Water Use Research Articles

Elastic modulus, water stability and resistivity for loess solidified with white mud based solid waste cementing material: Mechanism analysis and relationship establishment

To increase the engineering application value of white mud based solid waste cementing materials: white mud-slag and white mud-slag-Calcium Carbide Residue (CCR), this paper explored the changes in elastic modulus, water stability and resistivity of loess solidified with white mud based solid waste cementing material. Furthermore, relationships between elastic modulus, water stability and resistivity were established. The following conclusions can be obtained: The alkaline activation effect of CCR was stronger than white mud, therefore the formation rate of C-S-H and C-A-(S)-H cementitious products in CCR-containing solidified loess was more faster than that without CCR. At the same time, white mud not only served as an alkaline activator, but its finer CaCO3 components also helped fill pores, while the irregular fine particles provided nucleation sites for the formation of cementitious products. Consequently, slag-white mud-CCR solidified loess exhibited the best performance in terms of elastic modulus and water stability coefficient. This was followed by slag-white mud solidified loess and lime solidified loess. In addition, the analysis of the relationship between the resistivity of solidified loess and factors such as curing age, dry density, water content, elastic modulus, and water stability coefficient revealed that the main reasons for the increased resistivity of solidified loess were the consumption of internal water and the increase in cementitious products with poor conductivity. Furthermore, the modified resistivity formula was applied to establish the fitting relationships between the resistivity of solidified loess and various parameters. The formula has been successfully applied in the slag-white mud-CCR solidified loess, where the fitting of resistivity with various parameters yielded an R2 of 0.94. This paper facilitates the resistivity method (non-destructive testing) of loess treated with slag, white mud, CCR and promotes the application of these curing agents, contributing to their broader adoption in geotechnical engineering.

Continuously Learning Prediction Models for Smart Domestic Hot Water Management

Domestic hot water (DHW) consumption represents a significant portion of household energy usage, prompting the exploration of smart heat pump technology to efficiently meet DHW demands while minimizing energy waste. This paper proposes an innovative investigation of models using deep learning and continual learning algorithms to personalize DHW predictions of household occupants’ behavior. Such models, alongside a control system that decides when to heat, enable the development of a heat-pumped-based smart DHW production system, which can heat water only when needed and avoid energy loss due to the storage of hot water. Deep learning models, and attention-based models particularly, can be used to predict time series efficiently. However, they suffer from catastrophic forgetting, meaning that when they dynamically learn new patterns, older ones tend to be quickly forgotten. In this work, the continuous learning of DHW consumption prediction has been addressed by benchmarking proven continual learning methods on both real dwelling and synthetic DHW consumption data. Task-per-task analysis reveals, among the data from real dwellings that do not present explicit distribution changes, a gain compared to the non-evolutive model. Our experiment with synthetic data confirms that continual learning methods improve prediction performance.

Characterization of Water Bodies through Hydro-Physical Indices and Anthropogenic Effects in the Eastern Northeast of Brazil

Brazil, despite possessing the largest renewable freshwater reserves in the world (8.65 trillion m3 annually), faces growing challenges in water management due to increasing demand. Agriculture, responsible for 68.4% of water consumption, is one of the main drivers of this demand, especially in the São Francisco River Basin, where irrigation accounts for 81% of total water withdrawals. Water bodies play a crucial role in sustaining ecosystems and supporting life, particularly along the East-West axis of Alagoas, a water-rich region in the ENEB. This study aimed to map and quantify the spatiotemporal variations of water bodies in the ENEB region and assess the impacts of human activities using MODIS satellite data, applying hydrological indices such as NDWI, MNDWI, and AWEI. Between 2003 and 2022, significant variations in the extent of water bodies were observed, with reductions of up to 100 km2 during dry periods and expansions of up to 300 km2 during wet seasons compared to dry periods. AWEI and MNDWI proved to be the most effective indices for detecting water bodies with MODIS data, providing accurate insights into water dynamics. Additionally, the MapBiomas Rios dataset, despite being resampled from a 30 m to a 500 m resolution, offered the most accurate representation of water bodies due to its methodology for data acquisition. Changes in albedo and surface temperature were also detected, highlighting the influence of climate change on the region’s water resources. These findings are crucial for guiding the sustainable management of water resources, not only in Alagoas but also in other regions of Brazil and similar semi-arid areas around the world. The study demonstrates the hydrological variability in the state of Alagoas, indicating the need for adaptive strategies to mitigate the impacts of climate change and anthropogenic pressures, supporting the need for informed decision-making in water resource management at both local and national levels.

Technology Progress in High-Frequency Electromagnetic In Situ Thermal Recovery of Heavy Oil and Its Prospects in Low-Carbon Situations

Heavy oil resources are abundant globally, holding immense development potential. However, conventional thermal recovery methods such as steam injection are plagued by high heat loss, substantial carbon emissions, and significant water consumption, making them incompatible with carbon reduction goals and the sustainable socioeconomic development demands. A new method of high-frequency electromagnetic in situ heating, which targets polar molecules, can convert electromagnetic energy into heat so as to achieve rapid volumetric heating of the reservoir. This method has the potential to overcome the drawbacks of traditional techniques. Nevertheless, it faces significant drawbacks such as limited heating range and inadequate energy supply during later production stages, which necessitates auxiliary enhancement measures. Various enhancement measures have been reported, including nitrogen injection, hydrocarbon solvent injection, or the use of nano-metal oxide injections. These methods are hindered by issues such as pure nitrogen being easy to breakthrough, high costs, and metal pollution. Through extensive literature review, this article charts the evolution of high-frequency electromagnetic in situ heating technology for heavy oil and the current understanding of the coupled heat and mass transfer mechanisms underlying this technology. Moreover, based on a profound analysis of the technology’s progression trends, this work introduces a new direction: CO2-N2 co-injection as an enhancement strategy for high-frequency electromagnetic in situ heavy oil recovery. There is promising potential for the development of new technologies in the future that combine high efficiency, low carbon emissions, environmental friendliness, economic viability, and energy conservation. Furthermore, some research prospects in low-carbon situations and challenges for the new technology in future are presented in detail. All in all, the contribution of the paper lies in the summarizing of some main drawbacks of current enhanced electromagnetic in situ thermal recovery methods, and presents a novel research direction of using CO2-N2 co-injection as an enhancement strategy based on its current research status in low-carbon situations.

Penerapan IoT dengan Algoritma Fuzzy dan Mikrokontroler ESP32 dalam Monitoring Penyiraman

Smart farming has become a major focus in the development of modern agricultural technology. In this context, the Internet of Things (IoT) offers innovative solutions to increase productivity and efficiency in crop management. This research introduces an IoT-based plant watering monitoring system that uses a fuzzy algorithm and an ESP32 microcontroller. This system is designed to automatically regulate plant watering based on environmental conditions and plant needs. The ESP32 microcontroller acts as the brain of the system, collecting environmental data such as soil moisture, air temperature, and relative humidity. This data is analyzed using a fuzzy algorithm to determine plant watering needs in real-time. Based on the output of the fuzzy algorithm, the system automatically controls the water pump to water the plants according to the specified needs. The application of fuzzy algorithms allows the system to overcome uncertainty in plant watering decisions, especially in the face of complex variations in environmental conditions. With the adoption of IoT technology, farmers can monitor and control crop watering efficiently through web interfaces or mobile applications, even remotely. This research shows that the integration of IoT with fuzzy algorithms and ESP32 microcontrollers can be an effective solution in managing crop watering, increasing overall agricultural productivity, while reducing water and energy consumption.

Evaluating a vertical greening system mesocosm for kitchen greywater treatment: Comparison among vegetation species in water consumption, biomass growth and pollutants uptake and removal

The escalating climate imbalance, coupled with rising water demands in rapidly expanding urban areas, is forcing scientists and policymakers to seek alternative strategies for efficient water resource management. Nature Based Solutions (NBS) are gaining prominence due to their ability to provide multiple ecosystem services. However, the quantification of benefits and drawbacks mediated by different vegetation species remains inadequate. In this study, we investigated the performance of a pot-based vertical greening system (VGS) designed to integrate the functions of green facades with those of treatment wetlands. The VGS was vegetated with Mentha aquatica L. (hereafter Mentha), Oenanthe javanica (Blume) DC. (hereafter Oenanthe) and Lysimachia nummularia L. (hereafter Lysimachia), and their respective effects on water balance and mass removal of common greywater pollutants were compared. Results indicated that VGS lines vegetated with Oenanthe and Mentha exhibited comparable pollutant removals. Oenanthe showed a preference for greywater that had already undergone partial treatment, while Mentha was not affected by any pollutant load in water removal −48.1 % of total inflow– and in nutrients uptake in aboveground biomass −14.3 % N and 7 % P– due to sustained and robust growth, outperforming Oenanthe and Lysimachia. This has suggested the potential use of Oenathe in combination with Mentha for enhanced performances, particularly given Oenanthe's rapid growth in the early season and high biomass and nitrogen content following initial greywater treatment.

The Environmental Impact of Low-Pressure Anhydrous Dyeing Technology for Polyester: Carbon Footprint Quantification and Evaluation

Many emerging dyeing technologies have recently entered laboratory research or industrial production phases. However, only a few studies have evaluated and compared the environmental impact of different dyeing systems. This study calculated the carbon footprint of low-pressure anhydrous dyeing for polyester and compared with conventional water bath dyeing. The results showed that the carbon footprint of the anhydrous dyeing process was 1670 kgCO2 eq/1000 kg polyester. Steam occupied the most significant proportion, accounting for 55.5%, followed by electricity at 35.5%. The waste has the lowest environmental impact, with 0.55%. Uncertainty analyses showed that the data and results in this article were reliable. The results of the sensitivity analyses indicated that more attention should be paid to the data quality of steam and electricity. Compared with the traditional water bath dyeing process, the low-pressure anhydrous dyeing system can reduce greenhouse gas emissions by more than 30% and, more importantly, can avoid almost all the consumption of clean water. This anhydrous dyeing system can save water and reduce carbon emissions, which is of positive significance to the sustainable development of the textile and fashion industry. Further studies could use the water footprint as an indicator to evaluate this dyeing system in terms of water consumption and potential environmental impact.

Biomimetic Adaptive Building Façade Modeling for Sustainable Urban Freshwater Ecosystems: Integration of Nature's Water-Harvesting Strategy into Sun-Breakers.

Urban freshwater ecosystems have many critical functions, such as providing water to all living things and supporting biodiversity. Factors such as water pollution, increased water consumption, habitat loss, climate change, and drought threaten the health of urban freshwater ecosystems. Looking for solutions to these challenges, this article aims to recycle water and return it to its life cycle using a climate-sensitive water collection strategy. The model focuses on the biomimetic method as a basic strategy. In this regard, the concept of water-harvesting has been examined in detail by conducting a deep literature review, including architecture and engineering disciplines. With all these data obtained, a synthesis/integration study was carried out by developing a model proposal based on adaptive building façade elements to solve the water problems experienced in cities. The model proposal, which is directly related to the titles of "Clean Water and Sanitation (SDG 6)" and "Sustainable Cities and Communities (SDG 11)", which are among the Sustainable Development Goals (SDGs), aims to provide different perspectives on the disciplines with its superficial and functional features. In this context, it is anticipated that the article will become an indispensable resource for other researchers working on the subject.

Azimuthal and radial variations in sap flow and its effects on the estimation of transpiration for Picea mongolica.

In this study, we applied thermal dissipation probe technology to examine sap flow in various directions (east, south, west, and north) and at different depths (0-2, 2-4, 4-6 cm) within the stem of natural Picea mongolica trees in the eastern of Otindag Sandy Land to provide a scientific basis for accurately quantifying water consumption of P. mongolica forests through transpiration and to enhance the understanding of water relations. The results showed that the diurnal variation of sap flow in different directions displayed a unimodal curve, with the sap flow sequence being south>east>west>north. The sap flow at different sapwood depths exhibited an obvious unimodal curve, with a significant decrease as sapwood depth increased. Compared with that calculated from the mean sap flux density in four directions (23.57 kg·d-1), water consumption calculated using the mean value in south-east, east-west, south-west, north-east, north-south, and north-west was overestimated by 10.2%, 5.5%, 14.5%, and underestimated by 12.3%, 8.2%, 9.8%, respectively. The water consumption calculated using the values from the east, south, and west was overestimated by 6.1%, 14.4%, and 15.4%, respectively, and underestimated by 30.7% in the north. In addition, compared with the water consumption calculated from the mean value in three sapwood depths (48.51 kg·d-1), that calculated using sap flux density at sapwood depths of 0-2, 2-4, and 4-6 cm were overestimated by 18.8%, underestimated by 1.7%, and underestimated by 62.9%, respectively. These results indicated that sap flow of P. mongolica had significant azimuthal and radial variations, which considerably influence the estimation of tree water consumption. Installing probes at 0-2 cm simultaneously in both the north and east of the trunk could effectively reduce the estimation error of whole-tree water consumption by 4.2%. This approach enabled the accurate quantification of water consumption of individual P. mongolica trees in sandy areas, thereby improving the precision of transpiration water consumption estimates scaling up from individual level to stand level.

Evaluating the Impact of Hotel Classification on Pool Water Consumption: A Case Study from Costa Brava (Spain)

Swimming pools are key assets in the hotel industry. With climate change and water stress, more sustainable pools are needed in tourist areas. The study examines the relationship between hotel categories and the consumption of water in swimming pools in a Mediterranean coastal region facing water scarcity. The study focuses on the Costa Brava, with a focus on Lloret de Mar, a popular tourist destination. The research employs a combination of data analysis and the utilisation of evaporation models in order to estimate the consumption of water by swimming pools. The findings indicate that hotels in the higher categories, particularly those with three or four stars, contribute a notable proportion of the total water consumption due to their larger pool sizes and higher guest numbers. The study underscores the necessity for the implementation of sustainable water management strategies, particularly in the context of climate change. It recommends the utilisation of pool water-saving technologies as potential solutions. Furthermore, the paper highlights the broader environmental impact of tourism infrastructure on water resources and suggests policy measures to mitigate these effects. The research aligns with global sustainability goals such as the European Green Deal and the 2030 Agenda.

ASSESSMENT OF THE INFLUENCE OF INORGANIC PIGMENTS ON THE TECHNOLOGICAL PROPERTIES OF DECORATIVE CEMENTS

The article presents the results of research on the influence of inorganic pigments on the technological properties of decorative cements. It has been established that regardless of the color of the pigment, with an increase in its quantity in the system, we get a more saturated and bright color of cement stone, but at the same time there is a negative effect of pigments and technological and physical and mechanical properties of artificial stone. The research was conducted on cement systems based on white Portland cement without additives and on cement systems based on white Portland cement modified with polycarboxylate superplasticizer. An increase in the amount of pigment, regardless of its color, leads to an increase in the water consumption of the cement system, however, when a superplasticizer is introduced, the effect of the pigment is not so significant. At the same time, the introduction of a superplasticizer reduces the water consumption of white cement without the introduction of pigments by an average of 37-40%. In addition, it was established that the introduction of pigments affects the hardening time of cement systems. At the same time, pigments, depending on their color and dosage, have different effects on both the start and end of aging. With an increase in the pigment content in a cement system without a plasticizer, the time of the onset of hardening increases, and the introduction of a permanent pigment has the greatest effect on the end of hardening of such a system. The introduction of pigments into plasticized cement systems increases both the start and end time of hardening. As the number of pigments of all colors increases, the strength of the samples decreases. At the same time, the red pigment leads to the greatest decline in strength at all stages of hardening. The decrease in strength can be explained by the increased water consumption, and, as a result, the increased porosity of pigmented samples compared to samples without the introduction of pigments. Further research aimed at finding additives that will reduce the negative impact of inorganic pigments on the processes of hydration and hardening of the cement system, and therefore on the durability of the obtained artificial stone, will be relevant. At the same time, it is important to preserve the intensity of the color and the absence of sediment formation.

Eco‐efficiency improvement strategies for disinfectants

AbstractDisinfectants are essential products for reducing health risks, but they also have significant environmental impacts. This study assessed the Eco‐efficiency of disinfectants based on the NBR ISO 14045:2014. Primary data were collected from Brazilian producers, while secondary data were obtained from patents and the Ecoinvent database. The system boundaries encompassed cradle‐to‐consumer use. The selling price was adopted as the product system value indicator (economic analysis). Raw materials production had the greatest impact on the environmental performance of disinfectants A (Antibacterial, surfactant and preservative) and C (Antibacterial, surfactant and opacifier). Disinfectant B, in addition to raw materials production (Antibacterial, opacifier and surfactant), also experienced significant impacts from consumer transport. These critical processes represent more than 60% of the overall impacts in both categories. The Eco‐efficiency matrix (profile) related environmental and economic indicators. All disinfectants occupied quadrants three or four, indicating high impact on the environmental categories. Disinfectant C had the highest Eco‐efficiency while disinfectant B had the lowest, mainly due to its product system value. Sensitivity analysis indicated environmentally viable changes in the products' composition, such as replacing the antibacterial, surfactant, preservative, and opacifier. Energy and water consumption did not significantly impact the assessed products.

Sustainable Textile Manufacturing with Revolutionizing Textile Dyeing: Deep Learning-Based, for Energy Efficiency and Environmental-Impact Reduction, Pioneering Green Practices for a Sustainable Future

The textile industry, a substantial component of the global economy, holds significant importance due to its environmental impacts. Particularly, the use of water and chemicals during dyeing processes raises concerns in the context of climate change and environmental sustainability. Hence, it is crucial from both environmental and economic standpoints for textile factories to adopt green industry standards, particularly in their dyeing operations. Adapting to the green industry aims to reduce water and energy consumption in textile dyeing processes, minimize waste, and decrease the carbon footprint. This approach has become crucial in achieving sustainability in textiles following the signing of the Paris Climate Agreement. Important elements of this transformation include the reuse of washing waters used in the dyeing process, the recycling of wastewater, and the enhancement of energy efficiency through necessary methodological and equipment changes. This study analyzes the energy, labor, production, and consumption data since 2011 for a textile factories with four branches located in the Adana Organized Industrial Zone. Among these factories, the one designated as UT1, which has the highest average energy and water consumption compared to the other three branches, is selected. In recent years, the use of artificial intelligence and machine learning technologies in predicting industrial processes has been increasingly observed. The data are analyzed using LSTM (Long Short-Term Memory) and ANN (Artificial Neural Networks) forecasting methods. Particularly, the LSTM algorithms, which provided the most accurate results, have enabled advanced forecasting of electricity consumption in dyeing processes for future years. In 2020, electricity consumption was recorded as 3,717,224 kWh and this consumption was reflected in the total energy cost as TRY 1,916,032. Electricity consumption accounts for 22.34% of total energy consumption, while the share of this energy type in the cost is 43.25%. In the light of these data, the MAPE value for energy consumption forecasts using the LSTM model was 0.45%, which shows that the model is able to forecast with high accuracy. As a result, a solar power plant was installed to optimize energy consumption, and in 2023 60% energy savings were achieved in summer and 25% in winter. The electricity consumption forecasting results have been an essential guide in planning strategic initiatives to enhance factory efficiency. Following improvement efforts aimed at reducing energy consumption and lowering the carbon footprint, significant optimizations in processes and layouts have been made at specific bottleneck points within the facility. These improvements have led to savings in labor, time, and space, and have reduced unit production costs.

Time Series Analysis to Estimate the Volume of Drinking Water Consumption in the City of Meoqui, Chihuahua, Mexico

Water is a vital resource for sustaining life and for numerous processes within the transformation industry. It is a finite resource, albeit one that can be renewed, and thus sustainable management is imperative. To achieve this objective, it is necessary to have the appropriate tools to assist with the planning policies for its management. This paper presents a time series analysis approach to measure and predict the pattern of water consumption by humans throughout subsectors (domestic, commercial, public sector, education, industry, and raw water) and total water consumption in Meoqui, Chihuahua, Mexico with data from 2011 to 2023, applying calibration model techniques to measure uncertainty in the forecasting. The municipality of Meoqui encompasses an area of 342 km2. The climate is semi-arid, with an average annual rainfall of 272 mm and average temperatures of 26.4 °C in summer and 9.7 °C in winter. The municipal seat, which has a population of 23,140, is supplied with water from ten wells, with an average consumption of 20 ± 579 m3 per user. The consumption of the general population indicates the existence of a seasonal autoregressive integrated moving average (SARIMA) (0,1,2)(0,0,2)12 model. (Sen’s Slope = 682.7, p < 0.001). The domestic sector exhibited the highest overall consumption, with a total volume of 17,169,009 m3 (13 ± 93). A SARIMA (2,1,0)(2,0,0)12 model was estimated, with a Sen’s slope of 221.65 and a p-value of less than 0.001. The second-largest consumer of total water was the “raw water” sector, which consumed 5,124,795 (30,146 ± 35,841) m3 and exhibited an SARIMA (0,1,1)(2,0,0)12 model with no statistically significant trend. The resulting models will facilitate the company’s ability to define water resource management strategies in a sustainable manner, in alignment with projected consumption trends.

Assessing Trace Metal Contamination and Associated Risks in the Kossan River Ecosystem, Southern Côte d'Ivoire

Trace metals accumulate in aquatic systems and can pose a threat to human health and wildlife. In recent decades, human activity has become the main source of metals in the environment. In order to gain a better understanding of metal contamination in Ivorian rivers impacted by human activity, and to help set up a database, we studied the distribution of arsenics (As), cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn) in the Kossan River. A total of 21 surface water and sediment samples were taken at 7 stations along the River Kossan between March 2019 and July 2020. Total concentrations of the metals were analyzed by atomic absorption spectroscopy (AAS). Carcinogenic and non-carcinogenic risks were assessed in surface water. Contamination indices such as EF, CF; Igeo and PLI were calculated to determine the level of sediment contamination. Ecological risk indices Er and RI were used to assess the potential risks associated with metals. The concentrations of As, Pb, Cd, Cu and Zn found in surface water samples fell within the following ranges: 2.03 - 17.19, 1.752 - 13.264, 0.067 - 0.774, 17.44 - 2369.11 and 136.72 - 3669.37 µg/L, respectively and in sediment: 0.69 - 4.60, 2.10 - 11.30, 0.13 - 5.00, 1.70 - 28.20 and 4.10 - 90.30 µg/g, respectively. The results showed high levels of As, Cu, Pb and Zn contamination in places, above WHO limits. The calculation of non-carcinogenic and carcinogenic risk indices revealed that arsenic and copper can present major health risks for humans through the consumption of water. Cd concentrations exceeded geochemical background values. The results suggest moderate to very severe Cd contamination of the sediments by anthropogenic origin at certain sampling points. In general, the results of the ecological risk indices revealed low to moderate levels of contamination for metals, with the exception of heavy cadmium contamination in the river. The highest concentrations of trace metals were observed in water and sediment samples collected from stations with high anthropogenic pressure. The continuing intensification of human activity may in the long term present a major risk to man and his environment, hence the need to set up a system for monitoring river watercourses and to develop a system for remediating trace metals in river water such as phytoremediation.

A Short-Term Evaluation of the Eat and Exercise to Win Program for Adults with Intellectual and Developmental Disabilities.

(1) Study Aim: Adults with intellectual and developmental disabilities (IDD) face a multitude of chronic health risks related to obesity, including diabetes and heart disease. Day adult service programs offer unique opportunities for improving and monitoring the health of this vulnerable group. To promote exercise and healthy eating habits among adults with IDD, the Eat and Exercise to Win Program (EE-2-Win) was offered weekly at two locations over 8-9 months. (2) Methods: Using daily logs, staff assessed outcomes of 26 program participants, including changes in knowledge, eating and exercise habits, and water consumption. Participants' weights were measured, and their lunches were photographed at baseline and 3 months. (3) Results: While participants' weights did not significantly differ at 3 months, assessing photographs indicated that participants' lunches included more fruits and vegetables. Staff surveys indicated that participants had greater knowledge of MyPlate and were consuming more water at three months. Survey responses indicated that staff perceived the program to be valuable overall, and challenges in learning and assessment were reported given differences in the cognitive abilities of adults with IDD. Staff also suggested engaging home caregivers in the program, as they often make dietary decisions. (4) Conclusions: Overall, results confirmed that the EE-2-Win Program positively impacted healthy eating and exercise. Future work, however, with both staff and caregivers is needed to further optimize the program.

Mediating role of specific environmental beliefs in the relationship between general beliefs and water consumption

AbstractThis study investigates the impact of general environmental beliefs (GEB) on water consumption behaviour (WCB) and the mediating role of specific environmental beliefs (SEB) in Kuala Lumpur. By administering 1584 surveys via a 5‐point Likert scale questionnaire, the study analyses the influence of utilitarian beliefs (UB) and ecological beliefs (EB) at both the Kuala Lumpur and district levels. The results demonstrate that EB significantly mediates the relationship between GEB and WCB, while UB also plays a significant mediating role. The study highlights practical measures for environmental preservation, such as prioritizing utilitarianism for environmentally beneficial choices, afforestation, waste reduction, reusability and recycling of production materials and ensuring ecological system compatibility for waste disposal.

The Piped Water and Household Food Consumption: Evidence from Cambodia

<p style="text-align: justify;"><span style="font-family: 'times new roman', times, serif; font-size: 14pt;">This study analyses the effects of piped water on household food consumption per capita by adopting inverse-probability-weighted regression adjustment and endogenous treatment effects approaches with data from the Cambodia Socio-Economic Survey carried out in 2013 and 2017. A complementary analysis of the effects on primary household income per working-age member is also conducted to give insights into the potential consequences. The study also conducts a robustness check by estimating the fixed effects of piped water utilising village panel data. The results suggest that households using piped water are likely to enjoy higher food consumption per capita, with a complementary finding demonstrating that the use of piped water is likely to increase household income per working-age member.</span></p>

ESG transformation of water supply and sewerage enterprises in the Russian Federation to achieve sustainable development goals

Subject. This article discusses the issues of modernization of water supply and sewerage systems, housing and communal services as a whole, and the problem of rational use of water resources. Objectives. The article aims to determine areas for the development of water supply and wastewater disposal organizations, and develop mechanisms to reduce the negative impact of industry enterprises on the environment. Methods. For the study, I used the general scientific research methods. Results. The article finds that the key task of the industry is to reduce the depreciation of fixed assets. It is necessary to reduce water consumption and losses in production processes and during transportation. Conclusions. The introduction of green technologies will help increase the investment attractiveness of the industry. The Government of the Russian Federation considers water supply and wastewater disposal as a priority sector that ensure the country's sustainable development.

Variation characteristic analysis of regional agricultural water consumption under Budyko-type framework

ABSTRACT Agricultural water consumption security is crucial for maintaining food production stability. Aiming to investigate water consumption efficiency and objectives in agricultural and non-agricultural sectors, we adopted a Budyko-analogous framework to establish an optimal water allocation model based on the maximum water utilization benefits principle. The proposed Budyko framework was verified through its application in Anhui Province, China, and the difference in water utilization efficiencies among different regions was discussed. The research findings can be concluded as follows: (1) during 2011–2020, the provincial agricultural productive loss caused by per-unit water shortage was lower compared to non-agricultural sectors, and this trend was adaptive in the south but totally opposite in the north; (2) the guaranteed level of agricultural water consumption was higher compared to non-agricultural sectors in the north due to the predominance of agricultural production but totally contrary in the south. Overall, the above findings are consistent with the actual industrial structure of Anhui Province.