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Inactivation of Antibiotic-Resistant Bacteria in Wastewater by Ozone-Based Advanced Water Treatment Processes
The inactivating effect of ozone (O3)-based advanced oxidation processes (AOPs) (O3/H2O2, O3/UV, and O3/UV/H2O2 systems) on antimicrobial-resistant bacteria (AMRB) and antimicrobial-susceptible bacteria (AMSB) in sewage treatment plant (STP) wastewater was investigated. The AMRB were grouped into six classes: carbapenem-resistant Enterobacteriaceae (CRE), extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E), multidrug-resistant Acinetobacter (MDRA), multidrug-resistant Pseudomonas aeruginosa (MDRP), methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant Enterococcus (VRE); these classes constituted the World Health Organization (WHO) global priority list of AMRB. The results indicate that O3-based advanced wastewater treatment inactivated all AMRB and AMSB (>99.9%) after 10 min of treatment, and significant differences (p < 0.5) were not observed in the disinfection of AMRB and AMSB by each treatment. Altered taxonomic diversity of micro-organisms based on 16S rRNA gene sequencing via O3/UV and O3/UV/H2O2 treatment showed that advanced wastewater treatments not only inactivated AMRB but also removed antimicrobial resistance genes (AMRGs) in the wastewater. Consequently, this study recommends the use of advanced wastewater treatments for treating the STP effluent, reducing environmental pollution, and alleviating the potential hazard to human health caused by AMRB, AMSB, and infectious diseases. Overall, this study provides a new method for assessing environmental risks associated with the spread of AMRB and AMSB in aquatic environments, while keeping the water environment safe and maintaining human health.
Journal Article
Occurrence and Quantitative Microbial Risk Assessment of Methicillin-Resistant Staphylococcus aureus (MRSA) in a Sub-Catchment of the Yodo River Basin, Japan
The occurrence of Staphylococcus aureus (S. aureus) and methicillin-resistant S. aureus (MRSA) in a sub-catchment of the Yodo River Basin, a representative water system of a drinking water source in Japan, was investigated. The chromogenic enzyme-substrate medium method was used for the detection of S. aureus and MRSA by the presence or absence of antimicrobials in the medium for viable bacteria in a culture-based setting. The contributions of S. aureus and MRSA from wastewater to the rivers were estimated based on mass flux-based analysis, and quantitative microbial risk assessment (QMRA) was further conducted for S. aureus and MRSA in river environments. The mean abundance of S. aureus and MRSA was 31 and 29 CFU/mL in hospital effluent, 124 and 117 CFU/mL in sewage treatment plant (STP) influent, 16 and 13 CFU/mL in STP effluent, and 8 and 9 CFU/mL in river water, respectively. Contribution of the pollution load derived from the target STP effluent to river water ranged from 2% to 25%. The QMRA showed that to achieve the established health benchmarks, the drinking water treatment process would need to yield 1.7 log10 and 2.9 log10 inactivation in terms of infection risk and disability-adjusted life year (DALY) indexes, respectively. These findings highlight the link between medical environment and the importance of environmental risk management for antimicrobial-resistant bacteria in aquatic environments.
Journal Article
Characterization and removal of microplastics in a sewage treatment plant from urban Nagpur, India
Sewage treatment plant (STP) acts as a potential source of microplastic contamination in the environment. The presence of microplastics in the sewage treatment plant is reported over the globe in varying concentrations. Hence, the current study is intended to evaluate the presence and abundance of microplastics occurring in sewage treatment plants in India. The samples were processed through digestion and density separation, followed by microscopic and polymer identification through Fourier transform infrared spectroscopy. Also, different wastewater parameters were studied to analyze their influence. High microplastic concentrations were detected in the influent (1860 ± 265 MPs/L), which reduced by > 90%, to around 148 ± 51 MPs/L in the effluent. The concentration of microplastics in sewage sludge was 830 MPs/kg. The prominent plastic types identified include low-density polyethylene, polypropylene, polyurethane, polyvinyl chloride, and rayon. The smaller particles prevail in the effluent, releasing around 30 billion particles per day to the environment. This suggests that the current STP is efficient in removing the majority of the particles, but considerations are needed to avoid the ecological risks associated.
Journal Article
Water and wastewater treatment : a guide for the nonengineering professional
\"Designed to meet the information needs of professionals without an engineering background, this book describes and explains in simple, non-mathematical terms the unit processes used to treat both drinking water and wastewater. The text presents each unit process, states what function(s) it performs, illustrates what equipment it uses, and explains its role in the process of purifying or cleaning water. Now featuring summary sections, each chapter in this second edition has been fully updated and revised to present the latest regulatory and technological advancements as well as new drinking and wastewater regulatory requirements\"-- Provided by publisher.
Book
Free-living bacteria and potential bacterial pathogens in sewage treatment plants
To comprehensively understand the profile of free-living bacteria and potential bacterial pathogens in sewage treatment plants (STPs), this study applied high-throughput sequencing-based metagenomics approaches to investigate the effects of activated sludge (AS) treatment process and ultraviolet (UV) disinfection on the community of bacterial pathogens in two full-scale STPs. A total of 23 bacterial genera were identified as free-living bacteria, and 243 species/OTU97% were identified as potential bacterial pathogens, 6 of which were confidently detected in the STPs (with the total abundances ranging from 0.02 to 14.19%). Both diversity and relative abundance of the detected bacterial pathogens decreased obviously after AS treatment process (p < 0.05), and increased slightly after sedimentation (p < 0.05). UV disinfection shows no obvious effects on the total relative abundance of the free-living pathogenic bacteria in sewage. Although large amounts of the particle-bound pathogens were eliminated through the sewage treatment process, the STPs could not effectively remove the free-living bacterial pathogens, and some pathogenic bacteria (e.g., Pseudomonas aeruginosa) present in the effluent had higher relative abundance after UV disinfection. Overall, the results extend our knowledge regarding the community of potential pathogens (especially free-living pathogens) in STPs.
Journal Article
Prediction of effluent quality in ICEAS-sequential batch reactor using feedforward artificial neural network
It is highly essential that municipal wastewater is treated before its discharge and reuse in order to meet the standard requirements for safe marine life and for farming and industries. It is beneficial to use reclaimed water, since availability of fresh water is inadequate. An investigation was conducted on the Jamnagar Municipal Corporation Sewage Treatment Plant (JMC-STP) to develop a feedforward artificial neural network (FF-ANN) model. It is an alternate for the modelling/ prediction of JMC-STP to circumvent over the versatile physical, chemical, and biological treatment process simulations. The models were developed to predict effluent quality parameters through influent characteristics. The parameters are pH, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total Kjeldahl nitrogen (TKN), ammonium nitrogen (AN) and total phosphorus (TP). The correlation coefficient RTRAINING and RALL were calculated for all parametric models. The MAD (mean absolute deviation), MSE (mean square error), RMSE (root mean square error) and MAPE (mean absolute percentage error) were evaluated for FF-ANN models. This proves to be a useful tool for the plant management to optimize the treatment quality as it enhances the performance and reliability of the plant. The simulation results were validated through the measured values.
Journal Article