The world witnessed one of the largest lockdowns in the history of mankind ever, spread over months in an attempt to contain the contact spreading of the novel coronavirus induced COVID-19. As billions around the world stood witness to the staggered lockdown measures, a storm brewed up in the urns of the rather hot Bay of Bengal (BoB) in the Indian Ocean realm. When Thailand proposed the name “Amphan” (pronounced as “Um-pun” meaning ‘the sky’), way back in 2004, little did they realize that it was the christening of the 1st super cyclone (Category-5 hurricane) of the century in this region and the strongest on the globe this year. At the peak, Amphan clocked wind speeds of 168 mph (Joint Typhoon Warning Center) with the pressure drop to 925 h.Pa. What started as a depression in the southeast BoB at 00 UTC on 16th May 2020 developed into a Super Cyclone in less than 48 hours and finally made landfall in the evening hours of 20th May 2020 through the Sundarbans between West Bengal and Bangladesh. Did the impact of the COVID-19 induced lockdown drive an otherwise typical pre-monsoon tropical depression into a super cyclone?

This paper reexamines climate justice through the framework of environmental sociology, offering fresh perspectives on the intersection of social and ecological systems in the face of escalating global climate crises. It emphasizes that inequality lies at the heart of global climate politics, often obstructing pathways toward achieving true climate justice. Drawing from established traditions within environmental sociology—such as the new ecological paradigm, the post-growth society, and the environmental justice paradigm—the paper advocates for profound systemic and structural reforms in political and economic systems to tackle entrenched inequalities. By integrating these frameworks, the paper proposes a comprehensive model of climate justice, encompassing material, procedural, compensatory, and transformative justice. This holistic approach not only addresses environmental sustainability but also prioritizes social equity, ensuring that marginalized communities are included in the global response to climate change. The paper thus positions climate justice as a critical component of broader environmental and social transformation.

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts and manage natural resources. Policy makers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products as well as the reference measurements used to calibrate, validate or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service, the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite derived datasets by prototyping a robust, generic system for the implementation and evaluation of Quality Assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface Albedo, Leaf Area Index, FAPAR, NO₂, HCHO and CO. Provision of standardized QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products their specific applications.

The climate crisis is developing to a life-changing event on a global level. Health promotion with the aim to increase the health status of individuals, independent from the present health status has been developed on scientific basis at least for the last eight decades and follows. There are some basic principles, which are prerequisites for both, health promotion and climate protection. Those principles include (1) sustainability, (2) orientation on determinants, and (3) requirement of in-dividual as well as community approaches. People are generally aiming to protect their lifestyle habits (e.g. traveling, consumer habits) and personal properties (e.g. car, house) by easy solution with as little effort as possible, and this can affect both, health and climate. To reduce the emission of greenhouse gases and to protect our environment, changes towards a sustainable lifestyle have to be embed into everybody’s mind. Examples for domains, that need to be addressed in health promotion as well as in climate protection include education/ knowledge/ (health) literacy, physical activity, nutrition and dietary habits, mental health, and social capital. If health promo-tion fails to tackle those domains, this will continue to drive climate crisis. And climate change, in turn, will affect health. On the other hand, developing and promoting health resources in the domains mentioned could again help to mitigate the health-damaging effects of climate change.

In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures measured at sites throughout the contiguous US and low-frequency variability of multiple climate indices (CIs) are analyzed over the period 1948 to 2018 using correlation analysis. The Pearson’s correlation coefficient is used to assess correlation strength, while Leave-One-Out Cross-Validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlation and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the strongest correlations overall; beginning months were optimized on an individual site basis. Strong (r >= 0.60) and significant (p-value <= 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help focus future research regarding specific mechanisms of climate variability that appear the exhibit strong links to US regional weather and sea level variability and prediction.

Estimating the economic risks of climate shocks and climate stressors on spatially heterogeneous cities over time remain highly challenging. The purpose of this paper is to present a practical methodology to assess the economic risks of climate change in developing cities to inform spatially sensitive municipal climate response strategies. Building on a capital-based framework (CBF), spatially disaggregated baseline and future scenario scores for economic wealth and its exposure to climate change are developed for six different classes of capital and across 77 major suburbs in Cape Town, South Africa. Capital-at-risk was calculated by combining relative exposure and capital scores across different scenarios and with population impacted plotted against the major suburbs and the city’s 8 main planning districts. The economic risk assessment presented here provides a generic approach to assist investment planning and the implementation of adaptation options through an enhanced understanding of relative levels of capital endowment vis-à-vis relative levels of exposure to climate-related hazards over time. An informed climate response strategy in spatially heterogeneous cities need to include spatially sensitive estimates on capital-at-risk and populations disproportionally impacted by climate exposure over time. The economic risk assessment approach presented here helps in advancing to such a goal.

The outcomes of the 2015 Paris Agreement triggered a number of climate impact assessments, such as for floods and droughts, to focus on future time frames corresponding to the years of reaching specific levels of global warming. Yet, the links between the timing of the warming levels and the corresponding greenhouse gas concentration pathways to reach them, remain poorly understood. To address this gap, we compare projected changes of annual mean, extreme high and extreme low river discharges in Europe at 1.5°C and 2°C under scenarios RCP8.5 and RCP4.5 from an ensemble of Regional Climate Model (RCM) simulations. The statistical significance of the difference between the two scenarios for both warming levels is then evaluated. Results show that in the majority of Europe (>95% of the surface area for the annual mean discharge, >98% for high and low extremes), the changes projected in the two pathways are statistically indistinguishable. These results suggest that in studies of changes at specific warming levels the projections of the two pathways can be merged into a single ensemble without major loss of information. With regard to the uncertainty of the unified ensemble, findings show that the projected changes of annual mean, extreme high and extreme low river discharge are statistically significant in large portions of Europe.

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

In Eucalyptus plantations, coppice rotations often yield less than initial rotations. The TECHS project (Tolerance of Eucalyptus Clones to Hydric, Thermal and Biotic Stresses) studied short rotation coppicing across a 3,000 km gradient. The main objective of this work was to compare the survival, sprouting and initial growth of Eucalyptus clones managed, and to examine factors that might influence the productivity of the coppice rotation: climate, genotypes and stocking. Eight of the TECHS sites spread from latitudes 6o S to 30o S were included in the coppice study, with 17 genotypes at each site. The initial rotation had been planted at a 3 x 3 m spacing, and also in a spacing trial at densities from 450 to 14,000 trees ha-1. Six months after harvesting the initial Eucalyptus rotation, average survival was 88%, with tropical clones showing over twice the sprouting biomass (6.7 vs 2.9 Mg ha-1) and four times the woody biomass compared to subtropical clones (4.7 vs 1.1 Mg ha-1). Greater initial water deficits had stronger sprouting and growth. Clones with higher belowground carbon allocation in the initial rotation performed better in coppicing, and precipitation became more influential after 12 months. Drought and spacing trial significantly affected growth.

Food insecurity remains a significant developmental challenge, particularly in rural areas, despite ongoing efforts to mitigate it. To better understand the persistence of this issue, this study investigates the causes of household food insecurity and the coping strategies employed by households in Zorkor Goo, Zorkor Kanga, and Zorkor Kadaare communities within the Bongo District of Ghana’s Upper East Region. A descriptive cross-sectional survey was conducted, sampling 196 households systematically from these communities. Data were collected through a structured questionnaire covering socio-demographic factors, causes of food insecurity, household coping strategies, and dietary intake. The analysis was performed using SPSS (Version 21.0), with food security status and dietary intake assessed via the FANTA Household Food Insecurity Access Scale (HFIAS) and Food Consumption Score, respectively. The study identified key factors contributing to food insecurity, including soil infertility, poor rainfall patterns, food spoilage, extravagant funerals, large family size, high unemployment, and lack of education. Major coping strategies among households included meal skipping, reducing meal size and frequency, migration, asset sales, and basket weaving. The findings revealed that 96.4% of households were severely food insecure, and over two-thirds (67.3%) exhibited poor dietary consumption. Notably, household employment levels, education, and food consumption scores were significantly associated with food insecurity (P<0.001). These findings underscore the need for targeted interventions addressing the root causes of food insecurity and enhancing household resilience in these communities.

The aim of the study was to explore attitudes towards climate change among wilderness seekers. The subjects were 273 (M=23.15; SD=7.72) adults. The respondents completed four questionnaires: Wilderness Novelty Seeking Scale, Wilderness Self-Efficacy Sale, Wilderness Courage Scale and Attitude Towards Climate Changes Scale. There were three distinct profiles of the respondents: Curious, who are interested in the wilderness but lack the skills and courage to explore dangerous wilderness places; Adventurous, who actively seek experiences in dangerous wilderness places and have survival skills; and Indifferent, who have little interest in the wilderness. The participants in these profiles differed in terms of attitude toward climate change. The Curious and Adventurous groups were significantly more concerned about climate change. In addition, they were more likely to believe that climate change is already having a negative impact on the lives of people in the places where they live. Furthermore, the Curious group experienced positive feelings towards climate change less often than the Adventurous group. On the other hand, the Curious group experienced significantly more negative feelings in relation to climate change. Finally, wilderness seekers (Curious and Adventurous) were statistically more likely to engage in pro-environmental behaviors in the context of climate change compared to the Indifferent group.

With the development of the energy sector based on renewable primary sources, structural changes are emerging for the entire national energy system. Initially, it was estimated that energy generation based on fossil fuels would decrease until its disappearance. However, the evolution of CO2 capture capacity leads to a possible coexistence for a certain period with the renewable energy sector. The paper develops this concept of coexistence of the two systems, with the positioning of green hydrogen not only within the renewable energy sector but also as a transformation vector for carbon dioxide captured in the form of synthetic fuels such as CH4 and CH3OH. The paper also analyzes the economic aspects related to price differences for energy produced in the two sectors, as well as their interconnection. The technical aspect, as well as the economic one, for storage through various other solutions besides hydrogen, has been highlighted. The development of the renewable energy sector and its demarcation from the fossil fuel energy sector, even with the transcendent vector represented by green hydrogen, leads to the deepening of dispersion aspects between the electricity sector and the thermal energy sector, a less mentioned aspect in current works but of great importance.

California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO), and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes, the interplay between Fire Weather Index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks, and geographical variations in the relationship between FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. Findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r > 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).

Climate change is a big challenge for agriculture since it affects crop productivity and yield. The increase of droughts, salinity, and soil degradation are some of the main consequences of climate change. The use of microorganisms has emerged as an alternative to mitigate them. Among these microorganisms, dark septate endophytes (DSEs) have garnered more attention in recent years. Various studies show that their association with plants helps reduce the harmful effects of abiotic stresses and increases nutrient availability, allowing plants to thrive under adverse conditions. This work reviews the effect of DSEs and the subjacent mechanisms that will help plants develop a higher tolerance to climate change.

Bettelmatt cheese, a cherished Italian culinary gem hailing from the picturesque Val d'Ossola region, is deeply intertwined with its natural environment. This article explores the intricate relationship between the organoleptic attributes of Bettelmatt cheese and the challenges posed by climate change. The sensory qualities of this cheese, including its flavor profile, texture, and aroma, are profoundly influenced by the alpine pastures where the cows graze, the unique terroir, and the traditional production methods. However, as climate change continues to impact ecosystems and weather patterns, it raises questions about the resilience and adaptability of this traditional cheese. In addition to these challenges, the article would like to explore the complexities of regulation and protection of this cheese, crucial for food and gastronomic sciences.

Background:. Knowledge and positive perception of climate change are crucial for public participation in activities that contain climate change. Limited studies, particularly in South Africa have reported on the knowledge and perceptions of climate change by university students. Study Aim: This study aimed to assess the level of knowledge and perceptions of climate change by the science students at the University of South Africa (UNISA). Methods: This was a quantitative cross sectional survey, undertaken among science students using questionnaire emailed to 500 students in the School of Science through Unisa email system. Bivariate logistic regression was used to test the association between socio-demographics, level of knowledge and perceptions of climate change. Results: A total of 420 students participated in the study. They were predominantly male (70.3%), mostly younger than 35 years of age. Most of the respondents were in the 2nd (34.7%) and 3rd (33.8%) year of study. Majority of respondents (97.9%) knew and perceived (93.6%) that climate change was happening. Overall, 93.8% of respondents had an excellent knowledge and basic concepts of climate change. Conclusion: The majority of students were knowledgeable and had positive perceptions about the basic concepts of climate change. However, the year of study was not significantly associated with positive perceptions of climate change. There is need to include climate change modules in South African university curriculum.

Both globally and in Hungary, agriculture is one of the industries that is most vulnerable to weather and climate extremes. Intense temperature rises, spatial and temporal variations in precipitation, and significant changes in extreme climatological and weather parameters have contributed to changes in the conditions of cropland, crop losses, and impacts on crop quality in recent years. This paper depicts the transformation of the domestic agricultural sector due to the extreme drought shock of 2022, as well exploring the adaptation strategies applied. The research is based on official agro-climate database and crop data, and the temperature, precipitation, and radiation during the growing season are all examined. The agro-meteorological properties in Hungary had to be investigated for the entire year and all four of its seasons, with indicator analysis projected onto the ever-increasing and dormant seasons. Long-term climate analysis is necessary to understand the historic drought of 2022 and the success of future adaptation and mitigation techniques. The results can help smallholders effectively reduce the adverse impacts of drought conditions, thereby increasing their adaptation to similar shocks.

The intricate relationship between physical and social environments within organizations plays a pivotal role in shaping sustainable innovation endeavors. This paper presents a comprehensive analysis of two key dynamics that have garnered substantial scholarly attention for promoting sustainable innovation: the physical environment and the organizational climate. To elucidate the intricate interplay between these dynamics, we propose a novel three-dimensional framework that guides the modeling of the intricate processes through which the physical environment and innovation climate synergistically influence innovation outcomes. Building on this framework, we delve into an in-depth literature review concerning physical environments that exert a significant impact on innovation. Through this review, we identify and elaborate on four pivotal elements of the physical environment: communality, personalization, comfort, and healthiness. Leveraging insights gleaned from this review, we outline two promising avenues for future research in the realm of the physical environment's interaction with the innovation climate. Furthermore, we underscore the critical importance of adopting an interdisciplinary approach that seamlessly integrates insights from both the physical and social domains to comprehensively understand the sustainable innovation landscape.

This study examines the projected impact of climate change on the Density Altitude (DA) at Chinese airports during the summer by the end of the 21st century. Findings indicate that climate change is expected to significantly increase the DA at all Chinese airports, with an estimated rise between 300 and 800 feet. The analysis suggests temperature increases will universally contribute to a rise in DA. Pressure changes, however, are more variable. Most airports are predicted to see an increase in pressure, which could offset some temperature effects on the DA. Airports in eastern China are expected to see a decrease in pressure, amplifying the effects on DA and creating operational challenges.

Understanding how climatic variables impact the reference evapotranspiration (ET0) is essential for water resource management, especially considering potential fluctuations due to climate change. Therefore, we used the Sobol method to analyze the spatiotemporal variations of Penman-Monteith ETo sensitivity to the climatic variables: downward solar radiation, relative humidity, maximum and minimum air temperature, and wind speed. The Sobol’s indices variances were estimated by Monte Carlo integration, setting the sample limits to 2.5 and 97.5 percentiles of the daily data of 33 automatic weather stations located in the state of Mato Grosso, Brazil. The results of the Sobol analysis indicate considerable spatiotemporal variations in the sensitivity of ETo to climatic variables and their interactions. The dominant climatic variable responsible for ET0 fluctuations in Mato Grosso is incident solar radiation, which has a more significant impact in humid environments, as observed in the areas of the Amazon biome in the state. Air relative humidity and wind speed have higher sensitivity indices during the dry season in the areas of the Cerrado biome (Savanna) in Mato Grosso. Our findings show that changes in solar radiation, relative humidity, and wind speed cannot be ignored when analyzing changes in reference evapotranspiration.

The Antarctica and High Arctic regions are extreme environments, with average maximum temperatures below 0 °C for most days of the year. Interestingly, fungi inhabit these regions. This review describes the history of fungal surveys near the Syowa Station and the fungal diversity in this region. In the High Arctic region, I summarized the changes in fungal communities in glacial retreat areas of Ny-Ålesund, Norway and Ellesmere Island, Canada in response to climate change. In addition, growth and enzyme secretion ability of Antarctic and Arctic fungi at sub-zero temperatures are presented. Finally, I have also provided the future directions of Antarctic and Arctic fungal research.

Changes in the dates of phenological phases of plants and insects reflect changes in climate. The aim of the study was to determine the phenological patterns and interrelationships of spring-flowering entomophilous plants (Corylus avellana L., Alnus incana Moench., Tussilago farfara L., Salix caprea L., Acer platanoides L., Taraxacum officinale L., Prunus L., Malus domestica Mill.) and the honey bee (Apis mellifera L.) in response to climate change. The research was carried out at Vokė Branch of the Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry, using data from phenological observations during 1961–2020. The results of the studies showed that over a 60-year period, a trend towards earlier dates of all phenological events studied was observed. Significant and larger-scale changes occurred starting from the decade 1981–1990. Throughout the entire study period, with the exception of one decade, the dates of honeybee emergence on flowers correlated reliably with the dates of entomophilous plant phenophases. Due to the advance of plants phenophase dates the synchrony with honeybee emergence dates changes however, these changes had a positive effect on the foraging conditions of overwintering honeybees.

The build-up of greenhouse gases (GHGs) is causing warmness in the Earth’s atmosphere, resulting in climate change. The transport sector is one of the active members of GHG emissions and it is imperative to use sustainable transport sources to control climate change. The measure aims to encourage citizens to stop using their private vehicles as their choice of transport and instead opt for joint sustainable mobility during traveling. In this study, a quantitative research method was used and data were collected from a sample of 410 respondents through questionnaire. On the other hand, study also took a simulation-based (N=10000) sample size of private vehicle data. The data were analyzed using structural equation modelling. The results revealed that sustainable transportation, climate change technologies and electric rail vehicles reduce climate change in the ecoregions of China. We conclude that sustainable transportation policies could be formulated and implemented to reduce climate change. In response to the research results, it is recommended that, since climate change is a multi-level governance issue and the outdated pyramidal transport industry models must be shifted to a sustainable transportation system model.

The study presents an assessment of climate suitability for outdoor leisure activities in Romania using the Holliday Climate Index (HCI) for the near future (2021-2040), focusing on unfavorable and good climate conditions. The analysis employs data from an ensemble model in the context of RCP45 and RCP85 climate change scenarios. The results indicate that the number of days with low weather suitability is decreasing in almost the entire country, especially during the warm season, while during the winter and spring extended regions may be characterized by a higher number of days favorable for outdoor activities than during the current climate. An estimation of the impact of climate changes on tourism flux in Romania is further carried out, suggesting that the increasing attractivity of climate conditions may lead to an increased number of tourist overnights in the near future, more pronounced in rural destinations.

The paper provides a critical synthesis of analysis and evaluation of some case studies in the Italian national context, which allowed, through an inductive method, to assess, in terms of integration and coherence, the process of transposition of climate change adaptation contents, possibly already contained within a regional urban framework (Regional Urban Laws) or specific Regional Adaptation Strategies or Local Adaptation Plans, within the territorial and urban planning tools of metropolitan or local scale.

Climate change is the long-term shift in global weather patterns, largely caused by anthropogenic activity of greenhouse gas emissions. Global climate temperatures have unmistakably risen and naturally-occurring climate variability alone cannot account for this trend. Human activities are estimated to have caused about 1.0 °C of global warming above the pre-industrial baseline and if left unchecked, will continue to drastically damage the Earth and its inhabitants. Globally, natural disasters and subsequent economic losses have become increasingly impactful as a result of climate change. Both wildlife ecosystems and human habitats have been negatively impacted, from rising sea levels to alarming frequency of severe weather events around the world. Attempts towards alleviating the effects of global warming have often been at odds and remain divided among a multitude of strategies, reducing the overall effectiveness of these efforts. It is evident that collaborative action is required for avoiding the most severe consequences of climate change. This paper evaluates the main strategies (industrial/energy, political, economic, agricultural, atmospheric, geological, coastal, and social) towards both mitigating and adapting to climate change. As well, it provides an optimal combination of seven solutions which can be implemented simultaneously, working in tandem to limit and otherwise accommodate the harmful effects of climate change. Previous legislation and deployment techniques are also discussed as guides for future endeavors.

Climate change poses a major threat to development in most low and middle-income countries, especially the sub – Saharan Africa. Wurompo is a small farming community in the Wenchi Municipality of the Brong-Ahafo region of Ghana that depends on rain-fed agriculture activities for livelihood. In recent years, droughts, unpredictable rainfall pattern and crop failure have become common in the area. The study assessed knowledge and awareness, effects of climate change on female farmers, and their adaptation strategies. A case study in design, qualitative methods were used to collect data from 50 purposefully selected participants. Data were analyzed using themes and sub-themes generated from the research questions. Findings showed lack of adequate information and knowledge on climate change and its effects. Climate change has impacted negatively on these farmers stemming from decline in crop production and unavailability of adequate water supply in due season. Challenges to climate change adaptation are poverty, poor basic infrastructure, and modern farming practices. Farmers must be educated on climate change and its effects, with training on the necessary adaptation strategies to build their resilience. Policies that target rural farmers to adapt to climate change, and device modern agricultural techniques and practices are also necessary.

Natural disasters ravage the world's cities, valleys, and shores on a monthly basis. Having precise and efficient mechanisms for assessing infrastructure damage is essential to channel resources and minimize the loss of life. Using a dataset that includes labeled pre- and post- disaster satellite imagery, we train multiple convolutional neural networks to assess building damage on a per-building basis. In order to investigate how to best classify building damage, we present a highly interpretable deep-learning methodology that seeks to explicitly convey the most useful information required to train an accurate classification model. We also delve into which loss functions best optimize these models. Our findings include that ordinal-cross entropy loss is the most optimal loss function to use and that including the type of disaster that caused the damage in combination with a pre- and post-disaster image best predicts the level of damage caused. Our research seeks to computationally contribute to aiding in this ongoing and growing humanitarian crisis, heightened by climate change.

Not only are humans responsible for the anthropogenic causes of currently observed climate change, but we are also responsible for our responses to climate change. How we choose to respond provides important insights into our ability to collectively act in the face of threats with the unique characteristics of climate change. This communication attempts to provide an overview of some the difficulties in forging new policy directions along our coastlines in an era of climate change. It is meant as a referential framing for the research presented in this special issue. As this communication is being written, the world is gripped by a global pandemic caused by a variant of the coronavirus. There are important corollaries between the underlying characteristics of the coronavirus and the causes and effects of climate change. Seeing how the global citizenry is responding to the current epidemic provides some insight into the difficulties in fostering collective action towards climate change. As with the pandemic, the issue is not really one of understanding the problem, but rather the varying human responses to the problem. We can expect the same difficulties as we continue to confront the ever-growing problem of climate change.

This manuscript describes the construction and validation of high resolution daily gridded (0.05° × 0.05°) rainfall and maximum and minimum temperature data for Bangladesh : the Enhancing National Climate Services for Bangladesh Meteorological Department (ENACTS-BMD) dataset. The dataset was generated by merging data from weather stations, satellite products (for rainfall) and reanalysis (for temperature). ENACTS-BMD is the first high-resolution gridded surface meteorological dataset developed specifically for studies of surface climate processes in Bangladesh. Its record begins in January 1981 and is updated in real-time monthly and outputs have daily, decadal and monthly time resolution. The Climate Data Tools (CDT), developed by the International Research Institute for Climate and Society (IRI), Columbia University, is used to generate the dataset. This data processing includes the collection of weather and gridded data, quality control of stations data, downscaling of the reanalysis for temperature, bias correction of both satellite rainfall and downscaled reanalysis of temperature, and the combination of station and bias-corrected gridded data. The ENACTS-BMD dataset is available as an open-access product at BMD’s official website, allowing the enhancement of the provision of services, overcoming the challenges of data quality, availability, and access, promoting at the same time the engagement and use by stakeholders.

Changing mobility patterns combined with changes in the climate present challenges and opportunities for global health, requiring effective, relevant and humane policy responses. This study used data from a systematic literature review that examined the intersection between climate change, migration and health. The aim of the present study was to synthesize policy recommendations in the peer-reviewed literature, regarding this type of environmental migration with respect to health, to strengthen the evidence-base. Systematic searches were conducted in four academic databases (PubMed, Ovid Medline, Global Health and Scopus) and Google Scholar for empirical studies published between 1990 – 2020 that used any study design to investigate migration and health in the context of climate change. Studies underwent a two-stage protocol-based screening process and eligible studies were appraised for quality using a standardized mixed-methods tool. From the initial 2,425 hits, 68 articles were appraised for quality and included in the synthesis. Among the policy recommendations, six themes were discernible: (1) avoid the universal promotion of migration as an adaptive response to climate risk; (2) preserve cultural and social ties of mobile populations; (3) enable the participation of migrants in decision-making in sites of relocation and resettlement; (4) strengthen health systems and reduce barriers for migrant access to health care; (5) support and promote optimization of social determinants of migrant health; (6) integrate health into loss and damage assessments related to climate change. The results call for transformative policies that support the health and wellbeing of people engaging in, or affected by mobility responses, including those whose migration decisions and experiences are influenced by climate change, and to establish and develop inclusive migrant healthcare.

Background: The current coronavirus disease 2019 (COVID-19) is spreading globally at an accelerated rate. There is some previous evidence that weather may influence the incidence of COVID-19 infection. We assessed the role of meteorological factors including temperature (T) and relative humidity (RH) considering the concentrations of two air pollutants, inhalable coarse particles (PM10) and nitrogen dioxide (NO2) in the incidence of COVID-19 infections in Finland, located in arctic-subarctic climatic zone. Methods: We retrieved daily counts of COVID-19 in Finland from Jan 1 to May 31, 2020, nationwide and separately for all 21 hospital districts across the country. The meteorological and air quality data were from the monitoring stations nearest to the central district hospital. A quasi-Poisson generalized additional model (GAM) was fitted to estimate the associations between district-specific meteorological factors and the daily counts of COVID-19 during the study period. Sensitivity analyses were conducted to test the robustness of the results. Results: The incidence rate of COVID-19 gradually increased until a peak around April 6 and then decreased. There were no associations between daily temperature and incidence rate of COVID-19. Daily average RH was negatively associated with daily incidence rate of COVID-19 in two hospital districts located inland. No such association was found nationwide. The sensitivity analyses indicate the results are robust. Conclusions: Weather conditions, such as air temperature and relative humidity, may not be important factors affecting the COVID-19 incidence in the arctic and subarctic winter and spring. More evidence is needed on the associations between weather and COVID-19 during different seasons.

An opinion dependent cross sectional survey was conducted among charland peoples of Noakhali, Bangladesh with a view to identify the factors that affect green economy. Nijhumdwip Island and Tamaruddi union are highly affected by cyclone and soil salinity. Unpredictable rainfall is the most acute in Nijhumdwip. Lack of information the main problem in Nijhumdwip Island. Farmers are found less interest in integrated farming and crop diversification. Few farmers from Sonadia Union are involved in homestead gardening. Regression analysis have shown a negative relationship (p<0.001) between education of stockholders and decrease of crop production. On the other hand education level of stockholders is to be found positively (p<0.05) varied with decrease of food insecurity. So it can be said that educated farmers are more adaptive against climate change.

This research paper aims to examine the relationship between CO2, temperature, area, fertilizers and rice production in Pakistan. This study used Augmented Dickey Fuller (ADF) and Phillips Perron (PP) unit root tests to check the order of integration of each variable. The cointegration analysis with ARDL bounds testing approach is used to examine the impact of climate change on rice production in Pakistan over time series data from the period 1968 to 2014. The parameter stability test of the model is also checked at the end. The results of estimation show that the important variables of the study are cointegrated demonstrating the presence of long-run association among them. Furthermore, climate change factors, e.g. CO2 and temperature have a long-run and short-run positive effect on the production of rice in Pakistan. This present work is original and it is first time empirically tested the impact of climate change on rice production in Pakistan. The annual time series data of 47 years enhances the validity of the empirical findings. The most fruitful finding of this research is that rice production in Pakistan is positively influenced by emission of carbon dioxide (CO2) at 5 percent significance level in both long-run and short-run.

In this study, air temperatures were collected between 1985 and 2016 and compared to water temperatures in four locations in the distribution system of Pasadena Water & Power (PWP) that received imported surface water between 2001 and 2016 and from the purveyor of imported water. The concentration of chloramine residual and nitrite concentrations were collected between 2001 and 2016 these five locations. The results indicate that the median nighttime temperature of the period 2009 - 2016 was 1.6 ^oC warmer than the period of 1985 - 2000 and 0.5 ^oC warmer than the period 2001 - 2008. The median water temperature in the four distribution system samples increased by 0.8 ^oC to 1.4 ^oC depending on the location over the study period (p<0.001). The median chloramine concentration fell significantly (p<0.001) at three distribution system locations and the nitrite concentrations increased significantly at all four distribution system locations.

The purpose of this article is to analyze urban form through the mapping of morphological indices, namely impervious surface fraction, building density, verticality, height/width ratio, roughness length, and porosity, to support urban planning in the city of João Pessoa, PB, in northeastern Brazil. The application of this study identifies and calculates such significant indices for the city's urban space from a Geographic Information System (GIS) model. The spatial indices play notable roles in climate at different scales, developing guidelines to maximize environmental quality, promote improvements to thermal comfort, minimize the urban heat island in the city of João Pessoa, and provide relevant data (considering microclimate aspects), guiding decisions related to the planning process.

The province of Macerata, Italy, is a topographically complex region which has been little studied in terms of its temperature and precipitation climatology. Temperature data from 81 weather stations and precipitation data from 55 rain gauges were obtained, and, following quality control procedures, were investigated on the basis of 3 standard periods: 1931-1960, 1961-1990 and 1991-2014. Spatial and temporal variations in precipitation and temperature were analysed on the basis of six topographic variable (altitude, distance from the sea, latitude, distance from the closest river, aspect, and distance from the crest line). Of these, the relationship with altitude showed the strongest correlation. Use of GIS software allowed investigation of the most accurate way to present interpolations of these data and assessment of the differences between the 3 investigated periods. The results of the analyses permit a thorough evaluation of climate change spatially over the last 60 years. Generally, the amount of precipitation is diminished while the temperature is increased across the whole study area, but with significant variations within it. Temperature increased by 2 to 3°C in the central part of the study area, while near the coast and in the mountains the change is between about 0 and 1°C, with small decreases focused in the Appennine and foothill belt (-1 to 0°C). For precipitation, the decrease is fairly uniform across the study area (between about 0-200 mm), but with some isolated areas of strong increase (200-300 mm) and only few parts of territory in which there is an increase of 0-200 mm, mainly in the southern part of the coast, to the south-west and inland immediately behind the coast. The monthly temperature trend is characterized by a constant growth, while for precipitation there is a strong decrease in the amount measured in January, February and October (between 25 and 35 mm on average).

New energy vehicles (NEVs) have been proposed as a promising technology to reduce greenhouse gas (GHG) emissions. China is one of the leading countries in the development of NEVs, and a wide range of companies, including large and smaller businesses, are involved in the Chinese NEV market. Given that the NEV market involves the creation of nascent technologies, there are significant barriers to the development of NEV companies in the business growth stage. This is particularly significant in the case of small and medium-sized enterprises (SMEs). This study surveyed 100 NEV SMEs in China using a structured questionnaire to determine the most significant barriers to the growth of their businesses. Calculating the relative importance index (RII) from the collected questionnaire responses revealed that the most significant barrier at the growth stage is the lack of skilled scientists in China. The most important category of barriers is legal and institutional barriers, which suggests that government intervention in business activities, taxes, and unclear regulations are viewed by entrepreneurs as a serous hindrance to further development in the NEV industry.

A large-scale, high-resolution, fully coupled hydrological/reservoir/hydroelectricity model is used to investigate the impacts of climate change on hydroelectricity generation and hydropower potential of non-powered dams across the Northeast United States megaregion with 11,037 dams and 375 hydroelectric power plants. The model is calibrated and validated using the U.S. Department of Energy records. Annual hydroelectricity generation in the region is 41 Terawatt-hours (Twh). Our estimate of the hydropower potential of non-powered dams adds up to 350 Twh. West Virginia, Virginia, Pennsylvania, and New York have significant potential for generating more hydroelectricity from already existing dams. On the other hand, this potential virtually does not exist for Rhode Island and Delaware and is small for New Jersey and Vermont. Climate change may reduce annual hydropower potential from non-powered dams by up to 13% and reduce current annual hydroelectricity generation by up to 8% annually. Increased rainfall in winters and earlier snowmelt in springs result in an increase in regional water availability in December through March. In other months, reduced precipitation and increased potential evapotranspiration rates combined with reduced recharge from the shift in spring snowmelt and smaller snowpack result in a decrease in availability of water and thus hydroelectricity generation. This changes call for the recalibration of dam operations and may raise conflict of interests in multipurpose dams.

This paper proposes a method to utilize weather and land cover models to generate future environmental scenarios, and presents the watershed models to simulate the hydrological impact on watershed-scale hydrology. The Weather Generator model and General Circulation Model were applied to produce rainfall and local temperature under different climate conditions, and the Conservation and Land Use and its Effects model was incorporated to simulate future land cover variability. The circumstances of future climate and land cover changes were used as inputs to drive the HEC-HMS rainfall runoff model for obtaining surface runoff in a mountainous area. The WASH123D model was then utilized for the entire watershed simulation. Modeling results were then examined to discuss hydrological impacts on three different time periods: near future (2020-2039), future (2050-2069), and distant future (2080-2099). The Fengshan Creek basin in northern Taiwan was selected as study site. Simulations results indicated that the influence of climate change revealed more relevant effects when compared to local land cover changes. The ground water levels tended to diminish as the land cover area changed. In addition, both river and groundwater levels reveal that it is drier in dry season and wetter in wet season in future.

Recent satellite measurements of glacier mass balance show mountain glaciers all over the world had generally negative mass balances in the first decades of the 21st century. Mean summer temperatures all over the world rose from 1961-90 to 1991-2020, implying increasingly negative mass balances. We study archived annual balances for 38 Northern Hemisphere glaciers to assess changes within in the 19612020 period. We use a modified doublemass curve to visualize mass balance changes occurring around 1990. Mean balances 196190 were already small negative for many of the studied glaciers and became even more negative in 19912020 for glaciers in the Alps, at high latitudes and in western North America. The largest mass balance changes are for some glaciers in the Alps. We are unable to explain the lack of change in mean balance for one glacier in High Mountain Asia. We find complex changes for eight glaciers in Scandinavia, even including one glacier with positive balance. We explain these changes by visualizing deviations of winter and summer balances from their respective 1961-90 mean values. High winter balances in the 1990s for Scandinavia partly obscured the emerging trend of increasingly negative summer balances, which we expect to continue in the future.

When attempting to quantify future harms caused by carbon emissions and to set appropriate energy policies, it has been argued that the most important metric is the number of human deaths caused by climate change. Several studies have attempted to overcome the uncertainties associated with such forecasting. In this article, approaches to estimating future human deaths tolls from climate change are compared and synthesized, and implications for energy policy are considered. Several studies are consistent with the “1000-ton rule,” according to which a future person is killed every time 1000 tons of fossil carbon are burned (order-of-magnitude estimate). If warming reaches or exceeds 2°C this century, mainly richer humans will be responsible for killing roughly 1 billion mainly poorer humans through anthropogenic global warming. Such mass manslaughter is clearly unacceptable. On this basis, relatively aggressive energy policies are summarized that would enable immediate and substantive decreases to carbon emissions. The limitations to such calculations are outlined and future work is recommended to accelerate the decarbonization of the global economy while minimizing the number of sacrificed human lives.

In recent years, the need to make the built environment more resilient and adaptable to climate change has become increasingly evident. In Europe, this aspect concerns the vast majority of existing buildings, which present several deficiencies from the energy-efficiency point of view, considering they were designed before the introduction of modern energy codes. Nowadays, it is possible to retrofit existing buildings using advanced and high-efficient technologies such as Double Skin Façades (DSFs). The research aims to evaluate the use of properly designed DSFs for the energy restoration of existing buildings. In detail, various DSF configurations are applied to a residential building located in central Italy and investigated under present and future climate conditions, estimated through regional climate models. The results underline that all the analysed Double Skin Façades confirm to be a useful option, and, in particular, the Multi-Storey typology allows drastic energy needs decrement. Moreover, the general increase in temperatures and solar radiations could affect the building energy performance, and the insertion of DSF can mitigate the climate change effects, reducing the predicted energy consumption and ensuring better behaviours than the building in its original state.

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.

The goal of Man and the Biosphere (MAB) Programme is to support sustainable development through effective management, innovative technologies, policy suggestion and governance. Today, the concept of Biosphere Reserves plays an important role in scientific investigations, generating knowledge, and experiences to link socio-economic development and biodiversity conservation for human well-being. This research, through an independent study which takes place in the Hungarian Biosphere Reserves of Pilis and Kiskunság aims at identifying practical sustainable business models which are suitable for supporting livelihood of locals. In this research, the two Biosphere Reserves serve as the learning sites under the light of global principles and state-of-the-art-of knowledge on sustainable development and sustainable business models. To do so, the state-of-the-art-of sustainable business model has been investigated through a comprehensive academic research. The lessons that learned from this investigation are used to support the data gathering method and planning the field trips to identify the sustainable business models currently in use at the Biosphere Reserves. This research particularly had been interested in small-sized sustainable business models practiced by small communities or families in various zones of Biosphere Reserves. First set of interviews and questionnaires designed to identify the business models in practice. The results identify foraging the wild plants in the buffer zone and transition areas as a potential sustainable business model in practice. Further interviews and surveys were conducted with foragers shows the beneficial of their practice on the local ecosystem and in increasing awareness on the deep connection with the ecosystems. The sustainable business model of foraging in addition to providing a sustainable livelihood for the locals maintains a spiritual connection between people and land. The identified sustainable business model can further be educational and practical for other 685 biosphere reserves.

This research investigates the transformative role of digital health solutions in tackling climate-related health challenges. The study underscores the potential of digital health innovations to empower individuals and communities, fostering resilience and collective action in addressing the health impacts of climate change. By enhancing the accessibility of critical health information and enabling real-time responses, these digital tools not only mitigate immediate risks but also contribute to long-term public health strategies. The findings highlight the importance of integrating digital health solutions into broader climate health initiatives, demonstrating their capacity to bridge gaps in public health infrastructure, especially in vulnerable populations. This research calls for continued investment and innovation in digital health technologies as a vital component of global efforts to combat the growing challenges posed by climate change

Zimbabwe has ambitious and laudable GHG mitigation targets. Compared to a coal based future emissions reductions by 33% per capita by 2030 are targeted, by implementing a set of identified nationally determined contributions (NDCs). If historical climate conditions continue, it can do this at low or negative cost. However, anticipated conditions may not continue, and of the planned emissions reductions in the NDCs, 88% would come from the expansion of hydropower, which is driven by rainfall. If climate change causes the extreme droughts witnessed in recent years to become more frequent, embarking on Zimbabwe’s NDC future (underpinned by its official system development plan) may be expensive and further cripple the economy. Note that the economy is already being strangled by constrained power supplies due to unusually dry conditions in the Zambezi river basin. If the NDC Future is pursued, but the climate becomes drier, proactive efforts might be made to overcome the power shortages. However, this may result in a rapid ramp up of greenhouse gas emissions if the country turns to coal to reinforce its system and increase its resilience against hydropower vulnerability and the costs that would otherwise ensue. If the country were to keep its NDC investments and supplement them with more aggressive deployment of clean adaptation options, strongly positive outcomes appear possible. Specifically, this would require increased deployment of renewable energy technologies, a restructured power market, and deep increases in energy efficiency investments. In so doing, the country would not only exceed its NDC targets, but also reduce costs in a manner that is climate resilient. This would not remove the country's need for hydropower and some level of coal reliance. However, it will introduce requirements to ensure flexibility in both hydropower and coal power production. For hydropower, power stations will need to provide and be recompensed for providing ‘balancing services’, that is, storing water and producing electricity when the wind is not blowing, nor sun shining. In order to ensure continuous output from mines, it may require intelligent stockpiling combined with dynamic forecasting. This would apply not only to production in Zimbabwe, but potentially for neighboring countries. Doing so would allow predictable mining activities, but allow electricity systems to absorb low cost, low carbon hydropower at high rainfall periods. To make the NDCs resilient via clean adaptation, strong institutional restructuring is required. However, internalizing those costs and moving to advanced market structures and business cases may strain the capacity of current institutions.

The Greenland ice sheet is a major contributor to sea level rise, adding an estimated 0.47 +/− 0.23 mm/yr to global mean sea level between 1991 and 2015 (van den Broeke et al., 2016). Making sea level rise projections for the future and understanding the processes controlling current observed rates of sea level rise are crucially dependent on understanding the present-day state of the ice sheet. Here, we provide an overview of the current state of the mass budget of Greenland based on satellite gravimetry and remote sensing observations of surface elevation change, ice sheet velocity and calving front positions. We also combine these essential climate variables with a regional climate model (RCM) output from an ice sheet model (ISM) to gain insight into poorly understood ice sheet dynamical and surface mass processes. On average from 1992 to 2017 the ice sheet in some locations has lost up −2.65 m/yr in elevation based on ESA Radar altimetry analysis. Calving fronts have retreated all around Greenland since the 1990s and in only two out of 28 study locations have they remained stable. The locations of grounding lines at 5 key glaciers with floating ice tongues have remained stable over the observation period. However a detailed case study at Petermann glacier with an ice fracture model shows the sensitivity of these floating ice shelves to future climate change. GRACE gravimetric mass balance (GMB) data allows us to tie together disparate lines of evidence showing that Greenland has lost about 265 +/− 25 Gt/yr of ice over the period 2002 to 2015. RCM and ISM simulations show that surface mass processes dominate the overall Greenland ice sheet mass budget except for areas of fast ice sheet flow but marked differences between models and between models and observations indicate that not all processes are captured accurately, indicating areas of greater uncertainty and directions of future research for future sea level rise projections.

Climate disruption has serious impact on the entire agricultural production system at global scale. Research and development efforts as well as innovations may be necessary to offset the negative impact of climate change. Adaptation to climate change has remained a major socio-ecological issue in the Northern Region of Cameroon for three decades. Several agricultural innovations have been promoted in this region by international organizations and NGO, within the framework of different projects and programs, with a strong potential for adaptation to climate change. However, little is still known about agricultural innovations that have evolved over time in response to climatic factors. Therefore, research aiming at identifying adaptation strategies and practices at the local level is still limited. Also, rural communities and households do not always have access to these agricultural innovations because of lack of efficient innovation support service for agriculture. Through surveys and focus group discussions carried out in several villages in the Northern Cameroon Region, this study provides empirical data on emerging agricultural innovations in contrasting socio-economic, agricultural and ecological contexts. The study demonstrated that the process of adaptation at the village level using agricultural innovations is the result of various forms of support provided by a diversity of actors. However, heads of household (83%) are more involved in innovative initiatives to the detriment of other social strata, resulting in an imbalance in access and proximity to agricultural innovations. Also, support for agricultural innovations is segmented over time and weakens the sustainable transformation of adaptation due to the lack of coordination and the very low visibility of permanent structures dedicated to supporting agricultural innovations.

The objective of the described activity is to develop technologies or proposals that can be implemented within the cycle to enhance the relationship between climate change, water, energy, and food. The focus is on analyzing natural treatment systems for wastewater (NTSW) within the context of Macaronesia, considering factors such as life cycle assessment (LCA), carbon footprint, impacts, and mitigation capacity. The analysis of real case data from the Canary Islands and Cape Verde will inform the development of appropriate technologies tailored to different areas and scales within Macaronesia. This work includes a comprehensive life cycle analysis of the Santa Catarina (Cape Verde) NTSW. This analysis encompasses: a) Inventory analysis of the construction phase: This involves the assessment of inputs and outputs associated with the construction of the NTSW, including materials, energy consumption, transportation, and waste generation. The maintenance and operation phase is then evaluated, with a focus on the ongoing maintenance and operation activities required for the NTSW, including energy consumption, water usage, chemical inputs (if any), labour, and equipment maintenance. Finally, the impacts of the NTSW are evaluated. The environmental, social, and economic impacts generated by the NTSW are assessed. This includes an analysis of factors such as carbon emissions, water usage, land use, ecosystem impacts, human health effects, and economic costs. By conducting a comprehensive analysis of the Santa Catarina NTSW, the document aims to provide insights into the environmental performance and sustainability of the system. This information can then be used to identify areas for improvement, develop mitigation strategies, and inform decision-making processes regarding wastewater treatment technologies in Macaronesia. Furthermore, lessons learned from real case studies in the Canary Islands and Cape Verde can be applied to similar regions within the Macaronesia archipelago.

This article examines the impact of climate change on the hydrometeorological state of some lakes and reservoirs in the Akmola and North Kazakhstan regions. Time series with values of various climate parameters for the period 1986-2023 are used for the climate analysis; the reliability of the results was assessed using the Fisher criteria. Hydrometric indicators were studied using the ArcGIG program. Using GIS to spatially analyze water climate data, 8-channel satellite images from 1995 to 2023 were used. During the study, it was found that the area of the main lakes has undergone changes.

CO2 emission activity of xylotrophic fungi response to an increase in temperature in the range of 10-30 °C on the example of pure dikaryotic cultures of Fomes fomentarius s. str., F. inzengae, Fomitopsis betulina, F. pinicola, Phellinus igniarius was analyzed. Emission activity was assessed by the difference in CO2 concentration in 0.5-liter exposure chambers with Petri dishes with mycelium growing on agar at the beginning of exposure and an hour later using a Gasmet DX-4030 FTIR spectrometer (Gasmet Technologies Oy, Finland), error measurements ±50 ppm. Specific (μg CO2/cm2/h) and total (μg CO2/h) emission activity and its relationship with temperature and size (area) of the mycelium were assessed. It has been shown that in the range of 10-30 °C, the specific and total CO2 emission activity of the mycelium is closely and positively related to temperature. Specific emission, which is an indicator of the respiratory activity of the mycelium, does not depend on its size; its only driver is temperature, the relationship with which is linear: an increase in temperature by 10 °C causes an increase in the specific emission activity of the mycelium by 1.7 times. The total CO2 emission activity, which is an indicator of the total amount of CO2 emitted, is directly proportional to the specific emission activity and the size of the mycelium. In the range of 10-30 °C, an increase in temperature causes an almost equal increase in both the specific emission activity of the mycelium (Q10 1.7) and its growth (Q10 1.5) and causes an exponential increase in the total emission of CO2. This must be taken into account when predicting CO2 emissions from woody debris under climate change, as it could potentially contribute to accelerating climate change.

Urban ecology is a factor that significantly affects the urban landscape. Proper management and sustainable planning of ecosystems in cities can help urban landscapes to increase biodiversity and contribute to the efficient use of natural resources. In this framework, the integration of green spaces and ecosystem services can improve the quality of urban landscapes by increasing the health and resilience of urban ecosystems. This paper, which examines the effects of ecological factors on urban landscape in Antalya-Muratpaşa, presents a detailed analysis using various data sets. Within the scope of the research, the number of vehicles, carbon emissions by years, the ratio of green areas to population, CORINE data and land surface temperatures were analyzed. In addition, the change in land use from 1990 to 2018 and the land surface temperature forecast for 2040 and 2041 shed light on the evolutionary processes in the city. In an effort to understand the ecological status of Antalya-Muratpaşa, the paper highlights the potential impacts on the sustainability of the urban landscape. In particular, predicting the possible impacts of future land use on the urban landscape with population growth offers a strategic approach in planning processes. This study can be an important resource for urban planners, researchers and local governments because the data in the Antalya-Muratpaşa case provides a comprehensive overview that can guide those who want to consider sustainability and environmental factors in urban landscape planning. In line with this perspective, it is recommended to encourage green roof and green facade practices, rainwater harvesting, gray water recycling, etc. in new constructions.

This paper explores the emergence of Sustainability-Linked Bonds (SLBs) as an innovative instrument to finance sustainability objectives. SLBs have emerged as a transformative financial instrument, establishing an explicit link between cost of funding and sustainability objectives. SLBs were first launched in 2019 and represent 7% of labelled bonds, still dominated by the more established green bonds. Issuance of SLBs now exceeds $250 billion. Following initial enthusiasm, they are now facing criticism. In the context of the growth of sustainable finance and concerns of greenwashing, this paper investigates ways to enhance the design of SLBs. Drawing on literature and expert interviews, the findings highlight the strong potential of SLBs to contribute to sustainability financing, especially in hard-to-abate sectors. The paper identifies the key positive attributes of SLBs and their limitations in five areas: key performance indicators’ (KPI) selection, sustainability performance targets’ (SPT) calibration, bond characteristics, reporting practices, and resource requirements. Recommendations to financial intermediaries, issuers and policy makers include defining standardized KPIs based on a materiality assessment, requesting SPTs to be supported by science and in line with an issuer’s core strategy, tailored step-up mechanisms and avoidance of call loopholes, and stricter reporting. SLBs represent an opportunity to add rigor to sustainable finance and better price externalities, where material topics have an explicit impact on cost of funding and credit ratings.

This paper focuses on environmental policies for mitigating the impacts of climate change on the Taj Mahal, an iconic structure built on the banks of the Yamuna River from 1632 to 1653 with a blend of Persian and Indian architectural styles. The Taj Mahal is threatened by damage caused by climate change, including air pollution resulting in acid rain and floods that lead to erosion and discoloration of the main marble material of the Taj Mahal. This study employs a Systematic Literature Review (SLR) of peer-reviewed journal articles with a primary focus on environmental policy, the impacts of climate change, and the preventive measures undertaken by the Indian government. Based on the analysis of 270 papers, it is concluded that out of the total, 30 papers specifically address objectives relevant to this research. The study period spans from 2014 to 2024. The research findings reveal that air pollution has a significantly adverse impact on the Taj Mahal. Furthermore, nine policies are generally identified from the journal literature review aimed at preserving and protecting the Taj Mahal from the negative effects caused by air pollution.

We investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances of Larix gmelinii (Dahurian larch). Seedlings of 11 L. gmelinii provenances were transplanted into two common gardens with different climate conditions (control and warming climate). We measured the leaf photosynthetic capacity and explored its influencing factors. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). The Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the correlations between Pmax-a and Vcmax, Jmax, and TPU was steeper in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. The effects of warming on Pmax-a, Vcmax, Jmax, and TPU increased and then decreased as the aridity index of the original site increased. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming.

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

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

Polar stratospheric clouds (PSCs) form in polar regions typically between 15 and 25 km, when the local temperature is sufficiently low. PSCs play an important role in the ozone chemistry and the dehydration and denitrification of the stratosphere. Lidars with a depolarization channel may be used to detect and classify different classes of PSCs. The main PSC classes are water ice, nitric acid trihydrate (NAT) and supercooled ternary solutions (STS), the latter being liquid droplets consisting of water, nitric acid and sulphuric acid. PSCs have been observed at the lidar observatory at Concordia Station from 2014 on. The harsh environmental conditions at Concordia during winter render successful lidar operation difficult. In order to facilitate the operation of the observatory several measures have been put in place to achieve an almost complete remote control of the system. PSC occurrence is strongly correlated with local temperatures and is affected by dynamics, as the PSC coverage during the observation season shows.

The increasing demand for transporting people and goods, rail system is needed for enhancement. An architectural design of train station can significantly impact investment from any government. However, a proper guideline for designing the train station in tropical climate is not publicized. This review examine railway station design through an analysis of student design theses in Thailand, from 1983 to 2022. Furthermore, the building analyses on architectural design theory were done in terms of service area, form, entrance structure, roof structure, style, and design development. The analysis reveals curved and gable roofs are most frequent, followed by 3D curved roofs. HSR stations' main entrances are designed to represent local culture and save walking distance. Curved and gabled porticos provide the most extravagant main entryway, a feeling of grandeur and beauty. A public building's overlapping portico or curving gabled portico lends majesty and refinement to its façade. Architects and designers strive to make buildings more attractive and practical. Besides, university-designed stations prioritize conceptual design and functional space over cost. Finally, railway station design should prioritize transparency, connectivity, movement, and cost- and time-efficiency. Research gaps are identified, such as designing user-friendly for thermal comfort and design-for-all the railway station in tropical climate, are critical for future evaluation.

The Earth's fresh water resources predominantly is groundwater that is pumped out due to rapid urbanization and aggravated by climate change. Groundwater modeling is a crucial tool for understanding aquifer systems, employing 1D, 2D, and 3D numerical models with distinct applications. One-dimensional models focus on vertical dynamics, examining aquifer properties and simulating vertical contaminant transport. Two-dimensional models extend to regional scales, considering horizontal variations and assessing groundwater-surface water interactions, making them valuable for watershed-scale studies. Three-dimensional models provide a comprehensive representation of hydrogeological systems, capturing intricate flow patterns and aiding site-specific assessments. Comparative analysis reveals model strengths and limitations, emphasizing the importance of calibration for reliable results. Case studies showcase practical applications, such as 1D models in flooding analysis and 2D models for simulating debris flows. Three-dimensional modeling proves essential for understanding complex river-aquifer exchange fluxes. Future directions call for a global groundwater platform to address data variability and technical challenges. Despite substantial investments required, the anticipated returns in scientific advancements, societal benefits, and economic gains are expected to outweigh the initial costs. This review aims in highlighting the significance of advancing all three-dimension groundwater modeling for sustainable water resource management and environmental protection.

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.

In 2021, the American Association of Colleges of Nursing (AACN) added “the impact of climate change on environmental and population health” into The Essentials: Core Competencies for Professional Nursing Education. Presently, little guidance exists for nursing faculty new to climate education. The year prior, the Nurses Climate Challenge (NCC) - a campaign to educate 50,000 health professionals about health impacts of climate change - launched the School of Nursing Commitment through a series of focus groups and collaborative content development. With an aim of increasing access to knowledge and tools to support education about the health impacts of climate change, the NCC Commitment partners with nursing schools and provides a community of practice. Partner schools use NCC resources in courses and report the number of students educated. Within three years, 61 nursing schools in 30 states joined the Commitment. Participants included academic health centers, research institutions, multi-state schools, and small private colleges, and programs ranged from AD to PhD. Faculty 1) integrated resources into didactic and clinical settings such as population or organ-system content, leadership, and policy and 2) used resources to support assignments. In four years, faculty reported educating over 37,700 students using NCC resources in 439 educational sessions. The Commitment may be valuable for faculty fulfilling AACN Essentials by bringing climate change to the classroom, community, and bedside. Furthermore, the Commitment may be a replicable model for health professional education and inspiring action on climate change.

Due to the major impact of climate change on the world's environment, political and economic systems, climate change mitigation has become a pressing priority for the international community and requires rapid action from the whole society. With the continuous advancement of artificial intelligence research, the integration of AI and other technologies makes it more and more used in the whole society. It has become a promising and innovative avenue in the field of climate change mitigation. This paper comprehensively considers the key role of AI technology in the field of climate change mitigation, such as climate modeling, the optimization of renewable energy systems, the development of intelligent solutions for sustainable practices and CSS technology, and affirms its future prospects. It also describes the challenges of AI in the field of climate change mitigation. As researchers, policymakers, and industries collaborate to refine AI methodologies and integrate them into practical applications, a concerted effort is required to establish ethical guidelines, transparency standards, and inclusive governance frameworks.

In this study, we employ the GARCH-MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the predictability of commodity return volatility in relation to US climate policy uncertainty (CPU). Our analysis utilizes the 20-day annualized realized commodity volatility returns of nine global commodities (Aluminium, Cocoa, Coffee, Copper, Cotton, Rice, Soybean, Sugar, and Wheat) to construct the GARCH-MIDAS model, with Climate Policy Uncertainty (CPU) serving as the predictive variable. The outcomes of our investigation reveal a consistently positive and statistically significant relationship between CPU and the selected commodities. This implies that CPU effectively serves as a robust predictor of volatility in commodity returns. The implications drawn from our results suggest that climate change policies play a pivotal role in influencing economic activities within the commodity market. This underscores the substantial impact of climate change considerations on investment decisions and further emphasizes the integral role of climate change in shaping economic choices.

This paper aims to explore how climate change affects electricity generation (fossil-fueled power plants, hydroelectric stations, wind systems and photovoltaics) and energy demand in residential buildings in Greece for the period up to 2050. In both cases RCP scenarios results are considered in the appropriate spatial and temporal dimension. Energy supply technologies were examined through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. With respect to energy demand, bottom-up models were developed that integrate behavioral and policy aspects. The analysis showed that climate change is expected to mainly affect electricity generation from hydro and thermal power plants, while the impacts on solar and wind energy are significantly lower. The range of impacts on hydro potential and electricity generation depends on the geographical location of the power plants and shows significant uncertainty due to the corresponding uncertainty in climate models estimates regarding precipitation and runoff changes while showing significant geographical variations. With respect to energy demand, climate change is expected to affect energy consumption, but the expected range of effects depends on both the implementation and the characteristics (deep vs. shallow renovation) of measures for upgrading the thermal performance of the building stock and the intensity of climate change.

The predominant management approach for municipal solid waste (MSW) remains disposal, given significant increases in generation and disposal rates of MSW in recent decades. In addition to the well-documented carbon emissions from disposal sites, these sites accumulate numerous elements, the masses of which are substantial globally yet inadequately quantified. The unique combinations of waste constituents, elements, diverse environments, and confined spaces in disposal sites create distinct biogeochemical conditions, setting them apart from any other infrastructure or geological feature on Earth. This review first presents a global summary of the cumulative masses and disposal rates of MSW constituents and associated elements. The five dominant transformation and transport processes influencing disposed elements are examined: biochemical degradation, physicochemical transformation, gas migration, leachate migration, and solid spillage. The magnitudes and rates of the processes corresponding to major disposed elements, including carbon, nitrogen, sulfur, chlorine, and several metals, are systematically summarized. We examine and quantify the potential environmental impacts and health risks associated with element transformation and transport. We also explore the existing knowledge and techniques for resource recovery and site remediation of disposal sites. The distilled compilation of measurements and insights herein serves as a valuable primer for researchers, practitioners, and decision-makers involved in MSW management.

The study combines two critical aspects of climate research in Nigeria. The first segment focuses on improving predictive performance of global circulation models (GCMs) employing ensemble techniques. ANN ensemble displayed significant improvement in the accuracy of climate projections, particularly in high-altitude geographic areas where traditional models exhibit limitations. Performance evaluation metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Nash–Sutcliffe Efficiency (NSE) demonstrate the effectiveness of the ANN multimodal ensemble. Building on the improved climate modelling, the second segment delves into a spatial and temporal analysis of rainfall and mean temperature patterns under climate change in Nigeria. By considering two Representative Concentration Pathways (RCPs), namely RCP4.5 and RCP8.5, the study utilizes dynamically downscaled GCMs obtained from the Coupled Model Intercomparison Project phase 5 (CMIP5). The Mann-Kendall test reveals significant spatiotemporal variations in climate trends across the country. The warming trend is particularly pronounced in the northern regions, with RCP8.5 showing more severe impacts compared to RCP4.5. This integrated approach not only highlights the importance of multimodal ensembles in climate modelling but also provides valuable insights into the spatial and temporal patterns of climate change to inform effective adaptation and mitigation strategies for Nigeria.

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.

Dengue is one of the most important arboviruses worldwide, with currently approximately 2.5 billion people at risk of becoming infected, mainly in tropical countries. The present study evaluated the influence of climatic variables on the incidence of dengue fever in an endemic urban area. A time series study of cases was carried out with all confirmed cases of dengue fever in the municipality of Belo Horizonte from 2001 to 2021. The climatic explanatory variables were obtained from the National Institute of Meteorology. The analysis was performed using a generalized linear regression model with three scenarios: a no-lag model, 1-month lag model (1 month earlier) and 2-month lag model (2 months earlier). In the no-lag model, the maximum temperature was associated with an increase in the monthly incidence of dengue (IRR: 1.5). In the 1- and 2-month lag models, the monthly average temperature was associated with an increase in incidence (IRR: 1.9 in both). Our results suggest that temperature contributed to the increase in the incidence of dengue, and an increase of 1 °C could increase the incidence of the disease by approximately 90%. Thus, temperature monitoring can direct efforts towards prevention and control of the disease.

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.

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.

In this analysis, we assess the performance of GSMaP-GNRT6 data in capturing precipitation climatology and climate variability across China from 2001 to 2020. The evaluation involves comparing four precipitation indices of accumulated precipitation, the number of rainy days, rainstorm days, and precipitation maximum with the daily precipitation data from 2419 stations in China. The findings reveal that the GSMaP data effectively captures the overall spatial distribution of annual, summer, and monthly precipitation. However, it exhibits minor limitations in accurately depicting the spatial distribution of the number of rainy days from July to September and the precipitation maximum during wintertime in eastern China. While the GSMaP data depicts a coherent annual cycle consistent with the station observations, a general underestimation is observed. Notably, the GSMaP data presents a much smoother annual cycle in precipitation maximum. Regarding accumulated precipitation, the number of rainstorm days, and precipitation maximum, the GSMaP data shows an almost consistent interannual variation and increasing trends, aligning with station observations. However, it is noteworthy that the magnitude of the increasing trend based on the GSMaP data is greater, especially entering the early 21st century. Conversely, a significant discrepancy in the annual variation and an almost opposite changing trend are noticed in the number of rainy days between the GSMaP data and station observations.

Climate change not only affects weather conditions, patterns, and the frequency and severity of extreme weather events but also changes how governments spend money. Agriculture is an important sector of the European Union (EU), and it is projected to decrease by 16% by 2050, therefore a third of the EU budget has been spent on agricultural funding, adaptation, and climate action. The effect of climate change on agriculture is mixed and dependent on the country and its location. The southern EU is adversely affected while the northern EU is positively affected by the changes in weather patterns. The main goal of this paper is to gain insight regarding the effect that climate change has on public spending in relation to the agricultural sector of the EU, by using the pooled OLS and GMM methods. The study concluded that agriculture has a significant impact on public spending in the southern countries of the EU, where it represents a significant portion of the GDP. Inflation influences public spending in the whole EU region, the northern and southern countries of the EU. Rain has a moderately significant impact on public spending in the whole EU region. It is advised that governments maintain a controllable level of inflation using fiscal and monetary policy that will implicitly control public spending.

With the rapid development of artificial intelligence, machine learning is gradually becoming popular in predictions in all walks of life. In meteorology, It is gradually competing with traditional climate predictions dominated by physical models. This survey aims to consolidate the current understanding of Machine Learning (ML) applications in weather and climate prediction—a field of growing importance across multiple sectors including agriculture and disaster management. Building upon an exhaustive review of more than 20 methods highlighted in existing literature, this survey pinpointed eight techniques that show particular promise for improving the accuracy of both short-term weather and medium-to-long-term climate forecasts. According to the survey, while ML demonstrates significant capabilities in short-term weather prediction, its application in medium-to-long-term climate forecasting remains limited, constrained by factors such as intricate climate variables and data limitations. Current literature tends to focus narrowly on either short-term weather or medium-to-long-term climate forecasting, often neglecting the relationship between the two, as well as general neglect of modelling structure and recent advances. By providing an integrated analysis of models spanning different time scales, this survey aims to bridge these gaps, thereby serving as a meaningful guide for future interdisciplinary research in this rapidly evolving field.

Tropical forest and savanna biomes are pivotal in the functioning of the Earth system. Tropical forests are one of the largest terrestrial biosphere carbon pools, whereas savannas exchange carbon between the biosphere and atmosphere via frequent and extensive landscape fires. Both are biodiverse and under increasing threat due to land clearing and anthropogenic climate change. Reliable mapping of tropical forest and savanna is essential to provide understanding of how anthropogenic impacts are affecting the extent of these biomes. Using Google Maps satellite imagery, we manually classified 24,239 random points as forest, savanna, or anthropogenic landscapes within the tropics. Because fire and climate are correlated, we developed separate geospatial models to rank the importance of climate, topography, and human influence on vegetation present. This modelling confirmed that those areas with more fires had lower probabilities of tropical forest, that forest was most likely in areas with high mean annual rainfall with little seasonal variation in precipitation, and that anthropogenic factors disrupt this environmental predictability. We found there were environments where tropical forest and savanna were equally probable are geographically restricted. These relationships suggest that future drier climates projected under anthropogenic climate change, combined with clearing and burning that have reduced tropical forest extent to a subset of its theoretical distribution, will lead to irreversible loss of tropical forests. Our modelling provides global mapping that can be used track further changes to distribution of rainforests.

In the era of persistent globalization, climate governance has emerged as a prominent concern within both the theoretical community and government departments of diverse nations. Of particular interest in academic research is the adverse effect of climate shocks on the global economy. This paper employs average temperature as a surrogate indicator for climate shocks and examines the influence of temperature fluctuations on inflation levels using a balanced panel dataset from 1995 to 2021. The findings indicate a positive association between temperature change and inflation within the country, which remains consistent even after subjecting the analysis to multiple robustness tests. Furthermore, accounting for heterogeneity reveals variations in the magnitude of response of inflation levels to temperature fluctuations. Regarding the analysis of underlying mechanisms, the study underscores the significance of energy demand as a pivotal pathway influencing inflationary pressures at the national level. Lastly, by incorporating GDP per capita as a threshold, the research reveals a nonlinear relationship between temperature change and inflation levels.

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.

The gradual decline of the Aral Sea’s water level over the past five decades poses a huge environmental problem in the heart of Central Asia. Uzbekistan, once blessed with abundant water resources, now struggles with water scarcity in certain regions. While global environmental issues contribute to some degree to this dilemma, irrigation mismanagement plays a central role. This study focuses on the widespread problem of irrigation mismanagement in Uzbekistan and specifically addresses the rural district of Oltinsoy in the southern province of Surkhandarya. The main objective of this research project is to propose effective measures that can alleviate the pressing problem of water scarcity in the region while emphasizing the urgent need for well-executed projects and careful maintenance to ensure long-term sustainability at the local level. It is important to note that this study does not include an examination of the impact of global warming on the decline of water resources in Uzbekistan.

Evapotranspiration (ET) is an essential part of energy flow between the surface of the earth and the atmosphere, simultaneously involving the water, carbon, and energy cycles. It is mainly determined by climate change, land use, and land cover changes. Climate change is expected to intensify the hydrological cycle and alter ET. Land use affects ET within regional ecosystems mainly through vegetation changes and agricultural activities such as farmland reclamation, crop cultivation, and agricultural management. However, there is still a need for quantitative characterization of the impacts of climate change and human activities on ET and regional water resource efficiency in arid and semiarid regions. Based on Landsat-8 remote sensing imagery and land use data, the planting structure in the Liangzhou District of the middle reaches of the Shiyang River Basin was identified using a multiband and multitemporal approach in this study. Subsequently, the ET of major cash crops was inverted using the three-temperature model. This research quantitatively describes the responses of wheat and corn to the climate and human activities over a two-year period. Furthermore, the impact of planting structure and climatic factors on ET was elucidated. The results indicate that a combination of multitemporal green and shortwave infrared 1 bands is the optimal spectral combination to extract the planting structure. Compared to 2019, the wheat area decreased by 23.27% in 2020, while the corn area increased by 5.96%. Both crops exhibited significant spatial heterogeneity in ET during the growing season. The typical daily range of ET for wheat was 0.4–7.2 mm/day, and for corn, it was 1.5–4.0 mm/day. Among the climatic factors, temperature showed the highest correlation with ET (R = 0.80, p ≤ 0.05). Our research findings provide valuable insights for the fine identification of planting structures and a better understanding of the response of ET to climatic factors and human activities.

Climate data are important in building a hydrological risk assessment model. The ClimInonda web application enables interactive and dynamic visualizations of different data collected from different weather stations in the study area on a single platform, allowing users to explore and analyze data in an easy way. This can assist decision-makers and stakeholders in understanding the current state of the environment and in identifying areas of flooding risk. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models by providing easy-to-understand visualizations. The different stations of the Gafsa and Kasserine governorates in the study area are included and other stations of the Algerian territory (Tebessa governorate) are incorporated. This web application also provides the capability to include each user's stations.

The migratory life history of anadromous salmonids requires successful migration between nursery, feeding and spawning habitats. Smoltification is the major transformation anadromous salmonids undergo before migration to feeding areas and prepares juvenile fish for downstream migration and entry to seawater. We reviewed the effects of climate change on smolt ecology from growth of juveniles in freshwater to early post-smolts in sea. Shift in the suitable thermal conditions by climate change is causing Atlantic salmon to expand their range northwards, while in the southern edge of their distribution populations struggle with high temperatures and occasional droughts. Climatic conditions, particularly warmer temperatures, are affecting growth during freshwater phase in the river. Better growth in the northern latitudes leads to earlier smoltification. Thermal refuges, the areas of cooler water in the river, are especially important for salmonids impacted by climate change. Restoring and maintaining connectivity and suitable diverse mosaic habitat in rivers are important for survival and growth throughout the range. The start of the smolt migration has shifted earlier as a response to increasing water temperatures, which has led to concerns of mismatch with optimal conditions for post-smolts in the sea decreasing their survival. A wide smolt window allowing all migrating phenotypes from early to late migrant’s safe access to sea is important in changing environmental conditions. This is true also for regulated rivers, where flow regulation practices cause selection pressures on migrating salmonid phenotypes. Life history in freshwater affects also marine survival, and there is a need for better collaboration across life stages and habitats among researchers and managers to boost the smolt production in rivers.

The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. To overcome this, simpler modules such as modal aerosol modules with three lognormal modes (MAM3) can be used. In this study, the coupling of the Carbon Bond Mechanism, version Z (CBMZ), and MAM3 chemistry modules in WRF-CAM5 was improved by adding biomass-burning emissions to both gas- and particle-phase chemistry and incorporating a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs). The study conducted six simulations over the western U.S. and northeastern Pacific region and compared the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The results showed that the model with enhanced chemistry capabilities had a 31% and 58% reduction in root-mean-square errors (RMSE) for black carbon (BC) and organic carbon (OC) surface concentrations, respectively. The earlier release of the WRF-CAM5 version had two deficiencies that were addressed in this study. This research highlights the importance of accurate aerosol representation in climate-chemistry models for improving accuracy and reducing errors in simulations.

The agricultural sector provides employment and income to the majority of Myanmar's population. The sector, however, is extremely susceptible to severe weather, rising temperatures, and changes in precipitation. This paper aims to analyze how vulnerable Myanmar's agricultural sector is to climate change and highlights the key sectors that are most at risk. This report also examines historical climate information, and the anticipated effects of climate change on Myanmar's agricultural sectors. In-depth literature reviews and summaries of Myanmar's climate change adaptation efforts are included in the report, along with recom-mendations for targeted, locally appropriate actions to strengthen the country's agricultural sector's resilience. Additionally, the study reviews Myanmar's in-stitutional framework for climate action and government priorities for adaptation measures, emphasizes the urgent need for climate action in Myanmar's agricul-ture sectors and calls for more research and development efforts on the effects of climate change on rural livelihoods and agriculture.

We investigated rainfall patterns in India over during the 60-year period from 1951 to 2010 and predicted changes for the next century (2051-2100) with an assumed 4K warming from large ensemble experiments (190 members). We focused on rainfall patterns during two periods of present-day climate (1951-1980 and 1981-2010) and their projected changes for the near and far future (2051-2080 and 2081-2110). Our analysis revealed that the northeastern region of India and some southern regions received higher rainfall during the period of 1951-2010. This finding is consistent with daily observations from the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE). In a warming climate, rainfall events in India are predicted to carry more precipitation, with the northeast and southern regions experiencing stronger rainfall events. The frequency and intensity of these events (with more than 20mm of rainfall per day, on average) are also expected to increase. Overall, our study suggests that water-related disasters such as flooding and landslides could be much worse in India in the future due to climate warming.

Dengue Fever (DF) is an important arthropod-borne viral infection, which has repeatedly oc-curred as outbreaks in eastern and northeastern Ethiopia since 2013. A cross-sectional epidemio-logical outbreak investigation was carried out from September - November 2019 on febrile pa-tients (confirmed malaria negative) who presented with suspected and confirmed DF at both public and private health facilities in Gewane District, Afar Region, northeastern Ethiopia. Ento-mological investigation of containers found in randomly selected houses belonging to DF positive patients was undertaken, to survey for the presence of Aedes larvae or pupae. A total of 1185 DF cases was recorded from six heath facilities during the 3-month study period. The mean age of DF cases was 27.2 years and 42.7% of the cases were female. The most affected age group was 15-49 years (78.98%). However, the attack rate (AR) was highest in the 49+ age group (134.2). A total of 162 artificial containers were inspected from 62 houses, with 49.4% found positive for Aedes larva/pupae. Aedes mosquitoes were mostly found breeding in buckets/bowls, clay jars, plastic tanks, and tires. World Health Organization entomological indices classified the study site as high risk for dengue outbreaks (House Index=45.2%, Container Index=49.4% and Breteau In-dex=129). Study findings highlight the importance of vector control to prevent future dengue out-breaks in the region. The scarcity of drinking water and changing climactic conditions may have also contributed to the occurrence of this outbreak.

Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a "stress test" for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in burned area, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47-58% of historic values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

The objective was to estimate the monetary loss of potato producers up to the year 2100 as a result of temperature and precipitation impacts, taking into account the A2 and B2 scenarios of the IPCC (Intergovernmental Panel on Climate Change). The Pooled Production Panel Model was used, whose database was prepared taking into account climatic variables (temperature and precipitation) and agricultural variables (production, harvested area, farm-gate price) for the period 1996 - 2020, which form the independent variables of the study. The estimations used 60 observations and a total of 38 estimations were run in the econometric software EViews8, of which Equation 05 of the Production Pooled Panel Model was chosen as the best. The model obtained used temperature and precipitation forecasts from Brazil's INPE (National Institute for Space Research), validated for the study area. The results indicate a concave function between potato production (t/ha), temperature and precipitation. Finally, based on the A2 climate scenario, which is the most pessimistic and using the period 2021 - 2100, a loss for potato producers of approximately 8'927,521.48 million soles was estimated.

As its capital, Jakarta plays a critical role in boosting Indonesia’s economic growth and setting the precedent for broader change outside of the city. One crucial avenue of inquiry to better understand, and prepare for, the future of a country so heavily impacted by disastrous weather events is understanding the effects of climate change through data. This study investigates meteorological data collected from 1996 to 2021 and compares the application of the SARIMA and the Holt-Winters methods to predict the future influence of climatic parameters on Jakarta’s weather. The performance of the SARIMA method is proven to provide better results than the Holt-Winter models and both methods showed the best performances when forecasting the humidity data. The results of the forecast are able to demonstrate the characteristic of the climate in Jakarta, with dry season ranging from May to October and wet season ranging from November to April.

Each year, the global population and agriculture suffer critical agricultural output losses as a result of severe drought devastation. Physiological drought occurs when plants are unable to extract water from the soil, even though it is available in the root zone. Apart from having a significant effect on plant physiology, drought stress has the effect of reducing crop yield. Drought stress influences plant metabolism both directly and indirectly. Drought stress alters the morpho-anatomical, physiological, and biochemical composition of plants, thereby decreasing transpiration water loss and increasing the efficiency with which plants use their water. Constant water loss through transpiration, combined with previously lost water, results in leaf water deficits. Nonetheless, drought stress has a wide variety of effects, ranging from lesions to confusion. Plant health is harmed when their ability to absorb water and nutrients, interact with their environment, and breathe is harmed. Apart from oxidative damage to plants, it may also result in cell death, which can occur under certain conditions when cells are exposed to their environment. Drought induces a plethora of physiological and molecular changes in plants, the majority of which assist them in adapting to the harsh environment. To mitigate drought's adverse effects, we must first gain a better understanding of how drought affects plant physiology. The purpose of this research is to better understand how drought affects plant development by examining the causes and effects of drought stress.

Climate change is a major threat to agricultural food production globally and locally. It poses both direct and indirect effects on soil functions. Thus, agricultural management practices has evolved to adaptation strategies in order to mitigate the risks and threats from climate change. The study concludes with a recommendation the coconut farmers should explore the idea of soil biodiversity in a bid to mitigate the potential negative impact of climate related risk on the farming. The study proffers the need for adopting sustainable agricultural practices to boost local coconut production. This can contribute to the simultaneous realisation of two of the Sustainable Development Goals (SDGs) of the United Nations: SDG 2 on food security and sustainable agriculture and SDG 13 on action to combat climate change and its impacts. The study findings has implications for tackling climate change in Sub-Saharan Africa and in particular Nigeria in order to boost local agricultural production and coconut in particular without negative environmental consequences and an ability to cope with climate change related risks.

The assessment of aridity conditions is a key factor for water management and the implementation of mitigation and adaptation policies in agroforestry systems. Towards this aim three aridity indices were computed for the Iberian Peninsula (IP): the De Martonne Index (DMI), the Pinna Combinative Index (PCI), and the Erinç Aridity Index (EAI). These three indices were first computed for the baseline period 1961‒1990, using a gridded observational data (E-OBS), and, subsequently, for the periods 2011‒2040 (short-range) and 2041‒2070 (medium-range) using an ensemble of six Regional Climate Models (RCMs) experiments generated by the EURO-CORDEX project. Two Representative Concentration Pathways (RCPs) were analyzed, an intermediate anthropogenic radiative forcing scenario (RCP4.5) and a fossil-intensive emission scenario (RCP8.5). Overall, the three indices disclose a strengthening of aridity and dry conditions in central and southern Iberia until 2070, mainly under RCP8.5. Strong(weak) statistically significant correlations were found between these indices and the total mean precipitation (mean temperature) along with projected significant decreasing(increasing) trends for precipitation(temperature). The prevalence of years with arid conditions (above 70% for 2041‒2070 under both RCPs) are projected to have major impacts in some regions, such as southern Portugal, Extremadura, Castilla-La Mancha, Comunidad de Madrid, Andalucía, Región de Murcia, Comunidad Valenciana, and certain regions within the Aragón province. The projected increase in both the intensity and persistence of aridity conditions in a broader southern half of Iberia will exacerbate the exposure and vulnerability of this region to climate change, while the risk of multi-level desertification should be thoroughly integrated into regional and national water management and planning.

The main purpose of this research is to analyze the perception of climate change impacts on human health in Bangladesh through data from nationality representative surveys conducted in some district of Bangladesh. In Bangladesh there have a few research has been conducted on public perceptions about the impact of climate change on human health. A structured questionnaire method was conducted, and data collected from 615 respondents. The findings of this study reveal that out of 615 respondents, 76.0% of the respondents replied positively while remaining 24.0%, almost one-fourth of total respondents, indicated that they have not heard the term climate change before. Knowledgeable in climate change, 92.5% of respondents agreed that climate change has an impact on human health while only 7.5% respondents disagreed with this statement. 90.5% of respondents argued that they are agreed with the opinion that climate change is a serious threat to human health.

Abstract Depending upon altitudinal gradient in the Himalayas, the rate of climate change varies from lowland to upland. The Chitwan Annapurna Landscape (CHAL) is the central part of the Himalayas and covers all bioclimatic zones. Analysis of time series data (1970-2019) of temperature and precipitation was carried out in seven bioclimatic zones extending from lowland Terai to higher Himalayas. The non-parametric Mann-Kendall test was applied to determine the trend, which was quantified by Sen’s slope. Annual and decade interval average temperature, precipitation trends, and lapse rate were analyzed in each bioclimatic zone. Out of seven bioclimatic zones, four zones showed a decreasing precipitation trend (lower tropical, upper tropical, upper subtropical, and alpine bioclimatic zones)at the rate of 1.8, 1.98, 2.06, and 1.80 mm/year, and in lower sub-tropical, temperate, and lower subalpine bioclimatic zones, increasing at the rate of 0.45, 1.81 and 1.28mm/year, respectively. Precipitation did not show any particular trend at decade intervals. The average annual temperature at different bioclimatic zones clearly indicates that temperature at higher elevations is significantly increasing more than at lower elevations. In lower tropical bioclimatic zone (LTBZ), upper tropical bioclimatic zone(UTBZ), lower subtropical bioclimatic zone (LSBZ), upper subtropical bioclimatic zone(USBZ), and temperate bioclimatic zone(TBZ), the average temperature increased by 0.022, 0.030, 0.036, 0.042 and 0.051oC/year, respectively. The decade level temperature scenario revealed that the hottest decade was from 1999-2009. The average temperature was found as 24.1, 21.8, 19.7, 17.5, and 13.3oC in LTBZ, UTBZ, LSBZ, USBZ, and TBZ, respectively, and the average annual precipitation in LTBZ, UTBZ, LSBZ, USBZ, TBZ, LBZ, and ABZ was 2002.1, 2613.1, 2223.9, 3146.9, 1447.2, 952.1, and 361.7mm/year, respectively, in CHAL. With the impact of climate change site and region-specific, this information highlights the need to mitigate climate change in different bioclimatic zones.

There is growing awareness that “Nature-based Solutions” (NbS) can help to protect us from climate change impacts whilst slowing further warming, supporting biodiversity and securing ecosystem services. However, the potential of NbS to provide the intended benefits has not been rigorously assessed. There are concerns over their reliability and cost-effectiveness compared to engineered alternatives, and their resilience to climate change. Trade-offs can arise if climate mitigation policy encourages NbS with low biodiversity value, such as afforestation with non-native monocultures. This can result in maladaptation, especially in a rapidly changing world where biodiversity-based resilience and multifunctional landscapes are key. Here we highlight the rise of NbS in climate policy—focussing on their potential for climate change adaptation as well as mitigation—and discuss barriers to their evidence-based implementation. We outline the major financial and governance challenges to implementing NbS at scale, highlighting avenues for further research. As climate policy turns increasingly towards greenhouse gas removal approaches such as afforestation, we stress the urgent need for natural and social scientists to engage with policymakers. They must ensure that NbS can achieve their potential to tackle both the climate and biodiversity crisis while also contributing to sustainable development. This will require systemic change in the way we conduct research and run our institutions.

Caribbean SIDS are among the most vulnerable to climate change which will have a disproportionate impact on local environments and economies. Whilst there is a growing literature on how Caribbean SIDS can adapt to become more resilient a question that has received little attention is with regard to migration as an unplanned response. It is recognised that events such as hurricanes and flooding can lead to internal relocation in the short term but societal responses to droughts through migration have not generally been investigated. This paper seeks to address this by considering the case of the island of Carriacou, part of the state of Grenada. Carriacou with its small population, limited land area and local economy, historically based on agriculture has had a high degree of migration. This is in part a response to limited economic opportunities. Environmental stress manifest through limited water availability, inappropriate land management and social conditions is likely to be exacerbated by climate change and variability. Resultant increases in the frequency and intensity of droughts, in the absence of proactive interventions, are likely to result in non-linear migration, both to Grenada itself and beyond.

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

This paper performs non-parametric Mann Kendall (MK) trend analysis of historical hydroclimatic data (1961-2016), an ensemble climate model validation and a computation of 16 Expert Team on Climate Change Detection and Indices (ETCCDI) temperature and rainfall extremes indices. The climate indices are evaluated using MK test and annual trend analysis for two Representative Concentration Pathways (RCP4.5 & RCP8.5) future scenarios from 2020 to 2045 over Mono River Basin (MRB) in Togo. The annual and seasonal trend analyses are assessed on historical potential evapotranspiration, mean temperature, rainfall and discharge data. Results show positive and negative trends of hydroclimatic data over MRB from1961 to 2016. Mean temperatures increase significantly in most of the stations while a negative non-significant trend is noticed for rainfall. Meanwhile, the discharge presents a significant seasonal and annual trend for three gauge stations (Corrokope, Nangbéto and Athiémé). Validation of the ensemble climate models reveals that the model under-estimates observations at Sokode, Atkakpamé and Tabligbo stations, however linear regression and spatial correlation coefficients are higher than 0.6. Moreover, the percentage of bias between climate model and observations are less than 15% at most of the stations. Finally, the computation of extreme climatic indices under RCP4.5 and RCP8.5 scenarios shows a significant annual trend of some extreme climatic indices of rainfall and temperature at selected stations between 2020 and 2045 in the MRB. Therefore, relevant governmental politics are needed to elaborate strategies and measures to cope with projected climate changes impacts in the country.

Humans may be exposed to microbial pathogens at recreational beaches via environmental sources, such as water, sand, and aerosols. Although infectious disease risk from exposure to waterborne pathogens has been an active area of research for decades, sand is a relatively unexplored reservoir of pathogens and fecal indicator bacteria (FIB). Beach sand and water habitats provide unique advantages and challenges to pathogen introduction, growth, and persistence, as well as continuous exchange between habitats. Models of FIB and pathogen fate and transport in sandy beach habitats can help predict the risk of infectious disease from recreational water use, but filling knowledge gaps such as decay rates and potential for microbial growth in beach habitats is necessary for accurate modeling. Climatic variability, whether natural or anthropogenically-induced, adds complexity to predictive modeling, but may increase human exposure to waterborne pathogens via extreme weather events, warming of water bodies and sea level rise in many regions. The popularity of human recreational beach activities, combined with predicted climate change scenarios, could amplify the risk of human exposure to pathogens and related illnesses. Other global change trends such as increased population growth and urbanization are expected to exacerbate contamination events and the predicted impacts of increasing levels of waterborne pathogens on human health. Such changes will alter microbial population dynamics in beach habitats, and will consequently affect the assumptions and relationships used in population models and quantitative microbial risk assessment (QMRA). Here, we discuss the literature on microbial population and transport dynamics in sand-water continuum habitats at beaches, how these dynamics can be modeled, and how climate change and other anthropogenic influences (e.g., land use, urbanization) should be considered when using and developing more holistic, beachshed-based models.