Wetland ecosystems provide valuable services to human beings, but they are also among the most threatened ecosystems in the world (1). Sixteen ecosystem services are identified through the South African Water Research Commission's Wet-Health Tool (2). This study sought to establish which of these ecosystem services are highly ranked/rated by the community members living in the Soutpansberg area in South Africa. This area is a strategic water source/watershed. The area is rich in biodiversity and is also experiencing competing administrative jurisdictions: the local traditional leadership and the municipal council. This study also sought to determine the influence of age, education status, employment status, and family income, among other demographic factors, on how people view the importance of services derived from wetlands. It also sought to establish whether people in urban settings view the ecosys-tem services obtained from wetlands similarly to people in rural settings. A literature review was conducted to understand the wetland ecosystem services and how communities benefit from these services. A close-ended questionnaire was used to collect data for the current study, which was circulated among the villagers around the wetlands, particularly those living close to the wetlands. One hundred and sixteen responses from the study were recorded. Food for livestock was ranked the greatest benefit or service derived from the wetlands rated by 82% of the participants, followed by the provision of cultivated foods at 60%, provision of water for human use at 58%, provision of harvestable resources at 42% and erosion control at 38% completes the top 5 ranked ecosystem services in the area. The study concluded that the participants living in rural areas had greater awareness of wetlands' ecosystem services than their urban counterparts.

Flood disasters have become an annual occurrence along the East Coast of North Sumatra (ECNS) and Medan City. Numerous studies have examined the causal factors flood disasters in this area, such as changes in land use, drainage issues, and population growth, but the intensity of flood disasters continues to rise. In this research, we focused on evaluating the unexplored factors of land subsidence and rising sea levels in this region. Our investigation uses multi-sensor satellite data and field surveys to conduct an assessment of the rate of land subsidence and sea level rise and assess their implications on flood disasters. This study highlights the potential of multi-sensor satellite data as a primary resource for assessing flood disasters in coastal areas and densely populated large cities. Furthermore, we propose a solution to reduce the negative impact of flood disasters by by engaging local communities and environmental enthusiasts in mangrove reforestation along the coastline.

Image classification in Remote Sensing and Geographic Information Systems (GIS) containing various land-cover classes is essential for efficient and sustainable land-use estimation, and other tasks like object detection, localization and segmentation. Deep Learning (DL) techniques have shown a tremendous potential in the GIS domain. While Convolutional Neural Networks (CNN) have dominated most of the image analysis domain, a new architecture called transformers have proved to be a unifying solution for several AI-based processing pipelines. Vision Transformers (ViT), a variant of transformers can have comparable and in some cases better accuracy than a CNN. However, they suffer from a significant drawback associated with an excessive use of training parameters. In this research we explore several modifications in the vision transformer architectures, especially MobileViT that can be optimized while boosting accuracy. To verify our proposed approach these new architectures are trained on four land-cover datasets AID, EuroSAT, UC-Merced, and WHU-RS19. Experiments reveal that combination of lightweight convolutional layers including ShuffleNet along with depthwise separable convolutions and average pooling can reduce the trainable parameters by 17.85% and yet achieve higher accuracy than the base MobileViT. It is also observed that utilizing a combination of convolution layers along with multi-headed self attention layers in MobileViT variants provide better performance in capturing local and global features unlike the standalone ViT architecture that utilizes almost 95% more parameters than the proposed MobileViT variant.

In Ethiopia, land degradation in the form of gully development and soil nutrient depletion is a very serious issue. The goal of this study is to determine how different types of land management practices and slope positions affect particular soil physico-chemical characteristics in the Agamssa watershed. Using systematic sampling techniques, soil samples were taken using a sampling quadrat (15 * 15 m) that was placed 50 m apart from one another. A total of 54 quadrats were planted at three slope positions: upper (>15%), middle (10–15%), and foot (3–10%) slope respectively. 18 composite soil samples were then. A two-way ANOVA was used to analyze the data, and the Least Significant Difference (LSD) test was used to separate the means at p ≤ 0.05. According to the study's findings, the value of most soil physical and chemical characteristics was higher in closed area than on open grazing land, as well as at foot slope position compared to middle and upper slope positions. The higher mean value (7.3 ppm) was recorded at the foot slope, while the lower mean value (4.9 ppm) was found at the upper slope position. The exchangeable cations such as Mg+2, K+, and Na+ were significantly (p≤ 0.01) affected by the main effect of land-use types. The higher mean values of Mg+2 (9.70 mq/100g), K+ (0.38 mq/100 g), and Na+ (0.035 mq/100 g) were found at area closure, whereas the lower mean values of Mg+2 (7.33 mq/100g), K+ (0.30 mq/100 g), and Na+ (0.027 mq/100g) were recorded at open grazing land. It was able to conclude this study that area closure enhances the physical and chemical qualities of soil and recovers woody plant species. Therefore, converting open grazing land into a closure area is advised.

In response to the problem of increasing climate change and energy security, investment in renewable energy sources has increased significantly both in Europe and globally. Wind and solar power plants are expected to be the largest contributors to global decarbonization, ranking first and second in projected capacity by 2050. Since all power plants have some impact on the environment, this also applies to photovoltaic power plants. Because of the large capacities projected for PV installed capacity, their environmental impacts should be evaluated. The environmental impacts of PV power plants change over time. Improving the manufacturing technology of PV system components, increasing the efficiency of solar cells, and using materials that are less harmful to the environment will reduce these impacts. Manufacturing PV system components is a highly energy-intensive process that involves greenhouse gas emissions. As new renewable energy capacity is built, the amount of "green" electricity on the grid increases, reducing CO2 emissions per kWh consumed. The objective of this paper is to analyze the current status of the environmental impact of PV power plants under these changing conditions in terms of CO2 emissions, land use, pollutant and noise emissions, and water consumption. The capacity installed to date will reach the end of its lifetime by 2050, which means that the amount of waste associated with it will increase over time. This can have a significant impact on the environment, which is why part of the work is dedicated to this problem. In addition to the available information from the literature, in the part related to land use, the authors also made their own estimates based on data on newly installed PV power plants and PV modules available on the market. The results of the analysis show that there is enough land both in Europe and worldwide to install the planned capacities of rooftop and ground-mounted PV power plants. CO2 emissions are at the same level as for concentrated solar power, with a decreasing trend. Pollutant emissions, noise and water consumption are not a major problem compared to other types of power plants. Overall, it can be concluded that the expansion of PV capacity has a very positive impact on the environment.

Large-scale land cover plays a crucial role in global resource monitoring and management, as well as research on sustainable development. However, the complexity of the mapping process, coupled with significant computational and data storage requirements, often leads to delays between data processing and product publication, creating challenges for dynamic monitoring of large-scale land cover. Therefore, improving the efficiency of each stage in large-scale land cover mapping and automating the mapping process is currently an urgent and critical issue that needs to be addressed. We propose a high-performance automated large-scale land cover mapping framework(HALF) that introduces high-performance computing technology to the field of land cover production. HALF optimizes key processes, such as automated sample point extraction, sample-remote sensing image matching, and large-scale classification result mosaic and update. We selected several 10°×10° regions globally and the research makes several significant contributions:(1)We design HALF for land cover mapping based on docker and CWL-Airflow, which solves the heterogeneity of models between complex processes in land cover mapping and simplifies the model deployment process. By introducing workflow organization, this method achieves a high degree of decoupling between the production models of each stage and the overall process, enhancing the scalability of the framework. (2)HALF propose an automatic sample points method that generates a large number of samples by overlaying and analyzing multiple prior products, thus saving the cost of manual sample selection. Using high-performance computing technology improved the computational efficiency of sample-image matching and feature extraction phase, with 10 times faster than traditional matching methods.(3)HALF propose a high-performance classification result mosaic method based on the idea of grid division. By quickly establishing the spatial relationship between the image and the product and performing parallel computing, the efficiency of the mosaicking in large areas is significantly improved. The average processing time for a single image is around 6.5 seconds.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

The major industrial cities of Bangladesh are heavily experiencing air pollution-related problems due to the increased trend of Particulate Matter (PM2.5) and other pollutants. This paper aimed to investigate and understand the relationship between PM2.5 and land use and climatic variables and to identify the riskiest area and population groups using a Geographic information system and regression analysis. The results show that about 41% of PM2.5 concentration increased within 19 years (2002-2021) in the study area, while the highest concentration of PM2.5 was found from 2012 to 2021. The concentrations of PM2.5 were higher over barren lands, forests, croplands, and urban areas. About 64%, 62.7%, 57%, and 55% concentrations were increased annually over barren lands, forests, cropland, and urban regions, respectively, from 2002-2021. The highest concentration level of PM2.5 (84 mg m-3) among other land use classes was found in urban areas in 2021. The regression analysis shows that air pressure (r2= - 0.26), evaporation (r2= - 0.01), humidity (r2= - 0.22), rainfall (r2= - 0.20), and water vapor (r2= - 0.03) were negatively correlated with PM2.5. On the other hand, air temperature (r2= 0.24), ground heat (r2= 0.60), and wind speed (r2= 0.34) were positively correlated with PM2.5. More than 60 Upazilas were the most polluted areas, with 1,948,029 populations (ages 0-5), 485,407 (ages 50-69), and a total population of 11,260,162 were in the high-risk/hotspot zone. The government line department may use the main results paper's key results, policymakers, stainable development practitioners, academicians, and others for integrated air pollution mitigation and management in Bangladesh and other geographical settings worldwide.

The application of machine learning techniques to satellite imagery has been the subject of interest in recent years. The increase in quality and quantity of images, made available by Earth observation programs, such as the Copernicus program, led to the generation of large amounts of data. Among the various applications of this data is the creation of land cover maps. The present work aimed to create machine learning models capable of accurately segment and classify satellite images, to automatically generate a land cover map of the Portuguese territory. Several experiments were carried out with the spectral bands of the Sentinel-2 satellite, with vegetation indices, and with several sets of land cover classes. Three machine learning architectures were evaluated, which adopt two different techniques for image classification. One of the classification techniques follows an object-oriented approach, and in this case the architecture adopted in our models was a U-Net artificial neural network. The other classification technique is pixel-oriented, and the machine learning models tested were random forest and support vector machine. The overall accuracy of the results obtained ranged from 68.6% to 94.75%, depending strongly on the number of classes into which the land cover is classified. The result of 94.75% was obtained when classifying the land cover only into 5 classes. However, a very interesting accuracy of 92.37% was achieved by the model when trained to classify 8 classes. These results are superior to those reported in the related bibliography.

Abstract: In the last five years, the urban development of Limassol City has rapidly increased in the sectors of industry, trade, real estate, and many others. This exponentially increased urban development introduces several concerns about the aggravation of the land subsidence in the Limassol coastal front. Fifty Copernicus Sentinel-1 data from 2017-2021 have been processed and analyzed using the Sentinel Application Platform (SNAP) and the Stanford Method for Persistent Scatters (StaMPS). A case study for the identification and analysis of the elements (PS) in pixels in a series of interferograms, and then, the quantity of the land displacements in the Line of Sight, in the Limassol coastal front, is presented in this research, with the subsidence rates up to about (-5 to 4 mm / year). For the validation of the detected deformation, accurate ground-based geodetic measurements along the coastal area were used. Concordantly, taking into account that there are a significant number of skyscrapers planned to be built, this study attempts a preliminary assessment of the impact these structures will pose on the coastal front of the area of Limassol.

According to this study, approximately half of Africa's forests are utilized primarily or partially for the production of wood and non-wood commodities. Aims to evaluate Africa's forestry and forest products, namely Wood Forest Products (WFPs) and Non-wood Forest Products (NWFPs) in the sixteen (16) West African countries. While adhering to the following guidelines: wood extraction and preparation, analyzing wood primarily used as an energy source in Africa, identifying non-wood forest products in Africa, the state of export, trade, and customs procedures in West Africa, and examining the role of forests and forest stakeholders in Africa's low-carbon economy transition. An exploratory literature review of selected wood forest products and non-wood forest products (plants and animals) in West Africa identifying the country, the natural land area with the natural habitat issues of the forest, the species most harvested and traded in the West African sub-region. The study reemphasized some government legislation, policies, and market trade failures and limitations while also stating that trees may help in the low-carbon revolution through interventions aimed at maintaining, improving, and restoring natural capital have demonstrated that high environmental requirements of sustainable forest management (SFM) may be met in both natural and planted forests. The study identified a systematic assessment of the most common forest products (wood and non-wood forest products) considering the available data on the national forest reserves of the selected countries in West Africa. The study also revealed the need for biodiversity conservation of the available forest reserves to help mitigate the impact of global warming targeting the United Nation’s Sustainable Development Goal 13- Climate Action. Which is focused on integrating climate change mitigation, adaptation, impact reduction, and early warning signs into the national policies, improving forest planning and management education, awareness-raising, and institutional capacity within the sub-region.

Remote sensing/GIS techniques are a versatile tool for x-raying serial forest structural changes in retrospect. It would be impossible to evaluate past occurrences and changes in forest extents in past decades at Effan Forest Reserve without non-conventional means. Therefore, we adopted remote sensing technology using Landsat images to evaluate land-use change and degradation rates in the area with a view to ascertaining causal factors for possible minimization of forest degradation in Effan Forest Reserve. Land-use/land-cover changes were analyzed using USGS-Landsat TM and ETM images of 1987, 2002, 2014 and 2019. Field-data were collected using handheld GPS receiver and spatial statistical analyses were conducted using the ground control points (GCPs). For inventory data, a systematic sampling technique was adopted using ten 1.05 km-transects at 500 m intervals. A total of 50 sample plots of 50 × 50 m were used. All tree species with Dbh ≥10 cm were enumerated. Nineteen tree species in ten families were encountered with Vitellaria paradoxa as the most-frequently occurring species in the area. IUCN-listed endangered Pterocarpus erinaceus, hitherto abundant in the area, was rarely encountered during the survey, while Vitellaria paradoxa is gradually shrinking, going the relative abundance in the area. The result further showed that primary and secondary forests decreased considerably by 258.03 ha (46.72%) and 9.18 ha (3.63%), respectively, with a total forest loss of 50.3% in 32 years (8.4 hayr-1, 1.6% per annum). While forest plantation size doubled by 369.72 ha within the period. This is worrisome as the remaining fragmented forests appeared to be on the decline, except the riparian vegetation, due to inaccessibility to the riparian by loggers. It thus appeared that forest protection approaches were ineffective. Increased protection efforts could save this forest reserve, and the concerned authority should consider a focused-enrichment planting involving indigenous species for ecosystem-repair.

The 2018 summer drought in Europe was particularly extreme in terms of intensity and impact due to the combination of low rainfall and high temperatures. However, it remains unclear how this drought developed in time and space in such an extreme way. In this study we aimed to get a better understanding of the role of land-atmosphere interactions. More specifically, we investigated whether there was a change in water vapor originating from land, if that caused a reduction in rainfall, and by this mechanism possibly the propagation and intensification of the drought in Europe. Our first step was to use remote sensing products for soil moisture content (SMC) and the normalized difference vegetation index (NDVI) to see where the 2018 drought started and how it developed in time and space. Our SMC and NDVI analysis showed that the 2018 drought started to impact the soil and vegetation state in June in Scandinavia and the British Isles. After that it moved towards the West of Europe where it intensified in July and August. In September, it started to decay. In October, drought was observed in southeast Europe as well. Based on the observed patterns we divided Europe into six regions of similar spatiotemporal characteristics of SMC and NDVI. Then, we used a global gridded dataset of the fate of land evaporation (i.e., where it ends up as precipitation) to investigate whether the drought intensification and propagation was impacted by the reduction in water vapor transported from the regions that first experienced the drought. This impact was investigated by identifying the anomalies in the water vapor originating from land recycling, imports and exports within Europe during the spring, summer, and autumn seasons. From these regions we identified four drought regions and investigated the changes in water vapor originating from source regions on the development of drought in those regions. It was found that during the onset phase of the 2018 drought in Europe that the water vapor originating from land played an important role in mitigating the precipitation anomalies as, for example, the share of land evaporation contributing to precipitation increased from 27% (normal years) to 38% (2018) during July in West of Europe. Land evaporation played a minor role in amplifying it during the intensification phase of the drought as the share of land evaporation contribution to precipitation decreased from 23% (normal years) to 21% (2018) during August in West of Europe. These findings are somewhat in contrast to similar studies in other continents that found the land surface to play a strong amplifying role for drought development. Subsequently, we found that the relative increase in the amount of land water vapor originating from eastern half of Europe played a role in delaying the onset and accelerating the decay of the 2018 drought in West of Europe.

Abstract: Green walls and green dams are increasingly being considered as part of many nation-al and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria) from 1972 to 2019 by using Landsat imagery, Land Change Modeler and Open Land package. The future evolution of pine plantations for the year 2029 was also forecasted, based on an anthropogenic scenario (i.e., an-thropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but after that, pine plantations deteri-orated significantly due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land Change Modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation con-tinues at the same rate, the green dam will disappear in the Moudjbara region during the next few decades. Aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation

In response to the complex social, environmental and economic situation caused by the "Terra dei Fuochi" phenomenon, the IZSM collaborated closely with the Terra dei Fuochi working group, carrying out additional monitoring surveys both on food (QR Code Campania project[30]), and on the environment (Campania Trasparente project[31]). This model was developed in the context of the experience accumulated in the field of environmental and food monitoring, and represents an innovative tool aimed at increasing knowledge of the environmental context of the Campania Region through an objective, integrated and organic synthesis of complex environmental phe-nomena and territorial dynamics. The model proposed here is useful for the global and synthetic assessment of environmental pressure on a municipal basis. As shown, it can also be applied to aggregations of municipalities. Furthermore, it can be used in the context of institutional actions for the planning and monitoring of improvements on a local or regional scale. Finally, the pro-posed municipality-based environmental pressure index represents the basis for geo-stratification of the sample in the context of population biomonitoring studies on a regional scale, as in the described biomonitoring study design applicable to the Campania Region.

Based on the recorded watershed characteristics, the future conditions on the basin system can be predicted using a different method. In this study, dynamic land-use change and its impacts on the streamflow for the Dabus watershed were predicted using ANN-CA based method. The model performance for accurate prediction of the future land-use change on the Dabus River watershed has been checked by validation of the simulated value with the actual value, hence the overall kappa value (k) = 0.83 for the simulated 2016-LULC validated with actual 2016-LULC. Then, 2026-LULC was predicted based on the 2004 and 2009-LULC. The streamflow for the case of 2004 and 2009-LULC has been simulated using the SWAT model. The value of NSE = 0.87 and 0.90 was attained during validation of simulated streamflow for 2004 and 2009-LULC data cases, respectively. The agreement of simulated value of streamflow with the observed data is indicated as R2 = 0.91 and 0.96 for 2004-LULC and 2009-LULC. The effects of the dynamic land-use change on streamflow for the predicted land use(2026-LULC) catchment were evaluated by T-test analysis. Hence, T-stat =0.04 and -0.002 in the case of simulated streamflow used 2004-LULC and 2009-LULC, respectively compared with simulated value using 2026-LULC.

Analysis of the correlation between indices (Normalized Difference Vegetation Index, Normalized Difference Barren Index and Modified Normalized Difference Water Index) and land surface temperature is used to natural resources and environmental studies. This research aimed to analysis of Land Surface Temperature due to dynamics of Different Indices (NDVI, NDBaI and MNDWI) Using Remote Sensing Data in three selected districts (Gida Kiremu, Limu and Amuru), western Ethiopia. From thermal and multispectral bands of landsat imageries (Landsat TM of 1990, landsat ETM+ of 2003 and landsat OLI/TIRS of 2020) Land surface temperature and NDVI, NDBaI and MNDWI were calculated. Correlation analysis was used to indicate relationships between LST with NDVI, NDBaI and MNDWI. The study found that Land Surface Temperature was increased by 5⁰C from 1990 to 2020. Vegetation areas (NDVI) and Water bodies (MNDWI) have strong negative relationship with Land Surface Temperature (R²= 0.99, 0.95) whereas Barren land (NDBaI) has positive relationship with Land Surface Temperature (R²= 0.96). Finally, we recommend the decision makers and environmental analyst to emphasis the importance of vegetation cover and water body to minimize the potential impacts of land surface temperature.

Taking a typical forest underlying surface as the research area, this study employed the unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including tree height and canopy radius, which were used to improve the Noah-MP land surface model conducted in Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of CN-Din forest followed a Weibull distribution. The replacement of the parameters by these observed UAV would result in the Noah-MP model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux which could decrease up to -11% in the midday while increase up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately deliver the heterogeneity for the underlying surface.

The stormwater drainage problem is one of the major challenges facing in Shire Endaslasse town, Ethiopia. In a town, Street flooding and overtopping drainage system problems are occurring during the rainy season. This causes ponding which poses difficulties in ease of transportation and it hinders the day-to-day activity of the people. So, the study focuses on the performance of the stormwater drainage system in Shire Endaslasse town using Arc GIS and SWMM5.1. For this study, the primary data were collected by field surveys and interviews with the council body. Simulation results for storm events show that in some of the drainage systems in different regions of Shire Endaslasse town have flooded. During the field observation, the drainage structures are filled with solid wastes, inadequate inlet and outlet structures and some of the top element of the manhole have been broken this may cause a problem of aesthetic and healthy at large it may increase flood risk. The flooding risk in the drainage systems is very high due to the drainage system is undersized to cope with the current rainfall rates, but also is very limited to face the upcoming predicted rainfall.

Agricultural land fires have been linked to various and adverse impacts on ecosystems, food security and the agriculture sector. Understanding the patterns and drivers of agricultural land fires is essential for effective agricultural land fire management. The key objectives of this study were to (1) analyze the temporal and spatial patterns of agricultural land fires using satellite remote sensed data, (2) assess a range of environmental conditions that could drive the occurrence of agricultural land fires, (3) determine the best model for predicting agricultural land fires and (4) determine the relative contribution of each environmental condition variable on the best predictive model. We used both univariate and multivariate regressions for the fire prediction capability of four independent environmental conditions (fuel, weather, topographic and anthropogenic). Analysis of historical satellite data revealed that agricultural land fires were more frequent than forested land fires. Our analyses also revealed that fuel condition was the most important variable for predicting agricultural land fires followed by weather, topographic and anthropogenic conditions. This study provides a novel multivariate model for predicting agricultural land fires that harbors the potential to improve agricultural land fire management and reduce fire risk within the agricultural sector.

Lake Urmia in northwestern Iran is the largest lake in Iran and the second largest saltwater lake in the world. The water level in Lake Urmia has decreased dramatically in recent years, due to drought, climate change, and overuse of water resources for irrigation. This shrinking of the lake may affect local climate conditions, assuming that the lake itself affects the local climate. In this study, we quantified the lake’s impact on the local climate by analyzing hourly time series of data on climate variables (temperature, vapor pressure, relative humidity, evaporation, and dewpoint temperature for all seasons, and local lake/land breezes in summer) for the period 1961-2016. For this, we compared high quality, long-term climate data obtained from Urmia and Saqez meteorological stations, located 30 km and 185 km from the lake center, respectively. We then investigated the effect of lake level decrease on the climate variables by dividing the data into 1961-1995 (normal lake level) and 1996-2016 (low lake level). The results showed that at Urmia station (close to the lake), climate parameters displayed fewer fluctuations and were evidently affected by Lake Urmia compared with those at Saqez station. The effects of the lake on the local climate increased with increasing temperature, with the most significant impact in summer and the least in winter. The results also indicated that, despite decreasing lake level, local climate conditions are still influenced by Lake Urmia, but to a lesser extent.

Demographic and socio-economic developments couple with other requirements to satisfy human needs result in rapid urban expansion sometimes with increasing rate of surface extent greater than the rate of growth of population, that result in continuous sealing of ground surface thereby affecting ecosystem services. This study applied remote sensing toward achieving the progress of SDGs and stage to determine the ratio of the rate of land consumption to the rate of population growth of Gombe metropolis. QGIS 2.18 was used for the image processing and classification analysis for the key Landsat ETM+ (Enhanced Thematic Mapper), Impervious Surface Indices and population data to inform on the urban trend and LCR/PGR for the periods 2000-2005, 2005-2010, and 2010-2015. The result appears that the LCR/PGR for the periods of study show split trends. During 2000-2005 the result shows that the study area expanded outward with LCR/PGR of 1.2. The result also indicate that during 2005-2010, the study area densified with little expansion with the LCR/PGR of 0.8. The result further reveals that during 2010-2015 the LCR/PGR reached 1.8. Pointing that the study area expanded outward with the rate of ground sealing getting high.

Abstract: Many countries around the world suffer from the lack of a sea port directly linked to the rest of the world. Such countries are called "landlocked countries". This leads to Weak competitiveness of their products in the global market, as well as to the high cost of the imports. Africa has the largest share of these countries, with 16 of the 43 landlocked countries around the world. The aim of this paper is to propose a general framework for criteria that can be used to choose between ports in transit countries that can be used for import or export. These criteria are related to the assessment of the sea ports in terms of infrastructure and tariffs. It is also related to transport infrastructure from the transit country to the landlocked country and the level of safety. The study identified nine criteria that could be used to compare between ports in transit countries. Using Full Consistency Method (FUCOM) to evaluate those criteria showed that the number of navigation lines is the most important criteria followed by the port service level.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

The Sentinel-2 satellite mission offers high resolution multispectral time series image data, enabling the production of detailed land cover maps globally. At this scale, the trade-off between processing time and result quality is a central design decision. Currently, this machine learning task is usually performed using pixelwise classification methods. The radical shift of the computer vision field away from hand engineered image features and towards more automation by representation learning comes with many promises, including higher quality results and less engineering effort. In this paper we assess fully convolutional neural networks architectures as replacements for a Random Forest classifier in an operational context for the production of high resolution land cover maps with Sentinel-2 time series at the country scale. Our contributions include a framework for working with Sentinel-2 L2A time series image data, an adaptation of the U-Net model for dealing with sparse annotation data while maintaining high resolution output, and an analysis of those results in the context of operational production of land cover maps.

A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error-covariance in the EnOI is sampled in two ways: i) by using the stochastic spread from an ensemble open-loop run, and ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in-situ observations at a 95% significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in-situ data at the same significance level; however this improvement is dependent on which in-situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95% significance level. The study also suggest that the EnOI can be used for bias-correction of the atmospheric fields where post-processed data are not available. Finally, we assimilate three different Level-2 satellite derived soil moisture products from ESA Climate Change Initiative (CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in-situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in-situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.

Earth’s land surface area is raised from conventionally flat 15 to 64 Gha to account for hilly undulation and soil relief detail. Three main aspects are: topography, rugosity/tortuosity and micro-relief/porosity of vegetation-free ground. Recalibration is arrived at from four approaches: first, direct empirical estimates from the few compiled satellite or LiDAR data with means of +2.5–26% progressively overlain by +94% at cm² scale for soil ruggedness then +108% for mm² micro-relief; second, from digital elevation models with 1.6–2.0 times flat areas; third, by ‘reverse engineering’ global soil bulk densities and carbon reserves requiring x 2–6 land. Finally, a Fermi estimation conveniently sets the World’s new surface area – that exposed to Sun, air and rain – at 100 Gha (with 36 Gha flat ocean). Soil organic carbon (SOC) is thence raised to 8,580 Gt mainly in SOM/humus with its biotic complexity plus roots, VAM-fungi and leaf-litter, that itself = 17,800 Gt. Although four to six times IPCC’s or NASA/NOAA’s calculations of just 1,500–2,300 Gt SOC, this is likely an underestimation. Global biomass and biodiversity are at least doubled (x 2–3.5) and net primary productivity (NPP) similarly increased on land to >270 Gt C yr^-1 due to terrain.

Accurate, detailed and recent Information about land cover/use is important and much more needed for different aspects of sustainable development and environmental management. As remote sensing datasets are becomes one of the most important and effective tools to generate such information, this study aimed to generating land cover map for sub area in Al-Ahasaa Oasis, Saudi Arabia, by using and classifying a subset of Landsat-ETM+ image of the selected study area, as bases and required input for future studies and researches. Different image preprocessing techniques in addition to a will-known and widely used classification method (i.e., Maximum Likelihood classifier) were applied. To be reliable with the final product, accuracy assessment was carried out with 89% agreement and accepted according to the applied method. Different land cover classes were found in the study area, which includes (Sand dunes, Water bodies, Sabakha, Bare soil, Urban, and Agricultural lands). The study also revealed that the dominant land cover class is sand dunes with approximately ± 70% in area. The study strongly indicated that the area has long been affected by sand movement. Finally, the study suggested that, further researches with more advanced methods rather than traditional methods are needed in the future to support the findings of this study, with high degree of accuracy.

Regional heat capacity change is calculated from the ratio between the addition or subtraction of heat (ΔQ) with the increase or decrease in temperature (ΔT) region. The purpose of this study is to calculate the regional heat capacity change due to the changes of land cover composition with forest, shrubs, oil palm plantation and bare soil using Landsat-5 TM satellite data on 1994, 2000 and 2010. Total area that used on ​​this study is 12971 ha. In 1994-2000, 4 % of forest area and 2% shrubs were increased, followed by additional of biomass forest 4.01 tons/ha and 2.83 tons/ha for shrubs. The increased of forest area and biomass (tons/ha) caused by forest and shrubs growth processing towards climax that added the canopy volume. So that, the regional heat capacity in 1994 amounted 19384 MJC^o-1 increased to 19929 MJC^o-1 in 2000. Data observation for 2000-2010 showed that forest area decreased by 66% due to forest’s clearing into oil palm plantations (47%), shrubs (8%) and bare soil (11%). But, plant’s biomass continue to increased, i.e 1.48 ton/ha for forest, 2.73 tons/ha for shrubs and 4.63 tons/ha for bare soil. Before 2000, there was no land cover by oil palm plantations, so the increasing rate from this land was the biggest than the three other lands, amounting to 122.29 tons/ha. Decreasing in the percentage of forest area does not cause a decrease in the heat capacity of the region. Intensive maintenance on oil plam plantation such as water management, fertilizer and planting space made it biomass productivity and ability to save the heat is greater than the forest. As the result, in 2010 regional heat capacity increased to 22508 MJC^o-1.

Woody vegetation in farmland acts as a carbon sink and provides ecosystem services for local people, but no macro-scale assessments of the impact of management and climate on woody cover exists for drylands. Here we make use of very high spatial resolution satellite imagery to derive wall-to-wall woody cover patterns in tropical West African drylands. In arid and semi-arid Sahel, areas of more people are associated with more trees: mean woody cover is greater in farmlands (12%) than in savannas (6%), and likewise it is higher close to villages than further away. In sub-humid savannas of West Africa, woody cover is generally above 20% and decreases with increasing population density, but remains around 15% in farmlands, independent of rainfall. In the region as a whole, rainfall, terrain and soil are the most important (80%) determinants of woody cover, while management factors play a smaller (20%) role. We conclude that agricultural expansion cannot generally be claimed to cause woody cover losses, and that observations in Sahel contradict simplistic ideas of a high negative correlation between population density and woody cover.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

The goods and services produced by forest vegetation ecosystem are the driving force for the rapid, high-quality and sustainable development of human society. In history, with the increase of population and economic development, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services in a country or a region. To meet the demands, most of the original forest has become farmland, plantation and grass and crops land. As a result, the plant water relationship changed from equilibrium to non-equilibrium, which easily led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the question and realize the sustainable utilization of soil water resources and the high-quality sustainable development of forest, it is necessary to apply the limit theory of plant utilization of soil water resources and the vegetation carrying capacity theory in the critical period of plant-water relationship regulation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit and realize high-quality and sustainable development.

The article discusses the use of satellite data and drones for land monitoring in Kazakhstan, emphasising their importance in the context of population growth and increasing agricultural demand. Satellite technologies, such as Sentinel-2 and Landsat, provide essential data for analysing land resources, including soil erosion and the condition of agricultural lands. Unmanned aerial vehicles (UAVs) complement satellite data by offering detailed low-altitude imagery, enabling the detection of local issues such as irrigation system failures and soil compaction.The study demonstrates that integrating drone and satellite data allows for more efficient land resource management. For example, 35% of agricultural land in southern Kazakhstan is affected by soil degradation, while overgrazing issues were identified in the northern regions. These innovative monitoring methods enable early detection of threats, allowing timely measures to be taken to improve land management practices.The conclusion highlights that the use of these technologies requires not only infrastructure but also skilled professionals. The integration of satellites and drones creates opportunities for more precise and timely monitoring, which is essential for sustainable land resource management in Kazakhstan.

Climate change-induced Sea level rise, shoreline changes, and coastal erosion are projected to drive massive population displacement and mobility in Africa. This study was conducted to examine the pattern of shoreline changes, coastal erosion, land use/Land cover dynamics their projections, and its implications on internal migration in Senegal, Kenya and Tanzania representing West and East Africa. The digitized shoreline was mapped into both erosion, accretion and trend analysis which further explains the vulnerability and physical processes that could trigger human displacement within the context of environmental/climate migration. Analysis of landuse and land cover dynamics was obtained from Landsat 5 TM of 1986, Landsat 7 ET of 2006, Landsat 8 OLI/TIRS of 2016 and Landsat 9 OLI/TIRS 2022 and computed using ArcGIS 10.7 for Land-use change and percentage change in square kilometers was conducted to examine landuse/landcover dynamics and their contributions to the risk of coastal erosion in the study regions. The outcome of the shoreline analysis reveals that 972.03sqkm of land has been lost to coastal erosion in Senegal from 1986-2022 with 2016-2022 described as the period with the highest in terms of land loss. In Kenya, -463.30sqkm of land has also been lost to coastal erosion and agents of wave processes with 1986-2006 recording the highest share of -87.74% loss of valuable land while In Tanzania, -1033.35sqkm of valuable land has been lost from 1986-2022 to coastal erosion with 2006-2016 alone recording -10.4634% of land loss. The result of the land use/land cover percentage change analysis indicates a massive loss of vegetation cover with a significant increase in settlement representing urbanization. The scenario modeling of the shoreline on 10,20 and 30ms indicates that 567 persons per sq, 25904.5 persons per sqm and 25904.5 persons per sq km for both 20 and 30ms will be displaced in Senegal while in Kenya 577.5 persons per sq km will be displaced at 10m followed by 1210.3 persons per sq km at 20m and 7737.3 sq km at 30m. In, Tanzania, 702001.9 persons per sq km are projected to be displaced at 10m shift in the shoreline. Structured Questionnaires were administered to elicit responses from coastal dwellers on their perception of coastal erosion and environmental migration as part of ground truthing and the result of the survey affirms that coastal erosion and its exposure are the major drivers of environmental migration in the study area.

Although floods, as well as other natural disasters, can be considered relevant causes of intra-generational inequalities, the frequent catastrophes and the resulting damages to territory reflect the generalized indifference about inter-generational justice. Societal concerns, such as land protection, typically involve the administrative system performing proactive policies in the perspective of inter-generational solidarity, but subsidiarity has made more and more independent the local communities. As a consequence, the attention toward the long run effects – typically concerning the territorial system, as a whole, at the geographical scale – has been dispersed, and the proactive policies coming from the central government has became more ineffective. Regarding the case of the flood happened in 2009 in the Fiumedinisi-Capo Peloro hydraulic basin, in the northeastern part of Sicily, Italy, we propose an economic valuation – carried out by performing the method of the imputed preferences – in order to compare the expenses incurred by the public authorities responsible for protecting the territory to the costs of the rehabilitation of the damaged areas. Some considerations about the economic significance of the proactive policies for the arrangement of territory are addressed according to the role played by the social discount rate in the inter-temporal economic calculation.

Water resource management in agriculture faces complex challenges due to increasing scarcity, exacerbated by climate change, and the intensification of conflicts among various user groups. This study addresses the issue of predicting and managing these conflicts in the Longaví River Basin, Chile, by considering the intricate interactions between hydrological, social, and economic factors. A socio-hydrological agent-based model (SHABM) was developed, integrating hydrological, economic, and behavioral data. The methodology combined fieldwork with computational modeling, characterizing three types of agents (selfish, neutral, and cooperative) and simulating scenarios with varying levels of water availability and oversight across three Water User Organizations (WUOs). The key findings revealed that: (1) selfish agents are more likely to disregard irrigation schedules under conditions of scarcity and low supervision; (2) high supervision (90%) significantly reduces conflicts; (3) water scarcity exacerbates non-cooperative behaviors; (4) high-risk conflict areas can be identified; and (5) behavioral patterns stabilize after the third year of simulation. This work demonstrates the potential of SHABM as a decision-making tool in water management, enabling proactive identification of conflict-prone areas and evaluation of management strategies.

The role of trees in watershed hydrology is governed by many environmental factors along with their inherent characteristics and not surprisingly has generated into diverse debates in the literature. Herein, this state-of-the-art review provides an opportunity to propose a conceptual model for understanding the role of trees in watershed hydrology and examine the conditions under which they can be an element that increases or decreases water supply in a watershed hydrology. To achieve this goal, this review addressed the interaction of forest cover with climatic conditions, soil types, infiltration, siltation and erosion, water availability, and the diversity of their ecological features. The novelty of the proposed conceptual model highlights that tree species and densities, climate, precipitation, type of aquifer, and topography are important factors affecting the relationships between trees and water availability. This suggests that forests can be used as a nature-based solution for conserving and managing natural resources, including water, soil and air. To sum up, forests can reduce people’s imprint, thanks to their role in improving water and air quality, conserving soil, and other ecosystem services. The outcomes of this study should be valuable for decision-makers when investing in reforestation in a watershed hydrology.

Flood protection infrastructures are crucial for enhancing the resilience of societies exposed to natural hazards. Newly designed infrastructures are evaluated for sustainability using a coherent and internationally recognized method defined by the International Hydropower Association (IHA). However, older structures require a different assessment approach. Popescu et al. (2024) proposed a modified IHA protocol, mHSAP, which identifies opportunities for improvement and develops a sustainability evaluation framework for existing infrastructures. This paper applies the modified protocol to evaluate the sustainability of two types of flood protection structures: a unique canal system for flood-drought protection of an urban area and a flood protection dyke. The time of operation of over 250 years, and respectively over 50 years. The application of the modified framework demonstrates its advantages in identifying areas for improvement in operating the flood protection structure, such that it is maintained sustainable. It also illustrates how Romanian water boards can use such tools to facilitate collaboration between structure owners and stakeholders, allowing them to assess the risks and effects of flooding on society. Potentially water boards, could use the results of the method to account for the effects of climate change and addressing the issue in a coordinated and efficient manner. Through these two examples from Romania, we also show that the mHSAP framework has the potential to actively support the fulfillment of the United Nations Agenda 2030 Sustainable Development Goals (SDGs).

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Groundwater represents a pivotal asset in conserving natural water reservoirs for potable consumption, irrigation, and diverse industrial uses. Nevertheless, human activities intertwined with industry and agriculture contribute significantly to groundwater contamination, highlighting the critical necessity to appraise water quality for safe drinking and effective irrigation. This research primarily focused on employing the Water Quality Index (WQI) to gauge water's appropriateness for these purposes. However, the generation of an accurate WQI can prove time-intensive owing to potential errors in sub-index calculations. In response to this challenge, an artificial intelligence (AI) forecasting model was devised, aiming to streamline the process while mitigating errors. The study collected 422 data samples from Mirpurkash, a city nestled in the province of Sindh, for a comprehensive exploration of the region's WQI attributes. Furthermore, the study probed into unraveling the interdependencies amidst variables in the physiochemical analysis of water. Diverse machine learning classifiers were employed for WQI prediction, with findings revealing that random forest and gradient boosting eclipsed other algorithms, achieving an accuracy rate of 99%. In close pursuit were SVM and XGBoost, registering accuracy scores of approximately 95% and 93%, respectively, while KNN and Decision Trees garnered accuracy rates of 88% and 87%, respectively. In addition to WQI prediction, the study conducted an uncertainty analysis of the models using the R-factor, providing insights into the reliability and consistency of predictions. This dual approach, combining accurate WQI prediction with uncertainty assessment, contributes to a more comprehensive understanding of water quality in Mirpurkash and enhances the reliability of decision-making processes related to groundwater utilization

The increasing demand for water resources in urban areas, such as Bangladesh, due to population growth is a significant concern. One potential solution under consideration is the use of air conditioning (AC) condensate water. A study conducted at the European University of Bangladesh (EUB) focused on assessing the quality and quantity of AC condensate water from various systems. The results indicate that the collected water generally adhered to the quality standards established for drinking and household use in Bangladesh. Parameters such as pH (averaging 6.8), turbidity (1.08 NTU), total dissolved solids (TDS) (averaging 219 mg/L), iron content (0 mg/L), alkalinity (averaging 41.67 mg/L), arsenic (0 mg/L), chemical oxygen demand (COD) (averaging 3.67 mg/L), biochemical oxygen demand (BOD) (averaging 1.33 mg/L), chloride content (averaging 30.77 mg/L), and other factors were evaluated. Moreover, the AC units at EUB, varying in cooling capacity (1 ton, 2 tons, and 4 tons), produced substantial monthly volumes of 96, 177, and 354 liters of condensate water, respectively. This underscores the potential of AC condensate water as a valuable resource for addressing urban water scarcity. As a result, there is a pressing need for local decision-makers and policymakers to establish well-defined guidelines for the effective utilization of AC condensate water to mitigate water scarcity issues in urban areas.

A very important role in determining the quality of water is the assessment of its microbiological quality. Water quality control, which could pose a direct threat to human health and life, is performed in the case of water produced at the water treatment plants, tap water or water in swimming pools. However, these traditional methods used to assess its quality are laborious and time consuming. In emergency and incidental situations, in the era of terrorist threats, the need for quick, reliable and reproducible microbiological determinations seems to be essential. In this study, an attempt was made to compare various methods of assessing the microbiological quality of water. The assessment was carried out for waters with different microbiological characteristics: surface waters, rainwater, groundwater, and water supply. The evaluation was carried out using traditional culture methods and high-speed methods: flow cytometry and luminometry. The analysis of microbiological parameters were the basis for the statistical analysis. The conducted microbiological analysis of various types of water, along with their statistical evaluation, showed different dependencies for each of the analysed waters.

Knowledge of water availability in terms of spatial (i.e., depth) and temporal variability of soil water is essential to describe soil water infiltration and storage processes accurately. Therefore, performing simulations of soil water dynamics can be a valuable tool to evaluate different land uses and their impact on water availability. Consequently, this study aimed to model the volumetric soil water content (θ, cm3 cm-3) under agroforestry systems (AFS) with cocoa. For this purpose, the θ was monitored at different depths (0-20, 20-40, 40-60, 60-80, 80-100 cm) in the soil profile of four plots (20 × 50 m) of cocoa under agroforestry systems. Environmental conditions significantly influenced the water balance of the cocoa crop. There were seven moments when evapotranspiration (ET0) was higher than 5 mm d-1. During those moments, the environment exhibited higher PAR values of 1041 µmol m-2 s-1, very low atmospheric relative humidity (RHa) levels (around 45%), higher ambient temperatures of 32.2 ºC and a vapor pressure deficit of 1.6 kPa whose θ levels reached 0.32 cm3 cm-3 and a water balance of -5.7 mm, which presented negative values during most of the study period. The θ obtained from the HYDRUS-1D model presented a slight bias as a high level of coherence between the observed values, based on the model's goodness-of-fit estimators. The above provides accurate simulations of soil water content at various depths, much-needed information for management schemes for cocoa cultivation under agroforestry systems.

Within this paper, a machine learning algorithm is used to investigate the importance of certain setpoints and parameters in the filtration processes of a large-scale water treatment facility. Previously, a model for the filtration process based on Run-to-Run Control was proposed and tested against sample data from the treatment plant, but it was quickly found that such a model was incompatible for successfully computing setpoints of operation which minimize the energy cost of running the filtration systems. The machine learning model described herein is an attempt to elucidate the importance of the available data on the filtration systems and to identify the most important variables that influence the filtration run time.

With permafrost degenerating caused by climate change, water accumulation increases in permafrost regions during last decades. Water accumulation will deteriorate existing status of engineering in cold regions. Water accumulation can make a thermal effect on permafrost under construction, even result in failure of the subgrade. Moreover, the thermal effect is related to water temperature. However, temperature variation of water accumulation is complex, and its influence factors include air temperature, environment, scope of water accumulation and so on. In order to make analysis of the damage mechanism of water accumulation on permafrost, it is necessary to explore the internal temperature change of water accumulation. This paper proposes a review about temperature calculation method of water accumulation in cold environment. The thermal calculation method between air and water boundary of water accumulation is summarized. Water temperature change of water accumulation with various type is analyzed. The thermal calculation considering phase transformation in water accumulation is discussed, and heat transfer from the bottom of water accumulation to the underlying soil is further studied. Finally, the key factors which are advantageous to make research about the thermal effect of water accumulation in permafrost is proposed to optimize calculation method.

Since the second half of the second millennium AD, water management among the Chagga people of Kilimanjaro in Tanzania has involved community collaboration in the construction, ownership and management of water infrastructure. Chagga settlement on the lower slopes of Kilimanjaro transformed the landscape significantly to reflect an agrarian society characterised by decentralised forms of socio-political and economic organisation. Such organization involved conception, construction, and post-construction management of water distribution systems, constituting high-level socio-political complexity. The study employs ethnography, archaeological surveys and GIS to document water infrastructures on the lower slopes of Kilimanjaro. We conclude that community collaboration was key in management of the water infrastructure and by extension, agriculture, which sustained Chagga and chiefdoms for centuries.

Rocks are materials with a wide variety of structures and properties. These can be unprocessed conglomerates of conglomerated minerals as well as crystallized outcrop or metamorphic rocks. Their processing, especially shaping, poses many technological difficulties. Therefore, it is very important to answer the question of how these natural materials yield to high-pressure water jet and abrasive water. It is equally important to determine the effect of key process parameters such as pressure, water nozzle diameter and feed rate on cutting efficiency. The first two parameters determine the water output and power of the jet, while the third determines the jet erosion time per unit volume of material. Their interdependence, using appropriate evaluation indicators, allows to determine the energy intensity of processing and directions for its minimization.

This study looks at the application of delayed action Passive InfraRed (PIR) sensors in the control of water use for urinal flushing. In this we briefly review the literature on urinal controls before reviewing four different approaches to PIR urinal controls. Existing literature discusses some of the pros and cons of different types of urinal control. However, the literature doesn’t consider the marked differences that can occur within individual approaches, based on the way controls operate. This study was initiated at the University of Surrey during 2019 following a water saving audit, in an attempt to bring down what had been identified as one of the largest users of water. This paper therefore aims to identify the most effective way to reduce water consumption of urinal systems, through retro-fitting PIR control systems within the variety of settings found across university campuses. This paper also reviews the different reductions achieved over periods of different levels of use, linked to term time, holidays, Covid-19 related lockdowns, and the ‘new normal’. It found that grouped delayed action flushing was the most effective form of urinal control for reducing water use. The delayed action, grouped PIR sensors, achieved between, a 59-64% adjusted reduction against the control group during non-Covid19 periods, and a 35% reduction against the control group during lockdowns.

Turbulence is a fluid dynamic problem refractory to mathematical treatment. Examining a theoretical model of liquid water flowing in a cylinder at different Raleigh numbers, we propose a novel approach to elucidate the first stages of turbulent flows. The weakly bonded molecular assemblies of liquid water form a fluctuating branched polymer in which every micro-cluster displays different density. Against the common view of liquid water as an incompressible and continuous fluid, we suggest that the occurrence of transient local aggregates could be able to generate the vortices and eddies that are the hallmarks of turbulence. We quantify the local changes in velocity, diameter and density required to engender “obstacles” to the average flow. Then, we show how these microstructures, equipped with different Raleigh numbers and characterized by high percolation index, could generate boundary layers that contribute to micro-vortices production. We conclude that the genesis of turbulence cannot be assessed in terms of collective phenomena, rather is sustained, among many other factors, by the underrated microscopic inhomogeneities of fluids like liquid water.

Stable isotope concentrations in the soil, rain and ground water have been used to trace the water extraction zones of plants in different environments. The need to identify the plant water use by plants in afforestation programs to control desertification increases the importance of sap water partitioning of plants in sand dune areas. However, the introduction of new plant covers exerts pressure on the water resources and can affect the local soil water conditions. In this study, we analyzed the isotope concentrations in rain, soil, sap, and ground water after the summer of 2010. Two experimental plots established in the Hailiutu catchment (Shaanxi province, northwest China) were selected to gather the water samples between September and October 2010. One plot is dominated by Salix bushes (Salix psammophila C. Wang \& Chang Y. Yang) and the other by the tree species Willow (Salix matsudana Koidz.). The total precipitation at the experimental site was 401 mm/yr during 2010, while 88.7 mm was collected in total for the period September to October. Willow trees transpired 12.82 kg/d being almost three times larger than Salix shrubs (4.57 kg/d). Despite the transpiration rates of both plant species and the few rain events in the region, the soil water beneath the plant covers is not depleted. Stable isotope signature of soil water beneath both covers shows the fractionation front in Salix at 20 cm depth and at Willow at 40 cm depth. However, soil water signature is closer to the groundwater than the collected rain water.

In this article, the quality of water in the reservoirs of Lake Arpi, Lake Yerevan, Akhuryan, Azat, Aparan and Kechut was estimated with usage of the Armenian Water Quality Index. It was established that in the waters of reservoirs the the maximum permissible concentration of copper, vanadium, aluminum, chromium, manganese, iron, NH4+ and NO2- regularly increases. The following computational algorithm was used for determination of the Armenian Water Quality Index values: to determine the number of cases of MPC excess of i-substance or indicator of water –n; to estimate the total amount of cases of the maximum permissible concentration (N) – N = ∑n; to computes log2N, nlog2n and ∑nlog2n; to determine geoecological syntropy (I) and entropy (H): I = ∑ nlog2n/N and H = log2N – I. Then, Geo-Ecological Evolving Organized index index was determined: G = H/I. Further, the total amount multiplicity of MAC exceedances was estimated: (M) - M=∑m and log2M was computed. Finally, Armenian Water Quality Index was obtained: AWQI = G + 0.1log2M. It was established that the Armenian Water Qquality Index showed a linear dependence on the Water Contamination Index, the Specific Combinatory Water Quality Index, the Geo-Ecological Evolving Organized index and an inverse dependence on the Canadian Water Quality Index.

For decades, the Ébrié Lagoon in Côte d'Ivoire has been the receptacle of wastewater effluent and household waste transported by runoff water. This work assesses the spatio-temporal variability of the Ébrié lagoon water quality at the city of Abidjan. The methodological approach used in this study is summarized in three stages: the choice and standardization of the parameters for assessing water quality for uses such as aquaculture, irrigation, watering, and sports and recreation; the weighting of these parameters using the Hierarchical Analysis Process (AHP) of Saaty; and finally, the aggregation of the weighted parameters or factors. Physicochemical and microbiological analysis data on the waters of the Ébrié lagoon for June and December of 2014 and 2015 were provided by the Ivorian Center for Anti-Pollution (Centre Ivoirien Anti-Pollution, CIAPOL) and the concentrations of trace elements in sediments (As, Cd, Cr, Pb, Zn) were used. The aggregation of standardized and weighted parameters allowed the determination of the Water Quality Indices (WQI) by usage for each bays of the lagoon. The results show that in both 2014 and 2015, the waters of the Ébrié lagoon were generally of poor quality for the different uses examined in this study (aquaculture, irrigation, watering and sport and recreation) with an accentuation in 2015. However, some bays of the lagoon have waters of dubious to satisfactory quality. This study contributes an improved evaluation of the Ébrié lagoon waters.

This study estimates rainfall interception losses from natural wetland ecosystems based on maximum canopy storage measurements. Rainfall interception losses play an important role in water balance, which is crucial in wetlands, and has not yet been thoroughly studied in relation to this type of ecosystem. Maximum canopy storage was measured using the weight method. Based on these measurements, daily values of interception losses were estimated and then used to calculate long term interception losses based on precipitation and potential evapotranspiration data for the 1971–2015 period. Depending mainly on the number of days with precipitation, the results show that total interception losses for the growing season as well as monthly interception losses are around 13% of gross rainfall. This value is similar to the values observed for some forests. Hence, interception losses should not be disregarded in hydrologic models of wetlands, especially because data trends in meteorological conditions (mainly number of days with precipitation) show that interception losses will increase in the future if those trends stay the same.

As the cost of conventional energy continues to rise, and concerns over the environment grow, there is a growing interest in sustainable energy. It is believed that conventional energy will only last for around 50 years, making it essential to find a renewable energy source that is safe and feasible to replace fossil fuels. Solar energy is a superior alternative to conventional energy, as it is renewable and produces green energy that can be used directly. The maritime industry has found itself at the forefront of an evolving environmental consciousness, driven by the imperative to mitigate the carbon footprint left in the wake of ships. In this journey towards sustainability, solar energy has emerged as a beacon of hope, harnessing the boundless energy of the sun to wean vessels off their dependence on fossil fuels. Technological advancements have made solar power more accessible, and we can now see the use of solar panels on large ships and small crafts to reduce fuel usage and emissions. Solar panels are also increasingly used to power homes and businesses, and many countries are implementing policies to encourage their use. Solar energy is a key solution in reducing our dependence on non-renewable energy sources and combating climate change. However, the adoption of solar energy is but a stepping stone towards maritime sustainability, as the integration of CO2 capture, utilization, and storage (CCUS) technologies promises to amplify the industry's environmental impact to unprecedented heights.

Energy imbalance gap (EIG) is defined as the average daily difference between energy intake (EI) and energy expenditure (EE). This study aimed to examine the associations between EIG and sociodemographic and anthropometric variables in the adolescent population of eight Latin American countries. A total of 680 adolescents aged 15 to 18 were included in this study. EI was estimated using two non-consecutive 24-hour dietary recalls. EE was predicted from Schofield equations using physical activity levels obtained through the long version of the International Physical Activity Questionnaire. Sociodemographic data and anthropometric measurements were also obtained. A descriptive analysis and multilevel linear regression models were used to examine associations between variables. The mean EI, EE, and EIG were 2091.3 kcal, 2067.8 kcal, and 23.5 kcal, respectively. Argentina and Colombia had the highest EI and EIG, whereas Chile and Costa Rica had the lowest EI and EIG. Males had a higher EI (2262.4 kcal) and EE (2172.2 kcal) than females (1930.1 kcal and 2084.5 kcal), respectively (p<0,05). Overweight subjects had a lower EIG than did underweight and normal-weight subjects (p<0,05). Subjects with high SES had a lower EE (2047.0 kcal) than those with low SES (1963.7 kcal) (p<0,05). Sex and BMI were associated with EIG in adolescents from Latin America.

Energy management, especially in communities, is attracting growing interest, but is often marred by confusion between the terms "Energy Information System" (EIS) and "Energy Man-agement System" (EMS). This ambiguity hinders understanding of their use and role in improv-ing energy performance. Our objective is to clarify these terms and their contribution to energy management. We used a mixed qualitative and quantitative approach to evaluate and compare the criteria of definition, objective, functionality, role, as well as correlated elements such as or-ganizational structure, responsibilities, planning and policy, according to the requirements of ISO 50001, in addition to criteria specific to the two systems. The study reveals differences in the roles of the EIS and the SME, with a complementarity of 40% between the two systems, depend-ing on the positioning of the EIS in relation to the elements of the SME process. The EIS plays a crucial role in facilitating the implementation of the EMS according to ISO 50001. This clarifica-tion contributes to a better understanding of the respective roles of these systems in energy management, thus helping communities to improve their energy performance in an effective manner.

A comprehensive Energy Audit of a Maintenance facility was performed to assess its energy performance and identify scope for improvement. The facility’s Energy Use Intensity (EUI) for 2022 was 404 kWh/m2 — more than double the Benchmark EUI for Maintenance facilities (151 kWh/m2) recommended by EnergyStar. Furthermore, the Load Factor for 2022 was 0.22, which is lower than the recommended minimum of 0.75 for an efficient building. The audit encompassed an in-depth evaluation of the building's structural and operational characteristics, comprising HVAC systems, lighting, building envelope, and energy-intensive machinery. An energy model of the building was developed to emulate the baseline building energy performance for 2022. Following the energy model's development and validation, an analysis was conducted to identify energy-intensive areas and opportunities for optimization. Energy Efficiency Measures were then formulated, focusing on improving energy efficiency while focusing on energy consumption reduction and GHG emission reduction. Results demonstrated the potential of Energy Audits and Modeling to enable significant reductions in energy consumption and promote sustainable building practices. Among the Energy Efficiency Measures considered, re-sizing and decarbonizing HVAC equipment contributed the most to energy savings, with a 100% decrease in natural gas and 37% decrease in electricity use annually.

The analysis presented is based on actual GHU energy demand. The special feature of this load is the existence of strong daily fluctuations in energy consumption, especially during the summer months. This study presents a methodology for managing such loads with the main objective of maximizing the operating efficiency of MG.

In the last 20 years, the share of renewable energy sources in the production of electricity in the European Union has doubled, from about 15% to almost 35%. The main driver of this development has been the increase in the share of wind energy and solar photovoltaic energy. The authors aim to analyze the influencing factors that affect the energy transition process applied to nautical tourism, from polluting energy to renewable solar energy. The authors' research approach consists in using the framework offered by the energy transition process from the perspective of the socio-technical and economic approach, by applying the qualitative research method with a deductive approach. The tool used to achieve the objective was the semi-structured interview. The research unitarily, holistically, and specifically approaches the problem of energy transition from polluting sources to renewable ones offered by solar energy, in the case of nautical tourism with direct implications on the specific industry in the Netherlands. The research results are structured in the fields of technology, governance, economics, and user preferences. This research has the potential to provide support to find optimal solutions that encourage users to accelerate the energy transition process by adopting sustainable solutions for nautical tourism.

Sustainability of current energy policies and known mid-term policies are analised in their multiple facets. First an overview is given about the trend of global energy demand and energy production, analysing the share of energy sources and the geographic distribution of demand, on the basis of statistics and projections published by major agencies. The issue of sustainability of the energy cycle is finally addressed, with specific reference to systems with high share of renewable energy and storage capability, highlighting some promising energy sources and storage approaches.

Since the requirements in terms of power of the electronic applications range wide, the developed Energy Harvesting (EH) systems limit their availability to the less power demanding applications. However, this paper focuses on increasing the energy levels collected in the EH system so that it can be included in more demanding applications in terms of power. Therefore, an electronic system capable of grouping many single harvesting channels into one single system is analyzed in this paper. This multi-harvester electronic system is able to manage efficiently the energy collected by multiple vibratory transducers. The paper includes a comparison of its performance against some of the State-of-the-Art EH energy management circuits that interface the transducers. The method employed to demonstrate the intrinsic efficiency of each of the electronic circuits tested was based on experimental tests, where the average power transferred from several identical and simultaneous electric sources to a single storage element was measured. It was found out that only one energy management circuit was able to increase the transferred energy in a linear way while new input electric sources were added.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

Adherence to the Mediterranean diet has been shown to lower the risk of developing chronic non-communicable diseases like cardiovascular and neurodegenerative diseases and cancer. Improvements in depression, participation in daily activities in older individuals, weight loss and reduction in adverse pregnancy outcomes are associated with adherence to the Mediterranean diet. The number of studies that have evaluated barriers to the adherence of the Mediterranean diet in the US and in particular, in racial and ethnic minority populations within the US are few. Among Native American and Alaskan Native populations, studies evaluating traditional or alternative Mediterranean diet adherence for chronic non-infectious diseases is unavailable. Mediterranean diet scoring instruments used in studies in European and Mediterranean countries and among white participants in the US fail to capture the dietary patterns of racial and ethnic minority populations. In this narrative review the food components of the traditional Mediterranean diet are discussed, adherence to the Mediterranean diet is examined in Mediterranean and non-Mediterranean countries and barriers preventing adherence to the Mediterranean diet in the US and among racial and ethnic minority populations is reviewed. Recommendations for improving nutrition education and intervention, and increasing adherence and cultural adaptions to the Mediterranean diet are provided.

Balancing the efficiency and robustness of food systems is a well-known trade-off process. Over-optimization of efficiency may lead to excessive use of resources. On the other hand, under-optimization of efficiency may lead to excessive waste of resources. Using non-parametric methods can help in developing actionable frameworks through which decision-makers and stakeholders can effectively balance and improve food systems' efficiency and robustness. Under this context, this paper presents a new structured approach integrating two well-suited non-parametric methods for analyzing and balancing the interconnection between the efficiency and robustness of food systems. This approach consists of three main steps. First, the slacks-based data envelopment analysis (SBM-DEA) is utilized to analyze the efficiency of five food robustness dimensions. Second, the weighted efficiency of these dimensions is computed and analyzed to provide an insight into their influence on the food system efficiency. Finally, two search methods were developed to identify opportunities for improving efficiency and robustness. The outcomes of these methods have been analyzed and validated to ensure their effectiveness and viability. The operational and mathematical properties of the proposed approach were evaluated using data from thirty-seven food-producing countries. The weights of the robustness dimensions in this study were determined using the analytic hierarchy process (AHP) method. The input matrix of the AHP was constructed using expert judgment and consultations with stakeholders. The results of this study have shown an appropriate level of applicability and effectiveness of the proposed approach. While the first search method provided valuable insights, the second method proved to be more effective in identifying the sources of inefficacy of robustness dimensions. Several conclusions have been drawn and reported with some recommendations for future research works.

Abstract Global marine fish harvest has reached a plateau over the last decade. Efforts to increase aquaculture tend to face limitations in water resources and contamination problems. Of the current fish harvest at least 50% is discarded as waste. The chemical and microbiological contaminations limit the utilization of harvested fish. There is a need to improve fish preservation to minimize spoilage and process them into more appealing products. Instead of resorting to individual food processing methods, the efficiency of processing could best be increased by a combination of conventional and modern processing methods, or combinations of modern processing methods. Fish waste is a rich source of oils containing essential fatty acids, polypeptides, and amino polysaccharides that could be utilized through upscaling of the current scientifically proven methods, to new processing technologies. Separation of collagens, gelatins, bioactive peptides, edible fish oils, and chitosan form the primary stages in the utilization of fish waste. The products need purification to meet food quality and safety standards, and desirable industrial characteristics. The diversity of information and products generated through new methods requires advanced data handling and prediction systems, such as artificial intelligence, to address food safety and get the best out of fish processing and utilization.

Urbanization influences food culture, particularly in low- and middle-income countries, where there is an increasing consumption of processed and pre-packaged foods. This shift is contributing to a rise in non-communicable diseases. Food labeling standards are crucial for regulating manufacturing practices and aiding consumers in making healthy food choices. We aimed to assess the compliance of local and imported pre-packaged snacks with Tanzanian and international labeling standards in Dar es Salaam, Tanzania. A cross-sectional study was conducted on 180 snack products. A checklist based on Tanzanian and Codex labeling standards was used to evaluate adherence. We also examined factors influencing adherence, such as product origin, price, category, purchase location, and package size. The majority of the snacks demonstrated partial adherence to labeling standards. Imported products showed significantly better full adherence to both Tanzanian and International standards. Notably, over half of the products used English for labeling, and infrequently used the recommended World Health Organization Front-of-Pack nutrition Labeling. Product category, origin, and package size were significantly associated with higher levels of International standard adherence (p<0.05). The inadequate adherence to mandatory labeling standards, scarce use of Swahili and FoPL highlight the need to strengthen labeling practices and potential challenges faced by consumers in understanding nutritional information. Thus, strengthening and emphasizing good labeling practices is of urgency as we seek to address diet-related Non-communicable diseases.

Objective: To evaluate the existing meta-analytic evidence of associations between exposure to ultra-processed foods, as defined by the Nova food classification system, and adverse health outcomes. Design: Systematic umbrella review of existing meta-analyses. Data Sources: MEDLINE, PsycINFO, Embase, and the Cochrane Database of Systematic Reviews, as well as manually searching reference lists from 2009 to June 2023. Inclusion Criteria: Systematic reviews and meta-analyses of cohort, case-control, and/or cross-sectional study designs that evaluated the associations between exposure to ultra-processed foods and adverse health outcomes in humans across the lifespan. Results: The search identified 45 unique pooled analyses, including 13 dose-response and 32 non-dose-response associations (n=9,888,373). Overall, direct associations were found between exposure to ultra-processed foods and 32 (71%) health outcome domains spanning cardiometabolic, gastrointestinal, and respiratory conditions, cancer, mental health, and mortality. Based on a pre-specified evidence classification criteria, convincing evidence (Class I) supported direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease-related mortality (RR: 1.50; 95%CIs: 1.37 to 1.63), type two diabetes (dose-response RR: 1.12; 95%CIs: 1.11 to 1.13), and depressive outcomes (HR: 1.21; 95%CIs: 1.16 to 1.28), as well as higher risks of prevalent anxiety outcomes (OR: 1.48; 95%CIs: 1.37 to 1.59) and combined common mental disorder outcomes (OR: 1.53; 95%CIs: 1.43 to 1.63). Highly suggestive (Class II) evidence indicated that greater exposure to ultra-processed foods was directly associated with higher risks of incident all-cause mortality (RR: 1.21; 95%CIs: 1.15 to 1.27), heart disease-related mortality (dose-response HR: 1.66; 95%CIs: 1.51 to 1.84), and type two diabetes (OR: 1.40; 95%CIs: 1.23 to 1.59), together with higher risks of prevalent obesity (OR: 1.55; 95%CIs: 1.36 to 1.77), adverse sleep-related outcomes (OR: 1.41; 95%CIs: 1.24 to 1.60), and wheezing (RR: 1.40; 95%CIs: 1.27 to 1.55). Out of the remaining 34 pooled analyses, 21 were graded as suggestive or weak strength (Class III-IV) and 13 were graded as no evidence (Class V). Using the GRADE framework, 22 pooled analyses were rated as "Low" quality, with 19 rated as "Very Low” and four rated as "Moderate" quality. Conclusions: Higher exposure to ultra-processed food was associated with a greater risk of adverse health outcomes, especially cardiometabolic, common mental disorder, and mortality outcomes. These findings provide a rationale to evaluate the effectiveness of using population-based measures to target and reduce dietary exposure to ultra-processed foods for improved human health. Systematic Review Registration: PROSPERO CRD42023412732.

Background: In this secondary analysis of the Supporting the Modification of Lifestyle In Lowered Emotional States (SMILES) randomised controlled trial, we investigated if the beneficial effects of a dietary intervention on clinical depression were driven, in part, by reducing the consumption of foods classified as ultra-processed.Methods: The SMILES trial enrolled 67 adults with major depressive disorder, randomly assigning them to either a 12-week modified Mediterranean dietary intervention or a social support control. Our analysis included 44 participants with non-missing dietary data and at least one valid Montgomery–Åsberg Depression Rating Scale (MADRS) assessment at 12 weeks of follow-up. The Nova food classification system was used to estimate the proportion of ultra-processed foods in the overall diet (percentage of grams) based on data from seven-day food diaries. We fitted linear regression models under blinded conditions to determine whether ultra-processed food intake-change from baseline to 12 weeks moderated the dietary intervention effects on depressive symptoms. We estimated mean differences in depressive symptoms along with ninety-five per cent confidence intervals (95%CIs).Results: For participants in the dietary intervention, there was an additional 2.5-point improvement in MADRS scores for each 10% reduction in the dietary share of ultra-processed foods compared to participants in the control group (between-group mean differences in depressive symptoms: −2.46, 95%CIs −4.71 to −0.20, p=0.039, η _p ² of 0.10).Conclusions: These preliminary findings suggest that the therapeutic benefit of a dietary intervention for depression may stem, at least in part, from reductions in the dietary share of ultra-processed foods.

Radical reactions in water or aqueous media are important for organic synthesis, realizing high yielding processes under non-toxic and environmentally friendly conditions. This overview includes (i) a general introduction to organic chemistry in water and aqueous media, (ii) synthetic approaches in-, on- and with-water as well as in heterogeneous phase, (iii) reaction of carbon-centered radicals with water (or deuterium oxide) activated through coordination with various Lewis acids, (iv) photocatalysis in water and aqueous media, and (v) synthetic applications bioinspired from naturally occurring processes. A wide range of chemical processes and synthetic strategies under different experimental conditions have been reviewed that lead to important functional group translocation and transformation reactions, leading to the preparation of complex molecules. These results reveal how water as a solvent/medium/reagent in radical chemistry has matured over the last two decades and how further discoveries are foreseen to come in the near future.

This article presents a field-performance investigation on an Integrated Solar Water Supply System (SWSS) at two isolated agricultural areas in Thailand. The two case-study villages (Pongluek and Bangkloy ) have experienced severe draughts in the last decades, and therefore water supply has become a major issue. A stand-alone 15.36 kW solar power and a 15 kW solar submersible pump were installed along with the input power generated by solar panels supported by four solar trackers. The aim is to lift water at the static head of 64 and 48 m via piping length of 400 metres for each village to be stored in 1,000 m3 and 1,800 m3 reservoirs at an average of 300 m3 and 400 m3 per day, respectively for Pongluek and Bangkloy villages. The case study results have shown that the real costs of electricity generated by SWSS using solar PV systems intergraded with the solar tracking system yield better performance and are more advantageous compared with the non-tracking system. This study illustrates how system integration has been employed. System design and commercially available simulation predictions are elaborated. Construction, installation, and field tests for SWSS are discussed and highlighted. Performances of the SWSS in different weather conditions such as sunny, cloudy, and rainy days were analysed to make valuable suggestions for higher efficiency of the integrated solar water supply systems.

Drought-induced plant mortality has increased globally during the last decades and is forecasted to influence global vegetation dynamics. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. The most common metric that has been used for decades for measuring water stress is leaf water potential (Ψ_L), which is measured destructively. To obtain information on water dynamics from trees and forested landscapes, remote sensing methods have been developed. However, the spatial and temporal resolution of the existing methods have limited our understanding of water dynamics and diurnal variation of Ψ_L within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in Ψ_L during a 50 hour monitoring period and aimed to improve understanding on how large part of the diurnal variation in Ψ_L can be captured using intensity observations. We found that TLS intensity at 905 nm wavelength was able to explain 78% of the variation in Ψ_L for three trees of two tree species with a root-mean square error of 0.137 MPa. Based on our experiment with three trees, time-series of TLS intensity measurements can be used in detecting changes in Ψ_L, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales.

The global energy transition is motivated largely by the need to combat climate change. Other reasons include limits to available fossil fuels, energy-related environmental impacts of many kinds, and societal goals such as equity and providing sustainable energy for the poor. This transition will significantly change the world both technically, economically and socially. It is taking shape with characteristics which prioritise certain types of policy, interventions and solutions, as well as certain actors and institutional forces. More fundamentally, it embodies underlying assumptions about what constitutes a desirable type of economy and society. Briefly stated, the energy transition is being geared to a conventional economic growth-focused type of development; including the not unchallenged concept of green growth. Not everyone, however, would agree on those priorities or the underlying assumptions. We point out various constraints and limitations which this approach places on the energy transition. Whilst much of the change being initiated is positive, we argue that different views, which lie closer to discourses such as strong sustainability (1), deep ecology (2) and ecological economics (3, 4) might prioritise differently and offer both necessary and desirable outcomes. Given the predominant focus on energy and climate, equally essential goals such as equity and eradication of poverty appear to be at particular risk of being missed. Building on examples and recent experience we argue that achieving global sustainable energy, not least the societal goals, remains unlikely within socio-political frameworks permeated by the imperatives of market-driven growth, the commodification of resources, and intense competitive dynamics. Technology and economics, the themes of this issue, have far-reaching societal implications and outcomes. We argue that it is essential that they be considered within the broad context discussed here.

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

There is great importance and need of improving existing carbon materials fabrication methods. As such, this work proposes to discuss, interrogate, and propose viable hydrothermal, solvothermal, and other advanced carbon materials synthetic methods. The advanced carbon materials to be interrogated will include the synthesis of carbon dots, carbon nanotubes, nitrogen/titania-doped carbons, graphene quantum dots, and their nanocomposites with solid/polymeric/metal oxide supports. This will be done with special mind to microwave-assisted solvothermal and hydrothermal synthesis due to their favourable properties such as rapidity, low cost, and green/environmentally-friendliness. Thus, these methods are important during the current and future synthesis and modification of advanced carbon materials for application in energy, gas separation, sensing, and water treatment. Simultaneously, the work will pay special cognizance to methods reducing the fabrication costs and environmental impact while enhancing the properties as a direct result of the synthesis methods. As a direct result, the expectation is to impart a significant contribution to the scientific body of work regarding the improvement of the said fabrication methods.

The large-scale introduction of renewable energy, replacing fossil fuels, is presented as an essential part of the energy transition; this substitution is being observed in electrical systems, but it will also be necessary to introduce them in other sectors, such as transportation, either by incorporating renewable energy sources in the sector's facilities, including automotive service centers, or by electrifying transportation technology. The introduction of electromobility in a country is associated with a group of technologies that are required to make this introduction feasible. In Cuba, the introduction of electric vehicles, electric charging stations and charging points, including residential charging points, could increase the current demand by about 330 MW, based on the prospects for the introduction of electrification in the country's transportation system. Taking all of the above as a point of reference, this article addresses the basic elements of an energy transition proposal in the transportation sector, arriving at a proposed Roadmap to achieve the required synergy between energy transition and electromobility.

Paper presents the energy policy of the Republic of Serbia with special attention to the energy situation on the government controlled territory. South Serbian autonomous province of Kosovo and Metohija is under UN jurisdiction since the 1999 according to UNSC Resolution 1244. Renewable energy sources are rarely used in Serbia with exception of energy from hydropower plants, but in this sector priorities in geothermal and energy coming from biomass recently increased. In natural gas sector, Serbia has the deal with Russia for construction of South Stream gas-line through Serbia and for construction of the first underground storage in depleted gas reservoir in Banatski Dvor. In 2008, Serbia also sold 51% of the government founded petroleum industry – NIS which has exclusive monopoly for exploitation of crude oil. Serbian government has complete monopoly in electric power sector. Electric power infrastructure became technologically obsolete, and operative efficiency is at very low level. Serbia has not yet decided whether Serbian Electric Power Industry – EPS will be privatized. District heating sector mostly natural gas fuelled is highly inefficient and it is in jurisdiction of local municipalities but also has social component dictated by central government.

The purpose of the evaluation of the Peruvian energy generation system is to project the electricity generation and demand until the year 2050. To achieve this, three alternative scenarios have been defined and analyzed using the LEAP (Long-range Energy Alternatives Planning) software. The scenarios are as follows: the first one, Business-as-Usual scenario, based on normal trends according to historical data and referencing projections made by Peruvian state entities; the second one is focused on Energy Efficiency, the highlighted characteristic is taking into consideration the efficient conditions in transmission and distribution of electric energy; and the third one, centered on Geothermal Energy, focused on the development of this type of energy source and prioritizing it. The primary purpose of this analysis is to identity advantages and disadvantages inherent in each scenario in order to get the best of each one. In this way, the intention is to propose solutions based on Peru’s national reality or possible uses of the country’s energy potential to supply its energy demand. Currently, Peru’s energy demand relies on fossil fuels, hydraulic, and thermal energy. However, there is the possibility of transforming this system into a sustainable one, by strengthening existing and growing energy sources such as solar and wind energy, and new technologies for hydraulic and thermal energy, in addition to considering geothermal energy as the main energy source in the third scenario. The new system mentioned satisfactorily indicate that the CO2 equivalent emissions decrease significantly in the third scenario, with a 15.8% reduction compared to the first scenario and a 9.7% reduction in comparison to the second. On the other hand, the second scenario shows a 5.6% decrease in CO2 emissions compared to the first, resulting from improvements in technology and energy efficiency without requiring significant modifications or considerable investments, as in the third scenario.

Arsenic is naturally present in many geological formations around the world and is a major source of groundwater contamination. Bolivia is not exempt from this problem. Physical-chemical studies of water quality in deep and shallow wells have determined the presence of arsenic in some areas of the Bolivian Altiplano, valleys, and plains. In the Lake Poopó basin, water from shallow wells (up to 30 m) has arsenic concentrations that exceed the Bolivian drinking water standard and the WHO recommendation of 10 μg-As/l by up to 25 times. In peri-urban areas of Cochabamba, the arsenic content in groundwater is up to 113 μg-As/l. chronic exposure to arsenic is associated with neurological and dermatological problems and carcinogenic effects. To date, no measures have been taken to mitigate the arsenic problem for the rural population, who often rely on arsenic-contaminated water as their only source of drinking water. This contamination represents a serious threat to the health and economic well-being of the inhabitants and ecosystem in these areas. In this work, for arsenic removal, iron and iron oxide nanoparticles obtained from recycling metal chips by top-down and bottom-up technology have been used for arsenic adsorption in an experimental filter combined with other artisanal filtering materials in the form of layers. The results have shown that water contaminated with arsenic after passing through the filter reduces the concentration of total arsenic filtered from 83, 52 ppb to less than 5 ppb, less than the Bolivian standard 512 of 10 ppb for drinking water.

The aim of this research involves investigating the elimination of nitrogen ions from groundwater through the application of dynamic permeable reactive barriers (PRB) utilizing A400-nZVI. The aim also implyies determining barrier parameters, as well as assessing the overall retention capacity of nitrogen ions through percolation with a potassium nitrate solution. The research involves obtaining zero valent iron nanoparticles (nZVI), which were synthesized and doped onto an anionic resin support material (A400) through the reduction reaction of ferrous ions with sodium borohydride (NaBH4). This was achieved by preparing a ferrous sulfate solution, contacting it with the ion exchange resin at various solid-liquid mass ratios, and gradually adding sodium borohydride under continuous stirring in an oxygen-free environment to create the A400-nZVI barrier. The outcomes of this study, focusing on the development of permeable reactive barriers composed of nanovalent iron and ion exchangers, demonstrate significant potential in purification processes when appropriately dimensioned. The research specifically evaluated the efficacy of NO3- removal using the A400-nZVI permeable reactive barrier, conducting laboratory tests that simulated a naturally stratified aquifer with high nitrate contamination.

Nephrolithiasis affects around 10% of the population and is frequently associated with impaired dietary factors. The first one is insufficient fluid intake inducing reduced urine volume, urine supersaturation, and subsequently urinary lithiasis. Kidneys regulate 24-hour urine volume, which, under physiological conditions, approximately reflect daily fluid intake. Increasing fluid intake has a preventive effect on the risk of developing a first kidney stone (primary prevention) but also decreases the risk of stone recurrence (secondary prevention). Current guidelines recommend increasing fluid intake at least at 2.5L /day to prevent stone formation, and even at 3.5-4L in some severe forms of nephrolithiasis (primary or enteric hyperoxaluria or cystinuria). Fluid intake must also be balanced between day and night, to avoid urinary supersaturation during the night. Patients should be informed and supported in this difficult process of increasing urine dilution, with practical ways and daily routines to increase their fluid intake. The liquid of choice is water, which should be chosen depending on its composition (such as calcium, bicarbonate or magnesium content). Finally, some additional advices have to be given to avoid some beverages such as those containing fructose or phosphoric acid, which are susceptible to increase the risk of nephrolithiasis.

A biofilm is any syntrophic consortium of microorganisms in which cells adhere to one another and, in some cases, to a surface. These adherent cells become encased in a slimy extracellular matrix made up of extracellular polymeric substances (EPSs). Until now, the use of commercial disinfectants remains the main strategy to control biofilm-mediated problems. This mini review summarizes common antibiofilm mode of actions taken by disinfectants and how water channels in microbial biofilms contribute to disinfectant resistance.

This research was conducted to analyze the content of Fe, Cu, Cd, Cr, and Pb in several species of fish taken from three lakes that is closely to disposal of industrial waste in Indonesia. The fish samples were taken from three lakes, namely, Muara Angke, Weda, and Morowali. The samples from Morowali were analyzed in April 2019, those from Weda from November to December 2019, and those from Muara Angke in June 2018. All the samples were then analyzed at the chemistry laboratory of the Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, and the Integrated Laboratory of IPB. The results showed that all types of fish from Morowali and Weda were no longer safe to consume because they contained Fe, Cu, Cd, and Cr exceeding the threshold of metal contamination. Meanwhile, all types of fish from Muara Angke, except for ayam-ayam, are still safe for consumption. The results of this study can be a source of information regarding metal content in fish and fish feed for safe consumption. Several studies have been done to determine the metal pollutants contained by fish. Given the high consumption rate of fish and the hazards of heavy metals on humans’ health, such research must be furthered

The Delaware River has made a marked recovery in the half-century since the adoption of the Delaware River Basin Commission (DRBC) Compact in 1961 and passage of the Federal Clean Water Act amendments during the 1970s. During the 1960s, the DRBC set a 3.5 mg/l dissolved oxygen criteria for the river based on an economic analysis that concluded a waste load abatement program designed to meet fishable water quality goals would generate significant recreation and environmental benefits. Scientists with the Delaware Estuary Program have recently called for raising the 1960s DO criteria along the Delaware River from 3.5 mg/l to 5.0 mg/l to protect anadromous American shad and Atlantic sturgeon and address the prospect of rising temperatures, sea levels, and salinity in the estuary. This research concludes through a marginal abatement cost (MAC) analysis that it would be cost effective to raise DO levels to meet a more stringent standard by prioritizing agricultural conservation and wastewater treatment investments in the Delaware River watershed to reduce 90% of the pollutant load 13.6 million kg/year of nitrogen (30 million lb/year) for $160 million at 35% of the $449 million annual cost. The annual least cost to reduce nitrogen loads and raise dissolved oxygen levels to meet more stringent water quality standards in the Delaware River totals $45 million for atmospheric NOX reduction, $130 million for wastewater treatment, $132 million for agriculture conservation, and $141 million for urban stormwater retrofitting. This 21st century least cost analysis estimates that $50 million/year is needed to reduce pollutant loads in the Delaware River to raise dissolved oxygen levels to 4.0 mg/l, $150 million/year is needed to reach 4.5 mg/l, and $449 million/year is needed to reach 5.0 mg/l.

The integration of the increasing share of Renewable Energy Sources (RES) requires the availability of suitable energy storage systems to improve the grid flexibility, and Compressed Air Energy Storage (CAES) systems could be a promising option. In this study, a CO2-free Diabatic CAES system is proposed and analysed. The plant configuration is derived from a down-scaled version of the McIntosh diabatic CAES plant, where the natural gas is replaced with green hydrogen, produced on site by a Proton Exchange Membrane electrolyser powered by a Photovoltaic power plant. In this study, the components of the hydrogen production system are sized to maximize the Self-Consumption share of PV energy generation and the effect of the design parameters on the H2-CAES plant performance are analysed on a yearly basis. Moreover, a comparison between the use of natural gas and hydrogen in terms of energy consumption and CO2 emissions is discussed. The results show that the proposed hydrogen fuelled CAES can effectively match the generation profile and the yearly production of the natural gas fuelled plant by using all the PV energy production, while producing zero CO2 emissions.

The production and consumption of plastic bottled water have several negative environmental impacts worldwide. The EU countries have adopted strategies and programs to reduce single-use plastics, including PET bottles. A key aspect of designing effective policies is understanding consumer behaviour. To identify barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3,411 respondents in the Czech Republic in 2022. The results reveal that people aged 18-34 appear to be moderate consumers of bottled water and very frequent consumers of tap water. Bottled water consumption tends to be less frequent among people with higher education, while tap water consumption is less frequent among people with lower incomes. The most important factors that explain the frequency of drinking bottled and tap water are taste perception, health concerns and habit. Health concerns about tap water and the unpleasant taste of tap water influence higher consumption of bottled water and vice versa. People with a strong habit of drinking tap water are less likely to consume bottled water. The constructs from the Theory of Planned Behaviour were statistically significant. The results can guide decision-makers in promoting tap water to consumers. To encourage tap water drinking, we suggest measures to increase the availability of tap water in public places in conjunction with campaigns targeting taste and health perception and the habit of drinking tap water.

Access to reliable water supply is critical for sustainable development and public health, yet many peri-urban and rural communities in the developing world face challenges such as poor maintenance, faulty infrastructure, and inadequate governance of water services, hindering the UN’s Sustainable Development Goals (SDG). In Emina-Boadi, a small town in Kumasi, Ghana, residents increasingly rely on boreholes due to substandard service from the Ghana Water Company Limited (GWCL). This shift highlights concerns about water reliability, quality, and affordability, impacting public health and hindering progress toward SDG 6. This case study assesses water service levels using key performance indicators (KPIs) such as quantity, quality, affordability, accessibility, and reliability, focusing on sources like boreholes, hand pumps, piped water, hand-dug wells, rainwater, and surface waters. The study aims to delineate the roles of different water providers, understand community dynamics, and evaluate contributions to rural development and SDG 6 through stakeholder interviews and questionnaires. Leveraging the WASHCost framework, which aims to improve planning methods and provision of water and sanitation services by addressing the lack of cost information in rural and peri-urban areas, and the Joint Monitoring Programme (JMP) framework, which monitors progress toward global targets related to water, sanitation, and hygiene, the study categorizes indicators and draws connections among them. Findings reveal a significant preference for borehole services, with 87% usage and an 83% reliability rate compared to 13% for GWCL. Daily water consumption averages 60.75 liters per person, with on-premises access improving water collection efficiency to 7 minutes. Dissatisfaction with GWCL services highlights the need for improved delivery aligned with community needs and SDG targets. Adopting sustainable management practices, enhancing infrastructure, and improving governance are crucial for ensuring safe and affordable water access for all residents of Emina-Boadi and similar communities.

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.

Indigenous Peoples in Canada have shown great strength and resilience in maintaining their cultures and ways of life to date in the face of settler colonialism. Centering the water crises within Indigenous sovereignty and self-determination, we explore the impacts these crises are having on community members. Particularly, the continuous failure of the Canadian government to end the water crises in remote Indigenous communities, Star Blanket Cree Nation, is investigated in this paper. What implications have these water governance gaps had on Indigenous Peoples’ sovereignty and self-determination? We adopted an Indigenist theoretical framework to guide the study. Additionally, a community-based participatory research approach was adopted. To achieve our research goals of investigating the implications of the current water crises for Indigenous sovereignty and self-determination, specific methods of sharing circles were used to gather knowledge from community members, Elders, and knowledge keepers. The research findings strongly highlight the strength and resilience shown by remote Indigenous communities in the face of the current water crises and continuous government failure. Solving the current water crises will involve remote Indigenous communities taking charge of their own water governance through Indigenous-led water governance systems. Additionally, taking steps to rebuild trust through genuine reconciliation will be key. Therefore, listening to remote Indigenous communities and taking collaborative action is fundamental.

In Mexico, the evaluations of environmental flows are regulated by the Mexican Norm NMX-AA-159-SCFI-2012 and they warrant the establishment of water reserves for the environment. Yet, the pressure for water use limits the establishment of said reserves. This research aimed to evaluate the changes through time of the variables that serve as a basis for the implementation strategy by the Mexican government. A geographical information system was built with updated variables, the desired conservation status was analyzed, and the potential reserves were estimated based on the reference values for all basins nationwide. The results were examined according to their historical, current, and potential contribution to the conservation of natural protected areas and their connectivity. The outcomes point towards an administrative implementation strategy with positive outcomes despite the growing pressure for water use, with a change rate higher than the one for the creation of new protected areas. Currently, basins with low pressure and high conservation value have the potential to contribute to 86–88% of the goal set by the present administration without affecting water availability. Finally, reserving water in the priority basins would guarantee the legal protection of the flow regime in 48–50% of the hydrographic network in a desired conservation status, 45–49% of wetlands of international importance, and other natural protected areas in 85–89% of the global ecoregions represented in Mexico.

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.

We investigate if anyone is being left behind in accessing safely managed drinking water (SM) in achieving the 2030 agenda. We use 23 countries grouped globally as critically insecure water (CIWC). The results indicate none of the CIWC had over 50% of the population accessing SM, N. America and Europe had highest percentages while Sub Saharan Africa had the least. People left behind are found in rural areas, in countries vulnerable to climate change because of poor governance, low-income, and women’s low education. Institutional quality, equity and equality should be improved in using resources critical to leaving no one behind.

In this study, we investigated water transparency estimation models in the hypertrophic lagoon of the Albufera of Valencia using Sentinel-2 images. Water transparency, a crucial environmental indicator, was assessed via Secchi disk depth (ZSD) measurements. Three optical models (R490/R560, R490/R705, R560/R705) were explored to establish a robust algorithm for ZSD estimation. Through extensive field sampling and laboratory analyses, weekly data spanning 2018 to 2023 were collected, including water transparency, temperature, conductivity, and chlorophyll-a concentration. Remote sensing imagery from the Sentinel-2 mission was employed, and images were processed using SNAP software. The R560/R705 model, calibrated for turbid lakes, emerged as the most suitable. The algorithm's calibration was validated with high correlation coefficients (R2) in both calibration (0.6149) and validation (0.916) phases, demonstrating the model's accuracy in estimating ZSD. This new algorithm significantly outperformed a previous approach, highlighting the importance of tailoring algorithms to specific water body characteristics. The study contributes to improved water quality assessment and resource management, underscoring the value of remote sensing in environmental research.

The municipal water supply, related mainly to the cities of Albanian, began to develop in the second half of the 19th century and much intensively after 1945. Today the reported mean water production for the cities, on average, is about 300 l/capita/d including drinking and industrial water supply. The territory of Albania consists of uneven distribution of very heterogeneous aquifers conditioning the reach variety of the municipal water supply solutions. In this article are analyzed and classified the hydrogeological aspects of water supply sources of the settlements, which are summarized in five groups: (a) Wells in alluvial intergranular aquifers; (b) karst springs; (c) wells in karst aquifers; (d) springs in fissured rocks, and (e) mixed water sources. For each group of the water supply sources the main concerns regarding the quantity and quality problems are analyzed facilitated by the description of a variety of representative examples of different situations. Based on the gained experience important recommendation are given for the better understanding of hydrogeological aspects of water supply systems emphasizing the problematics along the river water recharge areas and on the seawater intrusion in coastal aquifers, as well as on transboundary aquifers. However, the main problems of public water supply of Albania remain the poor management of water supply systems which is reflected in the e high water losses, as well as the low public awareness of request for sustainable use.

Nitrogen (N) applications can play a key role in achieving profitable wheat production in the low-fertility soils prevalent under rainfed conditions. The model-predicted N partitioning revealed that ammonia-nitrogen (NH4-N) contributed little to the plant N nutrition, and its concentration in the soil remained below 2 ppm throughout the crop season except immediately after the NH4-N based fertilizer application. Nitrate-nitrogen (NO3-N) gradually increased (maximum 144 ppm) with time, especially in the 0-40 cm horizons, and contributed to most N uptake during both seasons at both locations. The N losses from the soil at the medium rainfall site (3.5-20.5 kg ha-1) were mainly attributed to NH4-N volatilization (Nv) and NO3-N leaching (NL) below the crop root zone. Water productivity (8-40 kg ha-1 mm-1) and N use efficiency (31-41 kg kg-1) showed immense variability induced by climate, water availability, and N dynamics in the soil. These results suggest that combining water balance and N modeling can help manage N applications to optimize wheat production and minimize N losses in rainfed agriculture.

Differences in the physical and chemical properties of reclaimed water (RW) and natural surface water (SW) lead to the differences in terms of nitrogen and phosphorus release when pipeline sediments enter these water bodies. The nitrogen and phosphorus release kinetics from pipe sediments with different particle sizes have been investigated. The results demonstrated that both SW and RW had a pH buffering effect after sediment addition, and the final pH (approximately 8.1) of RW was lower. The release of total phosphorus (TP) and ammonia nitrogen ( NH₄⁺-N) fitted the first-order kinetic model where the release of TP reached equilibrium; TP release was inhibited in both SW and RW, where RW exhibited the lowest (by a factor of 1.23~2.44) release (0.002 mg/g). The release of NH4+-N was promoted in both SW and RW; the maximum release in RW was 0.0188 mg/g. The amounts of NH₄⁺-N released in SW and RW were 1.02-1.40 and 1.30-1.80 times that of the control group (CG), respectively. The percentage of TP and NH₄⁺-N release in the three groups was highest in 75-154 μm pipe sediment, reaching 34.53% and 43.51% in SW and RW, respectively. These results can assist in the development of water quality evolution models for specific urban scenarios, and provide important guidance for the precise regulation of recharge water quality during and after rainfall.

Multivariate predictive analysis of the Stream-Water (SW) parameters (discharge, water level, temperature, dissolved oxygen, pH, turbidity, and specific conductance) is a pivotal task in the field of water resource management during the era of rapid climate change. The highly dynamic and evolving nature of the meteorological and climatic features have a significant impact on the temporal distribution of the SW variables in recent days making the SW variables forecasting even more complicated for diversified water-related issues. To predict the SW variables, various physics-based numerical models are used using numerous hydrologic parameters. Extensive lab-based investigation and calibration are required to reduce the uncertainty involved in those parameters. However, in the age of data-informed analysis and prediction, several deep learning algorithms showed satisfactory performance in dealing with sequential data. In this research, a comprehensive Explorative Data Analysis (EDA) and feature engineering were performed to prepare the dataset to obtain the best performance of the predictive model. Long Short-Term Memory (LSTM) neural network regression model is trained using over several years of daily data to predict the SW variables up to one week ahead of time (lead time) with satisfactory performance. The performance of the proposed model is found highly adequate through the comparison of the predicted data with the observed data, visualization of the distribution of the errors, and a set of error matrices. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. This model can be transferred to other locations with proper feature engineering and optimization to perform univariate predictive analysis and potentially be used to perform real-time SW variables prediction.

Clean production of renewable fuels is a great challenge of our scientific community. Iridium complexes have demonstrated a superior catalytic activity in the water oxidation (WO) reaction, which is a crucial step in water splitting process. Herein we have used a defective zirconium MOF with UiO-66 structure as support of a highly active Ir complex based on EDTA with formula [Ir(HEDTA)Cl]Na. The defects are induced by the partial substitution of tereftalic acid with smaller formiate groups. Anchoring of the complex occurs through a post-synthetic exchange of formiate anions, coordinated at the zirconium clusters of the MOF, with the free carboxylate group of the [Ir(HEDTA)Cl]-complex. The modified material was tested as heterogenous catalyst for the WO reaction by using Cerium Ammonium Nitrate as sacrificial agent. Although TOF and TON values are comparable to those of other iridium heterogenized catalysts, the MOF exhibits iridium leaching not limited at the first catalytic run, as usually observed, suggesting a lack of stability of the hybrid system under strong oxidative conditions.

Water hyacinth (Eichhornia crassipes) is an invasive species that has modified ecosystem functioning in the Sacramento-San Joaquin Delta (Delta), California, USA. Studies in lakes and rivers have shown that water hyacinth alters water quality. In tidal systems, such as the Delta, water moves back and forth through the water hyacinth patch so water quality directly outside the patch in either direction is likely to be impacted. In this study, we asked whether the presence or treatment of water hyacinth with herbicides resulted in changes in water quality in this tidal system. We combined existing datasets that were originally collected for permit compliance and long-term regional monitoring into a dataset that we analyzed with a before-after control-impact (BACI) framework. This approach allowed us to describe effects of presence and treatment of water hyacinth, while accounting for seasonal patterns in water quality. We found that although effects of treatment were not detectable when compared with water immediately upstream, dissolved oxygen and turbidity became more similar to regional water quality averages after treatment. Temperature became less similar to the regional average after treatment, but the magnitude of the change was small. Taken together, these results suggest that tidal hydrology exports the effects of water hyacinth upstream, just as river flow is known to transport the effects downstream, creating a buffer of altered water chemistry around patches. It also suggests that although water hyacinth has an effect on dissolved oxygen and turbidity, these parameters recover to regional averages after treatment.

Integrated Water Resources Management (IWRM) is one of the system thinking approaches emerged in the 1990s. Since then it has been applied in various countries and contexts. However, the implementation of the IWRM is contested. There are paucity of literature and guidelines as to how the concept can be operationalized. In Ethiopia, there is no evidence that IWRM is successfully instituted. Particularly, IWRM has never been implemented in the Awash River Basin. The study generated data from household and institutional surveys, in-depth interviews, focused group discussions, workshops, and secondary sources. Multiple sources of data were triangulated and thematically summarized. We found that pragmatic water resources management through system approach helps to recognize river basin as a bigger system in which the natural and human systems function. This resolves the problem of fragmentations among among various actors, sectors, interest and priorities. That it facilitates the coordination of various subsystems. The operationalization of IWRM as a system to secure water resources require the establishment and/or strengthening of the interactions of various systems, subsystems, and the elements within the entire basin system. Finally, enabling institutional environments should be considered as a medium of realizing IWRM.

Water pollution associated with flooding is one of the major problems in cities in the global South. However, studies of water quality dynamics during flood events are not often reported in literature, probably due to difficult conditions for sampling during flood events. Water quality parameters in open water (canals, rivers, and lakes), floodwater on roads and water in sewers have been monitored during the extreme fluvial flood event on 7 October 2013 in Can Tho city, Vietnam. This is the pioneering study of urban flood water pollution in real time in Vietnam. The results showed that water quality is very dynamic during flooding, especially at the beginning of the event. In addition, it was observed that the pathogen and contaminant levels in the floodwater are almost as high as in sewers. The findings show that population exposed to flood water runs a health risk that is nearly equal to that of being in contact with sewer water. Therefore the people of Can Tho not only face physical risk due to flooding, but also exposed to health risk.