-economic context. We consider, on the one hand, a firm that aims to optimize its emission level under the double objectives of maximizing its production profit and respecting the emission mitigation scenarios. Solving the penalized optimization problem provides the optimal emission according to a given SSP benchmark. On the other hand, such transitions affect the firm's credit risk. We model the default time by using the structural default approach. We are particularly concerned with how, by following different SSPs scenarios, the adopted strategies may influence the firm's default probability. [ABSTRACT FROM AUTHOR]

The aim of this policy paper is to characterize the current situation of Tunisian municipalities in matters of climate change policies and actions and to understand the barriers and best practices. By surveying municipalities in Tunisia, we were able to provide an overview of the Tunisian municipalities in matters of climate change actions and strategies, as well as finding the main barriers and best practices. First, we found that most Tunisian municipalities are facing different effects of climate change. Second, the majority of municipalities do not have a strategy for mitigation and adaptation of climate change at the local level. Third, the main barrier that municipalities face in investing in climate change actions is the lack of financial resources and funding. Four, we have identified some of the best climate change mitigation and adaptation practices of surveyed cities, which should be taken into consideration and implemented also by the other cities. [ABSTRACT FROM AUTHOR]

Graduate students can face difficulties collaborating across disciplines and outside of academia. Stakeholder-engaged research (i.e., research involving partners outside of academia) presents challenges for developing a project, finding collaborators, and co-creating knowledge. Past reflections on how to navigate stakeholder-engaged research assume a faculty member leads the project and do not often address implementation from a student-led approach. In this paper, we provide insight on our team science process from an applied, graduate student perspective. We reflect on the formation of our student team and the implementation of a tourism planning research project with community partners. We discuss challenges and focus on practical tips to overcome these challenges. Specifically, we include reflections on co-developing a research project, building authentic partnerships, negotiating power dynamics, and the role of institutional support. Lessons learned from this project can guide other graduate student teams working with stakeholders, as well as faculty seeking to train graduate students in stakeholder-engaged research. [ABSTRACT FROM AUTHOR]

Globally, mangroves have been promoted to protect the coastal ecosystems and human settlements against weather vagaries including climate change impacts. However, climate change can also affect the mangrove ecosystems, affecting their ability to mitigate losses and damages caused by climate change. Recognizing the need to understand the impact of climate change on the ability of mangroves to mitigate loss and damage, this paper presents the impact of climate change on mangrove ecosystems in Dat Mui commune, Ngoc Hien district, Ca Mau province, Vietnam by using community-based methods. Results showed that the most noticeable impact of climate change is the loss in mangrove area, aquatic resources, and coastal erosion prevention. In addition, there is a decline in timber, firewood supply, and habitat of mangrove species. Despite adaptation actions taken by the local authorities and households, mangrove ecosystems are is still facing loss and damage. Solutions have been proposed to help the local and national authorities and communities to address losses and damages caused by the climate change. [ABSTRACT FROM AUTHOR]

Nature-based Solutions (NbS) are integral to efforts to keep global warming below 2°C in accordance with the United Nations' 2015 Paris Agreement on Climate Change. Yet the transboundary governance dimensions of NbS remain unclear and largely undocumented. In Southeast Asia, NbS have emphasised the conservation and/ or sustainable commodification of carbon sinks found in terrestrial and mangrove forests, seagrass meadows, peatlands and agricultural soils. Mostly project-driven and fixed-term, these "solutions" have often failed to meet their social and ecological objectives. Increasingly, they have added to cross-border problems of: (1) displaced carbon emissions; and (2) economic migration and societal dispossession. This perspective paper delineates a transboundary governance research agenda to mitigate these trade-offs and enhance the co-benefits of NbS in carbon sinks. Building on NbS literature, it identifies cross-sector, multi-scalar and interdisciplinary pathways to improve transboundary cooperation, inclusion and equity in carbon sink governance in varying Southeast Asian contexts. [ABSTRACT FROM AUTHOR]

In the past decades, land use pattern and climate conditions of Shaying River Basin have changed significantly, which will inevitably have a significant impact on the river hydrological situation. Therefore, in order to study the response of the hydrological cycle process of the Shaying River Basin to land use and climate changes, this paper constructed the Soil and Water Assessment Tool (SWAT) hydrological model of the Shaying River Basin based on historical meteorological and hydrological data, and conducted parameter calibration and model verification to quantitatively explore the response of the runoff of the Shaying River Basin to different land use and climate change scenarios. The results showed that: (1) In calibration and verification periods, the determination coefficients (R2) were 0.80 and 0.83 respectively, the Nash–Sutcliffe efficiency coefficients (NSE) were 0.77 and 0.73 respectively, and the percentage deviation (PBIAS) was within ± 25%. (2) Setting different combinations of land use and climate changes into four scenarios S1, S2, S3, and S4, the simulated runoff depths were 257 mm, 298 mm, 259 mm, and 301 mm, respectively. The impacts of land use and climate changes on the annual runoff of Shaying River were 0.9% and 16.1% respectively. (3) In the scenario with 4 °C reduction and 20% precipitation increase and scenario 4 °C increase and 20% precipitation reduction, the maximum and minimum annual runoff were increased by 81.9% and decreased by 70.9% compared with the baseline period, respectively. (4) Under the seven scenarios, the precipitation, temperature and runoff in the middle and late 21st century showed an increasing trend, and precipitation will be the main controlling factor affecting runoff. The annual runoff depth showed an increasing trend, and the change of runoff depth in the lower reaches of the basin will be the most obvious. [ABSTRACT FROM AUTHOR]

The authors comment on the article "Closed-form analytical solutions for assessing the consequences of sea-level rise on groundwater resources in sloping coastal aquifers" published in a previous issue of the journal. They state concerns over the impact of sea-level rise on seawater intrusion, and mention limitations to the article associated with the choice of mathematical model and inland boundary condition. They mention the possibility of employing the Strack single potential approach.

Many higher education institutions around the world are engaged in efforts to tackle climate change. This takes place by not only reducing their own carbon footprint but also by educating future leaders and contributing valuable research and expertise to the global effort to combat climate change. However, there is a need for studies that identify the nature of their engagement on the topic, and the extent to which they are contributing towards addressing the many problems associated with climate change. Against this background, this paper describes a study that consisted of a review of the literature and the use of case studies, which outline the importance of university engagement in climate change and describe its main features. The study identified the fact that even though climate change is a matter of great relevance to universities, its coverage in university programmes is not as wide as one could expect. Based on the findings, the paper also lists the challenges associated with the inclusion of climate change in university programmes. Finally, it describes some of the measures which may be deployed in order to maximise the contribution of higher education towards handling the challenges associated with a changing climate. [ABSTRACT FROM AUTHOR]

Evidence of the health impact of climate change has been extensively documented in recent scholarly literature. In order to mitigate the adverse health effects induced by climate change, the need for conducting vulnerability assessments (VAs) has been emphasised. A higher vulnerability to climate change is often linked with substantial risks to human lives and built environment. Despite the potential of VAs in alleviating risks posed by climate change, only a limited amount of scholarly work in this domain has been conducted in the Indian context. The present research addresses this lacuna and contributes to the limited scholarship on climate change and health VAs in India. Drawing on the VA framework introduced by the fourth assessment report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), this paper estimates district-level health vulnerabilities caused by climate change using multi-dimensional indices. The indices are multi-dimensional since they integrate 50 district-level indicators from 8 data sources for all 640 Census 2011 districts. The statistical technique of Principal Component Analysis (PCA) has been used for integrating the indicators. The findings of this paper indicate that nearly 56% of India’s population in 344 districts is highly vulnerable to the health impact of climate change. The results show that high vulnerability in certain districts is mediated by high adaptive capacity (AC). Since climate exposure varies across districts, the paper highlights the need for local-level responses and Complex Adaptive System (CAS) thinking to understand the implications of climate change and human health. [ABSTRACT FROM AUTHOR]

This paper explores the operationalization of climate-related indicators in violent conflict research. The climate-conflict narrative gained traction in recent decades and climate change is often referred to as a 'threat multiplier' by both policy makers and scholars. Yet, the relationships between climate-related phenomena and violent conflict are complex and context-specific. However, limited attention has been given to the climatic indicators applied in climate-conflict research. This paper addresses that gap by analyzing 32 studies published from 2004 to 2020 on the operationalization of climatic indicators and their relationship with violent conflict. It first categorizes climate indicators operationalization into five clusters: natural disasters, basic climate variability, advanced climate variability, freshwater availability, and the ENSO. The study evaluates the climate indicators for each cluster and shows that at an aggregate level these clusters examine 68 different climate representations. When paired with their respective conflict types, it finds a total of 113 climate-conflict combinations. Most operationalizations represent various forms of climate-related phenomena and variability rather than climate change. Some indicators are advancements over time, for example moving from changes in average rainfall to standardized precipitation indices. However, other indicators refer to various natural processes, making it challenging to determine whether climatic variability impacts conflict. The paper then demonstrates a discrepancy between the pathways through which climate may affect violent conflict and the representation of these pathways in the selected climate indicators. It discusses how the selection and operationalization of climate indicators requires careful consideration, and the phenomena researched should be well-specified in research findings. [ABSTRACT FROM AUTHOR]

The challenges posed by climate change, biodiversity loss, and land-use are deeply interconnected and integrated solutions are needed. This paper presents results from 11 contributions to a special issue covering topics of integrated modeling and spatial prioritization, mass-balance studies, Earth Observation techniques, research infrastructure developments, and evaluation of policy measures and economic compensation schemes. The spatial scale of the studies ranges from detailed site-specific to a European scale. This paper briefly summarizes the main findings of these studies, makes some general overall conclusions, and identifies topics for further research and methods developments. [ABSTRACT FROM AUTHOR]

Background: This paper addresses the escalating global issue of electronic waste (e-waste), a consequence of the burgeoning demand for electronic products coupled with their transient lifespan. The rapid accumulation of e-waste is a significant concern, especially in the context of climate change, necessitating a detailed analysis of current management strategies and the development of sustainable management practices. The intricate relationship between e-waste and climate change is emphasized, illustrating how improper disposal and recycling practices substantially contribute to greenhouse gas emissions. A meticulous analysis is conducted to critique the prevailing e-waste management strategies, identifying their shortcomings and the urgent need for enhancement and globalization of these protocols. The paper argues for a fortified, universal approach to e-waste management to address the deficiencies in current methodologies. A set of strategic, sustainable solutions for e-waste management is proposed, encompassing comprehensive regulatory frameworks, advanced recycling technologies, the incorporation of eco-design principles, and the enhancement of consumer awareness. These solutions pivot around the circular economy concept, viewing waste as a valuable resource rather than a disposal predicament, thereby promoting sustainability. Short conclusion: The paper concludes that a consolidated, global approach to e-waste management is imperative for addressing the proliferation of discarded electronics and is pivotal in the wider context of mitigating climate change and fostering sustainable development. It underscores the transformative potential of sustainable e-waste management, transforming a formidable challenge into an opportunity for environmental conservation, economic growth, and societal progress, emphasizing the importance of viewing e-waste management as a vehicle for sustainability. [ABSTRACT FROM AUTHOR]

Agro-pastoral ecotone of northern China is the prominent area for agricultural production, but it is also the most typical ecological fragile area with frequent drought disasters. Taking Yulin City at Shaanxi Province in China as the case area, the paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought in China's agro-pastoral ecotone in the period 2000 to 2020. The results show that: 1) the agricultural vulnerability to drought in Yulin City has shifted from high vulnerability in the period 2000–2010 to low vulnerability in the period 2011–2020. 2) There exist obvious spatio-temporal differences of the agricultural vulnerability to drought in Yulin City during the research period. 3) Four sensitive events and 14 resilient events were identified in the research and the crops of Yulin had become more resilient to drought. Finally, the paper put forward with policy implications to make adaptive strategies of agriculture to climate change in China's agro-pastoral ecotone in the future, e.g., carrying out agricultural zoning based on agricultural production conditions, intensifying the construction of disaster prevention and relief system, and integrating with modern agricultural technology to develop new type agriculture. [ABSTRACT FROM AUTHOR]

The Canadian Cordillera in the province of British Columbia witnesses numerous rock falls every year. Studies on the recorded rock fall data in this area show that rock fall hazard follows weather conditions, especially precipitation and freeze-thaw cycles. This relationship indicates that a weather-based approach can be implemented to estimate possible changes in the rock fall hazard due to climate change. In this paper, we used a statistical approach to quantify the relationship between monthly weather averages and rock fall frequencies for a section of a transportation corridor along the Fraser River in British Columbia, Canada. In this regard, von Mises distributions are used to find the best-fitted models to the monthly precipitation and freeze-thaw cycles, and proper relative weights are applied to the models in order to calibrate them to the rock fall monthly frequency. The calibrated model is used with input data from climatic predictions for 2041–2070 and 2071–2100 to see how rock fall distribution will be affected due to climate change in the future decades. Results show that between 9 and 19%, more rock fall is anticipated in future winters. Rock falls are expected to decrease in other months, especially in October, November, March, and April. This paper presents a method to predict changes in rock fall hazard seasonality due to climate change and illustrates the method with a case study along a section of the Canadian Cordillera. [ABSTRACT FROM AUTHOR]

This paper discusses the radiation budget and its temporal variability over Poland. The data analysis is based on the MERRA-2 reanalysis for the years 1980–2020. During the last four decades, the enhancement of climate warming has been observed, which coincides with the changes in the radiation budget. Positive and statistically significant trends at the top of the atmosphere (TOA; 0.7 ± 0.2 W/m2/10 year) and on the Earth's surface (1.5 ± 0.2 W/m2/10 year) radiation budget (net downward flux) are mainly a consequence of changes in the amount of aerosol and greenhouse gases (GHG). According to MERRA-2, the AOD during this period decreased by − 0.19 (at 550 nm), which is 87% of the long-term (1980–2021) mean value (0.22). The reduction of AOD is due mainly to the decline of non-absorbing sulfate particles, which leads to a reduction of single-scattering albedo (SSA) by − 0.008 per decade and Angstrom exponent (AE) by − 0.06 per decade (both trends statistically significant). On the other hand, the GHG concentration increased by 4.9%/10 year and 3%/10 year, respectively, for CO2 and CH4. The total column of water vapor increased (1.3%/10 year), while ozone decreased (− 1%/10 year). Despite the fact that cloud cover and cloud optical depth (COD) decreased (− 1.8%/10 year and − 1.0%/10 year), the impact of cloud on temporal variability radiation budget is small. It can be explained by nearly compensated shortwave (SW) cooling and longwave (LW) heating effects. During the analysis period, near-surface air temperature increased by 2.0 °C. The estimated increase in SW net surface radiation (7.9 W/m2) leads to climate warming by 0.8 °C, which is a consequence mainly of the reduction of aerosol (0.4 °C) and cloud cover (0.2 °C). The impact of the change of SW radiation on air temperature is more pronounced during the warm season, while during the cold, air temperature change is controlled mainly by the variability of air mass advection. [ABSTRACT FROM AUTHOR]

AI chatbots such as ChatGPT help people produce texts. According to media reporting, these texts are also used for educational purposes. Thus, AI influences people's knowledge and perception of current issues. This paper examines the narrative of ChatGPT's stories on climate change. Our explorative analysis reveals that ChatGPT's stories on climate change show a relatively uniform structure and similar content. Generally, the narrative is in line with scientific knowledge on climate change; the stories convey no significant misinformation. However, specific topics in current debates on global warming are conspicuously missing. According to the ChatGPT narrative, humans as a species are responsible for climate change and specific economic activities or actors associated with carbon emissions play no role. Analogously, the social structuration of vulnerability to climate impacts and issues of climate justice are hardly addressed. ChatGPT's narrative consists of de-politicized stories that are highly optimistic about technological progress. [ABSTRACT FROM AUTHOR]

The impact of global climate change on water resources is a pressing concern, particularly in arid and semi-arid regions, where water shortages are becoming increasingly severe. Rainwater harvesting (RWH) offers a promising solution to address these challenges. However, the process of selecting suitable RWH sites is complex. This paper introduces a comprehensive methodology that leverages various technologies and data sources to identify suitable RWH locations in the northern region of Iraq, considering both historical and future scenarios. The study employs remote sensing and geographic information systems to collect and process geospatial data, which are essential for the site selection process. AHP is utilized as a decision-making tool to assess and rank potential RWH locations based on multiple criteria, helping to prioritize the most suitable sites. The WLC approach is used to combine and weigh various factors, enabling a systematic evaluation of site suitability. To account for the uncertainty associated with future climate conditions, a stochastic weather generator is employed to simulate historical and future precipitation data for period (1980–2022) and (2031–2100). This ensures that the assessment considers changing climate patterns. Historical precipitation values ranged from 270 to 490 mm, while future projections indicate a decrease, with values varying from 255 to 390 mm. This suggests a potential reduction in available water resources due to climate change. The runoff for historical rainfall values ranged from 190 mm (poor) to 490 mm (very good). In the future projections, runoff values vary from 180 mm (very poor) to 390 mm (good). This analysis highlights the potential impact of reduced precipitation on water availability. There is a strong correlation between rainfall and runoff, with values of 95% for historical data and 98.83% for future projections. This indicates that changes in precipitation directly affect water runoff. The study incorporates several criteria in the model, including soil texture, historical and future rainfall data, land use/cover, slope, and drainage density. These criteria were selected based on the nature of the study region and dataset availability. The suitability zones are classified into four categories for both historical potential and future projections of RWH zones: very high suitability, covering approximately 8.2%. High suitability, encompassing around 22.6%. Moderate suitability, constituting about 37.4%. Low suitability, accounting for 31.8% of the study region. For the potential zones of RWH in the future projection, the distribution is as follows: very high suitability, approximately 6.1%. High suitability, around 18.3%. Moderate suitability, roughly 31.2%. Low suitability, making up about 44.4% of the study region. The research's findings have significant implications for sustainable water resource management in the northern region of Iraq. As climate change exacerbates water scarcity, identifying suitable RWH locations becomes crucial for ensuring water availability. This methodology, incorporating advanced technology and data sources, provides a valuable tool for addressing these challenges and enhancing the future of water management to face of climate change. However, more investigations and studies need to be conducted in near future in the study region. [ABSTRACT FROM AUTHOR]

This paper examines various studies on weather and climate extreme events (WCEE) to identify thematic trends and research gaps and suggest directions for further studies. The review identifies 14 subthemes and 23 research focuses, that address impacts and issues in the pre-, during-, and post-disaster phases. Using a matrix of WCEE dimensionality and content matrix analysis, we analyze the distribution and research focus of these studies, revealing areas with both extensive and limited research. While significant literature exists on certain WCEE subthemes, with a strong focus on damage assessment, spatial extent, losses, and disaster management approaches, only a limited number of studies have explored crucial areas such as risk prediction, urban planning, water quality, urban resilience, and public health dimensions. These areas are vital for effective disaster risk reduction. To bridge the knowledge gaps in these areas and other areas with multi-dimensional outlooks within the context of WCEE, we recommend prioritizing research in these subthemes. Our findings underscore the importance of interdisciplinary collaboration and the need for additional research to enhance our understanding of WCEE. Through evidence-based strategies, policymakers and practitioners can develop measures to enhance resilience and mitigate the impacts of WCEE. [ABSTRACT FROM AUTHOR]

In Finland, agriculture is practiced in variable growing conditions that are further challenged by climate change and under external pressure caused by international competition, changing consumer preferences and demands, and the renewal of the European Union Common Agriculture Policy and Paris Agreement climate targets. Futures studies in agriculture have focused on scenario building with expert panels, though usually without farmers' involvement. This study focuses on farmers' views of shaping the future of Finnish agriculture. It builds on the disaggregative Delphi method and combines interviews and a representative survey of Finnish farmers. The study is based on a bottom-up process in which a farmer panel of 20 farms defined their views of the future in a semi-structured thematic interview. The views were turned into statements in a structured survey sent to the second panel, which comprised all Finnish farmers who had received agricultural subsidies in 2016, with 4401 respondents. The results were analyzed using quantitative factor analysis, which produced five future images for Finnish agriculture. The images were shown to the original farmer panel for reflection. They considered the probability of each future image and their own role in it. Technology solves as a future image was most favored by farmers, followed by Ecological and specializing small-scale production image. Business-as-usual was the least likely future images according to the interviewed farmers. This paper describes the process and discusses both methodological benefits and pitfalls, as well as farmers' future views of the forthcoming decades. [ABSTRACT FROM AUTHOR]

While political debates on climate change become increasingly heated, our houses and city infrastructure continue to suffer from an increasing trend of damages due to adverse atmospheric events, from heavier-than-usual rainfalls to heat waves, droughts, and floods. Adapting our homes and critical infrastructure to sustain the effects of climate dynamics requires novel data-driven interdisciplinary approaches for efficient risk mitigation. We develop a new systematic framework based on the machinery of statistical and machine learning tools to evaluate water-related home insurance risks and quantify uncertainty due to varying climate model projections. Furthermore, we introduce the concept of data depth to the analysis of weather and climate ensembles, which remains a novel territory for statistical depth methodology as well as the field of environmental risk and ensemble forecasting in general. We illustrate the new data-driven methodology for risk analysis in application to rainfall-related home insurance in the Canadian Prairies over 2002–2011. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

Using data from 32 European countries for nearly 244 million live births between 1969 and 2021, this paper examines the effects of temperatures on birth rates. The results show that exposure to hot days slightly reduces birth rates five to eight months later, while much stronger negative effects are observed nine to ten months after exposure to hot temperatures. Thereafter, a partial recovery is observed, with slightly increased birth rates. This study also shows that the effect of high-humidity hot days is much stronger than that of hot days with low humidity. Besides, the effect of heatwave days has been found to be more severe than that of hot days that are not preceded by other hot days. This study finds that some adaptation to heat might be expected only in the long run. [ABSTRACT FROM AUTHOR]

Under global warming and climate change (CC), the vulnerable piece of land is India's Eastern-Himalayan-Region (EHR), where millions' livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perception of kiwifruit growers under EHR and the impact of CC on its cultivation. Perceived and scientific data were used for accurate decision-support information. The climatic variables of two locations were analyzed for trend using Mann–Kendall's test. Results suggested that the rainfall trend was found non-significant for both locations, but there was a negative trend during winter for Pasighat and during all seasons for Itanagar. Maximum temperature exhibited an increasing trend for annual, and minimum temperature showed an increasing trend across seasons for the Pasighat region. For the Itanagar region, the maximum temperature was found to have a significantly increasing trend in all seasons, while the minimum temperature showed an increasing trend during winter and annual seasons. Morning relative humidity showed an increasing trend for annual data for Pasighat, while annual evening relative humidity was significantly increased for Itanagar. The study shows that the indigenous farming communities were following shifting cultivation and diversifying their traditional agriculture to kiwifruit cultivation as an adaptation strategy. The community had a clear perception of CC trends and an inadequate perception of the impact on agriculture, therefore, engaging indigenous communities and other stakeholders to postulate a comprehensive adaptation and mitigation strategy for CC. [ABSTRACT FROM AUTHOR]

Our environment has been significantly impacted by climate change. According to previous research, insect catastrophes induced by global climate change killed many trees, inevitably contributing to forest fires. The condition of the forest is an essential indicator of forest fires. Analysis of aerial images of a forest can detect deceased and living trees at an early stage. Automated forest health diagnostics are crucial for monitoring and preserving forest ecosystem health. Combining Modified Generative Adversarial Networks (MGANs) and YOLOv5 (You Only Look Once version 5) is presented in this paper as a novel method for assessing forest health using aerial images. We also employ the Tabu Search Algorithm (TSA) to enhance the process of identifying and categorizing unhealthy forest areas. The proposed model provides synthetic data to supplement the limited labeled dataset, thereby resolving the frequent issue of data scarcity in forest health diagnosis tasks. This improvement enhances the model's ability to generalize to previously unobserved data, thereby increasing the overall precision and robustness of the forest health evaluation. In addition, YOLOv5 integration enables real-time object identification, enabling the model to recognize and pinpoint numerous tree species and potential health issues with exceptional speed and accuracy. The efficient architecture of YOLOv5 enables it to be deployed on devices with limited resources, enabling forest-monitoring applications on-site. We use the TSA to enhance the identification of unhealthy forest areas. The TSA method effectively investigates the search space, ensuring the model converges to a near-optimal solution, improving disease detection precision and decreasing false positives. We evaluated our MGAN-YOLOv5 method using a large dataset of aerial images of diverse forest habitats. The experimental results demonstrated impressive performance in diagnosing forest health automatically, achieving a detection precision of 98.66%, recall of 99.99%, F1 score of 97.77%, accuracy of 99.99%, response time of 3.543 ms and computational time of 5.987 ms. Significantly, our method outperforms all the compared target detection methods showcasing a minimum improvement of 2% in mAP. [ABSTRACT FROM AUTHOR]

The widespread demand for animal-sourced foods poses challenges in addressing climate change due to their significant greenhouse gas emissions. Alternative proteins like cultured meat show promise with lower greenhouse gas emissions, but have faced public resistance, posing substantial barriers to their broad development and adoption. This paper reports a survey that examined the perceived naturalness of protein sources as an important factor that predicts perceived risks, benefits, and support for consumption. A diverse sample from the United States considered six different protein technologies, including three newer alternative proteins such as cultured meat and three more conventional proteins. Newer alternative proteins were perceived as less natural and were less supported than conventional proteins. Additionally, the more participants perceived protein sources as natural, the less risky and more beneficial they perceived them to be, contributing to their support. These results suggest that perceived naturalness, and associated risks and benefits, could be an important factor in shaping public support for or opposition to new proteins. These findings have theoretical and broader implications for the development and adoption of sustainability technologies. [ABSTRACT FROM AUTHOR]