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Climate change is a challenge for the sustainable development of an international economy and society. The impact of climate change on infectious diseases has been regarded as one of the most urgent research topics. In this paper, an analysis of the bibliometrics, co-word biclustering, and strategic diagram was performed to evaluate global scientific production, hotspots, and developing trends regarding climate change and infectious diseases, based on the data of two decades (1999-2008 and 2009-2018) from PubMed. According to the search strategy and inclusion criteria, a total of 1443 publications were found on the topic of climate change and infectious diseases. There has been increasing research productivity in this field, which has been supported by a wide range of subject categories. The top highly-frequent major MeSH (medical subject headings)/subheading combination terms could be divided into four clusters for the first decade and five for the second decade using a biclustering analysis. At present, some significant public health challenges (global health, and travel and tropical climate, etc.) are at the center of the whole target research network. In the last ten years, "Statistical model", "Diarrhea", "Dengue", "Ecosystem and biodiversity", and "Zoonoses" have been considered as emerging hotspots, but they still need more attention for further development.

Simple Summary: During overwintering diapause, the gynes of paper wasps (Polistes sp.) are mainly dormant in sheltered hibernacles, protecting them against predators and adverse weather conditions but hardly against low temperatures. By measuring the temperature inside hibernacles occupied by species from both Mediterranean (Italian; P. dominula, P. gallicus) and temperate (Austrian; P. dominula) climates (mean hibernacle temperatures: 8.5 °C and 3.2 °C, respectively), we were able to calculate the energetic demand of overwintering. The cumulative energetic costs differed between the populations. Costs were lowest for the P. dominula population from the cooler Austrian winter climate and significantly higher in P. dominula and P. gallicus from the warmer Italian climate. The lower costs of the temperate species were a result of the lower winter temperature and physiological acclimation processes. Energetic calculations with an assumed temperature increase of up to 3 °C due to climate change predict a dramatic increase of up to 40% in overwintering costs in all species. Gynes of paper wasps (Polistes sp.) spend the cold season in sheltered hibernacles. These hibernacles protect against predators and adverse weather conditions but offer only limited protection against low temperatures. During overwintering diapause, wasps live on the energy they store. We investigated the hibernacles' microclimate conditions of species from the Mediterranean (Italy, P. dominula, P. gallicus) and temperate (Austria, P. dominula) climates in order to describe the environmental conditions and calculate the energetic demand of overwintering according to standard metabolic rate functions. The temperatures at the hibernacles differed significantly between the Mediterranean and temperate habitats (average in Austria: 3.2 ± 5.71 °C, in Italy: 8.5 ± 5.29 °C). In both habitats, the hibernacle temperatures showed variance, but the mean hibernacle temperature corresponded closely to the meteorological climate data. Cumulative mass-specific energetic costs over the studied period were the lowest for the temperate P. dominula population compared with both Mediterranean species. The lower costs of the temperate species were a result of the lower hibernacle temperature and acclimation to lower environmental temperatures. Model calculations with an increased mean temperature of up to 3 °C due to climate change indicate a dramatic increase of up to 40% in additional costs. [ABSTRACT FROM AUTHOR]

Anthropogenic activity is considered a central driver of current climate change. A recent paper, studying the consensus regarding the hypothesis that the recent increase in global temperature is predominantly human-made via the emission of greenhouse gasses (see text for reference), argued that the scientific consensus in the peer-reviewed scientific literature pertaining to this hypothesis exceeds 99%. This conclusion was reached after the authors scanned the abstracts and titles of some 3000 papers and mapped them according to their (abstract) statements regarding the above hypothesis. Here, we point out some major flaws in the methodology, analysis, and conclusions of the study. Using the data provided in the study, we show that the 99% consensus, as defined by the authors, is actually an upper limit evaluation because of the large number of "neutral" papers which were counted as pro-consensus in the paper and probably does not reflect the true situation. We further analyze these results by evaluating how so-called "skeptic" papers fit the consensus and find that biases in the literature, which were not accounted for in the aforementioned study, may place the consensus on the low side. Finally, we show that the rating method used in the study suffers from a subjective bias which is reflected in large variations between ratings of the same paper by different raters. All these lead to the conclusion that the conclusions of the study does not follow from the data. [ABSTRACT FROM AUTHOR]

It is important to classify academic papers in a fine-grained manner to uncover deeper implicit themes and semantics in papers for better semantic retrieval, paper recommendation, research trend prediction, topic analysis, and a series of other functions. Based on the ontology of the climate change domain, this study used an unsupervised approach to combine two methods, syntactic structure and semantic modeling, to build a framework of subject-indexing techniques for academic papers in the climate change domain. The framework automatically indexes a set of conceptual terms as research topics from the domain ontology by inputting the titles, abstracts and keywords of the papers using natural language processing techniques such as syntactic dependencies, text similarity calculation, pre-trained language models, semantic similarity calculation, and weighting factors such as word frequency statistics and graph path calculation. Finally, we evaluated the proposed method using the gold standard of manually annotated articles and demonstrated significant improvements over the other five alternative methods in terms of precision, recall and F1-score. Overall, the method proposed in this study is able to identify the research topics of academic papers more accurately, and also provides useful references for the application of domain ontologies and unsupervised data annotation. [ABSTRACT FROM AUTHOR]

This document provides an overview of a special issue on landscape ecology, which explores the relationships between ecological and environmental processes in various types of landscapes. The issue includes articles from researchers worldwide, covering topics such as landscape design, climate change interactions, sustainability, and the impact of human activities. The research utilizes tools like remote sensing and GIS to analyze landscape patterns and changes. The articles emphasize the importance of optimizing landscape patterns to reduce environmental degradation and maintain ecosystem services, particularly in the context of urbanization and climate change. The special issue also highlights the interdisciplinary nature of landscape ecology and the significance of cultural perspectives in landscape management. [Extracted from the article]

Climate-change-induced unpredictable weather patterns are adversely affecting global agricultural productivity, posing a significant threat to sustainability and food security, particularly in developing regions. Wealthier nations can invest substantially in measures to mitigate climate change's impact on food production, but economically disadvantaged countries face challenges due to limited resources and heightened susceptibility to climate change. To enhance climate resilience in agriculture, technological solutions such as the Internet of Things (IoT) are being explored. This paper introduces a digital twin as a technological solution for monitoring and controlling temperatures in a greenhouse tunnel situated in Stellenbosch, South Africa. The study incorporates an aeroponics trial within the tunnel, analysing temperature variations caused by the fan and wet wall temperature regulatory systems. The research develops an analytical model and employs a support vector regression algorithm as an empirical model, successfully achieving accurate predictions. The analytical model demonstrated a root mean square error (RMSE) of 2.93 °C and an R 2 value of 0.8, while the empirical model outperformed it with an RMSE of 1.76 °C and an R 2 value of 0.9 for a one-hour-ahead simulation. Potential applications and future work using these modelling techniques are then discussed. [ABSTRACT FROM AUTHOR]

The rising population and the ongoing climate crisis call for improved means to monitor and optimise agriculture. A promising approach to tackle current challenges in food production is the early diagnosis of plant diseases through non-invasive methods, such as the detection of volatiles. However, current devices for detection of multiple volatiles are based on electronic noses, which are expensive, require complex circuit assembly, may involve metal oxides with heating elements, and cannot easily be adapted for some applications that require miniaturisation or limit front-end use of electronic components. To address these challenges, a low-cost optoelectronic nose using chemo-responsive colorimetric dyes drop-casted onto filter paper has been developed in the current work. The final sensors could be used for the quantitative detection of up to six plant volatiles through changes in colour intensities with a sub-ppm level limit of detection, one of the lowest limits of detection reported so far using colorimetric gas sensors. Sensor colouration could be analysed using a low-cost spectrometer and the results could be processed using a microcontroller. The measured volatiles could be used for the early detection of plant abiotic stress as early as two days after exposure to two different stresses: high salinity and starvation. This approach allowed a lowering of costs to GBP 1 per diagnostic sensing paper. Furthermore, the small size of the paper sensors allows for their use in confined settings, such as Petri dishes. This detection of abiotic stress could be easily achieved by exposing the devices to living plants for 1 h. This technology has the potential to be used for monitoring of plant development in field applications, early recognition of stress, implementation of preventative measures, and mitigation of harvest losses. [ABSTRACT FROM AUTHOR]

This review paper examined the global landscape of research on continental flood early warning systems (EWS), shedding light on key trends, geographic disparities, and research priorities. Continental floods stand as one of the most pervasive and devastating disasters worldwide, necessitating proactive measures to mitigate their impact. Drawing upon a comprehensive analysis of the scholarly literature indexed in the Web of Science repository, this study unveiled significant patterns in EWS research. While the emphasis on flooding is evident, a considerable portion of research focuses on precipitation as a variable and modeling approaches. Furthermore, the influence of climate change emerges as a prominent theme, though distinguishing between climate change and variability remains a crucial area for exploration. Geographically, Europe, particularly England and Italy, dominates research efforts in flood related EWS. Conversely, the limited representation of Central America and other regions such as Asia and Oceania, underscores the need for greater attention to regions facing significant flood risks. Importantly, the concept of total link strength emerges as a valuable metric, highlighting collaborative networks established by European countries and the United States. Based on these findings, recommendations are proposed to enhance the inclusivity and effectiveness of flood related EWS research, including a broader consideration of socio-economic factors, fostering collaboration among researchers from diverse regions, and prioritizing initiatives to strengthen research capacities in vulnerable areas. Ultimately, this study provides valuable insights for policymakers, researchers, and practitioners seeking to advance flood risk management strategies on a global scale. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) have been used to forecast the impact of climate change on species' potential distribution, with results that might support decisions for conservation and biodiversity management. Despite their vulnerability to parameterization and data quality input, SDM use has been increasing in the last decades. In fact, inappropriate inputs and the lack of awareness about the effects of methodological decisions on results can lead to potential unreliability in results, a problem that might gain relevance when SDMs are used to predict climate change impacts on species-suitable areas. Aiming to assess how far such a topic is considered, an analysis of the calibration data and methodological decisions was conducted for recent publications (2018 to 2022) that include SDMs in this context, aiming to identify putative deviations from the consensual best practices. Results show that the parameters presented more consistently are the algorithm in use (MaxEnt was used in 98% of the studies), the accuracy measures, and the time windows. But many papers fail to specify other parameters, limiting the reproducibility of the studies. Some papers fail to provide information about calibration procedures, others consider only a fraction of the species' range, and others provide no justification for including specific variables in the model. These options can decrease reliability in predictions under future scenarios, since data provided to the model are inaccurate from the start or there is insufficient information for output discussion. [ABSTRACT FROM AUTHOR]

Archaeology is often argued to provide a unique long-term perspective on humans that can be utilised for effective policy-making, for example, in discussions of resilience and sustainability. However, the specific archaeological evidence for resilient/sustainable systems is rarely explored, with these terms often used simply to describe a community that survived a particular shock. In this study, a set of 74 case studies of papers discussing archaeological evidence for resilience/sustainability are identified and analysed using bibliometric methods. Variables from the papers are also quantified to assess patterns and provide a review of current knowledge. A great variety of scales of analysis, case study locations, stressors, resilient/sustainable characteristics, and archaeological evidence types are present. Climate change was the most cited stressor (n = 40) and strategies relating to natural resources were common across case studies, especially subsistence adaptations (n = 35), other solutions to subsistence deficiencies (n = 23), and water management (n = 23). Resilient/sustainable characteristics were often in direct contrast to one-another, suggesting the combination of factors is more important than each factor taken individually. Further quantification of well-defined variables within a formally-produced framework is required to extract greater value from archaeological case studies of resilience/sustainability. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM's application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period. [ABSTRACT FROM AUTHOR]

Nigeria is one of the most vulnerable countries to climate change (CC) impact. Thus, there is a need to mitigate emission and implement strategies to adapt to the impacts of CC. This study is a review of publications on CC mitigation and/or adaptation in Nigeria. The aims are as follows: to identify commonly adopted climate change adaptation strategies (CCAS) and their determinants; and to identify the climate change mitigation strategies (CCMS) that are widely deployed to reduce emissions in Nigeria. Relevant keywords were used to search for publications in Scopus and Google Scholar. Our dataset shows that from 1999 to the present, there has been an exponential growth in the number of publications on CCAS and CCMS. In total, 75.2% of the papers were on CCAS, 19.6% were on CCMS and 5.2% combined CCAS and CCMS. Many of the papers on CCMS were on 'Energy' and 'Agriculture'. Other sectors identified from the included studies pertinent to mitigation in Nigeria included 'forestry', 'waste management', 'industry' and others. Most (80.7%) of the CCAS papers were related to 'Agriculture', showing the most important sector where CC-adaptive capacity is required in Nigeria. In all, 45% of the papers on CCAS were on 'Social' adaptation, followed by 'Structural measures' (42%), with the smallest amount being on 'Institutional' measures (13%). The relatively fewer number of papers on institutional CCAS highlights the need for more research. This is because institutional measures which include policies, legal and fiscal support are important to build resilience to climate change impact. The greatest determinant influencing the adoption of CCAS is 'Education'. A higher number of publications on 'Agriculture' for both CCMS and CCAS underscores the importance of the sector and the need to develop its mitigation and adaptive capacity strategies. Our results and findings were also compared and discussed in line with similar works on CCMS and CCAS in Africa. [ABSTRACT FROM AUTHOR]

In recent years, climate change has begun to put pressure on humanity and affect natural and human systems. The aim of this paper is to provide an improved understanding of the state of the literature on the impacts of climate change that can be addressed through measures related to disaster risk reduction, sustainable agricultural practices, and the circular economy. This review also represents a valuable and fundamental reference for both researchers and practitioners in these fields. A total of 74,703 articles (climate change adaptation, 45,030; disaster risk reduction, 5920; sustainable agricultural practices, 7940; circular economy, 15,813) published between 1990 and 2022 were extracted from the Web of Science Core Collection, and the links between these areas were mapped using VOSviewer. There has been an increase in the amount of published research on these four topics since 2007, indicating the increasing involvement of researchers to address these topics, influenced by the concerns of national and international bodies to address these changes. [ABSTRACT FROM AUTHOR]

In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests. [ABSTRACT FROM AUTHOR]

Climate change affects water resources through the decrease in rainfall and the increase in temperatures and evapotranspiration. An indirect impact of climate change is also the increase in water uses by human activities. In this review, 320 papers were retrieved, of which 134, spanning five continents and dealing with impacts and solutions, were selected to be used to better understand the effects of climate change on water resources, ecosystems, human health, security, and socio-economic aspects. Here, suggestions and proposals towards solutions by scientists from around the world, tips and ideas to deal with climate change, and the best solutions for future water management are presented. The main solutions highlighted concern integrated water resource management, political direction, policies, an increase in knowledge, and new technologies. Furthermore, most of the analyzed papers underline that water resource management needs to incorporate the protection and restoration of ecosystems and their services. Nature-based solutions need to be the starting point of new scientific and innovative ways to deal with climate change and look towards future climate adaptation. In this complex evolution of the water resource, the political position of Italy is also shown, illustrating what actions could be implemented for water resource management. [ABSTRACT FROM AUTHOR]

This paper describes the data gathered for a paper published in Earth-Science Reviews (DOI: 10.1016/j.earscirev.2023.104339) to address the problem of studies using incorrect equations to calculate rainfall erosivity (R factor), which can lead to issues related to land degradation, soil productivity loss, and biodiversity loss. The aim was to locate articles containing the incorrect equations and create a relational database that could be used to perform an in-depth analysis of the errors. Because the search target is an equation, it is impossible to directly query any literature database for the articles that contain the incorrect R equations. Therefore, a manual search of multiple databases was conducted. Subsequently, the literature search was broadened to identify the origin of the misuse of the R equations, and SQL (Structured Query Language) queries were formulated to understand why the errors continued to persist for a minimum of 33 years. The resulting entity-relationship-based Microsoft Access database was determined to be a valuable tool for performing in-depth analysis. It can be used to add incorrect studies and perform further analysis. It is suggested that further research should be conducted to determine the extent of the impact of these errors on soil erosion, ecosystems, and the environment. Dataset: 10.17632/ryn6wdgckf.1. Dataset License: CC BY 4.0 [ABSTRACT FROM AUTHOR]

Central Chile (CC, latitudes 32–40°S) experienced very active fires in 2017 and 2023. These fires burned large areas and killed many people. These unprecedented fires for CC presented a need for more defined fire weather conditions on the synoptic scale. In this paper, fire weather conditions were analyzed using various satellite-derived fire data (hotspots, HSs), wind streamlines, distribution maps of wind flow and temperature, and various synoptic-scale weather maps. Results showed that local winds, known as Puelche, blew on the peak fire days (26 January 2017 and 3 February 2023). The number of HSs on these days was 2676 and 2746, respectively, about 90 times the average (30). The occurrence of Puelche winds was confirmed by streamlines from high-pressure systems offshore of Argentina to the study area in CC. The formation of strong winds and high-temperature areas associated with Puelche winds were identified on the Earth survey satellite maps. Strong winds of about 38 km h−1 and high temperatures above 32 °C with low relative humidity below 33% were actually observed at the weather station near the fire-prone areas. Lastly, some indications for Puelche winds outbreaks are summarized. This paper's results will be used to prevent future active fire occurrences in the CC. [ABSTRACT FROM AUTHOR]

Therefore, crop mechanism models play an important role in assessing the effects of climate change on crop production and proposing effective coping strategies. Climate change and its impacts on agricultural production and food security are a significant source of public concern around the world. The paper by Shayanmehr et al. [[13]] constructed a new integrated climate-hydrological-economic model to assess the impact of future climate change on water resources and crop production. [Extracted from the article]

It is essential to conduct research on low-carbon behaviour in order to address global climate change and promote sustainable development. This study conducts a thorough examination of a bibliometric analysis of the existing literature in this field. We analysed 129 papers from the Web of Science Core Collection database to conduct a study on the concept of "low-carbon behaviour". Review articles, proceedings papers, and editorial materials were all excluded. This investigation examines a diverse array of research environment factors, including the most highly ranked publications, publication trends, significant publishers, and patterns in citations and publications over time. The primary institutional contributors in the discipline and the most influential works worldwide are also mentioned. The application of advanced visualisation techniques, such as wordcloud representations, the spatial distribution of research output, and co-occurrence and overlay networks, is employed to generate maps of keyword relationships and collaboration networks using Bibliometrix Stable Version, VOSviewer 1.6.20, and Scimago Graphica Beta 1.0.45. This multi-modal methodology enables a comprehensive investigation of significant research issues and emerging directions in low-carbon behavioural studies. This study contributes to the ongoing endeavours to promote sustainable development and mitigate climate change by conducting a comprehensive evaluation of the current state of research and establishing a robust framework for future investigations into low-carbon behavioural patterns and behaviours. [ABSTRACT FROM AUTHOR]

In recent years, forest fires have been occurring frequently around the globe, affected by extreme weather and dry climate, causing serious economic losses and environmental pollution. In this context, timely detection of forest fire smoke is crucial for realizing real-time early warning of fires. However, fire and smoke from forest fires can spread to cover large areas and may affect distant areas. In this paper, a lightweight joint forest fire and smoke detection network, SmokeFireNet, is proposed, which employs ShuffleNetV2 as the backbone for efficient feature extraction, effectively addressing the computational efficiency challenges of traditional methods. To integrate multi-scale information and enhance the semantic feature extraction capability, a feature pyramid network (FPN) and path aggregation network (PAN) are introduced in this paper. In addition, the FPN network is optimized by a lightweight DySample upsampling operator. The model also incorporates efficient channel attention (ECA), which can pay more attention to the detection of forest fires and smoke regions while suppressing irrelevant features. Finally, by embedding the receptive field block (RFB), the model further improves its ability to understand contextual information and capture detailed features of fire and smoke, thus improving the overall detection accuracy. The experimental results show that SmokeFireNet is better than other mainstream target detection algorithms in terms of average APall of 86.2%, FPS of 114, and GFLOPs of 8.4, and provides effective technical support for forest fire prevention work in terms of average precision, frame rate, and computational complexity. In the future, the SmokeFireNet model is expected to play a greater role in the field of forest fire prevention and make a greater contribution to the protection of forest resources and the ecological environment. [ABSTRACT FROM AUTHOR]

Global surveys show that young people are concerned about sustainability and climate change and how it will affect their future. Education for Sustainability is seen as a key approach that can equip young people with the knowledge, skills, and competencies to act for climate justice. Despite much policy attention on Education for Sustainable Development (ESD), this paper argues that current educational approaches inadequately prepare young people to understand and engage with climate change and sustainability issues. Drawing on a unique survey of 1655 young people in England, this study identifies significant knowledge gaps in understandings of sustainability concepts and a strong demand for educational reforms. Quantitative data reveal variations in sustainability understandings across age, gender, and income, while qualitative insights uncover young people's feelings about the gaps in their education, exposing their fears, anger, powerlessness, and hopes for change. This study highlights the dominance of consumer choice in young people's perceptions of sustainability, emphasizing the need to shift from individualistic to collective actions. This paper concludes with a call to integrate sustainability education into the English National Curriculum to promote holistic and action-oriented learning and create opportunities for nurturing hope through transformative education. [ABSTRACT FROM AUTHOR]

The main objective of the study was to determine the effect of impregnation of the paper core with acetylated starch on the mechanical properties and absorbed energy in the three-point bending test of wood-based honeycomb panels under varying temperatures and relative air humidity conditions. Nearly six hundred beams in various combinations, three types of facings, three core cells geometries, and two paper thicknesses were tested. The experiment results and their statistical analysis prove a significant relationship between the impregnation of paper with modified starch and mechanical properties. The most effective in absorbing energy, the honeycomb panels, consisted of a core with a wall thickness of 0.25 mm and a particleboard facing. [ABSTRACT FROM AUTHOR]

Life Cycle Assessment (LCA) and Life Cycle Cost Assessment (LCCA) are essential tools for environmental and economic assessment and decision-making in an evolving world with continuous climate change. In the same conditions, one of the most used and assessed solutions for facing climate change is using pervious pavements, with many papers proving its benefits. However, the literature has shown a need for more research on the LCA methodological aspects in the context of new green infrastructure. This research aims to review pervious pavements, LCA and LCCA combined, while discussing possible differences in boundaries, functional units, and other parameters. Thus, a string search was performed, leading to 89 documents. The main results indicate LCA is usually scope-bounded in the field of pervious pavements, with different benefits and characteristics, such as traffic impact, urban heat island effects, and carbonation. As for LCCA, private and public cost differentiation provide a scope definition and monetisation difficulties. In conclusion, both tools offer promising applications in pervious pavements. As a significant deliverable and recommendation of this paper, both LCA and LCCA theoretical frameworks were provided based on the benefits and specific characteristics included in the literature. These frameworks introduce novel ideas and perspectives, inviting further exploration and discussion. [ABSTRACT FROM AUTHOR]

Sea level change, a consequence of climate change, poses a global threat with escalating impacts on coastal regions. Since 1880, global mean sea level has risen by 8–9 inches (21–24 cm), reaching a record high in 2021. Projections by NOAA suggest an additional 10–12-inch increase by 2050. This paper explores research methodologies for studying sea level change, focusing on Geographic Information System (GIS) techniques. GIS has become a powerful tool in sea level change research, allowing the integration of spatial data, coastal process modeling, and impact assessment. This paper sets the link with sustainability and reviews key factors influencing sea level change, such as thermal expansion and ice-mass loss, and examines how GIS is applied. It also highlights the importance of using different scenarios, like Representative Concentration Pathways (RCP), for accurate predictions. The paper discusses data sources, index variables like the Coastal Vulnerability Index, and GIS solutions for modeling sea level rise impacts. By synthesizing findings from previous research, it contributes to a better understanding of GIS methodologies in sea level change studies. This knowledge aids policymakers and researchers in developing strategies to address sea level change challenges and enhance coastal resilience. Furthermore, global analysis highlights the pivotal roles of the United States and China in sea level change (SLC) and GIS research. In the Gulf Cooperation Council (GCC) region, rising temperatures have substantial impacts on local sea levels and extreme weather events, particularly affecting vulnerable coastal areas. [ABSTRACT FROM AUTHOR]

Acknowledging the importance of climate challenges to our environment, landscape and cities, this review focuses on the exploration of visual methods (e.g., design, drawing, sketches) in relation to a deeper understanding of climate emergency and sustainability on a spatial scale. It provides an overview of existing research and highlights the role design and drawing can play in landscape-led projects, as well as the impact these might have on behavioural change and decision-making. Looking at how design and drawing are perceived in landscape architecture and what their contribution is to the narrative of a project as well as the decisions made, this paper establishes a connection between pictorial forms and landscape. At the same time, this paper explores whether visualisations are used in relation to the climate and environmental challenges we face, sharing some light on the role they can play with regards to climate awareness and sustainability and how important they might be for our communities, cities and regions. This review highlights the need for further research around this topic and explains that there is a minor part of the literature looking at ways in which landscape design can be integrated into the wider climate emergency agenda and how this might influence behavioural change and the decision-making of various stakeholders. [ABSTRACT FROM AUTHOR]

Featured Application: This work helps to realise improvements in the cultivation of corn and corn–nixtamalisation–dough–tortillas production, which could mean more environmentally friendly food production. The research on the environmental impacts of corn-derived products has been mainly on cultivation techniques and the production of biofuels, so there is limited information on the impacts produced by the transformation of corn for human consumption. The tortilla is a millennial product derived from corn of which consumption is increasing in North America. The aim of this study is to identify the environmental hotspots of the tortilla using a life cycle assessment (LCA) approach. The process studied included only the corn–nixtamalisation–dough–tortillas production. The functional unit is one kg of tortillas packed in kraft paper. The impacts of the tortilla production process were evaluated using SimaPro 8.5.0 software, considering ReCiPe Midpoint. The production has the greatest impact in 15 of the 18 impact categories. The normalisation reveals that the most significant impacts concentrate in the categories terrestrial acidification (TA), particulate matter formation (PMF), marine ecotoxicity (MET) and fossil fuel depletion (FD). Improvements in the cultivation could mean more environmentally friendly tortilla production. [ABSTRACT FROM AUTHOR]

The effect of climate change on forest dynamics is likely to increase in importance in the forthcoming decades. For this reason, it is essential to predict the extent to which changes in temperature, precipitation, and atmospheric CO2 might affect the development of forest ecosystems and successional pathways. The gap model ZELIG-CFS was used to simulate the potential long-term effects of climate change on species-specific annual change in mean basal area and stand density under two scenarios of representative concentration pathways (RCP), 4.5 and 8.5, for the boreal forest region of Ontario, Canada, where mean temperature, precipitation, and atmospheric CO2 are expected to increase. Forest ecosystems in this boreal region included pure and mixed stands of black spruce (Picea mariana [Mill.] B.S.P.), paper birch (Betula papyrifera Marsh.), balsam fir (Abies balsamea [L.] Mill.), jack pine (Pinus banksiana Lamb.), trembling aspen (Populus tremuloides Michx.), white spruce (Picea glauca [Moench] Voss), northern white cedar (Thuja occidentalis L.), American larch (Larix laricina [Du Roi] K. Koch), and balsam poplar (Populus balsamifera L.). Simulation results under climate change generally predicted a decline in the basal area and stand density for black spruce, balsam fir, jack pine, and white spruce, but an increase for paper birch, trembling aspen, American larch, and balsam poplar. However, the extent of change differed regionally among species. Forest composition is expected to change over the long term. Simulation results indicated that shade-intolerant deciduous and conifer species will increase their dominance over the 100-year time horizon. This transition toward the increasing presence of deciduous forests is likely explained by more favorable temperature conditions for their growth and development. [ABSTRACT FROM AUTHOR]

The impact of climate change on agricultural quality development under the constraint of China's "Double Carbon" target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China's provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies. [ABSTRACT FROM AUTHOR]

Over recent decades, the Arctic has begun facing a range of climate-related challenges, from rising temperatures to melting ice caps and permafrost thaw, with significant implications for ecosystems and human well-being. Addressing the health impacts of these issues requires a comprehensive approach, integrating scientific research, community engagement, and policy interventions. This study conducts a literature review to assess the effects of climate change on human health in northern latitudes and to compile adaptation strategies from the Arctic countries. A literature search was performed between January and April 2024 for papers published after 2000, using the electronic databases Web of Science, Pubmed, Science Direct, Scopus, Google Scholar, and eLibrary.RU, with specific questions formulated to direct the search: (i) What are the climate changes? (ii) How does climate change affect human health? (iii) What adaptation measures and policies are required? The key phrases "climate change", "human health", "adaptation practices", and "Arctic" were employed for searching. Ultimately, 56 relevant studies were identified, reviewing health risks such as infectious diseases, mental health issues, and diseases connected with extreme weather events; wildfires and their associated pollution; permafrost degradation; pure water; and food quality. The paper also examines mitigation and adaptation strategies at all levels of governance, emphasizing the need for international cooperation and policy action to combat negative health outcomes, investments in healthcare infrastructure, emergency preparedness, and public health education. Incorporating diverse perspectives, including Indigenous knowledge, Community-Based Adaptation, EcoHealth and One Health approaches, is crucial for effectively addressing the health risks associated with climate change. In conclusion, the paper proposes adaptation strategies to mitigate the health impacts of climate change in the Arctic. [ABSTRACT FROM AUTHOR]

Mega ports, defined in this study as those handling over 5 million TEUs annually, are major hubs within the dynamic framework of global trade, influencing both economic and environmental landscapes. This study identifies climate change as the foremost environmental concern for these ports, necessitating urgent and strategic responses. Through comprehensive research, this paper explores the main Climate Change Mitigation (CCM) strategies and evaluates their implementation across mega ports worldwide. Findings indicate widespread adoption of certain strategies, such as setting greenhouse gas (GHG) reduction targets and providing on-shore power supply (OPS), while also identifying challenges, particularly in implementing environmentally differentiated port fees. Additionally, this paper outlines key strategies for climate change adaptation (CCA) in ports. The results of this research offer insights into sustainable practices and collaborative efforts to confront climate change challenges effectively. These findings have the potential to significantly improve maritime policy and ship management strategies. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have already been acknowledged to be the most viable solution to the climate change that the entire globe has long been combating. Along the same line, it is a salient subject to expand the availability of EV charging infrastructure, which quintessentially necessitates the optimization of the charger's locations. This paper proposes to formulate the optimal EV charger location problem into a facility location problem (FLP). As an effort to find an efficient method to solve the well-known nonpolynomial deterministic (NP) hard problem, we present a comparative quantification among several representative solving techniques. This paper features two comprehensive case studies representing regions with an average and a high density of EVs. As such, this paper shows that the proposed framework can lead to successful location optimization with adequate refinement of solving techniques. [ABSTRACT FROM AUTHOR]

In this study, we analyzed the newly emerging research field of climate change in combination with tea production. We adapted a valid search query to cover the relevant literature as completely as possible and to exclude irrelevant literature. The search resulted in a publication set of 14 key papers dealing with the implications of climate change for tea production as well as 71 papers citing at least one of the 14 key papers. The VOSviewer software was used for revealing the thematic content of the publication set based on the analysis of the keywords. The analysis illustrates the importance of climate change for tea production and mirrors the emerging discussion on climate change impacts and adaptation strategies. Questions regarding the historical context of research fields or specific research topics can be answered by using a bibliometric method called "Reference Publication Year Spectroscopy" (RPYS). The standard RPYS, as well as RPYS-CO, which is based on co-citations of a marker paper, were applied and the most important publication in the historical context of climate change in combination with tea production was identified: both RPYS analyses revealed a paper by M.A.Wijeratne working at the Tea Research Institute (TRI) in Sri Lanka as the starting point of the newly emerging research topic. Currently, the research topic is stimulated by research projects and publications of Selena Ahmed at the Montana State University (USA). [ABSTRACT FROM AUTHOR]

The field of water management is continually changing. Water has been subject to external shocks in the form of climate change and globalization. Water management analysis is subject to disciplinary developments and inter-disciplinary interactions. Are these developments well-documented in the literature? Initial observations in the interdisciplinary literature suggest that results are fragmented, implying that a state-of-the-art review is needed. This paper aims to close such a gap by reviewing recent developments in water economics that address increasing perceptions of water scarcity by looking first at changes in the supply and quality of water and then at the impacts of climate change on water supply extremes. Among responses to such challenges, this paper identifies changes to water use patterns by including and co-managing water from different sources, including surface and groundwater, reclaimed wastewater, and desalinated water. Technological advancements are also among the resources that address water challenges. Water challenges are also reflected in the management of internationally shared water. A recent surge in scientific work identified international treaties as a significant contributor to international water management. This paper reviews recently employed economic approaches, such as experimental economics, game theory, institutional economics, and valuation methods. And, finally, it explores modeling approaches, including hydro-economic and computable general equilibrium models, that are being used to deal with water challenges. [ABSTRACT FROM AUTHOR]

Since 1971, remote sensing techniques have been used to map and monitor phenomena and parameters of the coastal zone. However, updated reviews have only considered one phenomenon, parameter, remote data source, platform, or geographic region. No review has offered an updated overview of coastal phenomena and parameters that can be accurately mapped and monitored with remote data. This systematic review was performed to achieve this purpose. A total of 15,141 papers published from January 2021 to June 2023 were identified. The 1475 most cited papers were screened, and 502 eligible papers were included. The Web of Science and Scopus databases were searched using all possible combinations between two groups of keywords: all geographical names in coastal areas and all remote data and platforms. The systematic review demonstrated that, to date, many coastal phenomena (103) and parameters (39) can be mapped and monitored using remote data (e.g., coastline and land use and land cover changes, climate change, and coastal urban sprawl). Moreover, the authors validated 91% of the retrieved parameters, retrieved from remote data 39 parameters that were mapped or monitored 1158 times (88% of the parameters were combined together with other parameters), monitored 75% of the parameters over time, and retrieved 69% of the parameters from several remote data and compared the results with each other and with available products. They obtained 48% of the parameters using different methods, and their results were compared with each other and with available products. They combined 17% of the parameters that were retrieved with GIS and model techniques. In conclusion, the authors addressed the requirements needed to more effectively analyze coastal phenomena and parameters employing integrated approaches: they retrieved the parameters from different remote data, merged different data and parameters, compared different methods, and combined different techniques. [ABSTRACT FROM AUTHOR]

Nature-based solutions (NbS) is an approach to solving climate change and social issues based on nature. Despite NbS being widely studied as an effective method to solve social problems, the trends in NbS research have hardly been analyzed. Therefore, this study examined change patterns in NbS-related research topics over time and analyzed the interactions of NbS research and relevant activities in various fields. After reviewing research papers based on the search term 'nature-based solutions' on Scopus, and collecting 1567 research papers, we conducted dynamic topic modeling (DTM) and network analysis. The papers were classified into 19 topics via DTM. Water, forest, and urban topics made up the greatest portion of NbS research, while NbS topics in the forest sector showed a steady increase over time. This study also found close connections between NbS studies on forests and other sectors and confirmed that the forest sector can become an integrated means of contributing to climate change responses and other resultant social issues. This study demonstrates that DTM and network analysis are useful tools for understanding the trends in NbS research and finding the linkages between various fields. [ABSTRACT FROM AUTHOR]

Extreme weather events like typhoons have become more frequent due to global climate change. Current typhoon monitoring methods include manual monitoring, mathematical morphological methods, and artificial intelligence. Manual monitoring is accurate but labor-intensive, while AI offers convenience but requires accuracy improvements. Mathematical morphology methods, such as brightness temperature perturbation (BTP) and a spatio-temporally consistent (STC) Scale-Invariant Feature Transform (SIFT), remain mainstream for typhoon positioning. This paper enhances BTP and STC SIFT methods for application to Fengyun 4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) L1 data, incorporating parallax correction for more accurate surface longitude and latitude positioning. The applicability of these methods for different typhoon intensities and monitoring time resolutions is analyzed. Automated monitoring with one-hour observation intervals in the northwest Pacific region demonstrates high positioning accuracy, reaching 25 km or better when compared to best path data from the China Meteorological Administration (CMA). For 1 h remote sensing observations, BTP is more accurate for typhoons at or above typhoon intensity, while STC SIFT is more accurate for weaker typhoons. In the current era of a high temporal resolution of typhoon monitoring using geostationary satellites, the method presented in this paper can serve the national meteorological industry for typhoon monitoring, which is beneficial to national pre-disaster prevention work as well as global meteorological research. [ABSTRACT FROM AUTHOR]

Water security is a critical global issue that has gained increasing attention from researchers, policymakers, and practitioners over the past few decades. This paper presents a comprehensive overview of the evolution of potable water security indices from the 1980s to the 2020s, focusing on the key research themes, trends, and influential factors in the field. We conducted a comprehensive search of the relevant literature and examined the development of water security indices to provide insights into the current state of research and identify future research directions. This paper will explore the historical context, key indicators, sector-specific challenges, climate change implications, governance and policy considerations, technological advancements, community engagement efforts, and future directions for research in this critical field. Researchers and policymakers will find this review valuable as it offers insights into the existing knowledge and the areas that require further exploration to address global water security challenges. [ABSTRACT FROM AUTHOR]

This study leverages explainable artificial intelligence (XAI) techniques to analyze public sentiment towards Environmental, Social, and Governance (ESG) factors, climate change, and green finance. It does so by developing a novel multi-task learning framework combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning to extract nuanced insights from a large corpus of social media data. Our approach integrates state-of-the-art models, including the SenticNet API, for sentiment analysis and implements multiple XAI methods such as LIME, SHAP, and Permutation Importance to enhance interpretability. Results reveal predominantly positive sentiment towards environmental topics, with notable variations across ESG categories. The contrastive learning visualization demonstrates clear sentiment clustering while highlighting areas of uncertainty. This research contributes to the field by providing an interpretable, trustworthy AI system for ESG sentiment analysis, offering valuable insights for policymakers and business stakeholders navigating the complex landscape of sustainable finance and climate action. The methodology proposed in this paper advances the current state of AI in ESG and green finance in several ways. By combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning, our approach provides a more comprehensive understanding of public sentiment towards ESG factors than traditional methods. The integration of multiple XAI techniques (LIME, SHAP, and Permutation Importance) offers a transparent view of the subtlety of the model's decision-making process, which is crucial for building trust in AI-driven ESG assessments. Our approach enables a more accurate representation of public opinion, essential for informed decision-making in sustainable finance. This paper paves the way for more transparent and explainable AI applications in critical domains like ESG. [ABSTRACT FROM AUTHOR]

Positive Energy Districts (PEDs) are a promising approach to urban energy transformation, aiming to optimize local energy systems and deliver environmental, social and economic benefits. However, their effectiveness and justification for investment rely on understanding the additional value they provide (additionality) in comparison to current policies and planning methods. The additionality perspective is not used yet in current evaluations of PED demonstrations and pilots. Therefore, this paper introduces the concept of additionality in the evaluation of PEDs, focusing on the additional benefits they bring and the circumstances under which they are most effective. We discuss the additionality of PEDs in addressing the challenges of climate neutrality and energy system transformation in three European cities that are funded by the European Commission's H2020 Programme. It should be noted that given the ongoing status of these projects, the assessment is mainly based on preliminary results, as monitoring is still ongoing and quantitative results are not yet available. The paper discusses the drivers and barriers specific to PEDs, and highlights the challenges posed by technical complexities, financing aspects and social and legal restrictions. Conclusions are drawn regarding the concept of additionality and its implications for the wider development of PEDs as a response to the challenges of climate neutrality and energy system transformation in cities. We conclude that the additionality perspective provides valuable insights into the impact and potential of PEDs for societal goals and recommend this approach for use in the final evaluation of R&I projects involving PEDs using actual monitored data on PEDs. [ABSTRACT FROM AUTHOR]

Posthuman discourse calls for a fundamental shift away from modern anthropocentric thought. This shift stems from the reflection that many of the problems in the modern capitalist world, including climate change, are rooted in anthropocentric attitudes and ways of life. Amid rapid climatic and technological changes, transforming our way of thinking is essential. This paper argues that such a transformation is possible through the exploration of new subjectivities that incorporate the other, transforming the self in the process. It examines how 1930s Korean colonial modernist literature illustrates this search for new subjectivities. Based on this exploration, this paper also concretizes the tendencies and problems in our society, particularly concerning technological fascism, through recent Korean fiction and discusses the significance of the literary imaginations of 1930s colonial Korean modernism in the posthuman era. [ABSTRACT FROM AUTHOR]

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of mapping land cover types in Senegal and recognition of vegetation systems in the Saloum River Delta on the satellite images. Multi-seasonal landscape dynamics were analyzed using Landsat 8-9 OLI/TIRS images from 2015 to 2023. Two image classification methods were compared, and their performance was evaluated in the GRASS GIS software (version 8.4.0, creator: GRASS Development Team, original location: Champaign, Illinois, USA, currently multinational project) by means of unsupervised classification using the k-means clustering algorithm and supervised classification using the Support Vector Machine (SVM) algorithm. The land cover types were identified using machine learning (ML)-based analysis of the spectral reflectance of the multispectral images. The results based on the processed multispectral images indicated a decrease in savannas, an increase in croplands and agricultural lands, a decline in forests, and changes to coastal wetlands, including mangroves with high biodiversity. The practical aim is to describe a novel method of creating land cover maps using RS data for each class and to improve accuracy. We accomplish this by calculating the areas occupied by 10 land cover classes within the target area for six consecutive years. Our results indicate that, in comparing the performance of the algorithms, the SVM classification approach increased the accuracy, with 98% of pixels being stable, which shows qualitative improvements in image classification. This paper contributes to the natural resource management and environmental monitoring of Senegal, West Africa, through advanced cartographic methods applied to remote sensing of Earth observation data. [ABSTRACT FROM AUTHOR]

This paper mainly explores the feasibility of using desert sand (DS) and recycled aggregate in cement-stabilized bases. Recycled coarse aggregate (RCA) and DS serve as the substitutes of natural coarse and fine aggregates, respectively, in cement-stabilized bases. A four-factor and four-level orthogonal test is designed to analyze the unconfined compressive strength, splitting tensile strength, and compressive resilient modulus. Furthermore, this paper investigates the effects of cement content, fly ash (FA) replacement rate, RCA replacement rate, and DS replacement rate on the road performance of cement-stabilized bases composed of RCA and DS. The test results reveal that the performance of cement-stabilized bases with partial RCA instead of natural coarse aggregate (NCA) and partial DS instead of natural fine aggregate satisfies the road use. The correlation and microscopic analyses of the test results imply the feasibility of applying DS and recycled aggregate to cement-stabilized bases. This paper calculates and evaluates the life cycle of carbon emissions of desert sand and recycled coarse aggregate cement-stabilized macadam (DRCSM) and finds that both DS and RCA can reduce the carbon emissions of CSM, which has a positive effect on improving the environment and solving the climate crisis. It is hoped that this paper can offer a solid theoretical foundation for promoting the application of DS and recycled aggregate in road engineering. [ABSTRACT FROM AUTHOR]

Climate change has brought several natural disasters to South Africa in the form of floods, heat waves, and droughts. Neighbouring countries are also experiencing tropical cyclones, almost on a yearly basis. The insurance sector is faced with an increased level of climate change risk with individuals, corporates, and even the government approaching it for financial cover. However, with an increased level of competition in the insurance sector, (re)insurers must engage in massive product research and development. Therefore, this paper looks at the possibility of the insurance industry developing new products in the form of catastrophe resilience bonds (CAT R Bonds). A qualitative approach is used following content analysis of (re)insurers' product development policies, marketing documents, company reports, and risk management reports as well as the Conference of Parties 27 and 28 resolution papers. The findings reveal that (re)insurers' underwriting capacity, reinsurance protection, and innovative and creative product development increase because of CAT R Bonds. CAT R Bonds enhance the interaction between the capital market and money market, thereby giving speculative investors another investment option. Increased investment into new product development such as CAT R Bonds must continue in South Africa in pursuit of climate change resilience goals. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

This paper addresses the necessity of adopting renewable energy technologies in order to achieve sustainable development goals in light of increasing global challenges, with a particular focus on the current generation's well-being. It addresses the potential impacts of global crises, such as energy and food crises, on the transition to renewable energy. Using a descriptive and analytical approach, this paper examines the environmental and economic costs and benefits of renewable energy as well as the commitment of oil-producing countries to international environmental treaties. The research utilises an econometric model to analyse the relationship between sustainable development goals and global challenges. Data from the United Nations Conference on Trade and Development and the International Renewable Energy Agency are used to inform the analysis. The findings showed that the rights and well-being of current generations are currently maintained by the persistent use of fossil fuels in oil-producing nations. Fossil fuels continue to be, and may likely remain, the primary energy source in various sectors of development, despite their significant contribution to environmental and climate issues. The paper offers insights and recommendations for policymakers seeking to determine when government spending should best be allocated to renewable energy technologies, balancing national economic interests with international agreements. [ABSTRACT FROM AUTHOR]

In this paper, a method based on an improved intelligent bat algorithm (IIBA) in cooperation with a voltage and current sensor was applied in maximum power point tracking (MPPT) for a photovoltaic module array (PVMA), where the power generation performance of a PVMA was enhanced. Due to the partial shading of the PVMA from climate changes or the surrounding environment, multiple peak values were generated on the power–voltage (P-V) curve, where the conventional MPPT technology could only track the local maximum power point (LMPP), hence the reduction in output power of PVMAs. Therefore, the IIBA-based MPPT was proposed in this paper to solve such issues and to ensure the capability of a PVMA in tracking the global maximum power point (GMPP) and utilization for enhancing the output power of a PVMA. Firstly, the Matlab/Simulink software was used to establish a boost converter model that simulated the actual 4-series–3-parallel PVMA under different shaded conditions, where the P-V curve with 1-peak, 2-peak, 3-peak and 4-peak values were generated. Subsequently, the tracking paces of the conventional bat algorithm (BA) were adjusted according to the gradient of the P-V curve for a PVMA. At the same time, 0.8 times the maximum power point (MPP) voltage Vmp under standard test conditions (STCs) for a PVMA was set as the initial tracking voltage. Lastly, the simulation results proved that under different environmental impacts, the proposed IIBA led to better performances in tracking both dynamic and steady responses. [ABSTRACT FROM AUTHOR]

This paper considers some problems of the Late Palaeolithic and the Mesolithic periods in Northern Italy. More precisely, it deals with chronology, settlement pattern, techno-typological characteristics of knapped stone assemblages, and climatic changes that have taken place in the region from the discovery of the first sites in the 1960s and the excavations that soon followed to the present state of research. The Italian Alps, the Piedmont, and the valleys that descend from the high massifs have yielded important traces of Late Palaeolithic (Final Epigravettian) and Mesolithic (Sauveterrian and Castelnovian) sites and findspots, some of which are rock shelters that were settled throughout several millennia. This paper describes and discusses the evidence available mainly from two regions of the western and eastern Alpine arc, which are characterised by very different landscapes and yielded a great variety of archaeological features. [ABSTRACT FROM AUTHOR]

Environmental shock migration is a pressing phenomenon that became prominent with the continuous emergence of natural disasters and climatic shocks worldwide. In order to cope with these various disasters or shocks, people choose to migrate either internally, internationally, permanently, or temporarily; the paper named this phenomenon "environmental shock migration". For a holistic understanding, this paper analyzes the impact of environmental changes on migration and discusses the relevant consequences, specifically in the EU region. The paper demonstrates that natural disasters and climatic shocks as environmental changes lead to several forms of shock migration and differ depending upon the context of migration, the duration, the number of migrants, and the region. A comprehensive literature review will be provided to tackle the work of previous scholars and identify the gaps required to be studied in the future. [ABSTRACT FROM AUTHOR]