Water Research X最新文献

Efficient carbon use is crucial for biological nitrogen removal. Traditional aerobic processes can waste carbon sources, exacerbating carbon deficiency. This study explores an anaerobic/oxic/anoxic system with sludge double recirculation to improve nitrogen removal in low C/N wastewater. This system integrated aerobic nitrification after the carbon intracellular storage, separating carbon and nitrogen by denitrifying glycogen-accumulating organisms (DGAOs) with endogenous partial denitrification and Anammox within the anoxic units. A significant efficiency of 91.02±7.01% chemical oxygen demand (COD) was converted into intracellular carbon in anaerobic units, significantly reducing carbon futile oxidation in the aerobic units by effectively separating COD from ammonia. Intracellular storage of carbon sources and microbial adaptation to carbon scarcity prevent futile oxidation of COD in the aerobic units even with short-term high dissolved oxygen (DO), thereby enhancing nitrogen removal under anoxic conditions with sufficient intracellular carbon source. The microbial analysis identified Candidatus Brocadia as the dominant anammox bacteria, in combination with the activity of DGAOs and other related microbial communities, accounting for 37.0% of the TN removal. Consequently, the system demonstrated remarkable nitrogen removal efficiencies, achieving 81.3±3.3% for total nitrogen (TN) and 98.5±0.9% for ammonia nitrogen while maintaining an effluent COD concentration of 17.2±9.1 mg/L, treating the low C/N of 4.18 in the influent wastewater. The findings in this study provide a sustainable and energy-saving technique for conventional WWTPs to meet strict discharge standards by avoiding futile oxidation of COD and encouraging anammox contributions.

Due to the large amounts of pharmaceuticals and personal care products (PPCPs) currently being consumed and released into the environment, this study provides a comprehensive analysis of pharmaceutical pollution in both raw and treated water from full-scale drinking water treatment plants nationwide. Our investigation revealed that 30 out of 37 PPCPs were present in raw water with mean concentrations ranging from 0.01–131 ng/L. The raw water sources, surface water (ND – 147 ng/L), subsurface water (ND – 123 ng/L) and reservoir sources (ND – 135 ng/L) exhibited higher mean concentration levels of pharmaceutical residues compared to groundwater sources (ND – 1.89 ng/L). Meanwhile, in treated water, 17 of the 37 analyzed PPCPs were present with carbamazepine, clarithromycin, fluconazole, telmisartan, valsartan, and cotinine being the most common (detection frequency > 40 %), and having mean concentrations of 1.22, 0.12, 3.48, 40.1, 6.36, and 3.73 ng/L, respectively. These findings highlight that, while water treatment processes are effective, there are some persistent compounds that prove challenging to fully eliminate. Using Monte Carlo simulations, risk assessment indicated that most of these compounds are likely to have negligible impact on human health, except for the antihypertensives. Telmisartan was identified as posing the highest ecological risk (RQ > 1), warranting further investigation, and monitoring. The study concludes by prioritizing specific 14 pharmaceuticals, including telmisartan, clarithromycin, lamotrigine, cotinine, lidocaine, tramadol, and others, for future monitoring to safeguard both ecological and human health.

This study explored the impact of varying nitrate to sulfide (N/S) ratios on nitrogen removal efficiency (NRE) in the sulfide-driven autotrophic denitrification and anammox (SDAD-anammox) system. Optimal nitrogen removal was observed at N/S ratios between 1.5 and 2.0. Isotope tracing results showed that the contribution of anammox to nitrogen removal was enhanced with increasing N/S ratios, reaching up to 37 % at the N/S ratio of 2.5. Additionally, complex nitrogen pathways were identified, including dissimilatory nitrate reduction to ammonium (DNRA). Furthermore, isotope tracing was innovatively applied to investigate N₂O emissions, demonstrating that higher N/S ratios significantly reduced N₂O emissions, with the lowest emissions at N/S ratio of 2.5. Gene expression analysis indicated that nitrogen and sulfide transformation genes decreased with increasing N/S ratios, while anammox-related genes first increased and then decreased, reflecting the system's microbial dynamics. These findings offer insights into nitrogen transformation pathways and N₂O production mechanisms in the SDAD-anammox process.

Over the last two decades, proliferations of benthic cyanobacteria producing derivatives of anatoxin-a have been reported in rivers worldwide. Here, we follow up on such a toxigenic event happening in the Areuse river in Switzerland and investigate the diversity and genomics of major bloom-forming riverine benthic cyanobacteria. We show, using 16S rRNA-based community profiling, that benthic communities are dominated by Oscillatoriales. We correlate the detection of one Microcoleus sequence variant matching the Microcoleus anatoxicus species with the presence of anatoxin-a derivatives and use long-read metagenomics to assemble complete circular genomes of the strain. The main dihydro-anatoxin-a-producing strain in the Areuse is distinct from strains isolated in New Zealand, the USA, and Canada, but forms a monophyletic strain cluster with them with average nucleotide identity values close to the species threshold. Compared to the rest of the Microcoleus genus, the toxin-producing strains encode a 15 % smaller genome, lacking genes for the synthesis of some essential vitamins. Toxigenic mats harbor a distinct microbiome dominated by proteobacteria and bacteroidetes, which may support cyanobacterial growth by providing them with essential nutrients. We recommend that strains closely related to M. anatoxicus be monitored internationally in order to help predict and mitigate similar cyanotoxic events.

Microalgae biofilm has garnered significant attention from researchers in the field of sewage treatment due to its advantages such as ease of collection and stable sewage treatment capabilities. Using agricultural waste as biofilm carriers has become a hotspot in reducing costs for this method. This study first combined Tetradesmus obliquus with loofah to form a microalgae biofilm for the study of periodic nitrogen and phosphorus removal from municipal wastewater. The biofilm could stably treat 7 batches of wastewater within one month. The removal rate of TP almost reached 100 %, while the removal rates of NH₄⁺ and TN both reached or exceeded 80 %. The average biomass yield over 25 days was 102.04 mg/L/day. The polysaccharide content increased from 8.61 % to 16.98 % during the cyclic cultivation. The lipid content gradually decreased from 40.91 to 26.1 %. The protein content increased from 32.93 % in the initial stage to 41.18 % and then decreased to 36.31 % in the later stage. During the mid-stage of culturing, the richness of anaerobic bacteria decreased, while the richness of aerobic and facultative bacteria increased, which was conducive to the construction of the microalgae-bacteria symbiotic system and steadily improved the effect of nitrogen and phosphorus removal. As the culturing progressed, the Rotifers that emerged during the mid-stage gradually damaged the biofilm over time, leading to a decline in the effectiveness of sewage treatment in the later stages. This study offers technical support for carrier selection in microalgae biofilm methods and for the periodic removal of nitrogen and phosphorus from wastewater.

Extracellular polymeric substances (EPS) play a crucial role in the aggregation of partial denitrification (PD) consortia, as EPS is closely linked to bioreactor performance. However, the structural and compositional properties of EPS from PD consortia have not yet been investigated. In this study, photometric measurements indicated that PD consortia contained significantly more EPS (168.81 ± 2.10 mg/g VSS) compared to conventional activated sludge (79.79 mg/g VSS). The EPS of PD consortia exhibited a significant predominance of proteins over polysaccharides, with a protein/polysaccharide ratio of 1.43 ± 0.10. FTIR analysis revealed that the EPS of PD consortia contained fewer hydrophilic functional groups, particularly carboxyl and carbonyl groups, indicating a high aggregation potential. The content comparison of EPS and functional groups across three stratified EPS subfractions from PD consortia consistently followed the sequence: TB-EPS > LB-EPS > S-EPS. XPS results corroborated the FTIR findings and the protein/polysaccharide ratio determined by photometric measurements, all of which suggested that the EPS of PD consortia exhibited a higher abundance of hydrophobic functional groups. However, the higher α-helix/(β-sheet + random coil) ratio (0.99) suggested that the proteins in PD consortia had a compact structure, making inner hydrophobic groups difficult to expose. This compact protein structure could limit aggregation among bacterial cells, indicating the need for process optimization to enhance sludge aggregation in PD-related processes. Overall, understanding the aggregation characteristics of PD consortia could improve the application of PD-based processes.

Climate change is driving global endeavours to achieve carbon neutrality and renewable energy expansion. Sludge, a nutrient-rich waste, holds energy potential yet poses environmental challenges that need proper management. We conducted a comprehensive life cycle assessment to evaluate the energy balance and environmental footprint of the most commonly used sludge management scenarios in BRICS countries, namely Brazil, Russia, India, China, and South Africa. Technologies such as incineration and anaerobic digestion with energy recovery units (i.e., cogeneration unit) maximize energy balance and minimize the environmental footprint, with incineration showing a superior performance. Shifting sludge management scenarios from the worst to the best can boost energy production by 1.4–98.4 times and cut the environmental footprint by 1.5–21.4 times. In 2050, these improvements could lead to a 98-fold boost in energy generation and a 25-fold drop in carbon emissions, according to the Announced Pledges Scenarios. Optimizing parameters such as volatile solids and anaerobic digestion efficiency further boosts energy output and minimizes the environmental footprint. This study offers robust evidence to support sustainable sludge management and thus promote energy recovery and carbon neutrality goals, guide technological transitions, and inform policymaking for sustainable development.

Freshwater biodiversity is increasingly threatened by dams and many other anthropogenic stressors, yet our understanding of the complex responses of different biotas and their multiple facets remains limited. Here, we present a multi-faceted and integrated-indices approach to assess the differential responses of freshwater biodiversity to multiple stressors in the Yangtze River, the third longest and most dam-densely river in the world. By combining individual biodiversity indices of phytoplankton, zooplankton, periphyton, macroinvertebrates, and fish with a novel integrated aquatic biodiversity index (IABI), we disentangled the effects of hydrology, water quality, land use, and natural factors on both α and β diversity facets in taxonomic, functional, and phylogenetic dimensions. Our results revealed that phytoplankton and fish species and functional richness increased longitudinally, while fish taxonomic and phylogenetic β diversity increased but phytoplankton and macroinvertebrate β diversity remained unchanged. Hydrology and water quality emerged as the key drivers of all individual biodiversity indices, followed by land use and natural factors, with fish and phytoplankton showed the strongest responses. Importantly, we found that natural, land use, and hydrological factors indirectly affected biodiversity by altering water quality, which in turn directly influenced taxonomic and phylogenetic IABIs. Our findings highlight the complex interplay of multiple stressors in shaping freshwater biodiversity and underscore the importance of considering both individual and integrated indices for effective conservation and management. We propose that our multi-faceted and integrated-indices approach can be applied to other large, dam-modified river basins globally.

The rapid expansion of coastal aquaculture has led to an increase in the coverage of aquaculture ponds, where intense feed-derived nitrogen is causing significant emissions of nitrous oxide (N₂O). Multiple N₂O production pathways and the relative importance of water column vs. sedimentary production in aquaculture ponds remain uncertain. Clarifying these pathways is vital for sustainable aquaculture development. Using ¹⁵N-labeled dissolved inorganic nitrogen, the pathways and rates of N₂O production in subtropical aquaculture ponds located in south China, cultivating whiteleg shrimp, Japanese seabass, and giant river prawn, were successfully characterized. Total N₂O production rates ranged from 6 to 70 µmol-N m⁻² d⁻¹, with the shrimp pond exhibiting the highest total N₂O production rates, followed by ponds for seabass and prawn. These differences are primarily due to varying feed amounts causing differences in dissolved nutrients in water column and sediment. Particularly, nutrient and organic matter accumulation at the surface sediment stimulated N₂O production. The oxygenated sediment on a centimeter scale could produce substantially more N₂O compared to the water column above on a meter scale. Partial denitrification, i.e., nitrate and nitrite reduction to N₂O, was more important (> 60 %) for N₂O production in aquaculture ponds. The availability of nitrite is likely a major factor driving partial denitrification for both sedimentary and water column N₂O production.

In the field of water supply management, multi-steps water demand forecasting plays a crucial role. While there have been many studies related to multi-steps water demand forecasting based on deep learning, little attention has been paid to the interpretability of forecasting models. Aiming to improve both the forecasting accuracy and interpretability of the model, a novel urban water demand forecasting neural network (UWDFNet) was presented in this paper. Compared with traditional deep learning models, it innovatively considered domain-specific prior knowledge from water supply management and incorporated the correlation relationship between different input variables into the design of the neural network structure, and verified the consistency between the knowledge learned by the model and prior knowledge through interpretability analysis. Additionally, a systematic performance evaluation was conducted and proved that UWDFNet possesses better accuracy and stability compared to other baseline models(e.g., gated recurrent unit network (GRUN), GRUN with a corrected Network (GRUN+CORRNet), GRUN+PID, GRUN+Kmeans).