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The scientific discourse on climate change throughout the US has primarily revolved around changes in mean climate and/or climate extremes. However, little is known about the impacts of climate change on mild weather conditions despite its significant relevance to quality of life. Here, we adopt the concept of "outdoor days" defined as those relatively pleasant days when most people may enjoy outdoor activities (Choi et al., 2024). We project how climate change reshapes seasonality of US outdoor days: relatively large drops in summer, late spring, and early fall; and a significant increase in winter. However, annual outdoor days are projected to change slightly, with notable exceptions. We project relatively large drops in southeast (−23%), south (−19%), and Ohio Valley (−19%), and a significant increase in northwest (14%) toward the end of the century. Our findings have implications for quality of life in different regions, and for nation‐wide travel and tourism. Plain Language Summary: Here, we contribute to the understanding of how climate change will influence quality of life in the US by applying the concept of outdoor days—thermal comfort conditions allowing for outdoor activities, such as walking, jogging, and cycling by most people. We project using state‐of‐the‐art global climate models that climate change will shift the seasonality of outdoor days, resulting in less frequent outdoor days in summer and more frequent outdoor days in the other seasons across the country. Our results highlight specific regional hotspots in the US where annual outdoor days could significantly decrease or increase with important implication for quality of life in different climate regions of the US. Key Points: We project how climate change reshapes seasonality of US outdoor daysFuture climate change will likely result in a northwest‐southeast disparity in the projected change of annual outdoor days in the USWe provide new evidence of the impact of global warming on the quality of human life, travel, and tourism in the US [ABSTRACT FROM AUTHOR]

This study assesses the impact of climate change on streamflow characteristics in the Lualaba River Basin (LRB), an important yet ungauged watershed in the Congo River Basin. Two conceptual hydrological models, HBV-MTL and GR4J, were calibrated using the reanalysis datasets and outputs of Generalized Circulation Models (GCMs) under CMIP6 during the historical period. The hydrological models were fed with outputs of GCMs under shared socioeconomic pathways (SSPs) 2-45 and 5-85, moderate- and high-radiative future scenarios. The results demonstrate that hydrological models successfully simulate observed streamflow, but their performance varies significantly with the choice of climate data and model structure. Interannual streamflow (Q) percentiles (10, 50, 90) were used to describe flow conditions under future climate. Q10 is projected to increase by 33% under SSP2-45 and 44% under SSP5-85, suggesting higher flow conditions that are exceeded 90% of the time. Q50 is also expected to rise by almost the same rate. However, a considerably higher Q90 is projected to increase by 56% under the moderate- and 80% under the high-radiative scenario. These indicate the overall higher water availability in this watershed to be used for energy and food production and the need for flood risk management. [ABSTRACT FROM AUTHOR]

Key message: A novel periodic site index is introduced for the quantification of dynamic forest site productivity. The measure is age-independent, sensitive to environmental changes and efficient for the estimation and prediction of stand height and stand volume increment. Context: Accurate and up-to-date prediction of site productivity is crucial for the sustainable management of forest ecosystems, especially under environmental changes. Aims: The aim of this study was to introduce a novel concept: a periodic site index based on growth-effective age for the quantification of dynamic forest site productivity. Methods: The growth-effective age based periodic site index is estimated from repeated or multi-temporal measurements of stand dominant height. Furthermore, a recursive procedure to update the underlying site index model is presented by using repeated measurements of stand dominant height. The database used in this study comprised repeated measurements of 945 Norway spruce (Picea abies L.) experimental plots at 508 different locations in Southwest Germany. Results: The evaluation shows that periodic site index is statistically superior to the conventional site index, based on chronological stand age, for estimating stand height and stand volume increment. The analysis of temporal differences between growth-effective stand age and chronological stand age and between periodic site index and conventional site index in the period 1900 to 2020 reveals trends referring to stand age and site productivity, which corroborate earlier regional studies on forest growth trends due to environmental changes. Conclusions: The periodic site index is a better indicator for site productivity than conventional site index. Under conditions of environmental changes, conventional site index is biased, whereas the growth-effective age based site index provides an unbiased estimate of stand height development. With the more widespread application of remote sensing techniques, such as airborne laser scanning, the availability of multi-temporal stand height data will increase in the near future. The novel concept provides an adaptive modeling approach perfectly suited to these data for an improved estimation and prediction of forest site productivity under environmental changes and can straightforwardly be applied also to uneven-aged and multi-species stands. [ABSTRACT FROM AUTHOR]

This study harnesses Geographic Information Systems (GISs) and the Analytical Hierarchy Process (AHP) to identify optimal areas for olive cultivation in Jordan amidst the challenges of climate change. Recognizing the olive tree's economic, environmental and cultural significance in the Mediterranean, this research focuses on the impact of altered climatic conditions, such as rising temperatures, shifting precipitation patterns and increased weather extremes, over the period from 1994 to 2021. By integrating climatic and topographical data, including factors such as altitude, slope, aspect and temperature variations, a multi-criteria analysis pinpoints regions suitable for sustainable olive agriculture. The methodology combines GIS-based spatial analysis with AHP to assess the suitability of various regions for olive farming, taking into account the complex interplay between climate and topography. This approach allows for the evaluation of potential agricultural zones under both current and projected climate scenarios, highlighting northern and western Jordan as areas with the highest suitability due to favorable precipitation and temperature conditions. The results of this study are vital for strategic agricultural planning, offering insights that can help enhance the resilience of olive production against climate variability. By identifying regions with optimal growing conditions and suggesting adaptive strategies, this research aims to support policymakers, agricultural developers and farmers in making informed decisions that ensure the sustainable future of olive farming in Jordan. [ABSTRACT FROM AUTHOR]

This paper introduces a generalized approach structured for the systematic supervising and the performance assessment of drought environments. A significant part of the Time Series Analysis module is taking the history of drought-related parameters measures and giving more detail on the progress and the intensity of the drought esvents. Moreover, Deep Learning algorithms are used to train data sets and to make predictions about future values. The research was done using the multimodal technique (which encompasses machine learning approaches and data-driven analysis based on the satellite images of many sources) for the dispelling of the drought problem in Maharashtra, India in 2018 to 2021 in a bid to disseminate information. With respect to this issue, thorough and prompt drought estimation is a top concern to the successful management of these threats through water resource management. The study adopted the use of new models such as ConvLSTM2D, LSTM models, ARIMA and Random Forest regression to improve drought monitoring. Experimental results were scrutinized and illustrated with performance measures like R-squared, mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). LSTM algorithm demonstrated a very strong potential for learning extended connections and sequences. ARIMA method was more likely to catch the seasonal patterns. The ConvLSTM2D algorithm was enforced to enhance the drought monitoring process. It is as a result of this improvement that both drought evaluation and prediction matured, ultimately enabling more informed decision-making in a bid to manage the crisis as early as possible with mitigation measures being immediately put in place. [ABSTRACT FROM AUTHOR]

Abstract Key message A novel periodic site index is introduced for the quantification of dynamic forest site productivity. The measure is age-independent, sensitive to environmental changes and efficient for the estimation and prediction of stand height and stand volume increment. Context Accurate and up-to-date prediction of site productivity is crucial for the sustainable management of forest ecosystems, especially under environmental changes. Aims The aim of this study was to introduce a novel concept: a periodic site index based on growth-effective age for the quantification of dynamic forest site productivity. Methods The growth-effective age based periodic site index is estimated from repeated or multi-temporal measurements of stand dominant height. Furthermore, a recursive procedure to update the underlying site index model is presented by using repeated measurements of stand dominant height. The database used in this study comprised repeated measurements of 945 Norway spruce (Picea abies L.) experimental plots at 508 different locations in Southwest Germany. Results The evaluation shows that periodic site index is statistically superior to the conventional site index, based on chronological stand age, for estimating stand height and stand volume increment. The analysis of temporal differences between growth-effective stand age and chronological stand age and between periodic site index and conventional site index in the period 1900 to 2020 reveals trends referring to stand age and site productivity, which corroborate earlier regional studies on forest growth trends due to environmental changes. Conclusions The periodic site index is a better indicator for site productivity than conventional site index. Under conditions of environmental changes, conventional site index is biased, whereas the growth-effective age based site index provides an unbiased estimate of stand height development. With the more widespread application of remote sensing techniques, such as airborne laser scanning, the availability of multi-temporal stand height data will increase in the near future. The novel concept provides an adaptive modeling approach perfectly suited to these data for an improved estimation and prediction of forest site productivity under environmental changes and can straightforwardly be applied also to uneven-aged and multi-species stands.

This study examines the possible effects of climate change on sorghum in the western zone (WZ) comprising Coimbatore, Tirupur, and Erode districts of Tamil Nadu. The DSSAT crop simulation model was used to simulate sorghum yields with considering various planting dates and amounts of fertilizer application. The downscaled CCSM4 climate model data was utilized for the historical baseline period spanning from 1991 to 2020, as well as for future pridicted data from 2021 to 2099, under the RCP 4.5 scenarios. The key findings indicate that there is a projected yield decline range of -1.3% to -12.5% for the near century (2021-2040), -6.2% to -23.7% for the mid-century (2041-2070), and -12.6% to -30.5% for the end century (2071-2099). The sorghum yield experiences a high decrease at the end of the century (276.83 kg ha-1), mid-century (178.16 kg ha-1), and lastly in the near century (89.4 kg ha-1). The study revealed that a enhanced fertilizer application can have a minor positive effect on sorghum productivity. The study underscores the significant threat that climate change poses to food security in Tamil Nadu and emphasizes the need for adaptation strategies to protect agricultural productivity. [ABSTRACT FROM AUTHOR]

Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one‐way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate‐induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O3 episodes using extreme value theory, and extend the approach to projections of mid‐ and end‐century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O3 concentrations by over 2.3 ppb on average across the U.S. at mid‐century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non‐compliance due to a climate‐induced increase in frequency of high ozone days. Plain Language Summary: Climate change can worsen O3 air pollution across much of the U.S., threatening environmental policy goals and posing health risks. Projections of this impact rely on models that have uncertainties associated with simulating future climate. We investigated the influence of uncertainty from climate sensitivity, or the simulated change in Earth's average surface temperature in response to an increase in atmospheric CO2, on projections of air quality using a collection of simulations. To improve O3 estimates based on model simulations, we applied a new bias correction method to the model concentrations that accounts for spatial differences in atmospheric pollution. Then, we applied extreme value statistics to describe the behavior of the highest O3 concentrations. We found that, under climate change, the most polluted days worsen and occur more frequently, making it more difficult to meet air quality standards in highly populated regions and suggesting that continued efforts to mitigate pollutant emissions are necessary to counteract climate change's effects on O3. Further, our results indicate that the model's climate sensitivity is as influential as greenhouse gas emissions scenario for mid‐century projections, showing that the strength of the earth system's response to greenhouse gas levels is a critical consideration when simulating climate impacts. Key Points: We project climate impacts on US ozone episodes with spatially varying bias correction and a climate and air quality simulation ensembleClimate sensitivity can be as influential as GHG scenario without air pollutant emissions changes in mid‐century ozone episodesClimate‐induced increases in ozone pollution may increase risk of not meeting air quality standards in several areas of the U.S. [ABSTRACT FROM AUTHOR]

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets. [ABSTRACT FROM AUTHOR]

Yerba mate (Ilex paraguariensis) is renowned for its nutritional and pharmaceutical attributes. A staple in South American (SA) culture, it serves as the foundation for several traditional beverages. Significantly, the pharmaceutical domain has secured numerous patents associated with this plant's distinctive properties. This research delves into the climatic influence on yerba mate by leveraging the CMIP6 model projections to assess potential shifts brought about by climate change. Given its economic and socio-cultural significance, comprehending how climate change might sway yerba mate's production and distribution is pivotal. The CMIP6 model offers insights into future conditions, pinpointing areas that are either conducive or adverse for yerba mate cultivation. Our findings will be instrumental in crafting adaptive and mitigative strategies, thereby directing sustainable production planning for yerba mate. The core objective of this study was to highlight zones optimal for Ilex paraguariensis cultivation across its major producers: Brazil, Argentina, Paraguay, and Uruguay, under CMIP6's climate change forecasts. Our investigation encompassed major producing zones spanning the North, Northeast, Midwest, Southeast, and South of Brazil, along with the aforementioned countries. A conducive environment for this crop's growth features air temperatures between 21 to 25 °C and a minimum precipitation of 1200 mm per cycle. We sourced the current climate data from the WorldClim version 2 platform. Meanwhile, projections for future climatic parameters were derived from WorldClim 2.1, utilizing the IPSL-CM6A-LR model with a refined 30-s spatial resolution. We took into account four distinct socio-economic pathways over varying timelines: 2021–2040, 2041–2060, 2061–2081, and 2081–2100. Geographic information system data aided in the spatial interpolation across Brazil, applying the Kriging technique. The outcomes revealed a majority of the examined areas as non-conducive for yerba mate cultivation, with a scanty 12.25% (1.5 million km2) deemed favorable. Predominantly, these propitious regions lie in southern Brazil and Uruguay, the present-day primary producers of yerba mate. Alarming was the discovery that forthcoming climatic scenarios predominantly forecast detrimental shifts, characterized by escalating average air temperatures and diminishing rainfall. These trends portend a decline in suitable cultivation regions for yerba mate. [ABSTRACT FROM AUTHOR]

This study is the first to develop food supply and demand projections over the 21st century for Uzbekistan by considering the combined effects of climate change and soil salinization. The study results suggest that rising summer temperatures and soil salinity will considerably reduce wheat production. Projections indicate that a large wheat supply–demand gap will emerge in the midterm, particularly under the SSP3-RCP7.0 scenario. For the two more pessimistic scenarios, supply losses of about 24–29% are expected by the end of the century. Supply–demand gaps of up to 2.7 million tons of wheat would pose serious challenges to national food security. [ABSTRACT FROM AUTHOR]

Rice plants (Oryzae Sativa sp.) are rice-producing food plants which play an important role in economic life in Asian countries, especially Indonesia. This primary need is very difficult to replace with other staples, such as corn, tubers, sago and other sources of carbohydrates. However, global climate change which has an impact on climate anomalies causes rice diseases to develop rapidly. The aim of this research is to create an application on an Android-based cell phone that can identify and classify rice plant diseases using the Convolutional Neural Network (CNN) method. The research material was 1600 images of rice leaves consisting of 4 classes, namely 400 images of rice affected by Leaf Blight disease, 400 images of rice affected by Brown Spot disease, 400 images of rice affected by Leaf Smut disease, and 400 images of healthy rice. In each class, the images are divided into 380 for training and 20 for testing. During the rice image training process using the Python programming language, the accuracy results were 83%. Then the results are saved in the form of a model file, and entered as training data into the program in Android Studio to be used as an application. Testing the application with 20 rice leaf images for each class resulted in an actual accuracy of 94%. This application can also be run on all versions of Android. [ABSTRACT FROM AUTHOR]

Abstract The scientific discourse on climate change throughout the US has primarily revolved around changes in mean climate and/or climate extremes. However, little is known about the impacts of climate change on mild weather conditions despite its significant relevance to quality of life. Here, we adopt the concept of “outdoor days” defined as those relatively pleasant days when most people may enjoy outdoor activities (Choi et al., 2024). We project how climate change reshapes seasonality of US outdoor days: relatively large drops in summer, late spring, and early fall; and a significant increase in winter. However, annual outdoor days are projected to change slightly, with notable exceptions. We project relatively large drops in southeast (−23%), south (−19%), and Ohio Valley (−19%), and a significant increase in northwest (14%) toward the end of the century. Our findings have implications for quality of life in different regions, and for nation‐wide travel and tourism.

Methods for assessing the groundwater-dependent ecosystems (GDEs) risk remain underexplored, particularly concerning the threat of groundwater pollution. This article presents the application of the DIRECT index – a multicriteria indicator – designed for the coupled assessment of groundwater vulnerability to pollution (GV) and the risk affecting GDEs. This ecological indicator modifies the DRASTIC index to enable the assessment of GDEs pollution risk and provide a more holistic approach. The assessment of GV and GDEs risk was conducted in areas with varying hydrogeological and geomorphological conditions within a temperate climate zone in Poland (Central Europe). In the reference scenario, GV was categorized as high and very high, constituting 53% and 41% in the Świder and Wisłok study areas, respectively. Spatial variability in GV was noted, with the highest values observed in river valleys where the majority of GDEs are located. The proportion of areas with very high and high-risk GDEs accounted for 73% and 44% of the total GDEs area in the study regions, respectively. Additionally, 59% and 45% of all springs in these areas were situated in zones deemed to have extremely high and high GDEs risk, respectively. A further objective of this study was to project how GV and the associated risk to GDEs might evolve up to the years 2050 and 2100. Four climate change scenarios were examined under the RCP4.5 and RCP8.5 emission pathways. The projections indicated that climate change effects, primarily increases in groundwater recharge, could elevate the pollution risk to GDEs by 2050, with a potential slight reduction by 2100. The application of the DIRECT index facilitated a scenario-based assessment of GV coupled with an evaluation of pollution risk to GDEs. This approach should prove beneficial for managing this risk in the context of climate change and aid in preserving the overall ecological status of GDEs.

The combined effects of climate and land cover changes influence hydrologic responses of a basin in an offsetting or synergistic manner depending on the nature and severity of the changes. As such, estimating the impacts of these environmental changes on hydrologic responses is crucial for planning water resources management. However, such a comprehensive study is missing in most basins of Ethiopia, particularly in the Dhidhessa River basin (DRB). The aim of this study is, therefore, to quantify the combined and separate impacts of land cover and climate changes on multiple hydrologic variables for the DRB. The Calibrated Soil and Water Analysis Tool (SWAT) model and statistical techniques were integrated for this study. Quantifying the separate and combined effects of land cover and climate changes on multiple hydrologic responses at a local scale, and determining the relative contribution of the changes are the strength of this study. The result indicated better performance of the SWAT model in simulating water balance components for the DRB. Significant changes in hydrologic responses were observed in response to the land cover changes, and the increasing trends of temperature and rainfall observed during the last 30 years in DRB. The result showed increasing actual evapotranspiration (AET), streamflow, and surface runoff while decreasing groundwater recharge. Surface runoff was more affected by land cover change than by climate change, whereas streamflow and AET were more affected by climate change than land cover change during the last 30 years in the basin. The combined effects of land cover and climate changes played an offsetting effect on groundwater recharge and AET. Overall, the simulated hydrologic responses will have negative effects on water resource availability and agricultural production in the basin and the surroundings. Therefore, implementing integrated watershed management strategies, such as soil and water conservation and afforestation, could minimize the negative impact. [ABSTRACT FROM AUTHOR]

The increasing temperature and variability in precipitation, in terms of both frequency and intensity, are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extremes in the Kabul River Basin (KRB) of the western Himalaya using high-resolution climate datasets. We selected four representative General Circulation Model (GCM) runs from Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, based on future projections, climatic extremes and their abilities to represent the historical climate cycle (1981–2010) of KRB. The seasonal analysis of precipitation shows decreasing pattern during the winter and pre-monsoon seasons and annual mean temperature will increase consistently by 3 to 5 °C in RCP4.5 and 8.5 scenarios. Ten indices were selected to study climatic extremes pertaining to the health, agriculture and water resources sectors. The extremes, like consecutive summer days, warm days and heatwaves, will increase, whereas the frost days, cold nights, cold waves and extreme precipitation days will decrease towards the end of this century. Besides, the extremes are not homogenous in time and space. Based on the results of this study, there is a need for prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build resilient livelihoods in the KRB. [ABSTRACT FROM AUTHOR]

Purpose: The degrading impacts of livestock production on the environment are well acknowledged. Although ruminants are much studied due to their large contribution to climate change impact, monogastrics are also known to carry a significant load, and mitigation options need investigation. Here, the climate change impact and water scarcity impact of Finnish pork production was investigated using the life cycle assessment approach. Methods: As the importance of communicating reliable environmental information has been acknowledged in the EU, methods and guidance for this purpose have been developed. Product Environmental Footprint Category Rules have also been published for several food product categories, although not yet for meat. Here, the life cycle assessment methods were used based on PEFCR guidance and the draft version of red meat PEFCR guidance to achieve a reliable, transparent and comparable assessment. Results: Finnish pork production resulted in a climate change impact of 3.6 kg CO2 eq. kgCW−1 and a water scarcity impact of 0.69 m3 eq. kgCW−1. The largest contribution to the climate change impact came from feed crop production, with an impact of 43%. Land-use changes were included, and their contribution to the Finnish pork climate change impact was 3%. Similarly, in the water scarcity impact, feed crop production was a major contributor, with 41% from fattening pig feed production. Significant contributions to both categories also came from piglet production, including feed crop production, and to the climate change impact from manure storage. Conclusions: Finnish production was seen to already largely utilise sidestreams and domestic feed ingredients, although, e.g. soybean is still used. Based on the results, in mitigating the environmental impacts of Finnish pork production, attention should especially be paid to the resource-efficient production of domestic feed crops and reduced use of organic soils. As current assessment models are unable to grasp the impacts of regenerative farming techniques, the development of LCA methods is also required. Water scarcity impact was seen to be largely affected by the utilisation of feed crops originating from water-scarce countries. As a mitigation measure, the procurement of these feed crops and ingredients should therefore be directed to water-abundant areas and from production which does not depend on irrigation water or the extensive use of synthetic inputs. [ABSTRACT FROM AUTHOR]

Today, a major challenge for climate science is to overcome what is called the “usability gap” between the projections derived fromclimate models and the needs of the end-users. Regional Climate Models (RCMs) are expected to provide usable information concerning a variety of impacts and for a wide range of end-users. It is often assumed that the development of more accurate, more complex RCMs with higher spatial resolution should bring process understanding and better local projections, thus overcoming the usability gap. In this paper, I rather assume that the credibility of climate information should be pursued together with two other criteria of usability, which are salience and legitimacy. Based on the Swiss climate change scenarios, I study the attempts at meeting the needs of end-users and outline the trade-off modellers and users have to face with respect to the cascade of uncertainty. A conclusion of this paper is that the trade-off between salience and credibility sets the conditions under which RCMs can be deemed adequate for the purposes of addressing the needs of end-users and gearing the communication of the projections toward direct use and action. [ABSTRACT FROM AUTHOR]

An innovative process layout for sludge waste management based on chemical looping combustion and flue gas methanation is analyzed in this work. The technical performance of the system was assessed by considering that the flue gas is first purified and then mixed with a pure hydrogen stream sourced from an array of electrolysis cells to produce methane. The life cycle assessment (LCA) and life cycle cost (LCC) methodologies were applied to quantify the environmental and economic performances of the proposed process, and a hotspot analysis was carried out to recognize its most critical steps. The proposed system was then compared with a reference system that includes both the conventional waste management pathways for the Italian context and methane production. Finally, to account for the variability in the future economic climate, the effects of changes in landfill storage costs on sewage end-of-life costs for both the proposed and reference systems were evaluated. With respect to 1 kg/h of sewage sludge with 10%wt of humidity, the analysis shows that the proposed system (i) reduces landfill wastes by about 68%, (ii) has an end-of-life cost of 1.75 EUR × kg−1, and (iii) is environmentally preferable to conventional sewage sludge treatment technologies with respect to several impact categories. [ABSTRACT FROM AUTHOR]

This research delves into the crucial role of groundwater in underpinning ecosystems and human resilience amidst drastic and unpredictable climate change, particularly as water resources face increasing sustainability concerns due to population surges and climate change. Utilizing a combined approach of SWAT-MODFLOW models, we estimate the streamflow discharge and groundwater recharge in the Choushui River Alluvial Fan, Taiwan. These models allow evaluation of the distribution and proportion of recharge areas as well as the accuracy and the potential influence of future climate change scenarios on groundwater recharge. The findings show a strong correlation between the simulation and actual observations, evidenced by the Nash–Sutcliffe model efficiency coefficients (NSE) of 0.920 and 0.846 for calibration and validation in the Choushui River, and 0.549 and 0.548 for the Pei-Kang River, respectively. The model demonstrates a reliable representation of the watershed response, supported by robust statistical performance. The analysis reveals the variable impacts of climate change on groundwater recharge, dependent on the chosen scenario and period. Some scenarios indicate that the maximum observed increase in groundwater recharge is 66.36% under the RCP2.6 scenario in the long-term period (2061–2080), while the minimum observed increase is 29.67% under the RCP4.5 scenario in the initial time frame; however, all demonstrate a decrease ranging from 23.05% to 41.92% across different RCPs in the impact of climate change over time, suggesting a potential long-term decrease in the impact of climate change on groundwater recharge. This study provides indispensable insights into the spatial hotspots in the top fan and the potential range of impact rates of climate change on groundwater recharge, underscoring the importance of continuous research and the thorough evaluation of multiple scenarios. Moreover, we establish a primary framework for using a top-ranked MIROC5 projection of general circulation models (GCMs) to delineate an essential premise that facilitates the advanced exploration of alternative scenario augmentations, bolstering the comprehensive investigation of climate change impacts on groundwater recharge. It is proposed that these findings serve as a guidepost for sustainable water resource management and policy-making in the face of climate change and escalating water demand. [ABSTRACT FROM AUTHOR]

The systematic review using the PRISMA protocol aims to identify the observed and projected impacts of climate change on crop production and food security, water resources, and livestock and explores the perspectives of adaptation strategies employed to cope with this challenge across African countries. The review permits visualization in one scheme of the most recent various results of ongoing climate impact on agriculture and strategies across African countries. It enables the agricultural community and policymakers to consider it as they address climate change risks to agriculture, livestock, water resources, as well as food security. Overall results from 125 selected articles show that in the last four years, there has been a lack of research on climate change-related issues analysis in agriculture in some countries, especially in Northern Africa, Middle Africa, and Southern Africa. In the same regions, studies on the impact analysis on livestock, water, and management techniques are limited. Even though the agriculture sector is severely impacted by climate change, the effects can still be positive or negative depending on the products cultivated and the region. The various adaptation strategies implemented seem to be more effective when applied as a combination than a single application. However, some challenges including the lack of knowledge, limited input access, insufficient equipment, and financial constraints in strategy adoption exist. As climate change is a persisting and continuing fact getting worse over time, the adaptation strategies implemented today may require further improvement. Thus, our study suggests that more research should be done in this area to facilitate continuous improvement. Women’s leadership is important in the adoption of sustainable adaptation strategies. The introduction of gender factors in the assessment of the effectiveness of climate change adaptation strategies and food security components is recommended. Also, serious research should be carried out to define the most impactful adaptation strategies according to the important staple growing crops by region to cope with climate change impacts in the African food system. [ABSTRACT FROM AUTHOR]

Abstract Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one‐way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate‐induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O3 episodes using extreme value theory, and extend the approach to projections of mid‐ and end‐century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O3 concentrations by over 2.3 ppb on average across the U.S. at mid‐century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non‐compliance due to a climate‐induced increase in frequency of high ozone days.

The impacts of climate change on hydrology underscore the urgency of understanding watershed hydrological patterns for sustainable water resource management. The conventional physics-based fully distributed hydrological models are limited due to computational demands, particularly in the case of large-scale watersheds. Deep learning (DL) offers a promising solution for handling large datasets and extracting intricate data relationships. Here, we propose a DL modeling framework, incorporating convolutional neural networks (CNNs) to efficiently replicate physics-based model outputs at high spatial resolution. The goal was to estimate groundwater head and surface water depth in the Sabgyo Stream Watershed, South Korea. The model datasets consisted of input variables, including elevation, land cover, soil type, evapotranspiration, rainfall, and initial hydrological conditions. The initial conditions and target data were obtained from the fully distributed hydrological model HydroGeoSphere (HGS), whereas the other inputs were actual measurements in the field. By optimizing the training sample size, input design, CNN structure, and hyperparameters, we found that CNNs with residual architectures (ResNets) yielded superior performance. The optimal DL model reduces computation time by 45 times compared to the HGS model for monthly hydrological estimations over five years (RMSE 2.35 and 0.29 m for groundwater and surface water, respectively). In addition, our DL framework explored the predictive capabilities of hydrological responses to future climate scenarios. Although the proposed model is cost-effective for hydrological simulations, further enhancements are needed to improve the accuracy of long-term predictions. Ultimately, the proposed DL framework has the potential to facilitate decision-making, particularly in large-scale and complex watersheds.

Abstract Background There is a paucity of resources focusing on the climate change experience of readymade garment (RMG) workers in developing countries such as Bangladesh. Therefore, this mixed method approach aims to understand the distinctive types of climate change experiences from a health and occupational perspective, along with the consequences of these changes among RMG workers in Bangladesh. Methods The study was conducted from January 2022 and February 2022 where the quantitative data were collected from 200 RMG workers in 10 randomly selected garments and two focus group discussions took place with 20 conveniently selected RMG workers. The key informants were relevant stakeholders in the industry. Quantitative findings were reported using descriptive methods and qualitative findings were analysed using a content analysis approach. Result A total of 200 RMG workers were included in the study of which the majority belonged to the age group of 26–30 years (44%), were male (55%), worked in a compliant factory (70%), and were machine operators (79%). Half of the respondents experienced damage from natural disasters (51%), but only approximately 37% received humanitarian help. Migration and urbanisation were among the aftermath of the damage caused by e natural disasters, and 42% were forced to shift their homes due to natural disasters. Competition in the job market increased, and the owners had the opportunity to take on employees at a reduced salary. The respondents flagged climate change as a major contributor to their disease patterns. More than three-quarters of the respondents became sick because of increased heat while working; however, only half received any treatment. Conclusion Employee participation in hazard recognition, employer preparedness, prevention through design, research, surveillance, and upholding workplace ethics and standards can be the answers to climate change problems for readymade garment workers.

This study assesses the impact of climate change on streamflow characteristics in the Lualaba River Basin (LRB), an important yet ungauged watershed in the Congo River Basin. Two conceptual hydrological models, HBV-MTL and GR4J, were calibrated using the reanalysis datasets and outputs of Generalized Circulation Models (GCMs) under CMIP6 during the historical period. The hydrological models were fed with outputs of GCMs under shared socioeconomic pathways (SSPs) 2-45 and 5-85, moderate- and high-radiative future scenarios. The results demonstrate that hydrological models successfully simulate observed streamflow, but their performance varies significantly with the choice of climate data and model structure. Interannual streamflow (Q) percentiles (10, 50, 90) were used to describe flow conditions under future climate. Q10 is projected to increase by 33% under SSP2-45 and 44% under SSP5-85, suggesting higher flow conditions that are exceeded 90% of the time. Q50 is also expected to rise by almost the same rate. However, a considerably higher Q90 is projected to increase by 56% under the moderate- and 80% under the high-radiative scenario. These indicate the overall higher water availability in this watershed to be used for energy and food production and the need for flood risk management.

Climate change has comprehensive consequences on agriculture and livestock that will directly impact farmers, the perception of Agricultural scientists concerning climate change regionally is crucial in addressing its negative impacts effectively, thus the study was purposively conducted in the state of Telangana during 2021-2022 in nine major Indian institutes viz., ICRISAT, CRIDA, IIMR, IIOR, NIPHM, PJTSAU, NAARM, NIRD & PR, and MANAGE to assess the perception of Agricultural scientists on causes of climate change, changes in climatic parameters, and on the impact of climate change on crop and dairy farming, random sampling procedure was followed and the total respondents for the study was 150. Pre-tested and standardized interview schedules were used to obtain data. The study through scientists' perception identified the most important causes of climate change, the most observed changes in climatic parameters, and, the greatest impact of climate change on crop and dairy farming. The composite index developed using Principal Component Analysis showed that most of the respondents had a medium level of perception. Thus, the perceptions of agricultural scientists should be tapped to their fullest potential by policymakers in framing suitable solutions for adverse climate change impacts. [ABSTRACT FROM AUTHOR]

As a consequence of climate change impact, a significant variation in terms of temperature, atmospheric humidity, and carbon dioxide concentration levels is happening. This condition leads to several negative effects on the safety and the life cycle of existing concrete structures, such as the increase in the rate of material degradation, due to corrosion phenomena. In fact, the presence of carbonation and corrosion phenomena significantly influence the load-bearing capacity of existing reinforced concrete (RC) structures, under both static and dynamic loads. Among the wide range of existing RC constructions, bridges stand out for their importance. Furthermore, as structures directly exposed to the weather effects, they are more susceptible to these phenomena. In this paper, the influence of corrosion on existing RC motorway viaducts' seismic behavior, considering the impact of climate change, is investigated, by means of an efficient procedure based on the implementation of 3D simplified finite element models and the use of analytical relations to obtain the amount of reduction in the steel reinforcement area as a function of the age of the bridge and of the different corrosion scenarios analyzed. Several scenarios for the expected variations in CO2 concentrations, temperature, and relative humidity are evaluated, considering that most of the viaducts present in the Italian motorway network were built between the 1960s and the 1970s. The results obtained using the projection of climate change impacts are compared with those calculated considering the corrosion scenarios resulting from the DuraCrete research project, to understand if the evolution of climate change leads to worse scenarios than those previously assessed. [ABSTRACT FROM AUTHOR]

Climate change may significantly impact the availability and quality of water resources in dam reservoirs by potentially altering the hydrological regime of lake tributaries and the corresponding flow–duration curves. Hydrological models driven by climate projections (downscaled to the watershed scale and bias corrected to eliminate systematic errors) are effective tools for assessing this potential impact. To assess the uncertainty in future water resource availability, resulting from the inherent uncertainty in climate model projections, an ensemble of climate models and different climate scenarios can be considered. The reliability and effectiveness of this approach were illustrated by analyzing the potential impact of climate change on the water availability at Brugneto Lake in northern Italy. This analysis was based on climate projections derived from an ensemble of 13 combinations of General Circulation Models and Regional Climate Models under two distinct scenarios (RCP4.5 and RCP8.5). The semi-distributed HEC-HMS model was adopted to simulate the hydrological response of the basin upstream of the lake. The hydrological model parameters were calibrated automatically via the PEST software package using the inflows to the lake, estimated through a reverse level pool routing method, as observed values. Future water availability was predicted for short- (2010–2039), medium- (2040–2069), and long-term (2070–2099) periods. The results indicate that the uncertainty in reservoir inflow is primarily due to the uncertainty in future rainfall. A moderate reduction in water availability is expected for Brugneto Lake by the end of the current century, accompanied by modifications in the flow regime. These changes should be considered when planning future adaptation measures and adjusting reservoir management rules. [ABSTRACT FROM AUTHOR]

This paper reviewed the impacts of climate change on the management of the water sector in Malaysia discussing the current status of water resources, water service, and water-related disasters. The implementation of engineering practices was discussed to provide the detailed assessment of climate change impacts, risks, and adaptation for sustainable development. The narrative methods of reviewing the literatures were used to get an understanding on the engineering practices of water infrastructures, implication of the government policies, and several models as the main motivation behind the concept of integrated water resource management to contribute as part of the sustainable development goals to achieve a better and more sustainable future for all. The findings of this review highlighted the impacts of climate change on the rivers, sea, lakes, dams, and groundwater affecting the availability of water for domestic and industrial water supplies, irrigation, hydropower, and fisheries. The impacts of climate change on the water-related disasters have been indicated affecting drought-flood abrupt alternation and water pollution. Challenges of water management practices facing climate change should be aware of the updated intensity–duration–frequency curves, alternative sources of water, effective water demand management, efficiency of irrigation water, inter-basin water transfer, and nonrevenue water. The transferability of this review findings contribute to an engagement with the society and policy makers to mobilize for climate change adaptation in the water sector. [ABSTRACT FROM AUTHOR]

Background: There is a paucity of resources focusing on the climate change experience of readymade garment (RMG) workers in developing countries such as Bangladesh. Therefore, this mixed method approach aims to understand the distinctive types of climate change experiences from a health and occupational perspective, along with the consequences of these changes among RMG workers in Bangladesh. Methods: The study was conducted from January 2022 and February 2022 where the quantitative data were collected from 200 RMG workers in 10 randomly selected garments and two focus group discussions took place with 20 conveniently selected RMG workers. The key informants were relevant stakeholders in the industry. Quantitative findings were reported using descriptive methods and qualitative findings were analysed using a content analysis approach. Result: A total of 200 RMG workers were included in the study of which the majority belonged to the age group of 26–30 years (44%), were male (55%), worked in a compliant factory (70%), and were machine operators (79%). Half of the respondents experienced damage from natural disasters (51%), but only approximately 37% received humanitarian help. Migration and urbanisation were among the aftermath of the damage caused by e natural disasters, and 42% were forced to shift their homes due to natural disasters. Competition in the job market increased, and the owners had the opportunity to take on employees at a reduced salary. The respondents flagged climate change as a major contributor to their disease patterns. More than three-quarters of the respondents became sick because of increased heat while working; however, only half received any treatment. Conclusion: Employee participation in hazard recognition, employer preparedness, prevention through design, research, surveillance, and upholding workplace ethics and standards can be the answers to climate change problems for readymade garment workers. [ABSTRACT FROM AUTHOR]

Rising atmospheric CO2 levels drive greenhouse effects, elevating temperatures, and diminishing water accessibility in semi-arid regions, affecting agriculture. Alfalfa contributes to climate change mitigation by sequestering carbon, enhancing soil fertility and carbon storage, reducing synthetic nitrogen fertilizer use, preventing soil erosion, supplying high-quality livestock feed, and serving as a bioenergy source. This research examined the effects of elevated CO2 levels in climate change scenarios (600, 800, and 1000 ppm, with control at 400 ppm) on two alfalfa varieties, Medicago sativa cv. Nimet and Bilensoy-80. The experiments were conducted in specialized Climate Change Simulation Greenhouses, allowing control of CO2, water, and temperature variables. Results revealed a positive relationship between higher CO2 concentrations and increased photosynthesis (P ≤ 0.001), promoting the plant growth leaf area (P ≤ 0.001), yields and both leaf (P ≤ 0.05) and stem dry biomass (P ≤ 0.001). At 1000 ppm CO2, a saturation point was reached, halting further photosynthesis. This down-regulation was linked to decreased intercellular CO2 levels, which expedited chlorophyll and breakdown and potentially induced leaf senescence. High CO2 levels led to greater biomass, as anticipated. However, total protein levels, a forage quality indicator, initially decreased with high CO2 concentrations (up to 1000 ppm) due to an inverse relationship with shoot yield. Surprisingly, the 1000 ppm CO2 concentration mitigated this protein reduction in both alfalfa varieties.

Study area: Katar and Meki subbasins, Rift Valley Lakes Basin, Ethiopia.Study focus: This research was carried out to characterized the recharge mechanism and quantify the steady-state groundwater balance and its sensitivity to future climate change. A groundwater simulation model was constructed and calibrated using a hydro-geo spatial dataset. Three regional climate models were used to assess the potential impact of changes in future precipitation on the recharge rate and groundwater balance components.New Hydrogeological Insight: Groundwater potential assessment depends on accurate estimation of the recharge rate. Precipitation contributed 11.95% and 11.96% to groundwater recharge in the Katar and Meki subbasins, respectively. The steady-state numerical groundwater model was calibrated and the model performed in the ranges of R2: 0.95–0.99; RMSE: 16.17–25.18; and MAE: 12.69–24.55, demonstrating 'excellent' model performance. In particular, the model exhibited high sensitivity to changes in the recharge rate and horizontal hydraulic conductivity. Future change in precipitation caused a reduction in groundwater potential in the range of 6.24–40.32% by the 2040 s and 2070 s, respectively, in the Katar subbasin. Likewise, the Meki Subbasin will experience a reduction in groundwater potential in the range of 0.29–37.17% by the 2040 s and 2070 s, respectively. These results emphasize how crucial it is for future water resource development initiatives to take into account climate variability for sustainable groundwater development.

Comparison of old and new vegetation maps is an effective way to detect vegetation dynamics. Recent developments in computer technology have made it possible to accurately compare old paper vegetation maps with current digitized vegetation maps to reveal long-term vegetation dynamics. Recently, a 1:50,000 scale vegetation map of the Hakkoda Mountains in northern Japan, located in the ecotone of cool temperate and subalpine forests in northern Japan under an East Asian monsoon climate, from 1930 was discovered. We compared the 1930s vegetation map with the most recent 2010 vegetation map to test the following hypotheses: 1) the occurrence of upward expansion of the upper limit of cool-temperate deciduous forests, and 2) whether designation as a national park in 1936 would have reduced forestry and land use, expanded beech forests, and cool-temperate deciduous forests. To compare vegetation changes, 67 types of vegetation legends for the 1930 and 2010 maps were unified to 21 based on plant species composition. Consequently, vegetation has changed substantially over the past 80 years. 1) In the subalpine zone above 1,000 m, the coniferous forest area decreased by half. In the cool temperate zone below 1,000 m, the area of beech forests increased 1.48 times, and some of them could be shifted upwards, replacing subalpine fir forests in the lower part of the subalpine zone. 2) In areas below 700 m, deciduous oak forests once used as thickets were almost halved. Instead, climax and beech forests expanded. However, we also found that even after the area was declared a national park, oak forests were cleared and converted to commercial forests such as cedar plantations, cattle ranches, and horse pastures in some areas. These results will be useful for future ecosystem and biodiversity research/conservation and will provide baseline information for climate change adaptation policies.

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets.

The interaction of the atmosphere and the land surface is vital in hydrological processes. In this paper, climate change impacts on streamflow are explored using soil and water assessment tool (SWAT) in one of the tropical watersheds, Wabi Shebele River Basin of Ethiopia. Regional climate model (RCM) from CORDEX-Africa region is used to analyze the basin's hydrological responses to climate forcing in the projected period. The result indicates that the watershed is likely to experience an increase in flood hazard with an increase in precipitation in the future as temperatures increase less than 2 °C. Flood hazard indices showed a larger value downstream of the river station (i.e., Gode) and a smaller value at the upper and middle stations with no change in climate variables (i.e., the baseline scenario, T + 0 °C, P + 0%). Based on separation method analysis, climate change has a greater impact on the streamflow and flood hazards in the region during the last four decades. Model uncertainty analysis reveals that simulated seasonal streamflow using RCMs has similar oscillation patterns to streamflow using observed climate data within uncertainty bands (UBs) in the study area with NSE and R2 values greater than 0.75 and 0.92, respectively. HIGHLIGHTS Regional climate model (RCM) from CORDEX-Africa has the capability to forecast the climate condition of southeastern Ethiopia.; SWAT model has the capability to simulate streamflow and explore climate change impacts in tropical watersheds.; Uncertainty level of climate change impact on flood hazard at present and future is explored.; Climate change is the most driving force for flood hazard in southeastern Ethiopia.;

Abstract The main purpose of this study is to understand influences of bulk structure of geomaterials on water storage and transfer, in order to assess durability and climate change impact on the UNESCO world heritage sites in Alexandria, Egypt. This study deals with the responses of water towards the physiochemical and physicomechanical behaviours of Calcarenitic rocks, that are utilized in Greek and Roman monuments at Alexandria. Many vulnerable archaeological sites [2.3–2.5 m above mean sea level (M.S.L)] are identified at Alexandria, specifically at the Eastern Harbor, El-Shatby the Greek necropolis and Moustafa Kamil Roman tombs and addition to the Roman Catacombs of Kom El-Shoqafa which excavated with deepth − 18 m from the land surface. These UNESCO heritage sites suffer climate change impact (heavy rains and sea water rising) as well as multiple geoenvironmental and geophysical hazards. In this study a general outline of the various tests, surveys and analyses is presented, highlighting the most important issues related to the durability and climate change impact. This paper represents the comprehensive in-situ, field and laboratory surveys and tests undertaken in these outstanding world heritage sites. The field testing program comprises various geotechnical and geophysical field and laboratory tests aiming to define the physical, mechanical and dynamic properties of the hard soils/soft rock materials of the archaeological sites where these outstanding monuments are excavated and constracted. By analysis of linear correlations, some essential mechanisms should be underlined, which may connect the macrostructure to the microstructure of the geomaterial. A systematic method of analysis clearly appeared and emphasized the role of the bulk structure (i.e. grain size, grain contact, specific area, pore shape and microporosity) on petrophysical and petromechanical behavior of rock materials. The study revealed that the petrophysical and geomechanical properties of Calcarenitic rocks are influenced by size, shape, packing of grains, porosity, cement and matrix content, all controlled strongly by depositional fabric and postdepositional processes. The accurate analysis of the physiochemical and physicomechanical behaviours of Calcarenitic rocks that are utilized in Greek and Roman monuments at Alexandria allowed us to define the pathology of these monuments and to estimate the durability, climate change impact and ultimate geostatic loads that they can survive under their present geoenvironmental conditions.

This study aims to evaluate the impact of climate change on the surface water hydrology of the Gopad river basin in India. The outputs of four CMIP6 Global Climate Models have been downscaled using the statistical downscaling method to the basin level. A comparative analysis for the accuracy achieved in the bias correction for the combination of GCM and downscaling method has been performed before utilising the downscaled weather parameters for hydrological study. The MIROC6 and ACCESS-CM2 were found best for the simulation of precipitation and temperature, respectively. The Distribution Mapping and Variance Scaling methods have shown better accuracy w.r.t other statistical methods. The impact of climate change has been found significant since the temperature has been observed to be increased by 3.16 °C by the end of 2060; meanwhile, there is an average decrease of 9.2% in the annual rainfall from the baseline. The peak runoff has increased while there is a significant decrease in the groundwater recharge. Further, hydrologically critical subbasins (HCS) have been delineated based on the runoff, groundwater recharge, and baseflow. Most HCS was observed to be situated in the upper Gopad river basin, representing the area's pristine conditions. HIGHLIGHTS The ACCESS-CM2 and MIROC6 are more accurate for the study area.; The Variance Scaling and Distribution Mapping methods have shown better accuracy than others.; A rise in average temperature has been observed, while there is a decrease in annual rainfall from the baseline.; The area with less human intervention has proven to be hydrologically critical for the Gopad river basin.;

Study Region: Barrier island at the German North Sea coast Study Focus: Drinking water supply on small barrier islands strongly depends on extractions from their freshwater lens below the island when no pipeline to the mainland exists. The shape and extend of the lens is influenced by sea level change, abstraction and groundwater recharge, while groundwater recharge is the only inflow of freshwater into the system. To ensure sustainable use of groundwater in the future within changing climate conditions, knowledge in long-term groundwater recharge is required which can be obtained by climate scenario-based simulations. However, hydrological modelling on small barrier islands faces challenges, such as the lack of calibration and validation data. In addition, the historical long-term mean of main climate variables, such as precipitation and temperature, is represented inadequately in available regional climate models. In order to quantify previously mentioned topics, a water balance model was set up for the small barrier island Norderney. Subsequently, climate change impact on groundwater recharge was simulated.New hydrological insights for the region: The applied methodology increases plausibility and confidence in impact assessments compared to a-priori model applications. Future long-term development of groundwater recharge is highly dependent on the underlying climate model and emission scenario, but also affected by large uncertainties throughout the model chain, e.g. by the approach used for bias-correction. The scenario results can be directly used as forcing data for three-dimensional groundwater models.

Study region: Abashiri River, northeastern Hokkaido, Japan. Study focus: In response to the growing concern over likely future climate and land use land cover (LULC) changes, a better understanding of the consequent streamflow changes is needed in northeastern Hokkaido, Japan. The present study focuses on the Abashiri River Basin (ARB), northeastern Hokkaido, and estimates the future local streamflow and its change in quantity, seasonality, flow regime, and spatial distribution under various possible impacts of climate and LULC conditions. The estimation is produced using the Soil and Water Assessment Tool (SWAT), a hydrological model suitable for managemental analysis. Future conditions are applied as alterations to the initial model inputs. New hydrological insights for the region: Possible impact of climate change leads to significant changes in streamflow quantity and flow pattern around the snowmelt season, while negative and insignificant change in streamflow is expected in response to possible LULC change. The results highlight a concerning future for local agricultural water use. Consequently, practical recommendations for local water resources management are advised, focusing on precautionary measures and development insights. Compared to existing research in this region, the present study provides a comprehensive estimation of the possible future streamflow changes on a finer spatiotemporal scale. Further application in the future to help the local water resources management is expected.

Extreme dry and hot conditions lead to intense droughts in central India. However, the precise changes in future drought characteristics and their consequences on crop production have not been fully examined in Godavari River Basin. Therefore, this study focuses on the spatiotemporal modelling of climate change impacts on drought over the past, present, and future periods using long-term high spatial gridded data. The past and present observed datasets were obtained from Indian Meteorological Department, whereas the future datasets were obtained from d4PDF Scenarios. The standardized precipitation evapotranspiration index (SPEI) was applied to analyse drought statistics to identify the worst-case drought scenario (i.e. year most affected by severe-to-extreme drought with high drought severity), which was used further to access precise drought risk. Because SPEI considers the effect of both rainfall and temperature and therefore it is the widely recommended meteorological drought indices and best suited for climate change impact assessment. Drought severity was analysed using a Multi-criteria assessment risk matrix, and the areas under higher agriculture drought risk were mapped. The frequency of droughts with higher intensity and magnitude increased in the present decade compared to the past three decades. 75% area showed higher vulnerability to drought risks, whereas only 25% showed lower risks and less vulnerability to drought occurrences. Results demonstrate that drought severity varies from one sub-basin to another. More drought episodes were predicted for the central belt, particularly over the sub-basins of Wardha, Wainganga, Pranitha, and part of Indravati and Lower Godavari. 11% of the area covering six districts in the GRB was identified as highly vulnerable, and rice production was drastically reduced, accounting for 41.02% of production loss during the worst-case drought event. The frequency of severe-to-extreme droughts is expected to increase under future scenarios; therefore, effective mitigation strategies are recommended to minimise the agriculture drought risks and economic loss.

The propagation from meteorological to hydrological drought is critical for better understanding hydrological drought. However, how climate change would affect the drought propagation has not been well studied, especially over regions mixed with massive human interventions. The study attempts to explore changes in the characteristics of meteorological and hydrological droughts, and the corresponding drought propagation under different climate change scenarios across six watersheds over the Yangtze River basin (YZB). Seasonal meteorological and hydrological droughts were characterized by using standardized precipitation and streamflow index at 3‐month scales (SPI‐3 and SSI‐3), which were calculated using precipitation simulations from 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models and streamflow simulations from PCR‐GLOBWB 2.0 hydrological model driven by CMIP6 outputs. Drought propagation characteristics, including propagation ratio, lag and lengthening, were then determined. Both meteorological and hydrological drought durations would shorten, while their drought severity would increase excluding a downstream watershed. About 40%–50% of meteorological droughts could develop into hydrological droughts, with lag time less than 1.4 months and lengthening time less than 1.8 months, respectively. Under climate warming, the drought propagation ratio would increase over two watersheds, while decrease and then increase over three watersheds. The drought propagation lag time is expected to prolong over the regions above Cuntan under moderate emission scenario, while prolong first and then shorten over most watersheds under high‐emission scenario. The drought propagation lengthening time would shorten over most watersheds excluding a downstream watershed, where drought conditions would further worsen during drought propagation. This study calls for climate mitigation efforts to suppress drought aggravation in the propagation particularly for the downstream YZB. [ABSTRACT FROM AUTHOR]

Summary: This study addresses the critical need to report original and current findings on the global food system's ability to meet the growing natural resource demands of an estimated 9 billion global population. The objective is to provide guidance for researchers in developing strategies to reduce climate change risks in the food and beverage supply. To achieve this, we propose integrating innovative industry insights and digital applications into existing food system models as industrial demonstrators. Our research encompasses six impactful themes, demonstrating effective delivery methodologies. We highlight that human‐centred activities and practices, often overlooked in sustainability assessments, hinder improved security and sustainability in the food system. Through our work, we showcase how smarter food production processes, along with active citizen engagement, can achieve desired outcomes outlined in frameworks, such as the Sustainable Development Goals. A crucial aspect is the development of Internet of Things (IoT) platforms, integrating workforce practices into manufacturing activities, and driving the necessary cultural changes for a sustainable food system. This study illuminates challenges faced by the global food system and provides actionable insights and methodologies to guide researchers and industry stakeholders in creating a more sustainable and secure future for food production and consumption. [ABSTRACT FROM AUTHOR]

Most automotive plastic waste (APW) is landfilled or used in energy recovery as it is unsuitable for high‐quality product mechanical recycling. Chemical recycling via pyrolysis offers a pathway toward closing the material loop by handling this heterogeneous waste and providing feedstock for producing virgin plastics. This study compares chemical recycling and energy recovery scenarios for APW regarding climate change impact and cumulative energy demand (CED), assessing potential environmental advantages. In addition, an economic assessment is conducted. In contrast to other studies, the assessments are based on pyrolysis experiments conducted with an actual waste fraction. Mass balances and product composition are reported. The experimental data is combined with literature data for up‐ and downstream processes for the assessment. Chemical recycling shows a lower net climate change impact (0.57 to 0.64 kg CO2e/kg waste input) and CED (3.38 to 4.41 MJ/kg waste input) than energy recovery (climate change impact: 1.17 to 1.25 kg CO2e/kg waste input; CED: 6.94 to 7.97 MJ/kg waste input), while energy recovery performs better economically (net processing cost of −0.05 to −0.02€/kg waste input) compared to chemical recycling (0.05 to 0.08€/kg waste input). However, chemical recycling keeps carbon in the material cycle contributing to a circular economy and reducing the dependence on fossil feedstocks. Therefore, an increasing circularity of APW through chemical recycling shows a conflict between economic and environmental objectives. [ABSTRACT FROM AUTHOR]

An overview of publications on the hydrological consequences of climate change in the context of the ongoing and projected threats to water security is presented. Two hydrological indicators of water security are considered both at the global and regional scales: mean river flow regime as an indicator of the provision of the territory with surface water resources, as well as the flood regime, as an indicator of flood hazard. The paper is structured as follows. The first section briefly discusses the current understanding of the mechanisms of the influence of anthropogenic climate change on water resources and flood hazard. The second section considers the methodological aspects of constructing assessments of the ongoing changes in the river regimes, and reviews some of the estimates of changes in water resources and high river flow in the world and Russia. The third section is devoted to the global and regional assessments of future changes in the river runoff regime in the twenty-first century and discusses the methodological challenges of carrying out such assessments. The fourth section evaluates socio-economic consequences of the current and forecasted hydrological changes and their influence on water security. The paper is finalized by several summarizing remarks. [ABSTRACT FROM AUTHOR]

Climate change has a crucial impact on the global energy and water cycle. The hydrological cycle can be studied both from ground and satellite measurements on a global scale. Yet a comprehensive overview is challenging to establish given the spatial and temporal limitations related to various Earth Observation satellite sensors or maintenance of in-situ gauges. Optical remote sensing of visible light can not overcome the substantial obstacle from cloud cover that vastly limits its capability in daily global monitoring. Active satellite sensors like SAR or altimetry are not capable to provide global coverage on a daily basis, therefore, they can be geographically limited. Passive microwave radiometry (PMR) can acquire both daily and global scales that enables the temporally frequent and spatially extensive observations of continental river gauge. Previous studies demonstrated the use of PMR measurements for global daily river gauge benefiting from its high sensitivity of microwave radiation to water presence. This study aims at comparing the methodology of PMR to optical river gauge measurements based on the assumption that at selected locations along the river channel, increase in streamflow is related to increase in the floodplain water surface inundation. Comparison showed a significant obstacle of cloud cover over tropical regions, where PMR has the potential to measure river streamflow. Yet over regions with less clouds both optical and PMR can be good alternative to in-situ streamflow ground measurements. [ABSTRACT FROM AUTHOR]

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Climate and land use/cover (LULC) changes are essential factors that influence hydrological regimes by altering the groundwater recharge and river flow. This study investigated the separate and combined impact of climate and LULC changes on streamflow. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow under near-term (2021–2050) and mid-term (2051–2080) period against 1985 to 2015 baseline period. The Cellular Automata (CA)-Markov chain model was used to predict the future LULC change. The three-ensemble average of regional climate models (CCLM4.8, RACMO22T, EC-EARTH) under RCP 4.5 and RCP 8.5 emission scenarios were applied for future climate projection. The LULC predictions between 2035 and 2055 showed an increase in agricultural land, grassland, settlement areas and woodlands by 44.02%, 30.35%, 69.2%, and 55.05%, respectively, while forest and scrub/bush lands showed a decrease by decrease by 21.53% and 11.08%, respectively. The annual, wet, and dry seasons rainfall projections increased by 0.13%, 0.02%, and 0.85% respectively, during the near term period under RCP 4.5 scenarios. Overall, the annual, wet, and dry season rainfall projections showed slightly increasing tendency. The temperature projection consistently indicated a warmer future with the highest mean annual projected temperature being 2.0°C under high emission scenario during the midterm period. The projected streamflow under the combined impact of climate and LULC changes will increase by up to 8.72% in wet seasons and by up to 6.62% in dry seasons during the near-term period under RCP4.5 scenarios. Similarly, the projected mean annual streamflow will increase by up to 8.13%. The annual, wet and dry season's streamflow projections showed a consistent increase during both near and midterm periods under both climate scenarios. Understanding the future response of streamflow under climate and LULC changes is crucial to plan adaptation options for water resources management under future warming condition. [ABSTRACT FROM AUTHOR]

The impact of climate change on the Earth's environments has been widely discussed, although there is still little consensus on the degree of influence, and to what extent the effects are positive, negative or neutral. Predicting the impacts of climate change on organisms and their response to this process has been a growing challenge for ecologists in recent years. In this review, we surveyed the published research on the relationship between lizards and global climate change. We surveyed the keywords "climate change" and "warming", combined with "lizard*" (there is, all words with this prefix), in three reference databases. We identified 401 relevant papers, and analyzed in further detail the group of studies (59 papers, 14.7% of the total) that developed thermoregulatory models to predict the persistence of lizards in a scenario of global warming. These 59 papers focused on species of 13 lizard families found on five continents. Overall, 62.5% of the papers that predicted the impacts of climate change on lizards indicated negative effects, while 21.9% reported positive effects, and 15.6%, a neutral scenario. The lizards identified as the most vulnerable to warming were tropical, viviparous, and thermoconformers, whereas species adapted to cooler climates would be the most likely to benefit from warming. On a broader scale, however, this scenario would lead to competition between lowland and highland lizards, for example, for thermally favorable areas. We conclude that it will be important to develop more detailed models that contemplate the specific features of each group for the development of more reliable predictions, in addition to the need for social conservation projects and the systematic identification of priority areas for conservation. [ABSTRACT FROM AUTHOR]

Intense anthropogenic impacts in tidal rivers can cause habitat loss and ecosystem degradation. In addition, changes in water temperature associated with climate change are significantly impacting the distribution area of fish fauna within tidal rivers. In the present study, we used long-term fish fauna data to determine the relationship between climate change-induced increases in water temperature and changes in the distribution of fish species in tidal rivers in the Japanese archipelago. The distribution ranges of many subtropical and tropical fish species were found to move northward in areas affected by warm currents, suggesting further possible distributional dispersal in future. This study is the first to examine the nationwide distributional changes and future projections of fish fauna in tidal rivers. The results suggest that many subtropical and tropical fishes are expanding their distribution areas in tidal rivers and in coastal and estuarine areas. [ABSTRACT FROM AUTHOR]