Urbanization and greenhouse gas emissions from municipal wastewater in coastal provinces of China: Spatiotemporal patterns, driving factors, and mitigation strategies.

Coastal cities, as hubs of social and economic activity, have witnessed rapid urbanization and population growth. This study explores the transformative changes in urban municipal wastewater treatment practices and their profound implications for greenhouse gas (GHG) emissions in Chinese coastal provinces. The approach employed in this study integrates comprehensive data analysis with statistical modeling to elucidate the complex interplay between urbanization, wastewater treatment practices, and GHG emissions. Results reveal a substantial surge in GHG emissions from coastal wastewater treatment, rising from 3367.1 Gg CO2e/yr in 1990-23644.8 Gg CO2e/yr in 2019. Spatially, the top 20 cities contribute 56.0% of emissions, with hotspots in the Bohai Sea Region, Yangtze River Delta, and Pearl River Delta. Initially dominated by emissions from untreated wastewater, post-2004, GHG emissions from treatment processes became the primary source, tied to electricity use. Growing population and urbanization rates escalated wastewater discharge, intensifying GHG emissions. From 1990 to 2019, average GHG intensity ranged between 320.5 and 676.6 g CO2e/m3 wastewater, with an annual increase of 12.3 g CO2e/m3. GHG intensity variations relate to the wastewater treatment rate, impacting CH4, N2O, and CO2 emissions, underscoring the need for targeted strategies to mitigate environmental impact.

Bacterial community and filamentous population of industrial wastewater treatment plants in Belgium.

The discharge of industrial water requires the removal of its pollutants, where biological wastewater treatment plants (WWTPs) are the most used systems. Biological WWTPs make use of activated sludge (AS), where bacteria are responsible for the removal of pollutants. However, our knowledge of the microbial communities of industrial plants is limited. Understanding the microbial population is essential to provide solutions to industrial problems such as bulking. The aim of this study was to identify at a high taxonomic resolution the bacterial population of 29 industrial WWTPs using 16S rRNA amplicon sequencing. Our results revealed that the main functional groups were dominated by Thauera and Zoogloea within denitrifiers, Dechloromonas in phosphate-accumulating organisms, and Defluviicoccus in glycogen-accumulating organisms. The activated sludge characterization indicated that 59% of the industrial plants suffered from bulking sludge, with DSVI values of up to 448 mL g-1. From the bulking cases, 72% corresponded to filamentous bulking with Thiothrix as the most abundant filament; meanwhile, the other 28% corresponded to viscous bulking sludge in which Zoogloea was the most abundant genus. Furthermore, the bacterial population did not share a core of taxa across all industrial plants. However, 20 genera were present in at least 50% of the plants comprising the general core, including Thauera, Ca. Competibacter, and several undescribed microorganisms. Moreover, statistical analysis revealed that wastewater salinity strongly affected the microbial richness of the industrial plants. The bacterial population across industrial plants differed considerably from each other, resulting in unique microbial communities that are attributed to the specificity of their wastewaters. KEY POINTS: • The general core taxa of industrial plants were mostly made up of undescribed bacterial genera. • Filamentous bacteria constituted on average 4.1% read abundance of the industrial WWTPs. • Viscous bulking remains a significant type of bulking within industrial WWTPs.

Pilot-scale performance of gravity-driven ultra-high flux fabric membrane systems for removing small-sized microplastics in wastewater treatment plant effluents.

The ubiquitous nature and environmental impacts of microplastic particles and fibers demand effective solutions to remove such micropollutants from sizable point sources, including wastewater treatment plants and road runoff facilities. While advanced methods, e.g., microfiltration and ultrafiltration, have shown high removal efficiencies of small-sized microplastics (<150 µm), the low flux encountered in these systems implies high operation costs and makes them less effective in high-capacity wastewater facilities. The issue presents new opportunities for developing cheap high-flux membrane systems, deployable in low-to high-income economies, to remove small-sized microplastic and nanoplastics in wastewater. Here, we report on developing an ultra-high flux gravity-driven fabric membrane system, assessed through a laboratory-scale filtration and large-scale performance in an actual wastewater treatment plant (WWTP). The method followed a carefully designed water sampling, pre-treatment protocol, and analytical measurements involving Fourier transform infrared (FTIR) spectroscopy and laser direct infrared (LDIR) imaging. The result shows that the ultra-high flux (permeance = 550,000 L/m2h⋅bar) fabric membrane system can effectively remove small-sized microplastics (10-300 µm) in the secondary effluent of an actual WWTP at high efficiency greater than 96 %. The pilot system demonstrated a continuous treatment capacity of 300,000 L/day through a 1 m2 surface area disc, with steady removal rates of microplastics. These findings demonstrate the practical, cheap, and sustainable removal of small-sized microplastics in wastewater treatment plants, and their potential value for other large-scale point sources, e.g., stormwater treatment facilities.

Nutrient recovery from wastewater for hydroponic systems: A comparative analysis of fertilizer demand, recovery products, and supply potential of WWTPs.

Nutrient recovery from wastewater treatment plants (WWTPs) for hydroponic cultivation holds promise for closing the nutrient loop and meeting rising food demands. However, most studies focus on solid products for soil-based agriculture, thus raising questions about their suitability for hydroponics. In this study, we address these questions by performing the first in-depth assessment of the extent to which state-of-the-art nutrient recovery processes can generate useful products for hydroponic application. Our results indicate that less than 11.5% of the required nutrients for crops grown hydroponically can currently be recovered. Potassium nitrate (KNO3), calcium nitrate (Ca(NO3)2), and magnesium sulfate (MgSO4), constituting over 75% of the total nutrient demand for hydroponics, cannot be recovered in appropriate form due to their high solubility, hindering their separated recovery from wastewater. To overcome this challenge, we outline a novel nutrient recovery approach that emphasizes the generation of multi-nutrient concentrates specifically designed to meet the requirements of hydroponic cultivation. Based on a theoretical assessment of nutrient and contaminant flows in a typical municipal WWTP, utilizing a steady-state model, we estimated that this novel approach could potentially supply up to 56% of the nutrient requirements of hydroponic systems. Finally, we outline fundamental design requirements for nutrient recovery systems based on this new approach. Achieving these nutrient recovery potentials could be technically feasible through a combination of activated sludge processes for nitrification, membrane-based desalination processes, and selective removal of interfering NaCl. However, given the limited investigation into such treatment trains, further research is essential to explore viable system designs for effective nutrient recovery for hydroponics.

The potential for water recovery from urban waste water - The perspective of urban waste water treatment plant operators in Poland.

Water recovery from waste water has become an essential element of the circular economy in the Baltic Sea region. However, there is little data on the possibility of using water recovered from urban waste water. A survey was conducted to learn the opinions of Poland waste water treatment plant operators. They were asked whether they recovered water for internal or external needs. Respondents indicated opportunities and barriers in this activity. The opinions of 107 operators show that work is underway on closing internal circuits in urban WWTPs. These solutions are technically relatively easy to implement and show measurable benefits (i.e., saving drinking water). However, water recovery for external purposes is rare and is at a very early stage. Despite this, the potential is significant, although many financial, organizational, technical, and mental barriers exist. The most critical challenge is the safe use of reclaimed water and the cost-effectiveness of the solutions. The survey also shows a need for education and involvement of the public.

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.

Effect of FeCl3 concentration in chemically enhanced primary treatment on the performance of a conventional wastewater treatment plant. A case study.

The effect of coagulant dosage in a chemically enhanced primary treatment (CEPT) on the performance of a conventional wastewater treatment plant (WWTP) has been investigated. Lab-scale experiments simulations were carried out in order to evaluate the effect of coagulant addition on the primary settling performance. In these experiments, FeCl3 was used as coagulant. Later, the WWTP was theoretically simulated using a commercial software (WEST®) to evaluate the effect of coagulation/flocculation on the global system, based on the results obtained at lab-scale. According to these results, the CEPT modifies the organic matter balance in the WWTP, decreasing the contribution of readily (SS) and slowly (XS) biodegradable fractions of COD to the aerobic biological process up to 27.3% and 80.8%, respectively, for a dosage of FeCl3 of 24 mg L-1. Consequently, total suspended solids in the aerobic reactor and the secondary purged sludge decreased up to 33% and 13%, respectively. However, the influence on effluent quality was negligible. On the contrary, suspended solids concentration in the sludge to be treated by anaerobic digestion increased, mainly regarding the Ss and Xs fractions, which caused an 8.1% increase in biogas production potential, with approximately 60% of CH4 concentration.

Source apportionment and specific-source-site risk of quinolone antibiotics for effluent-receiving urban rivers and groundwater in a city, China.

There is a large surface-groundwater exchange downstream of wastewater treatment plants (WWTPs), and antibiotics upstream may influence sites downstream of rivers. Thus, samples from 9 effluent-receiving urban rivers (ERURs) and 12 groundwater sites were collected in Shijiazhuang City in December 2020 and April 2021. For ERURs, 8 out of 13 target quinolone antibiotics (QNs) were detected, and the total concentration of QNs in December and April were 100.6-4,398 ng/L and 8.02-2,476 ng/L, respectively. For groundwater, all target QNs were detected, and the total QNs concentration was 1.09-23.03 ng/L for December and 4.54-170.3 ng/L for April. The distribution of QNs was dissimilar between ERURs and groundwater. Most QN concentrations were weakly correlated with land use types in the system. The results of a positive matrix factorization model (PMF) indicated four potential sources of QNs in both ERURs and groundwater, and WWTP effluents were the main source of QNs. From December to April, the contribution of WWTP effluents and agricultural emissions increased, while livestock activities decreased. Singular value decomposition (SVD) results showed that the spatial variation of most QNs was mainly contributed by sites downstream (7.09%-88.86%) of ERURs. Then, a new method that combined the results of SVD and PMF was developed for a specific-source-site risk quotient (SRQ), and the SRQ for QNs was at high level, especially for the sites downstream of WWTPs. Regarding temporal variation, the SRQ for WWTP effluents, aquaculture, and agricultural emissions increased. Therefore, in order to control the antibiotic pollution, more attention should be paid to WWTP effluents, aquaculture, and agricultural emission sources for the benefit of sites downstream of WWTPs.

Microplastic emission trends in Turkish primary and secondary municipal wastewater treatment plant effluents discharged into the Sea of Marmara and Black Sea.

Wastewater Treatment Plants (WWTPs) are recognized as one of the primary sources of microplastics, a class of contaminants that has lately gained attention. The quantity of MP that WWTPs release into the environment depends on several factors, including the treatment type, season, and population serviced. MP abundance and characterization were explored in 15 WWTP effluent waters, 9 discharged to the Black Sea from Türkiye and 6 to the Marmara Sea, with varying population densities and treatment methods. The mean MP abundance in primary treatment WWTPs (76.25 ± 49.20 MP L-1) was found to be substantially greater than that in secondary treatment WWTPs (20.57 ± 21.56 MP L-1) (p<0.05). MPs in WWTP effluent waters showed significant seasonal and spatial differences (Two Way ANOVA, Tukey, p<0.05). However, no positive correlation was detected between the population serviced and MP abundance in effluent waters. While the fiber was the dominant shape (49.5%) among MPs in effluent waters, ≈80% of the length was <1000 µm. MPs are classified into polymer types as follows: polyethylene terephthalate (34.9%) > polypropylene (32.4%) > polyethylene (19.9%) > polyamide (11%) > polystyrene (1.2%) > polyvinyl chloride (0.6%). With effluent waters from the WWTPs tested, we calculated that 1.24x1010 daily MPs are discharged into the Black Sea while 4.95x1010 MPs are into the Marmara Sea, for a combined annual discharge of 2.26x1013 MPs highlighting that WWTPs are key contributors of MP in Turkish coastal waters.

Highly socially vulnerable communities exhibit disproportionately increased viral loads as measured in community wastewater.

Wastewater surveillance has proven to be a useful tool for evidence-based epidemiology in the fight against the SARS-CoV-2 virus. It is particularly useful at the population level where acquisition of individual test samples may be time or cost-prohibitive. Wastewater surveillance for SARS-CoV-2 has typically been performed at wastewater treatment plants; however, this study was designed to sample on a local level to monitor the spread of the virus among three communities with distinct social vulnerability indices in Shreveport, Louisiana, located in a socially vulnerable region of the United States. Twice-monthly grab samples were collected from September 30, 2020, to March 23, 2021, during the Beta wave of the pandemic. The goals of the study were to examine whether: 1) concentrations of SARS-CoV-2 RNA in wastewater varied with social vulnerability indices and, 2) the time lag of spikes differed during wastewater monitoring in the distinct communities. The size of the population contributing to each sample was assessed via the quantification of the pepper mild mottle virus (PMMoV), which was significantly higher in the less socially vulnerable community. We found that the communities with higher social vulnerability exhibited greater viral loads as assessed by wastewater when normalized with PMMoV (Kruskal-Wallis, p < 0.05). The timing of the spread of the virus through the three communities appeared to be similar. These results suggest that interconnected communities within a municipality experienced the spread of the SARS-CoV-2 virus at similar times, but areas of high social vulnerability experienced more intense wastewater viral loads.

Environmental metabolomics uncovers oxidative stress, amino acid dysregulation, and energy impairment in Daphnia magna with exposure to industrial effluents.

Anthropogenic activities are regarded as point sources of pollution entering freshwater bodies worldwide. With over 350,000 chemicals used in manufacturing, wastewater treatment and industrial effluents are comprised of complex mixtures of organic and inorganic pollutants of known and unknown origins. Consequently, their combined toxicity and mode of action are not well understood in aquatic organisms such as Daphnia magna. In this study, effluent samples from wastewater treatment and industrial sectors were used to examine molecular-level perturbations to the polar metabolic profile of D. magna. To determine if the industrial sector and/or the effluent chemistries played a role in the observed biochemical responses, Daphnia were acutely (48 h) exposed to undiluted (100%) and diluted (10, 25, and 50%) effluent samples. Endogenous metabolites were extracted from single daphnids and analyzed using targeted mass spectrometry-based metabolomics. The metabolic profile of Daphnia exposed to effluent samples resulted in significant separation compared to the unexposed controls. Linear regression analysis determined that no single pollutant detected in the effluents was significantly correlated with the responses of metabolites. Significant perturbations were uncovered across many classes of metabolites (amino acids, nucleosides, nucleotides, polyamines, and their derivatives) which serve as intermediates in keystone biochemical processes. The combined metabolic responses are consistent with oxidative stress, disruptions to energy metabolism, and protein dysregulation which were identified through biochemical pathway analysis. These results provide insight into the molecular processes driving stress responses in D. magna. Overall, we determined that the metabolic profile of Daphnia could not be predicted by the chemical composition of environmentally relevant mixtures. The findings of this study demonstrate the advantage of metabolomics in conjunction with chemical analyses to assess the interactions of industrial effluents. This work further demonstrates the ability of environmental metabolomics to characterize molecular-level perturbations in aquatic organisms exposed to complex chemical mixtures directly.

Condition-Based Failure-Free Time Estimation of a Pump.

Reliable and continuous operation of the equipment is expected in the wastewater treatment plant, as any perturbations can lead to environmental pollution and the need to pay penalties. Optimization and minimization of operating costs of the pump station cannot, therefore, lead to a reduction in reliability but rather should be based on preventive works, the necessity of which should be foreseen. The purpose of this paper is to develop an accurate model to predict a pump's mean time to failure, allowing for rational planning of maintenance. The pumps operate under the supervision of the automatic control system and SCADA, which is the source of historical data on pump operation parameters. This enables the research and development of various methods and algorithms for optimizing service activities. In this case, a multiple linear regression model is developed to describe the impact of historical data on pump operation for pump maintenance. In the literature, the least squares method is used to estimate unknown regression coefficients for this data. The original value of the paper is the application of the genetic algorithm to estimate coefficient values of the multiple linear regression model of failure-free time of the pump. Necessary analysis and simulations are performed on the data collected for submersible pumps in a sewage pumping station. As a result, an improvement in the adequacy of the presented model was identified.

Semi-Supervised Anomaly Detection of Dissolved Oxygen Sensor in Wastewater Treatment Plants.

As the world progresses toward a digitally connected and sustainable future, the integration of semi-supervised anomaly detection in wastewater treatment processes (WWTPs) promises to become an essential tool in preserving water resources and assuring the continuous effectiveness of plants. When these complex and dynamic systems are coupled with limited historical anomaly data or complex anomalies, it is crucial to have powerful tools capable of detecting subtle deviations from normal behavior to enable the early detection of equipment malfunctions. To address this challenge, in this study, we analyzed five semi-supervised machine learning techniques (SSLs) such as Isolation Forest (IF), Local Outlier Factor (LOF), One-Class Support Vector Machine (OCSVM), Multilayer Perceptron Autoencoder (MLP-AE), and Convolutional Autoencoder (Conv-AE) for detecting different anomalies (complete, concurrent, and complex) of the Dissolved Oxygen (DO) sensor and aeration valve in the WWTP. The best results are obtained in the case of Conv-AE algorithm, with an accuracy of 98.36 for complete faults, 97.81% for concurrent faults, and 98.64% for complex faults (a combination of incipient and concurrent faults). Additionally, we developed an anomaly detection system for the most effective semi-supervised technique, which can provide the detection of delay time and generate a fault alarm for each considered anomaly.

Purification performance from bypass ecological treatment systems treating WWTPs effluents and improvement of water quality in receiving rivers: A case study in southern China.

Effluents from wastewater treatment plants (WWTPs) is the main source of pollution in rivers in developing countries. In this case study, three bypass ecological treatment systems along urban rivers achieved high removal efficiencies for chemical oxygen demand (COD; 55.7-64.0%), ammonium N (NH4+-N; 63.1-89.4%) and total phosphorous (TP; 27.6-76.7%). 16 S rRNA gene sequencing analysis confirmed that Proteobacteria was the main bacterial phylum (44.4%) in the ecological treatment system, and members were enriched significantly in the non-aeration area (59.3%). The relative abundance of Nitrospirae was highest in the inflow area (25.0%), but restrained in the non-aeration area (5.7%). 18 S rRNA gene annotation results indicated that phylum Rotifer was gradually inhibited with the direction of water flow and diffusion, while phylum Rhodophyta displayed the opposite trend. After implementation of bypass ecological treatment systems, receiving rivers were improved significantly from Grade Ⅴ to Ⅳ, and the biodiversity of zooplankton, zoobenthos and fish communities was greatly improved.

Elemental composition and microbial community differences between wastewater treatment plant effluent and local natural surface water: A Zhengzhou city study.

Wastewater treatment plant (WWTP) effluent is discharged into rivers as supplemental water, which may result in ecological risk. This study compares the element composition and microbial community of WWTP effluent and natural surface water (NSW) and reveals the potential ecological risk of WWTP effluent discharge. Twenty recently upgraded WWTPs and three relatively large reservoirs in Zhengzhou city, China, were selected. The contents of N, P, S, K, Ca, Mg, B, Si, Na, Fe, Mn, Co, Ni and Sn were significantly higher in WWTP effluent than in NSW, while those of Mo, V, Pb and Cd were significantly lower. There was no significant difference between WWTP effluent and NSW in terms of the element imbalance index (IMI) (representing the extent of imbalance of element proportions) relative to the class IV surface water quality standard (the control standard for most Chinese rivers). The macronutrient IMI relative to the Hoagland formula was significantly lower in WWTP effluent than in NSW, and WWTP effluent discharge could significantly lower this index in NSW; this may be an important cause of primary productivity explosion. The microbial diversity was significantly higher in WWTP effluent than in NSW. The predicted relative abundances of mobile genetic elements and oxidative-stress-tolerant phenotypes were significantly higher in WWTP effluent than in NSW, whereas the abundance of gram-negative phenotypes was significantly lower, and that of potential pathogenic phenotypes was slightly lower. The effluent from upgraded WWTPs exhibited a low risk of pathogen diffusion but a high risk of antibiotic resistance gene diffusion. The element composition and microbial community should be considered when evaluating the ecological risk of WWTP effluent discharge.

Tracking spatio-temporal distribution and transmission of antibiotic resistance in aquatic environments by using ESBL-producing Escherichia coli as an indicator.

Wastewater treatment plants (WWTPs) play an important role in the production, and transmission of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) as a convergence for human, animal, and environmental wastewater. The aim of this study was to investigate the spatio-temporal variation and influencing factors of ARB in different functional areas of the urban WWTP and the connecting rivers for 1-year monitoring using extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-Ec) as an indicator bacteria, and to study the transmission patterns of ARB in the aquatic environment. The results showed that ESBL-Ec isolates were identified from the WWTP (n = 219), including influent (n = 53), anaerobiotic tank (n = 40), aerobiotic tank (n = 36), activated sludge tank (n = 31), sludge thickner tank (n = 30), effluent (n = 16), and mudcake storage area (n = 13). The dehydration process can significantly remove the ESBL-Ec isolates; however, ESBL-Ec was still detected in samples collected from the effluent of the WWTP (37.0%). The detection rate of ESBL-Ec was significantly different across seasons (P < 0.05), and ambient temperature was negatively correlated with the detection rate of ESBL-Ec (P < 0.05). Furthermore, a high prevalence of ESBL-Ec isolates (29/187, 15.5%) was detected in samples collected from the river system. These findings emphasize that the high majority of ESBL-Ec in aquatic environments is alarming because it poses a significant threat to public health. Clonal transmission of ESBL-Ec isolates between the WWTP and rivers based on the spatio-temporal scale was observed by pulsed-field gel electrophoresis analysis, ST38 and ST69 ESBL-Ec clone were selected as prioritized isolates for antibiotic resistance monitoring in the aquatic environment. Further phylogenetic analysis showed human-associated (feces, blood) E. coli was the main source contributing to the presence of antibiotic resistance in aquatic environments. Longitudinal and targeted monitoring of ESBL-Ec in WWTPs and the development of effective wastewater disinfection strategies before effluent discharge from WWTPs are urgently required, to prevent and control the spread of antibiotic resistance in the environment.

Odour mapping and air quality analysis of a wastewater treatment plant at a seaside tourist area.

Although wastewater treatment plants (WWTPs) play a fundamental role in protecting the aquatic environment as they prevent organic matter, nutrients and other pollutants from reaching the natural ecosystems, near residential areas they can generate unpleasant smells and noise. The plant studied in the present work is in a seaside tourist area in the Valencian Community, Spain. The main aim was to detect any possible perceptible H2S concentrations from the WWTP by experimental measurement campaigns (including sensor readings and olfactometry measurements by two experts) plus mathematical modelling. After a thorough data analysis of the essential variables involved, such as wind speed, wind direction and H2S concentrations (the main odorant) and comparing their temporal patterns, it was found that the probability of affecting the residential area was highest from June to August before noon and in the late evening. The hourly H2S concentration, influent flow rate and temperature showed a positive correlation, the strongest (R2 = 0.89) being the relationship between the H2S concentration and influent flow rate. These two variables followed a similar daily pattern and indicated that H2S was emitted when influent wastewater was being pumped into the biological reactor. The H2S median concentration at the source of the emission was below 1393.865 µg/m3 (1 ppm), although concentrations 10 times higher were occasionally recorded. The observed H2S peak-to-mean ratio (1 min to 1 h of integration times) ranged from 1.15 to 16.03. This ratio and its attenuation with distance from the source depended on the atmospheric stability. Both H2S concentrations and variability were considerably reduced after submerging the inlet. The AERMOD modelling framework and applying the peak-to-mean ratio were used to map the peak H2S concentration and determine the best conditions to eliminate the unpleasant odour.

Small villages and their sanitary infrastructure-an unnoticed influence on water quantity and a threat to water quality in headwater catchments.

In rural catchments, villages often feature their own, separate urban water infrastructure, including combined sewer overflows (CSOs) or wastewater treatment plants (WWTPs). These point sources affect the water quantity and quality of the receiving low order streams. However, the extent of this impact is rarely monitored. We installed discharge and water quality measurements at the outlet of two small, neighbouring headwater catchments, one that includes a village, a WWTP, and two CSOs, while the other is predominantly influenced by agricultural activities. We also deployed electrical conductivity (EC) loggers at the CSOs to accurately detect discharge times. Discharge from the WWTP and CSOs led to higher peak flows and runoff coefficients during events. Less dilution of EC and increasing ammonium-N (NH4 - N) and ortho-phosphorus (oPO4 - P) concentrations indicate a significant contribution of poorly treated wastewater from the WWTP. During CSO events, water volumes and nutrient loads were clearly elevated, although concentrations were diluted, except for nitrite-N (NO2 - N) and particulate phosphorus (PP). Baseflow nitrate-N (NO3 - N) concentrations were diluted by the WWTP effluent, which led to considerably lower concentrations compared to the more agriculturally influenced stream. Concentrations of oPO4 - P, NH4 - N, and NO2 - N, which are most likely to originate from the WWTP, vary throughout the year but are always elevated. Our study shows the major and variable impact rural settlements can have on stream hydrology and water quality. Point sources should be monitored more closely to better understand the interaction of natural catchment responses and effects caused by sanitary infrastructure.

Vinylmethylsiloxanes in Municipal Wastewater Treatment Plant and Biosolid-Amended Soils: Their Distribution and Backbone/Vinyl Branch Degradation.

This study is the first to investigate the emission and environmental fate of one type of modified methylsiloxane with double-bond (vinyl) groups. During 2018-2020, 2,4,6-trimethyl-2,4,6-trivinylcyclotrisiloxane (V3), 2,4,6,8-tetramethyl-2,4,6,8-tetravinylcyclotetrasiloxane (V4), and 2,4,6,8,10-pentavinyl-2,4,6,8,10-pentamethylcyclopentasiloxane (V5) were found in aqueous (

Inhalable Antibiotic Resistome from Wastewater Treatment Plants to Urban Areas: Bacterial Hosts, Dissemination Risks, and Source Contributions.

Antibiotic resistance genes (ARGs) are commonly detected in the atmosphere, but questions remain regarding their sources and relative contributions, bacterial hosts, and corresponding human health risks. Here, we conducted a qPCR- and metagenomics-based investigation of inhalable fine particulate matter (PM2.5) at a large wastewater treatment plant (WWTP) and in the ambient air of Hong Kong, together with an in-depth analysis of published data of other potential sources in the area. PM2.5 was observed with increasing enrichment of total ARGs along the coastal-urban-WWTP gradient and clinically relevant ARGs commonly identified in urban and WWTP sites, illustrating anthropogenic impacts on the atmospheric accumulation of ARGs. With certain kinds of putative antibiotic-resistant pathogens detected in urban and WWTP PM2.5, a comparable proportion of ARGs that co-occurred with MGEs was found between the atmosphere and WWTP matrices. Despite similar emission rates of bacteria and ARGs within each WWTP matrix, about 11-13% of the bacteria and >57% of the relevant ARGs in urban and WWTP PM2.5 were attributable to WWTPs. Our study highlights the importance of WWTPs in disseminating bacteria and ARGs to the ambient air from a quantitative perspective and, thus, the need to control potential sources of inhalation exposure to protect the health of urban populations.