Cyclic methylsiloxanes in wastewater treatment plants: Occurrence, emissions, environmental distributions, and occupational exposure.

Cyclic methylsiloxanes (CMSs), widely found in wastewater treatment plants (WWTPs), are potentially hazardous to the environment and human health. In this study, the environmental behavior and human exposure risks of three CMSs (D4-D6) were evaluated in WWTPs located in Beijing and Kunming, Yunnan province. D5 had the highest concentrations in air, water, and sludge, with seasonal variation that consisted of a high concentration in summer and low concentration in winter. The CMS concentrations in air were 3-4-fold higher in the A2/O (Anaerobic-Anoxic-Oxic) treatment units than in the other units. CMS emissions to air, soil, and water from the Beijing WWTP were in the ranges of 3.4 × 104-5.0 × 104 kg·a-1, 4.5 × 102-7.5 × 102 kg·a-1, and 2.5 × 102-2.9 × 102 kg·a-1, constituting 98 %, 1.3 %, and 0.7 % of the total emissions, respectively. Total daily inhalation exposure doses of CMSs (ADDinh,CMSs) associated with four different jobs in WWTPs showed that wastewater treatment technicians had the highest ADDinh,CMSs (51 µg/kg/day), indicating that these people had the highest occupational exposure risk in WWTPs. Therefore, this study identified that atmospheric emission was the main environmental fate of CMSs in WWTPs, and provide a basis for the improvement of WWTP process and risk management decisions. ENVIRONMENTAL IMPLICATION: Assessing the environmental fate and occupational exposure risk of cyclic methylsiloxanes (CMSs) found in wastewater treatment plants (WWTPs) is crucial. This is the first study to identify that atmospheric emission was the main environmental fate of CMSs in WWTPs, especially D5; the inhalation exposure doses of CMSs were all significantly higher in the occupational population working in WWTPs. The results described in our study will help enhance the understanding of current knowledge base of environmental fate and exposure risk of CMSs in WWTPs, and provide a basis for the improvement of WWTP process and risk management decisions.

Impact of wastewater treatment and drought in an Alpine region: a multidisciplinary case study.

In the context of global climate change, drought occurrence in streams of alpine origin is a recent phenomenon, whose impact is still poorly investigated. In this study, we adopted a three-disciplinary approach to investigate the response of an Alpine river (NW Italy) to severe drought conditions occurred in the year 2022. We hypothesised that the considerable loss in the water flow could exacerbate wastewater treatment plant (WWTP) discharge effects, lowering dilution capacity of the stream system and then increasing chemical/microbial pollution and altering benthic community characteristics. To assess river response to drought conditions of the considered year, the concentration of the main chemical variables, faecal indicator bacteria, pathogen presence and structural/functional organisation of benthic macroinvertebrates and diatom communities were measured monthly in the reaches located upstream and downstream of a WWTP (January-December 2022). Main environmental variables, such as flow velocity, water depth, and flow regime, were also considered. A multivariate analysis approach was then applied to emphasise correlations between selected variables and flow regime. Comparing upstream and downstream sections over the considered year, a common behaviour of chemical/microbiological parameters was observed, with generally higher concentrations of nutrients and bacterial indicators downstream of the local WWTP. Moreover, a positive correlation between water scarcity and nutrients/bacterial concentrations was revealed. The macroinvertebrate communities responded accordingly, both in terms of density and biological metric shift. Interestingly, differences between the two sections were strictly associated with hydrological conditions, with higher dissimilarities found in low-flow conditions. As the magnitude and duration of drought events are projected to increase in the years to come in different parts of Europe, this work can serve as a first building block and as a hint for future studies aimed at improving our knowledge about the consequences of these events that is pivotal for planning effective management strategies.

Analyzing the variation of greenhouse gas emissions from typical municipal wastewater treatment plants in Beijing during 2007-2021.

With the proposal of dual carbon goals and stringent effluent standards, the path of mitigating greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has gained significant research attention. Here, we evaluate the impact of season, elevated standards, operating parameters, and using clean energy on GHG emissions from 8 typical WWTPs in Beijing based on 180 monthly monitoring data. Coupled with the increasing demand for wastewater treatment and 77% more chemical oxygen demand being removed in 2017, total GHG emissions from 5 WWTPs increased by 89% compared to the status quo in 2007, and after energy structure reform total GHG emissions decreased by 17% in 2021. Scenario analysis reveals that energy recovery and clean energy utilization provide 64% and 48% mitigation potential by 2050, respectively. We argue stricter effluent standard leads to GHG emissions growth in WWTPs; meanwhile, process optimization, proper temperature and targeted policies at WWTPs can reduce GHG emissions.

Pre-training enhanced spatio-temporal graph neural network for predicting influent water quality and flow rate of wastewater treatment plant: Improvement of forecast accuracy and analysis of related factors.

Efficient management of wastewater treatment plants (WWTPs) necessitates accurate forecasting of influent water quality parameters (WQPs) and flow rate (Q) to reduce energy consumption and mitigate carbon emissions. The time series of WQPs and Q are highly non-linear and influenced by various factors such as temperature (T) and precipitation (Precip). Conventional models often struggle to account for long-term temporal patterns and overlook the complex interactions of parameters within the data, leading to inaccuracies in detecting WQPs and Q. This work introduced the Pre-training enhanced Spatio-Temporal Graph Neural Network (PT-STGNN), a novel methodology for accurately forecasting of influent COD, ammonia nitrogen (NH3-N), total phosphorus (TP), total nitrogen (TN), pH and Q in WWTPs. PT-STGNN utilizes influent data of the WWTP, air quality data and meteorological data from the service area as inputs to enhance prediction accuracy. The model employs unsupervised Transformer blocks for pre-training, with efficient masking strategies to effectively capture long-term historical patterns and contextual information, thereby significantly boosting forecasting accuracy. Furthermore, PT-STGNN integrates a unique graph structure learning mechanism to identify dependencies between parameters, further improving the model's forecasting accuracy and interpretability. Compared with the state-of-the-art models, PT-STGNN demonstrated superior predictive performance, particularly for a longer-term prediction (i.e., 12 h), with MAE, RMSE and MAPE at 12-h prediction horizon of 2.737 ± 0.040, 4.209 ± 0.060 and 13.648 ± 0.151 %, respectively, for the algebraic mean of each parameter. From the results of graph structure learning, it is observed that there are strong dependencies between NH3-N and TN, TP and Q, as well as Precip, etc. This study innovatively applies STGNN, not only offering a novel approach for predicting influent WQPs and Q in WWTPs, but also advances our understanding of the interrelationships among various parameters, significantly enhancing the model's interpretability.

[N2O Emission Factors from Wastewater Treatment Plants Based on Literature Statistics and Model Fitting].

The emission of nitrous oxide （N2O） during wastewater treatment cannot be ignored. The analysis of statistical data from literature based on 126 empirical studies revealed that the geographical factors of wastewater treatment plants （WWTPs） had a significant impact on N2O emission factors. However, the N2O emission factors of WWTPs in all regions of the world were generally lower than the Intergovernmental Panel on Climate Change （IPCC） recommended values. In China, the N2O emission factors （in N2O-N/Ninfluent） of WWTPs were approximately 0.000 35-0.065 20 kg·kg-1. Meanwhile, the N2O emission factors of different wastewater treatment processes were also significantly different, especially since the sequencing batch reactor （SBR） process had higher emissions. The use of uniform default emission factors for accounting was prone to overestimate N2O emissions, and it is recommended that countries conduct actual monitoring or modeling studies to develop categorical emission factors suitable for local conditions. In addition, the N2O emission factor based on total nitrogen （TN） removal was weakly negatively correlated with TN removal in 126 empirical data, which was more in line with bioprocessing stoichiometry and could provide an accurate accounting method for N2O. To this end, a digital twin model was developed to dynamically simulate a case anaerobic-anoxic-aerobic （AAO） WWTP to comprehensively quantify the dynamic emission behavior of N2O, which demonstrated that N2O emissions had significant seasonal and daily variability and were only equivalent to 11% of the calculated value of the emission factor based on the IPCC recommendation. Comparing the scatter linear fitting and categorical mean exponential fitting methods, it was found that the latter could more accurately reflect the negative correlation between the N2O emission factors and the TN removal rate, and an exponential regression equation between the average N2O emission factor based on the amount of TN removed and the TN removal rate was further developed to predict the N2O emission. The dynamic simulation and categorical index fitting methods provided in this study are important references for the accurate accounting of N2O emissions in similar WWTPs and provide help for understanding and responding to the N2O emission problems.

Detection of Multiple Human Viruses, including Mpox, Using a Wastewater Surveillance Approach in Brazil.

Sewage surveillance can be used as an effective complementary tool for detecting pathogens in local communities, providing insights into emerging threats and aiding in the monitoring of outbreaks. In this study using qPCR and whole genomic sewage surveillance, we detected the Mpox virus along with other viruses, in municipal and hospital wastewaters in Belo Horizonte, Brazil over a 9-month period (from July 2022 until March 2023). MPXV DNA detection rates varied in our study, with 19.6% (11 out of 56 samples) detected through the hybrid capture method of whole-genome sequencing and 20% (12 out of 60 samples) through qPCR. In hospital wastewaters, the detection rate was higher, at 40% (12 out of 30 samples) compared to 13.3% (4 out of 30 samples) in municipal wastewaters. This variation could be attributed to the relatively low number of MPXV cases reported in the city, which ranged from 106 to 341 cases during the study period, and the dilution effects, given that each of the two wastewater treatment plants (WWTP) investigated serves approximately 1.1 million inhabitants. Additionally, nine other virus families were identified in both hospitals and municipal wastewaters, including Adenoviridade, Astroviridae, Caliciviridae, Picornaviridade, Polyomaviridae, Coronaviridae (which includes SARS-CoV-2), Herspesviridae, Papillomaviridae and Flaviviridae (notably including Dengue). These findings underscore the potential of genomic sewage surveillance as a robust public health tool for monitoring a wide range of viruses circulating in both community and hospitals environments, including MPXV.

Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches.

Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (TPs) is very limited. Here, we investigated occurrence and transformation of pharmaceuticals and TPs in WWTPs and receiving rivers by using suspect and non-target analysis as well as target analysis. Results showed identification of 113 pharmaceuticals and 399 TPs, including mammalian metabolites (n = 100), environmental microbial degradation products (n = 250), photodegradation products (n = 44) and hydrolysis products (n = 5). The predominant parent pharmaceuticals (n = 37) and transformation products (n = 68) were mainly derived from antimicrobials, accounting for 32.7 % and 17.0 %, respectively. The identified compounds were found in the influent (387-428) and effluent (227-400) of WWTPs, as well as upstream (290-451) and downstream (322-416) of receiving rivers, most predominantly from antimicrobials, followed by analgesic and antipyretic drugs. A total of 399 identified TPs were transformed by 110 pathways, of which the oxidation reaction was predominant (27.0 %), followed by photodegradation reaction (10.7 %). Of the 399 TPs, 49 (with lower PNECs) were predicted to be more toxic than their parents. Compounds with potential high risks (hazard quotient >1 and risk index (RI) > 0.1) were found in the WWTP influent (126), effluent (53) and river (61), and the majority were from the antimicrobial and antihypertensive classes. In particular, the potential risks (RI) of TPs from roxithromycin and irbesartan were found higher than those for their corresponding parents. The findings from this study highlight the need to monitor TPs from pharmaceuticals in the environment.

Tracing Gadolinium levels throughout wastewater treatment: Insights from a yearly assessment in northern Spain.

Gadolinium (Gd) is a rare earth element (REE) used in the formulation of contrast agents for Magnetic Resonance Imaging (MRI) due to its paramagnetic properties. The growth in population and the improved quality of the healthcare systems over the last years, has promoted the use of MRI as an effective diagnostic tool thus increasing the consumption of gadolinium and its release into the wastewater treatment network. Therefore, the tracking and quantification of this metal in sewage treatment plants and water bodies, is of paramount importance since there are currently no specific rare earth treatment technologies installed in WWTPs, and consequently gadolinium is finally discharged into the environment. In this work, the presence of gadolinium and all other rare earth elements was monitored during a year in three WWTPs in northern Spain (Vuelta Ostrera and San Román in Cantabria and Galindo in País Vasco). These WWTPs are located close to urban centres with hospitals where MRI tests are performed. By tracing Gd throughout the wastewater treatment facilities, its presence was confirmed in water streams, in the order of ng per litter, and in sludge and ashes, in the order of mg per kilogram. A significant human influence was observed, with Gd anomaly values between 3.14 and 79.2 and anthropogenic Gd percentages above 90 %. The presence of Gd in water streams is affected by the sampling period due to the variations of the activity periods of the hospitals nearby the treatment plants. On the contrary, its content in sludge and ashes remains almost constant along the year. The concentration of this metal found in the ashes opens the door to its possible recovery together with other critical raw materials in the context of the circular economy.

Long term study on the fate and environmental risks of favipiravir in wastewater treatment plants and comparison with COVID-19 cases.

In recent years especially during COVID-19, the increased usage of antiviral drugs has led to increased interest in monitoring their presence in wastewater worldwide. In this study, it was examined the occurrence, fate and environmental risks of favipiravir which is used for COVID-19 treatment in two wastewater treatment plants (WWTPs) with different treatment processes in Istanbul, Turkey. Favipiravir was measured in WWTPs influent samples, effluent samples and sludge samples with maximum concentrations of 97 µg/L, 64.11 µg/L and 182.47 µg/g, respectively. Favipiravir had removal efficiency below 55 % for both WWTPs. Mass balance analysis showed that favipiravir removal in WWTPs mainly attributed to biodegradation/biotransformation. Statistical analysis revealed a significant correlation between favipiravir concentration and COVID-19 incidence in Istanbul. The microbial distribution analysis indicated that comparison of collected COVID-19 pandemic sludge and post-pandemic period sludge samples, a noteworthy reduction in the Chloroflexi and Actinobacteriota phyla at the phylum level was observed. Environmental risk assessment using risk quotients ranged from 168 to 704, indicating that the presence of this antiviral drug posed significant ecological risks to aquatic organisms. The study concluded that WWTPs were releasing antiviral drugs into the environment, thereby posing risks to both the aquatic ecosystem and public health. The results of this study demonstrate the persistence of favipiravir in WWTPs and offer crucial supporting data for further research into the advancement of wastewater treatment technology. Also, this study shows wastewater based monitoring is supplementary and early warning system for determining the occurrence of antiviral drugs.

Fit-for-purpose WWTP unmanned aerial systems: A game changer towards an integrated and sustainable management strategy.

In the ongoing Anthropocene era, air quality monitoring constitutes a primary axis of European and international policies for all sectors, including Waste Water Treatment Plants (WWTPs). Unmanned Aerial Systems (UASs) with proper sensing equipment provide an edge technology for air quality and odor monitoring. In addition, Unmanned Aerial Vehicle (UAV) photogrammetry has been used in civil engineering, environmental (water) quality assessment and lately for industrial facilities monitoring. This study constitutes a systematic review of the late advances and limitations of germane equipment and implementations. Despite their unassailable flexibility and efficiency, the employment of the aforementioned technologies in WWTP remote monitoring is yet sparse, partial, and concerns only particular aspects. The main finding of the review was the lack of a tailored UAS for WWTP monitoring in the literature. Therefore, to fill in this gap, we propose a fit-for-purpose remote monitoring system consisting of a UAS with a platform that would integrate all the required sensors for air quality (i.e., emissions of H2S, NH3, NOx, SO2, CH4, CO, CO2, VOCs, and PM) and odor monitoring, multispectral and thermal cameras for photogrammetric structural health monitoring (SHM) and wastewater/effluent properties (e.g., color, temperature, etc.) of a WWTP. It constitutes a novel, supreme and integrated approach to improve the sustainable management of WWTPs. Specifically, the developments that a fit-for-purpose WWTP UAS would launch, are fostering the decision-making of managers, administrations, and policymakers, both in operational conditions and in case of failures, accidents or natural disasters. Furthermore, it would significantly reduce the operational expenditure of a WWTP, ensuring personnel and population health standards, and local area sustainability.

Opportunity Analysis of Phosphorus Recovery from Municipal Wastewater for Cropland Based on the Simulated Vehicle Transport Distance in the Yangtze River Delta, China.

With the rapid depletion of phosphate rocks and increasing agricultural demand, establishing a phosphorus (P) flow "loop" rather than a one-way trajectory between cropland and urban areas was imperative. Recovering P from municipal wastewater stood as a viable strategy to mitigate reliance on traditional P-containing chemical fertilizer. This study analyzed the intricate relationships between the potentials of P recovery from municipal wastewater and the P demand of croplands in the populated Yangtze River Delta (YRD), China. An indicator of the P vehicle transport distance was constructed and calculated to estimate the potential to recover and reuse P in agriculture, applying the simulated annealing (SA) algorithm and road networks obtained from OpenStreetMap (OSM). The results indicated that, on a regional scale, recovered P from municipal wastewater could fulfill 14.0% of the cropland P demands in the YRD, with a median P vehicle transport distance of 3.1 km/Mg of P. Notably, the P vehicle transport distance varied largely depending upon the cropland distributions, road density, and P recovery potential from municipal wastewater. The novel methodology developed here determined the optimal transportation routes for P recovery from wastewater treatment plants (WWTPs) to cropland, which played a crucial role in refining the wastewater management strategies aligned with the United Nations Sustainable Development Goals.

Factors in the decline of the African penguin: Are contaminants of emerging concern (CECs) a potential new age stressor?

The African penguin is currently experiencing a significant decline, with just over 10,000 breeding pairs left. A substantial body of research reflects the impacts of contaminants of emerging concern (CECs) on the marine environment, with wastewater treatment plants reported as one of the main sources of CEC release. In South Africa, CECs were identified contaminating the marine environment and bioaccumulating in several marine species. Approximately 70 % of all African penguin colonies breed in close proximity to cities and/or harbors in South Africa. Currently, the impact of CECs as a stressor upon the viability of African penguin populations is unknown. Based on the search results there was a clear lack of information on CECs' bioaccumulation and impact on the African penguin. This narrative review will thus focus on the prevalent sources and types of CECs and examine the reported consequences of constant exposure in seabirds, particularly African penguins.

Treated wastewater: A hotspot for multidrug- and colistin-resistant Klebsiella pneumoniae.

Wastewater treatment plants are hotspots for the release of antimicrobial resistant pathogenic bacteria into aquatic ecosystems, significantly contributing to the cycle of antimicrobial resistance. Special attention should be paid to antimicrobial resistant ESKAPE bacteria, which have been identified as high-priority targets for control measures. Among them, Klebsiella pneumoniae is particularly noteworthy. In this study, we collected wastewater samples from the inlet, sedimentation tank, and effluent water of a wastewater treatment plant in June, July, October, and November of 2018. We detected and characterized 42 K. pneumoniae strains using whole genome sequencing (15 from the inlet, 8 from the sedimentation tank, and 19 from the effluent). Additionally, the strains were tested for their antimicrobial resistance phenotype. Using whole genome sequencing no distinct patterns were observed in terms of their genetic profiles. All strains were resistant to tetracycline, meanwhile 60%, 47%, and 37.5% of strains isolated from the inlet, sedimentation tank, and effluent, respectively, were multidrug resistant. Some of the multidrug resistant isolates were also resistant to colistin, and nearly all tested positive for the eptB and arnT genes, which are associated with polymyxin resistance. Various antimicrobial resistance genes were linked to mobile genetic elements, and they did not correlate with detected virulence groups or defense systems. Overall, our results, although not quantitative, highlight that multidrug resistant K. pneumoniae strains, including those resistant to colistin and genetically unrelated, being discharged into aquatic ecosystems from wastewater treatment plants. This suggests the necessity of monitoring aimed at genetically characterizing these pathogenic bacteria.

Non-target liquid chromatography high-resolution mass spectrometry screening to prioritize unregulated micropollutants that persist through domestic wastewater treatment.

Efforts to regulate and monitor emerging contaminants are insufficient because new chemicals are continually brought to market, and many are unregulated and potentially harmful. Domestic wastewater treatment plants are not designed to remove micropollutants and are important sources of emerging contaminants in the aquatic environment. In this study, non-target screening, an unbiased method for analyzing compounds without prior information, was used to identify compounds that may be emitted in wastewater treatment plant effluent and should be monitored. Nine wastewater treatment plants using different treatment methods were studied, and a non-target screening data-processing method was used. The frequencies at which the contaminants were detected and contaminant persistence through the treatment processes were considered, and then the contaminants were prioritized. The predicted no-effect concentration of each prioritized contaminant was used to determine whether further analysis and monitoring of the contaminant was necessary. Quantitative analyses of five compounds (amantadine, atenolol, benzotriazole, diphenhydramine, and sulpiride) were performed using reference standards. Probable molecular formulae and structures were proposed for 17 contaminants, and the risks posed by the contaminants were estimated using predicted no-effect concentrations. The results provide valuable insights into how unregulated micropollutants can be identified and prioritized for monitoring in future studies.

Amphetamine-like substances and synthetic cathinones in Portuguese wastewater influents: Enantiomeric profiling and role of suspended particulate matter.

Wastewater based epidemiology (WBE) has been used worldwide to estimate drug consumption routinely. Even though WBE provides valuable data to support legal and health interventions associated to drug use, monitoring studies in Portuguese wastewaters are scarce. Hence, this work aimed to estimate the consumption of some conventional abuse and illicit drugs such as amphetamine (AMP), methamphetamine (MAMP), 3,4-methylenedioxymethamphetamine (MDMA), and the synthetic cathinones buphedrone (BPD), butylone (BTL), 3,4-dimethylmethcathinone (3,4-DMMC) and 3-methylmethcathinone (3-MMC), considering not only the liquid phase, but also the suspended particulate matter (SPM). Moreover, the enantiomeric profiling of the samples was studied, exploring for the first time the possible enantioselective sorption of these drugs onto SPM. For that, 24 h composite raw wastewaters were collected from a conventional wastewater treatment plant (WWTP) in Portugal. After extraction, the liquid phase and SPM extracts were derivatized with an enantiomerically pure reagent and then, analysed using a gas chromatography-mass spectrometry (GC-MS) analytical method. The results showed a low and non-enantioselective adsorption to SPM at environmental relevant levels. Only (S)-AMP was detected in two SPM samples, whereas AMP, MAMP, MDMA, BPD, and 3,4-DMMC were detected in the liquid phase. AMP was the most frequently found drug with an estimated load up to 166.0 mg day-1 1000 people-1 and mostly found with enrichment of (S)-AMP. Nevertheless, (R)-AMP was also determined, which may be related to the consumption of either the illicit racemic AMP or the medicine (R)-deprenyl. The use of MDMA, MAMP and synthetic cathinones (BPD and 3,4-DMMC) was also suggested in Portugal. Nevertheless, the levels and the consumption estimate of the target chemicals were lower than in other European countries or worldwide. These findings provide the first step to the implementation of WBE monitoring campaigns to assess the status of drug consumption in Portuguese communities, contributing to the understanding of drug use patterns and trends worldwide and helping enforce preventive measures.

Filling the Knowledge Gap Regarding Microbial Occupational Exposure Assessment in Waste Water Treatment Plants: A Scoping Review.

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.

Occurrence and profiles of perfluoroalkyl substances in wastewaters of chemical industrial parks and receiving river waters: Implications for the environmental impact of wastewater discharge.

A total of 17 groups of wastewaters from the chemical industrial parks and matched receiving river waters were collected in the east of China. The measured total concentrations of 21 analyzed PFAS analogues (∑21PFAS) in the influents and effluents of the wastewater treatment plants (WWTPs) were in the range of 0.172-20.6 µg/L (mean: 18.2 µg/L, median: 3.9 µg/L) and 0.167-93.6 µg/L (mean: 10.8 µg/L, median: 1.12 µg/L), respectively, which were significantly higher than those observed in the upstream (range: 0.0158-7.05 µg/L, mean: 1.09 µg/L, median: 0.482 µg/L) and downstream (range: 0.0237-1.82 µg/L, mean: 0.697 µg/L, median: 0.774 µg/L) receiving waters. Despite the concentrations and composition profiles of PFAS varied in the water samples from different sampling sites, PFOA was generally the major PFAS analogue in the research areas, mainly due to the history of PFOA production and usage as well as the specific exemptions. The calculated concentration ratios of the short-chain PFCAs and PFSAs to their respective predecessors (PFOA and PFOS) in most of the samples far exceeded 1, indicating a shift from legacy PFOA and PFOS to short-chain PFAS in the research areas. Correlation network analysis and the calculated concentration ratios of PFAS in the effluents versus influents indicated transformation may have occurred during the water treatment processes and PFAS could not be efficiently removed in the WWTPs. Wastewater discharge of chemical industrial parks is a vital source of PFAS dispersed into the aquatic environment.

Wastewater treatment process enhancement based on multi-objective optimization and interpretable machine learning.

Optimization and control of wastewater treatment process (WTP) can contribute to cost reduction and efficiency. A wastewater treatment process multi-objective optimization (WTPMO) framework is proposed in this paper to provide suggestions for decision-making in setting parameters of WTP. Firstly, the prediction models based on Extreme Gradient Boosting (XGB) with Bayesian optimization (BO) are developed for predicting effluent water quality (EQ) and energy consumption (EC) for different influent quality and process parameter settings. Then, the SHapley Additive exPlanations (SHAP) algorithm is used to complement the interpretability of machine learning to quantitatively evaluate the impact of different features on the predicted targets. Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with the Technique for Ordering Preferences on Similarity of Ideal Solutions (TOPSIS) is introduced to solve and make decisions on the multi-objective optimization problem. The WTPMO applicability is validated on Benchmark Simulation Model 1 (BSM1). The results show that BOXGB achieves accurate prediction for EQ and EC with R2 values of 0.923 and 0.965, respectively, indicating that BO can effectively select the model hyperparameters in XGB. Based on SHAP supplemented the interpretability of the model to fully explain how the influent water quality and decision variables affect the EQ and EC of the WTP. In addition, the optimized process parameters are determined based on NSGA-II and TOPSIS, and the EC optimization rate is 1.552% while guaranteeing water quality compliance. Overall, this research can effectively achieve the optimization of WTP, ensure that the effluent water quality meets the standards while reducing energy consumption, assist Wastewater treatment plants (WWTPs) to achieve more intelligent and efficient operation and maintenance management, and provide strong support for environmental protection and sustainable development goals.

Wastewater surveillance of antibiotic resistance and class 1 integron-integrase genes: Potential impact of wastewater characteristics on genes profile.

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.

Sunscreens Part 2: Regulation and Safety.

The second part of this CME article discusses sunscreen regulation and safety considerations for humans and the environment. First, we provide an overview of the history of the United States Food and Drug Administration's regulation of sunscreen. Recent Food and Drug Administration studies clearly demonstrate that organic ultraviolet filters are systemically absorbed during routine sunscreen use, but to date there is no evidence of associated negative health effects. We also review the current evidence of sunscreen's association with vitamin D levels and frontal fibrosing alopecia, and recent concerns regarding benzene contamination. Finally, we review the possible environmental effects of ultraviolet filters, particularly coral bleaching. While climate change has been shown to be the primary driver of coral bleaching, laboratory-based studies suggest that organic ultraviolet filters represent an additional contributing factor, which led several localities to ban certain organic filters.