The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

The effects of climate change on yield and quality for different climate regions had high uncertainty. Risk assessment is an effective measure to assess the seriousness of the projected impacts for decision-makers. The modified quality model was used to simulate integrated impacts of climate change, environment and management on wheat yield and quality. Then, the Canadian Earth System Model (CanESM2) was used to forecast the daily meteorological data, and Statistical Down Scaling Model was used for downscaling. CERES-Wheat was combined with the forecasted meteorological data to simulate the future wheat yield and grain protein concentration (GPC). The risk of wheat yield and quality in three climatic regions of Shaanxi combined with two climate change scenarios of CanESM2 were assessed. Temperature increased 0.22-3.34 °C and precipitation increased 10-60 mm for RCP4.5 and RCP8.5. Elevated temperature and precipitation had positive effects on yield in all regions. The yield risk of most regions with climate change decreased 3.8%-25.1%. The GPC risk of all regions with climate change decreased 7.3%-27.2%. Irrigation decreased yield risk greatly in all regions, while had totally different effects for the three climatic regions. Yield risk with irrigation decreased 37.7%-52.1% in different climate. In contrast to previous studies, GPC risk with irrigation increased greatly 25.8%-28.9% in humid region, 3.9%-8.8% in sub-humid region, and decreased 37.7%-52.1% in semi-arid region. Climate change decreased yield risk and GPC risk together. While irrigation decreased yield risk greatly in all regions, had totally different effects for the three climatic regions.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

Fish is essential to feeding the world's population and provides hundreds of millions of people with a substantial amount of protein in their diets. Fish is one of the most affordable and readily available forms of animal protein, making up roughly 20% of total animal protein intake. It is simple to obtain these fish through cultivated or captured fisheries. However, the aquaculture industry is viewed as the main means of supplying the world's growing fish demand given the ongoing indiscriminate harvests in capture fisheries. Global aquaculture systems are under serious threats from climate change, which will have an impact on disease prevalence, species mix, water quality, and overall production. The possible impacts of climate change on freshwater aquaculture production and its consequences for the sustainability of the sector are reviewed in this paper. Rising temperatures, El Niño Southern Oscillation events, lowered dissolved oxygen, toxic algal blooms, altered rainfall patterns, water pH, altered salinity, and extreme weather events are a few of the aspects of a changing climate that have been discussed.

We develop and apply a systematic literature review methodology to identify and characterize the ways in which the peer-reviewed literature depicts how climate change adaptation is occurring in Australia. We reviewed the peer-reviewed, English-language literature between January 2005 and January 2018 for examples of documented adaptation actions. Our results challenge previous assumptions that adaptation action is not happening in Australia and describes adaptation processes that are underway. For the most part, actions can be described as preliminary or groundwork, with a particular focus on documenting stakeholder perspectives on climate change and adaptation, and modelling or scenario planning in the coastal zone, agriculture and health sectors. Where concrete adaptations are reported, they are usually in the agricultural sector and are most common in the Murray-Darling Basin, Australia’s food basket. The findings of the review advance our understanding of adaptation to climate change as a process and the need to consider different stages in the process when tracking adaptation.

The paper provides a methodological framework based on Multiple Criteria Decision Aid methods for determining relative regional vulnerabilities associated with forest fires that occurred during a given period. Different notions of ex-post vulnerability are defined based on the forest area burned and the frequency of forest fires, and their relation to the regions’ area and several socioeconomic characteristics. The methodology is applied to Greece and its administrative regions for the period 2000–2022. Linking the forest fire events with summer and spring temperatures and precipitation and using econometric count data analysis, the paper explores the climatic drivers of forest fire occurrence and provides projections of the expected change in the frequency of fires of specific size classes conditional on the evolution of mean seasonal regional temperature and precipitation according to IPCC scenarios. The results regarding relative regional vulnerabilities and expected forest fires could be useful in designing policies for preserving forests as natural capital and promoting sustainability.

The study assesses the direct effects of climate change by 2060, including extreme events, on the productivity of regional crop farming and livestock in Greece, and the broader socio-economic effects on the agri-food and other sectors. Different approaches (i.e., agronomic models, statistical regression models, equations linking thermal stress to livestock output) were combined to estimate the effects on productivity from changes in the average values of climatic parameters, and subsequently the direct economic effects from this long-term climate change. Recorded damages from extreme events together with climatic thresholds per event and crop were combined to estimate the direct economic effects of these extremes. The broader socio-economic effects were then estimated through input-output analysis. Under average levels of future extreme events, the total direct economic losses for the Greek agriculture due to climate change will be significant, from €437 million/ year to €1 billion/ year. These losses approximately double when indirect effects on other sectors using agricultural products as inputs (e.g., food and beverage, hotels, restaurants) are considered, and escalate further under a tenfold impact of extreme events. Losses in the GDP and employment are moderate at the national level, but significant in regions where the contribution of agriculture is high.

This paper delves into the essential role of local communities in mitigating climate change in the post-pandemic landscape, with a specific focus on Barangay Acmac, Iligan City, Philippines. Employing a qualitative research approach, the study integrates in-depth literature reviews, informal interviews with participants (B-Part 1 to B-Part 20), meticulous observations, and thematic analysis. The research has uncovered crucial insights, including variations in community climate change awareness that emphasize the necessity of comprehensive education and awareness campaigns. It highlights the significance of community-driven initiatives, adaptation, and resilience as key elements in addressing climate change. Collaborative efforts between local government officials and the community are showcased as effective instruments of climate change mitigation, yet challenges persist, including addressing the perceived powerlessness of some community members. The methodology, participants, and theoretical framework offer a robust foundation for exploring community responses to climate change. Drawing from a diverse theoretical framework, this study presents a comprehensive understanding of the climate change and pandemic intersection. The findings firmly establish that local communities are pivotal players in the global endeavor to mitigate climate change, underscoring the need for collective action, extensive education, and shared responsibility. The post-pandemic era presents a unique opportunity for local communities, policymakers, barangay officials, and residents to champion climate education, foster community-driven initiatives, and empower individuals to enact change at the grassroots level. The collaborative spirit observed in Barangay Acmac in 2022 serves as a model for communities worldwide, offering a blueprint for addressing similar challenges. Overall, this paper concludes with a resounding call to action, advocating for the recognition of local communities as the driving force in climate change mitigation, stressing that the power to combat climate change resides within these communities. The time for action is now, and local communities are the catalysts of this essential mission.

The purpose of this review is to investigate the role of legume cover crops in improving climate adaptability and water use efficiency in South African grassland systems. Climate change is posing significant obstacles to agricultural systems all over the world, which includes South Africa, where shortages of water and fluctuations are significant issues. Legume cover crops are growing in popularity as a long-term and cost-effective solution to these problems. The purpose of this review is to demonstrate the possible advantages of legume cover crops for enhancing climate resilience and water use efficiency in South African grassland systems, as well as the fundamental processes and present study findings. According to the outcomes, legume cover crops may boost soil water availability, nutrient cycling, carbon sequestration, and overall ecosystem productivity, resulting in increased climate resilience and water use efficiency. However, a variety of factors, including species selection, management practices, and environmental conditions, can all have an impact on the effectiveness of legume cover crops. With the concerted efforts, adaptation strategies of livestock farmers that seeks to maximise the potential of legume cover crops in South African grassland systems, it is critical to consider site-specific factors when establishing them. This review offers significant insights into the role of legume cover crops in climate resilience and water use efficiency, laying the groundwork for future research and agricultural practices.

This research provides an in-depth analysis of drought impacts in West Pokot, Kenya, utilizing both remote sensing surveys and focus group discussions. The study commenced by assessing the impact of drought on vegetation health via spatial sensors. It then utilized surveys and focus group discussions (FGDs) to engage farmers from the most drought-affected areas in Kacheliba and Sigor sub-counties. The analysis of remote sensing data from 1990 to 2022 highlighted that Sigor and Kacheliba experienced significant drought events during the years 1995, 2000, 2002, 2005, and 2009, and 1991, 1995, 2000, 2005, and 2019, respectively. This study delves into both the meteorological and socio-economic effects on local communities. Using the Multinomial Logistic Regression (MLR) model with the glm function, the research uncovered the impacts of so-cio-economic factors and agricultural practices on household livestock production. Additionally, the study employed Multiple Correspondence Analysis (MCA) to explore the dynamics between livestock production, community resilience, and crop production. The findings underscore the urgent need for tailored interventions to enhance community resilience in the face of increasing climatic extremes, serving as a blueprint for similar arid and semi-arid regions worldwide.

The important topic of climate change is discussed in this article, with a focus on the historical background and present effects. It draws attention to the differences between climate change and global warming and attributes the faster pace of climate change to human activity, specifically the release of greenhouse gases into the atmosphere. Agricultural practices, deforestation, and the combustion of fossil fuels are examined in conjunction with natural contributors like volcanic emissions. There is discussion of the far-reaching effects of climate change, such as increased temperatures, rising sea levels, harsh weather, and effects on water supplies. The article emphasizes how crucial it is to mitigate and adapt to the effects of climate change by putting in place climate-resilient infrastructure, switching to renewable energy sources, and lowering greenhouse gas emissions. While recognizing the difficulties involved, it examines several approaches, including nuclear energy, wind power, carbon capture and storage, and green building techniques. To successfully address the global challenge of climate change, the conclusion emphasizes the urgent need for joint efforts by scientists, environmentalists, communities, and governments.

Climate change is one of the most concerning global issues and has the potential to influence every aspect of human life. Like different components of society, it can impose significant adverse impacts on pavement infrastructure. Although several research efforts have focused on studying the effects of climate change on natural and built systems, its impact on pavement performance has not been studied extensively. Due to the weather effect the lifetime of pavement is getting lower on the other hand maintenance cost is getting higher and higher. The data has been collected from LTTP website and as a site The State of Texas has been considered. The primary objective of this project is to quantify the effect of temperature as well as precipitation changes on pavement response and performance prediction using the ARIMA model and develop a logistic regression model to analyze the forecast data.

The paper aims to introduce user-friendly modelling approaches to analyze how abiotic factors influence various trophic levels within the marine ecosystem, both naturally and through human impact. It specifically investigates the connections between environmental parameters (like temperature, salinity, and nutrients) and plankton along the Romanian Black Sea coast during the warm season (May-September) over a decade. Utilizing machine learning (ML) algorithms and data collected during this period, models were developed to project the proliferation of zooplankton. During the warm season, water temperature emerged as a significant factor affecting copepods and “other groups” zooplankton densities, while no discernible impact was noted on Noctiluca scintillans blooms. Salinity fluctuations notably influenced typical phytoplankton proliferation, with phosphate concentrations primarily driving widespread blooms. Two scenarios were explored for forecasting zooplankton growth: Business as Usual, predicting modest increases in temperature, salinity, and constant nutrient levels, and the Mild scenario, anticipating more substantial temperature and salinity increases while nutrients decrease significantly by 2042. The findings highlight that under both scenarios, Noctiluca scintillans displays notably high densities, with the second scenario projecting even higher values, surpassing the first by around 70%. These densities indicate characteristics of a eutrophic ecosystem, suggesting the potential implications of altered abiotic factors on ecosystem health.

We assessed machine learning techniques (MLTs) for downscaling global climate model’s precipitation to local level in Bolivia. The skill, assumptions and uncertainty of the process are analyzed. Additionally, future projections are delivered. For that, an ensemble of 20 global climate models (GCMs) from CMIP6, with random forest (RF) and support vector machines (SVM), is used on four zones (highlands, Andean slopes, Amazon lowlands and Chaco lowlands). The downscaled series’ skill is evaluated in terms of relative errors. The uncertainty is analyzed through variance decomposition. MLTs’ skill is adequate in most cases, especially for the highlands and the Andean slopes. Moreover, RF tends to outperform SVM. Stationary assumptions are robust in the highlands and Andean slopes. Perfect prognosis assumption is poor in the highlands and Andean slopes; topographical complexity appears to be the reason. Regarding uncertainties, MLTs are the dominant source. In future projections, the highlands show shorter dry spell lengths with more frequent but less intense high rainfall events and higher annual rainfall. The Andean slopes exhibit an increased annual rainfall with a reduction in the high precipitation intensities but an increased frequency. The Amazon lowlands present a decrease in annual rainfall, and the Chaco lowlands an increase.

Rising temperatures due to the climate change can significantly impact the frost/thaw condition of airport pavements in cold regions. This case study investigates the implications of the the warming temperatures on frost/thaw penetration and frost-heave of pavements for critical airports across Canada. To this end, different methods were used in the quantification process through climate change simulations considering the emission scenario RCP8.5 in a 20- and 40-year time horizon. The results show that climate change would have different design implications for airport pavements depending on their location. The predictions suggest a shallower frost penetration depth and possibly less frost-heave for the airports not underlain by permafrost, while airports over permafrost areas might experience an increase in thickness of the active layer ranging from 41 to 57 percent by 2061. Among the different methods used in this study, it was observed that some methods performed the best in predicting frost depth of fine soils, while others worked better with the frost depth prediction of coarse soils. The results indicate the need for more mechanistic models to provide a more realistic prediction of frost/thaw penetration as compared to the existing empirical models.

Climate information can help vulnerable populations anticipate disasters before they happen and enable communities prepare for and cope with them. A complementary log-log regression model based on quantitative study in coastal communities in Tanzania was used to assess the likelihood of the rural poor, rural non poor, urban poor, and urban non poor to receive early warning information about flood, drought and other disasters. Individuals in the urban poor category were 35% less likely to receive early warning information about flood, drought and other disasters whereas urban non-poor residents were 49% more likely to receive same. This disadvantage to the urban poor persists even when adaptive capacity, geographical location and socio-environmental factors are accounted. Nuclear households consisting of a male head and female partner who have children or not had higher likelihood of receiving early warning information on flood, drought and other disasters (OR = 1.47, p < 0.001) compared with their counterparts in female-centred households (no husband or male partner). Residents with tertiary education were more likely (OR = 1.91, p < 0.001) to report that they had received early warning information about flood, drought and other disasters compared with their counterparts without any formal education. This zero-order relationship was completed mediated by geographical location and socio-environmental factors in the multivariate model. The results underline the key role access to climate- and disaster-related information play in enhancing adaptive capacity to reduce vulnerability to natural hazards, as well as the importance of targeting the most vulnerable households in policy interventions to improve resilience in the face of a changing climate.

Strong convective storms can be a serious threat to modern society, influencing both the economy and human life. Thunderstorms can bring much-needed rain after a dry spell, but the nature of thunderstorm mostly causes damage due to high wind associated with it and heavy intensity rain that mostly causes quick overlandflow and flashfloods. The paper focused on the 2011 Pukkelpop event in Belgium where due to heavy thunderstorm a lot of financial damage occurred, and five casualties. In this paper we look into the basic elements that enforces the creation of a thunderstorm like CAPE and windshear. A representative grid has been taken from the Alaro-0 model of 12.5 km resolution for the analysis of the thunderstorm over Belgium which is detailed out in the methodology. The model runs of Alaro-0 from Royal Meteorological Institute of Belgium (RMI) is used for historical and future years for CAPE and Shear. We look into STEnv which is a composite number that can provide some insight on occurrence of thunderstorm, and STEnv is when CAPE*Shear exceeds certain threshold. In this study the threshold has been chosen as 97%. Only summer months have been taken into account into this study as summer(s) has the most thunderstorm in Belgium. The analysis of CAPE and STEnv over historical period (1977-2005), near future (2041-2069) and far future (2071-2099) shows significant increase in occurrence of thunderstorm in the 2071-2099s, specially in extreme cases such as 97% and 99% quantile. CAPE (J/Kg) increases in all future scenarios compared to the historical period. In 2071-2099s, CAPE increases from 2100 J/Kg to 2300 J/Kg (90% quantile) and from 3500 J/Kg to 3900 J/Kg (99% quantile) compared to the historical period. The number of STEnv increases from 300 to 378 in top 10% storm case (90% quantile), 158 to 218 in top 5% storm (95% quantile), 97 to 153 in top 3% storm (97% quantile) and 33 to 66 in top 1% storm (99% quantile) with a 90% confidence interval overall. Shear mostly remains unchanged. The study also shows spatial variation of CAPE, shear and STEnv over Belgium for present and future scenarios in different extremities (90%, 95%, 97% and 99% quantiles). There is a good indication that increase in CAPE translates to increase in STEnv, which is an accepted measure to predict occurrence of thunderstorm. Future climate change also amplifies the occurrence of thunderstorm, which is coherent with relevant studies. The uncertainty related to the study can be reduced with more detailed dataset and involvement of numerical weather prediction models beyond data statistics.

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating degree-day (HDD), the cooling degree-day (CDD) and the HDD+CDD were computed from an ensemble of 7 high-resolution bias-corrected simulations attained from EURO-CORDEX under RCP4.5 and RCP8.5. These three indicators were analyzed for 1971-2000 (from E-OBS) and 2011-2040 and 2041-2070, under both RCPs. Results show that the overall spatial distribution of HDD trends for the 3 time-periods points out an increase of energy demand to heat internal environments in Portugal's northern-eastern regions, most significant under RCP8.5. It is projected an increase of CDD values for both scenarios; however, statistically significant linear trends were only found for 2041-2070 under RCP4.5. The need for cooling is almost negligible for the remaining periods, though linear trend values are still considerably higher for 2041-2070 under RCP8.5. By the end of 2070, higher amplitudes for all indicators are depicted for southern Algarve and Alentejo regions, mainly under RCP8.5. For 2041-2070 the Centre and Alentejo (North and Centre) regions present major positive differences for HDD(CDD) under RCP4.5(RCP8.5), within the 5 NUTS II regions predicting higher heating(cooling) requirements for some locations.

The relationship between Climate Change and Water is an obvious and key issue within the Sustainable Development Goals. This study aims to investigate the social representation created around this relationship in three different territorial contexts in order to evaluate the influence of the territory on the perception of the risk of Climate Change and its relationship with water. By means of a questionnaire completed by 1709 university students, the climatic literacy of the individual was evaluated in order to relate it to other dimensions on the relationship between Climate Change and Water (information, training previous on climate change and pro-environmental attitudes) in their different dimensions in three different territorial contexts. The results show that the socio-cultural context influences the social representation of Climate Change, but not from the climatological condition, so that it is reasonable to think that the social representation of this relationship is favoured by a common culture around this relationship.

Wildfire is the main disturbance in forested ecosystems of southern Europe and is due to complex interactions between climate-weather, fuels and people. Warmer and drier conditions projected in this region are expected to profoundly affect wildfires, which will impact ecosystems and humans. We review the scientific literature addressing the assessment of climate change impacts on wildfires in southern Europe, with a twofold objective: (i) report the trends in wildfire danger and activity projected under warming climate in southern Europe and (ii) discuss the limitations of wildfire projections under the specific biogeographical context of southern Europe.We identified 22 projection studies that examined future wildfire danger or wildfire activity at local, regional or continental scale. Under the scenario with the highest greenhouse gas emissions, we found that projections studies estimate an increase in future fire danger and burnt areas varying, on average, from 2 to 4 % and from 15 to 25 % per decade, respectively. Fire-prone area expansion to the north and to Mediterranean mountains is a concern, while climate-induced burnt area increase might be limited by fuel availability in the most arid areas. While all studies agreed on the direction of changes, further comparisons on the magnitude of increase remained challenging because of heterogeneous methodological choices between projections studies (climate models, projection period, spatial scale and fire metrics). We then described three main sources of uncertainty that may affect the reliability of wildfire projections: climate projections, climate-fire models, and the influences of fuel load/structure and human related factors on the climate-fire relationships. We finally suggest research directions to address some of these issues for the purpose of refining fire danger and fire activity projections in southern Europe.

This article explores the intersection of innovative leadership and climate change, aiming to provide outstanding contributions to the existing body of knowledge in this field. The article identifies the critical role of innovative leadership in driving sustainable solutions and strategies for addressing climate change. It examines the defining characteristics and behaviors of innovative leaders and explores how their transformative leadership approaches can create a positive impact on climate change mitigation and adaptation efforts. The article also highlights the importance of fostering innovation within organizations and societies to tackle the complex challenges posed by climate change. Through a comprehensive review of relevant literature and case studies, this article presents novel insights, theoretical frameworks, and practical implications for policymakers, organizations, and individuals involved in climate change leadership.

Climate change is expected to increase the occurrence of droughts with the hydrology in alpine systems being largely determined by snow dynamics. In this paper we propose a methodology to assess the impact of climate change on both meteorological and hydrological droughts taking into account the dynamics of the snow cover area (SCA). We will also analyse the correlation between these types of droughts. We have generated ensembles of local climate scenarios based on regional climate models (RCMs) representative of potential future conditions. We have considered several sources of uncertainty: different historical climate databases, simulations obtained with several RCMs, and some statistical downscaling techniques. We then used a stochastic weather generator (SWG) to generate multiple climatic series preserving the characteristics of the ensemble scenario. These were simulated within a cellular automata (CA) model to generate multiple SCA future series. They were used to calculate multiple series of meteorological drought indices, the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)) and a novel hydrological drought index (Standardized Snow Cover Index (SSCI)). A linear correlation analysis was applied to both types of drought to analyse how they propagate and the time delay between them. We applied the proposed methodology to the Sierra Nevada (southern Spain) where we estimated a general increase in meteorological and hydrological drought magnitude and duration for the horizon 2071-2100 under the RCP 8.5 emission scenario. The SCA droughts also revealed a significant increase in drought intensity. The meteorological drought propagation to SCA droughts is reflected in an immediate or short time (1 month), obtaining significant correlations in lower accumulation periods of drought indices (3 and 6 months). This will allow us to obtain information about meteorological drought from SCA deficits and vice versa.

Môle Saint-Nicolas, like all other communes in the Republic of Haiti, faces increasing climate variability, impacting agricultural production and water resources. Consequently, there is a pressing need for adaptation to these climatic changes. This research aims to showcase the adaptation strategies deployed by farmers to cope with the increasing climate variability. Surveys were conducted through group and individual discussions with a randomly selected cohort of 150 farmers. Two types of analysis were performed: quantitative and qualitative. The quantitative data analysis was conducted using SPSS software. The findings reveal that farmers have perceived changes in rainfall patterns, temperature, wind, and their environment. These changes manifest as irregular rainfall, higher temperatures, prolonged drought periods, violent winds accompanied by rain, premature cessation of rains, and reduced flow from water sources. In response, the most common adaptation strategies developed include selecting new cultivars, early-maturing varieties, crop rotation and diversification, canal dredging, new soil preparation methods, upstream water source protection, and micro-watershed management. The significance of this research lies in its contribution to enhancing farmers' adaptive capacities by alerting stakeholders in the irrigated perimeters about the consequences of climate change, thereby incorporating the real needs of farmers in future projects.

The Earth's water resources, totaling 1.386 billion cubic kilometers, predominantly consist of saltwater in oceans. Groundwater, plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as drinking water source and 60–70% for irrigation. Climate change, with temperature increase and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies, employ numerical models to assess climate change impacts on groundwater recharge that could help in management of Groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. The review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography, aquifer properties, and groundwater contamination processes and gradual sea level rise scenarios and realistic representations of the region of study. The advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence, could assist in the efforts to improve models for assessing the impacts of climate change on hydrological.

The impact of climate change on water resources is a global issue with significant regional implications. The Ghba subbasin has experienced a higher socioeconomic change. In this paper, we assess the potential impact of climate change and human activity on water supply and demand in the Ghba subbasin of Ethiopia. We then evaluate the effectiveness of regional adaptation strategies for water supply management under these conditions. To do this, we use the statistical downscaling model (SDSM) and the water assessment and planning tool (WEAP) to simulate and analyse future water conditions. After running the model through a calibration and validation process, minimum (Tmin) and maximum (Tmax) temperatures, water demand and unmet water demand were projected for 2100 horizon, using different climate change scenarios. The results showed that the model's performance, calibration, and validation were all satisfactory. The analysis showed that, under A2 and B2 emission scenarios of the Intergovernmental Panel on Climate Change (IPCC), the mean precipitation will increase by 31% and 26%, respectively. The projected mean Tmax and Tmin will be warmer than the baseline period, with Tmax increasing by 1.5°C (A2) and 1.3°C (B2), and Tmin by 1.7°C (A2) and 1.5°C (B2) by 2100. The results also illustrate that in all scenarios, water consumption would rise and that this need will not be satisfied, and the pressure on water resources will intensify, resulting in a water shortage. The findings show that future water demand under the influence of climate change is projected to exceed 210 million cubic meters (MCM) by 2100. The findings show that while the evaluations of the recommended adaption techniques are effective, they are not enough to guarantee the Ghba subbasin's water sustainability.

Rain-fed agriculture remains the source of employment for a majority of Ethiopian population, particularly in Dorebafana District, where annual rainfall is low. Perception of climate change and variability supported by local knowledge has helped to advance understanding of climate change and its impacts on agricultural land-use systems. Thus, the overall objective of this study was assessing farmers’ perception of climate change and variability and its impact on agriculture in Umbulo Kajima and Lebu Koromo kebeles of Dorebafana, Sidama region of Ethiopia. A total of 88 sample households from the two kebeles, farmers’ perception were compared with historical climatic data from the closest weather station of the study area. The household survey, focus group discussions and field observation were used as primary data sources in the study area. The data was analyzed by using descriptive statics in Statistical Package for the Social Sciences and multinomial logistic regression model. As data showed, there was the declining and high variability of rainfall in the last three decades In addition, the maximum annual rainfall was observed in 1998, 1755.4 mm and the lowest annual rainfall was recorded in 2015, 537.4 mm in the study area. The focus group discussions and key informant interviews further supported the idea that rainfall in the research area has been falling and very variable over the previous three decades. The finding showed that, temperature increased by 0.1oC over the previous three decade, and socioeconomic factors such sex, age, farming experience, knowledge of the climate, market access, and agro-ecology had an impact on farmers' perceptions of climate change and its impact in agriculture. Therefore awareness creation, increase educational level, sharing experience, scaling up best practice and using new technologies are the best alternatives to minimize the adverse effects of climate change.

Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.

Triticale is recognized worldwide due to its high protein and lysine content, high production capacity and adaptability to biotic and abiotic stress conditions, these qualities being taken over from wheat and rye. Triticale is widely used in various fields such as animal feed in various forms, in medicine, the bakery, beer, alcohol, cellulose, bioethanol industry and many others. Thus, the demand for triticale grains is increasing, and this has led to the research and improvement of culture technology to obtain superior products, both quantitatively and qualitatively. The purpose of this study was to identify the best varieties of triticale cultivated in the north-west of Romania, sown in different plots and fertilized on the ground or additionally, the study being carried out over a period of two years at the Livada Agricultural Research and Development Station, Satu Mare county. The study was located on an acidic soil with a pH between 5.19 and 6.65 and a humus content of 2.82%. The climatic conditions in the reference period were extremely variable, in the first year a deficit of more than 90 mm/m2 of precipitation was registered, and in the second year of the study, an increase of more than 34 mm/m2. The effects of additional fertilization were influenced by the level of precipitation, so in the experimental variants additionally fertilized, lower productions were obtained compared to the variants fertilized only on the soil. Compared to the Negoiu control, the Utrifun variety proved to be the most productive, but this will be proven in the following years of study, under different climatic conditions.

This study analyzes future hydrological droughts in LCKW using the SWAT model and data from 2010-2021, evaluating the Streamflow Drought Index (SDI) for 5, 10, 25, and 50-year return periods (RP) for 2029 and 2039 under RCP4.5 and RCP8.5 scenarios. The model shows high accuracy (R² = 0.82, NSE = 0.78). Under RCP4.5, streamflow may increase by 34.74% and 18.74%, while RCP8.5 predicts significant decreases of 37.06% and 55.84%. Historical data reveal frequent short-term droughts during SDI-3, notably in 2014–2016 and 2020–2021, with SDI-6 indicating less frequent but severe droughts, especially in 2015 and 2020. Future projections under RCP8.5 suggest wors-ening drought conditions in 2029 and 2039, with critical drought periods from January to April and November. Wavelet analysis indicates a high risk of severe hydrological drought in LCKW due to low annual recurrence rates, with the highest drought severity over a 50-year RP. The study high-lights an increasing likelihood of frequent and severe droughts, particularly under high emission scenarios such as RCP8.5, which could result in significant water shortages and ecosystem disrup-tions. It emphasizes the significance of adaptive water resource management strategies in mitigating negative impacts on water security and ecosystem health.

Fundamental principles of modern cities and urban planning are challenged during the COVID-19 pandemic, such as the advantages of large city size, high density, mass transport, free use of public space, unrestricted individual mobility in cities. These principles shaped the development of cities and metropolitan areas for more than a century, but currently, there are signs that they have turned from advantage to liability. Cities Public authorities and private organisations responded to the COVID-19 crisis with a variety of policies and business practices. These countermeasures codify a valuable experience and can offer lessons about how cities can tackle another grand challenge, this of climate change. Do the measures taken during the COVID-19 crisis represent a temporal adjustment to the current health crisis? Or do they open new ways towards a new type of urban development more effective in times of environmental and health crises? We address these questions through literature review and three case studies that review policies and practices for the transformation of city ecosystems mostly affected by the COVID-19 pandemic: (a) the central business district, (b) the transport ecosystem, and (c) the tourism-hospitality ecosystem. We assess whether the measures implemented in these ecosystems shape new policy and planning models for higher readiness of cities towards grand challenges. And how, based on this experience, cities should be organized to tackle the grand challenge of environmental sustainability and climate change.

Climate change and net zero are expected to have a significant impact on eco-nomic activity in developing countries, and thus, on the financial cash flow of organizations. In this paper, we propose a procedure for assessing the financial impact of climate change on organizational cash flow in developing countries. Our study contributes to the research on scenario-based climate change impact analysis. The applied research design is exploratory and mainly qualitative, constructing financial impact scenarios combined with narratives to determine the impact of climate change on individual cash flow line items. The narra-tives rationalize cash flow variations and enrich the estimates by adding expert knowledge, in the form of financial micro-stories and descriptions to the pro-posed procedure. We present a hypothetical citrus farming company in a de-veloping country to demonstrate the application of the proposed measurement procedure. The results obtained suggest that (1) the procedure is practical be-cause financial cash flows are known and widely used in financial analysis and because they can be implemented in a spreadsheet; that (2) the procedure pro-vides flexibility because it can be adapted to suit the specific needs of different companies, depending on a selected climate change scenario, the company’s exposure to climate change, its resilience and vulnerability; (3) that the prac-tice of thinking in terms of financial worst-case, base-case and best-case sce-narios, which reflect different levels of uncertainty, helps to model the finan-cial impacts of climate change and provides a forward-looking perspective on how much a company’s cash flow could change.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

Frequent employee resistance to innovation is one of the main barriers of change failure in a health care organization and one of the negative stimuli of employment relationships. Identifying the reasons of resistance is a topical issue for every organization, as the speed of change can affect their competitiveness. Consequently, it is helpful not only to know the causes of potential resistance but also to be ready to control any implicit opposition. The organizational climate and the attitude of the staff play an important role in understanding and accepting innovation. Purpose of the study is to develop a model, which would facilitate the choice of an appropriate strategy necessary to enable the health care organization to eliminate or at least to reduce resistance to often essential innovative changes. The article analyses the root causes of resistance and identifies strategies that help to mitigate or eliminate staff resistance for innovation. Use of suggested model can make easier reducing staff resistance to change processes and thus speed up the implementation of innovations. This methodology can be used to eliminate the reasons for staff resistance to change in health care institutions of different countries, but it was tested in Lithuania and achieved good enough results.

The Sangu river basin contributes to national economy significantly; however, exposures to water-related hazards frequently. As it is expected that water-related disasters will increase manifold in the future due to global warming, the Government of Bangladesh has formulated Bangladesh Delta Plan 2100 (BDP-2100) to enhanced climate resilience. Accordingly, this study assessed the hydro-meteorological characteristics of the Sangu River basin under changing climate. This study scientifically selected five General Circulation Models (GCMs) to include the model climate sensitivity and statistically bias-corrected their outputs. The Water and Energy Budget-based Rainfall-Runoff-Inundation (WEB-RRI) model was used to simulate the hydrological responses of the basin. The analysis of five GCMs under the Representative Concentration Pathway (RCP8.5) revealed that all selected GCMs estimate a 2-13% increase in annual rainfall and a 3-12% increase in annual discharge in the near-future (2025-2050), whereas four GCMs project an 11-52% increase in annual rainfall and a 7-59% increase in annual discharge in the far-future (2075-2100). The projected more frequent and intense increased extreme rainfall and flood occurrences in the future indicate an increase in flood disaster risk, whereas increased meteorological and hydrological drought in the future reflects a scarcity of water during dry periods. The number of projected affected people shows an increasing trend due to the increased inundation in the future. However, increasing trend of transpiration indicates agricultural productivity will increase in the future. Policymakers can utilize this evidence-based information to implement BDP-2100 and to reduce the disaster risks in the basin.

In the context of climate change in West Africa characterized by a reduction of precipitation, this study was conducted to evaluate the impact of climate change on water resources from now to the end of the 21st century in the transboundary watershed of the Sassandra River shared by Guinea and Côte d’Ivoire. Historical and future climate (Representative Concentration Pathways or RCPs 4.5 and 8.5 scenarios) data were projected with the model. The Abdus Salam ICTP RegCM4 was used. The hydrological modeling of the river basin was carried out with the conceptual hydrological model, GR2M. This model is a monthly time steps model that allows the assessment of the discharge of the Sassandra River for each climate scenario according to the 2030 (2021–2040), 2050 (2041–2060), 2070 (2061–2080), and 2090 (2081–2100) horizons. The results showed a reduction of the annual discharge when compared to the baseline (1961–1980). For the RCP 4.5, the observed values went from –1.2% in 2030 to –2.3% in 2070 and rose to –2.1% in 2090. Concerning the RCP 8.5, we saw a variation from –4.2% to –7.9% in the 2030 and 2090 horizons, respectively. With the general decrease of rainfall in West Africa, it is appropriate to assess the impact on water resources on the largest rivers (Niger, Gambia, and Senegal) that irrigate the Sahelo-Saharian zone.

Last Chance Tourism (LCT) is an increasingly popular phenomenon whereby tourists seek encounters with vanishing landscapes, cultures, and endangered species. However, there are concerns that it is not sufficiently ecologically informed, has a large carbon footprint, and may put further pressure on vulnerable ecosystems and communities. The Arctic has emerged as a major global frontier for LCT, and at the same time is at the forefront of disruptive and accelerating climate change. Here a review of important LCT literature is combined with a review of key insights from the concept of Ecological Grief, which calls for explicitly mourning the losses of formerly ecologically rich landscapes, species diversity, and traditional knowledge. While there is currently insufficient engagement with grief and mourning in LCT, Ecological Grief can provide a new research focus as well as a pathway to share empathy, concern, and sorrow between scientists, communities, and visitors—thereby offering an alternative way to critically reflect upon our connections with the vanishing cryosphere in the Anthropocene.

Climate change, one of the severest environmental threats to humankind, disproportionately affects low-income developing countries in the global South. Having no feasible mitigation alternatives, these countries resort to adaptation efforts in addressing the climate perturbations. Climate change adaptation (or resilience) is primarily a localized course of action that depends on individuals, social networks, economies, ecologies, political structures, and the capabilities of all those to work collectively to absorb, learn from and transform in the face of new realities. With a view to controlling the floods that shattered the life and economy of the then East Pakistan, which is Bangladesh now, during the mid-twentieth century, the coastal embankment project (CEP) was instituted as an adaptation strategy to natural disasters in southwestern Bangladesh. Based on the qualitative analysis of primary and secondary data, this paper seeks to critically evaluate the efficacy of the CEP in terms of the space for feasible action and ecological modernization. The findings of this research indicate that the CEP has become an unrealistic venture that hinders the growing economic activity of shrimp aquaculture in the area. This paper is expected to contribute to generate further theoretical and empirical discourse on evaluating similar development projects around the globe.

Abstract: Increasing population and urbanization are affecting human health and comfort. In order to get rid of these affects, mankind is changing its enviroment and looking for new life areas. This study investigates the influence of Land Cover Change (LCC) and Normalisied Densly Vegetation Index (NDVI) on Land Surface Temperature (LST) of Fethiye-Göcek Specially Protected Area (SEPA) in easterm mediterranean basin. In the study LCC, NDVI and LST were drived from landsat 5, 7 and 8 satellite image of resolation at 30x30 m acquired between 1995-2020. LST were computed based on Land Use/Land Cover (LULC) types. The Corine Index were used for determination of land uses. The results indicated that water, forest and maquia lands decreasing while urban fabric and bare lands are increasing depend upon the urbanization and forest fires in the basin. These changes in LULC widened the temperature differences between the urban and rural areas. The change in LST is associated with changes in constructional materials in urban land and in vegetation abundance both in the urban and rural areas. Vegetation has an important factor in the temperature of different land covers. That produces warming trend in temperetaure in built-up areas it causes to keep other lands warmer in cold weather. Another important result is affective Urban Heat Island (UHI) on climate change based on the impact of urbanization and land cover changes. Significantly possitive correlation were found between the urbanization rate, population and built-up area and warming rate of average air temperature and so the LST.

In the context of global warming and increasing scarcity of fresh water resources, it becomes significant to evaluate the contribution and evolution of non-rainfall waters such as dew. This study therefore aims to evaluate the relative dew and rain contributions in three sites of south-western of Madagascar (Ifaty, Toliara and Andremba), a semi-arid region which suffers from a strong water deficit. The studied period is 1/1991 – 7/2023, with extrapolation to 8/2033. Dew is calculated from meteo data by using a well-established energy model. The extrapolation of dew and rain follows an artificial neural network approach. It is found that dew forms regularly (2-3 days in average between events), in contrast to rain (10-15 days). The evolutions of dew and rain are similar, with an increase from 1991 to 2000, a decrease up to 2020 and a further increase until 2033. These oscillations follow the Indian Ocean dipole variations and should be influenced by the climate change. Dew contribution to the water balance remains modest on a yearly basis (3-4%) but is important during the dry season (Apr.-Oct.), up to 30%. Dew therefore appears to be a reliable and sustainable resource for plants, small animals and population, especially during droughts.

Enhanced food and nutrition security remains a primary goal for every community. Several interventions have been promoted in dry areas to improve issues on food and nutrition security. However, studies on the level of knowledge, cultural norms, perceptions and attitudes that are key drivers in adoption and uptake to highlight gaps and provide evidence for improvement are limited. This study investigated variables influencing the adoption and implementation of an integrated crop-dairy goat farming system in Elgeyo Marakwet. A descriptive cross-sectional survey entailing qualitative and quantitative approaches among farmers practicing integrated farming was undertaken. A thematic questionnaire was used to collect quantitative data, while key informant interviews and focus groups discussions were used in qualitative research. This study utilized the multi-stage sampling procedure to sample the farmers and sample size was calculated based on Krejcie and Morgan table. Data analysis for quantitative data was done using SPSS software while qualitative data utilized N-vivo software The findings show that farmers have knowledge on the integrated farming system. Age, level of education, land size, gender, perceptions and attitudes influence adoption. Small animals like dairy goats are associated to women in this community hence increasing their participation in access, control and decision making of agricultural resources. The key findings of this study provide baseline data that can form evidence to help inform policy on the indicators contributing to adoption of integrated crop-dairy goat systems to enhance food and nutrition security

Mangrove forests store and sequester large area-specific quantities of blue carbon (C_org). Except for tundra and peatlands, mangroves store more C_org per unit area than any other ecosystem. Mean mangrove C_org stock is 738.9 Mg C_org ha⁻¹ and mean global stock is 6.17 Pg C_org, which equates to only 0.4–7% of terrestrial ecosystem C_org stocks but 17% of total tropical marine C_org stocks. Seagrasses sequester more C_org per unit area than mangroves (179.6 g C_org m⁻²·a⁻¹) but twice the C_org sequestered by mangroves globally (15 Tg C_org a⁻¹). Mangroves sequester only 4% (range 1.3–8%) of C_org sequestered by terrestrial ecosystems, indicating that mangroves are a minor contributor to global C storage and sequestration. CO₂ emissions from mangrove losses equate to 0.036 Pg CO₂-equivalents a⁻¹ based on rates of C sequestration but 0.088 Pg CO₂-equivalents a⁻¹ based on complete destruction for conversion to aquaculture and agriculture. Mangrove CO₂ emissions account for only 0.2% of total global CO₂ emissions but 18% of CO₂ emissions from the tropical coastal ocean. Despite significant data limitations, the role of mangrove ecosystems in climate change mitigation is globally insignificant but may be more significant and effective at the national and regional scale.

Modern engineering faces challenges in ensuring technical standards for service, durability, and sustainability. Political, administrative, and budgetary factors, coupled with climate change, pose tasks to structural integrity, affecting industries and economies. Marine infrastructures represent a strategic asset of the country as it handles a large part of the economic exchanges. This article analyzes five essential factors that play a fundamental role in the performance analysis of coastal structures: Chloride-induced corrosion, degradation models, maintenance strategies, monitoring, and climate change. Starting with reinforcement corrosion, considered as the main cause of distress, particularly in coastal zones for the long-term behavior of structures. Additional pressure from the influences of climate change is becoming evident and extreme, leading to reduction in capacity. To guarantee the lifespan, degradation models contribute by estimating the long-term performance of the asset as a strategic piece to the development of effective maintenance solutions. Additionally, quantifying the condition of the structure from monitoring data, plays a crucial part that provides information on the current situation of the structure. Finally, this review summarizes the challenges associated with the maintenance of aging marine structures considering aspects such as corrosion, monitoring, and the future challenges this area will face due to climate change.

In the field of climate change adaptation, the future matters. Amongst others, river futures justify the way adaptation projects materialize in rivers. In this paper, we challenge the ways in which dominant paradigms and expert claims monopolise the truth concerning policies and designs of river futures, side-lining and delegitimizing alternative river futures. Currently, limited work is done to critically reflect on the power of river futures in the context of climate change adaptation. We conceptualized the power of river futures through river imaginaries: collectively performed and publicly envisioned reproductions of riverine socionatures, mobilized through truth claims of social life and social order. Through the Border Meuse project case study, a climate change adaptation project in a stretch of the river Meuse in the south of the Netherlands and a proclaimed success story of climate adaptation in Dutch water management, we elucidated how three river imaginaries: a modern river imaginary, a market-driven imaginary and an eco-centric river imaginary, merged and materialized as an eco-modern river imaginary. Importantly, not only the river futures merged, also their aligned truth regimes merged. To this end, we argue that George Orwell’s famous quote “Who controls the past, controls the future: who controls the present, controls the past” can be extended to ‘Who controls the future, controls how we see and act in the present, and how we rediscover the past’.

The main purpose of this article is to identify key areas of research on climate change in the context of the SDGs, focusing on the potential development impacts on Bolivia and Paraguay. Application of the Delphi technique with the involvement of a panel of experts allowed the consolidation of different perspectives and knowledge on climate change, focusing on those that experts considered to have the greatest potential impact on the regions. The results of this study constitute a valuable guide for decision-makers and funding bodies, highlighting research areas that could have a significant impact at the national and regional levels, as well as for researchers, identifying specific research areas crucial for regional development and climate change mitigation.

The potential impacts of climate change on the distribution of tuna in Pacific Island Countries’ Exclusive Economic Zones have yet to be investigated rigorously, and so their persistence and abundance in these areas remain uncertain. Here, we estimate optimal fisheries areas for four tuna species; Albacore (Thunnus alalunga), Bigeye (Thunnus obesus), Skipjack (Katsuwonus pelamis), and Yellowfin (Thunnus albacares). We consider different climate change scenarios, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, within a set of tuna catch records in the Exclusive Economic Zone of Tonga. Using environmental and CPUE datasets, species distribution modelling estimated and predicted these fisheries areas in the current and future climatic scenarios. Our projections indicate an expansion in area and a shift of productive areas to the southern part of this Exclusive Economic Zone of Tonga. This is an indication that future climatic scenarios might be suitable for the species under study however, changes in trophic layers, ocean currents and ocean chemistry might alter this finding. Information provided here will be relevant in planning future national actions towards proper management of these species.

Coastal areas are highly vulnerable to climate change hazards (e.g., sea-level rise, flooding, coastal erosion), which can lead to significant impacts at the ecosystem and societal level. Interest in Ecosystem-based Adaptation (EbA) is gaining importance due to its potential multiple benefits, including social and environmental aspects, when compared to more traditional approaches such as hard engineering interventions. When assessing EbA strategies, further understanding of the nature-society functions, processes, values, and benefits is needed to increase its application. This study contributes to a better knowledge of EbA by developing a systematic literature review of studies performing socio-economic assessments of climate change adaptation in coastal areas. The analysis of 54 publications revealed that most of the studies assessed adaptation solutions through cost-benefit analysis, followed by multi-criteria analysis, and other techniques. Hybrid adaptation strategies based on different combinations of hard, soft and EbA interventions were considered as potential optimal solutions in a significant part of the assessments. This study suggests the potential co-benefits of EbA in the form of ecosystem services, livelihood diversification or biodiversity conservation, but also stresses the need for further research on this topic, as well as on evaluating how EbA perform in the long-term under climate changing conditions scenarios.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Climate change, recognized as a global crisis, is not only altering our environment but also significantly impacting human health. Particularly, its influence on non-communicable diseases (NCDs), a leading cause of global mortality, is becoming increasingly evident yet underexplored. This review aims to synthesize current research on the impact of climate change on NCDs, addressing a critical gap in our understanding of how environmental changes affect human health. We examine the complex interplay between climate change and NCDs, drawing insights from recent studies that highlight the adverse effects of climate variables on chronic diseases, such as cardiovascular and kidney diseases, and the role of food and nutrition security in this nexus. Furthermore, the review explores the disproportionate impact on vulnerable regions and populations, particularly in Pacific Island countries and territories, underscoring the urgent need for context-specific solutions and a cross-sectoral approach. By integrating findings from various disciplines, this review aims to inform policy and public health interventions, highlighting the necessity of collaborative efforts to mitigate the burgeoning burden of NCDs in a rapidly changing climate.

We developed an artificial neural network as an air quality model and estimated the scope of the impact of climate change on future (until 2064) summertime trends of hourly Ozone (O3) concentrations at an urban air quality station in Tehran, Iran. Our developed scenarios assume that present-time emissions conditions of O3 precursors will remain constant in the future. Therefore, only the impact of climate change on future O3 concentrations is investigated in this study. GCM projections indicate more favorable climate conditions for O3 formation over the study area in the future: the surface temperature increases over all months of the year, solar radiation increases, and precipitation decreases in future summers, and summertime daily maximum temperature increases about 1.2 ∘C to 3 ∘C until 2064. In the scenario based on present-time O3 conditions in 2012 summer without any axceedances, the summertime exceedance days of 8-hr O3 standard are projected to increase in the future by about 4.2 days in the short term and about 12.3 days in the mid-term. Similarly, in the scenario based on present-time O3 conditions in 2010 summer with 58 days of exceedance from 8-hr O3 standard, exceedances are projected to increase about 4.5 days in the short term and about 14.1 days in the mid-term. Moreover, the number of Unhealthy and Very Unhealthy days in 8-hr AQI is also projected to increase based on pollution scenarios of both summers.

Climate change has significant implications for agriculture, especially in viticulture, where temperature plays a crucial role in grapevine growth. Mendoza's climate is ideal for producing high-quality wines, but 21st-century climate change is expected to have negative impacts. This study aimed to evaluate the effects of increased temperature on the phenology, physiology, and yield of Malbec, Bonarda, and Syrah. A field trial was conducted over two seasons (2019-2020 and 2020-2021) in an experimental vineyard with an active canopy heating system (+2-4ºC). Phenological stages (budburst, flowering, fruit set, veraison, harvest), shoot growth (SG), number of shoots (NS), stomatal conductance (gs), chlorophyll content (CC), chlorophyll fluorescence (CF), and water potential (ψa) were measured. Additionally, temperature, relative humidity, light intensity, and canopy temperature were recorded. Heat treatment advanced all phenological stages by approximately two weeks, increased SG and NS, and reduced gs and ψa during the hottest months. CC and CF remained unaffected. The treatment also resulted in lower yields, reduced acidity, and increased °Brix in both seasons. Overall, rising temperatures due to climate change advance the phenological phases of Malbec, Syrah, and Bonarda, leading to lower yields, higher °Brix, and lower acidity, although physiological variables remained largely unchanged.

The contextual and risk perception of climate change plays a critical role in an individual’s decision-making process. It could also help people to respond appropriately to the consequences of global climate change and eventually take necessary adaptation actions. However, the perceptions of climate change are often gendered and vary among men and women. Therefore, this study explores different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh. The research followed an empirical research methodology to collect primary and secondary information using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the individual level are relatively low (63%). Still, they have been observing significant changes in various climatic variables over the past 30 years. Moreover, this study identified some major adaptation options such as plinth raising (100%), livestock rearing (100%), homestead gardening (82%), seasonal migration (82%), and using indigenous knowledge (69%), and so on to tackle the adverse impacts of climate change-induced extreme events including flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount of financial resources from individual sources in the study area. Structural Equation Modeling (SEM) is used in addition to the statistical analyses to understand any connections between the climate change perceptions and other variables associated with the community under study. The SEM result shows that climate change will be a long–term problem, which offers a strong predictor in this model, considering standardized regression weight β= 0.56. It means, despite inadequate knowledge on climate change of the respondent’s, climate change is occurring and becoming the worst factor limiting cultural, economic, and environmental development in the study area.

Species have shown their habital variations in responding to climate change, especially during the spring and summer spawning seasons. The species distribution model (SDM) is considered the most favorable tool to study the potential effects of climate change on species distribution. Therefore, we developed the ensemble SDM to predict the changes in species distribution of Portunus trituberculatus among different seasons in 2050 and 2100 under the climate scenarios RCP4.5 and RCP8.5. The results of SDM indicate that the distribution of this species will move northward and have obviouse seasonal variations. Meanwhile, the suitable habitat for the species will be significantly reduced in summer, with loses rates ranging from 45.23% (RCP4.5) to 88.26% (RCP.8.5) by 2100s. Habitat reduction will mainly occur in the East China Sea and southern part of the Yellow Sea, while there will be a small increase in the northern Bohai Sea. These findings will be important to manage the ecosystem and fishery, provide an information forecast of this species in the future, and maintain species diversity if the seawater temperature rises.

Linking climate action with sustainable development goals (SDGs) might incentivize social and political support to forest conservation. However, further examination of the conceptual entry points for linking efforts for reducing forest-based emissions with those for delivering SDGs is required. This review paper aims to contribute to fulfilling this research need. It provides insights into the links between conserving forests for climate change mitigation and peacebuilding. Specifically, the paper examines opportunities to harness climate finance for conserving forests and achieving long-lasting peace. It does so via a literature review and the examination of the Orinoquia region of Colombia. Findings from the literature review suggest that harnessing climate finance for conserving forests and peacebuilding is, in theory, viable if activities are designed in accordance with social, institutional, and economic factors. Meanwhile, the Orinoquia region provides evidence that these two seemingly intractable problems are proposed to be solved together. At a time when efforts for reducing forest-based emissions are being designed and targeted at (post-) conflict areas in Colombia and elsewhere, the paper’s findings might demonstrate to government agencies — both environmental and non-environmental — the compatibility of programs aimed at reducing forest-based emissions with efforts relating to peacebuilding and sustainable food.

1). As on-the-ground projects come into existence and continue to expand to adapt to climate change and empower women, it is important to understand their location within TANs. Using the Bhungroo technology as a case study, we aim to assess the potential of TANs to increase the scope and scale of local projects as well as the ability of similar and emerging projects to create social change at local levels. 2). We do so by analyzing interview and earned media hits data from the UNFCCC Momentum for Change. 3). We find that while TANs may help increase the scale and scope of projects, increasing their ability to effectively reach more people and areas is still up for debate 4). We conclude by considering how women’s political participation may be enhanced by similar projects.

Considerable attention has recently been given to the contribution of greenhouse gas (GHG) emissions of the healthcare sector to climate change, which represents 4-6% of emissions worldwide. GHGs used in medical practice are regularly released into the atmosphere and contribute to elevation in global temperatures that produce detrimental effects on the environment and human health. Consequently, a comprehensive assessment of their global warming potential (GWP) characteristics and clinical uses, many of which have evaded scrutiny from policy makers due to their medical necessity, is needed. Of major interest are volatile anesthetics, analgesics, and inhalers, as well as fluorinated gases used as tamponades in retinal detachment surgery. In this review, we compare estimates of these gases’ GHG emissions in metric tons CO₂ equivalent (MTCO₂e) and their relative GWP. Notably, the anesthetics desflurane and nitrous oxide contribute the most emissions out of the major medical GHGs, equivalent to driving 12 million gasoline-powered cars annually in the US. Retinal tamponade gases have markedly high GWP up to 23,500 times compared to CO₂ and long atmospheric lifetimes up to 10,000 years, thus bearing the potential to contribute to climate change long-term. This review provides the basis for discussions on examining the environmental impacts of medical gases with high GWP, determining whether alternatives may be available, and reducing emissions while maintaining or even improving patient care.

Currently, one of the main challenges is the mitigation of the effects of climate change on the agricultural sector. Conventional agriculture, with the intensive use of herbicides and pesticides to control weeds and pests, and the improper use of mineral fertilizers, contributes to climate change by causing increased greenhouse gases and groundwater pollution. Therefore, more innovative technologies must be used to overcome these problems. One possible solution is nanotechnology, which has the potential to revolutionize the conventional agricultural system. Active nanoparticles can be used both as a direct source of micronutrients and as a delivery platform for bioactive agrochemicals to improve crop growth, yield and quality. The use of nanoparticle formulations, including nanopesticides, nanoherbicides, nano-fertilizers and nano-emulsions, has been extensively studied to improve crop health and shelf life of agricultural products. Comprehensive knowledge of the interactions between plants and nanoparticles opens up new opportunities to improve cropping practices through the enhancement of properties such as disease resistance, crop yield, and nutrient use. The main objective of this review is to analyze the main effects of climate change on conventional agricultural practices, such as the use of pesticides, herbicides and fertilizers. It also focuses on how the introduction of nanoparticles into conventional practices can improve the efficiency of chemical pest control and crop nutrition. Finally, this review examines in depth the last 10 years (2014-2024) of scientific literature regarding the use of nanoparticles in agriculture to mitigate the effects of climate change.

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. Globally the atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, the total increasing temperature globally averaged combined land and surface between the average of the 1850-1900 period and the 2003 to 2012 period is 0.78 °C (0.72 to 0.85). But should we prepare for such the relatively small change? The importance is not the mean of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the difference in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays to train services. During the period of flood, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration, high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion on to the infrastructure as well as additional quasi-static burden exerted. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore.

Multicropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to uneven distribution of precipitation. For this reason, investigations were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Single maize crop was compared with Crimson/red clover, Persian clover, and alfalfa intercropped maize cultivations. Results showed that under arid conditions, the intercrops biomass was about 4 times less than under humid. Humid conditions were less suitable for maize and when growing with intercrops they produced about 3-5 t ha-1 less dried biomass, and when growing sole - about 6 t ha-1 less biomass than in arid conditions. Due to the higher yield of maize biomass in arid season, better energy indicators of the crop were obtained in arid conditions than in humid. The difference between net energy was about 122-123 MJ ha-1 in all treatments, except for the maize crop with intercropped alfalfa, where the difference was 62 MJ ha-1. All tested technologies were environmentally friendly, CO2 equivalent varied between treatments from 804 to 884 kg ha-1. Uneven distribution of precipitation during vegetative season makes us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could improve its germination but increase the problem of weed spread.

Climate change has emerged as one of the defining issues of the early 21st century. It is now more certain than ever and poses a serious threat to sustainable urban development. Climate change has many destructive effects on cities. Land subsidence, rising air pollutants, severe storms, dust and water scarcity are just some effects of this phenomenon in the urban area of ​​Tehran. Urban management must be prepared to deal with these effects and adopt policies to mitigate and adapt to climate change. One of these tools in urban planning is urban development plans. The plans can have a great impact on controlling and counteracting with the effects of climate change. In this research, using content analysis method, 6 dimensions and 31 indicators have been used to evaluate 8 city and region development plans of Tehran from the view of reflecting the effects of climate change. Indicators were scored after studying the content of the plans. Findings indicate that among the reviewed plans, the second and third five-year development plans of Tehran with 61.9% and 61.3% as the highest rate and plan to reduce air pollution in Tehran and the transportation master plan with 20.6% and 23.2%, respectively have the least attention to the effects of climate change. Also, among the indicators, the urban transportation sector with 54.3% as the highest and the energy sector with 20.5% have the least attention to mitigation and adaptation policies.

Development of the continental shelf has accelerated significantly as nations around the world seek to harness offshore renewable energy. Many areas marked for development align with submerged palaeolandscapes. Poorly understood and difficult to protect, these vulnerable, prehistoric landscapes provide specific challenges for heritage management. Indeed, there now appears to be a schism between what underwater cultural heritage policy intends and what it is achieving in practice. Shortcomings in international and national legislature ensures that large parts of the continental shelf, including areas under development, may have little or no legal protection.

The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback to a national real-time risk knowledge base during extreme events (flooding and drought) is also discussed. Under climate change conditions, Denmark is likely to experience more rain in winter, more evapotranspiration in summer, intensified cloudbursts, drought, and sea level rise. These challenges have been addressed as part of the Joint Governmental Digitalization Strategy 2016-2020 for better use and sharing of public data about the terrain, water, and climate to support climate adaptation, water management, and disaster risk reduction. This initiative included the development of a new web-based data portal (HIP portal) developed by the Danish Agency for Data Supply and Infrastructure (SDFI). GEUS delivered 5 terra-byte of hydrological model data to the portal with robust calibration methods and hybrid Machine Learning (ML) being key parts of the deliverables. The paper discusses the challenges and potentials of further developing the HIP Digital Twin with ‘plug-in Digital Twins’ for local river basins including feedback to the national level.

Several extinctions have already been attributed, at least in part, to global warming, as climate change constitutes a serious threat for species living in isolated ecosystems and thus unable to track habitat changes. However, in all these cases extinction was due to human impacts, often directly but generally also through exotic invasive species. For two arboreal land snails in Indian Ocean islands a link has been proposed with decreasing rainfall. The decline (but probably not extinction) of Pachnodus velutinus, a specialist of moist forests on the summits of northwestern Mahé, was most likely caused instead by invasive plants altering its habitat and alien predators decimating the population in the small remaining moist forests. An alternative explanation assuming genetic swamping through hybridization with a species from lower elevations has no basis, as the presumed hybrid constitutes a distinct species able to survive in the altered, dryer habitat. On Aldabra Atoll, the endemic Rhachistia aldabrae was claimed to have been the first extinction due to climate change, but is still extant. No relationship can be detected between number of sightings and annual rainfall, although a weighted measure that takes into account rainfall in previous years suggests a limited impact of weather. Analysis of the sighting record in various ways yields a probability of survival over time that never dropped below 0.3. The decline was caused instead by intense impacts of exotic invasive species. Alternative shortcuts to evaluate extinction rates among poorly known species are shown to be unreliable. Although no contemporary extinction can still be attributed to climate change, indirect and synergistic impacts on biodiversity are expected, especially through promoting biological invasions.

Abstract: A large number of collecting expeditions were launched in regions of ‘centers of diversity’ and hundreds of thousands of sample have been collected and stored in gene banks as ‘genetic resources’. So far, only a small number of the samples have been evaluated for their biotic and abiotic stress tolerance. Now, their time to become useful has come. A new global phenomenon has arisen – climate change. The crop genetic resources and their wild progenitors that have survived countless years of changing environment during the last 11,000 years could harbor genes that may be useful under the new growing conditions and environmental factors thrown up by climate change and global warming. With the deployment of modern bio-engineering techniques selected genes or gene fragments can be transferred from genetic resources to modern varieties of crop plants to make them well-prepared to mitigate the effects of global warming and climate change. The latter is the most serious issue facing plant breeders today. New pests and diseases could affect crop production. These review paper discusses various impacts and issues as a result of this phenomenon and suggest ways to safeguard our most important crops through better management of crop plant genetic resources in the near future.

Climate change is unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems and the fisheries sector. This study documented the past occurrence of extreme climate change impacts, such as supertyphoon Pablo (ST: Bopha), which severely affected Baganga, Davao Oriental, about ten years ago. A mixed-methods data collection was used, combining semi-structured interviews with small-scale fishers (N=120) in four fishing villages and focus group discussions (N=4, participated by about 4 focus groups) on assessing the impacts and their adaptation after climatic events occurred. Our findings indicate that the four selected fishing villages were exposed to common factors of climate change events that destroyed many lives and their livelihood. Including a decrease in catch per trip and the fishing operations disruption (98%). However, due to the impact of the supertyphoon, small-scale fishers in Baganga developed psychological distress (emotional 44% and physical 24%) due to the extreme event or disaster and economic losses (32%). In order to survive, their adaptation strategies relied on government and non-government-provided provisions and projects, e.g., planting trees, constructing a sea wall with wave breakers, cash for work, and tourism as an alternative livelihood. Despite this, our study revealed that the community had limited knowledge on the impacts of climate change, lack clear management goals especially for fishers, and the widespread use of illegal fishing gears. The local government must strongly implement rules, policies, and adaptation measures that will contribute to better and more resilient communities. This can help them to withstand future shocks and provide sustainable fisheries resources that will benefit all the fishers. The study will be useful to policymakers, disaster management group and organization that will help assist affected communities highly affected by climatic events.

Climate change affects both human and natural systems. Afghanistan ranked globally on the top of highly vulnerable countries to the adverse effects of climate change. The agricultural communities of Afghanistan is highly affected by climate change. Understanding farmers’ real experiences on changing climate become crucial in planning the future adaptation strategies. This study assessed the farmers' perception of climate change and its impacts on farming communities. Primary data were collected through face-to-face interviews conducted with 120 household heads. Additional qualitative data were collected by conducting 4 Focus Group Discussions (FGDs), 4 Historical Timeline Calendars (HTCs), 18 Key Informant Interviews (KII), and sketches of 4 Crop Calendars. The study reveals that climate indicators have varied and changed. The farmers express their experiences of decreasing snowfall in winter and annual rainfall in spring and summer, which led to the intensity and frequency of drought and water shortages for agriculture and rangelands in the upper and lower part of the valleys. The temperatures in winter and summer have increased and led to earlier snow melting, earlier blooming, flowering, and greening of the plants. These changes affected both positively and negatively. There is a half-month new opportunity for cultivation and increased earlier animal ranching in the rangelands. These findings can be valuable inputs for developing effective and efficient adaptation strategies.

Climate projections show that southern Indonesia such as West Nusa Tenggara is projected to experience a lower precipitation and higher temperatures. To date, research on climate change impact on Indonesian rice production yield is limited. As climate change is projected to decrease rainfall and to increase temperatures, this paper offers a qualitative analysis using system archetypes to understand the impacts of climate change on rice production. Two system archetypes are identified including Limits to Growth and Success to Successful. Both archetypes explain that rice production is hampered by high minimum temperature as photosynthesis output is decreased by increasing respiration. This paper shows that using a simple tool, system archetypes, we can describe the impacts of climate change on rice production. The outputs of this study such as a causal loop diagram and system archetypes can be a basis to develop a simulation model in understanding the impacts of climate change on main crops.

Mangroves are among the world’s most threatened ecosystems. Understanding how these ecosystems responded to past natural and anthropogenic drivers of ecological change is essential not only for understanding how extant mangroves have been shaped, but also for informing their conservation. This paper reviews the available paleoecological evidence for Pleistocene and Holocene responses of Caribbean mangroves to climatic, eustatic and anthropogenic drivers. The first records date from the Last Interglacial when global average temperatures sea levels were slightly higher than the present and mangroves grew in locations and conditions similar to today. During the Last Glaciation temperatures and sea levels were significantly lower and Caribbean mangroves grew far from their present locations, on presently submerged sites. Current mangrove configuration was progressively attained after Early Holocene warming and sea-level rise, in the absence of anthropogenic pressure. Human influence began to be important in the Mid-Late Holocene, especially during the Archaic and Ceramic cultural periods, when sea levels were already at their present position, and climatic and human drivers were the most influencing factors. During the last millennium, the most relevant drivers of ecological change have been the episodic droughts linked to the Little Ice Age and the historical developments of the last centuries.

Consideration of climate change in Environmental Impact Assessment (EIA) is a rather novel topic, which became partly mandatory through the revised EU Directive on EIA. Through a mixed-methods approach involving key-actors from EIA practice, decision making and climate adaptation planning, this study presents a transdisciplinary point of view on barriers and opportunities to tackle climate change adaptation in environmental assessment of large-scale projects. It is based on both a retrospective ex-post evaluation of existing practices in Austria and Germany as well as prescriptive examination and development of outcomes for practice through the development of a climate-fit toolkit that supports the incorporation of climate change impacts into EIAs. The scenario analysis applied with a back casting approach provided the opportunity to look beyond limitations related to legal compliance and partly lack of data identified by previous research. Three scenario narratives were elaborated based on nine key impact factors based on literature review, content analysis of EIA documents and interviews with EIA actors. The groups of actors carried out a prioritization of actions towards consideration of climate change in EIA. Finally, the actors were involved in co-production of an online tool-kit for Austrian and German EIA practice.

This study investigates the impacts of climate change policies on businesses across various sectors, aiming to understand how these regulations affect operational, financial, and strategic aspects of business management. Utilizing a mixed-methods approach, data was collected from 500 businesses through surveys and interviews, encompassing a wide range of industries, sizes, and geographic locations. The findings reveal a complex landscape where 30% of businesses report positive impacts, primarily in the renewable energy and technology sectors, citing increased demand for green products and improvements in energy efficiency. Conversely, 45% of businesses, especially from manufacturing and agriculture, experience negative impacts, including increased operational costs and regulatory compliance challenges. Notwithstanding, a significant majority of businesses are committed to enhancing their sustainability practices, viewing climate change policies as an opportunity for innovation and long-term growth. The study highlights the nuanced effects of climate change policies, emphasizing the need for sector-specific support measures to alleviate financial and operational burdens on negatively impacted businesses. Moreover, it points to a broader shift towards sustainability within the business community, suggesting that climate policies, despite their varied impacts, are driving significant changes in business strategies towards environmental stewardship.

The mental health impact of the environmental crisis, particularly eco-anxiety, is a growing research topic whose measurement still lacks consensus. In this article, we use item response theory (IRT) to better un-derstand what existing questionnaires measure. To conduct this review, we used open-access data from the short French version of the Climate Change Anxiety Questionnaire (Mouguiama-Daouda et al. 2022, Heeren et al., 2023). Our results suggest that, of the different models tested, the unidimensional model seems to be the most appropriate for measuring eco-anxiety. The item difficulty parameter extracted from the IRT enabled us to discuss the level of severity of the items making up this tool. The Climate Change Anxiety Questionnaire is more appropriate for measuring severe to moderately severe eco-anxiety. Ave-nues for improving this questionnaire and the measurement of eco-anxiety in general are then discussed.

Rhynchocypris kumgangensis, endemic to Korea, is limited to the upper Hangang River and Gucheondongcheon Stream. As a key and climate-sensitive biological indicator species in Deogyusan National Park, it has a southern range limit in the Gucheondong Valley. Due to climate change, notable shifts in the activity, vertical distribution, and population of R. kumgangensis in the Gucheondongcheon Stream are expected. Owing to the rapidly changing climate, significant changes in the activity, vertical distribution, and population size of R. kumgangensis in the Gucheondongcheon Stream are anticipated, and continuous surveys of the distribution of R. kumgangensis in this river area have been conducted. This study assessed the habitat of R. kumgangensis at 13 sites, including five in the Gucheondongcheon Stream, from July to October 2020 and compared the results with historical data to evaluate the impacts of climate change. At the five Gucheondongcheon Stream sites, 102 individuals were recorded from April to October 2020, and 378 were recorded between June 2018 and July 2019. Additionally, the subdominant species shifted from R. kumgangensis (2014–2018) to Zacco koreanus (2020). In the two southernmost Gucheondongcheon Stream sites, only 18 R. kumgangensis were observed in 2020 compared to 82 in 2019, indicating a significant population decline.

The Congo River Basin is the second-largest watershed globally, flowing through nine countries before reaching the Atlantic Ocean. The Kasai River Basin (KARB), containing about one-fourth of Congo’s freshwater resources, plays a strategic role in sustaining navigation, food production, and hydroelectricity generation in Central Africa. A multi-model framework suited for data scarce regions is applied for climate change impacts on water availability in the KARB to propose effective development plans in the future. This includes consideration of two conceptual hydrological models calibrated using four reanalysis datasets and fed with bias-corrected outputs of 19 climate models under two future Representative Climate Pathways (RCPs). Changes in mean annual discharge in the KARB from -18% to +3% are projected depending on the considered modeling configuration. This shows the sensitivity of impact assessment to the choice of models as well as input data. Moreover, about 9%, 18%, and 13% decline in streamflow signatures (Q10, Q50 and Q90) are projected based on the ensemble of models under RCP 8.5. A decrease of 14% and 5% in annual hydropower potential of the mainstream is estimated under RCPs 4.5 and 8.5, respectively. These changes in flows conditions should be considered in decision-making around constructing reservoirs and hydroelectricity generation.

COVID‑19 pandemic, also known as the coronavirus pandemic, has spread rapidly across the globe since the end of 2019 and brought impressive changes in our life and living through partial or full lockdown and reduced anthropogenic activities. Hence, it is imperative to investigate the impacts and consequences of COVID-19 on global eco-system and environment. The present study accordingly addresses the impacts and consequences of COVID-19 by ten environmental indicators; viz., global warming (or greenhouse gas emission), stratospheric ozone depletion, ozone formation (on human health), fine particulate matter formation, smog, ionizing radiation, human carcinogenic toxicity, human non-carcinogenic toxicity, water resource consumption, and effect on human health. The overall study has been performed in agreement with the standard principle and guidelines of life cycle assessment. Worldwide changes in consumption of fossil fuels, viz., petroleum, coal and natural gas, as a result of COVID-19 pandemic, has been the core theme of the study. Outcomes from the study show that COVID-19 has been a ‘blessing in disguise’ for the global environment with most of the above-mentioned indicators declining by approximately 20-30% in 2020 in comparison to the 2019 level.

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction scenarios in a complex river basin, under conditions of climate change. The modeling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low streamflow conditions, compared to a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high resolution climate model data from the UKCP18 project with future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of surface water abstraction of public water supply in the downstream region: maximum licensed withdraw, 50 % authorized abstractions, monthly time series with 1% increase of water use, and maximum water withdraw year based on historical records repeated every year with 1% increase of water use, to estimate the unmet demands and streamflow requirement. This modeling approach can be used in other river basins to manage scenarios of supply and demand.

Global climate change, dominated by climate warming, is seriously affecting the balance of global ecosystems, but the risk of species extinction is particularly high in low-altitude mountain areas. To clarify the response of the endemic and critically endangered species Ilex nanchuanensis to climate change, this study used the MaxEnt model to simulate and predict the potential habitat of I. nanchuanensis during the Last Interglacial, Last Glacial Maximum, the current period, and two future periods (the 2050s and 2070s). The results showed that the hottest monthly minimum temperature is the most important climatic factor affecting the geographical distribution of I. nanchuanensis. Furthermore, I. nanchuanensis will be at risk of population shrinkage and extinction in the future, with the center of mass moving further northwest as concentrations of greenhouse gases increase, especially in the 2070s, when its geographical distribution shrinks the most under the RCP6 scenario. Global warming is causing habitat degradation for many species and will continue to migrate to higher altitudes and latitudes in the future, seriously affecting the global ecosystem balance. Therefore, to actively respond to the impacts of climate change, protected areas should be established around the geographical distribution centers of species, and core, buffer, and experimental areas should be scientifically and rationally delineated for the conservation and cultivation of germplasm resources.

The Shule River Basin (SRB) is a typical arid area in northwest China with a fragile ecology. Un-derstanding vegetation dynamics and its response to climate change and human activities provides essential information for ecological and environmental resource management. This study extracted fractional vegetation coverage (FVC) data from 2000 to 2019 using the Google Earth Engine plat-form and Landsat satellite images, employing trend analysis and other methods to examine spati-otemporal changes in vegetation in the SRB. Additionally, partial correlation and residual analysis were utilized to explore the response of FVC to climate change and human activities. The main results were as follows: (1) The regional average FVC in the SRB showed a significant upward trend from 2000 to 2019, increasing by 1.3 × 10−3 y–1. The area within 1 km of roads experienced a higher increase of 3 × 10−3 y–1, while the roadless areas experienced a lower increase of 1.1 × 10−3 y–1. Road construction from 2004 to 2006 significantly reduced the FVC within 200 meters of the roads. FVC spatial heterogeneity in the SRB is significant. (2) Partial correlation analysis shows that FVC has a strong positive correlation with precipitation and surface water area, with correlation coefficients of 0.575 and 0.744, respectively. There is a weak negative correlation between FVC and land surface temperature (LST). FVC changes are more influenced by precipitation than by LST. (3) Compared to climate factors, human activities have a greater impact on vegetation dynamics in the SRB. The contributions of climate change to vegetation recovery are increasing. (4) The area changes of dif-ferent land types are closely related to climate factors and human activities, reflecting their impact on vegetation. These results provide valuable information for ecosystem restoration and environ-mental protection in the SRB.

Abstract: This article aims to better understand the mechanisms that connect climate change perceptions and general willingness to engage in pro-environmental behavior using Spanish cross-sectional data (N = 403). To do this, we first developed and validated the General Willingness for Environmental Behavior Scale (GWEBS), which includes the classical approach of voluntarily doing new actions but also actions implying not doing things (degrowth) and actions forced by social constraints. The exploratory and confirmatory factor analysis showed a good fit for the one-factor structure, which had adequate validity based on their relationship with other variables. Additionally, the GWEBS distinguished between women and men, left- and right-oriented people, and people who belonged to pro-environmental groups and people who did not. In the second place, we tested the parallel mediator role of eco-anxiety and trust in science in the relationship between climate change perceptions and the GWEBS. The results showed that eco-anxiety, fully, and trust in science partially mediated such a relationship, making them crucial to mobilize the intention to act following the perception. This study contributes to our understanding of the psychological mechanisms that eventually drive pro-environmental behaviors and provides a clear direction for future research.

Dioscorea composita is a plant native to México and Central America with a high concentration of diosgenin precursors. Currently, México is one of the two most important countries producers of this yam; however, climate change is altering the environmental conditions of its natural habits, threatening its preservation and productivity. This is why this research was focused to characterize the eco-geography of D. composita and predict its potential geographic distribution under climate change scenarios in México-Central America. A collection of 408 geo-referenced accessions was used to determine its climatic adaptation, ecological descriptors, and the current and future potential geographic distribution, which was modeled with MaxEnt model through the Kuenm R-package. For future climate scenarios, an ensemble of the GCMs HadGEM-ES and CCSM4 was used. Results showed that D. composita adapts to warm humid and very humid agro-climates and that the most contributing variables for its presence are annual and seasonal moisture availability indices, seasonal photoperiod, annual thermal range, Bio14 and Bio11. The year 2050 RCP 4.5 climate scenario would contract the potential distribution of D. composita, whilst the 2050 RCP 8.5 scenario would expand it, indicating that this species could be a good crop option under this scenario of emissions.

This study aims to evaluate the climate-change response of greening persistently vacant houses and barren sites in deteriorated high-density residential areas in old downtown metropolitan areas. The current status of building demolition sites in Ami-dong and Chojang-dong, Busan Metropolitan City, was examined. In this area, of the 340 vacant houses from 2017, 246 (72.35%) remained persistently vacant till 2020. In 2020, 213 barren sites were neglected after building demolition. Amongst these sites, 177 (83.10%) were paved with concrete. Persistently vacant houses and barren sites were afforested, and the climate-change response was quantified in terms of flood reduction and CO2 mitigation in four scenarios (current, concrete, ground cover plants, and trees). Runoff analysis was performed using the Korea low-impact development model (K-LIDM) to assess flood mitigation. The tree scenario showed average runoff mitigations of 1.71%, 2.38%, and 3.06% in the long-term, 30-year, and 2-year rainfall scenarios, respectively. Additionally, 3058 deciduous broadleaf trees may be planted in the study area to promote CO2 mitigation. Thus, an additional annual carbon fixation of 62,123.78 kg CO2 may be expected. The greening of vacant houses and demolished sites was effective in all aspects of the climate-change response, and tree-based greening exhibited the most significant effect.

The main target of this study was to evaluate the impact of future climate change on the available surface water resources in the Dhidhessa Sub-basin, Abbay Basin, Ethiopia. For the prediction, high-resolution Regional Climate Models (RCMs) from multiple climate models with data from Representative Concentration Pathways (RCPs) prepared by the CCAFS were used. The predictions of future discharge (stream flow) were based on climate scenarios data of baseline period of 1991 to 2020 and for the future with two time windows, 2044 (2030–2059) and 2084 (2070–2099), on a monthly time step after bias correction was conducted to both precipitation and temperature in the future climate under each RCP scenario. After sensitivity analysis, calibration (1994–2011), and validation (2012–2020) of the model for the Dhidhessa Sub-basin with the SUFI-2 program in the SWAT-CUP model, the SWAT model was used to determine water balance and stream flow from the SWAT model system. The SWAT model performed well in predicting stream flow in the Dhidhessa Sub-basins, with a coefficient of determination (R2) ranging from 0.8 to 0.94 and a Nash Sutcliffe value (NSE) ranging from 0.76 to 0.89. The percent decrease in mean annual stream flow from 2044 and 2084 were 10 %, in 2044, and 6.3% in 2084 respectively. The seasonal result under short-term 2044 of stream flow present change significantly decreased in spring, winter, and autumn with 20.2%, 67.4%, and 67.4% respectively. While summer season increased by 43.1%, under short-term 204. In long-term 2084 percent change declined except summer seasons, with 14.7%, 58.1%, and 3.3%, change in spring, winter, and autumn, respectively, and summer, with 51.1% increased and With RCP4.5 (1.64%) and RCP8.5 (2.1%) changed. In the future Dhidhessa stream flow increases and decreases from the baseline era. The decreasing stream flow in 2044 and 2084 will negatively affect agricultural production. This study revealed that any effect on this river resulting in a drop in flow will have a direct impact on ongoing water resource development and socio-economic development of the area.

The 2030 global agenda of the United Nations emphasizes peace, human rights, gender equality, partnership, and women's empowerment. It balances the social, economic, and environmental dimensions of sustainable development. The SDG framework was designed to be integrated and indivisible, making the interconnections of 17 Goals and 169 Sustainable Development Goals Targets (SDTs) more complex that need extensive and intensive investigative research. Recent studies have increased on the interrelationships of SDGs, but none of these have focused on integrating Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), also known as CSI Nexus. This study aims to investigate and identify the 169 SDTs linked to CC, SFM, and ICT and assesses the significance of the relationships between these variables. The alignment of SDTs to CSI Nexus was identified through clustering and mapping techniques. The result argued that 56 SDTs are directly connected within CC+SFM+ICT, 16 within CC+SFM, one within SFM+ICT, and 51 within ICT+CC. Our result suggests that CC is significantly associated with SFM; however, ICT has no significant association with CC and SFM. It further asserts that the ICT and SFM have minimal influence on the SDG 2030 framework. The proposed CSI Nexus and SDTs Integration Framework was a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals. This study does not include interactions, network analysis and visualization, simulations, and modeling between SDG targets.

Artificial intelligence methods and application have recently shown great contribution in modeling and prediction of the hydrological processes, climate change, and earth systems. Among them, deep learning and machine learning methods mainly have reported being essential for achieving higher accuracy, robustness, efficiency, computation cost, and overall model performance. This paper presents the state of the art of machine learning and deep learning methods and applications in this realm and the current state, and future trends are discussed. The survey of the advances in machine learning and deep learning are presented through a novel classification of methods. The paper concludes that deep learning is still in the first stages of development, and the research is still progressing. On the other hand, machine learning methods are already established in the fields, and novel methods with higher performance are emerging through ensemble techniques and hybridization.

The article addresses the complex climatic situation faced by the state of Rio Grande do Sul, Brazil, which began on April 27, 2024, and extended for weeks. This unprecedented extreme weather event is yet another chapter in the global climate crisis. Initially, this rainfall seemed typical for the season. However, it quickly escalated into one of the worst climatic catastrophes in Brazil's history. In recent years, there has been a global increase in extreme weather events, including heavy precipitation, flooding, landslides, cyclones, and heatwaves, highlighting the ongoing climate crisis as one of the most serious threats we face today. In light of this, our study aims to elucidate the impact of climate change by examining one of Brazil's most severe climate disasters. We investigate the complex situation in Rio Grande do Sul, analyzing the ongoing climate crisis and projecting what can be expected in the near future.

Abstract: Floods can be defined as one of the most frequent and destructive disasters, that cause significant damage to people, while droughts present significant challenges in first place to most vulnerable communities. In consequence, state public policies are essential to manage the risk in the face of both phenomena and contribute to the construction of resilient communities. As a request of the National Water Commission of Mexico (CONAGUA) for the Regional Water Plan (PHR), we designed and applied a methodology based on virtual consultation fora in conjunction with digital survey tools to understand the population's perception of these phenomena. The workshops were organized in the five municipalities of Baja California Sur. Then, we performed an interdisciplinary analysis that combines hydrological considerations with the most critical social, economic, environmental, and law components, applying the PESTEL analysis. The results indicate that there is a clear and widespread awareness that floods and droughts increase the risk to the livelihoods of the population; however, there are deficiencies in different areas, which complicates risk management. Timely information and the inclusion of communities in mitigation and adaptation proposals would allow for achieving more successful cases with the efforts to minimize vulnerabilities and increase the resilience of the population in the face of a changing climate. This must be a collaborative work of the entire society, governmental, social, and private stakeholders.

Prunus armeniaca L. is the native species of cultivated apricot, which is important information for studying the origin, succession pattern, pest control, sustainable development of biodiversity of economic tree species of the genus Apricot, etc. However, with global climate change and increasingly intense human activities, the survival environment of Prunus armeniaca L. is under serious stress, and exploring the potential survival space of Prunus armeniaca L. is an important way to protect the health and development of Prunus armeniaca L.. Exploring the potential living space of Prunus armeniaca L. is an important way to protect the healthy development of Prunus armeniaca L. The Yili River Valley is a typical distribution area of Prunus armeniaca L. . Exploring the potential distribution suitable area of Prunus armeniaca L. in the Yili River Valley and analyzing its future change trend can provide scientific guidance for the protection, development, and utilization of Prunus armeniaca L.. Based on the Geographic Information System software platform combined with the MaxEnt Model, we simulated the potential distribution areas and the degree of adaptation of Prunus armeniaca L. in the Yili River Valley, and predicted the potential distribution changes of Prunus armeniaca L. in the future under different situations. Based on the above methods, the following results were obtained: (1) The MaxEnt Model simulated the geographic distribution of Prunus armeniaca L. with high accuracy and an AUC value of 0.969, and the area of the currently suitable area for Prunus armeniaca L. in the Yili River Valley was about 10407.77 km2, accounting for about 18.45% of the overall land area of the Yili River Valley; the area of the highly suitable area was about 1380.9 km², accounting for about 13.26%, the area of the medium suitable zone is about 2830.15km², and the area of low suitable zone is about 6196.05km². (2) The maximum increase in the total area of the suitable zone under the future low-radiation forcing scenario is 11.49%, and the minimum increase under the future medium-high forcing scenario is 4.94%. (3) The overall migration was in the southwest direction, with the largest migration angle under the SSP245 scenario and the largest migration distance under the SSP585 scenario. Under the background of future climate change, there is a tendency for the potential habitat of Prunus armeniaca L. in the Yili River Valley to expand from low altitude to high altitude, and altitude is the dominant geographic factor influencing the distribution of Prunus armeniaca L.. By simulating and studying the potential geographic distribution of Prunus armeniaca L. in the Yili River Valley under the background of climate change, we can reveal the response mechanism between the geographic distribution of Prunus armeniaca L. and the natural environment, which can provide scientific guidance and data support for the exploitation and protection of Prunus armeniaca L. in the future.

The measures related to climate change and international technology transfer have been closely intervened as most international environmental instruments, including the United Nations Framework Convention on Climate Change and Kyoto Protocol as well as Paris Agreement which contain the provisions concerning environmentally friendly technology transfer. However, technologies have not been transferred adequately owing to the flaws in the relevant provisions and due to the fact that most technologies are possessed by transnational corporations and other private sectors. In order to undertake the commitment by the governments of developed countries and at the same time, to conform the commercial activities of their respective private sectors to the level of promised international obligation, an uniform international technology transfer agreement needs to be established separately, particularly under the World Trade Organization regime in Post Pairs-Agreement era. This paper first explores the defects and challenges found in provisions related to technology transfer in existing environmental agreements, and examines the possibilities of concluding an international technology transfer agreement both from theoretical and practical perspectives. climate change;environmentally sound technology;international technology transfer;Post Paris-Agreement Era

Climate change impacts and adaptations is subject to ongoing issues that attract the attention of many researchers. Insight into the wind power potential in an area and its probable variation due to climate change impacts can provide useful information for energy policymakers and strategists for sustainable development and management of the energy. In this study, spatial variation of wind power density at the turbine hub-height and its variability under future climatic scenarios are taken under consideration. An ANFIS based post-processing technique was employed to match the power outputs of the regional climate model with those obtained from the reference data. The near-surface wind data obtained from a regional climate model are employed to investigate climate change impacts on the wind power resources in the Caspian Sea. Subsequent to converting near-surface wind speed to turbine hub-height speed and computation of wind power density, the results have been investigated to reveal mean annual power, seasonal, and monthly variability for a 20-year period in the present (1981-2000) and in the future (2081-2100). The results of this study revealed that climate change does not affect the wind climate over the study area, remarkably. However, a small decrease was projected for future simulation revealing a slightly decrease in mean annual wind power in the future compared to historical simulations. Moreover, the results demonstrated strong variation in wind power in terms of temporal and spatial distribution when winter and summer have the highest values of power. The findings of this study indicated that the middle and northern parts of the Caspian Sea are placed with the highest values of wind power. However, the results of the post-processing technique using adaptive neuro-fuzzy inference system (ANFIS) model showed that the real potential of the wind power in the area is lower than those of projected from the regional climate model.

Implementation of the German Climate change Strategy in the Federal State of Saxony-Anhalt is discussed in this paper. It shares the requirement and importance of sustainable development. An overview of strategy, The DAS Indicator System is provided with results of a portion of work being done for the ministry of agriculture by Deutscher Wetterdienst (DWD). Applicability of the indicator system is also shown by evaluation of results for specific indicators from 1961-2015.

The Asian longhorned beetle (ALB), Anoplophora glabripennis is a forestry pest found worldwide. ALB causes serious harm because of the lack of natural enemies in the invaded areas. Dastarcus helophoroides and Dendrocopos major are important natural enemies of ALB. MaxEnt was used to simulate the distribution of D. helophoroides and D. major in China and Xinjiang, and their suitable areas were superimposed to evaluate the pest control ability of D. helophoroides and D. major. The results showed that, with climate change, the suitable areas of D. helophoroides and D. major migrated northward; the centroid shift of ALB was greater than that of D. helophoroides and D. major, which would lead to fewer natural enemies encountered by ALB during migration, reduce the control ability of natural enemies, and increase the risk of disastrous outbreaks in the invaded areas. We found that the damage caused by ALB was not serious in the areas with natural enemies and very serious in the areas without natural enemies. We suggest that natural enemies should be included in the model used for predicting suitable areas for invasive pests, as this is more conducive to assessing the risks of invasive organisms to the local ecological environment.

Tree resin, which in addition to its widespread use in industry is also a macroergic component which has not yet been used for energy purposes. The main goal of this work is to determine the energy content of the resin of spruce, pine and larch and wood components – pulp and turpentine. The combustion heats of resin (MJ/kg) from each timber was determined calorimetrically. The energy values of tree resin (&gt;38.0 MJ.kg-1) were 2.2 and 2.4 times higher than that of bleached and unbleached cellulose, the highest value was recorded for the turpentine (&gt;39.0 MJ.kg-1). The best way of resin tapping is the America method, providing 5 kg resin ha-1 yr-1. The resin quantity tapped was raised at least 3 times applying stimulant, its production cost compared to other feedstocks was the cheapest. The tree resin can be applied as a good means to mitigate global warming and consequently dampen climate change. One tonne of tree resin burned instead of coal spares the atmosphere by 5.0 Mt CO2 since it is environmentally neutral. As resin heating values approach to the lower end of ones of liquid hydrocarbon fuels, greater efforts are needed to examine the most efficient energy use of resin.

Oncomelania Hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of its habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB), and the ecological stability. Therefore, it is crucial to analyse the influence of climate change on the distribution of O. Hupensis in order to achieve accurate control over its population. This study utilised the MaxENT model to forecast possible snail habitats by utilising snail distribution data obtained from historical literature. The subsequent outcomes were achieved: The primary ecological factors influencing the distribution of O. Hupensis are elevation, minimum temperature of coldest month, and precipitation of wettest month; Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution centre for O. hupensis; Specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest; These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, resulting in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

The need to address climate change and establish sustainable urban environments has driven increased efforts in Europe to develop climate-neutral cities. This study highlights the importance of integrating solar energy technologies and nature-based solutions as key strategies to achieve climate neutrality. By examining current practices, emerging trends, and case examples, it explores the benefits, challenges, and prospects associated with the integration of solar energy and nature-based solutions in urban contexts. The study presents a pioneering approach to assess the urban heat and climate change mitigation benefits of combining building-integrated photovoltaics and nature-based solutions specifically within the European context. The results emphasize the synergistic relationship between nature-based components and solar conversion technology, identifying effective combinations for different climatic zones. In warmer regions of Southern Europe, strategies like rooftop photovoltaics on cool roofs, photovoltaics shadings, green walls, and urban trees have demonstrated effectiveness. Conversely, mid- and high-latitude European cities have seen positive impacts through the integration of rooftop photovoltaics and photovoltaics facades with green roofs and green spaces. As solar cell conversion efficiency improves, the environmental impact of photovoltaics is expected to decrease, facilitating their integration into urban environments. The study emphasizes the importance of incorporating water bodies, cool pavements, spaces with high sky-view factors, and effective planning in urban design to maximize resilience benefits. It also highlights the significance of prioritizing mitigation actions in low-income regions and engaging citizens in the development of social photovoltaics positive energy houses, resilient neighbourhoods, and green spaces. By adopting these recommendations, European cities can lead the way in creating climate-neutral urban environments that prioritize clean energy, nature-based solutions, and the overall well-being of residents. The findings underscore the need for a multidisciplinary approach that combines technological innovation, urban planning strategies, and policy frameworks to effectively achieve climate neutrality in European cities.

This study investigated the content of macro- and microelements in the lower reaches of the Ob River (Western Siberia). Seasonal sampling was performed over a four-year period (2020-2023) during the main hydrological seasons (winter low water, spring-summer floods, and early fall low water) at three river stations. Suspended and dissolved fractions were separated by filtration through 0.45-micron nitrocellulose filters. The results revealed significant seasonal variations in the elemental content of the Ob River water, associated with changes in catchment inputs, physical and chemical conditions of the aquatic environment, and the amount and composition of incoming suspended sediment. During high water flow events in the Ob River, the concentration of suspended solids increased substantially. These included significant quantities of sparingly soluble hydrolysates such as Al, Ti, Zr, Ga. During the winter period when the Ob River was ice-covered, a 2- to 3-fold rise was observed in the concentration of Na, Mg, Ca, K, Si, Mn. Having accounted for these seasonal variations in water chemistry, we were able to refine our estimates of elemental export to the Arctic Ocean. Compared to estimates from previous studies, we observed with 2.3-fold higher dissolved loads of Mn, 2.1-fold for Zn, 1.6-fold for Fe, and 1.4-fold for Pb.

The climate change constitutes nowadays an enormous global threat for human health and environmental sustainability. The expanding world population and the increased global needs for food production have an important negative impact upon environment. Diet can link human health with environmental sustainability. Food production systems are closely related to anthropogenic greenhouse gas emissions and the aggravation of climate change, and current western type, animal-based, dietary patterns may lead to adverse environmental footprints. In the present narrative review, we address the interconnection of the Mediterranean diet (MD) with climate change and sustainability. MD is a highly recommended dietary intervention for the prevention and management of various endocrine and cardiometabolic diseases. Beyond its evidence-based, health-promoting effects, it also has beneficial environmental impact, reducing greenhouse gas emissions and enhancing biodiversity, food security and sustainability. Based on the evidence reviewed herein, MD should be incorporated within the framework of a “One Health” model, which involves the improvement not only of human health but also of planetary health and food system sustainability. Our review aims to provide a stimulus for health pro-fessionals to strongly recommend the implementation of MD under the current pressure of climate change, despite all barriers, targeting both human health preservation and the planetary well-being.

The overwhelming evidence supports the assertion that the climate is undergoing change. Understanding the perception of locals of the magnitude of climate change and its influence on non-timber forest products (NTFPs) challenge at a global scale. Although studies on climate change, value addition, and the multiple uses of NTFPs and their impact on local livelihoods have been conducted, locals' perceptions of these factors have not been fully explored. This study aims to assess various social factors, including education, gender, and religion, and their influence on locals' perceptions of the abovementioned factors. The research focused on five regions where NTFPs are prevalent in Ghana (Western North, Bono, Ahafo, Ashanti, and Eastern regions). To investigate the impact of social factors on local perceptions of climate change, value addition, and the multiple values of NTFPs within rural communities, a total of 732 interviews with a team of interviewers across these five regions in Ghana were carried out. We applied a logistic regression model to assess the social factors and their influencing locals’ perceptions of the mentioned variables. It was revealed that age, gender, education, and occupation did not significantly influence locals' perceptions of climate change. However, religion was found to influence locals' perceptions of climate change. Furthermore, the results demonstrated that gender (P<0.000328) and education (P<0.00426) strongly influenced locals' perceptions of value addition to NTFPs. In contrast, religion and constraints (related to time, finance, and skills) did not significantly influence locals' perceptions. Additionally, it was observed that gender (0.00132), education (0.00692), and religion (8.12e-05) significantly influenced how locals perceive and use NTFPs. In conclusion, this study provides valuable insights into the intricate interplay among local perceptions, climate change, value addition, multiple uses of NTFPs, and the capacity of NTFPs to enhance the well-being of forest fringe communities. These findings underscore the importance of comprehensive, tailor-made interventions that consider local perspectives and adhere to sustainable approaches, with the aim of optimising the positive impacts of NTFPs in poverty alleviation and overall community development.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Smallholder farmers in Ethiopia face increasing challenges from climate change and variability, which threaten their food security and livelihoods. This study examines how adopting single and combined climate change adaptation practices affects their vulnerability to food insecurity in Bench Maji Zone, southwest Ethiopia. Through multistage sampling, data was gathered from 390 rural households in four climate-prone districts. The study examines the impacts resulting from both individual and combined implementations of adaptation techniques. These techniques encompass crop management practices, soil and water conservation measures, and livelihood portfolio diversification strategies. The study employed the multinomial endogenous treatment effect regression model to address selection bias and endogeneity resulting from various sources of heterogeneity, whether observed or unobserved. The results show that farmers who adopted adaptation practices were less vulnerable to food insecurity than those who did not. The study also finds that adopting multiple practices has a more significant impact than adopting single practices. Our findings suggest that implementing climate change adaptation strategies can increase the resilience of smallholder farmers in the study area and decrease their vulnerability to food insecurity. The study recommends supporting farmers in adopting these strategies through research and development, information dissemination, and collaborations among farmers, researchers, and extension services.

This study aims to provide empirical evidence on whether using renewable and non-renewable energy, CO₂ emissions and the resulting changes in temperature and precipitation can alter cereal yields in European Union countries. To this end, a panel data set covering 1992-2021 has been used to analyse the impact of climate change and economic factors on cereal production in European Union countries. The study employed various analytical techniques to understand better the relationship between climate change, energy consumption, and economic growth. These included using annual average temperature and rainfall to measure climate change and energy consumption and economic growth to analyse the economic aspects. To achieve the objective, feasible generalised least squares (FGLS) models with robust standard errors and bootstrap and a quantile regression (QR) model with marginal analysis were employed. The Westerlund cointegration test confirmed the presence of cointegration between cereal production and climate variables, economic growth, and energy consumption. The results indicate that increases in temperature and precipitation may contribute to increased cereal production in European Union countries. In contrast, energy consumption, including renewable energy and CO₂ emissions, may have a nonlinear effect on cereal production. Quantile regression analysis suggests climate change may impact crop yields most in countries with low and moderate cereal production per hectare. Increased CO₂ emissions may increase yields in the initial period, but excessive CO₂ may negatively impact cereal production in the long term. It would be advisable for countries with low and moderate crop productivity to consider implementing technological advances and combating global warming by modernising cultivation methods and making greater use of renewable energy sources.

This study aims to investigate the influence of various economic, environmental, and social factors on sustainable development, with a specific focus on the impact of green technology and climate change adaptation. A panel dataset comprising 38 OECD member countries from 1990 to 2020 is employed, and a series of dynamic panel data models are estimated using the system generalized method of moments (GMM) approach. Numerous covariates, such as globalization, socio-economic conditions, economic and political values, climate and technological progress, and environmental determinants, are examined. The empirical findings highlight the significant role played by macroeconomic, institutional, social, and government policy-related factors in sustainable development. More importantly, our results provide novel and robust evidence that the diffusion of green technology and climate change adaptation positively affect green growth. The study's empirical outcomes are demonstrated to be robust to misspecification errors and statistically significant at traditional significance levels. These findings carry substantial policy implications for the development and implementation of strategies that promote climate change adaptation and green innovation. Consequently, policymakers should prioritize the integration of green technology and adaptive measures in their sustainable development agendas to foster a greener, more resilient future.

The silver fir (Abies alba Mill.) is among the most valuable conifers in Europe for ecological and economic reasons. In the course of history, primarily in the 20th century, its share in stands has been declining due to ill-suited management practices, especially clear-cut management, air pollution, and wildlife-induced damage. Based on recent knowledge of fir ecology and population dynamics, small-scale shelterwood and selection management have been introduced in fir stands, which have also stabilized them. Fir is an essential species for maintaining high stability and biodiversity, especially on planosols and in waterlogged habitats. Due to its shade tolerance and environmental flexibility, particularly at higher altitudes, it can coexist very well with many tree species in mixtures, which can increase the productive potential of stands. It can form stands of heterogeneous structure, ranging from single to multi-layer to selection. For its successful natural regeneration, it is essential to reduce cloven-hoofed game and thus prevent bud browsing damage. On the other hand, fir is a species relatively resistant to bark stripping and the spread of secondary rot compared to Norway spruce (Picea abies [L.] Karst.). During global climate change, fir is expected to shift to higher elevations with sufficient precipitation, while in the southern part of its natural range or at lower elevations, outside water-influenced habitats, it is likely to decline. This paper essentially reviews the description and distribution of the species, its ecological requirements, threats and diseases, habitat and stand conditions, and close-to-nature forest management practices with emphasis on ongoing climate change.