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.

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement was supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often characterized by an underlying climate gradient, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated variability. To solve this limitation, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial patern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern. Both calibrations reached comparable performance of Q. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

The amplified Arctic warming is one of several factors influencing atmospheric dynamics. In this work, we consider a series of numerical experiments to identify the direct role of the Arctic sea ice reduction process in forming climatic trends in the northern hemisphere. Aimed at this, we used two more or less independent mechanisms of ice reduction. The first is traditionally associated with increasing the concentration of carbon dioxide in the atmosphere from the historic level of 360 ppm to 450 ppm and 600 ppm. This growth increases air temperature and decreases the ice volume. The second mechanism is associated with a reduction in the reflectivity of ice and snow. We assume that comparing the results of these two experiments allows us to judge the direct role of ice reduction. The most prominent consequences of ice reduction, as a result, were the weakening of temperature gradient at the tropopause level in mid-latitudes, the slower zonal wind at 50-60∘N, intensification of wave activity in Europe, Western America, and Chukotka, and its weakening in the south of Siberia and Kazakhstan. We also consider how climate change may alter regimes such as blocking and stationary Rossby waves. The study used the INM-CM48 climate system model .

This study investigated the influence of land-use and precipitation change and variability on Lake Victoria’s water-level fluctuations. Extreme precipitation events, corresponding to extreme water-levels, over the lake and its catchment area were identified and their return periods estimated by fitting them into a generalized extreme value (GEV) distribution. Using general circulation models from the 6^th phase of the Coupled Model Intercomparison Project (CMIP6)’s Detection & Attribution Model Intercomparison Project (DAMIP), an assessment of the potential contribution of human-induced climate change on the observed precipitation patterns over the study area was done. The greatest precipitation anomalies for the period 1900-2020 were recorded in 1961’s October-December (OND) season and 2019’s June-August (JJA) and OND seasons, corresponding to the period when the highest water-levels were recorded in Lake Victoria. While land-use change in the study domain was observed, extended and unusually heavy June to December 2019 precipitation bore the greatest responsibility for the 2019/2020 high water-levels in Lake Victoria. The OND precipitation event of 2019 was a 1-in-52-year event compared to the 1961’s 1-in-693 years. Differences in return periods at various parts of the lake imply a high spatial climate variability within the lake itself. An analysis of the fraction of attributable risk (FAR) showed natural variability to have a greater influence on the JJA and OND precipitation patterns over Lake Victoria than human-induced climate change. However, variability over the land area of the study domain was mainly driven by human-induced climate change rather than natural variability, implying a unique climate system over Lake Victoria. Findings from the current study enhance the understanding of Lake Victoria’s water budget and motivate for further research to inform effective strategies on the planning and use of Lake Victoria’s water resources in a changing climate.

Climate change is one of the biggest challenges of our times. Its impact on human populations is not yet completely understood. Many studies have focused on single aspects with contradictory observations. However, climate change is a complex phoenomenon that cannot be adequately addressed from a single discipline's perspective. Hence, we propose a comprehensive conceptual framework on the relationships between climate change and human responses. This framework includes biological, psychological and behavioural aspects, and provides a multidisciplinary overview and critical information for focused interventions. The role of tipping points and regime shifts is explored, and a historical perspective is presented to describe the relationship between climate evolution and socio-cultural crisis. Vulnerability, resilience and adaptation are analyzed from an individual and a community point of view. Finally, emergent behaviours and mass effect phenomena are examined that account for mental maladjustment and conflicts.

While the ongoing climate change is well documented, the impacts exhibit a substantial variability, both in direction and magnitude, visible even at regional and local scales. However, the knowledge of regional impacts is crucial for the design of mitigation and adaptation measures, particularly when changes in the hydrological cycle are concerned. In this paper we present hydro-meteorological trends based on observations from a hydrological research basin in Eastern Austria between 1979-2019. The analysed state variables include the air temperature, the precipitation, and the catchment runoff. Additionally, trends for the catchment evapotranspiration were derived. The analysis shows that while the mean annual temperature was decreasing and annual temperature minima remained constant, the annual maxima were rising. The long-term trends indicate a shift of precipitation to the summer with minor variations observed for the remaining seasons and at an annual scale. Observed precipitation intensities mainly increased in spring and summer between 1979-2019. The catchment evapotranspiration, computed based on catchment precipitation and outflow, showed an increasing trend for the observed time period.

Tree decline resulting from climate change results in physiological weaknesses, attack by harmful pests and pathogen, and threatens forest ecosystem stability. In the work described here, the effects of drought on wood density, tree ring width, and variations in vessel morphology were investigated in Persian oak (Quercus brantii) in the forests of the Zagros Mountains, Ilam province, western Iran. Radial discs were cut from trunks of declined and healthy trees and wood blocks cut radially from the sapwood, heartwood, and juvenile core. Observations were made on transverse sections from the blocks using microscopy. In trees with decline symptoms, wood density was greater than the healthy trees. Furthermore, declining trees had the narrowest ring width, reduced vessel diameter, vessel area, and highest number of vessels and tylose in pith towards bark. It was concluded that changes in anatomical features are associated with the weakening of the trees and are components in declining tree health.

Dendroclimatology has gained relevance during the XXI century. We analyze the state of-the-art of dendroclimatology in Latin America during the past 28 years (1990 to 2019), identifying the current state and recent advances in the application of dendroclimatology in this region. We carried out a systematic review in ScienceDirect, Web of Science, and Scopus databases using Boolean operators to logically connect the keywords “dendrochronology,” “dendroclimatology,” “trend,” “climatic variability,” and “climatic variability trend”, for each country. Dendroclimatological research conducted in the region focused on climatic reconstruction and the evaluation of new tree species with dendrochronological potential, which increase in 2010, then there was a gap between 1995 and 1996, later increase to present. Dendroclimatological studies in Latin America have been mainly developed in temperate climate zones (82.4 %) followed by tropical or subtropical areas (17.6 %). Dendroclimatological research in Latin America has provided advances in the study of climate variability by defining response functions of tree rings to climate. The generated information allows for a better understanding of the spatial and temporal dynamics of climatic variability and about its effects on ecosystems and society. We also call for increased dendroclimatological research based on subtropical and tropical forests limited studied until today.

Small Shallow Lakes (SSL) support exceptionally high and original biodiversity, providing numerous ecosystem services. Their small size makes them especially sensitive to anthropic activities, that causes a shift to dysfunctional turbid states and induces loss of services and biodiversity. In this study we investigated the relationships between environmental factors and macrophyte communities. Macrophytes play a crucial role in maintaining functional clear states. Better understanding factors determining the composition and richness of aquatic plant communities in least-impacted conditions may be useful to protect them. We inventoried macrophyte communities and collected chemical, climatic and morphological data from 89 least-impacted SSL widely distributed in France. SSL were sampled across four climatic ecoregions, various geologies and elevations. Hierarchical cluster analysis showed a clear separation of four macrophyte assemblages strongly associated with mineralisation. Determinant factors identified by db-RDA analysis are, in order of importance, geology, distance from source (DIS, a proxy for connectivity with river hydrosystems), surface area, climate and hydroperiod (water permanency). Surprisingly, at country-wide scale, climate and hydroperiod filter macrophyte composition weakly. Geology and DIS are the major determinants of community composition, whereas surface area determines floristic richness. DIS is identified as determinant in freshwater lentic ecosystems for the first time.

Plans are currently being drafted for the next decade of action on biodiversity – both the post-2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) and Biodiversity Strategy of the European Union (EU). Freshwater biodiversity is disproportionately threatened and under-prioritized relative to the marine and terrestrial biota, despite supporting a richness of species and ecosystems with their own intrinsic value and providing multiple essential ecosystem services. Future policies and strategies must have a greater focus on the unique ecology of freshwater life and its multiple threats, and now is a critical time to reflect on how this may be achieved. We identify priority topics including environmental flows, water quality, invasive species, integrated water resources management, strategic conservation planning, and emerging technologies for freshwater ecosystem monitoring. We synthesize these topics with decades of first-hand experience and recent literature into 14 special recommendations for global freshwater biodiversity conservation based on the successes and setbacks of European policy, management and research. Applying and following these recommendations will inform and enhance the ability of global and European post-2020 biodiversity agreements to halt and reverse the rapid global decline of freshwater biodiversity.

There is accumulating evidence that prenatal exposure to air pollution disturbs fetal growth and development, but little is known about these effects in cold climates or their season-specific or joint effects. Our objective was to assess independent and joint effects of prenatal exposure to specific air pollutants on the risk of low birth weight (LBW). We utilized the 2568 children of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo. We conducted stratified analyses for births during warm and cold seasons separately. We analyzed the effect estimates using multi-pollutant Poisson regression models with risk ratio (RR) as the measure of effect. The risk of LBW was related to exposure to CO and (adjusted RR 1.44, 95% CI: 1.04-2.00) and exposure to O3 in the spring-summer season (1.82, 1.11-2.96). There was also evidence of synergistic effects between CO and O3 (relative risk due to interaction, RERI, all year 1.08, 95% CI: 0.27-4.94, spring-summer 3.97, 2.17-25.85) and PM2.5 and O3 (all year 0.72, -0.07-3.60, spring-summer 2.80, 1.36-19.88). We present new evidence of both independent and joint effects of prenatal exposure in a cold climate on the risk of LBW at low levels of air pollution.

The building sector accounts for nearly 40% of total primary energy consumption in the U.S. and E.U. and 20% of worldwide delivered energy consumption. Climate projections predict an increase of average annual temperatures between 1.1-5.4°C by 2100. As urbanization is expected to continue increasing at a rapid pace, the energy consumption of buildings is likely to play a pivotal role in the overall energy budget. In this study we used EnergyPlus building energy models to estimate the future energy demands of commercial buildings in Salt Lake County, Utah, USA, using locally-derived climate projections. We found significant variability in the energy demand profiles when simulating the study buildings under different climate scenarios, based on the energy standard the building was designed to meet, with reductions ranging from 10% to 60% in natural gas consumption for heating and increases ranging from 10% to 30% in electricity consumption for cooling. A case study, using projected 2040 building stock, showed a weighted average decrease in heating energy of 25% and an increase of 15% in cooling energy. We also found that building standards between ASHRAE 90.1-2004 and 90.1-2016 play a comparatively smaller role than variation in climate scenarios on the energy demand variability within building types. Our findings underscore the large range of potential future building energy consumption which depend on climatic conditions, as well as building types and standards.

Dengue hemorrhagic fever is an arboviral infectious disease that has occurred frequently as an extraordinary event due to its fast spread and lethal potential in Indonesia. The vector Aedes aegypti is sensitive to climate variability. This study determines the relationship between climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia from 2009 to 2017. This study used the monthly dengue hemorrhagic fever incidence obtained from the Surabaya Health Office and the monthly climate variability parameters (average temperature, rainfall, humidity) obtained from the Indonesian Agency for Meteorology, Climatology and Geophysics and website www.worldweatheronline.com. Data analysis was done using One-Sample Kolmogorov Smirnov Test and Spearman non-parametric correlation test. The results showed a correlation between all three climate variability parameters with dengue hemorrhagic fever incidence (average temperature p<0.05, r=-0.603; rainfall p<0.05, r=0.407; humidity p<0.05, r=0.7). Average temperature is negatively correlated to dengue hemorrhagic fever incidence, while rainfall and humidity are positively correlated to dengue hemorrhagic fever incidence. This study shows preliminary evidence on the correlation of climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia.

Dengue hemorrhagic fever is an arboviral infectious disease that has occurred frequently as an extraordinary event due to its fast spread and lethal potential in Indonesia. The vector Aedes aegypti is sensitive to climate variability. This study determines the relationship between climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia from 2009 to 2017. This study used the monthly dengue hemorrhagic fever incidence obtained from the Surabaya Health Office and the monthly climate variability parameters (average temperature, rainfall, humidity) obtained from the Indonesian Agency for Meteorology, Climatology and Geophysics and website www.worldweatheronline.com. Data analysis was done using One-Sample Kolmogorov Smirnov Test and Spearman non-parametric correlation test. The results showed a correlation between all three climate variability parameters with dengue hemorrhagic fever incidence (average temperature p<0.05, r=-0.603; rainfall p<0.05, r=0.407; humidity p<0.05, r=0.7). Average temperature is negatively correlated to dengue hemorrhagic fever incidence, while rainfall and humidity are positively correlated to dengue hemorrhagic fever incidence. This study shows preliminary evidence on the correlation of climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia.

Solar radiation is closely related to the energy buildings consume for cooling, heating, and lighting purposes. Glazing is the only material of the building envelope that transmits solar radiation and needs to be appropriately designed to reduce energy cㅈonsumption. Currently, smart glass technology is being actively investigated and developed for effective solar radiation control. Among the various types of smart glass, electrochromic glazing is one of the most promising technologies, as it can adjust transmittance on its own, has a wider transmittance range in both the clear and darkened states, and consumes less electricity. Considering the importance of solar radiation adjustment in electrochromic glazing technology, this study attempted to develop an optimal control method for electrochromic glazing. Toward this goal, the solar radiation incident on vertical surfaces and outdoor temperature conditions were controlled in three regions with different climatic characteristics, and the annual cooling, heating, and lighting loads, discomfort glare, and interior illumination were analyzed. This approach enabled the optimal conditions with respect to visual comfort to be determined. Subsequently, the EDPI (Energy and daylight performance index) was used to optimize control conditions for each region, thereby producing integrated evaluations from results with different units and properties. The proposed control method will be utilized to develop a control algorithm and a control system to reduce building energy consumption.

The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015-2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements in MERRA-2 reanalyses and the full revisit capacity of Sentinel-2.

Water scarcity is significantly increasing water stress in Africa and some parts of the world. This is due to human induced factors such as climate change, increase of human population that raises demand which outstrips food availability, and put great changes of land use which results in changes of hydrological mechanics and water availability as whole. The investigation was through literature review and it tries to examine the criticality of water scarcity in Africa regions, and the major factors that mastermind this menace. Also possible strategies that can be promptly used to manage water scarcity at domestic level and in agriculture are described in this paper, not with standing the fact that agriculture sectors in Africa and the rest of the world remain the utmost vulnerable enterprise to water scarcity and withdrawal on the planet earth.

Rain-fed maize production has significantly declined in Zimbabwe especially in semi-arid and arid areas causing food insecurity. Erratic rainfall received associated with mid-season dry spells largely contribute to low and variable maize yields. This study involved a survey of current farmers’ cropping practices, analyses of climatic data (daily rainfall and daily minimum and maximum temperature) of Hwedza station and simulation of maize yield response to climate change using DSSAT CERES crop growth simulation model. The climatic and maize yield data was analysed using mean correlation and regression analyses to establish relationships between rainfall characteristics and maize yield in the study area. Survey results showed that maize was the staple food grown by 100% of the farming households while 8.7% also grew sorghum. The survey concludes that 56.2% of the farmers grew short season varieties, 40.2% medium season varieties and 3.6% long season varieties. The result of the correlation analysis of climatic data and maize yield showed that number of rain days had strong positive relationship (r = 0.7) with maize yield. Non-significant yield differences (p > 0.05) between maize cultivar and planting date criteria were obtained. Highest yields were obtained under the combination of medium season maize cultivar and the DEPTH criterion in all simulations. The range of simulated district average yields of 0.4 t/ha to 1.8 t/ha formed the basis for the development of an operational decision support tool (cropping calendar).

El Niño Southern Oscillation (ENSO) is an important of mode of climatic variability that through altering climate patterns exerts a discernible impact on ecosystems and society. For this reason, ENSO has attracted much interest in the climate and health science community with many analysts investigating ENSO health links through considering the degree of dependency of the incidence of a range of climate diseases on the occurrence of El Niño events. Because of the mounting interest in the relationship between ENSO as a major mode of climatic variability and health this paper presents an overview of the basic characteristics of the ENSO phenomenon and its climate impacts, discusses the use of ENSO indices in climate and health research and outlines the present understanding of ENSO health associations. Also touched upon are ENSO-based seasonal health forecasting and the possible impacts of climate change on ENSO and the implications this holds for future assessments of ENSO health associations. The review concludes that there is still some way to go before a thorough understanding of the association between ENSO and health is achieved with a need to move beyond analyses undertaken through a purely statistical lens with due acknowledgement that ENSO as a complex non-canonical phenomenon and that simple ENSO health associations should not be expected.

Despite the ecological importance of forest tree species, our study was motivated by scarce data on dendrochronology studies limited to the northwestern part of Tajikistan due to lack of access to such a part of the country which is difficult to access. Current studies on Junipers in the northwestern part of Tajikistan identified that tree ring-based climate reconstruction is possible. Cores of Juniperus Turkestanica from Taboshar area, Sogd province were developed into 176-year tree-ring width chronology. In the current study a summer (June-September) minimum temperature reconstruction spanning AD 1840–2016 was developed, which can explain 30.0% of the instrumental variableness for the period of 1940–2015. Five warmest (1856–1866, 1869–1871, 1907–1916, 1923–1935, 1988–2016) and four coldest time periods (1840–1855, 1872–1906, 1917–1922, 1940–1984) were identified. The developed reconstruction coincides with cold and warm periods with prior investigations from tree-rings in China, Mongolia, Kyrgyzstan, Kazakhstan and Tajikistan. Spatial correlation analysis with the gridded minimum temperature data shows that the temperature reconstruction covers geographical representation over High Asia. Significant correlation was found between temperature reconstruction with summer SST, which suggests strong linkages of regional temperature variability with Indian-Ocean climate system. The obtained spectral peaks from the spectral analysis of the summer temperature reconstruction were significantly at 84.7-year (90%), 2.9-year (99%), 2.6-year (99%), 2.5-year (99%), 2.4-year (99%) and 2.2-year (99%).

Advances in remote sensing have led to use of satellite-derived rainfall products to complement the sparse rain gauge data. Although globally derived and some regional bias corrected, these products often show large discrepancies with ground measurements attributed to local and external factors that require systematic consideration. Decreasing rain gauge network however inhibits continuous validation of these products. We propose to deal with this problem by the use of Bayesian approach to merge the existing historical rain gauge information to create a consistent satellite rainfall data that can be used for climate studies. Monthly Bayesian bias correction is applied to the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS v2) data to reduce systematic errors using a corresponding gridded (0.05°) rain gauge data over East Africa for a period of 33 (1981–2013) years of which 22 years are utilized to derive error fields which are then applied to an independent CHIRPS data for 11 years for validation. The bias correction is spatially and temporally assessed during the rainfall wet months of March-May (MAM), June-August (JJA) and October–December (OND) in East Africa. Results show significant reduction of systematic errors at both monthly and yearly scales and harmonization of their cumulative distributions. Monthly statistics showed a reduction of RMSD (29–56)% and MAE (28–60)% and an increase of correlations (2–32) %, while yearly ones showed reductions of RMSD (9-23)%, and MAE (7–27)% and increase of correlations (4–77)% for MAM months, reduction of RMSD (15–35)% and MAE (16–41)% and increase in correlations (5–16)% for JJA months, and reduction of RMSD (3–35)% and MAE (9–32)% and increase of correlations (3–65)% for OND months. Systematic errors of corrected data were influenced by local processes especially over Lake Victoria and high elevated areas. Large-scale circulations induced errors were mainly during JJA and OND rainfall seasons and were reduced by the separation of anomalous years during training. The proposed approach is recommended for generating long-term data for climate studies where consistencies of errors can be assumed.

This paper presents a research carried out in the city of Chillan, a medium size city located on the southern limit of the Chilean Mediterranean domain, at 36º 36`s south latitude. Chillán provides a good representative example of warm summers in central and southern Chilean cities. Five public spaces were selected, representing different typologies and relating to different urban background conditions. Users in these public spaces were observed, counted and photographed five times a day (12, 14, 16, 18 and 20 hours, local time) during a heat wave event in the summer of 2016, while meteorological parameters were established at different points within the public space. The variables evaluated were impervious surfaces, Skyview factor, H/W, azimuth, shadow and radiation. Local public environmental management should pay attention to the complex relations between urban climate, public spaces and thermal comfort since they affect the quality of life of the most vulnerable sectors of the population. This is particularly important given the increasing episodes of high temperatures and intense heat waves occurred in the city of Chillán in recent summers, which are related to urban heat islands and climate change.

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.

In this study, an attempt was made to investigate the Kenya case of multivariate causality of carbon dioxide emissions by employing a time series data spanning from 1961-2011 using the ARDL method of cointegration analysis. The long-run elasticities show that, a 1% increase in financial development increases carbon dioxide emissions by 0.28%, a 1% increase in GDP per capita increases carbon dioxide emissions by 1.32% and a 1% increase in urbanization decreases carbon dioxide emissions by 1.14%. There was a unidirectional causality running from financial development, food production index, GDP per capita, industrialization and urbanization to carbon dioxide emissions. The innovation accounting shows that 20% of future shocks in carbon dioxide emissions are due to fluctuations in financial development, 9% of future shocks in financial development are due to fluctuations urbanization and 22% of future shocks in food production index are due to fluctuations in carbon dioxide emissions.

A superior variant of dried jujube in China is ‘Huizao’ (HZ) jujube. Nonetheless, detailed evaluations of the texture quality of HZ fruits have been the subject of few studies. Texture is a significant indicator of the sensory and processed quality of a fruit. Here, we differentiate and characterize the texture quality of HZ fruits from the four primary producing regions in southern Xinjiang, as well as develop a system for assessing the texture quality of HZ fruits. Furthermore, five texture indices of HZ fruits from 109 plantations were exhaustively evaluated utilizing principal component analysis, Pearson correlation analysis, and hierarchical clustering analysis. Consequently, by the 10th, 30th, 70th, and 90th percentiles, each index was classified into five grades—lower, medium, high, and higher. Correlation investigation indicated strong relationships between the springiness, chewiness, cohesiveness, gumminess, and hardness of HZ fruits. Springiness, hardness, and adhesiveness are essential indicators that influence the texture of HZ fruits. We used clustering analysis to separate the six texture indices into three major categories (hard factor, stick-elastic factor, and adhesive factor), with indices representing hardness, springiness, and adhesiveness, respectively. Furthermore, according to the factor molecules, the texture quality of HZ fruits in the four production areas was evaluated as Bazhou (1.24) > Hotan (0.773) > Kashi (-0.577) > Aksu (-0.852). RDA analysis of six texture quality parameters and 24 climate conditions identified higher mean temperature (TEM) and lower relative humidity (RHU) as the primary factors contributing to the improved texture quality of HZ fruits in Xinjiang. This study identified the texture quality characteristics of HZ fruits in four major producing areas of Southern Xinjiang, and it offered a theoretical foundation for optimizing the dominant producing areas and regional production of HZ varieties in Xinjiang.

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.

The thermal conditions of transitional (ranging from warm to cold) coldwater streams impact the ranges and resource availabilities for biota inhabiting these lotic systems. With ongoing climate change and increasing land modifications, thermal boundaries may shift, altering thermal transition zones and their biotic communities. The objective of this study was to investigate the condition of trout across three forks of the Whitewater River catchment and to investigate factors influencing fish community composition and distribution. Each fork was characterized into three separate sections: headwater (coolwater), middle (warmwater), and lower (coldwater). Springs were identified throughout each fork, with greatest concentrations in the lower sections of each fork. Using single-pass electrofishing, we sampled 61 sites across the three forks in the Whitewater River system (North = 21 sites, Middle = 19, South = 21), and catch statistics were used to calculate diversity, trout abundance, and trout condition. In general, diversity increased, and trout were healthier but less abundant in middle and headwater sections, whereas diversity decreased slightly, trout condition decreased, and trout abundance increased in lower reaches, with changes differing somewhat among forks. Canonical correlation analysis had strong significant correlations showing simpson diversity and condition increase going upstream with high non trout abundance and catch rates while trout catch rates and reach width decrease. The Whitewater River is a catchment exhibiting transitional temperature-pattern characteristics with generally low fish community diversity and trout conditions that range from thin, normal, and robust. Dominated by a changing landscape (agriculture) and intensifying climate change, we may begin to see stream temperatures increase along with species diversity. Understanding how spring temperature influences species composition and distribution can bring potential stressors to light increasing our understanding of thermal conditions and to help mitigate the negative impacts from land use and climate change.

Emission trading schemes (ETSs) have become vital tools in striving toward global emission reduction objectives and promoting a sustainable economy. This paper empirically investigates the impact of market conditions on interconnectedness within precious metals, clean energy, green bonds, and carbon markets, focusing on China and the EU ETSs as the study subjects. A TVP-VAR-based asymmetric connectedness approach is adopted to capture the evolving relationships between the variables of interest in the time–frequency domain. The empirical findings reveal that: First, time-varying asymmetric connectedness and spillover effects among clean energy, precious metals, green bonds, and carbon markets are identified in both time and frequency domains under diverse market conditions, with long-term connectedness asymmetry being particularly sensitive, although spillovers exhibit variations. Second, the role and intensity of net transmitters or receivers vary across market conditions and frequency domains, indicating the complex and nuanced nature of market interactions. The EU ETS demonstrates a higher level of connectivity with global markets for clean energy, precious metals, and green bonds when compared to the Chinese ETS. However, it also shows greater susceptibility to fluctuations in market conditions. These results have significant implications for both investors striving to build sustainable diversified portfolios and regulators endeavoring to craft effective policies for risk regulation and sustainable development.

In the present study we examine the relationship among sovereign yields, temperature and precipitation using a large monthly panel data set which consists of 20 eurozone members, over the period 1980M1 – 2023M4. To account for possible asymmetries along the distribution of the climate variables we assume a quadratic modelling specification and apply various mean panel estimation techniques of heterogeneous coefficients. At a next step, to consider possible nonlinearities in the distribution of the dependent variable (sovereign yields), we apply the quantile via moments methodology of Machado and Santos Silva (2019), which accounts for possible cross-sectional dependence and slope heterogeneity. We contribute to the existing literature in two main ways. First, by applying a quantile methodology that provides a more in-depth analysis of the climate effects along the distribution of the sovereign yields, especially in the presence of non-normally distributed data. Second, we find that climate change, as proxied by higher temperatures or lower precipitation (drought), will increase the sovereign risk of all countries, but the magnitude of the impact will be higher for countries that are already characterized by higher sovereign risk levels and/or face extreme weather conditions (hotter countries and/or countries with low levels of precipitation).

Ultramafic rocks become promising candidates for carbon sequestration by enhanced carbon dioxide (CO2) mineralization strategies due to their highly CO2-reactive mineral composition and its abundant availability. This study reports a mineralogy and microtextures of a representative ultramafic rock from the Ma-Hin Creek in northern Thailand and observes evidence of CO2 mineralization occurring through the interaction between CO2 and the rock with the existence of water under ambient conditions. After sample collection, rock description was determined by optical petrographic analysis. The rock petrography reveals a cumulated wehrlite comprising over 50% olivine and minor amounts of clinopyroxene, plagioclase, and chromian spinel. Approximately 25% of the wehrlite has altered to serpentine and chlorite. A series of CO2 batch experiments were conducted on six different rock sizes at a temperature of 40°C and pressure of 1 atm over five consecutive days. The post-experimental products were dried, weighed, and geochemically analyzed to detect changes in mineral species. Experimental results showed that product weight and the presence of calcite increased with reducing grain size. Additionally, the modal mineralogy of the wehrlite theoretically suggests a potential CO2 uptake of up to 53%, which is higher than the average uptake values of mafic rocks. These findings support the suitable rock investigation approach and the preliminary assessment of carbon mineralization potential, contributing to enhanced rock weathering techniques for CO2 removal that could be adopted by mining and rock supplier industries.

The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.

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

The objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

Water sustainability has become one of the most severe issues in the 21st Century due to dramatic urban population growth and climate change. This paper reviews some of the critical key water issues that need to be considered/incorporated in the quest for water sustainability for the upcoming decades. The purpose is to recognize the critical circumstances for maintaining water sustainability and recognize that many regions in the world have passed the ‘tipping point’ of balancing their water sustainability and failing to realize that restoring sustainability will be extremely difficult. From the water quantity perspective, several examples are used to demonstrate situations which, in hindsight, have been initially shown to be effective but highly problematic in the long term. The review considers, amongst others, the 1960s India example shows that an agricultural ‘success’ starting in the 1960s has subsequently become an environmental disaster. Additional issues, including the impacts of dietary adjustments, upstream diversions raising downstream shortfalls, and transfers of water from agriculture to urban areas, are examples that demonstrate that to achieve water sustainability, lessons must be learned from the past, and adaptive measures must be adopted to help humanity avoid adverse and irreversible environmental tragedies. Government authorities can learn from this critical review of some approaches and realize their responsibility to proactively promote better water resource management strategies (domestic and international collaborations) and strictly regulate water use practices to better manage water sustainability.

Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ response to major disaster. This paper will focus on strategies to support nursing response to disaster, specifically to strengthen resiliency and the ability to maintain function despite the shock of disaster, including those caused by climate changes. Methods: Semi-structured interviews were conducted with 11 hospital-based nurse executives who supervised nurses during some of the worst natural and human-made disasters in different regions of the United States. A phenomenological approach was used to analyze and describe emerging themes from qualitative data. Results: Three Nurse Executives demonstrated theme saturation for mitigation steps to augment traditional disaster readiness activities: 1.) Assessment of Human Infrastructure: Daily Skills Needed During Disaster Response, 2.) Identification and Study of Failure Points & Metrics, 3.) Strengthening Human Infrastructure: Rectifying Deficiencies), and 4.) Monitoring Metrics & Making Corrections During Conventional Periods. Conclusion: Mitigation steps may improve outcomes in hospital function during conventional times; therefore, may improve resiliency and the ability to maintain functions during major disasters, including climate change.

Implementing net-zero building design is a crucial step towards decarbonizing the built environment during the entire lifecycle of a building, encompassing both embodied and operational carbon. This paper presents a novel computational approach to design Life Cycle Zero-Carbon Building (LC-ZCB), utilizing parametric integrated modeling through the versatile Grasshopper platform and its plug-ins. The Department of Energy’s prototype residential building at New York Institute of Technology, optimized to fulfill the LC-ZCB target, serves as the base building for this comprehensive study. Four main influencing design parameters, namely geometry, construction technology, thermal resistance of the envelope, and on-site renewable energy production, are defined and three-hundred design combinations are evaluated through the assessment of the operational carbon (OC) and embodied carbon (EC). By incorporating bio-based materials in the design options, the influence of biogenic carbon on the whole carbon footprint of the building case study is addressed by utilizing the GWPbio dynamic method, which assumes 100-year time horizon and incorporates dynamic characterization factors based on time of pulse emissions and two variables: rotation of the biomass and storage period of carbon in products. Finally, to account for potential climate changes, future climate data and 2099 weather conditions are considered during the scenarios assessment. The results demonstrate the potential for achieving LC-ZCB when fast growing biobased materials are largely used as construction materials, fostering a more environmentally responsible future for the construction industry.

Recreational water activities are widely recognized to have a positive impact on our physical and mental well-being. However, recreational water sources and their management are also a risk factor for human health, due to different agents, including the overgrowth of cyanobacteria and algae. These organisms have the potential to metabolize organic matter and produce thermophilic and thermotolerant toxins. Different species of algae participate in biofilm formation and impact on maintenance of equipment for water treatment. We reviewed the state of the art by providing basic definitions, taxonomy and the epidemiological and clinical issues related to the recreational uses of waters. Methods for treatments and monitoring are summarized, considering both traditional and innovative strategies. Public health and surveillance perspectives impose to focus on the detection of toxins, the formation of biofilms, the understanding of the benthonic and planktonic components as part of a larger microbial biodiversity.

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.

The escalating concerns over climate change have propelled industries worldwide to seek innovative strategies for mitigating greenhouse gas emissions. Within the energy sector, Carbon Capture and Storage (CCS) technology emerges as a promising solution to curtail emissions and foster sustainable development aims for net zero approach. The research delves into the role of government support in expediting CCS adoption for the maximum potential of 9.79 MtCO2 storage from six major refinery plants. The refineries mentioned above are anticipated to necessitate an initial capital investment of approximately 18,307 million THB. This research focuses on potential business model proposals appropriate for a country's context, specifically applying CCS technology to Thai oil refining sector. To achieve the realization of CCS within the context of this study, a combination of three essential measures will be required: tax incentives, carbon credits, and grants. This process will commence with the implementation of tax incentives, followed by an increase in the carbon price within the country. Finally, the establishment of a dedicated fund, funded through deductions from oil excise tax revenue, will play a pivotal role in facilitating the necessary financial support for the emergence of CCS.

The public administrations (PAs) that have joined the Covenant of Mayors must now complete their adaptation plans with the climate chapter (SECAP). At the same time, the previous Plan for sustainable energy (SEAP) was mainly dedicated to mitigation actions (sustainable energy). It was often managed directly by municipalities' in-house energy companies or agencies. The WMO1234 Recommendation (Guidance on Integrated Urban Hydrometeorological, Climate and Environmental Services) is a fundamental Guidance to allow PAs to make policies and decisions regarding city regeneration and population health prevention. The purpose of this manuscript is to describe a process undertaken in the Emilia-Romagna region to build a coherent frame from the individuation of local environmental vulnerabilities and adopt specific policies. This frame was created by the contribution of various Institutions, including the Regional Authority, which furnished the main directives and tools for the mitigation and adaptation, the Municipality of Bologna, which prepared the first Adaptation Plan following the SECAP guidance, the Emilia-Romagna branch of Italian Association of Municipalities (ANCI), which took in charge the approach to harmonize different urban contexts and to communicate with stakeholders and population, and Research Institutes and Scientific Associations to explore, with specific studies and modeling application, the outcomes produced by a joint support to the new urban directives, such as the General Urban Planning Plan (PUG). To achieve this result, the WMO Guidance 1234 has been assumed as a reference methodology to ensure the best utilization of available data and widespread a common science-based methodological approach to other municipalities.

Flood inundation causes socioeconomic losses for coastal tourism under climate extremes, progressively attracting global attention. Mapping, evaluating, and predicting the flood inundation risk (FIR) is significant for coastal tourism. The study develops a spatial tourism–aimed framework integrating a weighted k-Nearest Neighbors (WkNN), Geographic Information Systems, and flood-related spatially environmental criteria such as precipitation, elevation, soil, and drainage systems. These model inputs were standardized and weighted using distance, and integrated into WkNN to infer regional probability and distribution of FIR. Zhejiang province, China, was selected as a case study. The resulting map was pictured to denote the likelihood of the criteria at various risk categories, which was validated by historical Maximum Inundation Extent (MIE) extracted from World Environment Situation Room. The result indicates 80.59% of WkNN results reasonably confirm the MIE. Precipitation and elevation make a negative contribution to high-medium risk, and drainage systems positively alleviate the regional stress of FIR. The results can help stakeholders make suitable strategies to protect coastal tourism, and also weigh WkNN is superior to kNN in FIR assessment. The framework provides a productive way to yield a reliable assessment of FIR and can also be extended to other risk-related environmental studies under climate change.

Among the main elements that contribute to climate change are degradation processes and the ecological level of the landscape. These two topics have been discussed and researched for many years and many studies have been conducted. The idea of the article is to determine the correlation between the ecological stability of the territory and the intensity of degradation processes and find out how the ecological stability affects the intensity of soil erosion and vice versa. The ecological stability was calculated based on various methods during the years analyzed, i.e., 1990, 2006, 2012, and 2018. The soil water erosion was performed for the same period in order to identify the relationship between the ecological stability and intensity of soil erosion. The investigated area is located in the Slovak Republic while each year reflects different management of the territory reflecting the current situation in the catchment according to the year evaluated. The intensity of the erosion process was conducted using a phycially-based EROSION-3D model and based on the precipitation derived using Community Land Model (the CLM model). In addition to identifying the relationship between the level of ecological stability and the intensity of erosion, this study also describes the development the ecological stability during the evaluated period together with changes in soil erosion processes.

Historically, Physalis physalis massive stranding events have been infrequent and poorly documented. However, their occurrence can have significant impacts on human health and the stability of coastal ecosystems. In this study we analyze the largest P. physalis stranding event historically recorded affected Cuba’s northwestern coast in December 2022. We counted all colonies during the massive event along ~ 3 km coast, within a 5 m stripe. Density, dimorphic form (left/right-handed), and colony size were quantified using 0.25 m2 quadrat placed every 50 m, 10 m from shoreline. Eighty-five people were stung, with 38 having strong allergic reactions, resulting in a health risk. Over ten thousand colonies were recorded, with the highest mean colony density (29.3 per m2) ever reported. The massive stranding coincided with the lowest Arctic Oscillation index (-2.59) in the past 11 years during December, likely linked to climate change. This led to the emergence of northeasterly winds reaching speeds of up to 24 km/h. Wind direction and speed, coupled with the dominance of left-handed colonies (71.4%), suggest the Sargasso Sea as the possible source of the bloom. The high prevalence of juvenile P. physalis colonies (68 %) likely aligns with the autumn breeding season in the northern hemisphere. The potential causes of P. physalis blooms are still poorly understood. Systematic monitoring of the distribution and abundance of this species should be a research priority considering the potential risk to human health and that the blooms could become more frequent and affect other areas in the Atlantic, given climate change and increasing eutrophication of the oceans.

Transitioning towards net zero emissions is critical in the chemical and process industries to combat climate change and ensure environmental sustainability. Key focus areas of this review include the reduction of carbon emissions, the efficient utilization of energy resources, and the adoption of sustainable practices. Cutting-edge technologies such as biomass utilization, biotechnology applications, and waste management strategies are crucial in achieving this transition. Industries, including cement production, encounter unique challenges in their quest for sustainability and must actively seek innovative solutions to mitigate their carbon footprint effectively. The role of hydrogen as a clean fuel and its potential to revolutionize the chemical and process sectors is also discussed. The European Green Deal and Sustainable Development Goals (SDGs) are significant for the chemical industry. They provide a clear roadmap and framework for promoting sustainability, driving innovation, and reducing the industry's environmental impact. By aligning with these initiatives, the chemical industry can enhance its competitiveness, contribute to societal well-being, and foster collaboration across sectors to achieve shared sustainability objectives.

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.

Abstract: Establishing carbon neutrality (or Net Zero) in cities appears to be an ambitious challenge, which drives urban transformation efforts around the world to enhance people-centric living. Cities launch corresponding strategies focusing mainly on the United Nations 2030 goals to form their climate-neutral future. This paper provides practical guidance on city digital transformation to achieve carbon net zero. These guidelines illustrate actionable recommendations to reduce their carbon footprint using digital technologies. Following a multi-method research approach, findings from a bibliometric literature and a standards’ gap analysis were combined with practical evidence and circulated with focus group experts to conclude to these guidelines, which are the foundation for further standardization. The outcomes provide concrete guidelines to policymakers, planners, and other stakeholders for city digital transformation to establish carbon neutrality, via emphasizing the need for digital technologies to enhance efficiency in several areas and via leveraging green ICTs for city economic growth while also transforming citizen behavior.

Bread wheat (Triticum aestivum L.) is one of the world's most important staple food crop providing 20% global energy and dietary proteins. It is widely grown in sub-tropical and tropical areas and as such exposed to heat-stress especially at grain filling period (GFP). Global warming has further affected its production and productivity in these heat-stressed environments. We examined the effect of heat-stress on 18 morpho-physiological and yield-related traits in 96 bread wheat accessions. Heat susceptibility index (HSI <0.60) and yield stability (i <0.55) used as criteria for selecting the tolerant accessions. Heat-stress, imposed by delayed sowing, decreased crop growth and GFP, and as a result reduced morphological and yield-related traits, namely days to 50% anthesis, plant height, peduncle length, flag-leaf area, spike length, spikelets per spike, grain length and width, thousand grain weight (TGW), harvest index and yield. The reduction in the trait values was severe in susceptible accessions (48.2% yield reduction in IC277741) than the tolerant. Physiological traits like chlorophyll content, canopy temperature depression (CTD), normalized difference vegetation index (NDVI), plant waxiness and leaf rolling showed higher expression in the tolerant accessions under heat-stress. Scanning electron microscopy of matured wheat grains revealed ultrastructural changes in endosperm and aleurone cells caused due to heat-stress. The reduction of size and density of large starch granules is the major cause of yield and TGW decrease in the heat-stress susceptible lines. The most stable and high-yielding accessions namely IC566223, IC128454, IC335792, EC576707, IC535176, IC529207, IC446713 and IC416019 were identified as the climate-smart germplasm lines. Germplasm lines possessing desirable traits were selected as po-tential parents for the development of bi-parental and multi-parental populations.

The difficulty in obtaining commercial fertilizers by smallholder farmers in sub-Saharan Africa makes it very important to optimize the use of local organic resources. In VilanKulo, Mozambique, a study was carried out on okra (Abelmoschus esculentus) over two growing seasons in a haplic Lixisol, a loamy-sand textured soil, applying both bat guano and biochar prepared by an artisanal process. Bat guano was applied at two rates (5 and 10 t ha−1), one month and just before sowing. Biochar was also used at two rates (5 and 10 t ha−1) applied close to sowing. Mixtures of biochar and guano at two rates (1 and 4 t ha−1, and 2 and 8 t ha−1, respectively) were also used along with a non-fertilized control. Field trials were arranged in a completely randomized design with three replicates. The treatments receiving high rates of guano tended to show significantly higher fruit yields (&gt; 10 t ha−1, being the two-year average) in comparison to the control, which showed the lowest average okra fruit yield (6.21 t ha−1). In guano treatments, the apparent recovery by okra of some important nutrients, such as nitrogen (N), was greater than the amount of nutrient contained in the guano itself. This result, together with many others related to tissue nutrient concentration, soil properties and residual fertilizing value in guano plots, indicates a strong mineralization of guano during the growing season, probably due to its low carbon (C)/N ratio and favourable environmental conditions for the mineralization process, such as high temperature and well-aerated soil. The result also suggests some kind of manuring effect, i.e., a fertilizing effect of guano beyond what can be explained by the nutrient supply. The use of biochar increased total organic C in the soil and cation exchange capacity (CEC) compared to the control, but did not affect variables related to plant performance, such as tissue nutrient concentration or plant growth and yield.

Agroecology is a holistic approach to farming that emphasizes the use of local resources and ecological processes to increase productivity, reduce environmental impact, and enhance resilience. Despite its potential benefits, the adoption of agroecological practices in Sub-Saharan Africa has been slow. This paper examines the opportunities for promoting agroecology in the region, including the growing demand for organic and sustainable food, the availability of local knowledge and resources, and the potential for agroecology to improve rural livelihoods and support climate change adaptation. The premise is that the promotion of agroecology faces several challenges. which include, inadequate policy and institutional support, lack of access to credit and markets, limited extension services, and weak land tenure systems. The paper draws on case studies from across Sub-Saharan Africa to illustrate the opportunities and challenges of promoting agroecology in the region. These case studies highlight the diversity of agroecological practices and the importance of context-specific approaches. Overall, the paper maintains that agroecology has the potential to transform agriculture in Sub-Saharan Africa, but that realizing this potential will require concerted efforts from governments, civil society, and the private sector.

Fresh water is an increasingly scarce resource in both urban and rural developments. As a response to this challenge, non-potable water reuse is on the rise. This research explored a potential off-grid system for water purification, consisting of a staircase wetland with terracotta pot plants working as a filter for greywater. The study further investigated the physicochemical properties of the greywater and the soil before and after the wetland purification. Results showed that the filtered water satisfied all requirements for water reuse, e.g., pH, turbidity, and total coliforms. The research then uniquely investigated the effect of greywater on the soil biodiversity and soil biomass using soil DNA extraction and the tea bag index testing method. The filtered greywater absorbed by soil decomposed the soil faster and stabilized it better compared to tap water-absorbed soil or unfiltered greywater. The DNA generation sequencing revealed no significant differences in alpha diversity between control and treatment samples. The beta diversity differences were significant. This nature-based solution can lead to reduced load on the sewage system, resulting in less wastewater generation.

The year 2022 was characterized by several major events that impacted the business world in Indonesia and even globally after the COVID-19 pandemic devastated all business sectors in Indonesia and the world. The current business environment is experiencing accelerating turbulence characterized by increasing intensity of business competition, rapid changes in the market, and industrial connections climate. The industrial connection climate of an institution can be measured by the pattern of relationships that occur between workers and management. Industrial connections are fundamental to the sustainability of an organization and are understood as an important factor in influencing institutional performance. This research aims to look at the impact of the existence of industrial connections instruments, turbulence in the business environment on the industrial connections climate. Besides, how the industrial connections climate relates to firm performance. The research design is an inferential quantitative, using sampling and snowball sampling methods with total sample are 406. The data collected were analyzed using Structural Equation Model using LISREL version 8.70. This research used a survey to build an SEM model that tested the effect of organizational turbulence and industrial connections instruments on organizational climate directly, and tested mediation on organizational performance. All related indicators have outer loading more than 0.5 and T-value more than 1.96. Therefore, the conclusion is that all measurements are valid. Composite Reliability (CR) and VE for all indicators are >0.7 and >0.5 respectively. This research shows that industrial assosiation climate has a positive effect on business turbulence and industrial connections instruments. However, industrial connections instruments show a greater impact on the assosiation climate. This is because industrial connections instruments are the media used in the implementation of industrial connections in organizations. This research also confirms that industrial assosiation climate is positively related to organizational performance. The result of the indirect influence (IE) of 0.20 with t value is 8.47 means that the climate of Industrial connections is able to mediate the influence of Industrial connections Facilities on Organizational Performance.

Climate change poses a serious threat to global agricultural activity and food production. To address this issue, plant genome editing technologies have been developed to provide an alternative solution for crop improvement. Unlike conventional breeding techniques (e.g., selective breeding and mutation breeding), modern genome editing tools offer more targeted and specific alterations of the plant genome to produce crops with desired traits, such as higher yield and/or stronger resilience to the changing environment. In this review, we discuss the current development and future applications of genome editing technologies in mitigating the impacts of biotic and abiotic stresses on agriculture. We focus specifically on the CRISPR/Cas system, which has been the center of attention in the last few years as a revolutionary genome-editing tool in various species. We also conducted a bibliographic analysis on CRISPR-related papers published from 2012 to 2021 (10 years) to identify trends and possible gaps in the CRISPR/Cas-related plant research. In addition, this review article outlines the current shortcomings and challenges of employing genome editing technologies in agriculture with notes on future prospective. We believe combining conventional and more innovative technologies in agriculture would be the key to optimizing crop improvement beyond the limitations of traditional agricultural practices.

Globally mangrove forests are substantially declining and a globally synthesized database of the drivers of deforestation and drivers’ interaction is scarce. Here we synthesized the key social-ecological drivers of global mangrove deforestation by reviewing about two hundred published scientific studies over the last four decades (from 1980 to 2021). Our focus was on both natural and anthropogenic drivers with gradual and abrupt impacts and their geographic ranges of effects and how these drivers interact. We also summarized the patterns of global mangrove coverage decline between 1990 and 2020 and identified the threatened mangrove species and their geographic ranges. Our consolidated studies reported a 8,600 km2 decline in the global mangrove coverage between 1990 and 2020 with the highest decline occurring in South and Southeast Asia (3870 km2). We could identify 11 threatened mangrove species, two of which are critically endangered (Sonneratia griffithii and Bruguiera hainseii). Our reviewed studies pointed to aquaculture and agriculture as the predominant driver of global mangrove deforestation though the spatial distribution of their impacts varied. Gradual climate variations, i.e. seal-level rise, long-term precipitation and temperature changes and driven coastline erosion, constitute the second major group of drivers. Our findings underline a strong interaction across natural and anthropogenic drivers with the strongest interaction between the driver groups aquaculture and agriculture and industrialization and pollution. Our results suggest prioritizing globally coordinated empirical studies linking drivers and mangrove changes and a global development of policies for mangrove conservation.

Due to rising global warming and climate change, biodiversity protection has become a critical ecological concern. The rich biodiversity zones are under threat and are deteriorating, necessitating national, regional, and provincial efforts to safeguard these natural areas. The effective conservation of National Parks and Nature-protected Areas helps to improve biodiversity conservation, forest, and urban air quality. The continuous encroachment and abuse of these protected areas have degraded the ecosystem over time. While exploring the geophysical ecology and biodiversity conservation of these areas in West Africa, Kainji National Park was selected for this study because of its notable location, naturalness, rich habitat diversity, topographic uniqueness, and landmass. The conservation of national parks and nature-protected areas is a cornerstone of biodiversity conservation globally. This study is aimed at the target of United Nations Sustainable Development Goal 13, 2030- Climate Action, targeted at taking urgent action towards combating climate change and its impacts. The study captures both flora and fauna that are dominant in the study area. The 15 identified tree species were selected from over 30 species with 563,500,000 (an average of 3,700,000 in each sample frame) trees for every tree species/type with a total of 63% tree green canopy cover. The study areas divided into three zones were randomly sampled within a stratum of 25x25km frames divided into 150 sample frames for proper analyses using the i-Tree Eco v6.0.23. The following microclimatic data were captured and analyzed; photosynthetically active radiation, rain/precipitation, temperature, transpiration, evaporation, water intercepted by trees, avoided a runoff by trees, potential evaporation by trees, isoprene and monoterpene by trees. This study also further discusses the tree benefits of a green, low carbon, and sustainable environment within the context of biodiversity conservation considering carbon storage, carbon sequestration, hydrology effects, pollution removal, oxygen production, and volatile organic compounds (VOCs). There is a quick need for remotely-sensed information about the protected areas at regular intervals and government policies must be strict against illegal poaching, logging activities and other hazardous human impacts.

Biodiversity conservation questions human practices towards biodiversity and, therefore, largely conflicts with ordinary societal aspirations. Decisions on the location of protected areas, one of the most convincing conservation tools, reflect such a competitive endeavor. Operations Research (OR) brings a set of analytical models and tools capable of resolving the conflicting interests between ecology and economy. Recent technological advances have boosted the size and variety of data available to planners, thus challenging conventional approaches bounded on optimized solutions. New models and methods are requested to use such a massive amount of data in integrative schemes addressing a large variety of concerns. Here, we provide an overview on the past, present and future challenges that characterize spatial conservation models supported by OR. By enlarging the spatial, temporal, taxonomic and societal horizons of biodiversity conservation planners navigate around multiple bio-socioeconomic equilibria and are able to decide on cost-effective strategies to improve biodiversity persistence.

The indigenous communities across the globe especially in the rural areas consume locally available plants known as Traditional Food Plants (TFPs) for their nutritional and health-related needs. Recent research shows that many of the traditional food plants are highly nutritious as they contain health beneficial metabolites, vitamins, mineral elements and other nutrients. Excessive reliance on the mainstream staple crops has its own disadvantages. TFPs are nowadays considered important crops of the future and can act as supplementary foods for the burgeoning global population. They can also act as emergency foods in times of pandemics and other situations like COVID-19. The current situation necessitates locally available alternative nutritious TFPs for sustainable food production. To increase the cultivation or improve the traits in TFPs, it is essential to understand the molecular basis of the genes that regulate some important traits such as nutritional components and resilience to biotic and abiotic stresses. The integrated use of modern omics and gene editing technologies provide great opportunities to better understand the genetic and molecular basis of superior nutrient content, climate-resilient traits and adaptation to local agroclimatic zones. Recently, realising the importance and benefits of TFPs, scientists have shown interest in the prospection and sequencing of traditional food plants for their improvements, further cultivation and mainstreaming. Integrated omics such as genomics, transcriptomics, proteomics, metabolomics and ionomics are successfully used in plants and have provided a comprehensive understanding of gene-protein-metabolite networks. Combined use of omics and editing tools has led to successful editing of beneficial traits in few TFPs. This suggests that there is ample scope of integrated use of modern omics and editing tools/techniques for improvement of TFPs and their use for sustainable food production. In this article, we highlight the importance, scope and progress towards improvement of TFPs for valuable traits by integrated use of omics and gene editing techniques.

The virtual airport hub business model is an innovative solution supported by digital technologies, the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analitics to identify the mobility needs of population and operational capabilities of the sector, gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

We have an aversion to density in America. Density is a continual trope in this country, blamed for all of the ills of urban life, from crime and racial unrest in the middle of the 20th century to public health concerns today. In the early stages of the COVID pandemic density was the culprit, even though we’ve subsequently seen outbreaks in rural areas and sprawling cities across the United States. This paper will look into the root of America’s problems with density and argue that density is not the problem but the solution to the challenges of today’s and tomorrow’s cities. As we deplete the resources of the planet, density is our most direct pathway to recover some balance with nature. Dense living is more efficient, less carbon intensive and more environmentally sustainable. As geospatial differentiations matter less due to advances in communication technology, it's the density of people and ideas that will continue to fuel innovation. Finally, in a world that is increasingly dominated by pluralism, denser living promotes openness, tolerance and diversity.

This work assesses sea-level rise using three different models created on Free and Open-Source Software for Geographic Information System (FOSS4GIS). Based on regional projections of Special Report on Climate Change and Oceans and Cryosphere (SROCC) of the Intergovernmental Panel on Climate Change (IPCC), the models were applied to a case of study on Rio Grande do Sul coast – Brazil under different sea-level rise scenarios by the end of this century. The End Point Rate for QGIS (EPR4Q), calculates a shoreline projection using End Point Rate method. The Uncertainty Bathtub Model (uBTM), analyses the sea-level rise impact by the uncertainty of sea-level projec-tions and vertical error of the Digital Elevation/Terrain Model (DEM/DTM). The Bruun Rule for Google Earth Engine Model (BRGM) predicts the shoreline position with sea-level rise, using topographic and bathymetric data from Unmanned Aerial Vehicles (UAV) and Coastal Modelling System (SMC – Brazil), respectively. The results indicated a maximum shoreline retreat for 2100 of -502 m and -1727 m using EPR4Q and BRGM, correspondingly. The uBTM using the land-use of Mapbiomas showed a maximum of 44.57 km2 of urban area impacted by the sea-level flood. This research highlights the possibility of performing coastal management analysis in GIS environ-ment using non-commercial software.

Greenhouse Gases (GHG) emissions from dairy farms are significant contributors to global warming. However much of the published work on GHG reduction is focused on either Methane (CH4) or Nitrous Oxide (N2O), with few, if any, considering the interactions that changes to farm systems can have on both gases. This paper takes the raw data from a year of activity on a 300 cow commercial dairy farm in Northern Ireland to more accurately quantify the GHG sources by use of a simple predictive model based on IPCC methodology. Differing herd management policies are examined together with the impact of integrating Anaerobic Digestion (AD) into each farm system. Whilst significant success can be predicted in capturing CH4 and Carbon Dioxide (CO2) as biogas and preventing N2O emissions, gains made can be lost in a subsequent process negating some or all of the advantage. The process of extracting value from the captured resource is discussed in the light of current farm parameters together with indications of other potential revenue streams. However, this study has concluded that despite the significant potential for GHG reduction, there is little incentive for widespread adoption of manure based farm scale AD in the UK at this time.

Drought stress at the reproductive stage in rice is one of the most important cause for yield reduction, affecting both productivity and quality. All Basmati rice varieties, including the popular cultivar ‘Pusa Basmati 1 (PB1)’ is highly sensitive to reproductive stage drought stress (RSDS). We report for the first time, improvement of a Basmati cultivar for RSDS tolerance, with the introgression of a major quantitative trait locus (QTL), ‘qDTY1.1’ into PB1. The QTL donor was sourced from an aus variety, Nagina 22 (N22). A QTL linked microsatellite (SSR) marker ‘RM 431’ was employed for foreground selection for qDTY1.1 in the marker assisted backcross breeding process. A set of 113 SSR markers polymorphic between N22 and PB1 were utilized for background selection to ensure higher genome recovery. After three backcrosses followed by five generations of selfing, eighteen near isogenic lines (NILs) were developed, through combinatory selection for agro-morphological, grain and cooking superiority traits. The NILs were evaluated for three consecutive Kharif seasons, 2017, 2018 and 2019 under well-watered and drought stress conditions. RSDS tolerance and yield stability indicated that NIL3, NIL5, NIL6, NIL7, NIL12, NIL15 and NIL17 were best in terms of overall agronomic and grain quality under RSDS. Additionally, NILs exhibited high yield potential under normal condition as well. The RSDS tolerant Basmati NILs with high resilience to water stress, is a valuable resource for sustaining Basmati rice production under water limiting production environments.

The severity of the ongoing COVID-19 outbreak demand from countries to adopt extreme measurements of social isolation to stop the spread and flatten the curve of contamination. Although social isolation measures may have negative impacts on economy, historically it has been showed to be more effective in saving lives and less damaging to economy than not adopting these measurements during a viral pandemic. In Brazil, despite the positioning of the president against social isolation due to the consequent economic recession, the rapid spread of the virus has worried the governors of the Brazilian states, which are thus managing stringent social isolation measurements to avoid the advance of the virus. Since one of the main strategies to guarantee progress and economic growth in Brazil has been the exploitation of natural resources from the Amazonia biome, here we discuss the importance of this biome to Brazilian economy during the post-pandemic recession and highlights potential strategies to burst the economy without promoting Amazonia destruction. We show that, together with the REDD+ and the Amazon Fund, the Forest bonds represents good strategies to burst Brazilian economy in a sustainable way, showing that it is possible to improve the commodities without increasing Amazonia deforestation or the greenhouse gases emissions. Amazonia is a biome of global importance for the avoidance of another global crisis, which will occur if we reach the climatic tipping point of 1.5°C. Thus, governmental actions should go towards its preservation, not exploitation and depletion. The commitment of the government with environmental conservation is paramount so that these economic strategies have positive results, especially in a post-pandemic scenario, where the economy will be extremely weakened. The COVID-19 brings us a lesson regarding how our attitudes can impact the world, and what we can expect from a global crisis. Perhaps we can apply these lessons and focus on change our economy towards a sustainable direction to avoid another global crisis in the years to come.

Many estuarine ecosystems and the fish communities that inhabit them have undergone substantial changes in the past several decades, largely due to multiple interacting stressors that are often of anthropogenic origin. Few are more impactful than droughts, which are predicted to increase in both frequency and severity with climate change. In this study, we examined over five decades of fish monitoring data from the San Francisco Estuary, California, U.S.A, to evaluate the resistance and resilience of fish communities to disturbance from prolonged drought events. High resistance was defined by the lack of decline in species occurrence from a wet to a subsequent drought period, while high resilience was defined by the increase in species occurrence from a drought to a subsequent wet period. We found some unifying themes connecting the multiple drought events over the fifty-year period. Pelagic fishes consistently declined during droughts (low resistance), but exhibit a considerable amount of resiliency and often rebound in the subsequent wet years. However, full recovery does not occur in all wet years following droughts, leading to permanently lower baseline numbers for some pelagic fishes over time. In contrast, littoral fishes seem to be more resistant to drought and may even increase in occurrence during dry years. Based on the consistent detrimental effects of drought on pelagic fishes within the San Francisco Estuary and the inability of these fish populations to recover in some years, we conclude that freshwater flow remains a crucial but not sufficient management tool for the conservation of estuarine biodiversity.

Because of the near-term risk of extreme weather events and other adverse consequences from climate change, and, at least in the longer term, global fossil fuel depletion, there is world-wide interest in shifting to noncarbon energy sources, especially renewable energy (RE). Because of possible limitations on conventional renewable energy sources, researchers have looked for ways of overcoming these shortcomings by introducing radically new energy technologies. The largest RE source today is bioenergy, while solar energy and wind energy are regarded as having the largest technical potential. This paper reviews the literature on proposed new technologies for each of these three RE sources: microalgae for bioenergy, photolysis and airborne wind turbines. The main finding is that their proponents have underestimated the difficulties facing their introduction on a very large scale.

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

To estimate The potential inventory of natural gas hydrates in the Levant Basin we correlated the gas hydrate stability zone (GHSZ), modeled with locally estimated thermodynamic parameters, with seismic indicators of gas. Compilation of oceanographic measurements define the deep-water temperature and salinity to 13.8°C and 38.8‰ respectively, predicting the top GHSZ at a water depth of 1250±5 m. Assuming beneath the seafloor a hydrostatic pore-pressure, the water body salinity, and geothermal gradients ranging between 20 to 28.5°C/km, yields a useful first-order base-GHSZ approximation. Our model predicts that the entire northwestern half of the Levant Basin lies within the GHSZ, with a median thickness of ~150 m. High amplitude seismic reflectivity (HASR) imaged on an extensive 3D seismic dataset, consistently correlates with verified active seafloor gas seepage and is pervasively distributed across the deep-sea fan of the Nile within the Levant. Two main trends observed for the distribution of HASR are suggested to represent: (1) shallow gas and possibly hydrates, within buried channel-lobe systems 25 to 100 m beneath the seafloor; and (2) a regionally discontinuous bottom simulating reflection (BSR) broadly matching the modeled base GHSZ. We therefore estimate the potential methane hydrates reserve within the Levant Basin at ~4 Tcf.

Low carbon cities are increasingly forming a distinct strand of sustainability literature. Models have been developed to measure the performance of low carbon cities. The purpose of this paper is to formulate a strategy-based model to evaluate current performance and predict future conditions of low carbon cities. It examines the dynamic interrelationships between key performance indicators (KPIs), induces changes to city plan targets and then instantly predicts the outcome of these changes. Designed generic and flexible, the proposed model shows how low carbon targets could be used to guide the transformation of low carbon cities under four strategies: (1) passive intervention, (2) problem solving, (3) trend modifying and (4) opportunity seeking. Further, the model has been applied to 17 cities and then tested on 5 cities: London, New York, Barcelona, Dubai and Istanbul. The paper concludes with policy implications to realign city plans and support low carbon innovation.

This study investigates proximate drivers of cropland and forest degradation in Kloto district (Togo, West Africa) as, way of, exploring integrated sustainable landscape approaches in respect to socio-economic and environmental needs and requirements. Net change analysis of major cash and food crops based on three time steps Landsat data (1985–2002, 2002–2017 and 1985–2017) and quantitative analysis from participatory survey data with farmers and landowners are used. Study underlines poor agricultural systems and cassava farming as major impediments to alarming forest losses between 1985–2017. Significant net loss in forests cover by 23.6% and surface areas under cultivation of cocoa agroforestry and maize by 12.99 and 10.1% from 1985 to 2017, due to, intensive cassava cropping (38.78%) and settlement expansions (7.84%). Meanwhile, loss in forest cover between 2017 and 2002 was marginal (8.36%) compared to the period 1985–2002 for which the loss was considerable (15.24%). Based on participatory surveys, majority of agricultural lands are threatened by erosion or physical deterioration (67.5%), land degradation or salt deposits and loss of micro/macro fauna and flora at 56.7%, declining in soil fertility (32.5%), soil water holding capacity (11.7%) and changes in soil texture (3.3%). Majority of farmers adhere to the adoption of the proposed climate smart practices with emphasis on cost effective drip irrigation systems (45.83%), soil mulching (35%) and adoption of drought resilient varieties (29.17%) to anticipate drought spells adverse. The study concludes that low adoption of improved soil conservation, integrated water management and harvesting systems and low productive and adaptive cultivars entail extreme degradation of croplands and crops productivity decline. Therefore, farmers are forced to clear more forests in search of stable and healthy soils for production and extraction of forest products to meet their food demands and improve their livelihoods conditions. Capacity building on integrated pathways of soil and land management practices are therefore needed to ensure sustainable and viable socio-ecological systems at local scale.

Marine cold air outbreaks (MCAOs) are large-scale events in which cold air masses are advected over open ocean. It is well-known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing ocean near-surface wind speeds during MCAOs in atmospheric reanalysis products with different horizontal grid spacings, along with two case studies using a convection-permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. One of the main findings is that wind speeds during the strongest MCAO events are higher than normal and higher than wind speeds during less severe events. Limited evidence from the case studies suggests that reanalyses with grid spacings of more than 50 km underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. The peak times of MCAO usually occur when baroclinic waves pass over the regions. Therefore, the strong wind episodes during MCAOs generally last for just a few days. However, MCAOs can persist for 50 days or more.

During the past two decades of e-commerce growth, the concept of a business model has become increasingly popular. More recently, the research on this realm has grown rapidly, with diverse research activity covering a wide range of application areas. Considering the sustainable development goals, the innovative business models have brought a competitive advantage to improve the sustainability performance of organizations. The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts, in a sustainable way. The process of sustainable business model construction forms an innovative part of a business strategy. Different industries and businesses have utilized sustainable business models’ concept to satisfy their economic, environmental, and social goals simultaneously. However, the success, popularity, and progress of sustainable business models in different application domains are not clear. To explore this issue, this research provides a comprehensive review of sustainable business models literature in various application areas. Notable sustainable business models are identified and further classified in fourteen unique categories, and in every category, the progress -either failure or success- has been reviewed, and the research gaps are discussed. Taxonomy of the applications includes innovation, management and marketing, entrepreneurship, energy, fashion, healthcare, agri-food, supply chain management, circular economy, developing countries, engineering, construction and real estate, mobility and transportation, and hospitality. The key contribution of this study is that it provides an insight into the state of the art of sustainable business models in various application areas and future research directions. This paper concludes that popularity and the success rate of sustainable business models in all application domains have been increased along with the increasing use of advanced technologies.

Countless disasters have resulted from climate change, with severe damage to infrastructure and the economy. Their societal impacts require mental health services for the millions affected. To prepare for and respond effectively to these events, it is important to understand people’s emotions and incidents both before and after a disaster strikes. The emotions and other life incidents expressed on Twitter during the 2017 Hurricane Harvey were mined in this case study. Between August 20 and August 30, we collected a dataset of approximately 400,000 public tweets that related to the storm. Using a BERT-based model, we predicted the emotions attached to each tweet. After that, we used various natural language processing techniques to analyze the tweets themselves to understand what kind of ’topics’ were being discussed when people expressed certain ’emotions’. Applying the Latent Dirichlet Allocation (LDA) technique for topic modeling sidesteps the need for manual content analysis and allows us to find meaningful patterns in the data. Results show that there is a significant change of emotions occurred when the hurricane is at most devastating and many of life incidents become pressing demands/concerns from population such as evacuation plan, animal safety, safety update, public policy, helps, flood, and fake news.

Land degradation, desertification and tree mortality related to global climate change are in the spotlight of Remote Sensing research in recent decades, since extreme climatic events could affect the composition, structure and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of tree mortality by reviewing both Remote Sensing and ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, ground-based monitoring and climatic drivers, focusing on their spatial and temporal patterns, in the methods applied, while highlighting research gaps. Forested ecosystems, especially in the Mediterranean area, appear to have experienced often climatic-induced physiological stress under extreme droughts and warming, raising concern that forests may become increasingly vulnerable to tree mortality. Our core results indicated that international publications on tree mortality are on the increase with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality on a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large scale assessment. We observed that almost all of the studies we have reviewed were based on less than 25 years of data and were of local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research.

Our study aimed to assess sprinkler irrigation's impact on the activity of selected soil enzymes concerning nitrogen metabolism and oxidation-reduction processes in the soil with different doses of inorganic nitrogen fertilizers. The soil Alfisol was sampled from the experimental field of spring barley in the University Research Center in the central part of Poland in the moderate transitory climate during the growing seasons 2015–2017. The index resistance (RS) was derived to recognise the resistance enzymes of drought. In the maturity phase, nitrate reductase activity was at an 18% higher level in irrigated soils and the activity of other enzymes was higher in no-irrigated treatments by 25% in dehydrogenase, 22% in peroxydase 33% in catalase and 17% in urease case. The development stage of barley influenced nitrate reductase activity. Enzymatic activity has been changing in the examined years of the research, depending on the weather conditions. During the maturity stage, the soil's lower ammonium nitrogen content resulted from higher spring barley uptake due to drought stress. Irrigation probably contributes to increased leaching of nitrate in soil. The highest index of resilience was presented in the soil catalase activity.

The publication presents an innovative tower cultivation device designed to significantly increase vertical farming efficiency. The device divides the cultivation system into separate chambers. One division corresponds to the different growth phases of the plants, while another reflects the daily variation in conditions. Each chamber presents slightly different conditions and cultivation patterns from the others. For the early stages, crops are grown horizontally in trays once they mature, transplanted into mobile cultivation towers. The closed circulation of ventilation and irrigation reduces water consumption by up to 95%. A unique separate day-night division optimises light, temperature and humidity conditions, mimicking natural growth patterns. This approach not only saves water and energy but also optimises cultivation in a three-dimensional space. The presented solution focuses on the often overlooked aspects of cultivating in vertical farms and makes this method of growing much more cost-effective and feasible to implement on a large scale.

Introduction: Papatasi fever, or three-day fever, is a viral disease transmitted by a species of female sandfly called Phlebotomus papatasi that has symptoms similar to influenza. Robat Karim County, due to the high abundance of Sandfly and climate change in recent years, provides a suitable environment for the growth and reproduction of Sandfly, especially Phlebotomus papatasi Therefore, the aim of this study was molecular monitoring of Papatasi fever virus in Sandfly of Robat Karim County, Tehran province. Materials and methods: In 7 selected areas in Robat Karim County, 679 Sandfly using sampling methods including traps and aspirators were caught and 500 samples were randomly selected according to the fishing location and transferred to the laboratory of the Medical Entomology Department. After fixing Sandfly on the slide surface, identification and percentage of frequency of sandfly species were determined and then by Real-time PCR method, molecular examination of Papatasi virus infection was performed at Tehran Pasteur Institute. Findings: Out of 679 samples taken, 310 (45.65%) belonged to males and 369 (54.35%) belonged to females. 7 species including 3 species of Sandfly of the genus Phlebotomus and 4 species of the genus Sergentomyia were identified among the samples, the highest percentage of catch belonged to Phlebotomus sergenti (28.57%). Of the 500 samples sent to the laboratory for testing for phleboviruses by Real-time PCR, no positive cases of Papatasi virus infection were observed in them. Conclusion: Robat Karim is one of the endemic areas of infectious diseases such as leishmaniasis. Due to climate change in this region that conditions for the growth and reproduction of Sandfly, especially Phlebotomus papatasi as a Vector of sandfly fever and since the sandfly fever disease is not vaccinated therefore, preventive measures to control and reduce diseases transmitted by Sandfly are important.

Heat waves represents a major concern for the tourism industry in the Mediterranean area. Therefore, it is necessary to deepen the study of the influence of high temperatures and their effects on tourist behavior. This research aims to develop a structural model that allows measuring how heat waves affect the behavior of external tourist demand in coastal destinations. The results are useful for the design by tourist destinations of adaptation measures to climate change. The proposed hypotheses have been contrasted using non-linear structural equations (SEM), estimated with data from the National Institute of Statistics on external demand in Spain. The results confirm lower tourist flows with the increase in high temperatures to the coasts of the Spanish Mediterranean area from traditional source markets, such as the United Kingdom. Furthermore, the tourist flow to the Balearic Islands decreases with high temperatures.

In 2023, residential and commercial sectors together consumed approximately 27.6% of total U.S. energy, equivalent to about 20.6 quadrillion Btu. Factoring in the electrical system energy losses, the residential sector represented approximately 19.7% of total U.S. energy consumption during that time. There were approximately 144 million housing units in the United States in 2023, which is increasing yearly. In this study, information on energy usage in the United States (U.S.) residential sector has been analyzed and then represented as energy intensities to establish benchmark data and to compare energy consumption of varying sizes and locations. First, public sources were identified, and data from these previously published sources were aggregated to determine the energy use of the residential sector within the US. Next, as part of this study, the energy data for seven houses/apartments from five different United States climate zones were collected firsthand. That data was analyzed, and the energy intensity of each home was calculated and then compared with the energy intensities of the other homes in the same states using RECS data. The energy intensity for each facility was calculated based on the actual energy bills. Finally, the study evaluated the carbon footprint associated with residential energy consumption in all 50 states to reinforce the importance of sustainable development initiatives.

Climate warming is expected to have pronounced effects on Arctic and Subarctic ecosystems, especially regions underlain by discontinuous and relatively warm permafrost. The main goal of this research is to evaluate the vulnerability and dynamics of permafrost under climate warming across the various ecotypes in respect of ecosystem stability, socioeconomic impact, and for better understanding possible future environmental changes. We suggested the new version of the spatially distributed permafrost dynamics model (GIPL2-MPI), which is developed in the Geophysical Institute, University of Alaska Fairbanks. This model is based on the ecosystem approach to simulate the permafrost dynamics, which we are discussing in this paper. We combined ground-based observations and numerical freeze/thaw modeling using climate-ecosystem-permafrost interactions to understand the physical processes and mechanisms controlling permafrost physical state. We predict the changes in permafrost conditions using output from two GCMs (NCAR-CCSM4 and GFDL-CM3) and Five-Model Average Ensemble for the RCP-4.5 and RCP-8.5 scaled down to 1 by 1 km spatial resolution (https://uaf-snap.org/) across entire Alaska. Our result shows that by the end of the current century widespread near-surface permafrost degradation could begin everywhere in Alaska southward of the Brooks Range as well as across some spots at the North Slope Alaska.

Scholars and policymakers see sustainability as depending on the interrelationships between the three pillars of the environment, society and the economy. However, it remains less clear how key stakeholders with a responsibility for educating the next generation perceive the concept of sustainability and act accordingly. In order to gain new insights, this research scrutinises participant perceptions on sustainability and climate change in two eco-schools in England for primary children (aged 5-11 years). Our case study involved individual interviews with classroom teachers and headteachers, group interviews with fourth- and fifth-year students (ages 10-12 years), and in-class observations. We also analysed data from student exercise books and photographs of school grounds to understand participants’ self-reported knowledge and perceptions of sustainability and climate change. Within a framework drawing on theories of science communication and transformative learning (a learning approach based on having challenging experiences), the results show that the integration of sustainability into the curriculum was limited and problematic. That is despite the fact that all students and teachers were aware of the environmental dimensions of sustainability, like climate change and the overuse of natural sources. These findings suggest that schools are no different to other institutional settings when it comes to dealing with the challenges of integrating sustainability into daily practice. We conclude that there is a need for in-service teacher education programmes to enable and motivate teachers to provide richer teaching-learning environments so as to enable effective learning in schools about sustainability and climate change.

Agriculture contributes towards South African economy, but this sector is highly vulnerable to risks imposed by climate change. Smallholder maize farmers are specifically susceptible to climate change impacts. Maize crop plays a crucial role in the country's food security as it is considered a stable food for households and source of feed for livestock. The study aimed to analyze the socio-economic factors influencing smallholder maize farmers’ willingness to adopt climate-smart agriculture. It was conducted in three different areas due to their specific agro-ecological zones. Multipurpose research design was used to gather data, and multistage random sampling to choose the study areas. Subsequently, 209 purposively selected farmers were interviewed face-to-face using structured questionnaires and focus discussion groups. Descriptive statistics and Double-hurdle regression model were used to analyze the data. Descriptive results indicated that 81%, 67%, and 63% farmers were willing to adopt CSA in Ga-Makanye, Gabaza, and Giyani, respectively. Empirical results from the first and second hurdles of the regression analysis showed that farmers’ education, crop diversification, information about CSA positively influenced the decision to adopt CSA while household size and agricultural experience negatively influenced the decision to adopt CSA. It is recommended that the Department of Agriculture, Land Reform, and Rural Development should provide CSA workshops and educational programs to farmers to enhance their knowledge and decision-making processes regarding adaptation strategies.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

Observations collected during cold season precipitation periods at Utquagvik, Alaska and at the mul-tidisciplinary drifting observatory for study of Arctic climate (MOSAiC) are used to statistically ana-lyze relations among the atmospheric water cycle parameters including the columnar supercooled liq-uid and ice amounts (expressed as liquid water and ice water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While correlation between snowfall rate and LWP is rather weak, correlations coefficients between radar-derived snowfall rate and IWP are high (~ 0.8), which is explained, in part, by generally low LWP/IWP ratios during significant precipitation. Corre-lation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r<0.3). Results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15-minute averaging versus daily averages). Observationally-based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations.

Climate change is one of the widely acknowledged challenges faced by international communities in the 21^st century. It poses challenges to fundamental elements of our understanding of appropriate goals for socioeconomic policies, such as the connection of prosperity, growth, equity and sustainable development. Human activities-induced climatic changes have been widely perceived as threatening criteria for the long-term resilience of societies and communities throughout the world. The United Nations Intergovernmental Panel on Climate Change (UNIPCC) reported that greenhouse gas (GHG) emissions due to human activities, such as the burning of fossil fuels for energy generation, is changing the climate of Earth. Despite contributing less towards the causes, poor citizens of developing countries bear a lot of its impacts. In particular, women and girls face a major impact and finally, they migrate due to the social gender division and scarcity of food. Studies on gender and climate change-induced migration are scarce. This study provides an overview of the induced impact of climate change on the livelihood, health and migration of women and girls. The aim of this study would significantly advance our understanding of the current inter-linkages between migration, displacement patterns and climate change impacts.

The promotion of active travel is deemed a crucial component of the transition to sustainable urban mobility. Several barriers hinder its policy implementation and uptake. Some evidence suggests that capacity building could be a useful tool for deepening sustainability efforts. However, a clear framework for understanding the dimensions of capacity building for active travel is lacking. Most research and findings use cases within a Global North context, constricting implications and transferability to the Global South, especially to African cities. This study responds to the dearth of scholarly work exploring Global South cases and fills a knowledge gap regarding capacity building in the case of active travel. Through a literature review, this study examines the dimensions of capacity building that are necessary to improve active travel in selected African countries. We focus on multilevel trans-portation governance, with highlights from five (5) African cities. Our findings suggest that the literature and policies on transport in Africa have key dimensions for capacity building for active travel but lack the introduction of key instruments and strategic pathways to meet these requirements for improved sustainable mobility. We propose a thematic guiding framework under three (3) levels of governance for integrating capacity building for active travel policies and implementation at institutional, individual, and environmental levels.

Understanding that organizational communication is crucial for the consistent functioning of any establishment, this research assesses its influence on work-life balance, organizational climate, and job satisfaction among Portuguese firefighters, a rarely studied group. Effective organizational communication is identified as a potential pathway for nurturing a favorable work setting and bolstering employee contentment, essential elements of work-life balance. Data compiled from a group of 102 firefighters, using a sociodemographic questionnaire, the Work Social Climate Scale, and Portuguese versions of the ICA Communication Audit Survey Instrument and the Labor Satisfaction Questionnaire S20/23, unveil multiple significant correlations among various dimensions of the ICA, the Work Social Climate Scale, and communication metrics. Explicitly, correlations were discerned between received and sent communications and aspects of implication, support, and cohesion. Links were also evident between desired communications and the control dimension. Positive and statistically significant relationships were further observed between received and sent communications, all five satisfaction dimensions, necessary outgoing communications and the physical environment, and required outgoing communications and benefits, highlighting the pivotal role of adept communication in augmenting work-life balance, organizational climate, and job satisfaction among firefighters.

The utilization of wild genera in sugarcane has been recognized as an important strategy to enhance the genetic base to impart biotic and abiotic stress tolerance in hybrid cultivars. A set of 15 Erianthus procerus derived hybrids along with five popular check varieties were evaluated for two years (2018–19 and 2019–20) for agro-morphological, quality, physiological traits and three years (2018–19, 2019–2020, and 2020–21 for winter sprouting potential. The E. procerus hybrid GU 12-19 recorded the highest winter sprouting potential with a winter sprouting index (WSI) of 10.6 and a percent superiority of 279 over best check (Co 0238) followed by GU 12-22 with WSI: 8.5 and % superiority over best check was 204. The other top-performing hybrids, GU 12-21 and GU 12-29, recorded the excellent winter sprouting potential with WSI of 7.2 and 6.9 respectively. The four E. procerus hybrids identified with higher WSI were also resistant to the prevalent races of red rot in both tropical and subtropical conditions. The association analysis revealed significant correlations between various traits, particularly fibre content with a maximum number of associations, which indicates its multifaceted impact on sugarcane characteristics. Principal component analysis (PCA) summarized the data, explaining 57.6% of the total variation for measured traits and genotypes, providing valuable insights into the performance and characteristics of the E. procerus-derived hybrids under subtropical climate. The anthocyanin content of E. procerus hybrids was better than the check varieties with a mean of 0.147 (2018–19) and 0.144 (2019–20) and range of 0.123–0.179 (2018–19) and 0.111–0.172 (2019–20), anthocyanin plays a vital role in mitigating the cold injury, acting as an antioxidant in cool weather conditions, particularly in sugarcane. Further, seven hybrids recorded more than 22% fibre threshold, indicating their industrial potential. These hybrids would be potential donors for cold tolerance and high ratooning ability along with red rot resistance under subtropical climate.

In the pursuit of sustainable solutions for carbon dioxide CO2 sequestration and emission reduction in the steel industry, this study presents an innovative integration of steelmaking slag with the modified Solvay process for sodium bicarbonate (NaHCO3) synthesis from saline brines. Utilizing diverse minerals, including electric arc furnace (EAF) slag, olivine, and kimberlite, the study explored their reactivity under varied pH conditions and examined their potential in ammonium regeneration. Advanced techniques such as XRD and ICP-OES were employed to meticulously analyze mineralogical transformations and elemental concentrations. The findings demonstrate that steelmaking slag, owing to its superior reactivity and pH buffering capabilities, outperforms natural minerals. The integration of finer slag particles significantly elevated pH levels, facilitating efficient ammonium regeneration. Geochemical modeling provided valuable insights into mineral stability and reactivity which aligned with the ICP-OES results. This synergistic approach not only aids in CO2 capture through mineral carbonation but also minimizes waste, showcasing its potential as a sustainable and environmentally responsible solution for CO2 mitigation in the steel industry.

Coasts are characterized by high biological and ecological productivities, and are theatre of strategic economic activities, including tourism, fishing and aquaculture. Both anthropic and natural hazards can thus affect coasts, causing their deterioration. The monitoring of coasts in terms of evolution, adaptation, contamination and resilience, is a pivotal point composed of both classic measurement approaches, and innovative approaches as remote sensing and the use of unmanned aerial vehicles. In the last years, climate change is increasing its effects all over the world and coasts are a delicate system suffering these effects particularly. Climate change has important impacts on coasts, with a serious consequence represented by sea level rise. The latter causes coastal erosion, leading to ecological and economic issues and with consequences for human health. The Mediterranean Basin, which has always represented an important crossroads of different civilizations and economic and cultural exchanges, is now threatened by the consequences of climate change. This area is decribed as an example of coastal system of strategic importance and subjected to serious challenges. Engineering interventions are countermeasures to cope with coastal erosion and coastal degradation. These countermeasures are aimed at protecting the coasts and the populations living on the coasts. The types of intervention can be defined of hard engineering, as in the case of fixed structures in concrete, and of soft engineering, with structures of protection builted according to the principles of nature. Engineering procedures provide coastal benefits, although they can cause further coastal damage. It is thus necessary to protect the coasts and the same time actions aimed at mitigating climate change must be implemented, according to the rules of sustainability.

Background: The seasonal variation of peptic ulcers is a rhythmic phenomenon reported worldwide, exhibiting diverse patterns and controversies. Unfortunately, it has remained an unresolved mystery for more than 90 years. Numerous studies have found that this phenomenon was closely associated with multiple environmental factors, but the underlying mechanism has never been elucidated. Objectives: This study aims to elucidate the seasonal variation of peptic ulcers and identify the role of environmental factors in the disease. Methods: Based on a recently identified etiology of peptic ulcers, two inverse operations in calculus, differentiation and integration, are iterated to analyze the existing data. First, the fluctuation curve in the seasonal variation is differentiated twice into the monthly incidences caused by multiple individual environmental factors, and the fluctuation curve due to each individual environmental factor is generated separately. Second, the monthly incidences caused by the individual environmental factors are integrated twice to reproduce the fluctuation curves in the seasonal variation of peptic ulcers. Results: The differentiations of the fluctuation curves in the season variation reveal a parallel relationship between the psychological impacts of each individual environmental factor and the monthly incidences of peptic ulcers. The integrations of the monthly incidences caused by 3 environmental factors reproduce the fluctuation curves in 3 representative seasonal patterns of peptic ulcers but make the parallel relationships invisible. Discussion: The parallel relationships revealed a causal role of environmental factors in peptic ulcers, whereas the reproduction of the fluctuation curves elucidated that multiple environmental factors cause the seasonal variation of peptic ulcers by Superposition Mechanism. The regional differences in environmental factors result in the diverse patterns, as well as the controversy questioning the seasonality of peptic ulcers. Significantly, the data analyses exemplify the application of a new concept, Superposition Mechanism, which might be an indispensable methodological complement to life science and medicine.

In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for the introduction and establishment of these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed by these emergent infections.

Shallow Geothermal Energy (SGE) exchanges heat with the ground. In continuous long-term operation, the initial temperature field can be disturbed, and subsurface thermal plumes can be developed. In this paper, the thermal impact of a SGE system under Mediterranean climate is handled. Temperature recordings from 104 thermal probes placed in depth along 15 monitoring boreholes are analysed. Those boreholes were drilled 1-2m from thermos-active boreholes of the case study system installed in a university building. The analysis handles one year of SGE system operation. Temperature depth profiles, reaching up to 140 m depth, were registered with a 10-minute time-step resulting in a large amount of data. Ground thermal conductivity was estimated experimentally and semi-empirically allowing to compute the initial undisturbed ground temperature profiles and compare it with the monitored values. Climate data was recorded by the university meteorological station. Globally, the measured and computed data were coherent and a non-negligible impact of the SGE system operation in the first year was observed. The building orientation as well as the nearby departments had significant impacts on shallow ground temperature. Maximum ground temperature changes, ranging from 2 to 3º C as observed in different boreholes indicating that the system is operating efficiently.

Using a variety of theoretical foundations, this paper examines the association between corporate social responsibility (CSR) and employees’ knowledge-sharing behavior, investigating the sequential mediation role of perceived organizational support and organizational commitment as well as the moderating role of ethical climate. Hypotheses were formulated to address both the sequential mediation effect of perceived organizational support and organizational commitment on the link between CSR and knowledge-sharing and the moderation effect of ethical climate on the relationship between CSR and perceived organizational support. In order to mitigate the problems of potential common method bias, data were gathered from a sample of 204 South Korean employees at three distinct time points. The results of the study offer compelling evidence that CSR activities exert a positive influence on employees’ knowledge-sharing behavior, an effect that is sequentially mediated by both perceived organizational support and organizational commitment. Furthermore, the research uncovers the positive moderating role played by ethical climate in the relationship between CSR and perceived organizational support. By integrating multiple theoretical frameworks, this study not only advances the extant literature but also offers invaluable insights for organizations striving to bolster knowledge-sharing through the strategic implementation of CSR initiatives.

As a part of the European Green Deal, the Corporate Sustainable Reporting Directive will apply to over 50,000 companies in Europe, meant to advance the quality of sustainability reporting in the EU, and reduce global emissions and emission distribution inequality. Part of the requirements centre around organisational emission quantification, which will bring much attention to the methodological aspects and resulting decision support capability, which calls for synthesis and argues for clarity. Currently, quantifying the emissions embedded in global transactions mostly focus on direct value-chain attributes, and do not consider unintended consequences beyond the scope of assessment. To achieve genuine reductions, estimated emissions must be considered from a systems perspective to accurately reflect their true impact. While emission inventories serve several purposes, incorrect application limits their potential. The CSRD aligns itself with the GHG Protocol, which does not explicitly facilitate this distinction, although new Land Sector and Removals Guidance draft does, in part. With first CSRD reports expected in 2025, and the GHG protocol entering a revisions period, it presents an opportunity to marry systems thinking with carbon literacy, thereby equipping the expected surge of activity with the sufficient tools for an accelerated transition.

Fungi constitute a diverse group with highly positive and negative impacts in different envi-ronments, having several natural roles and beneficial applications in human life, but also caus-ing several concerns. Fungi can affect human health directly, but also indirectly by being detri-mental for animal and plant health influencing food safety and security. Climate changes are al-so affecting fungal distribution, prevalence, and their impact on different settings. Searching for sustainable solutions to deal with these issues is challenging due to the complexity of the inter-actions among fungi and agriculture, animal production, environment, and human health. In this way, the “One Health” approach may be useful to get some answers since it recognizes that human health is closely connected to animal and plant health, as well as to the shared environ-ment. This review aims to explore and correlate each of those factors influencing human health in this “One Health” perspective.

In this study we investigated the association between weather types (WTs) and the Urban Heat Island Intensity (UHII) in the region of Attica (Greece). The application of the methodology results in ten WTs over Attica region. The UHII was calculated for every hour of the day from 2008 to 2017, using a new air temperature dataset produced by Copernicus Climate Change Service. To have more clear results concerning the association between WTs and UHII, we have used also the upper 5% of UHII (Urban Overheating-UO). The UO have been estimated for two-time intervals (daytime and nighttime) and for the warm period (June-September). The UHII frequency distribution as well as the spatial characteristics of the UO were also investigated. It was found that UO was amplified under WT2 during the night while, WT10 was mainly responsible for exacerbated UO magnitude at daytime, in all months. Furthermore, analysis results revealed that the UO effect is more pronounced in Athens during the night, especially at Athens center. The daytime hot-spots identified mainly in sub-urban and rural areas. Therefore, this methodology may help for heat mitigation strategies and climate adaptation measures, in urban environments.

Species diversity has been shown to be influenced by environmental factors, but the mechanism underlying their relationship remains unclear across spatial scales. Based on field investigation data collected from 3,077 sample plots in temperate forest ecosystems, we compared tree species richness, evenness and dominance at 10 km × 10 km, 30 km × 30 km and 90 km × 90 km spatial scales. Then, we detected the scale dependence of changes in tree species composition on climate, topography and forest structure using variation partitioning and quantified their contribution to tree diversity with gradient boosted models (GBMs) and fitted their relationships. The magnitude of tree richness, evenness and dominance significantly increased with spatial scale. Ecological factors jointly accounted for 24.3%, 26.5% and 38.5% of the variation in tree species composition at the three spatial scales, respectively. Annual mean temperature had a strong impact on tree richness, evenness and dominance and peaked at an intermediate scale. Tree evenness and dominance increased with the variation of temperature but had upper and lower limits. Tree richness obviously increased with annual precipitation on multiple scales and decreased with annual sunshine duration at large spatial scale. Tree richness, evenness and dominance obviously increased with the variation elevation and diameter at breast height at large scales and small scales, respectively. Tree dominance decreased with tree height in a hump at small scale. The dependence of tree diversity on ecological factors increased with spatial scales. Furthermore, different factors exert various controls on tree diversity at different spatial scales, representing a comprehensive mechanism regulating tree diversity.

Accurate detection and quantification of regional vegetation trends is essential for understanding the dynamics of landscape ecology and vegetation distribution. We applied a comprehensive trend analysis to satellite data to describe geo-spatial changes in vegetation along the Pacific slope of Peru and northern Chile, from sea level to the continental divide, a region characterised by biologically unique and highly sensitive arid and semi-arid environments. Our statistical analyses show broad regional patterns of positive trends in EVI, called “greening” alongside patterns of “browning” where trends are negative between 2000 and 2020. The coastal plain and foothills, up 1000m, contain notable greening of the coastal Lomas and newly irrigated agricultural lands occurring alongside browning trends related to changes in land use practices and urban development. Strikingly, the precordilleras show a distinct ’greening strip’ which extends from approximately 6°S to 22°S, with an altitudinal trend; ascending from the tropical lowlands (170-780 m) in northern Peru, to the subtropics (1000-2800 m) in central Peru, and temperate zone (2600-4300 m) in southern Peru and northern Chile. We find that the geographical characteristics of the greening strip do not match climate zones previously established by Köppen and Geiger. Greening and browning trends in the coastal deserts and the high Andes lie within well defined climatic and life zones, producing variable but identifiable trends. However, the distinct Pacific slope greening presents an unexpected distribution with respect to the regional Köppen-Geiger climate and life zones. This work provides insights on understanding the effects of climate change on Peru’s diverse ecosystems in highly sensitive, biologically rich arid and semi-arid environments on the Pacific slope.

In this study, the application of the main algorithms used for SDM, namely Boosted Regression Tree (BRT), Generalized Linear Model (GLM), Multivariate Adaptive Regression Splines (MARS), Maximum Entropy (MAXENT) and Random Forest (RF), were considered in order to simulate the citrus probability of distribution in a Mediterranean area, based on presence data and a random background sample, and in relation to several predictors. The predictors were grouped under 19 bioclimatic variables, elevation described through a Digital terrain model, soil physical properties, and irrigation. Sensitivity analysis was carried out by: modifying the values of the main models’ parameters; and reducing the input presence points.

South Italy is characterised by a semi-arid climate with scarce rain and high evaporative demand, therefore the need to optimise water resources in this area is crucial, and climate change could worsen this condition. In citrus cultivation, which is one of the most important crops bred in Southern Italy, and more generally in Mediterranean regions, deficit irrigation strategies are im-plemented in order to cope with limited resource availability. On this basis, knowledge on how the territorial distribution of citrus would change in relation to these strategies constitutes valuable information for the stakeholders. Therefore, the objective of this study was to determine the prob-ability of presence of citrus in Sicily at changing of the percentage of water deficit application, in order to analyse change in the surface area and localisation of the crop. The methodology was based on the application of Species Distribution Models and Geographic Information Systems to the case study of the Province of Syracuse in Sicily. Different geostatistical and machine learning models were applied, based on 3-decades bioclimatic variables, DTM and irrigation; assessment of the outcomes was carried by using classification evaluation metrics. The analysis of the outcomes showed that uncorrelated predictor layers mainly included water input that affected most the probability of presence. Moreover, GIS analyses showed that deficit irrigation strategies would generate an overall reduction of cultivation surfaces in the territory and a decrease of citrus pres-ence in southern areas of the considered territory, where climate conditions are less favourable in terms of temperature and precipitations, thus providing useful information for decision support tools in agriculture and land use policy.

The article describes the methodology of the experimental analysis of operational and cost-effective assessment using geographic information system (GIS) technologies, as opposed to the assessment of the tourism potential of the nature of the Fergana Valley in Uzbekistan using long term and costly classical approaches. Based on the ArcGIS (10.8) grid index approach of 20 natural geographical indicators of the valley, such as geographical location, relief, climate, hydrographic and biological, the level of tourism comfort was determined and the location of 6 tourist-recreation zones were defined. The level of accuracy of the tourist-recreational zones all situated utilizing GIS technologies was confirmed by field-expedition approaches.