Isolation and genome-wide analysis of the novel Acinetobacter baumannii bacteriophage vB_AbaM_AB3P2.

A lytic Acinetobacter baumannii phage, isolate vB_AbaM_AB3P2, was isolated from a sewage treatment plant in China. A. baumannii phage vB_AbaM_AB3P2 has a dsDNA genome that is 44,824 bp in length with a G + C content of 37.75%. Ninety-six open reading frames were identified, and no genes for antibiotic resistance or virulence factors were found. Genomic and phylogenetic analysis of this phage revealed that it represents a new species in the genus Obolenskvirus. Phage vB_AbaM_AB3P2 has a short latent period (10 min) and high stability at 30-70°C and pH 2-10 and is potentially useful for controlling multi-drug-resistant A. baumannii.

Effects of aeration control strategies on nitrous oxide emissions in alternating anoxic-oxic sequencing batch reactor systems.

Reducing N2O emissions is key to controlling greenhouse gases (GHG) in wastewater treatment plants (WWTPs). Although studies have examined the effects of dissolved oxygen (DO) on N2O emissions during nitrogen removal, the precise effects of aeration rate remain unclear. This study aimed to fill this research gap by investigating the influence of dynamic aeration rates on N2O emissions in an alternating anoxic-oxic sequencing batch reactor system. The emergence of DO breakthrough points indicated that the conversion of ammonia nitrogen to nitrite and the release of N2O were nearly complete. Approximately 91.73 ± 3.35% of N2O was released between the start of aeration and the DO breakthrough point. Compared to a fixed aeration rate, dynamically adjusting the aeration rates could reduce N2O production by up to 48.6%. Structural equation modeling revealed that aeration rate and total nitrogen directly or indirectly had significant effects on the N2O production. A novel regression model was developed to estimate N2O production based on energy consumption (aeration flux), water quality (total nitrogen), and GHG emissions (N2O). This study emphasizes the potential of optimizing aeration strategies in WWTPs to significantly reduce GHG and improve environmental sustainability.

Effect of the residual levofloxacin on hydroponic vegetables with sewage treatment plant tailwater: Microbial community, discharge risk and control strategy.

Tailwater-based hydroponic vegetable is a promising strategy for domestic wastewater recycling. However, the effect of residual antibiotics on the hydroponic vegetable system and the relation between hydroponic culture parameters and the residual water quality are still unclear. Here, the typical antibiotic Levofloxacin (LVFX) was employed, and the effect of LVFX (5 mg/L) on the residual water quality, plant growth and microbial community of water spinach hydroponic culture system were investigated under different hydraulic residence times (HRT). Obvious toxic effects on water spinach were observed, and the highest removal rate of LVFX (about 6 %) and TN (25.67±1.43 %) was observed when HRT was 7 days. Hydroponic culture increased the microbial abundance, diversity, and microbial community stability. To optimize the hydroponic culture, actual sewage plant tailwater spiked with 20 µg/L LVFX, along with three common planting substrates (sponge, ceramsite, and activated carbon) were used for the hydroponic culture of lettuce (seasonal reasons). The inhibition effect of LVFX on the removal of NO3--N and TN was observed even as the LVFX concentration decreased significantly (from 14.62 ± 0.44 µg/L to 0.65 ± 0.07 µg/L). The best growth situation of lettuce and removal rates of NH4+-N, NO3--N, TN, especially LVFX (up to 95.65 ± 0.54 %) were observed in the activated carbon treated group. The overall results indicate the negative effect of residual antibiotics on the hydroponic vegetable systems, and adding activated carbon as substrate is an effective strategy for supporting plant growth and controlling discharged risk.

A pilot-scale assessment of five common weeds in the sustainable treatment of sewage utilizing SHEFROL®, with prospects of a closed-loop biorefinery.

Relative efficacy of five common weeds-of the kind that are either rooted in soil or which freely float over water-was assessed in rapid, effective and sustainable treatment of sewage at pilot plant scale in the recently developed and patented SHEFROL® bioreactors. The plants were utilized in a unit of capacity 12,000 liters/day (LPD) which, after two years of use, was enlarged to handle 40,000 LPD of sewage. It was then further expanded after an year to treat 57,000 LPD. All the five weeds, of which none has previously been tested in a pilot-scale SHEFROL, were able to foster highly efficient primary treatment (in terms of suspended and total solids) and secondary treatment (in terms of BOD and COD) to levels exceeding 85% in most cases. Additionally, the weeds also helped in achieving significant tertiary treatment. At different hydraulic retention times, and at steady state, the five weeds achieved treatment of BOD, COD, suspended solids, nitrogen, phosphorous, copper, nickel, zinc, and manganese in the ranges, 80-95, 79-91, 82-95, 61-71, 51-73, 37-43, 30-38, 39-47, and 27-35%, respectively. It all occurred in a single process step and without the use of any machine or chemical. This made the system not only simple and inexpensive to install but also to maintain. Over continuous long-term operation for four years, the system was seen to be very robust as it was able to handle wide variations in the volumes and characteristics of sewage, as well as absorb shock loads without compromising the reactor performance. The sustainability of the system can be further enhanced by upgrading it to a circular biorefinery. Energy sources in the form of volatile fatty acids (VFAs) can be extracted from the weeds removed from SHEFROL and then the weeds can be converted into organic fertilizer using high-rate vermireactors recently developed by the authors.

A novel and inexpensive, yet very efficient sewage treatment system is presented.The versatility and robustness of the system has been assessed at pilot plant scale for several years.The long-term continuous studies establish the efficacy of five common weeds­not hitherto explored at pilot plant level­which can serve as the main bioagent(s) in the sewage treatment system.The system has the potential of being transformed in to a closed-loop-no-waste biorefinery.

A Wooden Carbon-Based Photocatalyst for Water Treatment.

Due to a large number of harmful chemicals flowing into the water source in production and life, the water quality deteriorates, and the use value of water is reduced or lost. Biochar has a strong physical adsorption effect, but it can only separate pollutants from water and cannot eliminate pollutants fundamentally. Photocatalytic degradation technology using photocatalysts uses chemical methods to degrade or mineralize organic pollutants, but it is difficult to recover and reuse. Woody biomass has the advantages of huge reserves, convenient access and a low price. Processing woody biomass into biochar and then combining it with photocatalysts has played a complementary role. In this paper, the shortcomings of a photocatalyst and biochar in water treatment are introduced, respectively, and the advantages of a woody biochar-based photocatalyst made by combining them are summarized. The preparation and assembly methods of the woody biochar-based photocatalyst starting from the preparation of biochar are listed, and the water treatment efficiency of the woody biochar-based photocatalyst using different photocatalysts is listed. Finally, the future development of the woody biochar-based photocatalyst is summarized and prospected.

Comparative assessment of microbiome and resistome of influent and effluent of sewage treatment plant and common effluent treatment plant located in Delhi, India using shotgun approach.

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%-16%), aminoglycosides (7%-9%), multi-drug (5%-9%), and rifampin (3%-9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance.

Continuous co-treatment of mine drainage with municipal wastewater.

Acid mine drainage (AMD) and municipal wastewater (MWW) are commonly co-occurring waste streams in mining regions. Co-treating AMD at existing wastewater facilities represents an innovative solution for simultaneous AMD reclamation and improved MWW treatment. However, unknowns related to biological processes and continuous treatment performance block full-scale use. The overarching goal of this work was to address questions related to efficacy and performance of continuous processing of AMD in a biological MWW treatment system. Synthetic AMD was co-treated with synthetic MWW in a continuously-operating bench-scale sequencing batch reactor (SBR). SBRs treated MWW with two strengths of AMD (91 and 720 mg/L as CaCO3 Acidity) to capture the variations of coal AMD chemistry and strength observed in the field. Each co-treatment phases lasted 40+ days, during which clarified effluent and settled sludge quality was routinely monitored to determine impacts of co-treatment relative to conventional MWW treatment performance. Co-treatment produced effluent that met key standards for secondary treatment including biochemical oxygen demand (BOD) < 5 mg/L, total suspended solids (TSS) < 20 mg/L, and pH ∼7.0. Addition of AMD also improved treatment performance, increasing Phosphate (PO4) removal by >60% and pathogen removal by an order of magnitude. Furthermore, AMD co-treatment did not exhibit any major impacts on the overall diversity of the wastewater microbial community. Co-treatment sludge had slightly higher settleability and a lower bound water content, but notable changes in sludge morphology was observed. This study demonstrates co-treatment allows for continuous mitigation of AMD without adversely impacting MWW treatment performance in conventional biological MWW processes.

Tackling data challenges in forecasting effluent characteristics of wastewater treatment plants.

In wastewater treatment plants (WWTPs), the stochastic nature of influent wastewater and operational and weather conditions cause fluctuations in effluent quality. Data-driven models can forecast effluent quality a few hours ahead as a response to the influent characteristics, providing enough time to adjust system operations and avoid undesired consequences. However, existing data for training models are often incomplete and contain missing values. On the other hand, collecting additional data by installing new sensors is costly. The trade-off between using existing incomplete data and collecting costly new data results in three data challenges faced when developing data-driven WWTP effluent forecasters. These challenges are to determine important variables to be measured, the minimum number of required data instances, and the maximum percentage of tolerable missing values that do not impede the development of an accurate model. As these issues are not discussed in previous studies, in this research, for the first time, a comprehensive analysis is done to provide answers to these challenges. Another issue that arises in all data-driven modeling is how to select an appropriate forecasting model. This paper addresses these issues by first testing nine machine learning models on data collected from three wastewater treatment plants located in Iran, Australia, and Spain. The most accurate forecaster, Bayesian network, was then used to address the articulated challenges. Key variables in forecasting effluent characteristics were flow rate, total suspended solids, electrical conductivity, phosphorus compounds, wastewater temperature, and air temperature. A minimum of 250 samples was needed during the model training to achieve a great reduction in the forecasting error. Moreover, a steep increase in the error was observed should the portion of missing values exceed 10%. The results assist plant managers in estimating the necessary data collection effort to obtain an accurate forecaster, contributing to the quality of the effluent.

Preparation of smart magnetic fluids and application in sewage treatment: Copper adsorption, kinetic and isotherm study.

The effective removal of heavy metal ions from sewage remains a critical issue, and applying the operability of magnetic materials to large volume wastewater treatment has been a significant challenge. In this paper, metal ions adsorption induced aggregation strategy is proposed to solve this contradiction. The intelligent magnetic fluid designed in this study is a well-dispersed fluid state when treating sewage, and can efficiently adsorb heavy metal ions in wastewater with high adsorption capacity and ultra-fast adsorption kinetics. More importantly, after saturation of adsorption, the magnetic fluid will transform from a well-dispersed fluid state to an agglomeration state which is easy to precipitate and separate via external magnetic field. In a simple and effective way, the particles size of magnetic nanoparticles was precisely controlled by cellulose derivatives modification to obtain a stable magnetic fluid in water. The Freundlich model best described Cu2+ adsorption on magnetite nanoparticles, the correlation coefficients from the Cu2+ adsorption on the two magnetic fluids are 0.9554 and 0.9336, n are 1.868 and 2.117, revealing a favorable adsorption of Cu2+ onto magnetic fluids. The pseudo second-order model fitted the adsorption kinetic data better, the qe are 0.1948 and 0.1315 mmol/g and the R2 are 0.9999, indicating that the adsorption of Cu2+ onto the magnetic fluid was dominated by chemisorption. Moreover, the removal rate of Cu2+ in tap water and lake water was more than 97.1%, and the removal rate of large volume sewage was 81.7%. The synthetic magnetic fluid has high adsorption capacity, ultra-fast adsorption kinetics, reusability and easy separation, indicating its potential application for the removal of heavy metal ions from large-volume sewage.

Hybrid life-cycle and hierarchical archimedean copula analyses for identifying pathways of greenhouse gas mitigation in domestic sewage treatment systems.

Electricity consumption and anaerobic reactions cause direct and indirect greenhouse gas (GHG) emissions within domestic sewage treatment systems (DSTSs). GHG emissions in DSTSs were influenced by the sewage quantity and the efficacy of treatment technologies. To address combined effects of these variables, this study presented an approach for identifying pathways for GHG mitigation within the DSTSs of cities under climate change and socio-economic development, through combining life cycle analysis (LCA) and the Hierarchical Archimedean copula (HAC) methods. The approach was innovative in the following aspects: 1) quantifying the GHG emissions of the DSTSs; 2) identifying the correlations among temperature changes, socioeconomic development, and domestic sewage quantity, and 3) predicting the future fluctuations in GHG emissions from the DSTSs. The effectiveness of the proposed approach was validated through its application to an urban agglomeration in the Pearl River Delta (PRD), China. To identify the potentials of GHG mitigation in the DSTSs, two pathways (i.e., general and optimized) were proposed according to the different technical choices for establishing facilities from 2021 to 2030. The results indicated that GHG emissions from the DSTS in the PRD were [3.01, 4.96] Mt CO2eq in 2021, with substantial contributions from Shenzhen and Guangzhou. Moreover, GHG emissions from the sewage treatment facilities based on Anaerobic-Anoxic-Axic (AAO) technology were higher than those based on other technologies. Under the optimized pathway, GHG emissions, contributed by the technologies of Continuous Cycle Aeration System (CASS) and Oxidation Ditch (OD), were the lowest. Through the results of correlation analysis, the impact of socioeconomic development on domestic sewage quantities was more significant than that of climate change. Domestic sewage quantities in the cities of the PRD would increase by 4.10%-28.38%, 17.14%-26.01%, and 18.15%-26.50% from 2022 to 2030 under three Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. These findings demonstrated that the capacities of domestic sewage treatment facilities in most cities of the PRD should be substantially improved from 0.12 to 2.99 times between 2022 and 2030. Under the optimized pathway, the future GHG emissions of the CASS method would be the lowest, followed by the OD method.

Insights into the Origin of Activity Enhancement via Tuning Electronic Structure of Cu2O towards Electrocatalytic Ammonia Synthesis.

The insight of the activity phase and reaction mechanism is vital for developing high-performance ammonia synthesis electrocatalysts. In this study, the origin of the electronic-dependent activity for the model Cu2O catalyst toward ammonia electrosynthesis with nitrate was probed. The modulation of the electronic state and oxygen vacancy content of Cu2O was realized by doping with halogen elements (Cl, Br, I). The electrocatalytic experiments showed that the activity of the ammonia production depends strongly on the electronic states in Cu2O. With increased electronic state defects in Cu2O, the ammonia synthesis performance increased first and then decreased. The Cu2O/Br with electronic defects in the middle showed the highest ammonia yield of 11.4 g h-1 g-1 at -1.0 V (vs. RHE), indicating that the pattern of change in optimal ammonia activity is consistent with the phenomenon of volcano curves in reaction chemistry. This work highlights a promising route for designing NO3-RR to NH3 catalysts.

Study on the performance of biochar prepared from walnut shell and traditional graphene electrode plate in the treatment of domestic sewage in microbial fuel cells.

As a new pollutant treatment technology, microbial fuel cell (MFC) has a broad prospect. In this article, the devices assembled using walnut shells are named biochar-microbial fuel cell (B-MFC), and the devices assembled using graphene are named graphene-microbial fuel cell (G-MFC). Under the condition of an external resistance of 1,000 Ω, the B-MFC with biochar as the electrode plate can generate a voltage of up to 75.26 mV. The maximum power density is 76.61 mW/m2, and the total internal resistance is 3,117.09 Ω. The removal efficiency of B-MFC for ammonia nitrogen (NH3-N), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) was higher than that of G-MFC. The results of microbial analysis showed that there was more operational taxonomic unit (OTU) on the walnut shell biochar electrode plate. The final analysis of the two electrode materials using BET specific surface area testing method (BET) and scanning electron microscope (SEM) showed that the pore size of walnut shell biochar was smaller, the specific surface area was larger, and the pore distribution was smoother. The results show that using walnut shells to make electrode plates is an optional waste recycling method and an electrode plate with excellent development prospects.

Low-cost, reliable, and highly efficient removal of COD and total nitrogen from sewage using a sponge-filled trickling filter.

Development of low-cost and reliable reactors demanding minimal supervision is a need-of-the-hour for sewage treatment in rural areas. This study explores the performance of a multi-stage sponge-filled trickling filter (SPTF) for sewage treatment, employing polyethylene (PE) and polyurethane (PU) media. Chemical oxygen demand (COD) and nitrogen transformation were evaluated at hydraulic loading rates (HLRs) ranging from 2 to 6 m/d using synthetic sewage as influent. At influent COD of ∼350 mg/L, PU-SPTF and PE-SPTF achieved a COD removal of 97% across all HLRs with most of the removal occurring in the first segments. Operation of PE-SPTF at an HLR of 6 m/d caused substantial wash-out of biomass, while PU-SPTF retained biomass and achieved effluent COD < 10 mg/L even at HLR of 8-10 m/d. The maximum Total Nitrogen removal by PE-SPTF and PU-SPTF reactors was 93.56 ± 1.36 and 92.24 ± 0.66%, respectively, at an HLR of 6 m/d. Simultaneous removal of ammonia and nitrate was observed at all the HLRs in the first segment of both SPTFs indicating ANAMMOX activity. COD removal data, media depth, and HLRs were fitted (R2 > 0.99) to a first-order kinetic relationship. For a comparable COD removal, CO2 emission by PU-SPTF was 3.5% of that of an activated sludge system.

Directional Separation of Highly Reductive Electrons to the Reactive Center in a Magnetic S-Scheme ZnFe2O4/A-MoS2 Heterojunction for Enhanced Peroxymonosulfate Activation toward Pharmaceuticals and Personal Care Product Removal.

Pharmaceuticals and personal care products (PPCPs) are ubiquitous in sewage, adversely affecting ecosystems and human health. In this study, an S-scheme magnetic ZnFe2O4/ammoniated MoS2 (ZnFe2O4/A-MoS2) heterojunction as a visible-light-driven PMS activator for PPCP degradation was developed. ZnFe2O4/A-MoS2 achieves improved photocatalytic activity because the construction of S-scheme heterojunction promotes the separation of the highly reductive photogenerated electrons. The optimized photocatalyst (10%-ZnFe2O4/A-MoS2, 0.2 g/L) achieved 100% removal of 2 ppm carbamazepine (CBZ) within 2.5 min at a PMS dosage of 0.5 mM (initial pH 7.0). Mechanistic investigation revealed that the separated electrons to the ZnFe2O4 reactive center of the heterojunction facilitated PMS activation and generated SO4·- as the dominant reactive species for CBZ degradation. The system exhibited excellent practicability in various samples of actual sewage, where most sewage components negatively impacted CBZ degradation. Further, the chloride ions in high-salinity sewage could be activated to generate additional reactive chlorine species for PPCP degradation. The heterojunction possesses outstanding reusability and stability in treating various water conditions. This work provides mechanistic and practical perspectives in developing novel S-type heterojunctions for recalcitrant pollutant treatment.

De novo granulation of sewage-borne microorganisms: A proof of concept on cultivating aerobic granular sludge without activated sludge and effective enhanced biological phosphorus removal.

Long start-up periods for granulating activated sludge and concerns on granular stability are the bottlenecks reported during implementation of novel aerobic granular sludge (AGS) technology in municipal wastewater treatment plants. Here, de novo granulation of sewage-borne microorganisms without using activated sludge (AS) inoculum was investigated in bench-scale sequencing batch reactors (SBR). Data showed that formation of AGS from sewage-borne microorganisms was rapid and first granules appeared within one week. Granulation was indicated by appearance of biomass particles (size >0.12 mm), high biomass levels (∼8 g/L) and superior settling properties (SVI30 min: 30 mL/g). Granulation process involved distinct stages like formation of aggregates, retention of aggregates, and growth of millimetre sized granules. Simultaneous COD, nitrogen and phosphorous removal was established within 10 days of start-up in the SBR without using AS inoculum. However, phosphorus removal became stable after 50 days of start-up. Total nitrogen (TN) and total phosphorus (TP) removals of 92% and 70%, respectively, were achieved from real domestic wastewater. Furthermore, addition of granular activated carbon (GAC) had improved both granulation and biological nutrient removals. Interestingly, phosphorus removal became quite stable within 10 days of start-up in the SBR operated with GAC particles. TN and TP removals were found to be higher at >98% and >94%, respectively, in GAC-augmented SBR. Removal of ammonia and phosphorus were mediated by nitritation-denitritation and enhanced biological phosphorus removal (EBPR) pathways, respectively. The bacterial diversity of AGS was lower than that of sewage. Quantitative PCR indicated enrichment of ammonia oxidizing bacteria, denitrifying bacteria and polyphosphate accumulating organisms during granulation. De novo granulation of sewage-borne microorganisms is a promising approach for rapidly cultivating AGS and establishing biological nutrient removal in sewage treatment plants.

Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences.

Centralized vs. decentralized sewage treatment is one of the key issues in the planning of rural sewage treatment (RST) in China due to the country's diverse regional characteristics. There are very limited comprehensive evaluation models for selecting regionally suitable schemes and facilities, particularly for national or provisional scale planning. As a scenario-based multi-attribute decision-making (MADM) issue, this paper develops a novel RST suitability evaluation model by integrating the multi-attribute analytic hierarchy process (AHP) with the technique for order preference by similarity to an ideal solution (TOPSIS). The suitability evaluation model sets up 3 small-centralized and 4 decentralized RST facilities as candidates and includes 12 evaluation indicators that cover economic cost, life cycle environmental impacts, technical features and operations management. Eight generic scenarios are classified for Chinese rural areas based on differences in three major characteristic factors, i.e., population density (PD), the economic development level (EDL), and topographic slope (TS). The universal evaluation results show that a centralized sewage treatment scheme is more suitable for areas with a high PD/high EDL/low TS, while a decentralized scheme is more suitable for areas with a low PD/low EDL/high TS. Sensitivity analysis shows that in regions with a high PD/low EDL, the indicator weight of the construction investment cost in the model has a great influence on the facility suitability ranking. However, in regions with a high PD/high EDL, the ranking is the most sensitive to the indicator weights of the global warming potential and sewage treatment effect. Furthermore, as a spatial decision issue, an RST suitability map of Hunan Province in China is produced at the county level of resolution, and the map is generally consistent with our field knowledge of several counties in Hunan Province. The presented evaluation framework can be integrated into environmental decision support systems in the future to help local and central governments, water utilities, design institutes and other stakeholders scientifically plan RST projects.

Modeling and optimizing of an actual municipal sewage plant: A comparison of diverse multi-objective optimization methods.

The activated sludge process of an actual municipal sewage treatment plant was systematically modeled, calibrated, and verified in this study. Identified multi-objective optimization (MOO) methods were employed to optimize the process parameters of the validated model, and the optimal MOO algorithm was obtained by comparing Pareto solution sets. The optimization model consisted of three key evaluation indicators (objective functions), which are the average effluent quality (AEQ), overall cost index (OCI), and total volume (TV) of the biochemical tank, along with 12 more process parameters (decision variables). Three optimization algorithms, i.e., adaptive non-dominated sorting genetic algorithm III (ANSGA-III), non-dominated sorting genetic algorithm II (NSGA-II), and particle swarm algorithm (PSO), were adopted using MATLAB. The comparison of these algorithms demonstrated that the ANSGA-III algorithm had better Pareto solution sets under the triple objective optimization, and the effluent quality of COD, TN, NH4+-N, and TP after optimization decreased by 2.22, 0.47, 0.13, and 0.02 mg/L, respectively. Additionally, the simulated AEQ was reduced by 13% compared to the original effluent, and the OCI and TV decreased from 21,023 kWh d-1 and 17,065 m3 to 20,226 kWh d-1 and 16,530 m3, respectively. The reported ANSGA-III algorithm and the proposed multi-objective method have a promising ability for energy conservation, emission reduction, and upgrading of municipal sewage treatment plants.

Dissemination of antibiotic resistance genes through fecal sewage treatment facilities to the ecosystem in rural area.

Infection of antibiotic-resistant pathogens mostly occurs in rural areas. In this paper, the dissemination of antibiotic resistance genes (ARGs) through fecal sewage treatment facilities to the ecosystem in a typical rural area is investigated. Household three-chamber septic tanks (TCs), household biogas digesters (BDs), wastewater treatment plants (WWTPs), vegetable plots, water ponds, etc. Are taken into account. The relative abundance of ARGs in fecal sewage can be reduced by BDs and WWTPs by 80% and 60%, respectively. While TCs show no reduction ability for ARGs. Fast expectation-maximization microbial source tracking (FEAST) analysis revealed that TCs and BDs contribute a considerable percentage (15-22%) of ARGs to the surface water bodies (water ponds) in the rural area. Most ARGs tend to precipitate in the sediments of water bodies and stop moving downstream. Meanwhile, the immigration of microorganisms is more active than that of ARGs. The results provide scientific basic data for the management of fecal sewage and the controlling of ARGs in rural areas.

A unified modelling framework for type I (discrete) settling and rising of microplastics in primary sedimentation tanks.

Sewage treatment plants (STPs) are considered as a significant source of microplastic pollution into the terrestrial and aquatic environment. Existing observations suggest that primary treatment accounts for major microplastics removal in STPs, though with high variability due to the complex nature of the polymer compositions, abundance, and sizes in the incoming sewage. Here, we develop a unified modelling framework to simulate the Type I (or discrete) settling or rising behaviour of microplastics to predict their eventual fate in Primary Sedimentation Tank (PST). The model was developed as per the conventional design protocol for PST involving Stokes equation and modifications as per flow regime for settling of nylon and polystyrene microplastics. It was subsequently validated with independent column experiments for both settling (nylon and polystyrene) and rising (low-density polyethylene and polypropylene) microplastics in different size ranges. The validated model was then applied for multiple realistic scenarios of polymer compositions, relative abundance, and size distributions in the incoming sewage. The model predicts removals ranging from 12% to 94% for a mixture of microplastics in the size fraction 0-500 µm. Model simulations also suggest better microplastics removal with the integration of skimming in PST, and optimization of surface overflow velocity.

Environmental spreading of clinically relevant carbapenem-resistant gram-negative bacilli: the occurrence of blaKPC-or-NDM strains relates to local hospital activities.

BACKGROUND: Aquatic matrices impacted by sewage may shelter carbapenem-resistant (CR) Gram-negative bacilli (GNB) harboring resistance genes of public health concern. In this study, sewage treatment plants (STPs) servicing well-defined catchment areas were surveyed for the presence of CR-GNB bearing carbapenemase genes (blaKPC or blaNDM). RESULTS: A total of 325 CR-GNB were recovered from raw (RS) and treated (TS) sewage samples as well as from water body spots upstream (UW) and downstream (DW) from STPs. Klebsiella-Enterobacter (KE) group amounted to 116 isolates (35.7%). CR-KE isolates were recovered from TS, DW (35.7%) and RS samples (44.2%) (p = 0.001); but not from UW samples. KE isolates represented 65.8% of all blaKPC or blaNDM positive strains. The frequency of blaKPC-or-NDM strains was positively associated with the occurrence of district hospitals located near STPs, as well as with the number of hospitalizations and of sewer connections serviced by the STPs. blaKPC-or-NDM strains were recovered from ST samples in 7 out of 14 STPs, including four tertiary-level STPs; and from 6 out of 13 DW spots whose RS samples also had blaKPC-or-NDM strains. CONCLUSIONS: Clinically relevant GNB bearing blaKPC-or-NDM resist sewage treatments and spread into environmental aquatic matrices mainly from STPs impacted by hospital activities.