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Antibiotic resistance (AR) is a major global health concern, but current surveillance efforts primarily focus on healthcare settings, leaving a lack of understanding about AR across all sectors of the One Health approach. To bridge this gap, wastewater surveillance provides a cost-effective and efficient method for monitoring AR within a population. In this study, we implemented a surveillance program by monitoring the wastewater effluent from two large-scale municipal treatment plants situated in Isfahan, a central region of Iran. These treatment plants covered distinct catchment regions and served a combined population about two million of residents. Furthermore, the effect of physicochemical and microbial characteristics of wastewater effluent including biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), temperature, total coliforms and Escherichia coli concentration on the abundance of ARGs (blaCTX-M, tetW, sul1, cmlA, and ermB) and class 1 integron-integrase gene (intI1) were investigated. Sul1 and blaCTX-M were the most and least abundant ARGs in the two WWTPs, respectively. Principal Component Analysis showed that in both of the WWTPs all ARGs and intI1 gene abundance were positively correlated with effluent temperature, but all other effluent characteristics (BOD, COD, TSS, total coliforms and E. coli) showed no significant correlation with ARGs abundance. Temperature could affect the performance of conventional activated sludge process, which in turn could affect the abundance of ARGs. The results of this study suggest that other factors than BOD, COD and TSS may affect the ARGs abundance. The predicted AR could lead to development of effective interventions and policies to combat AR in the clinical settings. However, further research is needed to determine the relationship between the AR in wastewater and clinical settings as well as the effect of other influential factors on ARGs abundance.

Wastewater treatment plants release substantial amounts of microplastics (MPs) into the environment. Various models and scenarios have been developed to estimate the sources and concentrations of MPs released by effluents. However, no model has included wastewater from washing machines. This study aims to estimate, in three scenarios, the number of MPs that are released by Bucharest households into the municipal wastewater treatment plant. The highest number of MPs has been estimated to be emitted by washing machines from synthetic clothing. From the category of cosmetics, the highest number of particles per year is potentially generated by face and hand creams. It has been estimated that the effluent of the wastewater treatment plant contains 48–4251 MP L−1 for the three proposed scenarios. The study shows that the population of Bucharest can generate high numbers of MPs, even in the minimum scenario. However, the use of MPs is expected to decrease, due to implementation of European Union policies, responsible consumer behavior, effective plastic waste management, and improved detection and separation technologies. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) play direct and indirect roles in the emission of greenhouse gases (GHG) produced by biological processes and energy consumption, respectively. Nowadays, reducing GHG emission and the energy consumption of WWTPs are of interest. In this study, at first, the GHG emissions and energy consumption of the Mashhad WWTP (MLE and aerobic digestion process) were compared with energy self-sufficient WWTPs. In the next stage, four scenarios were developed to reduce GHG emissions and energy consumption. According to the results, energy consumption and GHG emissions in this WWTP is outside of the acceptable value. By changing aerobic digestion to anaerobic digestion, the energy consumption will decreases from 1 kWh/m3 to 0.58 kWh/m3, and the total amount of CO2 equivalent (CO2e-T) increases from 0.64 kg CO2e/m3 to 1.65 kg CO2e/m3. In order to reduce energy consumption and GHG emissions, anaerobic digester and CHP must be used together. This process leads to reduced energy consumption and GHG emissions by about 70% and 53% , respectively. The lowest (highest) GHG emissions will occur in MLE with anaerobic digester and CHP (without CHP). Based on this study, GHG emissions and energy consumption can be controlled by selecting a correct process for WWTPs.

Sewage sludge can be used as an organic amendment as long as it is ensured that there is no risk of environmental contamination or risk to public health. In this study, sewage sludge from two wastewater treatment plants (WWTPs) subjected to two disinfection and stabilization treatments [40% (mass/mass), calcium oxide, and calcium hydroxide] and their respective untreated sewage sludge were used. Three control treatments were also added: conventional farmyard manure (FYM), a nitrogen (N) mineral fertilizer (ammonium nitrate 34.5% N) applied at a rate of 50 kg N ha−1 (N50) (the same rate of all organic amendments), and an unfertilized control (N0), totaling nine treatments. Lettuce (Lactuca sativa L.) was cultivated in pots for two growing cycles. The dry matter yield (DMY) was higher in the N50 treatment (13.5 and 10.6 g plant−1 in the first and second growing cycles, respectively), followed by sewage sludge (10.8 to 12.4 and 8.4 to 8.7 g plant−1), FYM (8.5 and 7.2 g plant−1), and the control (7.7 and 6.0 g plant−1). The DMY was related to the N provided by the different treatments, assessed by the N and nitrate concentrations in tissues, N uptake, and apparent N recovery (ANR). Sewage sludge, due to its high N concentration and low carbon (C)/N ratio, mineralized rapidly, providing a significant amount of N to plants, as well as other nutrients, such as phosphorus (P) and boron (B). FYM, with a higher C/N ratio, provided less N to plants, also due to the short duration of the lettuce growing cycle. Alkalized sewage sludge increased soil pH and calcium (Ca) availability for plants. Fertilizer treatments minimally influenced cationic micronutrients. Heavy metals in the initial sewage sludge were below the threshold values established in international legislation, and the levels in soil and lettuce tissues were generally not higher than those in other treatments. Both of the sewage sludges used in this study showed high fertilizing value and very reactive behavior, making nutrients available much more quickly than FYM. This information is relevant to consider in defining their agricultural use.

Bioaerosol emission at various WWTP treatment units has drawn attention due to their potential negative impacts on human health. This study conducted a bibliometric analysis of the global research on bioaerosol emissions from WWTPs from 1995 to 2022. The Scopus database was used to identify relevant articles and research trends, major contributors in the field, and recent developments. The study examined 122 articles in the field of bioaerosols in WWTPs. The analysis findings showed that publications and citations peaked in 2022, with values of 25 and 818, respectively. At the beginning of the study period, the USA, Poland, and Italy led the publications' ranking, but with time, China emerged as the most influential country in the field. Recent advances in the field have revealed that spectral intensity bioaerosol sensors have contributed to the faster and more reliable identification and classification of bioaerosols. It was also observed that probabilistic techniques relying on mathematical models and assumptions to ascertain the risks associated with bioaerosols may result in false interpretations. Despite their high cost, epidemiological studies were best for assessing plant workers' health risks. The outbreak has raised questions about accurately evaluating and modeling SARS-CoV-2 persistence, infectivity, and aerosolization over WWTP sites and environmental factors. Finally, the study highlighted the potential of three control treatment approaches: carbon absorption, UV irradiation, and ozone treatments, which proved efficient in reducing bioaerosol emissions. [ABSTRACT FROM AUTHOR]

Poor management in the municipal waste disposal is a serious crisis for the health of the ecosystem and society. The implementation of the waste-to-energy projects can simultaneously recover the available energy in waste and significantly mitigate the environmental impacts of releasing waste into the environment. In this article, a novel bio-waste-driven multigeneration cycle (BW-MGC) integrated with a solar thermal field for the production of various valuable products from sewage sludge is introduced and evaluated (from thermodynamic, environmental and economic points of view). Herein, the biogas and syngas are obtained through the anaerobic digestion and gasification processes, respectively. Besides that, hydrogen energy and water production cycles are based on the water-gas shift reaction and atmospheric water harvesting cycle (AWHC) units, respectively. In the offered project, the heating capacity and a part of the electricity are obtained through the waste heat recovery system. The offered project provides a new process with a novel structure and configuration to produce useful products. Moreover, it can jointly address the simultaneous issues of energy, water, and environment. The offered plant can produce 18.1 MW of electricity, 18.72 l/h of water, and 0.9 kg/s of hydrogen fuel. The energy efficiency of the system in such design conditions was calculated as 36.12%, while the exergy efficiency was 40.9%. Further, the exergy sustainability factor, total products unit cost, and levelized total CO 2 emissions are calculated as 0.5281, 0.05168 USD/kWh, and 0.2124 kg/kWh, respectively. [ABSTRACT FROM AUTHOR]

The study aimed to assess the impacts on four township areas under Emfuleni Local Municipality of poor water quality from inadequate wastewater management. The failure of the municipality to upgrade and maintain the wastewater treatment facilities has been ongoing for many years and raw sewage spills have been observed on the streets. The objectives of the study were addressed through questionnaires directed at obtaining feedback from household and small business participants. In total, 260 respondents participated, and the results showed differences in the perceptions of impacts due to poor water quality per area of residence; these were significant at 99% confidence interval. Results showed concerns about the impact of wastewater and poor infrastructure on the livelihoods of both residents and business owners. In conclusion, the infrastructural problems resulting in water quality issues have caused severe socio-economic strain on residents and businesses alike. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Amidst a global discourse on energy resources, it is imperative to provide decision makers with a comprehensive overview of energy consumption (EC) associated with various projects, particularly wastewater treatment plants (WWTPs). Ensuring compliance with stringent effluent quality criteria in the treatment of municipal wastewater necessitates a substantial EC, representing a predominant factor contributing to the operational expenses incurred by WWTP. Machine learning (ML) techniques can contribute to the estimation of the WWTPs' EC, which requires efficient and accurate data. This article uses data from several municipal WWTP projects in Greece, which are examined in order to produce EC estimation models. Data were first statistically analyzed, according to the context of project attributes and the context of EC, and correlation analysis identified the appropriate predictive project variables. Then, the attribute selection function in Waikato Environment for Knowledge Analysis 3.8.4 (WEKA 3.8.4) software emphasized the most effective subset of variables. The extracted variables from the combination of the correlation analysis and the WEKA attribute function were used as input neurons for the construction of neural network (NN) models, in the Fast Artificial Neural Network Tool 1.2 (FANN Tool 1.2). The optimum NN model resulted in a mean squared error (MSE) of 8.99899 × 10−5 and was based on treatment capacity, flow rate, influent load, and served population as its inputs. Notably, the research highlights the potential generalizability of these models in Greece and beyond the Greek context, offering valuable tools for stakeholders to inform decision making, allocate resources efficiently, and improve energy-efficient designs, resulting in cost savings and sustainability benefits. [ABSTRACT FROM AUTHOR]

Nutrients such as nitrogen and phosphorus are typically considered detrimental to wetland values, but waterfowl can be numerous on nutrient-rich wetlands. Waterfowl were counted three to six times per year on nine treatment lagoons and associated wetlands (2,025 ha) at the Western Treatment Plant (south-east Australia) from 2000, to help maintain ecological values of this Ramsar-listed wetland as well as treating sewage for a large city (Melbourne). Up to 185,000 waterfowl were counted, varying with season, continental rainfall and lagoon operation. Nutrient levels were reduced on Lake Borrie lagoon in 2005 (as part of an Environmental Improvement Program) and restored in 2015. Waterfowl declined on Lake Borrie lagoon from 2005 when it received treated effluent not raw sewage, and increased in 2015 when it received partially treated sewage. This pattern was highly significant for total waterfowl and most species and guilds at Lake Borrie but was not replicated on other lagoons. Modelling revealed positive relationships between waterfowl numbers and nutrient concentrations, including ammonia and nitrite, to moderate levels. This shows that with careful management nutrient enrichment can have positive benefits, allowing artificial wetlands such as wastewater treatment plants to support high densities of waterbirds and the food webs that sustain them. [ABSTRACT FROM AUTHOR]

The seismic vulnerability of public buildings must be estimated using structural or non-structural parameters. Scientists ought to investigate these factors for the estimation and analysis of lifelines such as wastewater treatment plants (WWTPs). Although efforts have been made in the past, the serious non-structural and operational parameters are not enough defined. This study considers the amount of shortening of the supposed factors after the literature retrieval of WWTPs' damages at sixteen severe earthquake events worldwide and three events from Greece. The corresponding parameters used for "ordinary structures" are taken into account. The most severe factors for non-structural vulnerability are seven while for operational vulnerability are nine, including soil, water and air pollution, respectively. These factors can assist the rapid qualitative estimation of seismic vulnerability. Implementing these agents by introducing them to an empirical estimation method will mitigate the seismic risk against the WWTPs, in parallel with measures adopted. [ABSTRACT FROM AUTHOR]

Copyright of Medicina y Seguridad del Trabajo is the property of Escuela Nacional de Medicina del Trabajo - Instituto de Salud Carlos III and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Economics & Environment / Ekonomia i Środowisko is the property of Fundacja Ekonomistow Srodowiska i Zasobow Naturalnych and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial Intelligence (AI) has recently emerged as a powerful tool with versatile applications spanning various domains. AI replicates human intelligence processes through machinery and computer systems, finding utility in expert systems, image and speech recognition, machine vision, and natural language processing (NLP). One notable area with limited exploration pertains to using deep learning models, specifically Recurrent Neural Networks (RNNs), for predicting water quality in wastewater treatment plants (WWTPs). RNNs are purpose-built for handling sequential data, featuring a feedback mechanism. However, standard RNNs may exhibit limitations in accommodating both short-term and long-term dependencies when addressing intricate time series problems. The solution to this challenge lies in adopting Long Short-Term Memory (LSTM) cells, known for their inherent memory management through a 'forget gate' mechanism. In general, LSTM architecture demonstrates superior performance. WWTP data represent a historical series influenced by fluctuating environmental conditions. This study employs simple RNNs and LSTM architecture to construct prediction models for effluent parameters, systematically assessing their performance through various training data scenarios and model architectures. The primary objective was to determine the most suitable WWTP dataset model. The study revealed that an epoch setting of 50 and a batch size of 100 yielded the lowest training time and root mean square error (RMSE) values for both RNN and LSTM models. Furthermore, when these models are applied to predict effluent parameters, they exhibit precise RMSE values for all parameters. The study results can be applied to detect potential upsets in WWTP operations. [ABSTRACT FROM AUTHOR]

ABSTRACTWastewater treatment plants (WWTPs) are indispensable biotechnology facilities for modern cities and play an essential role in modern urban infrastructure by employing microorganisms to remove pollutants in wastewater, thus protecting public health and the environment. This study conducted a 13-month bacterial community survey of six full-scale WWTPs in Hong Kong with samples of influent, activated sludge (AS), and effluent to explore their synchronism and asynchronism of bacterial community. Besides, we compared AS results of six Hong Kong WWTPs with data from 1,186 AS amplicon data in 269 global WWTPs and a 9-year metagenomic sequencing survey of a Hong Kong WWTP. Our results showed the compositions of bacterial communities varied and the bacterial community structure of AS had obvious differences across Hong Kong WWTPs. The co-occurrence analysis identified 40 pairs of relationships that existed among Hong Kong WWTPs to show solid associations between two species and stochastic processes took large proportions for the bacterial community assembly of six WWTPs. The abundance and distribution of the functional bacteria in worldwide and Hong Kong WWTPs were examined and compared, and we found that ammonia-oxidizing bacteria had more diversity than nitrite-oxidizing bacteria. Besides, Hong Kong WWTPs could make great contributions to the genome mining of microbial dark matter in the global “wanted list.” Operational parameters had important effects on OTUs’ abundance, such as the temperature to the genera of Tetrasphaera, Gordonia and Nitrospira. All these results obtained from this study can deepen our understanding of the microbial ecology in WWTPs and provide foundations for further studies.IMPORTANCEWastewater treatment plants (WWTPs) are an indispensable component of modern cities, as they can remove pollutants in wastewater to prevent anthropogenic activities. Activated sludge (AS) is a fundamental wastewater treatment process and it harbors a highly complex microbial community that forms the main components and contains functional groups. Unveiling “who is there” is a long-term goal of the research on AS microbiology. High-throughput sequencing provides insights into the inventory diversity of microbial communities to an unprecedented level of detail. At present, the analysis of communities in WWTPs usually comes from a specific WWTP and lacks comparisons and verification among different WWTPs. The wide-scale and long-term sampling project and research in this study could help us evaluate the AS community more accurately to find the similarities and different results for different WWTPs in Hong Kong and other regions of the world.

Erhai Lake is a highland freshwater lake in Dali, China. Rapid tourism development has generated large amounts of pollutants. Since 2015, six wastewater treatment plants (WWTPs) have been built to treat wastewater collected through sewage interception projects. In this study, reductions in the pollution load of wastewater from different sources were evaluated by considering the effects of groundwater leakage, microbial degradation, and rainfall-runoff. The results showed that the systems reduced the chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) loads by 85, 83, and 85%, respectively. Discharge wastewater has the characteristics of a low concentration of domestic sewage discharge, large tourist sewage discharge, and high concentration of livestock wastewater. Due to the high groundwater level, there is groundwater infiltration in the influent water of WWTPs, which dilutes the pollutant concentration of the influent and, therefore, results in a lower treatment efficiency. Further treatment of tailwater also reduced the pollution loads discharged into the lake as well as the COD and TN by 10.25 and 22.90%, respectively. The results indicate that groundwater infiltration in the sewer network system is the primary target to be addressed in future developments. HIGHLIGHTS Reduction of pollution loads based on sewage treatment projects can be easily quantified.; The sewage treatment project exhibited the high removal efficiency with the reduction loads of 85% COD, 83% TN, and 85% TP into Erhai Lake.; The groundwater infiltration in the sewer network system is the primary target to be solved in future developments.;

Effective modeling and management are critical in wastewater treatment facilities since the aeration process accounts for 65–70% of the overall energy consumption. This study assesses control strategies specifically designed for different sizes of WWTP, analyzing their economic, environmental, and energy-related effects. Small WWTPs see advantages from the utilization of on/off and proportional–integral–derivative (PID) control methods, resulting in 10–25% energy savings and the reduction in dissolved oxygen (DO) levels by 5–30%. Cascade control and model predictive control (MPC) improve energy efficiency by 15–30% and stabilize DO levels by 15–35% in medium-sized WWTPs. Advanced WWTPs that utilize technologies such as MPC integrated with artificial intelligence (AI) and machine learning (ML) can decrease energy usage by 30–40% and enhance DO levels by 35–40%. Life cycle assessment (LCA) demonstrates substantial decreases in greenhouse gas (GHG) emissions: 5–20% for small, 10–25% for medium, and 30–35% for large WWTPs. These findings illustrate the feasibility and expandability of these tactics in both controlled laboratory environments and real-world situations, emphasizing the significance of customized methods for improving energy efficiency and sustainability in wastewater treatment. Subsequent investigations should prioritize integrating renewable energy sources and resolving obstacles in developing nations to enhance wastewater treatment plants’ energy efficiency and sustainability.

Background: Wastewater treatment plants (WWTPs) are crucial in the scope of European Commission circular economy implementation. However, bioaerosol production may be a hazard for occupational and public health. A scoping review regarding microbial contamination exposure assessment in WWTPs was performed. Methods: This study was performed through PRISMA methodology in PubMed, Scopus and Web of Science. Results: 28 papers were selected for data extraction. The WWTPs’ most common sampled sites are the aeration tank (42.86%), sludge dewatering basin (21.43%) and grit chamber. Air sampling is the preferred sampling technique and culture-based methods were the most frequently employed assays. Staphylococcus sp. (21.43%), Bacillus sp. (7.14%), Clostridium sp. (3.57%), Escherichia sp. (7.14%) and Legionella sp. (3.57%) were the most isolated bacteria and Aspergillus sp. (17.86%), Cladosporium sp. (10.71%) and Alternaria sp. (10.71%) dominated the fungal presence. Conclusions: This study allowed the identification of the following needs: (a) common protocol from the field (sampling campaign) to the lab (assays to employ); (b) standardized contextual information to be retrieved allowing a proper risk control and management; (c) the selection of the most suitable microbial targets to serve as indicators of harmful microbial exposure. Filling these gaps with further studies will help to provide robust science to policy makers and stakeholders.

This study focuses on the occurrence status and removal efficiency of microplastics in wastewater treatment plant processes. Analysis of effluent and sludge samples from the Wulongkou and Shuangqiao wastewater treatment plants in Zhengzhou revealed an overall microplastic removal efficiency of 95.64% and 92.53%, respectively, indicating the effectiveness of wastewater treatment plants in reducing microplastic emissions. Microplastics primarily exist in forms such as fiber, fragment, floc, film, and grain. Fibers are predominant in the effluent of the Wulongkou plant, while fibers and films predominate in the effluent of the Shuangqiao plant. Moreover, microplastics are predominantly sized below 500 μm, with larger microplastics (2–5 mm) exhibiting higher removal efficiencies after secondary treatment. Analysis of microplastic types revealed that PE is the most common type in the effluent of the Wulongkou plant, while the Shuangqiao plant predominantly contains PE and PA66. The abundance of microplastics in sludge samples was found to be 6.4 ± 0.8 items/g and 11.3 ± 2.3 items/g, highlighting sludge as an important sink for microplastics. Surface analysis of microplastics revealed characteristics such as wrinkles and cracks, with energy-dispersive spectroscopy indicating significant adsorption of heavy metal elements such as Zn, Hg, and Pb onto microplastic surfaces in sludge. These findings underscore the importance of microplastic removal in wastewater treatment processes and provide scientific evidence for the control and management of microplastic pollution in the future.

Sewage sludge should primarily find use in agriculture, reducing the quantity directed towards alternative disposal methods like incineration or deposition in municipal landfills. This study evaluated the agronomic value and the risk of soil and plant tissue contamination with heavy metals in sewage sludge obtained from two wastewater treatment plants (WWTP). The experiment was arranged as a 2 × 5 factorial (two sewage sludges, five sanitation treatments), involving lettuce cultivation in pots over two growing cycles. The two sewage sludges were sourced from the WWTPs of Gelfa and Viana do Castelo and underwent five sanitation and stabilization treatments (40% and 20% calcium oxide, 40% and 20% calcium hydroxide, and untreated sewage sludge). The Gelfa sewage sludge, characterized by a higher initial nitrogen (N) concentration, resulted in greater dry-matter yield (DMY) (12.4 and 8.6 g plant−1 for the first and second growing cycles, respectively) compared to that from Viana do Castelo (11.0 and 8.1 g plant−1), with N release likely being a major factor influencing crop productivity. The high N concentration and the low carbon (C)/N ratio of sewage sludge led to rapid mineralization of the organic substrate, which additionally led to a higher release of other important nutrients, such as phosphorus (P) and boron (B), making them available for plant uptake. Alkalizing treatments further stimulated sewage sludge mineralization, increasing soil pH and exchangeable calcium (Ca), thereby enhancing Ca availability for plants, and indicating a preference for use in acidic soils. Cationic micronutrients were minimally affected by the sewage sludge and their treatments. The concentrations of heavy metals in the sewage sludge, soils, and lettuce tissues were all below internationally established threshold limits. This study highlighted the high fertilizing value of these sewage sludges, supplying N, P, and B to plants, while demonstrating a low risk of environmental contamination with heavy metals. Nevertheless, the safe use of sewage sludge by farmers depends on monitoring other risks, such as toxic organic compounds, which were not evaluated in this study.

Isolated m.FlexorHallucis Tendon (FHL) rupture is rare and uncommon. We looked for information on the topic of reconstruction of m.flexorhallucis longus and subsequent rehabilitation in the scientific databases of SCOPUS, Elsevier and Google Scholar, but the information found was scarce and partial. This provoked us to share our experience in surgical treatment and subsequent recovery from this type of injury. Case description and patient's information: The considered clinical case concerns a 46-year-old woman with the inability to actively bend the big toe and altered sensitivity of the foot and its plantar surface. Ligamentotomyin the area of the tarsal canal and decompression of the n.tibialis sin was performed surgically. A thorough gentle debridement was performed in the tarsal canal with tenoplasty of the flexor halluces longus with a graft of m. plantaris. Therapeutic intervention: The physiotherapy program was divided into three periods: I (1-6) postoperative week, II (6-12th) postoperative week and III (12-24th) postoperative week. Follow–up and outcomes: The patient was tested three times - on the third postoperative day, at the end of the 12th and at the end of the 24th postoperative week. The test battery included centimetry, goniometry, visual analogue scale (VAS), and manual muscle testing. Conclusion: Based on the difference in the values of the studied indicators in the initial postoperative and final results after reconstruction of FHL with plantar graft and postoperative rehabilitation, we believe that this combination of surgical technique and subsequent physiotherapy protocol is highly effective, with excellent functional outcome.

Wastewater treatment plants (WWTPs) are energy-intensive facilities that play a critical role in meeting stringent effluent quality regulations. Accurate prediction of energy consumption in WWTPs is essential for cost savings, process optimization, regulatory compliance, and reducing carbon footprint. This paper introduces an efficient approach for predicting energy consumption in WWTPs, leveraging deep learning models, data augmentation, and feature selection. Specifically, Spline Cubic interpolation enriches the dataset, while the Random Forest model identifies important features. The study investigates the impact of lagged data to capture temporal dependencies. Comparative analysis of five deep learning models on original and augmented datasets from Melbourne WWTP demonstrates substantial performance improvement with augmented data. Incorporating lagged energy consumption data further enhances accuracy, providing valuable insights for effective energy management. Notably, the Long Short-Term Memory (LSTM) and Bidirectional Gated Recurrent Unit (BiGRU) models achieve Mean Absolute Percentage Error (MAPE) values of 1.36% and 1.436%, outperforming state-of-the-art methods.

Antibiotic resistance is reportedly disseminated from wastewater treatment plants (WWTPs) into aquatic environments. In this study, it was hypothesized that discharge of effluent from WWTPs may influence resistome of the adjacent aquatic environment. Thus, we aimed at investigation of resistome in WWTPs and receiving waters, to observe the dynamics of resistome and to determine the indicators for consistent comparison of contamination level. In this study, twenty-seven samples of upstreams (n = 9), downstreams (n = 9), and effluents (n = 9) samples from nine WWTPs located in the Nakdong and Yeongsan Rivers, South Korea, were collected for four years, and a total of 343 antibiotic resistance genes (ARGs) were quantitatively amplified using SmartChip analysis. The five core ARGs (aadA, aadA2, aadA5, strB, and sul1) were commonly detected in all samples. Three (aadA, aadA2, aadA5) of the five core ARGs were significantly more abundant in the effluent than in the aquatic environment. Interestingly, the water sources of the aquatic environments and effluents could be differentiated based on the abundance of the five core ARGs. The decision-making tree model supported the classification of the two water sources: aquatic environments and effluents. Taken together, considering the ubiquitous presence of the five ARGs with significantly different abundance between water sources, core ARGs including aadA2 are recommended as indicator genes to monitor ARGs contamination by employing quantitative analysis in South Korea. Determination of indicators would help consistently evaluate contamination level by ARGs.

Little were certain about how wastewater treatment plants (WWTPs) affected the Japanese riverine microplastic contamination. This study explored the influences of WWTPs on microplastic pollution, assessed ecological risks, and looked at the sources-to-sinks phenomenon (WWTPs-to-rivers-to-marine) in riverine settings in Japan's Yamaguchi prefecture. Fifty surface water samples from the five selected rivers (Koya, Saba, Shimaji, and Fushino, Nishiki) and 11 effluent samples from WWTPs in the rivers' catchment were examined. Microplastics were analyzed using filtration, wet-peroxidation, density-separation, and attenuated reflectance-Fourier transform infrared spectroscopy techniques. Results suggested that the less populated and rural river (Nishiki) was less contaminated compared to the WWTPs and urban areas affected rivers (Koya, Saba, Shimaji, and Fushino). The WWTPs increased microplastic abundance twofold in the downstream regions compared to upstream stations. Microplastic characterization showed that the smaller microplastics < 500 µm, fiber-shaped, transparent, blue, and green color particles were major. Polymer identification demonstrated that the polyethylene, polypropylene, and polyethylene terephthalate were prevalent both for the rivers and WWTP effluents. There was a significant emission of microplastics from WWTPs to rivers (4.671 billion pieces per day; 71.8 kg per day) and rivers to Seto Inland Sea (0.13/billion pieces per day/km2; 7.1 kg per day). The per capita MP emissions to the rivers via WWTPs ranged from 0.02 to 6.49 g per day, which was approximately 2% of per capita single-use plastic wastes in Japan. An assessment of ecological risks showed that the WWTPs posed high ecological risks to rivers, and built up the pollution hotspots to their downstream areas by releasing higher number of microplastics and highly toxic polymers. Overall, the WWTPs influenced the rivers through both abundances and characteristics (shapes-size-color-polymers), increased the complexity of microplastic compositions as well as elevated ecological risks in the rivers. This study contributed to bridging the knowledge gaps about microplastic sources-to-sinks, ecological risks, and pollution management in Japan and beyond. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) have been identified as a source of microplastics, an emerging contaminant class of increasing concern, to the environment. Three WWTPs in the Canterbury region, New Zealand, were sampled bi-monthly from winter (June) to summer (December), to assess the variability of the abundance, morphology and polymer type of microplastics present over time. Microplastics were isolated from effluent via wet-sieving (300 μm and 1 mm) and wet peroxide oxidation (WPO) digest, and the polymer types determined using micro-Fourier-Transform Infrared Spectroscopy (μ-FTIR). Confirmed microplastics were detected at an average concentration of 1.3 ± 0.6 particles/L in effluent, with fragments comprising 58% of all morphotypes. Dominant polymer types detected were polyester, polyethylene, and polypropylene (26%, 22%, and 15%, respectively). The results of this study were comparable with those reported in international studies. An estimated 2.4 × 105 microplastics enter the receiving coastal environment daily from the discharge of effluent from the three WWTPs studied. No trends in microplastic concentration, morphotype and polymer type were observed in effluent samples from each WWTP, suggesting a common and continual source of microplastics into WWTPs. Further sampling is required to identify the factors that determine the variability of microplastics in WWTP influents and effluents. [ABSTRACT FROM AUTHOR]

Microplastic pollution in aquatic environments has been a ubiquitous concern in recent years, owing to their rapid production combined with poor waste management practices. However, information on freshwater microplastics in the Global South is still scarce, despite growing research on freshwater microplastics in recent years, particularly within the Global North. To help address this knowledge gap, we studied water and sediment microplastic dynamics along a subtropical river system, i.e. Crocodile River around the Nelspruit City area (South Africa), across three different seasons (i.e. cool-dry, hot-dry, hot-wet) using a combination of diversity indices and multivariate analyses. Microplastics were more abundant during the cool-dry season in the surface water samples (mean 1058 particles m−3) and high during the hot-dry season (mean 568 particles kg−1 dwt) in the sediment samples. The hot-wet season had a low particle density in both surface water (mean 625 particles m−3) and sediments (mean 86 particles kg−1 dwt) samples. Microplastic shapes were dominated by fibres and fragments, with the colour scheme dominated by transparent, blue, and black. The abundance of microplastics was positively correlated with pH and resistivity, and negatively with river flow. Wastewater was attributed as a primary source of microplastics, particularly because of the observed dominant fibre microplastics, usually released during laundry. Our results suggest that Crocodile River and its tributaries are temporary sinks of microplastics during periods of low rainfall. Implications of this pollution are far-reaching, including effects on residents who are dependent on the Crocodile River as a source of drinking water and aquatic biota which may be exposed to these pollutants. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 can be detected in the feces of infected people, consequently in wastewater, and in bivalve mollusks, that are able to accumulate viruses due to their ability to filter large amounts of water. This study aimed to monitor SARS-CoV-2 RNA presence in 168 raw wastewater samples collected from six wastewater treatment plants (WWTPs) and 57 mollusk samples obtained from eight harvesting sites in Campania, Italy. The monitoring period spanned from October 2021 to April 2022, and the results were compared and correlated with the epidemiological situation. In sewage, the ORF1b region of SARS-CoV-2 was detected using RT-qPCR, while in mollusks, three targets—RdRp, ORF1b, and E—were identified via RT-dPCR. Results showed a 92.3% rate of positive wastewater samples with increased genomic copies (g.c.)/(day*inhabitant) in December–January and March–April 2022. In the entire observation period, 54.4% of mollusks tested positive for at least one SARS-CoV-2 target, and the rate of positive samples showed a trend similar to that of the wastewater samples. The lower SARS-CoV-2 positivity rate in bivalve mollusks compared to sewages is a direct consequence of the seawater dilution effect. Our data confirm that both sample types can be used as sentinels to detect SARS-CoV-2 in the environment and suggest their potential use in obtaining complementary information on SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Effective environmental and energy management is crucial in the wastewater treatment sector. This article examines the implementation of biogas projects, which use anaerobic digestion to convert sewage sludge into energy and biofertilizer, in the Russian Federation. These projects, while common in the European Union, are rare in Russia due to financial constraints. Currently, they are primarily funded by utility operator investment programs, supported by tariffs for wastewater services. It is estimated that funding these projects through a five-year investment program would result in an annual tariff increase of 6-20% in the first two years. Additional financial mechanisms, such as 'green' credits and government interest rate compensation, have minimal impact on tariff growth. Any increase, however, can be burdensome for the population, and regional administrations may hesitate to implement these projects due to tariff concerns. Regardless, these projects are essential for Russia's transition to a circular economy. [ABSTRACT FROM AUTHOR]

Aquatic environments are the final receptors of human emissions and are therefore contaminated by molecules, such as pharmaceuticals. After use, these compounds and their metabolites are discharged to wastewater treatment plants (WWTPs). During wastewater treatment, compounds may be eliminated or degraded into transformation products (TPs) or may be persistent. The aim of this study was to develop an analytical method based on high resolution mass spectrometry (HRMS) for the identification of six psychotropic drugs that are widely consumed in France and present in WWTPs, as well as their potential associated metabolites and TPs. Four out of six psychotropic drugs and between twenty-five and thirty-seven potential TPs were detected in wastewater, although this was based on full scan data. TPs not reported in the literature and specific to the study sites and therefore to the wastewater treatment processes were tentatively identified. For the selected drugs, most known and present TPs were identified, such as desmethylvenlafaxine or norcitalopram. Moreover, the short fragmentation study led rather to the identification of several TPs of carbamazepine as ubiquitous persistent TPs. [ABSTRACT FROM AUTHOR]

The COVID-19 has been declared a pandemic by the World Health Organization. Along with impairing the respiratory system, it also affects the gastrointestinal system. By reviewing experiments on the wastewater analysis for the detection of coronavirus, this study explores the fate, persistence, and various remediation strategies for the virus removal from the wastewater. The results indicated that the virus can be detected in the wastewater samples, feces, and sewage, even before the onset of symptoms. Coronavirus can be a potential panzootic disease, as several mammalian species get infected by the deadly virus. The disinfection strategies used earlier for the treatment of wastewater are not sufficient for the removal of viruses from the wastewater. Therefore, concerted efforts should be made to understand their fate, sources, and occurrence in the environmental matrices. To prevent the spread of the panzootic disease, revised guidelines should be issued for the remediation of the virus. Recent viral remediation methods such as membrane bioreactors and advanced oxidation methods can be used. Therefore, the present review puts a light on the current knowledge on the occurrence of coronaviruses in wastewater, the possible sources, fate, and removal strategies. [ABSTRACT FROM AUTHOR]

For pharmacological reasons many active organic pharmaceutical substances (AOPSs) are singly or multiply halogenated. Halogenation can confer optimised steric fitting of an AOPS to its molecular receptor; moreover, by increasing the lipophilicity of a compound, passive permeation through bilipid membranes into target cells is enhanced. As halogenation is widely suspected to inhibit biodegradability in wastewater treatment plants, the relationship of halogenation vs. ready biodegradability was investigated. Among 230 AOPSs with empirical ready biodegradability data, all 70 halogenated AOPSs are not readily biodegradable, and halogenation is confirmed to be an impediment to ready biodegradability. As a counterexample to halogenation, hydrophilic substitutions (hydroxy, carboxylic-acid or terminal-amine groups) are positively correlated with ready biodegradability. Regarding halogenation, therefore, pharmacological goals stand in stark contrast to environmental goals. Possible ideas toward solutions for this contradiction are discussed. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) are energy-intensive facilities that fulfill stringent effluent quality norms. Energy consumption prediction in WWTPs is crucial for cost savings, process optimization, compliance with regulations, and reducing the carbon footprint. This paper evaluates and compares a set of 23 candidate machine-learning models to predict WWTP energy consumption using actual data from the Melbourne WWTP. To this end, Bayesian optimization has been applied to calibrate the investigated machine learning models. Random Forest and XGBoost (eXtreme Gradient Boosting) were applied to assess how the incorporated features influenced the energy consumption prediction. In addition, this study investigated the consideration of information from past data in improving prediction accuracy by incorporating time-lagged measurements. Results showed that the dynamic models using time-lagged data outperformed the static and reduced machine learning models. The study shows that including lagged measurements in the model improves prediction accuracy, and the results indicate that the dynamic K-nearest neighbors model dominates state-of-the-art methods by reaching promising energy consumption predictions. [ABSTRACT FROM AUTHOR]

Abstract Background Wastewater treatment plants (WWTPs) are one of the largest biotechnology applications in the world and are of critical importance to modern urban societies. An accurate evaluation of the microbial dark matter (MDM, microorganisms whose genomes remain uncharacterized) proportions in WWTPs is of great value, while there is no such research yet. This study conducted a global meta-analysis of MDM in WWTPs with 317,542 prokaryotic genomes from the Genome Taxonomy Database and proposed a “wanted list” for priority targets in further investigations of activated sludge. Results Compared with the Earth Microbiome Project data, WWTPs had relatively lower genome-sequenced proportions of prokaryotes than other ecosystems, such as the animal related environments. Analysis showed that the median proportions of the genome-sequenced cells and taxa (100% identity and 100% coverage in 16S rRNA gene region) in WWTPs reached 56.3% and 34.5% for activated sludge, 48.6% and 28.5% for aerobic biofilm, and 48.3% and 28.5% for anaerobic digestion sludge, respectively. This result meant MDM had high proportions in WWTPs. Besides, all of the samples were occupied by a few predominant taxa, and the majority of the sequenced genomes were from pure cultures. The global-scale “wanted list” for activated sludge contained four phyla that have few representatives and 71 operational taxonomic units with the majority of them having no genome or isolate yet. Finally, several genome mining methods were verified to successfully recover genomes from activated sludge such as hybrid assembly of the second- and third-generation sequencing. Conclusions This work elucidated the proportion of MDM in WWTPs, defined the “wanted list” of activated sludge for future investigations, and certified potential genome recovery methods. The proposed methodology of this study can be applied to other ecosystems and improve understanding of ecosystem structure across diverse habitats. Video Abstract

Purpose: To systematize the activities and relationships between employers, workers, and occupational health services in the process of risk management of exposure to biological agents in wastewater treatment plants (WWTPs) during the COVID-19 outbreak. Material/Methods: We studied the Bulgarian and European Union legislation and the recommendations of international organizations related to risk management of exposure to COVID-19 concerning workers in WWTPs from March 2020 to September 2021. Results: The EU and Bulgarian legislation has been updated with a focus on risk management of exposure to the SARS-CoV-2, including workers from WWTPs. Some of the Coronaviridae that are known to be pathogenic remain in the second group according to the degree of danger, while Coronaviridae such as SARS-virus, MERS-virus and SARS-CoV-2 are evaluated and classified in group 3 according to the level of risk of infection. The employers must take measures to protect workers in accordance with the new, higher level of danger. We systematized risk management measures. Conclusion: Bulgarian and international legislation on health and safety at work has been updated in the period 2020-2021 with an emphasis on the risk management of exposure to biological agents at work.Co-operation between employers and workers in WWTPs, and occupational health services is an essential part of the risk management process, including prevention of outbreaks of work-related infectious diseases such as coronavirus disease 2019 (COVID-19).

Wastewater Treatment Plants (WWTPs) are considered as an Ultra Low Head (ULH) hydraulic resource. This has provoked an inadequate extraction of its potential energy by Micro Hydroelectric Plants (MHP) due to the improper relationship between the size and performance of the turbine. Thus, this work proposes the optimized design of a turbine composed of an intake-runner-diffuser, which looks for the maximum energy extraction from this kind of hydraulic resource. The annual Flow Duration Curve (FDC) of a WWTP effluent was examined to determine the flow rate with which the maximal available energy could be extracted through an adequate runner design. A 3D computational model of the intake-runner-diffuser was optimized by coupling a Computational Fluid Dynamics (CFD) software with a Multi Island Genetic Algorithm, while the pressure and flow field of the selected cases were qualitative and quantitatively analyzed. It was found that with the lowest Reaction Degree (RD), a propeller turbine reached its highest efficiency and pressure ratio coefficient, extracting 76% of the annual available energy of the hydraulic resource. In this way, the maximal exploitation of a ULH resource through the turbine design of the MHP system instead of adapting turbines from Large Hydropower Plants (LHP) could help to establish an actual and attractive project cost-benefit ratio.

The concentration of viruses in sewage sludge is significantly higher (10–1000-fold) than that found in natural environments, posing a potential risk for human and animal health. However, the composition of these viruses and their role in the transfer of pathogenic factors, as well as their role in the carbon, nitrogen, and phosphorus cycles remain poorly understood. In this study, we employed a shotgun metagenomic approach to investigate the pathogenic bacteria and viral composition and function in two wastewater treatment plants located on a campus. Our analysis revealed the presence of 1334 amplicon sequence variants (ASVs) across six sludge samples, with 242 ASVs (41.22% of total reads) identified as pathogenic bacteria. Arcobacter was found to be the most dominant pathogen accounting for 6.79% of total reads. The virome analysis identified 613 viral genera with Aorunvirus being the most abundant genus at 41.85%. Approximately 0.66% of these viruses were associated with human and animal diseases. More than 60% of the virome consisted of lytic phages. Host prediction analysis revealed that the phages primarily infected Lactobacillus (37.11%), Streptococcus (21.11%), and Staphylococcus (7.11%). Furthermore, our investigation revealed an abundance of auxiliary metabolic genes (AMGs) involved in carbon, nitrogen, and phosphorus cycling within the virome. We also detected a total of 113 antibiotic resistance genes (ARGs), covering major classes of antibiotics across all samples analyzed. Additionally, our findings indicated the presence of virulence factors including the clpP gene accounting for approximately 4.78%, along with toxin genes such as the RecT gene representing approximately 73.48% of all detected virulence factors and toxin genes among all samples analyzed. This study expands our understanding regarding both pathogenic bacteria and viruses present within sewage sludge while providing valuable insights into their ecological functions.

Currently, one of the main goals is to make municipal wastewater treatment plants (WWTPs) energy-neutral. However, advanced wastewater treatments and sewage sludge processing are still classified as highly energy-intensive. In this study, the energy self-sufficiency potential assessment of the WWTP located in Krosno (Poland) was evaluated. Moreover, the possible paths for improving the energy balance of the analyzed facility are presented in this paper. The performed evaluation indicated that in 2016–2019, the energy consumption at WWTP Krosno varied from 0.25 to 0.71 kWh/m3 of wastewater (average 0.51 kWh/m3), and the highest energy utilization values in each year were recorded around the summer season. An analysis of the data showed that as the pollutant load flowing into the WWTP increased, its energy utilization decreased. Such results indicate that the treatment cost per cubic meter decreases as the load increases due to the capital cost being the same. The estimated self-sufficiency of the facility in the years analyzed was 50.5%. The average energy recovery from 1 m3 of wastewater was 0.27 kWh/m3, and the average energy recovery from 1 m3 of biogas was 1.54 kWh/m3. Since the energy balance of this wastewater treatment plant, determined primarily by the continuously increasing cost of energy purchases, has to be improved, two courses of action were identified that will allow for increasing self-sufficiency. The co-digestion strategy was indicated as the easiest solution to implement, given the on-going anaerobic stabilization of sewage sludge at this WWTP. Moreover, the possible co-substrates that can be obtained from local suppliers were indicated. The second course of action, which requires a thorough economic analysis, is sludge pre-treatment, which might improve sewage sludge properties, resulting in a more favorable biogas yield.

The aim of this study was to assess the impact of WWTP effluents on the sediment microbial communities throughout the Mureș River. This study shows the existence of an ecological equilibrium between the WWTP effluent disruptors and the resilience of the Mureș River sediment microbiomes, a fact that suggests the river’s stable/balanced ecological status in this regard, partly due to the microbial communities’ resilience to the local impact of WWTP effluents. High-throughput 16S bacterial metabarcoding was used to evaluate the bacterial communities in the sediment. Due to the lotic system’s sediment microbial communities’ sensitivity to environmental changes, we assumed the dependency of these community structures and functions on environmental abiotic and abiotic parameters. The study results show that, although bacterial communities are equally diverse in the three locations (upstream WWTP, WWTP effluents, and downstream WWTP), there is a difference in community structure between the upstream samples and the WWTP samples, while the downstream samples contain a mixture of the upstream and WWTP effluent communities. Just downstream of the WWTP sediment, microbial communities are influenced by the specific input from the WWTP effluents; nevertheless, the river sediment microbiome is resilient and able to further recover its natural microbial composition, as evidenced by the similarity in bacterial community structures at all upstream river locations. This study demonstrates the ecological equilibrium between the WWTP effluent disruptors and the resilience capacity of the Mureș River sediment microbiomes, a fact that indicates the river’s stable/balanced ecological status, in part due to the microbial communities’ resilience to the local impact of WWTP effluents. Based on these findings, a monitoring system should be implemented here in the future.

The spread of multidrug-resistant bacteria from humans or livestock is a critical issue. However, the epidemiology of resistant pathogens across wastewater pathways is poorly understood. Therefore, we performed a detailed comparison of third-generation cephalosporin-resistant Escherichia coli (3GCREC) from wastewater treatment plants (WWTPs) to analyze dissemination pathways. A total of 172 3GCREC isolated from four WWTPs were characterized via whole genome sequencing. Clonal relatedness was determined using multi-locus sequence typing (MLST) and core genome MLST. Resistance genotypes and plasmid replicons were determined. A total of 68 MLST sequence types were observed with 28 closely related clusters. Resistance genes to eight antibiotic classes were detected. In fluoroquinolone-resistant isolates, resistance was associated with three-or-more point mutations in target genes. Typing revealed high genetic diversity with only a few clonal lineages present in all WWTPs. The distribution paths of individual lines could only be traced in exceptional cases with a lack of enrichment of certain lineages. Varying resistance genes and plasmids, as well as fluoroquinolone resistance-associated point mutations in individual isolates, further corroborated the high diversity of 3GCREC in WWTPs. In total, we observed high diversity of 3GCREC inside the tested WWTPs with proof of resistant strains being released into the environment even after treatment processes.

Antibiotics are an essential tool of modern medicine, contributing to significantly decreasing mortality and morbidity rates from infectious diseases. However, persistent misuse of these drugs has accelerated the evolution of antibiotic resistance, negatively impacting clinical practice. The environment contributes to both the evolution and transmission of resistance. From all anthropically polluted aquatic environments, wastewater treatment plants (WWTPs) are probably the main reservoirs of resistant pathogens. They should be regarded as critical control points for preventing or reducing the release of antibiotics, antibioticresistant bacteria (ARB), and antibiotic-resistance genes (ARGs) into the natural environment. This review focuses on the fate of the pathogens Enterococcus faecium, Staphylococcus aureus, Clostridium difficile, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacteriaceae spp. (ESCAPE) in WWTPs. All ESCAPE pathogen species, including high-risk clones and resistance determinants to last-resort antibiotics such as carbapenems, colistin, and multidrug resistance platforms, were detected in wastewater. The whole genome sequencing studies demonstrate the clonal relationships and dissemination of Gram-negative ESCAPE species into the wastewater via hospital effluents and the enrichment of virulence and resistance determinants of S. aureus and enterococci in WWTPs. Therefore, the efficiency of different wastewater treatment processes regarding the removal of clinically relevant ARB species and ARGs, as well as the influence of water quality factors on their performance, should be explored and monitored, along with the development of more effective treatments and appropriate indicators (ESCAPE bacteria and/or ARGs). This knowledge will allow the development of quality standards for point sources and effluents to consolidate the WWTP barrier role against the environmental and public health AR threats. [ABSTRACT FROM AUTHOR]

Abstract—The microbial diversity and community structure of activated sludge in the biological treatment units of five municipal WWTPs and two industrial WWTPs were studied. The results showed that industrial WWTPs had the lowest diversity and abundance of activated sludge microbial communities, indicating that industrial wastewater inhibited the growth of microbial communities. In the correlation analysis between environmental factors and microbial diversity indices, pH and COD showed a significant negative correlation with the number of OTUs and microbial diversity. The main dominant microbial genus were Hyphomicrobium, Acinetobacter, Novosphingobium, Acinetobacter, and Meiothermus. Both principal coordinate analysis (PCoA) and phylogenetic analysis showed large differences in the structure of municipal and industrial microbial community structure, indicating the uniqueness of the activated sludge community structure in industrial WWTPs. Gene function predictions indicated that LJ had higher metabolic function associated with inorganic salt and lipid metabolism. Further co-occurrence network analysis showed that many of the key industrial WWTPs belonged in the same module, suggesting that they had strong interspecific interactions but were relatively independent from other microorganisms in the municipal WWTPs. This study broadens our understanding of microbial community differences between municipal WWTPs and industrial WWTPs. [ABSTRACT FROM AUTHOR]

Soil amendments, such as pyrochar (PC) and hydrochar (HC), have the potential to enhance soil properties and crop yields. The objective was to investigate the effects of HC from anaerobic digestion effluent (ADE) of sewage sludge (SS), ADE of manure (M), and PC, as soil amendments. Lettuce seeds were sown and grown in soil amended with chars at rates of 1 to 15 g char/kg soil. Soil properties and plant responses were compared to soil without amendment (control). Soil amended with HC-ADE-SS and HC-ADE-M had higher pH, phosphorus content, and cation exchange capacity than the control. All treatments and the control resulted in 80% + emergence rates. Root dry mass of plants grown on soil with 10 and 15 g/kg was higher than the control. No negative effects were observed in emergence and whole-plant dry biomass, indicating that HC-ADE-SS and HC-ADE-M could be amended without negative impacts on soil properties and plant responses. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) from each treatment process of wastewater treatment plants (WWTPs) contains abundant photosensitive substances, which could significantly affect the photodegradation of 17α-ethinylestradiol (EE2). Nevertheless, information about EE2 photodegradation behavior mediated by DOM from diverse WWTPs and the photosensitivity sources of such DOM are inadequate. This study explored the photodegradation behavior of EE2 mediated by four typical WWTPs' DOM solutions and investigated the photosensitivity sources of DOM in the anaerobic-anoxic-oxic (A2/O) process. The parallel factor analysis identified three varying fluorescing components of these DOM, tryptophan-like substances or protein-like substances, microbial humuslike substances, and humic-like components. The photodegradation rate constants of EE2 were positively associated with the humification degree of DOM (P < 0.05). The triplet state substances were responsible for the degradation of EE2. DOM extracted from the A2/O process, especially in the secondary treatment process had the fastest EE2 photodegradation rate compared to that of the other three processes. Four types of components (water-soluble organic matter (WSOM), extracellular polymeric substance, humic acid, and fulvic acid) were separated from the A2/O process DOM. WSOM had the highest promotion effect on EE2 photodegradation. Fulvic acid-like components and humic acid-like organic compounds in WSOM were speculated to be important photosensitivity substances that can generate triplet state substances. This research explored the physicochemical properties and photosensitive sources of DOM in WWTPs, and explained the fate of estrogens photodegradation in natural waters. [ABSTRACT FROM AUTHOR]