Stagnating low renovation rates, vacancies and underused town centers, unprecedentedly high levels of land sealing and excessive consumption of resources through the construction of new buildings and infrastructure as well as the effects of climate change were some of the reasons for carrying out the monumentum ad usum research project.Thermodynamic simulations were used to carry out in-depth analyses of specific building parameters such as energy balances and how they are influenced by the effects of climate change. Life cycle analyses under ecological and economic aspects examined the aspects of sustainability and the individual behaviour of predominantly listed existing buildings under standardized conditions.The project results show that sustainable refurbishment can significantly increase the attractiveness of using historic and listed buildings for non-profit building owners. The results and conclusions of the project are as varied as the recommendations derived from them. In practice, old buildings consume significantly less energy than predicted in the structural calculations. Correction factors are to be developed and thermodynamic simulation calculations are to be used instead of energy performance certificates for more realistic forecasts of energy requirements and emission savings potential. The aspects of sustainability in refurbishment are essential for the protection of our architectural heritage.

Abstract: Agroforestry has a sustainable attributes with both tangible and nontangible benefits. In this study carbon mitigation and credits potential of traditional agroforestry systems at different elevations were evaluated. These traditional systems are: Agrihortisilviculture system (AHS), Agrihorticulture system (AH) and Agrisilviculture system (AS). Stand density, living biomass carbon and soil carbon were measured in each sample plot. The results were that stand density of woody perennials varied from 61 to 233 tree ha-1 across t elevations and systems, and , Grewia oppositifoila was the predominant tree species occupying most of the agroforestry land use system. Plant and soil organic carbon were significantly different (P ≤ 0.05) among systems and elevations. Total carbon including plant and soil was significantly higher in the AH system at upper elevations. Total carbon emmision mitigation varied with changing elevations and systems, being highest at lower elevation with AHS system. The total carbon credits was also recorded high at lower elevation, whereas the total value of C credits was higher at mid elevation due to the estimated agroforestry area. The total value of C credits from all agroforestry systems was observed (128977.59 €) of the study area.

Land use and cover change (LUCC) is a key factor influencing global environmental and socio-economic systems. Many long-term geospatial LUCC datasets have been developed at various scales during the recent decades owing to the availability of long-term satellite data, statistical data and computational techniques. However, most existing LUCC products can not accurately reflect the spatiotemporal change patterns of LUCC at regional scale in China. Based on these geospatial LUCC products, Normalized Difference Vegetation Index (NDVI), socioeconomic data, and statistical data, we developed multiple procedures to represent both spatial and temporal changes of the major LUC types by applying machine-learning, regular decision tree and hierarchical assignment methods using the northeastern China (NEC) as a case study. In this approach, each individual LUC type was developed in sequence under different schemes and methods. The accuracy evaluation using sampling plots indicated that our approach can accurately reflect the actual spatiotemporal patterns of LUC shares in the NEC, with an overall accuracy of 0.82, Kappa coefficient of 0.77 and regression coefficient of 0.82. Further comparisons with existing LUCC datasets and statistical data also indicated our approach and dataset can more accurately and comprehensively represent the spatiotemporal patterns of all LUC types at subpixel level. Our approach unfolded the mixed pixel issue and integrated the strengths of all LUCC products through the fusion process. The analysis based on our developed dataset indicated that forest, cropland and built-up land area increased by 17.11×104 km2, 15.19×104 km2 and 2.85×104 km2, respectively during 1980-2020, while grassland, wetland, shrubland and bareland decreased by 26.06×104 km2, 4.24×104 km2, 3.97×104 km2, and 0.92×104 km2, respectively. The temporal change patterns of all these LUC types were consistent with the provincial inventory data. Our developed approach can be widely applied in the entire China and worldwide, and our data products can provide accurate data supports for studying the LUCC consequences and making effective land use policies.

Background: Atopic dermatitis is a chronic condition that significantly affects the daily life of those who suffer from it, requiring complex and personalized management with active participation of the patient in the management of their disease. Objective: to describe the design and development process of a mobile application, using the Design Thinking method, for the follow-up of patients with atopic dermatitis. Methods: User-centered design and prototype creation method, differentiating the phases of the empathize, define, idea, prototype, and test. A purposive snowball sampling was used to recruit patients with atopic dermatitis, family members, and health professionals. Three two-hour workshops were held, attended by 25 people. Results: the parameters to be monitored will include objective data (physical, behavioral, treatments, environmental, integration of daily routines) and subjective data (user experience). On the other hand, it will figure out behavior patterns, set up rewards, foster a feeling of community, and use notifications and a chatbot. Conclusion: The active integration of all stakeholders at each stage of the design and development of the digital solution has improved its relevance and acceptance, resulting in a tool that is expected to significantly improve the management of atopic dermatitis.

In addition to changes in the amount of rain, changes in land use upstream are considered a factor that directly affects the maximum runoff flow in a basin, especially in areas that have experienced floods and flash floods. This research article presents the application of the SWAT model to assess runoff in areas that have experienced flash floods, in order to analyze the proportion of land use change to the maximum runoff. Study areas that had experienced flash floods were in 3 basins in Thailand (Lam Saphung Basin, Phrom River Basin, and Chern River Basin Part 1 which is a subbasin of the Nam Chi River Basin). This study analyzed two main factors that influence runoff in the river basin: Changes in rainfall and changes in land use by considering 2 simulation situations.: (1) Changes in land use affecting runoff assessed by considering land use maps in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using rainfall data only in the year 2021 for all cases, and (2) Changes in the amount of rainfall influencing runoff by considering the rainfall record in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using the land use data only in the year 2021 for all cases. The results of the study found that the SWAT model can be effectively applied to estimate annual runoff in areas that have experienced flash floods under 8 parameters with R2 values of 0.74, 0.82 and 0.74 for the Lam Saphung River Basin and the Phrom River Basin and the Chern River Basin Part 1 respectively. In addition, it was found that the proportion of land use changes that involved changes from forest areas to residential areas was the greatest from 2008 to 2010 in the Phrom River Basin and Chern River Basin Part 1. This resulted in an increase in the maximum runoff amount of 77.78% and 46.87%, respectively. When land use was constant, it was found that the rainfall in 2010, which was the highest, also had the greatest impact on the runoff in all 3 areas.

Forest plantations have a large potential for carbon sequestration, playing an important role in the global carbon cycle. However, despite the huge amount of research carried out worldwide, the absolute contribution of industrial forest plantations is still incomplete for some parts of the world. To contribute to bridge this gap, we calculated the amount of C stock in three fast growing forest species in Chile. Relevant C pools (above-ground and below-ground biomass, forest floor, and soil) were considered for this analysis. Across the industrial plantation forests of Chile, carbon accumulated in the above-ground biomass was 181–212 Mg · ha−1 for Pinus radiata, 147–180 Mg · ha−1 for Eucalyptus nitens, and 95–117 Mg · ha−1 for Eucalyptus globulus (age 20–24 years for P.radiata and 10–14 years for Eucalyptus). Our results agree with other studies showing that 30%–50% of the total C stock is stored in the soil. Total C stocks were for 343 Mg · ha−1 for P.radiata, 352 Mg · ha−1 for E.nitens, and 254 Mg · ha−1 for E. gloubulus, also at the end of a typical rotation. The carbon pool in the forest floor was found to be significantly lower (less than 4% of the total) when compared to the other pools and showed large spatial variability. We conclude that industrial forest plantations are a valuable tool to reduce atmospheric CO2 and mitigate climate change. Given the contribution of soils to total carbon stocks, special attention should be paid to forest management activities that affect the soil organic carbon pool.

This study assessed stakeholders’ perception on the prospects and challenges of practising Climate–Smart Agroforestry in the Asunafo North Municipal Assembly in the Ahafo Region in Ghana. Interviewer administered questionnaires were used to collect cross-sectional data from 250 cocoa, food and cash crop farmers drawn from four (4) communities using simple random sampling. And nine (9) in-depth interviews were also conducted to elicit key stakeholder perspectives. Stakeholders also held the view that Climate-Smart Agroforestry encourages the use of stress-tolerant crop varieties, increase income, improve soil productivity, diversify farm produce, urges the reduction of input supply and recommends the timely usage of the inputs, ensures better market system for farm produce, cost of production decreases during the practice of Agroforestry, agro-ecological functions and Climate-Smart Agroforestry can best help adapt to the threats of climate change in the agriculture sector. The challenges included insecure tree ownership right, fast-declining soil fertility and long maturity period of Agroforestry trees, land tenure issues, illegal tree logging (chainsaw operators) on farms, lack of practical understanding of the approach, inadequate knowledge and information and inadequate supportive facilities in the study area. The study recommends further studies on the existing forest policy and legislations and its implications on the practice and adoption of Climate-Smart Agroforestry in respond to climate change in the area.

This study evaluated the impact of climate change on water resources in a large semi-arid urban watershed located in Niamey Republic of Niger, West Africa. The watershed was modeled using the fully integrated surface-subsurface HydroGeoSpheremodel at a high spatial resolution. Historical (1980-2005) and projected (2020-2050) climate scenario derived from the outputs of three Regional Climate Models (RCM) under the RCP 4.5 scenario were statistically downscaled using the multiscale quantile mapping bias correction method. Results show that the bias correction method is optimum at daily and monthly scales, and increased RCM resolution does not improve the performance of the model. The three RCMs predict increases of up to 1.6% in annual rainfall and of 1.58°C for mean annual temperatures between the historical and projected periods. The durations of the Minimum Environmental Flow (MEF) conditions, required to supply drinking and agriculture water, were found to be sensitive to changes in runoff resulting from climate change. MEF occurrences and durations are likely to be greater for (2020-2030), and then they will be reduced for (2030-2050). All three RCMs consistently project a rise in groundwater table of more than 10 meters in topographically high zones where the groundwater table is deep and an increase of 2 meters in the shallow groundwater table.

Hydro-climatic projections in West Africa are attributed with high uncertainties that are difficult to quantify. This study assesses the influence of the parameter sensitivities and uncertainties of three rainfall runoff models on simulated discharge in current and future times using meteorological data from 8 Global Climate Models. The IHACRES Catchment Moisture Deficit (IHACRES-CMD) model, the GR4J and the Sacramento model were chosen for this study. During model evaluation, 10,000 parameter sets have been generated for each model and used in a sensitivity and uncertainty analysis using the Generalized Likelihood Uncertainty Estimation (GLUE) method. Out of the three models, IHACRES-CMD recorded the highest Nash-Sutcliffe Efficiency (NSE) of 0.92 and 0.86 for the calibration (1997-2003) and the validation (2004-2010) period respectively. The Sacramento model was able to adequately predict low flow patterns on the catchment while the GR4J and IHACRES-CMD over and under estimate low flow respectively. The use of multiple hydrological models to reduce uncertainties caused by model approaches is recommended along with other methods of sustainable river basin managements.

The high-mountain and arctic plants are considered especially sensitive to the climate changes because of close adaptations to the cold environment. Kalmia procumbens, the typical arctic-alpine species reaches southernmost European localities in the Pyrenees and Carpathians. The aim of the study was the assessment and comparison of K. procumbens current potential niche areas in the Pyrenees and Carpathians and their possible reduction due to climate change, depending on the scenario. Realized niches of K. procumbens in the Pyrenees are compact while in the Carpathians dispersed. In both mountain chains, the species occurs in the alpine and subalpine vegetation belts, going down to elevations of about 1500-1600 m, while the most elevated localities in the Pyrenees are at ca 3000 m, about 500 m higher than in the Carpathians. The localities of K. procumbens in the Carpathians have a more continental climate than in the Pyrenees, with lower precipitation and temperatures but higher seasonality of temperature and of precipitation. The species covered a larger area of geographic distribution during Last Glacial, and reduced area during mid Holocene. Due to the climate warming, the strong reduction of potential area of occurrence to 2100 is expected in the Carpathians and moderate reduction in in the Pyrenees.

Fracking in the UK has yet to reach full industrial development but it is still subject to significant opposition. This study uses Beck’s Risk Society theory and anti-politics to examine the views voiced by opponents to fracking in Yorkshire, England. A qualitative approach was used; local newspaper reports were evaluated alongside semi-structured interviews with protesters to provide a thematic analysis. Although there are signs of post-materialist concerns with the environment these issues did not dominate the discussion. Scientists were not held responsible for the risks involved in fracking. Instead economic greediness of politicians and austerity measures were perceived as putting the environment and people’s health at risk. Interviewees thought fossil fuel energy production was economically advantaged over more sustainable energy and jobs in the low carbon economy. Protesters’ trust in politicians had been eroded but faith in democracy remained. It is suggested a citizen-led deliberative approach to all the concerns raised, not simply those relating to scientific risk, might achieve some level of resolution over fracking in the UK.

Sustainable development and climate change are related challenges for humanity because a good quality of life in the present and the future for human, natural, and economic systems must be achieved through the capacity to face climate change. In this context, this research aimed to identify the climate change adaptation measures contribution to the sustainable development aspects: environmental, social, and economic, applied to a case study, "The Coastal Watershed Conservation Project in the Context of Change Climate (C6)" through the Sustainable Development Goals (SDG) evaluation framework. The primary data collection was carried out directly from the project reports and the reports of 29 interventions in the communities. The results indicate that the adaptation actions implemented through the C6 project did contribute to sustainable development, to a greater extent, in the social aspect, followed by environmental aspects and later by economic ones; therefore, it can be concluded that one way to achieve sustainable development can be through the implementation of adaptation actions to face climate change.

Climate variation and change are an unavoidable phenomenon faced by the natural habitat of this planet. For getting potential yield from vegetable crops under the changing climate conditions, the practical strategies at field level can serve as a guideline for the farmers. Moreover, there are several strategies available for mitigating the harmful effects of climate change. In this manuscript, efforts have been made for reviewing the mitigating strategies against the impact of climate change in vegetable crops via conventional approaches. Considering the situation, the information reviewed revealed that significant result of conventional approaches with climate-smart adoptions strategies has a direct bearing on vegetable production for the increasing population in frenziedly changing climate scenario.

As humanity confronts the existential threats of climate change, biodiversity loss, and growing socioeconomic inequalities, the need for transformative, systemic change has never been more urgent. Conventional innovation approaches, often focused on technological solutionism and market imperatives, have consistently fallen short in delivering the comprehensive, equitable, and sustainable solutions required to navigate these interconnected crises. This pioneering article explores the profound intersection between speculative fiction, sustainable innovation, and the burgeoning field of innovationology. By harnessing the transformative power of imaginative narratives, the integrated praxis of innovationology and sustainability science can challenge existing mental models, spark collective imagination, and foster agency to co-create sustainable futures. Through a rigorous examination of cutting-edge research, empirical evidence, and case studies, this article positions speculative fiction as a critical lever for catalyzing the systemic changes required for a more just, regenerative, and resilient future.

water resources in Morocco have been severely influenced by climate change (CC) and pro-longed drought, particularly, in the pre-Saharan zone. The Tafilalet region faces increasing pres-sure due to high demographic growth, increased demand for water, excessive groundwater con-sumption, and investment in agriculture. Using the Water Evaluation and Planning System (WEAP), this study assessed land cover and elevation and created future scenarios using the Standard Precipitation Index (SPI) and Standard Groundwater Level Index (SGI) to monitor hy-droclimate drought conditions in the Ziz watershed from 1989 to 2022. Results show decreasing precipitation, particularly from 2010-2020, with the last four years being the most challenging (SPI<-2). SPI and SGI have a high correlation, suggesting precipitation impacts groundwater in-dicators. Future scenarios predict a high risk of CC, with a 30% decrease in annual precipitation accumulation by 2100 under the optimistic scenario SSP126. Minimum temperature is expected to increase by 1.08°C (SSP126) and 2.61°C (SSP585), and maximum temperature by 1.05°C (SSP126) and 2.93°C (SSP585). Keywords: Climate Change, Water Resources, SPI, SGI, WEAP, Ziz watershed, Drought

South Africa’s internationally celebrated water legislation placed the responsibility for investing in water services at the door of the government. In recent years South Africa has struggled to invest adequately to keep up with growing demand for these services. The result is a suite of social, economic and environmental risks that are destabilising to the fiscus and the financial sector. This paper explored both operating and capital costs, and applied the ‘Beyond the Gap’ analysis to show that an additional 55% investment (R91 billion annually) is necessary to ensure South Africa meets its water policy goals. The analysis explores the factors that influence the investment amount and shows that a combination of policy choices and exogenous factors such as climate change could render the investment gap anywhere between 30% and 90% of the estimated current allocation to the water sector. The most significant savings are attributed to reducing the extent of “non-revenue water”, an energy transition away from coal, sharing of some water taps between (up to) five houses, reduced water allocations to agriculture, investments in invasive alien plant (IAP) clearing in water catchments above dams, and water demand management, capacity building and more efficient integration of different bulk water schemes. The study revealed important dependencies between capital and operating costs; where operating costs are ignored, the decay of water infrastructure is accelerated. Showing the contingency of investment needs on policy choices, places responsibility for attaining water policy goals and SDG 6 in the hands of a diverse set of actors. Quantifying the investment need also raises the critical question of how to raise the required investment. Recognising the need to balance risks to financiers with the widespread risks to households, companies and government when investment in water services is inadequate, South Africa is exploring a Monetary Architecture approach of inter-balance sheet relationships in an attempt to mobilise investment from new sources.

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.

Surface temperature influences human health directly and alters the biodiversity and productivity of the environment. While previous research has identified that the composition of urban landscapes influences the physical properties of the environment such as surface temperature, a generalizable and flexible framework is needed that can be used to compare cities across time and space. This study employs the Structure of Urban Landscapes (STURLA) classification combined with remote sensing of New York City’s (NYC) surface temperature. These are then linked using machine learning and statistical modeling to identify how greenspace and the built environment influence urban surface temperature. It was observed that areas with urban units composed of largely the built environment hosted the hottest temperatures while those with vegetation and water were coolest. Likewise, this is reinforced by borough-level spatial differences in both urban structure and heat. Comparison of these relationships over the period between2008 and 2017 identified changes in surface temperature that are likely due to the changes in prevalence in water, lowrise buildings, and pavement across the city. This research reinforces how human alteration of the environment changes ecosystem function and offers units of analysis that can be used for research and urban planning.

At 8000 m and above, a ‘death zone’ reputation afforded protection for the fragile ecosystems of the Himalaya and Korakoram ranges for thousands of years. After decades of high-altitude mountaineering, environmental impacts have been documented such as associated carbon-intensive air travel and contamination from waste. Despite the growing popularity, high-risk and fragile context of the sport, the behaviour, perspectives and experiences of high-altitude mountaineers, and the social and economic consequences have not been researched. Following an interpretive paradigm and using purposive sampling, this qualitative study conducted in-depth interviews and open-ended survey questions to collect the experiences of sixteen high-altitude mountaineers. Analysis of the qualitative data was informed by Grounded Theory with the coding process leading to the overarching category of ‘leave no trace’. The results show how the high risks to life, and growing popularity of the activity influence mountaineer’s ability to act sustainably and increase unsustainable behaviour despite a desire to ‘leave no trace’ on the mountain. Meanwhile, climate change has already and will increasingly have profound impacts on the risks associated with 8000m mountaineering. Allowing more time for acclimation would help to address the root causes of unsustainable behaviours along with better enforcement of regulations.

According to current forecasts, global heating is likely to exceed 2,8°C by the end of the century. This makes substantial adaptation measures necessary to secure a broad basis for livelihoods provision and the conservation of biodiversity. While the implementation of top-down and technocratic adaptation efforts is the majority, related adaptation shortcomings of socio-economic and ecological nature are becoming more and more apparent. Community-based adaptation (CBA) with its participatory, inclusive and needs-based bottom-up approach offers a promising and powerful alternative. This article uses a semi-systematic literature review approach to screen the current literature and identify core issues of CBA. Linking communality, locality, multidimensionality, power imbalances, transformative potential, localisation, the triad of adaptation metrics and adaptation with nature to corresponding potential actions for practical implementations provides a more holistic conceptualisation and broadens the horizons for further learnings, research and improved application.

The impact of the climate crisis on urban environments and life within them is evident. In the face of challenges like heatwaves, floodings and other extreme events, pollution, and declining quality of life in cities, there is a growing demand for the preservation and expansion of urban green spaces, often driven by citizen-led transformations. This paper examines 100 urban greening projects initiated or supported by citizens globally, categorizing them according to the type of greenery, the stakeholders involved, the mode of implementation and the use of smart technologies incorporated. We notice variations in green endeavors based on the stakeholders spearheading them, however most of entirely citizen-led initiatives aimed at the creation of urban farms and food growing, demonstrating the pressuring needs for food securing and self-determination in communities. More than half of the assessed initiatives that managed to scale up and multiply had public authorities providing a framework or a type of support for their development or an NGO or other organization providing expertise and mobilize citizens at various stages. In terms of technological use, we find mostly websites and social media platforms easing participatory endeavors and knowledge sharing of best practices, accelerating scaling efforts, while there is a low integration of more advanced digital technologies, which if used, could enable real-time monitoring of green spaces, inform evidence-based decision-making, and streamline processes in scaling up green initiatives.

This study investigates the impact of climate change on the efficiency of organic honey production in Türkiye using a machine learning approach. The eXtreme Gradient Boosting (XGBoost) algorithm is employed for the Machine Learning (ML) modelling. The analysis includes data on organic honey production performance from 2004 to 2023, spanning a period of 20 years, and 8 different climate variables (16 variables depending on daytime and nighttime values). The dataset created to investigate the impact of climate change on organic honey yield comprises 28 columns and 120,960 rows. The study aimed to determine the significance of different climatic variables on the efficiency of organic honey production. The study found that, in addition to daytime solar radiation and temperature, wind speed and direction were also important factors. The sensitivity analysis has shown that minor alterations in the variables have a significant impact on the model's predictions. Additionally, non-linear relationships between the variables and honey production were identified. These findings suggest that it may be beneficial to consider implementing climate change adaptation and mitigation strategies in agricultural policies and beekeeping practices. The study suggests that machine learning has the potential to provide valuable insights into the complex relationship between climate change and agricultural production. This could aid in the sustainability and economic optimization of the sector.

Climate change is currently one of the main problems facing agriculture to achieve sustainability. It causes situations such as drought, increased rainfall, and increased diseases, causing a decrease in food production. In order to combat these problems, Agricultural Big Data contributes with tools that allow improving the understanding of complex, multivariate, and unpredictable agricultural ecosystems through the collection, storage, processing, and analysis of vast amounts of data from diverse heterogeneous sources. This research aims to discuss the advancement of technologies used in Agricultural Big Data architectures in the context of climate change. The study aims to highlight the tools used to process, analyze, and visualize the data and discuss the use of the architectures in the crop, water, climate, and soil management, especially to analyze the context, whether it is in Resilience Mitigation or Adaptation. The PRISMA protocol guided the study, finding 33 relevant papers. Despite the advances in this line of research, few papers were found that mention the components of the architectures, in addition to the lack of standards and the use of reference architectures, which allow the proper development of Agricultural Big Data in the context of climate change.

Concerns of food and environmental security have increased enormously in recent years due to the vagaries of climate change and variability. Efforts to promote food security and environmental sustainability often reinforce each other and enable farmers to adapt to and mitigate the impact of climate change and other stresses. Some of these efforts are based on appropriate technologies and practices that restore natural ecosystems and improve the resilience of farming systems, thus enhancing food security. Climate smart agriculture (CSA) principles, for example, translate into a number of locally-devised and applied practices that work simultaneously through contextualised crop-soil-water-nutrient-pest-ecosystem management at a variety of scales. The purpose of this paper is to review concisely the current state-of-the-art literature and ascertain the potential of the Pfumvudza concept to enhance household food security, climate change mitigation and adaptation as it is promoted in Zimbabwe. The study relied heavily on data from print and electronic media. Datasets pertaining to carbon, nitrous oxide and methane storage in soils and crop yield under zero tillage and conventional tillage were compiled. Findings show that, compared to conventional farming, Pfumvudza has great potential to contribute towards household food security and reducing carbon emissions if implemented following the stipulated recommendations. These include among others, adequate land preparation and timely planting and acquiring inputs. However, nitrous oxide emissions tend to increase with reduced tillage and, the use of artificial fertilizers, pesticides and herbicides is environmentally unfriendly.

Climate change is a buzzword in the world. Scientist has approved it as global warming with its projection of undesired and unpredicted frequent extreme events and their vulnerabilities not only at present but also at future. There is an assumption of occurrence of adaptive capacity and behavior of farmers in agriculture production activity at some extent to neutralize climate change vulnerabilities of flood and landslides on paddy production. This paper empirically examines the effects of climate change in paddy production and farmer’s adaptive behaviors to neutralize such climatic shocks and events in paddy production by employing CD production function based econometric model. The study employed primary data collected through 642 household surveys. The study finds that climatic shocks and events have huge loss (60%) in paddy production and revenue income in such plot where farmers have not indigenous knowledge and practices. But both small and larger farmers who have adaptive capacity and behavior with their indigenous knowledge have less loss in paddy production and revenue income, although they have heterogeneity in their socio-economic characteristics (income, asset holding, literacy, experience, land holding and age). The farmers who have used adaptive behavior have indigenous knowledge and experiences including bamboo wall construction to control flood and landslides and seed change to resist climatic shocks and events. In hilly region, the farmers have not sufficient alternative measures, except both adaptive measures because of their poverty, illiteracy and remote locations. The study finds their higher effective level to minimize vulnerabilities to paddy production and revenue per farm plot, although these adaptive behaviors are cost effective and local entity. Comparatively, bamboo wall construction is more effective measure in the paddy production than others are (seed switch) to minimize the flooding materials from the flood and the landslides. Thus, low cost indigenous adaption behavior of farmers is effective measure to climate change and climate change induced disasters and events vulnerability in paddy production.

Having sustained, over the course of more than two decades, record-breaking natural catastrophe losses, American insurers and reinsurers are justifiably questioning the potential linkage between anthropogenic climate change and extreme weather. Here, we explore issues pertaining to this linkage, looking at both the likely short-term implications for the insurance industry, as well as potential longer-term impacts on financial performance and corporate resilience. We begin our discussion with an overview of the implications that climate change is likely to have on the industry, especially as it relates to how catastrophic risks are construed, assessed, and managed. We then present the rudiments of an econometric analysis that explores the financial resilience of the property/casualty (P/C) industry in the face of both natural and man-made catastrophes. In this analysis, we explore the profitability consequences of several illustrative scenarios involving large-scale losses from extreme weather—specifically, a sequence of storms like those striking the U.S. in 2004—and a scenario that explores the prospect of a Katrina-scale storm in combination with a mass terror attack on the scale of 9/11. At systemic levels of aggregation, our analysis suggests a high degree of macro-resilience for the insurance industry. Moreover, we find that insurer resilience is higher for larger impacts, considering both the speed of recovery, as well as the inverse of the area under the unaffected system profile. We conclude with a summary of our findings and a closing commentary that explores the potential implications of these results for P/C insurers moving forward.

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

Innovative interventions in the planning and design of stair and escalator facilities call for understanding their effects on stair use. This study considers five planning variables for the twinned stair and escalator facilities–stair pitch and width, angle of deviation, height and separating distance. Public sites were identified in 8 commercial districts in Beijing. Facilities (n=21) presenting heterogeneously across variables were sampled for simultaneous up and down pedestrian counts in 18 5-minute video segments middays, for a total of 1464 counts. Stair width accounts for 20% of the variance in ascending rate and 10% in descending. Plan angle accounts for 2% in ascending and 5% in descending, while pitch accounts for 1% in ascending and 5% in descending. The study confirms the effects of layout and design of stairway and escalator facilities on facility choice. The results point directly to interventions in support of higher stair-climbing rates.

In northern Canada where permafrost is prevalent, a shortage of accessible, affordable, and high-quality housing has been ongoing for decades. Design of foundations in permafrost presents unique engineering challenges due to permafrost soil mechanics and climate change. There is no specific design code for pile or shallow foundations in northern Canada. Consequently, the design process heavily relies on the expertise and experience of Arctic geotechnical engineers who have specialized knowledge in this field. Therefore, a comprehensive review of the practice or literature in foundation design in the Arctic would be necessary. The main objective of this review paper is to provide an overview of the common foundations in permafrost and the techniques adopted to counteract the effects of frozen soils. This study conducted a literature review of state-of-the-art practices on deep and shallow foundations used in northern Canada, including common steel pipe piles and thermosyphons. The review summarized the current principles, including adfreeze strength, creep settlement, and frost heave, used in the foundation design in permafrost. Then this paper summarized the findings from interviewing several engineers or professionals who have experiences in the design of foundations in permafrost. The interviews revealed the technical and non-technical aspects of foundation design practice in northern Canada. Lastly, in order to demonstrate the design methods, the paper presented two examples where screw piles and steel pipe piles were designed to support a residential building in northern Canada, according to the state-of-practice criteria for adfreeze strength, long term settlement and frost heave.

General characteristics of K changes together with their fine structure associated with ground flashes in Sri Lanka in the tropics are presented. It is found that on average there are about 2 K changes associated with each return stroke. Analysis of the fine structure of the K changes shows that the K change is a chaotic pulse burst. Some of these chaotic pulse bursts start and the others end as a regular pulse bursts. Sometimes the chaotic part occurs in between two regular pulse bursts. This is in agreement with the recent published results that claim that chaotic pulse bursts are a random superposition of regular pulse bursts. The results show that the small step fields identified in the literature as K changes are the static fields associated with these pulse bursts.

: Seaweeds are among the most important biomass feedstocks for the production of third generation biofuels. They are also efficient in carbon sequestration during growth, and produce a variety of high value chemicals. Given these characteristics together with the relatively high carbohydrate content, seaweeds have been discussed as an ideal means for CO2 capture and biofuel production. Though third generation biofuels have emerged as some of the best alternatives to fossil fuels, there is currently no large-scale production or mainstream use of such liquid fuels due to the many technical challenges and high production costs. The present study describes the concept of coastal marine biorefineries as the most cost-effective and sustainable approach for biofuel production from sea-weeds as well as atmospheric carbon capture and storage (CCS). The suggested refinery system makes use of marine resources, namely seawater, seaweed, and marine microorganisms. Firstly, extensive screening of the current literature was performed to determine which technologies would enable the emergence of such a novel biorefinery system and its merits over conventional refineries. Secondly, the study investigates various scenarios assessing the potential of seaweeds as a means of carbon sequestration. We demonstrate that the removal of 100 Gigatons of excess CO2 using seaweed farms can be achieved in around 4 months to less than 12 years depending on the area under cultivation and the seaweed species. The total bioethanol that could be generated from the harvested biomass is around 8 trillion litres. In addition, high-value chemicals (HVC) that could potentially be recovered from the process represent a considerable op-portunity with multi-billion-dollar commercial value. Overall, coastal marine biorefineries have strong potential for a sustainable green economy and rep-resent a rapid approach for climate change mitigation.

Drought events are evident effects of climate change around the globe and yield several socio-economic impacts. Such effects are even more relevant for South America (SA) since different activities essential for the continent, like agriculture and energy generation, depend highly on water resources. Thus, this study aimed to evaluate future changes in precipitation and hydro-logical droughts occurrence in SA through climate projections from eight global climate models (GCMs) of CMIP6. To this end, statistical downscaling was applied to the projections with the Quantile Delta Mapping technique, and the method proved to be efficient in reducing systematic biases and preserving GCMs’ trends. For the following decades, the results show considerable and statistically significant reductions in precipitation over most of SA, especially during the austral spring, with the most intense signal under the SSP5-8.5 forcing scenario. Furthermore, GCMs showed mixed signals about projections of the frequency and intensity of drought events. Still, they indicated agreement regarding the increase in duration and severity of events over all of SA and a substantial proportion of moderate and severe events over most of Brazil during the 21st century. These results can be helpful for better management of water resources by deci-sion-makers and energy planners.

The WASP-Index is computed over Iberia for three monthly timescales in 1961-2020, based on an observational gridded precipitation dataset (E-OBS), and in 2021-2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under RCP4.5 and RCP8.5. The WASP performance in identifying extremely dry or wet events, reported by the EM-DAT disaster database, is assessed for 1961–2020. An overall good agreement between the WASP spatial patterns and the EM-DAT records is found. The areolar mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12m-WASP intermediate dry events under RCP8.5. Besides, the number of 3m-WASP intermediate-to-severe wet events is projected to increase, mostly the severest events under RCP4.5, but no evidence was found for an increase in the number of more persistent (12m-WASP) wet events under both RCPs. Despite important spatial heterogeneities, an increase(decrease) of the intensity, duration, and frequency of occurrence of the 12m-WASP intermediate-to-severe dry(wet) events is found under both scenarios, mainly in the southernmost regions of Iberia, thus becoming more exposed to prolonged and severe droughts in the future, corroborating the results from previous studies.

Abstract: Currently, thermal power is the largest source of power in the world. Although the impacts of climate change on cooling water sufficiency in thermal power plants have been extensively assessed globally and regionally, their economic consequences have seldom been evaluated. In this study, the Asia-Pacific Integrated Model Computable General Equilibrium model (AIM/CGE) was used to evaluate the economic consequences of projected future cooling water insufficiency on a global basis, which was simulated using the H08 global hydrological model. This approach enabled us to investigate how the physical impacts of climate change on thermal power generation influence economic activities in regions and industrial sectors. To account for the uncertainty of climate change projections, five global climate models and two representative concentration pathways (RCPs 2.6 and 8.5) were used. The ensemble-mean results showed that the global gross domestic product (GDP) loss in 2070–2095 due to cooling water insufficiency in the thermal power sector was −0.21% (−0.12%) in RCP8.5 (RCP2.6). Among the five regions, the largest GDP loss of −0.57% (−0.27%) was observed in the Middle East and Africa. Medium-scale losses of −0.18% (−0.12%) and −0.14% (−0.12%) were found in OECD90 (the member countries of the Organization for Economic Co-operation and Development as of 1990) and Eastern Europe and the Former Soviet Union, respectively. The smallest losses of −0.05% (−0.06%) and −0.09% (−0.08%) were found in Latin America and Asia, respectively. The economic impact of cooling water insufficiency was non-negligible and should be considered as one of the threats induced by climate change.

This study examines the attitudes of healthcare organizations and employees in the Greek Healthcare System towards climate change and the influence of management in promoting environmentally friendly practices. A questionnaire was sent electronically to the 7 Health Districts of Greece and private sector healthcare workers associated with the researchers, while the sample consisted of service (administration, nursing, technical, and medical). The main findings indicate that public sector health organizations are lacking in motivating employees to adopt "green" actions during their work. Communication and information dissemination from administration to healthcare professionals were identified as significant challenges, resulting in participants being unsure of how to respond, in contrast to the private sector which showed slightly more positive results. Moreover, the study highlights a positive association between education level and voluntary green behaviors of employees. This research emphasizes the urgency to confront climate change in conjunction with the principles of Organizational Behavior within the Greek Healthcare System.

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortage. In response to this pressing issue, this study provides a comprehensive as-sessment of water supply, demand and balance within the Cauto River Basin, considering the baseline and projected socio-economic and climatic conditions by coupling of SWAT and WEAP models. The obtained results reveal that the annual flow in the CRB is projected to slightly de-crease (2.5%) in which the reduction in the rainy season (3.1%) is higher than that in the dry sea-son (1.3%). Total water demand in the baseline scenario is around 1.194 billion m3, dominated by agriculture (96%), with rice crop requiring nearly half. For the future scenario of 2050, the study shows a 16.6% surge in demand to 1.394 billion m3, driven by climate change and agricultural expansion. However, domestic use decreases by 10% due to population reduction. Water deficit in the future is projected to increase by 52% from 172.4 to 262.7 million m3 due to rising water demand and declining water supply. This study shows that integrating a hydrological model into a water allocation model is a promising approach to estimate the water supply, demand and balance, which is a crucial component of water resources management.

The current study was planned to simulate runoff due to the snowmelt in the Lidder River catchment of Himalayan region under climate change scenarios. A basic degree-day model, Snowmelt-Runoff Model (SRM) was utilized to assess the hydrological consequences of change in climate. The SRM model performance during the calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found as 11.7, -10.1, -11.8, 1.96, and 8.6 during 2009-2014, respectively, while the R2 is 0.96, 0.92, 0.95, 0.90, and 0.94, respectively. The Dv and R2 values indicating that the simulated snowmelt runoff has a close agreement with the observed value. The simulated findings were also assessed under the different scenarios of climate change: a) increases in precipitation by +20 %, b) temperature rise of +2 °C, and c) temperature rise of +2 °C with a 20 % increase in snow cover. In scenario "b", the simulated results showed that runoff increased by 53 % in summer (April–September). In contrast, the projected increased discharge for scenarios "a" and "c" was 37 % and 67 %, respectively. In high elevation data-scarce mountain environments, the SRM is efficient in forecasting future water supplies due to the snowmelt runoff.

Changes in agricultural yields due to climate change will affect land use, agricultural production volume, and food prices as well as macroeconomic indicators, such as GDP which is important as it enables one to compare the climate change impacts across multiple sectors. This study considered five key uncertainty factors and estimated macroeconomic impacts due to crop yield changes using a novel integrated assessment framework. The five factors are 1) land-use change (or yield aggregation method based on spatially-explicit information), 2) the amplitude of the CO2 fertilization effect, 3) the use of different climate models, 4) socioeconomic assumptions and 5) the level of mitigation stringency. We found that their global impacts on the macroeconomic indicator value were 0.02 - 0.06% of GDP in 2100. However, the impacts on the agricultural sector varied greatly by socioeconomic assumption. The relative contributions of these factors to the total uncertainty in the projected macroeconomic indicator value were greater in a pessimistic world scenario characterized by a large population increase and low income (0.6%) than in an optimistic scenario (0.00%).

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

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

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.

Natural ecosystem of Islands and coastal region are vulnerable to climate change phenomena such as increasing temperature, fluctuating rainfalls, ocean acidification and tsunami. Andaman and Nicobar group of islands lies in Bay of Bangal facing such extreme climate phenomena. A spatial-temporal analysis of forest cover of middle Andaman region of the Andaman and Nicobar group of islands was done from 1990 to 2019 with an interval of 5-10 years. Support vector machine classifier, spectral indices such as Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index were used for the analysis of greenery, water resources, and urban land. Land surface temperature was estimated using split window algorithm for Landsat 8 and mono window algorithm for Landsat 5. The data showed relative contribution of forest region toward rising temperature in the island region. The research also showed that subsurface hydrology linked to interconnected lineaments provides a stable zone for forest cover. The open forest showed maximum fluctuation while minimum change was observed in Evergreen Forest. The spectral characteristics analysis using indices showed significant change except in 2005 due to Tsunami occurred in 2005. The land surface temperature showed fluctuation near to 30° C from 1990 to 2019.

Population is the main driver of land systems and environmental change. However, the population is usually treated as a variable that only considers the population number, and the multidimensional population structure is largely ignored. There has been a systematic transition of population structure in the past several decades, such as the changing household structure, the increasing aging population and divorce rate, and human migration. All these have direct or indirect impacts on land use and environmental issues. Here, we will take China as an example to examine the relationship between household dynamics and land use change in China by exam-ining changes in household structure and land use change in China between 1980 and 2020. The results show:1) the number of households increased by 130.95% from 1980 to 2020, while the population only increased by 42.83%. The size of households decreased from 4.41 to 2.92 in China from 1982 to 2020. The household dynamics vary from province to province, which is affected by urbanization rate and economic development. 2) Birth rates, divorce rates, population aging, and migration all affect household structure, which directly or indirectly affects changes in land use systems. 3) The changes in China's land use are interlinked and interact with changes in household structure, evident in the increase in residential land use and the abandonment of arable land. The rising household number increased the area of urban and rural settlement, leading to the fragmentation of cultivated land and the reduction of ecological land. To regulate land use change for sustainable development, future land use planning should take into effect of household dynamics, and reduce the negative effects of household dynamics on land systems and environmental change.

We have developed additive logistic models for the occurrence of lightning, large (≥ 2 cm), and very large (≥ 5 cm) hail to investigate the evolution of these hazards in the past, in the future, and for forecasting applications. The models, trained with lightning observations, hail reports, and predictors from atmospheric reanalysis, assign an hourly probability to any location and time on a 0.25° × 0.25° × 1-hourly grid as a function of reanalysis-derived predictor parameters, selected following an ingredients- based approach. The resulting hail models outperform the Significant Hail Parameter and the simulated climatological spatial distributions and annual cycles of lightning and hail are consistent with observations from storm report databases, radar, and lightning detection data. As a corollary result, CAPE released above the -10°C isotherm was found to be a more universally skilful predictor for large hail than CAPE. In the period 1950–2021, the models applied to the ERA5 reanalysis indicate significant increases of lightning and hail across most of Europe, primarily due to rising low-level moisture. The strongest modelled hail increases occur in northern Italy with increasing rapidity after 2010. Here, very large hail has become 3 times more likely than it was in the 1950s. Across North America trends are comparatively small, apart from isolated significant increases in the direct lee of the Rocky Mountains and across the Canadian Plains. In the southern Plains, a period of enhanced storm activity occurred in the 1980s and 1990s.

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.

Anthropogenic disturbances interacting with natural disturbances, ecological and socio-economic factors can provoke forest degradation and modulate ecosystem resilience. In Haiti, protected areas recently created to reduce forest loss, require studies about forest dynamics and land use to assure the development of sustainable management policies. We combine field interview with Landsat satellite images of the Macaya National Park collected between 1985 and 2021 to investigate: 1) how much of the original forest area has been converted into agricultural or logged area since 1985; and 2) how do elevation and slope influence the expansion of human-induced land-use changes. Our results indicate an increase of 11.36% in forest cover and a reduction of 75.34% in agriculture class cover, despite the passage of seven hurricanes in the region. Forest recovery was apparently unrelated to elevation and slope, and likely reflected the implementation of new environmental laws and policies with the creation of the Macaya National Park in 1983. Restoration and protection programs contributed to ensure access to financial resources, technical assistance and new technology, thus promoting a shift into a more resilient forest system. This study brings hope for forest conservation in Haiti by showing that positive results can be achieved through inclusive collaboration.

The Tsunami disaster was the first and the biggest in Banten Province. However, in response to the health crisis, the preparedness was still lacking, even though in an emergency response situation, the management of disaster management carried out was quite good. The method of research is based on data reports that include quantitative and qualitative methods. Analyzing health facilities and the impacts that occurred in the field during the tsunami period is the basis for this article and, at the same time, a discussion of describing problems that can be anticipated in the future.

Cleaning wastewater and using it again for secondary purposes is a measure to address water scarcity in urban areas. However, upscaling of recycled water schemes is challenging due to the possible emergence of various barriers. Based on a review of the governance literature we suggest that a set of five governance conditions is necessary for a successful upscaling of recycled water schemes; (1) policy leadership, (2) policy coordination, (3) availability of financial resources, (4) awareness of a problem, and (5) the presence of a public forum. In order to elaborate on the practical relevance of these conditions we studied a recycled water scheme currently being upscaled in Sabadell, Spain. We reviewed policy documents, conducted a set of 21 semi-structured interviews, and attended two policy meetings about the subject. Our results suggest that Sabadell meets the required conditions for upscaling reused water to a certain extent. However, the presence of a public forum is lacking. We discuss the implications of the absence of the venue and procedures for public participation in Sabadell and how it could be strengthened. Following this discussion, we conclude with some lessons for other cities that plan to upscale their recycled water schemes.

The aim of this study was to examine the seasonal variations in relevant indices of physical performance in female soccer players. Twenty-seven female soccer players were assessed at week 2 of the season (pre-season, PS), week 7 (end of pre-season, EP), week 24 (half-season, HS), and week 38 (end of season, ES). Testing sessions consisted of: 1) vertical countermovement jump (CMJ); 2) 20-m running sprint (T20); 3) 25-m side-step cutting maneuver test (V-CUT); and 4) progressive loading test in the full-squat exercise (V1-LOAD). Participants followed their normal soccer training, which consisted of three weekly training sessions and an official match, without any type of intervention. No significant time effects were observed for CMJ height (P = 0.29) and T20 (P = 0.11) along the season. Significant time effects were found for V-CUT (P = 0.004) and V1-LOAD (P = 0.001). V-CUT performance significantly improved from HS to ES (P = 0.001). Significant increases were observed for V1-LOAD throughout the season: PS-HS (P = 0.009), PS-ES (P &lt; 0.001); EP-ES (P &lt; 0.001); HS-ES (P = 0.009). In conclusion, female adapted soccer training may be effective for increasing muscle strength and change of direction ability. The high volume of endurance-type training typically accumulated throughout the season may prevent any sprint and jump improvements.

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

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.

This study evaluates spatial analyses of groundwater quality and environmental changes to obtain information on the groundwater contamination in the Permian Basin, Texas. Coupled with the U.S. government’s open data, these analyses can identify regions where environmental change could have potentially effected groundwater quality. A total of thirty-six wells were selected within the six counties: Andrews, Martin, Ector, Midland, Crane, and Upton. Spatial distribution maps were created for six different parameters: pH, total dissolved solids (TDS), chloride, fluoride, nitrate, and arsenic. Total groundwater quality maps incorporate all the contaminants and denote regions of poor, medium, and optimum conditions. To identify spatial changes in groundwater quality, maps were separated into two different time intervals, 1992-2005 and 2006-2019. We found that groundwater contamination resulted primarily from the mobilization of the contaminant from natural sources or anthropogenic activities such as chemical fertilizers. Overall, groundwater quality decreased during the study period from 1992 to 2019 as population and urban growth began to develop in the Permian Basin. This study contributes on understanding of the response of groundwater quality associated with environmental change in the Permian Basin. Therefore, this research provides important information for groundwater managements in developing plans for the use of water resource in the future for Texas.

Climate change threatens water, sanitation and hygiene (WaSH) facilities and services, as these are intimately linked to the water cycle and are vulnerable to changes in the quantity and quality of available water resources. Floods and droughts, which pollute and reduce water delivery respectively, have now become a perennial issue to deal with in the northern regions of the country, including the Bolgatanga Municipality. This study aimed to assess the degree to which climate change adaptation measures are mainstreamed into the WaSH development planning process in Ghana. Stakeholders from government and non-government agencies were interviewed to gain perspectives on the threat of climate change, the inclusion of climate change in WaSH planning and the barriers preventing mainstreaming. In general, despite awareness and concern about climate change, adaptation measures have been regarded to be far away from the immediate concerns of WaSH development planning. Most of the current measures are reactive and respond to environmental issues rather than to climate change stressors. In essence, stakeholders expressed the view that the adaptive capacity of the Municipality was low and that mainstreaming has not yet occurred. Despite the lack of progress, there are great opportunities for mainstreaming climate change adaptation into planning through increasing awareness and capacity, legislative and institutional changes and the development of participatory systems to provide early warning systems and disaster risk analyses that will inform future planning.

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

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.

Introduction: studies in the last two decades have found declining snake populations in both temperate and tropical sites, including informal reports from Drake Bay, Costa Rica. Objective: to investigate if reports of decreasing snake populations in Drake Bay had a real basis, and if environmental factors, particularly temperature, rain and light, have played a role in that decrease. Methods: we worked at Drake Bay from 2012 through 2017 and made over 4000 h of transect counts. Using head flashlights we surveyed a transect covered by lowland tropical rainforest at an altitude of 12–38 m above sea level, near the Agujas River, mostly at 1930–2200 hours. We counted all the snakes that we could see along the transect. Results: snake counts increase from August to September and then decline rapidly. The May snakes/rainfall peaks coincide, but the second snake peak occurs one month before the rain peak; we counted more snakes in dry nights, with the exception of Imantodes cenchoa which was equally common despite rain conditions. We saw less Leptodeira septentrionalis on bright nights, but all other species were unaffected. Along the six years, the number of species with each diet type remained relatively constant, but the number of individuals declined sharply for those that feed on amphibians and reptiles. We report Rhadinella godmani, a highland species, at 12–38 m of altitude. Conclusion: night field counts of snakes in Drake Bay, Costa Rica, show a strong decline from 2012 through 2017.

This paper introduces the self-supervised pretext task of rare visual token enhancement: given an image, the model is trained to push the rarest visual tokens far from all the others. This pretext task slightly-but-consistently improves baseline performances for both registration and few-shot change detection on OSCD, LEVIR-CD and S2looking.

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 paper argues that, in 2020, the beneficial atmospheric effect from the reduction in aviation may have been at least 7-8 times greater than that occurring from the reduction in fossil carbon dioxide emissions from all sectors. Specifically, compared to potential atmospheric effects in 2020 without the pandemic, the decrease in effective radiative forcing from reduced contrail-cirrus formation may have been in the order of 35mWm^-2 in 2020, compared to a reduction of only 4-5mWm^-2 from the drop in fossil CO₂ emissions. Over time, pursuing a low carbon pathway generates benefits that mount up to be much more significant than 2020 effects might imply, and is essential to stabilise the climate. However, a twin-track policy focus may be needed, with more emphasis on reducing short-term climate forcing, to minimise the impacts of climate change now, and to avoid detrimental feedback events. Future policy decisions about aviation should be made in this context.

Cities worldwide are facing ever-increasing pressure to develop mitigation strategies for all sectors to deal with the impacts of climate change. Cities are expected to house 70% of the world’s population by 2050 and developing related resilient health systems is a significant challenge. Because of their physical nature, cities’ surface temperatures are often substantially higher than that of the surrounding rural areas, generating the so-called Urban Heat Island (UHI) effect. Whilst considerable emphasis has been placed on strategies to mitigate against the UHI-associated negative health effects of heat and pollution, the World Health Organization estimates that one of the main consequences of global warming will be an increased burden of such vector-borne diseases. Many of the major mosquito-borne diseases are urban and thus the global population exposed to these pathogens will steadily increase. Mitigation strategies beneficial for one sector may, however, be detrimental for another. Implementation of inter-sectoral strategies that can benefit many sectors (such as water, labour and health) do exist and would enable optimal use of the meagre resources available. Discussion among inter-sectoral stakeholders should be actively encouraged.

This study considers the change-point test problem for time series based on the self-normalization ratio statistic test, which is constructed using residuals obtained from a support vector regression (SVR)-autoregressive moving average (ARMA) model. Under the null hypothesis, the series is a stationary process, and our test statistic converges to a non-degenerate distribution. Under the alternative hypothesis, there are change-points in the time series, and the self-normalization test statistic diverges to infinity. The simulations show that our proposed new test has better finite sample performance than other SVR-based tests in the literature. Finally, we illustrate its usefulness by analyzing two actual data sets.

Global change is affecting vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing offer a unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that NDVI has increased over the studied period, particularly at low and middle elevations and during fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily to temperature or precipitation trends. On the other hand, interannual fluctuation in NDVI is more correlated with temperature and precipitation. RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.

Semi-arid Namibia is marginal for agricultural production. Low soil fertility combined with low and variable rainfall restrict the livelihoods of smallholder farmers who often struggle to produce enough food. Although historically communities have adopted a number of coping mechanisms, climate change threatens to further reduce agricultural production. There are many additional options available to smallholder farmers to adapt to climate change, but they are not necessarily adopting these measures despite having noticed increasing temperatures and declining rainfall. Semi-structured interviews were conducted in three villages in Onesi constituency to examine what agricultural practices smallholder crop farmers use, perception of changes in their yields, their perspective on future yields and whether they are planning on changing their agricultural practices. The results suggest that to sustain the livelihoods of rural communities in north-central Namibia support is needed from local and regional authorities, as well as traditional and religious leaders to assist with enhancing access to information, enabling information sharing on adaptation options, and increasing awareness on climate change, it’s impacts and what can be done about it. In addition to this the implementation of adaptation action also requires demonstration sites and building capacity to enable the development of self-help groups.

The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 77.64% to 93.51% (kappa 0.09–0.59) in the Southern New England study area and 59.57% to 79.57% (kappa 0.09–0.45) in the Rio Grande National Forest study area. In general, ORS products met or exceeded the overall accuracy and kappa of IDS and RTFD products. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.

Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations - the extended AVHRR Polar Pathfinder (APP-x), trends in sea ice concentration, ice extent, ice thickness, and ice volume in the Arctic from 1982 to 2020 are investigated. Results show that the Arctic has become less ice-covered in all seasons, especially in summer and autumn. Arctic sea ice thickness has been decreasing at the rate of -3.24 cm per year, resulting in about a 52% reduction in thickness from 2.35 m in 1982 to 1.13 m in 2020. Arctic sea ice volume has been decreasing at the rate of -467.7 km³ per year, resulting in about a 63% reduction in volume, from 27590.4 km³ in 1982 to 10305.5 km³ in 2020. These trends are further examined from a new perspective, where the Arctic Ocean is classified into open water, perennial, and seasonal sea ice-covered areas based on the sea ice persistence. The loss of the perennial sea ice-covered area is the major factor in the total sea ice loss in all seasons. If the current rates of sea ice changes in extent, concentration, and thickness continue, the Arctic is expected to have ice-free summer by the early 2060s.

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.

Globalization and industrialization have significantly disturbed the environmental ecosystem, leading to critical challenges such as global warming, extreme weather events, and water scarcity. Forecasting temperature trends is crucial for enhancing the resilience and quality of life in smart sustainable cities, enabling informed decision-making and proactive urban planning. This research specifically targets Ahmedabad city in India and employs the Seasonal Auto Regressive Integrated Moving Average with eXogenous factors (SARIMAX) model to forecast temperatures over a ten-year horizon using two decades of real-time temperature data. The stationarity of the dataset was confirmed using the Augmented Dickey-Fuller test, and the Akaike Information Criterion (AIC) method helped identify the optimal seasonal parameters of the model, ensuring a balance between fidelity and predictive accuracy. The model achieved an RMSE of 1.0265, indicating high accuracy within the typical range for urban temperature forecasting. This robust measure of error underscores the model’s precision in predicting temperature deviations, which is particularly relevant for urban planning and environmental management. The findings provide city planners and policymakers with valuable insights and tools for preempting adverse environmental impacts, marking a significant step towards operational efficiency and enhanced governance in future smart urban ecosystems. Future work may extend the model's applicability to broader geographical areas and incorporate additional environmental variables to refine predictive accuracy further.

Achieving and sustaining stability for economic growth remain the greatest and most immediate development challenge for Ethiopia. For natural resource-based economies especially maintaining stability and growth depends fundamentally upon climate change adaptation and mitigation. The close links between climate and Ethiopia’s economy are reflected by the strong relationship between GDP growth rate and rainfall variability. A study by the World Bank projects that unless steps to build resilience are effective, climate change will reduce Ethiopia’s GDP growth by between 0.5 and 2.5% each year. Along with the challenges posed by climate change, a number of development opportunities are emerging in response to climate change which includes access to international climate finance. The international response to climate change in the form of external development finance plays a key role to support developing countries in their transition to a low-carbon, climate-resilient and sustainable development pathway. Therefore, this study was conducted to assess the flow and the overall contribution of climate finance to sustainable development in Ethiopia. Specifically, focused on outlining how climate finance is currently reconciled in the existing Ethiopian climate change governance and its contribution to sustainable development. In order to achieve these objectives, data were collected from different sources. The Rio Marker methodology applied to review climate financial flow over the 5 year period. The result reveals that, climate change is central to development agendas despite its recent emergence in the mainstream, with various initiatives under way to combat or reduce its impacts in Ethiopia. In addition, the amount of climate finance from the developed countries to Ethiopia shows some fluctuation for the past five years. In general, the overall flow of climate finance mostly targeted climate adaptation actions which spur and enable the transition towards climate-resilient growth and sustainable development.

El Niño is warming of the sea surface temperature of the Pacific Ocean. Extreme flooding, drought, lack of potable water for livestock and domestic use, food insecurity and market imbalance are associated with El Niño and La Niña in Ethiopia. Drought following El Niño caused 50 to 90% crop failure, in the eastern parts of Ethiopia. El Niño episodes are detected using different statistical indices such as Oceanic Nino Index (ONI), Agricultural Stress Index System (ASIS) and the Southern Oscillation Index (SOI), with magnitude ranging from weak to strong. Identifying the El Niño and La Niña seasons it is very important to adopt suitable adaptation strategies, which can resolve and/or reduce the negative impacts. Early warning and immediate support to the impacted areas have been carried out to minimize risks from El Niño animal feed for livestock from other areas has been transported to the vulnerable areas. Planting early maturing and drought resistant crops, supplementary irrigation, early waning information on weather and climate have been exercised as climate change adaptation strategies, early warning mechanisms by the government of Ethiopia. El Niño and La Niña are natural phenomena; however, it is necessary to study the occurrence and distribution of El Niño and La Niña episodes to enable early warning and identify suitable adaptation strategies and policy implications in the country.

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease- and species-specific and contingent upon a multitude of factors. The field of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favourable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate to high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems, AI algorithms, and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.

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.

The coastal zone of the Valparaíso Region has been historically threatened by its natural and anthropogenic conditions, which demands efficient management for the adaptation and mitigation of the impacts that occur on the coast, especially in the face of the growing effects of climate change. As a contribution to decision makers in the development of strategic actions through adaptation plans, this study presents an approach to coastal vulnerability in the southern part of the region, applying the Coastal Vulnerability Index considering the variables geomorphology, coastal slope, changes in sea level, coastal erosion, tidal range, and wave height. The result illustrates a sectorization of the coast according to the degree of vulnerability, where the sectors formed by fine sandy beaches near river mouths and estuaries present greater risks to climatic events than those rocky stretches with medium-low cliffs.

Biogenic emission can have significant impact on atmospheric chemistry. Isoprene (C5H8) is known as the most predominant volatile organic compound and its emission is highly dependent on temperature and light (solar radiation). This study aims to investigate future changes of isoprene emission under climate change scenario. The Southeast Asia (SEA) region is home to 15% of the world’s tropical forest, and the biogenic emission from this region can have significant effect on the global climate chemistry. Three climate change scenarios (RCP4.5, RCP6.0 and RCP8.5) were used to drive climate change simulation in 2013 (baseline), 2030 (near-future), 2050 (mid-century), 2070 (post-mid) and 2100 (end of century) using the Weather Research Forecasting (WRF v3.9.1) model. The Model Emission of Gases and Aerosol from Nature (MEGAN v2.1) was then used to simulate isoprene fluxes using climate output datasets from the WRF model. This study highlights that the projected mean surface temperature and PAR (photosynthetic active radiation) were higher in July than in January. Towards the end of the century, the overall surface temperature and PAR over the SEA region is expected to increase by 0.9℃ - 2.1℃, and 7.6 W m-2 – 12 W m-2 under all RCPs. The all-time high isoprene emitters are Borneo and Papua Island. Meanwhile, the projected increment of isoprene emission over this region is between 10 – 14%, 15-30% and 29 – 53% for RCP4.5, RCP6.0 and RCP8.5, respectively. Our result concludes that the total isoprene emission was higher during July, consistent with the high surface temperature and PAR. The results also agreed with the hypothesis of high isoprene emission over the region that has oil palm plantation. Thus, challenges in dealing with future emissions of isoprene in SEA are closely tied to future climate policies to limit the warming of the atmosphere over this region and the land-use conversion of palm oil plantations.

The literature on contract farming and climate change in Zimbabwe has blind spots in relation to the study of contract farming as a climate change response. While the literature on contract farming and climate change abounds, such literature is lacking when it comes to the exploration of how contract farming can facilitate climate change coping and adaptation strategies by smallholder farmers. This paper fills this gap. It draws on in-depth interviews with 10 contracted and 10 non-contract farmers who were engaged through face-to-face in-depth interviews in the Chipinge South Constituency. It found that contract farming does not only boost productivity, but it also enables farmers to positively respond to the ravages of climate change, and therefore, it should be supported and encouraged. Future research should explore more viable and sustainable way through which the state, instead of private sector actors, should be at the centre of contract farming.

As climate change should lead to an increase in the vulnerability and the sensitivity of forests to extreme climatic events, quantifying and predicting their response to more severe droughts remains a key task for foresters. Furthermore, recent works have suggested that tree diversity may affect forest ecosystem functioning, including their response to extreme events. In this study we aimed at testing whether the growth response of forest stands to stressful climatic events varied between mixed and monospecific stands, under various environmental conditions. We focused on beech-fir forests (Fagus sylvatica [L.] and Abies alba [L.]) and beech-oak forests (Fagus sylvatica [L.] and Quercus pubescent [L.]) in the French Alps. We used a dendrochronological dataset sampled in forest plots organized by triplets (one mixture and two monospecific stands) distributed in six sites along a latitudinal gradient. We tested (1) whether stand diversity (two-species stands vs monospecific stands) modulates the stands’ response to drought events in terms of productivity, (2) whether species identity may drive the diversity effect on resistance and recovery, and (3) whether this can be explained by interspecific interactions. We found that (1) interspecific differences in response to extreme drought events (possibly due to interspecific differences in hydraulic characteristics) can induce a mixture effect on stand growth, although it appeared (2) to be strongly depending on species identity (positive effect only found for beech-fir mixed stands), while (3) there were no significant non-additive effects of diversity on stand resistance and recovery, except for some specific cases. Overall, our study shows that promoting selected mixed stands management may buffer extrem drought effect on stand productivity.

PirAB is a binary protein complex secreted by specific strains of Vibrio parahaemolyticus (Vp) that harbor the pVA1 virulence plasmid and express PirAVp and PirBVp toxins. PirABVp causes acute hepatopancreatic necrosis disease (AHPND), a newly emergent penaeid shrimp disease that can cause 70–100% mortality and has resulted in great economic losses since its appearance. The cy-totoxic effect of PirABVp on the epithelial cell of the shrimp hepatopancreas has been extensively reported. Our studies found that the PirBVp subunit has lectin activity and recognizes mucin-like O-glycosidic structures in the shrimp hepatopancreas. The PirAVp subunit may have a stabiliza-tion function of the binary complex. However, we also found that Vp AHPND changes the water microbiota community structure and causes a significant reduction in several bacteria, especially Neptuniibacter spp. We propose that the PirABvp toxin could exhibit a dual role: damage the shrimp hepatopancreas and kill surrounding bacteria.

Climate change plays a pivotal role in the hydrology of tributaries in the upper Blue Nile basin. This study was designed to reveal the extent to which climate change impacts on stream flow of the Gumara watershed under the Representative Concentration Pathway (RCP) climate change scenario. The study considered the RCP 2.6, RCP 4.5 and RCP 8.5 scenarios using the second generation Canadian Earth System Model (CanESM2). The Statistical Downscaling Model (SDSM) was used for calibration and projection of future climatic data of the study area. Soil and Water Assessment Tool (SWAT) model was used for simulation of the future stream flow of the watershed. Result showed that the average temperature will be increasing by 0.84oC, 2.6oC and 4.1oC in the end of this century under RCP 2.6, RCP 4.5 and RCP 8.5 scenarios respectively. The change in monthly rainfall amount showed a fluctuating trend in all scenarios but the overall annual rainfall amount is projected to increase by 8.6%, 5.2% and 7.3% in RCP 2.6, RCP 4.5, and RCP 8.5 respectively. Overall, this study revealed that, due to climate change, the stream flow of the watershed is found to be increasing by 4.06%, 3.26%, and 3.67% under RCP 2.6, RCP 4.5 and RCP 8.5 scenarios respectively.

The present paper aims to elucidate the impact of climate change on the availability and security of water and energy in the Middle East and North Africa Region (MENA Region). The region is particularly challenged by a number of factors including a large variability of bio-geographical characteristics, extreme population growth over the last few decades and substantial societal and economical transitions as well as armed conflicts in some of the countries of the region. Anticipated changes in climate conditions will exacerbate the challenges with regard to providing sufficient amounts of water and energy to the communities in the region. Impacts of climate change will materialize as an increasing number of heat waves, primarily in urban structures and the decline in water availability as a result of enhanced droughts and a growing numbers of dry spells. The interrelationships between energy and water and their mutual dependencies are addressed by the Water-Energy-Nexus concept. With regard to the challenges addressed here, Cyprus and the Eastern Mediterranean are a particular point in case. Mitigation and adaptation strategies include enhanced efficiency of energy and water use, integrated technology assessments regarding electricity generation and the production of potable water and electricity through concentrated solar power.

To bring to the fore the aim of this research, effects of fluctuating temperature, was measured against food and nutrition security in the region using food production index, and undernourished population growth rate as proxies; controlled over share of arable land, irrigation, population and labour share for agriculture. Dynamic panel of generalized method of moments (GMM) was adopted, the period 2000 to 2016 were considered and 29 countries in sub-Sahara Africa were selected within the empirical framework of global water balance as mentioned by Rai and Singh (2012). Findings from the study reveals that the short run effect of temperature increase in degrees pose at least -3.1% negative and significant impact effects on the food production while the long run elasticity hits -7.5% and the controlled effect on arable land revealed a positive impact on the food production to the tune of 3.9%. Contrarily, arable land expansion reduces the under nourished population by -8.55%. Population increase on the other hand increases undernourished population in the region to the tune of 11.95%. The study therefore recommended expansion in the arable land and encourages population control policy in order to negate the undesired effects of temperature on food and nutritional security.

Available water resources in the Middle East, as one of the most water-scarce regions of the world, have undergone extra pressure due to climatic change, population growth, and economic development during the past decades. The objective of this study is to detect the trends and quantify the changes in aridity with respect to precipitation and potential evapotranspiration in 20 countries of the Middle East and the adjacent area. A Pixel-wised trend analysis was conducted on precipitation, potential evapotranspiration, and aridity index for 71 years from 1948 to 2018. A nonparametric Mann-Kendall test was used over 14106 points in the study area to detect the trends at monthly and annual time scales. Results showed statistically significant (|Z| >1.96) upward trends in aridity (a downward trend in aridity index) up to 96 percent from December through September in most parts of the region. Aridity in October and November had a downward tendency in most parts of the study area. At the annual time scale, 62.5 percent of the statistically significant trends in aridity were found to be upward (up to 96 percent increase in aridity) due to the combined effects of the decrease in precipitation and the increase in potential evapotranspiration and 37.5 percent of the detected trends were downward (up to 61 percent decrease in aridity). The highest and the lowest trends in aridity were found in the north of Sudan (96 percent increase in aridity) and Eastern Arabia (61 percent decrease in aridity), respectively.

The aim of this study was to evaluate the acceptability and feasibility of a theory-derived sedentary workplace intervention (single arm, pre-post design) for police office staff. Twenty-four staff participated in an 8-week intervention incorporating an education session, team competition with quick response (QR) codes, team trophy, and weekly leaderboard newsletters, a self-monitoring phone app, and electronic prompt tools. The intervention supported participants to reduce and break up their sitting time with three minutes of incidental movement every 30 minutes at work. Feasibility and acceptability were assessed using mixed methods via the RE-AIM QuEST and PRECIS-2 frameworks. The intervention was highly pragmatic in terms of eligibility, organisation, adherence, outcome, and analysis. It was slightly less pragmatic on recruitment and setting. Delivery and follow-up were more explanatory. Reach and adoption indicators demonstrated feasibility among police staff, across a range of departments, who were demographically similar to participants in previous office-based multi-component interventions. The intervention was delivered mostly as planned with minor deviations from protocol (Implementation fidelity). Participants perceived the intervention components as highly acceptable. Preliminary results showed improvements in workplace sitting and standing, as well as small improvements in weight and positive affect. Evaluation of the intervention in a fully powered randomised controlled trial to assess behaviour and health outcomes is recommended.

The effects of climate change are already being felt around the world; however, data on its socio-economic impacts in regions such as the Amazon are still insufficient. Thus, this article aims to reveal the socio-environmental vulnerability of riverine communities to climate change through an analysis carried out in the middle Juruá region, Brazil, focusing on the loss of agricultural production that occurred after the extreme flooding in 2021. Data were collected through semi-structured questionnaires with the participation of 638 agro-extractivists from traditional riverine communities in the municipality of Carauari in the Brazilian Amazon, as well as the collection of documentary information and field visits to quantify and qualify the damage caused by the flood. The loss of agricultural production in the territory exceeded the value of US$ 1,300,000 with greater losses in the production of cassava flour, an essential food for the riverine communities. Production chains of non-timber products, such as the case of rubber tapping and the harvesting of oilseeds, were also directly impacted. The damages caused by climate change to the Amazonian riverine sociological systems are already being experienced by the traditional communities of the middle Juruá region. Governments need to assist these populations in building adaptive measures and strengthening local resilience.

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

In recent years, there has been an intensification of weather variability worldwide as a result of climate change. Some regions have been affected by drought, while others have experienced more intense rainfall. The incidence and severity of mouldy grain and mycotoxin contamination during the growing and harvesting seasons have increased as a result of these weather conditions. Addi-tionally, torrential rains and wet conditions may cause delays in grain drying, leading to mold growth in the field. In July 2023, a wheat field in Lecco (Lombardy, Italy) was affected by torren-tial rains that led to the development of the Claviceps fungi. In the field, dark sclerotia were identi-fied on some ears. Wheat ears, kernels and sclerotia were collected and analyzed by LC-MS/MS at IZSLER, Food Chemical Department, in Bologna. The wheat ears, kernels and sclerotia were ana-lyzed for 12 ergot alkaloids (EAs) according to (EU) Regulation 2023/915 (er-gocornine/ergocorninine; ergocristine/ergocristinine; ergocryptine/ergocryptinine; ergome-trine/ergometrinine; ergosine/ergosinine; ergotamine/ergotaminine), after QuEChERS (Z-Sep/C18) purification. The analyzed sclerotia showed significant differences in total alkaloids content that varies between 0.01-0.5% (w/w), according to the results of 2017 EFSA scientific report. EAs de-tected in sclerotia were up to 4951 mg/kg, in wheat ears up to 33 mg/kg, and in kernels were 1 mg/kg. Additional mycotoxins including ochratoxin A, deoxynivalenol, zearalenone, fumonisins, T2-HT2 toxins, and aflatoxins were investigated in wheat kernels, after purification with immu-noaffinity columns (IAC). The analysis revealed the presence of deoxynivalenol in wheat kernels at a concentration of 2251 µg/kg. It is expected that climate change will increase the frequency of extreme weather events. In order to mitigate the potential risks associated with mycotox-in-producing fungi and to ensure the protection of human health, it is suggested to implement of-ficial controls in the field.

This study investigated the effects of two plyometric training protocols on sprint and change of direction (COD) performance in elite hockey players. A parallel-group randomized controlled trial design was used and seventeen elite male and female field hockey players were randomly allocated into either low-to-high (L-H, n = 8) or high-to-low (H-L, n = 9) training groups. Each group performed separate variations of the drop jump exercise twice weekly for six weeks, with an emphasis on either jump height (L-H) or drop height (H-L). Performance variables assessed included sprint times over 10 m and 20 m, as well as 505 time. A two-way repeated measures analysis of variance was performed and Cohen’s d effect sizes were calculated. The H-L group displayed significant small ES improvement from baseline to post-training in the 10 m sprint (1.893 ± 0.08 s pre vs 1.851 ± 0.06 s post) (ES = −0.44) (P = <0.05). Small but not statistically significant differences between groups were observed for 10 m and 20 m sprint performance, and no significant differences were observed within or between groups for 505 time. These findings highlight the difficulty in substantially enhancing speed and COD ability in highly trained athletic populations through the addition of a low volume, short duration plyometric training protocol.

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

Background: Pressure ulcers (PU) affect millions of people worldwide and always occur over bony areas of the body where pressure and tissue distortion is greatest. The national pooled prevalence of pressure ulcer remains unknown. Hence, the aim of this meta-analysis was to determine the effect of position change on pressure ulcer among hospitalized clients in Ethiopia. Methods: Studies were retrieved through search engines in PubMed, Scopus, WHO afro library, Google Scholar, Africa journal online, PsycINFO and web-science following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Analysis was done using STATA version 14 software. We checked the between-study heterogeneity using the I² and examined a potential publication bias by visual inspection of the funnel plot and Egger’s regression test statistic. The random-effect model was fitted to estimate the summary effects, odds ratios (ORs), and 95% confidence interval (CIs) across studies. Results: Out of the reviewing 401 studies, 7 studies fulfilled the inclusion criteria and were included in the meta-analysis. The estimated pooled prevalence of pressure ulcer in Ethiopia was 11.7% (95% CI (7.28, 16.13%)). Based on the subgroup analysis, the estimated magnitude of pressure ulcer was 15.89% (95% CI: 35.34, 54.04) among studies their sample size were greater than or equals to 250. Those clients who have position change during hospitalization were 85% less likely to develop pressure ulcer [(OR 0.15, 95%CI (0.06, 0.4)] than their counter part. Conclusion: The overall prevalence of pressure ulcer in Ethiopia was relatively high. Position change of the client during hospitalization had paramount benefit to reduce the burden of pressure ulcer. Therefore, policymakers could give special attention to minimize the magnitude of pressure ulcer in order to improve the overall quality of healthcare service. Further meta-analysis study is need to identify individual and health care service related factors to the occurrence of pressure ulcer.

Wildfires are a rising environmental threat which health impact remains poorly documented, in particular beyond the fire period. This ecological study investigates changes in health conditions before, during, and after two consecutive wildfires that occurred in France´s Gironde district in the summer 2022. Electronic records from the district´s emergency medical communication centre were used to identify calls with respiratory and cardiovascular diseases, and two specific subgroups of those, asthma (all ages and 0-5 years) and cardiac arrest, respectively. Compared to before the fires, respiratory disease cases were fewer during each fire (OR = 0.85, 95% CI: 0.79, 0.90 and OR = 0.62, 95% CI: 0.58, 0.67, respectively), cardiovascular disease cases, more common during the second fire, and asthma cases, higher following the fires (ORall ages= 1.85, 95% CI: 1.56, 2.21 and ORchildren= 3.52, 95% CI: 2.62, 4.80). Asthma cases also rose during the same calendar time in 2021, but to a lesser extent. In sum, except for asthma, emergency calls data in Gironde reveal few significant potentially smoke-related symptoms around fire periods, apart from post-fire asthma. Whether the effects are smoke- or season-related remains to be determined, preferably using additional data sources.

: Kentucky is one of the largest coal producing states and surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas and vegetation change and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age, mining percentage, reclaimed forest percentage, and reclaimed woods percentage) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n=9), summer (n=14), and fall (n=58) 2017 to study changes in water quality variables (SO42-, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+,Fe3+) in response to changes in land cover. Pearson correlation analyses indicated conductivity has strong to very strong relationships with other variables of water quality variables related to coal mining (except Al3+, Fe2+,Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate multivariate regression analyses were performed with conductivity values based on samples collected in the fall. First, conductivity response to mining percentage, reclamation age and topographic variables were examined (adjusted R2=0.818, p &lt; 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p &lt; 0.01). Finally, reclamation age and mining percentage were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p &lt; 0.01) with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal Mine Related Stream Chemistry in areas where agriculture and urban development are limited. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining as well as refining land reclamation practices.

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

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

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

Land includes vegetation and water bodies and provides the basis for human livelihoods through primary production, the supply of food, freshwater, and multiple other ecosystem goods and services. The last three decades have recorded frequent drought events as well as rapid population growth, which has resulted in often negative land use and land cover change (LULCC) in the Sahel of Sub-Saharan Africa. In order to propose sustainable land management strategies, it is important to investigate the rate of LULCC and its driving factors in specific locations. This study investigated the case of Wocoro municipality in Mali using a combined approach of remote sensing, Geographical Information System, and focus group discussions. Satellite images and local people's perceptions on LULCC and drivers were collected and analyzed for the years 1990, 2000, 2010, and 2020. We found that the study area faced a severe decrease in wooded savannah with an increase in farmland and settlement directly or indirectly related to the rapid population growth, high cotton price (which encouraged cropland expansion), drought, firewood extraction, and charcoal production, which was exacerbated by poverty. There is a need to promote integrated land management strategies that consider current and future livelihoods needs and preserve the health of the environment for the benefits of future generations.

This study utilizes a combination of optical PlanetScope imagery and Synthetic Aperture Radar (SAR) data from Sentinel-1 to investigate land cover changes in Dili, Timor-Leste, following Tropical Cyclone Seroja. The primary objective is to evaluate how integrating these datasets enhances disaster monitoring and response in flood-affected areas. The Random Forest classifier, known for its robustness in handling high-dimensional and noisy data, was applied to classify land cover into six distinct classes: vegetation, water, built-up areas, bare soil, clouds, and shadows. The classification was performed across three phases—pre-disaster, post-disaster, and recovery—using Google Earth Engine (GEE). Binary segmentation using Otsu thresholding was applied to the SAR images to refine the classification by delineating water bodies from non-water areas. The study achieved high classification accuracy, with overall accuracy ranging from 97.2% to 98.7%, and the Kappa index, which measures agreement between classified and reference data, remained consistently strong, indicating reliable model performance. Key results include a significant increase in water bodies and extensive damage to vegetation and built-up areas during the post-disaster phase, followed by partial recovery in the subsequent period. Despite the high accuracy, urban areas posed classification challenges due to misclassification between built-up and bare soil categories. This research offers a methodological framework for integrating optical and SAR data with machine learning for land cover change detection in post-disaster scenarios. The societal benefits of this study include improved disaster preparedness, enhanced recovery planning, and valuable insights into flood impact mitigation in regions like Timor-Leste, where technical and data limitations persist.

Climate change represents a prevalent challenge confronted by humanity, and with cities being one of the regions most heavily impacted by such change, enhancing their climate resilience is paramount in adapting to and mitigating the associated risks and losses. This article evaluates the climate resilience of 270 major cities in China by creating an urban climate resilience indicator system centered on exposure, vulnerability, and resilience. The article analyses the spatial and temporal evolution trend of climate resilience in Chinese cities, as well as the source of regional differences using Kernel density analysis and the Dagum Gini coefficient decomposition. The article then explores the influence of financial investments on urban climate resilience, considering the moderating effect of urbanization rate.

The paper will analyze the pressures and vulnerabilities of the consolidated city from two perspectives: technical and social. Some design and pragmatic experiences conducted by the author in his teaching and research experience first at the Department of Urbanism of TUDelft in the Netherlands and currently at the PDTA Department of La Sapienza University of Rome will be introduced and analyzed. In the first research activity, whose case study is Rotterdam, all urban vulnerabilities related to climate change will be analyzed while in the second one, conducted in Viterbo, the vulnerability related to the hull of social inclusion, poor accessibility and psycho-social stress that plague our established cities will be treated. The two areas of study, different in size and spatial governance tools, are comparable because they allow deciphering the city's risks through lines of intervention that could serve as best practices and serve the urban planning disciplinary update also allowing to define a reflection on morphology and fabrics and on the shape of the city itself. Both teaching and research activities in which the author is involved allow the topic of urban vulnerability to be addressed with a broad exploratory scope that, in the final stage, hypothesizes design intervention on the neighborhood scale, identified as the most appropriate to provide plausible climate and social adaptation and mitigation responses.

The once near-extinct Russell’s viper has recently come back to the area beyond its historical range. A couple of decades ago, its distribution was confined to 11 districts of Bangladesh. Hence, the study aims to update the distributional map of Russell’s Viper (Daboia russelii) across the country and find out the surges' causal factors. Both primary and secondary data were utilized in this study. It revealed that the distributional range of this snake was expanded from 22 to 33 districts in 2024. The respondents noted that climatic stressors like high humidity accompanied by hot weather, increased salinity, and increased frequency of flooding facilitated the spreading of the viper across the country. The cropping pattern and crop diversification were another major contributing factor. The shifting of the single-cropped area to a multi-cropped area in the Barind tract increased its main prey rats. Contrarily, the killing of natural predators such as foxes, monitor lizards and mongoose led to the rise in the snake population. The destruction of vegetation coverage in the upper part of the Padma Basin facilitated the movement of Russell's vipers downstream.

In the case of indigenous grapevine varieties, the aim of clonal selection is twofold: to improve their technological cultivation problem while preserving the varietal character. As the sensitivity of perennial crops to climate change becomes more pronounced, clonal selection, which is already very time-consuming for perennial woody crops, may take even longer. In Badacsony, clonal selection breeding of the ‘Kéknyelű’ and ‘Juhfark’ varieties was started in the early 2000s. The problem mentioned above in cultivation technology is the poor fertility of ‘Kéknyelű’ (functionally female-flowered variety), while in the case of ‘Juhfark’ the high susceptibility to grey rot (Botrytis). Based on 11 years of data significant difference in yield between clone B.2. and the base variety was found. In this comparison the year clusters also gave different values, as in years belonging to cluster 1 the ’Kéknyelű’ yielded more than in another year. Both clones of ‘Kéknyelű’ matured with significantly lower pH compared to the base variety. ‘Kéknyelű' is renowned for the distinctive variety character of its wine, which is said to be acidic. Given the acidic nature of ‘Kéknyelű’ wine and the expected increase in must degrees and pH due to climate change, these distinctions may be beneficial in the future. Daily meteorological parameters were also recorded in the years under study, and different indexes were calculated for both of varieties for different phenological periods. The years were classified into 3 clusters and the harvest data were analyzed within each cluster. In the case of 'Kéknyelű' our results revealed significant differences in yield between vintage clusters for clone B.2. However, clone B.1 demonstrated distinct KMW and pH values. Both 'Kéknyelű’ clones have produced a substantially higher incidence of Botrytis infection in cluster 2 years than in cluster 3 years. Botrytis infection only showed statistically significant differences between year clusters for ‘Juhfark’. It is intriguing that in most years, the rotting rate was lower in both clones, especially in year clusters 1 and 3 when the overall rate of Botrytis infection was quite low. Our results highlighted the year-round sensitivity of the two varieties studied and the difficulties of clonal selection.

Multi-cropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to increasing drought periods. For this reason, single maize crops with inter-row mellowing and weed-mulching practices were compared with faba bean, crimson and Persian clover, and alfalfa intercropped maize cultivations. Tests were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Results showed that by the 30% higher energy inputs were calculated in technologies with intercropped crimson, Persian clover, and alfalfa than in monocropped maize. Single maize crops produced by the 23-40% higher biomass yields compare to clover and alfalfa intercropped maize because, due to the drought periods, intercrops weakly sprouted and developed. Lower harvests reduced the energy output by up to 38%, energy efficiency ratio - by up to 2.5 times and net energy - by up to 42%. All tested technologies were environmentally friendly and similar according to the CO2 equivalent. Long-term drought periods during vegetative season due to climate change make us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could solve the problem of its germination but highlight the problem of abundant weed spread. Therefore, this takes us to another sphere of agrotechnologies - the effective non-chemical weed control.

Aflatoxins (AFs) contamination of cereals is considered one of the greatest food safety concerns worldwide. Occurrence of AFs in maize, wheat, rice and sorghum is highly prevalent with each commodity accounting for more than 10% of world’s AF exposure. Their occurrence as food contaminants is also associated with huge economic losses. AFs are highly stable compounds that cannot be eliminated by regular processing of grains. Hence, prevention of AFs in food and feed is now considered more important than the subsequent interventions to mitigate the deleterious health effects of AFs in human and animals. However, the development of an effective preventive strategy hinges on a clear understanding of the underlying factors influencing AFs production. Therefore, the present review aims to highlight the most significant factors influencing AFs contamination of cereals at pre-and post-harvest stages. This is crucial for effective monitoring of critical control points and optimisation of preventive strategies in food and feed supply chains. Several intrinsic and extrinsic factors have been reported of which nutritional composition, environmental factors (temperature, water activity and relative humidity) and climate change have been identified as primary factors, while pH of the substrate, carbon dioxide (CO2) levels in the gaseous environment, and agronomic and socioeconomic status are the main secondary factors promoting AFs biosynthesis in cereals. Additionally, an overview of global occurrence of AFs in cereals, with their health impacts and various preventive measures have also been highlighted.