Search Results (351)

Environmental protection has become one of the key challenges of our time. This has led to an increase in pro-environmental activities in the field of cosmetics and household chemicals, where manufacturers are increasingly trying to meet the expectations of consumers who are aware of the potential risks associated with the production of cosmetics and household chemistry products. This is one of the most important challenges of today’s industry, given that some of the raw materials still commonly used, such as surfactants, may be toxic to aquatic organisms. Many companies are choosing to use natural raw materials that have satisfactory performance properties but are also environmentally friendly. In addition, modern products are also characterized by reduced consumption of water, resources, and energy in production processes. These measures reduce the carbon footprint and reduce the amount of plastic packaging required. In the present study, seven formulations of environmentally friendly car shampoo concentrates were developed, based entirely on mixtures of bio-based surfactants. The developed formulations were tested for application on the car body surface, allowing the selection of the two best products. For these selected formulations, an in-depth physicochemical analysis was carried out, including pH, density, and viscosity measurements. Comparison of the results with commercial products available on the market was also performed. Additionally, using the multiple light scattering method, the foamability and foam stability were determined for the car shampoos developed. The results obtained indicate the very high application potential of the products under study, which combine high performance and environmental concerns. Full article

The quality of water in households can be affected by plumbing design and materials, water usage patterns, and source water quality characteristics. These factors influence stagnation duration, disinfection residuals, metal release, and microbial activity. In particular, stagnation can degrade water quality and increase lead release from lead service lines. This study employs numerical modeling to assess how combined corrosion control and flushing strategies affect lead levels in household taps with lead service lines under reduced water use. To estimate potential health risks, the U.S. EPA model is used to predict the percentage of children likely to exceed safe blood lead levels. Lead exceedances are assessed based on various regulatory requirements. Results show that exceedances at the kitchen tap range from 3 to 74% of usage time for the 5 µg/L standard, and from 0 to 49% for the 10 µg/L threshold, across different scenarios. Implementing corrosion control treatment in combination with periodic flushing proves effective in lowering lead levels under the studied low-consumption scenarios. Under these conditions, the combined strategy limits lead exceedances above 5 µg/L to only 3% of usage time, with none above 10 µg/L. This demonstrates its value as a practical short-term strategy for households awaiting full pipe replacement. Targeted flushing before peak water use reduces the median time that water remains stagnant in household pipes from 8 to 3 h at the kitchen tap under low-demand conditions. Finally, the risk model indicates that the combined approach can reduce the predicted percentage of children with blood lead levels exceeding 5 μg/dL from 61 to 6% under low water demand. Full article

Household appliances constitute the second largest source of residential energy consumption in China, accounting for over 20% of the total and exhibiting a steady growth trend. Despite their substantial impact on energy demand and carbon emissions, a comprehensive analysis of the current status and future trends of household appliances in China is still lacking. This study employs the Long-Range Energy Alternatives Planning (LEAP) system to model energy consumption and carbon emissions for five major household appliances (air conditioners, refrigerators, washing machines, TVs, and water heaters) from 2022 to 2052. Three scenarios were analyzed: a Reference (REF) scenario (current trends), an Existing Policy Option (EPO) scenario (current energy-saving measures), and a Further Strengthening (FUR) scenario (enhanced efficiency measures). Key results show that by 2052, the EPO scenario achieves cumulative savings of 1074.8 billion kWh and reduces emissions by 580.7 million metric tons of CO₂ equivalent compared to REF. The FUR scenario yields substantially greater benefits, demonstrating the significant potential of strengthened policies. This analysis underscores the critical role of improving appliance energy efficiency and provides vital insights for policymakers and stakeholders aiming to reduce residential sector emissions. Full article

With the increasing integration of renewable energy and smart technologies in residential energy systems, proactive household energy management (HEM) have become critical for reducing costs, enhancing grid stability, and achieving sustainability goals. This study proposes a ultra-short-term forecasting-driven proactive energy consumption optimization strategy that integrates advanced forecasting models with multi-objective scheduling algorithms. By leveraging deep learning techniques like Graph Attention Network (GAT) architectures, the system predicts ultra-short-term household load profiles with high accuracy, addressing the volatility of residential energy use. Then, based on the predicted data, a comprehensive consideration of electricity costs, user comfort, carbon emission pricing, and grid load balance indicators is undertaken. This study proposes an enhanced mixed-integer optimization algorithm to collaboratively optimize multiple objective functions, thereby refining appliance scheduling, energy storage utilization, and grid interaction. Case studies demonstrate that integrating photovoltaic (PV) power generation forecasting and load forecasting models into a home energy management system, and adjusting the original power usage schedule based on predicted PV output and water heater demand, can effectively reduce electricity costs and carbon emissions without compromising user engagement in optimization. This approach helps promote energy-saving and low-carbon electricity consumption habits among users. Full article

Global building energy consumption is significantly increasing. Utilizing renewable energy sources may be an effective approach to achieving low-carbon and energy-efficient buildings. A combined system incorporating solar photovoltaic–thermal (PV/T) components with an air-source heat pump (ASHP) was studied for simultaneous heating and power generation in a real residential building. The back panel of the PV/T component featured a novel polygonal Freon circulation channel design. A prototype of the combined heating and power supply system was constructed and tested in Fuzhou City, China. The results indicate that the average coefficient of performance (COP) of the system is 4.66 when the ASHP operates independently. When the PV/T component is integrated with the ASHP, the average COP increases to 5.37. On sunny days, the daily average thermal output of 32 PV/T components reaches 24 kW, while the daily average electricity generation is 64 kW·h. On cloudy days, the average daily power generation is 15.6 kW·h; however, the residual power stored in the battery from the previous day could be utilized to ensure the energy demand in the system. Compared to conventional photovoltaic (PV) systems, the overall energy utilization efficiency improves from 5.68% to 17.76%. The hot water temperature stored in the tank can reach 46.8 °C, satisfying typical household hot water requirements. In comparison to standard PV modules, the system achieves an average cooling efficiency of 45.02%. The variation rate of the system’s thermal loss coefficient is relatively low at 5.07%. The optimal water tank capacity for the system is determined to be 450 L. This system demonstrates significant potential for providing efficient combined heat and power supply for buildings, offering considerable economic and environmental benefits, thereby serving as a reference for the future development of low-carbon and energy-saving building technologies. Full article

In this study, relevant rice cultivation data were collected through a local survey, and the life cycle assessment (LCA) method was employed to quantify greenhouse gas (GHG) emissions from rice production on consolidated land in the Red River Delta (RRD). Systematic sampling was used in face-to-face interviews with 45 rice farming households in a representative commune of Hai Duong province. Specific GHG emissions were significantly higher in the summer crop (averaged at 11.4 t CO₂-eq/ha or 2.2 t CO₂-eq/t grain) than in the spring crop (6.8 t CO₂-eq/ha or 1.2 t CO₂-eq/t grain). Methane was a dominant GHG emitted from paddy fields, contributing 84% of the total emissions of CO₂-eq in the summer crop and 73% in the spring crop. Fertilizer use and N₂O emissions accounted for 9% of emissions in the summer crop and 16% in the spring crop. Energy consumption for machinery and irrigation added a further 4% and 8%, respectively. Annually, as of 2023, the rice production activities in the RRD release 7.3 Tg of CO₂-eq (100 years), a significant contribution to the national GHG emissions. GHG emissions under alternative scenarios of rice straw management were assessed. This study highlights the role of land consolidation in improving water management, which contributes to lowering emissions. Based on the findings, several mitigation measures could be identified, including improved irrigation practices, optimized fertilizer use, and the promotion of sustainable rice straw management practices. Full article

Water, the lifeblood of our planet, sustains ecosystems, economies, and communities. However, climate change and increasing hydrological variability have exacerbated global water scarcity, threatening livelihoods and economic stability. According to the United Nations, over 2 billion people currently live in water-stressed regions, a figure expected to rise significantly by 2030. To address this urgent challenge, this study proposes an AI-driven anomaly detection framework for smart water metering networks (SWMNs) using machine learning (ML) techniques and data resampling methods to enhance water conservation efforts. This research utilizes 6 years of monthly water consumption data from 1375 households from Location A, Windhoek, Namibia, and applies support vector machine (SVM), decision tree (DT), random forest (RF), and k-nearest neighbors (kNN) models within ensemble learning strategies. A significant challenge in real-world datasets is class imbalance, which can reduce model reliability in detecting abnormal patterns. To address this, we employed data resampling techniques including random undersampling (RUS), SMOTE, and SMOTEENN. Among these, SMOTEENN achieved the best overall performance for individual models, with the RF classifier reaching an accuracy of 99.5% and an AUC score of 0.998. Ensemble learning approaches also yielded strong results, with the stacking ensemble achieving 99.6% accuracy, followed by soft voting at 99.2% and hard voting at 98.1%. These results highlight the effectiveness of ensemble methods and advanced sampling techniques in improving anomaly detection under class-imbalanced conditions. To the best of our knowledge, this is the first study to explore and evaluate the combined use of ensemble learning and resampling techniques for ML-based anomaly detection in SWMNs. By integrating artificial intelligence into water systems, this work lays the foundation for scalable, secure, and efficient smart water management solutions, contributing to global efforts in sustainable water governance. Full article

Understanding the characteristics of residential hot-water consumption can be useful for developing effective water-conservation strategies in response to increasing pressure on natural resources. This study systematically investigates residential hot-water consumption through direct monitoring of over 40 domestic fixtures (belonging to six different end-use categories) in five Italian households, recorded over a period ranging from approximately two weeks to nearly four months, and using smart meters with 5 min resolution. A multi-step analysis is applied—at both household and end-use levels, explicitly differentiating tap uses by purpose and location—to (i) quantify daily per capita hot-water consumption, (ii) calculate hot-water ratios, and (iii) assess daily profiles. The results show an average total water consumption of 106.7 L/person/day, with at least 26.1% attributed to hot water. In addition, daily profiles reveal distinct patterns across end uses: hot- and cold-water consumption at kitchen sinks are not aligned over time (with cold water peaking before meals and hot water used predominantly afterward), while bathroom taps show more synchronized use and a marked evening peak in hot-water consumption. Study findings—along with the related open-access dataset—provide a valuable benchmark based on field measurements to support in the process of water demand modeling and the development of targeted demand-management strategies. Full article

Amid rapid urbanization and climate change, global urban water consumption, particularly household water use, has continuously increased in recent years. However, the impact of climate change on individual and household water use behavior remains insufficiently understood. In this study, we conducted tracking surveys in Beijing, China, to determine the correlation between climatic factors (e.g., temperature, precipitation, and wind) and household water use behaviors and consumption patterns. Furthermore, we proposed a genetic programming-based algorithm to identify and quantify key meteorological factors influencing household and personal water use. The results demonstrated that water use is mainly affected by temperature, particularly the daily maximum (TASMAX) and minimum (TASMIN) near-surface air temperature. In addition, showering and personal cleaning account for the largest proportion of water use and are most affected by meteorological factors. For every 10 °C increase in TASMAX, showering water use nonlinearly increases by 3.46 L/d/person and total water use nonmonotonically increases by 1.14 L/d/person. When TASMIN varies between −10 °C and 0 °C, a significant change in personal cleaning water use is observed. We further employed shared socioeconomic pathway scenarios of the Coupled Model Intercomparison Project 6 to forecast household water use. The results showed that residential water use in Beijing will increase by 21–33% by 2035 compared with 2020. This study offers a groundbreaking perspective and transferable methodology for understanding the effects of climate change on household water use behavior, providing empirical foundations for developing sustainable water resource management strategies. Full article

In this study, a Life Cycle Assessment (LCA) was conducted to evaluate the environmental impact of osmotically dehydrated, fresh-cut, pre-packaged potatoes compared to conventional untreated ones. The case study focused on a small processing line in Naxos Island, Greece, aiming to extend shelf-life by up to 5 days. The analysis covered the full value chain, from cultivation to household consumption, considering changes in energy and material use, transport volumes, waste generation, and cultivation demand. Three scenarios were assessed: (i) conventional untreated potatoes, (ii) dehydrated potatoes using market glycerol, and (iii) dehydrated potatoes using glycerol from vegetable oil treatment. Systems and life cycle inventories (LCI) were modelled in OpenLCA v2.4 software with the ecoinvent v3.11 database, applying the Environmental Footprint (EF) method, v3.1. The selected impact categories included the following: global warming potential, water use, freshwater ecotoxicity, freshwater and marine eutrophication, energy resource use, particulate matter formation, and acidification. Results showed that applying osmotic dehydration (OD) improved environmental performance in most, but not all, categories. When market glycerol was used, some burdens increased due to glycerol production. However, using glycerol from vegetable oil treatment resulted in reductions of 25.8% to 54.9% across all categories compared to the conventional scenario. Overall, OD with alternative glycerol proved to be the most environmentally beneficial approach. Full article

Adolescence is a critical period for growth and development, yet research on dietary quality and its influencing factors among Senegalese adolescent girls is limited. This study aims to assess dietary quality, with a focus on dietary diversity (DD), and identify its determinants in a nationally representative sample of adolescent girls in Senegal. A cross-sectional study was conducted in 2023 among 600 girls aged 10–19 years. Food intake was assessed over a seven-day period to evaluate DD. Household food security and sociodemographic data were gathered through face-to-face interviews. Half the sample had adequate DD. As for consumption, 80% had breakfast daily, while the same proportion consumed one snack per day. Fruits and vegetables, meat/poultry/fish, and dairy were consumed daily by less than 25% of the sample. Sweet foods, sweet beverages, and salty and fried food were consumed by less than 10% every day. Not having been sick in the past two weeks (Odds ratio (OR): 1.53, Confidence Interval (CI): 1.05–2.22), taking breakfast daily (OR: 1.89, CI: 1.23–2.93) and micronutrients (OR: 2.75, CI: 1.54–4.92), listening to the radio at least once a week (OR: 1.66, CI: 1.05–2.63), and living in a household with access to an improved source of water (OR: 4.13, CI: 2.28–7.49) were positively associated with adequate DD. Overall, the diet of adolescent girls is of poor quality. Potential determinants of their dietary quality should be considered in future nutrition programs and policies to ensure their optimal growth and development. Full article

The universalization of basic sanitation remains a challenge. For the development of sanitation infrastructure projects, it is essential to use water consumption data that accurately reflect reality, ensuring greater precision. This study aimed to determine the per capita contribution to fecal sewage (Cp) in six quilombola residences in Goiás (Brazil). The research was conducted in two phases: (a) a literature review on Cp in similar communities (CpL) and (b) the determination of Cp in six residences from different rural communities (CpP), varying in the number of inhabitants (8, 8, 5, 2, 1, and 1 persons in households R1 to R6, respectively). Flow measurements were obtained using a volumetric flowmeter (nominal flow rate of 1.5 m³/h) installed in the water pipeline supplying the toilet(s) of each household. A dearth of Cp data was observed in the literature, particularly for rural areas. Research on this topic remains in its infancy, as evidenced by the small number of publications (nine papers) published between 2006 and 2022, of which 44.4% reported on-site measurements. In the present study, the CpP ranged from 12.10 L/cap.day to 21.79 L/cap.day, with a mean of 16.22 L/cap.day (CV = 0.239). These calculated values lie within the lower (9.9 L/cap.day) and upper (51.5 L/cap.day) ranges reported in the literature. Generally, estimated data are higher than values calculated from flowrate measurements, highlighting the importance of direct measurements—which can also help reduce construction costs. Therefore, it is recommended that flowrate measurements and Cp calculations be expanded to residences with diverse demographic and geographic characteristics, also incorporating meteorological data, to obtain more accurate results. Full article

This study explores the driving factors of household energy consumption in high-density residential areas of Beijing and proposes targeted energy-saving strategies. Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. SHAP analysis revealed that key factors varied by season but included floor level, daily travel distance, building age, greening rate, water bodies, and household age. The findings inform strategies such as optimizing workplace–residence layout, improving building insulation, increasing green spaces, and promoting community energy-saving programs. This study provides refined data support for energy management in high-density residential areas, enhances the application of energy-saving technologies, and encourages low-carbon lifestyles. By effectively reducing energy consumption and carbon emissions during the operational phase of residential areas, it contributes to urban green development and China’s “dual carbon” goals. Full article

With the development of society, energy application and building thermal comfort in rural residences are receiving more and more attention. The rural residences in this survey mainly cover the rural areas of 21 prefectures in Guangdong province, of which 24.7% are in the Pearl River Delta, 18.9% in western Guangdong, 13.1% in eastern Guangdong, and 43.2% in northern Guangdong. Rural household energy consumption is mainly used for lighting equipment, household appliances, and cooking equipment, where lighting equipment and household appliances mainly consume electrical energy, and cooking equipment consumes different types of energy due to the diversity of types. First, there is a wide variety and variation in rural energy consumption, with electricity and liquefied petroleum gas as the main sources of cooking energy. Hot water is mainly obtained by heating with electricity and natural gas. Secondly, for rural residents, renewable energy is too expensive to build, is also affected by the environment and weather, and is often not convenient to use. Third, rural residents generally experience a warm, humid indoor environment with adequate airflow, but poor kitchen ventilation reduces air quality satisfaction. To enhance renewable energy adoption, technological advancements and cost reductions are necessary, along with increased government efforts in awareness campaigns, policy incentives, and demonstration projects. This study analyses the rural energy structure in Guangdong, proposes the direction of rural energy optimization, and analyses rural energy use and the feasibility of renewable energy promotion, considering the population and income of rural households. Full article

Water scarcity is a growing global issue, especially in arid regions like Iran. Global food trade complicates water and food resource management by moving virtual water (the water used to produce goods) between regions. This study uses circular economy principles and life cycle assessment (LCA) to analyze virtual water use across income groups in Iran, focusing on food consumption. This study divided households into three groups: economically vulnerable, middle-class, and affluent. Lower-income households are more water-efficient, using 3.33 L per USD, compared with 0.81 L for middle-class and 0.41 L for affluent households. The per capita virtual water consumption was 3916.7 L for vulnerable groups, 3481.6 L for middle-class, and 3418 L for affluent groups—all higher than the global average. This is because they rely on low-water foods like bread and legumes. Additionally, affluent households consume 80% more red meat, which has a high water footprint. The study calls for policies to promote water-conscious diets, optimize virtual water trade, and integrate sustainability into LCA frameworks. Aligning resource management with circular economy goals can help Iran improve water security and sustainable development. Full article