Sustainability, the word of the moment and a goal that all industries want to achieve, is based on three basic principles: society, environment, and economy. In search of more ecological practices and reduced costs, many companies are currently updating their practices and, consequently, evolving.

The textile and pharmaceutical industries are some of the most influential industries today, contributing to the well-being of humanity and providing socioeconomic benefits, but in them, water resources are affected, with current practices being insufficient to guarantee the treatment of wastewater.

The objective of this research is to develop a cellulose acetate (CA) membrane, originating from pre-consumer cotton waste, modified with an absorbent to capture wastewater contaminants, and to thereby prevent pollution and the deterioration of marine ecosystems. Cork particles will be incorporated into the membrane and tested as potential contaminant absorbers. Membranes with and without additives will be characterized physically, chemically, and mechanically to guarantee optimal performance.

Several stages in this project have already been completed. The first consisted of the extraction of CA from cotton waste via the homogeneous acetylation of cellulose. The extraction was successful, but it is not possible to produce a membrane of 100% recycled CA, though it is viable to create membranes with a combination of commercial CA and recycled CA, using a ratio of 50%. When joining the cork, the membrane does not break and remains in the structure.

Powdered cork was washed, and thanks to the reduced particle size, the stability and homogeneity of cellulose membranes was achieved during production via the phase inversion process. The preliminary results demonstrated the potential of cork to absorb the antibiotic ciprofloxacin and synthetic methylene blue dye (1g of cork to 20 mL of solution). With this formulation, the aim is to find a way of treating textile and pharmaceutical waste based on waste from the industries themselves.

Effective management of water resources is crucial for sustainable development, particularly in regions like the Amu Darya River Basin, where water availability directly influences ecological and human systems. This study leverages integrated remote sensing data and model outputs to enhance water budget and availability analyses within the basin. Utilizing the GLDAS CLSM 2.1 model alongside satellite-derived precipitation and evapotranspiration data, this research provides a comprehensive assessment of water budget components, including precipitation, evapotranspiration, terrestrial water storage changes, and runoff, during the period 2001-2023. Moreover, by utilizing the NASA GLDAS model, a novel global dataset of the water budget components measured in millimeters per month was developed, streamlining the estimation process across different scales. Our results reveal significant variations in the precipitation estimates between the satellite observations and model predictions, with the satellite data generally indicating lower precipitation rates. The evapotranspiration analysis showed that remote sensing data tend to underestimate the values compared to model outputs, emphasizing the necessity of multi-source data integration for accurate water budget estimations. Furthermore, this study highlights discrepancies in the runoff estimation between the modeled outcomes and the gauge observations, illustrating the challenges in capturing the actual streamflow dynamics without streamflow routing in the models. This analysis underscores the importance of using advanced remote sensing and modeling techniques to improve water availability assessments, facilitating better management and conservation practices in the basin. These findings contribute to a deeper understanding of the hydrological processes in the Amu Darya River Basin, supporting efforts towards more resilient water resource management.

Coastal wetlands are rich and dynamic ecosystems that provide a variety of essential ecosystem services. They act as natural filters, improving water quality by retaining sediments, nutrients, and contaminants, which contributes to water quality regulation. They also protect the coast against flooding, buffering the impact of waves during storms and minimizing coastal erosion risks. Additionally, they are important carbon sinks, helping to mitigate climate change by storing large amounts of carbon in their sediments and vegetation. Coastal wetlands provide unique habitats for numerous species of flora and fauna, including many that are endemic or endangered. The Ebro Delta, located on Spain's Mediterranean coast, is one of the largest and most biodiverse wetlands in Europe, offering numerous ecosystem services beyond those already mentioned. This region is a productive agricultural area, known for its high-quality rice. Furthermore, its coastal waters are rich in fish and shellfish, providing an important source of food and employment for local communities. However, the Ebro Delta faces significant challenges due to human activities, such as the regulation of the Ebro River, and climate change, with large floods associated with storms that have caused the loss of extensive areas of its coastline. These conditions underscore the need for conservation and sustainable management strategies to preserve its valuable ecosystem services. The purpose of this work is to establish a detailed cartography of the distribution of ecosystem services and their role in the natural system of the delta, as a crucial tool to address effective conservation and management strategies appropriate to the delta space. Additionally, there should be an emphasis on educational efforts to gain the support of the delta's inhabitants and their involvement in the management of its resources.

In the Upper Mahanadi basin, base flow estimation is essential for understanding the hydrological cycle and eco-hydrology of that region. As the Mahanadi River is a perennial river, this calculation plays an important role in water resource management, especially in the Upper Mahanadi basin. This study was conducted with help of hydrograph separation methods to analyse the behaviours of the base flow and base flow index of the Upper Mahanadi basin. The observed stream flow discharges along the basin were used to evaluate the base flow trends during the period from 1998 to 2018. This result gives an idea about the average base flow and base flow index (BFI) in the Upper Mahanadi basin, which has drastically decreasing trends. The annual base flow ranged between 0 and 189.075 cumecs for the Upper Mahanadi basin. The BFI varied from 0 to 0.4808 with an average of 0.2404. This study represents that, on average, 24.04% of the long-term stream, flow is likely to depend on groundwater discharge and shallow subsurface flow. This study helps policymakers, engineers, and government officials to understand base flow behaviours and improves awareness among local people, which can help in future strategies to manage river patterns and water quality in this region.

Wetlands are considered one of the most valued ecosystems in the world, due to their transitional role between the terrestrial and aquatic environments, which favors biodiversity. Ponds also provide some ecosystem services that are very useful for the population, such as flood regulation, or their involvement in essential processes, such as nutrient cycles. That is why the analysis of the historical evolution of these ecosystems and the effects they have suffered is a key aspect to understanding the current state of the conservation of wetlands in a given territory. The study area is located in the mountains and foothills of the province of Jaén, Andalusia (Spain); this is a set of mountain ranges that border the Guadalquivir valley. In total, this study covers 48 ponds, whose recent evolution is studied over a period of 68 years, starting from the study of American flights in 1956 to the PNOA images of today. The objective of this study is to establish a baseline on the main aggressions that, from an anthropic point of view, can affect the ecological alteration of wetlands and their environment in this period of time. Human action and changes in land use have led to a progressive decrease in the surface area of some of these wetlands, which has led to the invasion of the wetland basin area, in most cases due to the intensification of olive grove cultivation, especially in the last quarter of the twentieth century and in the present twenty-first century.

The water sector, whether for drinking water supply, water treatment plants, wastewater treatment, stormwater drainage, or plantation drainage, has significant electricity costs and carbon emissions associated with generating the energy needed for these operations. In addition, water utilities have high water losses and generally do not have their sources to generate electricity. According to ERSAR (the regulatory authority for water and waste management), only 43 out of 251 water utilities produced their energy in 2022. Self-generation of energy should be a prerequisite to achieving sustainability and carbon neutrality in the water sector, and there are several prerequisites for this in the sector. In this context, technological innovations in the water sector are also being used to achieve the goal of carbon neutrality. The use of smart water networks and hybrid renewable energy solutions is a methodology for assessing urban water resources, artificial intelligence methods, and smart technologies, improving system efficiency, and replacing pressure reducers with turbines, where possible. A case study of the island of Madeira is discussed. Madeira’s water network is one of the least efficient in Portugal and has the highest water losses. The reasons for this are the very different topography, the age of the water networks, and their length and low maintenance. Here, by determining the highest value (while maintaining the flow rates and the minimum pressure required by law) in the EPANET software, the possibility of installing a turbine to generate electricity instead of a pressure-reducing valve is evaluated. The turbine will use the overpressure to generate electricity. The aim is for the system to use this energy in these processes. These high-pressure points are also normally associated with water losses.

Introduction

This study addresses the critical need for energy optimization in water distribution networks (WDNs) amidst climate change, drought, and rising energy costs. Efficient WDN management ensures sustainable water supply and reduces operational costs. The research explores the use of digital technologies, such as smart meters and 5G, to enhance real-time data acquisition and control, aiming to minimize energy consumption and improve system efficiency.

Methods

The primary objective is to develop an optimization model to reduce pump energy consumption in WDNs through strategic intermittent water supply. The methodology involves a three-step optimization process. First, a simulation of the WDN using EPANET establishes baseline energy consumption and water demand. Second, an optimization model determines the optimal water volumes to be delivered and stored at each node, considering demand patterns, tank capacities, and energy costs. Finally, the speed of centrifugal pumps is adjusted to further reduce energy consumption while maintaining the required water flows.

Results

The case study on an EPANET network shows significant improvements in energy efficiency. The optimization strategy reduces pump energy consumption by approximately 25.3% compared to the baseline simulation. By scheduling water delivery during periods of lower energy costs and adjusting pump speeds, the model achieves more efficient resource use. Implementing smart meters and digital controls allows for precise and flexible water distribution management, enhancing overall network performance.

Conclusions

This research highlights the potential of digital transformation in the water sector, emphasizing environmental, operational, and financial benefits. The proposed optimization model offers a practical solution for existing WDNs, requiring minimal structural modifications. The findings indicate significant energy savings through strategic water supply and digital technology integration. Future work will refine optimization algorithms and explore renewable energy sources to enhance the sustainability of water distribution systems.

Introduction

Climate change is causing significant shifts in weather patterns and temperatures, leading to environmental degradation, natural disasters, and resource scarcity. Sustainable practices are crucial to mitigate these effects, particularly in the energy and water sectors. This paper presents a mathematical model aimed at optimizing the use of electric energy in water supply networks while ensuring water quality. The focus is on minimizing energy consumption by electric pumps and maintaining the integrity of the pumps through controlled on/off cycles.

Methods

The proposed optimization model considers a hydraulic network with multiple water sources, each with different quality indices. Key assumptions include maintaining minimum pressure throughout the network and ensuring the total volume of water meets demand. The model involves a non-linear formulation, which is later linearized for practical application. Decision variables indicate whether a pump is on or off at given times, and the objective function aims to minimize the total energy consumption of the pumps.

Results

The model's non-linear formulation calculates the energy used by each pump based on its flow rate, head, and efficiency. Constraints ensure that the water volume in each reservoir stays within capacity limits and that the mixed water quality remains within specified bounds. The model also limits the number of pump switches to prevent system wear. Application of the model to a real-world scenario demonstrated its effectiveness in reducing energy consumption while maintaining water quality and operational constraints.

Conclusions

This study addresses the need for energy-efficient water supply systems by optimizing pump operation schedules. The model successfully balances energy use with water quality requirements and system durability. Future work could involve further refining the model to incorporate more dynamic factors and expanding its application to larger and more complex water networks.

Coastal regions are rich in cultural heritage due to their historical significance as hubs of human activity and play a vital role in enhancing local economies through tourism. The intersection of natural beauty and historical importance creates unique and valuable cultural landscapes. However, these historical sites face risks from natural and human impacts, including climate change (CC), rising sea levels, and industrial development. The Mediterranean coastal regions are rich in cultural heritage, reflecting millennia of human history, diverse cultures, and significant historical events. Therefore, this research focuses on the complex interdependencies between coastal vulnerability, sustainable tourism, ecosystem services, and erosion phenomena due to CC. Recent research shows climate change threatens Mediterranean cultural heritage, with up to 30% of African sites predicted to be at risk by 2050, a 25% increase in vulnerabilities at Nora, Sardinia, and 40% of sites in Basilicata, Italy, at risk from erosion. To assess the susceptibility of coastal heritage sites to climate impacts and develop adaptive strategies for conservation, methodologies such as remote sensing, GIS, 3D photogrammetry, and stakeholder engagement are employed. These approaches help analyze historical and future shoreline changes, air pollution effects, and ecosystem services, offering comprehensive insights into integrated coastal zone management and sustainable development. This work aims to provide valuable recommendations for policymakers, heritage managers, and stakeholders, contributing to the integrated management and preservation of coastal heritage sites in the face of growing environmental challenges.

Rainwater harvesting (RWH) has emerged as a promising technique to improve water security amid the escalating effects of climate change. However, a comprehensive evaluation of various rainwater harvesting solutions is needed to promote sustainable practices in the building sector. This study aimed to analyse rainwater harvesting in social housing in twelve representative cities in Brazil. Computer simulations were performed for 60 scenarios, comprising five social housing reference models and using rainfall data from twelve representative cities of Brazil’s bioclimatic zones. Simulation parameters of the building's characteristics were obtained from the blueprints of the house models, and rainfall data were obtained from Brazilian government databases. Other parameters, such as the runoff coefficient and the non-potable water demand, were retrieved from the existing literature. The results were analysed to understand the influence of the building’s characteristics and the different cities' rainfall patterns. Single-family houses have greater potable water savings potential (around 20% to 22% of total water consumption), primarily due to their higher roof-area-to-residents ratio. The multi-family models had a higher average total volume of potable water saved (from 108 to 152 m³/year) due to their higher total volume of water consumed. The city analysis revealed that Canela has the highest water saving potential (up to 35.8%), while Vitória da Conquista has the lowest average potential (0.35%).