Cleaner Water最新文献

Pakistan is currently facing significant water scarcity issues, intensified by climate change. The main water source, the transboundary Indus River system, faces challenges such as water management, limited data availability, and inadequate management, leading to a gap between water demand and supply across various sectors. Agriculture, which consumes over 95 % of the country’s water resources, contributes nearly 25 % to the GDP, but is heavily dependent on irrigation due to limited rainfall. With rainfall meeting only 15 % of crop water requirements, groundwater plays a critical role, covering 40–60 % of irrigation needs. This study focuses on the Rechna Doab in the Indus Basin Irrigation System (IBIS) using the WEAP (Water Evaluation and Planning) model to assess the supply-demand gap under IPCC's climate change scenarios from Assessment Report Six (AR6). The main findings indicate: (1) Under SSP 8.5, unmet demand in the Upper Chenab Canal and other regions will increase by 33–47 % by mid-century; (2) demand site coverage will decline significantly, especially in Lower Gugera and Jhang branches; (3) groundwater dependency will increase substantially in response to the growing supply-demand gap. This work contributes to improving water management in Rechna Doab by providing a clear framework for adapting water resources to climate change using WEAP projections under various IPCC scenarios.

This work assesses the nutrient recovery potential in Panama City’s wastewater facilities. Nutrients can be recovered by using biosolids, which are currently dumped in landfills, and by precipitating struvite from waste streams. The economic viability of four types of struvite reactors was analyzed. The installation of struvite systems is not profitable for the current discharge limit of 10 mg/l for P. However, for P limits of 4 mg/l and below, struvite systems would generate significant revenue due to savings in the chemicals needed to remove the excess of P. For a P limit of 4 mg/l, the best struvite reactor presented a payback time of 10 years and a return on investment of 13.68 %. It is concluded that in Panama, as in the rest of Latin American countries, nutrient discharge standards are currently too loose for struvite systems to become viable. Meanwhile, the use of biosolids is of particular interest as the standards for their use are already well developed. The use of biosolids from Panama City could supply 1.6 % of the consumption of fertilizers in the country. It was found that the quality of the biosolids that are produced in the region is satisfactory, and that the demand from potential users can be improved through composting the material.

Optimizing membrane performance for efficient water treatment is crucial for sustainable development and environmental protection, aligning with UN SDGs. This study involves experimental design, statistical reliability of small data, and explainable machine learning (ML) using SHAP (Shapley Additive Explanations). The research uses ML models and statistical tests to ensure data reliability and stationarity and investigate various membranes’ fouling and separation efficiency (MX-CM, PDMX-CM, and SPDMX-CM). Stationarity tests, including the Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests, revealed that MX-CM is stationary at level (I(0)), while PDMX-CM and SPDMX-CM required first differencing (I(1)) to achieve stationarity. SHAP analysis showed that in the fouling study, higher values of PDMX-CM and MX-CM positively influenced model predictions, with SHAP values of +0.09 for Cycle, −0.06 for PDMX-CM, and −0.06 for MX-CM. In the separation efficiency study, Cycle had a neutral impact (0.00), PDMX-CM had a slight positive effect, and MX-CM had a slight negative impact. These findings highlight the importance of ensuring data stationarity and utilizing SHAP for model explainability in predicting membrane performance. Accurate preprocessing and model interpretation enhance decision-making and optimization in membrane fouling and separation efficiency studies, ensuring robust and reliable ML models.

Despite advancements in water treatment, the degradation of water quality during distribution remains under-researched in the Federal Capital Territory (FCT), Nigeria. This study addresses this gap by evaluating the physicochemical and microbial quality of the water distribution system, aligning with Sustainable Development Goal 6 (SDG 6), which focuses on water and sanitation management. The effectiveness of water treatment and distribution processes was assessed, identifying variations in water quality across 11 distribution points. Although most physicochemical parameters met standards, manganese levels exceeded WHO guidelines at 10 locations, and low residual chlorine was linked to microbial contamination. These findings underscore the need for enhanced monitoring and treatment, providing recommendations to improve water quality management and protect public health.

Common effluent treatment plants (CETPs) are integrated wastewater treatment systems meant to function as a consolidated process for several industrial units from a single industrial area. CETPs are installed as a common treatment plant to provide a uniform treatment system along with space and cost effectiveness and play an important role in industrial wastewater treatment and management. However, due to several reasons, including the varied nature of influent pollutants, the inability of CETPs to effectively treat wastewater can lead to contamination of water bodies in the city. Ahmedabad is an industrialized city in the state of Gujarat in India, where currently seven CETPs discharge their wastewater into the Sabarmati river. Due to the increased pollution in the Sabarmati river, it is necessary to evaluate the performance of these CETPs for their quality of wastewater treatment. The aim of this study was to present a reliability analysis of these CETPs using statistical data obtained from official Government websites. An established methodology was used to calculate the coefficient of reliability in terms of compliance of effluent chemical oxygen demand, biochemical oxygen demand, ammoniacal nitrogen, and phenolic compounds. The results revealed significant variations in the reliability levels across all CETPs. The reliability levels ranged from 7 - 99.99 % for COD, 25.5–99.99 % for BOD, 46.8–99.4 % for SS, 41.2–99.8 % for NH₃-N, and 85.2–98.1 % for PC. These discrepancies can be attributed to improper functioning in majority of CETPs. Further, the required operating mean concentrations for the studied parameters were obtained to improve the reliability level to 95 %. This study should definitely help the wastewater community as it can be applied to individual wastewater treatment plants to achieve optimum treatment performances.

Using a scoring technique, we have developed a Water Security Reporting Index (WSRI) to assess the disclosed information pertaining to the preparedness for extreme water events among 15 Brazilian water utilities. This evaluation is based on the analysis of annual reports from water and sanitation companies. The WSRI incorporates seven dimensions: (i) Climate changes and their impacts on water availability; (ii) Water availability evaluation and measurement; (iii) Improvements in supply infrastructure systems; (iv) Demand-side infrastructure improvements; (v) User awareness creation; (vi) Water availability prediction; and (vii) Actions to prevent water availability issues. The findings reveal a paradoxical scenario where the WSRI falls significantly below the maximum score. Simultaneously, the growing concerns about the impacts of global change, leading to an increase in the frequency and magnitude of extreme weather events, highlight a pressing issue in Brazil. Neglecting this concern implies disregarding the impending scarcity of water, the primary focus of water utilities. User awareness creation emerges as the dimension with the highest score. Conversely, water availability evaluation and prediction, along with demand-side infrastructure improvements, receive the least attention from water utility managers in terms of water security. This study underscores the disparity between the clear understanding that water supply companies possess regarding the impacts of climate change on the water industry and their failure to effectively communicate the actions they have adopted and planned.

Despite improvements to environmental protection initiatives, millions of Black, Indigenous, and other people of color (BIPOC) continue to live in communities that are disproportionately affected by environmental contamination. Environmental Justice (EJ) screening tools, such as CalEnviroScreen, EJ Map, and PennEnviroScreen, have been developed to help state and federal governments gauge the extent of EJ in their jurisdictions. These screening tools have propelled the EJ advocacy initiative, illustrating the historic and ongoing disproportionate effects of contamination in many BIPOC communities. Yet, screening tools and their indicators vary, and we must understand how these tools and indicator choices differently identify at-risk communities, including those facing drinking water violations. We investigate how indicator choices differently identify and affect communities facing such violations. Specifically, we examine how EJ screening tools differently identify at-risk communities experiencing drinking water violations, which indicators drive these differences, and how indicator choice affects community identification. Our analysis reveals that EJ screen indicators preferentially identify at-risk, low-income, unemployed, BIPOC renters. However, additional indicators such as middle-income and food insecurity/SNAP can expand identification to ensure actions reach neglected communities. By developing and enhancing EJ screening tools, we can better determine which drinking water violations are present, identify who is being affected by them, and better direct our mitigation efforts to communities in need of assistance.