Effect of microbial network complexity and stability on nitrogen and sulfur pollutant removal during sediment remediation in rivers affected by combined sewer overflows.

Discovering the complexity and improving the stability of microbial networks in urban rivers affected by combined sewer overflows (CSOs) is essential for restoring the ecological functions of urban rivers, especially to improve their ability to resist CSO impacts. In this study, the effects of sediment remediation on the complexity and stability of microbial networks was investigated. The results revealed that the restored microbial community structure using different approaches in the river sediments differed significantly, and random matrix theory showed that sediment remediation significantly affected microbial networks and topological properties; the average path distance, average clustering coefficient, connectedness, and other network topological properties positively correlated with remediation time and weakened the small-world characteristics of the original microbial networks. Compared with other sediment remediation methods, regulating low dissolved oxygen (DO) shifts the microbial network module hubs from Actinobacteria and Bacteroidetes to Chloroflexi and Proteobacteria. This decreases the positive association of networks by 17%-18%, which intensifies the competitiveness among microorganisms, further weakening the influence and transmission of external pressure across the entire microbial network. Compared with that of the original sediment, the vulnerability of the restored network was reduced by more than 36%, while the compositional stability was improved by more than 12%, with reduced fluctuation in natural connectivity. This microbial network succession substantially increased the number of key enzyme-producing genes involved in nitrogen and sulfur metabolism, enhancing nitrification, denitrification, and assimilatory sulfate reduction, thereby increasing the removal rates of ammonia, nitrate, and acid volatile sulfide by 43.42%, 250.68% and 2.66%, respectively. This study comprehensively analyzed the succession patterns of microbial networks in urban rivers affected by CSOs before and after sediment remediation, which may provide a reference for reducing the impact of CSO pollution on urban rivers in the subsequent stages.

Automatic identification of harmful algae based on multiple convolutional neural networks and transfer learning.

The monitoring of harmful phytoplankton is very important for the maintenance of the aquatic ecological environment. Traditional algae monitoring methods require professionals with substantial experience in algae species, which are time-consuming, expensive, and limited in practice. The automatic classification of algae cell images and the identification of harmful phytoplankton images were realized by the combination of multiple convolutional neural networks (CNNs) and deep learning techniques based on transfer learning in this work. Eleven common harmful and 31 harmless phytoplankton genera were collected as input samples; the five CNNs classification models of AlexNet, VGG16, GoogLeNet, ResNet50, and MobileNetV2 were fine-tuned to automatically classify phytoplankton images; and the average accuracy was improved 11.9% when compared to models without fine-tuning. In order to monitor harmful phytoplankton which can cause red tides or produce toxins severely polluting drinking water, a new identification method of harmful phytoplankton which combines the recognition results of five CNN models was proposed, and the recall rate reached 98.0%. The experimental results validate that the recognition performance of harmful phytoplankton could be significantly improved by transfer learning, and the proposed identification method is effective in the preliminary screening of harmful phytoplankton and greatly reduces the workload of professional personnel.

New insights into cyanobacterial blooms and the response of associated microbial communities in freshwater ecosystems.

Cyanobacterial blooms are important environmental problems in aquatic ecosystems. Researchers have found that cyanobacterial blooms cannot be completely prevented by controlling and/or eliminating pollutants (nutrients). Thus, more in-depth basic research on the mechanism of cyanobacterial blooms is urgently needed. Cyanobacteria, being primordial microorganisms, provide habitats and have various forms of interactions (reciprocity and competition) with microorganisms, thus having a significant impact on themselves. However, little is known about how environmental conditions and microbial communities in both water and sediment jointly affect cyanobacterial blooms or about the co-occurrence patterns and interactions of microbial communities. We investigated changes in environmental factors and microbial communities in water and sediment during different cyanobacterial blooms and revealed their interacting effects on cyanobacteria. Cyanobacteria had greater competitive and growth advantages than other microorganisms and had antagonistic and aggressive effects on them when resources (such as nutrients) were abundant. Furthermore, microbial networks from cyanobacterial degradation periods may be more complex and stable than those from bloom periods, with more positive links among the microbial networks, suggesting that microbial community structures strengthen interconnections with each other to degrade cyanobacteria. In addition, we found that sediment-enriched cyanobacteria play a key role in cyanobacterial blooms, and sediment microorganisms promote the nutrient release, further promoting cyanobacterial blooms in the water bodies. The study contributes to further our understanding of the mechanisms for cyanobacterial blooms and microbial community structural composition, co-occurrence patterns, and responses to cyanobacteria. These results can contribute to future management strategies for controlling cyanobacterial blooms in freshwater ecosystems.

[Metagenomic Analysis of Resistance Genes in Membrane Cleaning Sludge].

Wastewater treatment plants (WWTPs) are considered important reservoirs of antibiotic resistance genes (ARGs) and function as the main sources of ARGs in the environment. Membrane bioreactors (MBRs) have been recognized as effective tools for removing ARGs in WWTPs.There are a large number of pathogens and resistance genes in colloids, particulate matter, suspended matter, and microbial metabolites in intercepted wastewater by MBR. However, the distribution characteristics of resistance genes in membrane cleaning sludge remains unclear. In this study, resistance genes of membrane cleaning sludge were analyzed using a metagenomic technique. The results showed that there were 39 phyla in the membrane cleaning sludge. Proteobacteria, Nitrospirae, and Actinobacteria were the dominant phyla. The dominant genera were Nitrospira, Pseudomonas, and Bradyrhizobium. The pathogens accounted for 10.54% of all bacteria in the sample, among which Pseudomonas had the highest abundance, accounting for 3.94%. A total of 17 types of antibiotic resistance genes and 16 types of metal resistance genes (MRGs) (15 types of single metal resistance genes and 1 types of multi-heavy metal resistance gene) were identified. Multidrug resistance genes had the highest abundance, accounting for 49.08%. Multi-heavy metal resistance genes were the most abundant, accounting for 34.58%. The copper resistance genes were the most abundant of the single metal resistance genes, accounting for 19.99%. The most important functional pathway of microbial community in the membrane cleaning sludge was metabolic related, and many genes identified were related to human diseases. The numbers of genes related to bacterial resistance and bacterial infectious diseases were the largest, accounting for 34.50% and 16.62%, respectively. These results indicate that there were abundant ARGs, MRGs, and pathogens in the membrane cleaning sludge, which has potential environmental health risks. It is necessary to strengthen the control of ARGs, MRGs, and pathogens in membrane cleaning sludge to provide guidance for selecting appropriate technologies for effectively removing ARGs, MRGs, and pathogens.

Bibliometric analysis of zerovalent iron particles research for environmental remediation from 2000 to 2019.

Zerovalent iron (ZVI) has been a major focus of research and has attracted great attention during the last 2 decades by international researchers because of its excellent pollutant removal performance and several other merits in environmental remediation. Based on Web of Science Core Collection data, we present a comprehensive bibliometric analysis of ZVI research from 2000 to 2019. We analyze 4472 publications assuming three stages of growth trend of annual publication totals. We find that "The Chemical Engineering Journal" has been the most productive journal; Noubactep C is identified as the most productive author; China has been the most active country in this field and the Chinese Academy of Science the most productive institution. The timeline of keywords shows seven distinct co-citation clusters. In addition, the top 38 keywords with strong citation bursts are also detected, suggesting that the innovation of green composite synthesis of ZVI and nanoscale ZVI and its efficient removal capacity might be the prevailing research directions in the future.

New insights into restoring microbial communities by side-stream supersaturated oxygenation to improve the resilience of rivers affected by combined sewer overflows.

Combined sewer overflows (CSOs) are a dominant contributor to urban river pollution. Therefore, reducing the environmental impacts of CSOs and improving the self-purification capacity of water bodies are essential. In this study, the side-stream supersaturation (SSS) oxygenation was applied to restore microbial function of rivers which are affected by CSOs to improve the self-purification capacity. The results showed that apart from the dissolved organic matter inputs from CSO event, the sediment had become an important contributor to pollution in the studied river. After the long-term (46 d) implementation of SSS oxygenation, dissolved oxygen and the oxidation-reduction potential of the river water increased by 98% and 238%, respectively, compared to emergency control measures implemented following individual CSO events. The NH3-N concentrations and the chemical oxygen demand also decreased by 20% and 45%, respectively. In addition, the occurrence of microbial functions related to information storage and processing, and cellular process and signaling, increased by 1.87% and 0.82% in response to SSS oxygenation, respectively, and the Shannon index of the sediment microbial community increased by more than 15%. The frequencies of genes related to nitrification and sulfur oxidation also increased by 20-450% and >50%, respectively. This research provides new insights into the ecological restoration of rivers affected by CSOs.

Effects of hydrological and climatic variables on cyanobacterial blooms in four large shallow lakes fed by the Yangtze River.

Shallow lakes, one of the most widespread water bodies in the world, are easily shifted to a new trophic state due to external interferences. Shifting hydrologic conditions and climate change can cause cyanobacterial harmful algal blooms (CyanoHABs) in shallow lakes, which pose serious threats to ecological integrity and human health. This study analyzed the effects of hydrologic and meteorological variables on cyanobacterial blooms in Yangtze-connected lakes (Lake Dongting and Poyang) and isolated lakes (Lake Chao and Tai). The results show that (i) chlorophyll-a (Chl-a) concentration tends to decrease exponentially with increasing relative lake level fluctuations (RLLF) and precipitation, but to increase linearly with increasing wind speed and air temperature; (ii) Chl-a concentrations in lakes were significantly higher when RLLF < 100, precipitation < 2.6 mm, wind speed > 2.6 m s-1, or air temperature > 17.8 °C; (iii) the Chl-a concentration of Yangtze-isolated lakes was more significantly affected by water level amplitude, precipitation, wind speed and air temperature than the Yangtze-connected lakes; (iv) the RLLF and the ratio of wind speed to mean water depth could be innovative coupling factors to examine variation characteristics of Chl-a in shallow lakes with greater correlation than single factors.

The cotreatment of old landfill leachate and domestic sewage in rural areas by deep subsurface wastewater infiltration system (SWIS): Performance and bacterial community☆.

In this work, two deep subsurface wastewater infiltration systems (SWISs) were constructed and fed with domestic sewage (control system, S1) and mixed wastewater consisting of old landfill leachate and domestic sewage (experimental system, S2). S1 and S2 exhibited favorable removal efficiencies, with TP (98.8%, 98.7%), COD (87.6%, 86.9%), NH4+-N (99.8%, 99.9%) and TN (99.2%, 98.9%). Even when increasing the pollutant load in S2 by adding old landfill leachate, the almost complete removal performance could be maintained in terms of low effluent concentrations and even increased in terms of load removal capabilities, which included COD (19.4, 25.9 g∙m-2·d-1), NH4+-N (8.2, 19.9 g∙m-2·d-1), TN (8.9, 20.6 g∙m-2·d-1). To investigate the transformation of dissolved organic matter along depth, Three-Dimensional Excitation Emission Matrix fluorescence spectroscopy combined with Fluorescence Regional Integration analysis was applied. The results showed that PⅠ,n and PⅡ,n (the proportions of biodegradable fractions) increased gradually from 6.59% to 21.8% at S2_20 to 10.8% and 27.7% at S2_110, but PⅢ,n and PⅤ,n (the proportions of refractory organics) declined from 23.1% to 27.8% at S2_20 to 21.1% and 16.4% at S2_110, respectively. In addition, high-throughput sequencing technology was employed to observe the bacterial community at different depths, and the predicted functional potential of the bacterial community was analyzed by PICRUSt. The results showed that the genera Flavobacterium, Pseudomonas, Vogesella, Acinetobacter and Aquabacterium might be responsible for refractory organic degradation and that their products might serve as the carbon source for denitrifiers to achieve simultaneous nitrate and refractory organic removal. PICRUSt further demonstrated that there was a mutual response between refractory organic degradation and denitrification. Overall, the combined treatment of domestic sewage and old leachate in rural areas by SWIS is a promising approach to achieve comprehensive treatment.

Effects of ambient temperature on the redistribution efficiency of nutrients by desert cyanobacteria- Scytonema javanicum.

Cultures of Scytonema javanicum obtained from artificial medium are used to control desertification, and through the effective redistribution of nutrients, related environmental problems can be alleviated. Wastewater is considered to be a potential alternative medium for S. javanicum. However, the effect of temperature on the nutrient redistribution ability of S. javanicum cultured in wastewater has rarely been considered. Therefore, this study explores the effect of temperature on S. javanicum in wastewater. The results showed that a sufficient temperature increase (from 25 °C to 30 °C) increased the photosynthetic activity of photosynthetic system II (PSII), accelerated the accumulation rate of S. javanicum biomass, and improved the removal efficiency of nutrients in wastewater. However, an increasing temperature caused a decrease in the final accumulated biomass. When the temperature was above 35 °C, the ratio of the variable to maximal fluorescence (Fv/Fm) of S. javanicum decreased, thus, causing damage to PSII. The average Fv/Fm at 35 °C and 40 °C decreased by 10.49% and 72.37%, respectively, compared to that at 25 °C. By analysing the chlorophyll fluorescence induction kinetics (OJIP) curve after 30 days, the P phase at 30 °C increased by 15.47% relative to that at 25 °C, whereas that at 35 °C and 40 °C decreased by 45.54% and 86.37%, respectively. In particular, at 40 °C, the O-J-I-P phase transformed into the O-J (J = I = P) phase, which caused irreversible damage to the PSII of S. javanicum. Comprehensive scores were determined using the entropy weight method and revealed that 30 °C was the optimal temperature for the wastewater culture of S. javanicum. This temperature improved the biomass accumulation rate and wastewater transfer efficiency. These results provide a scientific basis for improving the efficiency of the coupling technology of wastewater treatment and desert algal cultivation.

[GIS Spatial Distribution and Ecological Risk Assessment of Heavy Metals in Surface Sediments of Shallow Lakes in Jiangsu Province].

To understand pollution of heavy metals in surface sediments of shallow lakes, surface sediments samples of 11 lakes in Jiangsu province were collected to determine the content of six heavy metals including As, Cr, Cu, Pb, Zn and Ni. GIS was used to analyze the spatial distribution of heavy metals, and geological accumulation index (Igeo), modified contamination index (mCd) pollution load index (PLI) and potential ecological risk index (RI) were used to evaluate heavy metal contamination in the sediments. The results showed that: in the lakes' surface sediments, the average content of As, Cu, Zn, Cr, Pb, Ni in multiples of soil background of Jiangsu province were 1.74-3.85, 0.65-2.66, 0.48-3.56, 0.43-1.52, 0.02-1.49 and 0.12-1.42. According to the evaluation results of Igeo and RI, As, which had high degree of enrichment and great potential ecological risk, was the main pollutant, followed by Cu, and pollution of the rest of heavy metals was relatively light. Combining the results of several evaluation methods, in surface sediments of Sanjiu Lake, Gaoyou Lake and Shaobo Lake, these heavy metals had the most serious pollution, the maximum pollution loading and moderate potential ecological risk; in surface sediments of Gehu Lake, Baima Lake and Hongze Lake, some regions were polluted by certain metals, the overall trend of pollution was aggravating, the pollution loading was large, and the potential ecological risk reached moderate; in the other 5 lakes, the risk of sediments polluted by heavy metals, as well as the pollution loading, was small, and the overall was not polluted.