Water Science and Technology最新文献

The construction and operational costs of drainage projects are high. Traditional construction management models impose significant financial pressure on the government and reduce stakeholder motivation. Within the market-oriented development context, reforming the construction management model is crucial for breaking the current predicament. This research establishes a framework for the market-oriented construction management model for drainage projects and constructs a behavioral strategy evolutionary game model involving government, drainage management companies, and pollution discharge subjects. Through theoretical analyses and simulations, this research presents recommendations for the implementation of the market-oriented model. The research findings indicate that: (1) the market-oriented model is feasible both theoretically and practically. Pollution rights trading aids pollution discharge subjects in adapting to the market-oriented model. (2) Ensuring sewage charges remain within the interval [P₁, P₁ + L₂ - L₁] is crucial for trilateral cooperation. (3) Simulation analysis shows that intensifying policy support, reducing the cost of technological equipment upgrades, enhancing comprehensive income, lowering the pricing of sewage charges, and raising initial selection probability all promote a tendency towards ESS.

Environmental pollution control in the growing world is a challenging task for all the countries in order to keep the environmental sustainability. Biochar, a processed carbon material, draws a significant attention in the field of environmental remediation, as of its active functional groups that help remove environmental pollutants to a level insignificant to cause hazardous effects. As such, there is an increasing interest developed to promote highly productive biochar for exploring environmental engineering aspects. There is limited comprehensive literature available for understanding biochar science and its potential applications under an umbrella. This review was set to fill this knowledge gap by discussing key points related to biochar, its novel engineering aspects and potential environmental applications. Therefore, this overview tends to summarize and discuss biochar, its fundamentals, engineering aspects commonly used modifications and the potential applications of biochar in water treatment with an intention of addressing the importance of biochar for environmental remediation process. This overview will be useful for researchers, policy-makers and stakeholders to plan and review relevant scientific works in order to produce customized biochar for future environmental applications.

Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series. Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.

Combined sewer overflows (CSOs) are one of the main sources of pollution in urban water systems and significantly impede the restoration of water body functionalities within urban rivers and lakes. To understand the research and frontier trends of CSOs comprehensively and systematically, a visual statistical analysis of the literature related to CSOs in the Web of Science core database from 1990 to 2022 was conducted using the bibliometric method using HistCite Pro and VOSviewer. The results reveal a total of 1,209 pertinent publications related to CSOs from 1990 to 2022, and the quantity of CSOs-related publications indicated an increasing trend. Investigations of the distribution and fate of typical pollutants in CSOs and their ecological effects on receiving waters and studies on pollution control technologies (source reduction, process control, and end-of-pipe treatment) are the current focus of CSOs research. CSOs pollution control technologies based on source reduction and the monitoring and control of emerging contaminants are at the forefront of scientific investigations on CSOs. This study systematically and comprehensively summarized current research topics and future research directions of CSOs, thus providing a reference for CSOs control and water environment management research.

We used bench-scale tests and mathematical modeling to explore chemical oxygen demand (COD) removal rates in a moving-bed biofilm reactor (MBBR) for winery wastewater treatment, using either urea or nitrate as a nitrogen source. With urea addition, the COD removal fluxes ranged from 34 to 45 gCOD/m²-d. However, when nitrate was added, fluxes increased up to 65 gCOD/m²-d, twice the amount reported for aerobic biofilms for winery wastewater treatment. A one-dimensional biofilm model, calibrated with data from respirometric tests, accurately captured the experimental results. Both experimental and modelling results suggest that nitrate significantly increased MBBR capacity by stimulating COD oxidation in the deeper, oxygen-limited regions of the biofilm. Our research suggests that the addition of nitrate, or other energetic and broadly used electron acceptors, may provide a cost-effective means of covering peak COD loads in biofilm processes for winery or another industrial wastewater treatment.

This study aims to optimize the removal of carbon and nitrogen pollutants from saline municipal wastewater using both membrane-based and biological treatment methods. It examines a pilot-scale sequential aerobic ceramic membrane bioreactor (AeCMBR) under various salinity levels (0-20 g NaCl/L) to assess biological processes and fouling behavior. While high COD removal rates of (≈90%) were consistently achieved, ammoniacal nitrogen removal dropped from 82 to 55% at 15 g NaCl/L, despite increased oxygenation flow rates. Notably, the biomass quickly adapted to salinity changes. Indicators such as mixed liquor suspended solids (MLSS), mixed liquor suspended volatiles (MLVSS), MLVSS/MLSS ratio, and sludge volume index (SVI) showed no significant correlation with increasing salt concentrations. Soluble microbial product (SMP) production was also unaffected by rising salinity levels. The transmembrane pressure (TMP) fluctuated, with the most pronounced trend at 15 g NaCl/L, even after reducing the flux from 20 to 15 L/m²/h. The primary fouling mechanism observed was reversible cake deposition. Overall, this research enhances our understanding of short-term operational impacts on AeCMBR performance as a function of different salinity levels.

Low-energy nitrogen removal from ammonium-rich wastewater is crucial in preserving the water environment. A one-stage nitritation/anammox process with two inflows treating ammonium-containing wastewater, supplied from inside and outside the wound filter, is expected to stably remove nitrogen. Laboratory-scale reactors were operated using different start-up strategies; the first involved adding nitritation inoculum after anammox biomass formation in the filter, which presented a relatively low nitrogen removal rate (0.171 kg N/m³ · d), at a nitrogen loading rate of 1.0 kg N/m³ · d. Conversely, the second involved the gradual cultivation of anammox and nitritation microorganisms, which increased the nitrogen removal rate (0.276 kg N/m³ · d). Furthermore, anammox (Candidatus Brocadia) and nitritation bacteria (Nitrosomonadaceae) coexisted in the biofilm formed on the filter surface. The abundance of nitritation bacteria (10.5%) in the reactor biofilm using the second start-up strategy was higher than that using the first (3.7%). Thus, the two-inflow nitritation/anammox process effectively induced habitat segregation using a suitable start-up strategy.

Aerobic granular sludge (AGS) in continuous-flow reactors (CFRs) has attracted significant interest, with notable progress in research and application over the past two decades. Cumulative studies have shown that AGS-CFRs exhibit comparable morphology, settleability, and pollutant removal efficiency to AGS cultivated in sequencing batch reactors, despite their smaller particle sizes. Shear force and selection pressure are the primary drivers of granulation. While not mandatory for granulation, feast/famine conditions play a crucial role in ensuring long-term stability and nutrient removal. Additionally, bioaugmentation can facilitate the granulation process. Furthermore, this paper comprehensively assesses the application of AGS-CFRs in full-scale wastewater treatment plants (WWTPs). Currently, AGS-CFRs have been implemented in nine WWTPs, encompassing two distinct processes. Hydrocyclone-based densified activated sludge significantly enhances sludge density, settleability, and biological phosphorus removal efficiency, thus increasing treatment capacity. The microaerobic-aerobic configuration with internal separators can induce granulation, ensuring long-term stability, eliminating the need for external clarifiers, and reducing land and energy requirements. This review demonstrates the high potential of AGS-CFRs for intensifying existing WWTPs with minimal retrofitting needs. However, further research is required in granulation mechanisms, long-term stability, and nutrient removal to promote the widespread adoption of AGS.

In this study, we report a facile hydrothermal synthesis of strontium-doped SnS nanoflowers that were used as a catalyst for the degradation of antibiotic molecules in water. The prepared sample was characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and ultraviolet-visible absorption spectroscopy (UV-Vis). The photocatalytic ability of the strontium-doped SnS nanoflowers was evaluated by studying the degradation of metronidazole in an aqueous solution under photocatalytic conditions. The degradation study was conducted for a reaction period of 300 min at neutral pH, and it was found that the degradation of metronidazole reached 91%, indicating the excellent photocatalytic performance of the catalyst. The influence of experimental parameters such as catalyst dosage, initial metronidazole concentration, initial reaction pH, and light source nature was optimized with respect to metronidazole degradation over time. The reusability of the strontium-doped SnS nanoflowers catalyst was investigated, and its photocatalytic efficiency remained unchanged even after four cycles of use.

Water treatment public-private partnership (PPP) projects are pivotal for sustainable water management but are often challenged by complex risk factors. Efficient risk management in these projects is crucial, yet traditional methodologies often fall short of addressing the dynamic and intricate nature of these risks. Addressing this gap, this comprehensive study introduces an advanced risk classification prediction model tailored for water treatment PPP projects, aimed at enhancing risk management capabilities. The proposed model encompasses an intricate evaluation of crucial risk areas: the natural and ecological environments, socio-economic factors, and engineering entities. It delves into the complex relationships between these risk elements and the overall risk profile of projects. Grounded in a sophisticated ensemble learning framework employing stacking, our model is further refined through a weighted voting mechanism, significantly elevating its predictive accuracy. Rigorous validation using data from the Jiujiang City water environment system project Phase I confirms the model's superiority over standard machine learning models. The development of this model marks a significant stride in risk classification for water treatment PPP projects, offering a powerful tool for enhancing risk management practices. Beyond accurately predicting project risks, this model also aids in developing effective government risk management strategies.