Cover illustration
Front Cover Story (See: Lizheng Guo, Xinyan Xiao, Kassim Chabi, Yiting Zhang, Jingjing Li, Su Yao, Xin Yu, 2024, 18(3): 35)
Viable but non-culturable (VBNC) bacteria, colloquially referred to as “The sleeping beauty”, have been detected in source water and effluent of drinking water treatment processes, leading to significant underestimation of viable cell counts. Limited information exists on VBNC bacteria in tap water, particularly in public places. To address this
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● Removal of cesium from radioactive wastewater is still a challenging. ● Main approaches used for waste treatment in Fukushima Daiichi accident were reviewed. ● Kurion/SARRY system + desalination system and ALPS were briefly introduced. ● The removal of cesium by adsorption and membrane separation were summarized.
Radiocesium is frequently present in radioactive wastewater, while its removal is still a challenge due to its small hydrated radius, high diffusion coefficient, and similar chemical behavior to other alkali metal elements with high background concentrations. This review summarized and analyzed the recent advances in the removal of Cs+ from aqueous solutions, with a particular focus on adsorption and membrane separation methods. Various inorganic, organic, and biological adsorbents have undergone assessments to determine their efficacy in the removal of cesium ions. Additionally, membrane-based separation techniques, including reverse osmosis, forward osmosis, and membrane distillation, have also shown promise in effectively separating cesium ions from radioactive wastewater. Additionally, this review summarized the main approaches, including Kurion/SARRY system + desalination system and advanced liquid processing system, implemented after the Fukushima Daiichi nuclear power plant accident in Japan to remove radionuclides from contaminated water. Adsorption technology and membrane separation technology play a vital role in treatment of contaminated water.
● Magnetic Co- γ -Fe2O3/MoS2 were prepared via facile hydrothermal methods. ● Doping γ -Fe2O3 with cobalt greatly increased PMS activation for BPA abatement. ● The compounding of MoS2 significantly enhanced the stability of the catalyst. ● Hybrid radical-nonradical pathways acted for effective degradation of BPA. ● The toxicity of intermediates was lower than BPA via T.E.S.T analysis.
Iron-based catalysts have been widely used to treat refractory organic pollutants in wastewater. In this paper, magnetic Co-γ-Fe2O3 was synthesized by a facile tartaric acid-assisted hydrothermal method, and Co-γ-Fe2O3/MoS2 nanocomposite catalyst was obtained via in situ growth of MoS2 nanosheets on Co-γ-Fe2O3 nanoparticles. The nanocomposite catalysts were used to decompose bisphenol A (BPA) by activating peroxymonosulfate (PMS). It was shown that only 0.15 g/L catalyst and 0.5 mmol/L PMS degraded 10 mg/L of BPA (99.3% within 10 min) in the pH range of 3–9. PMS was activated due to redox cycling among the pairs Co(III)/Co(II), Fe(III)/Fe(II), and Mo(VI)/Mo(IV). Quenching experiments and electron paramagnetic resonance spectroscopy demonstrated that both radical and non-radical pathways were involved in BPA degradation, in which active radical sulfate radical and non-radical singlet oxygen were the main reactive oxygen species. Ten intermediates were identified by liquid chromatography-coupled mass spectrometry, and three possible BPA degradation pathways were proposed. The toxicity of several degradation intermediates was lower, and Co-γ-Fe2O3/MoS2 exhibited excellent reusability and could be magnetically recovered.
● Impact of WWTP effluent discharge on ARGs in downstream waterbodies is hotspot. ● Various mechanisms influence the diffusion of ARGs in effluent-receiving waterbodies. ● Controlling AMR risk of WWTPs needs further investigation and management strategies.
Antimicrobial resistance (AMR) has emerged as a significant challenge in human health. Wastewater treatment plants (WWTPs), acting as a link between human activities and the environment, create ideal conditions for the selection and spread of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). Unfortunately, current treatment processes are ineffective in removing ARGs, resulting in the release of large quantities of ARB and ARGs into the aquatic environment through WWTP effluents. This, in turn, leads to their dispersion and potential transmission to human through water and the food chain. To safeguard human and environmental health, it is crucial to comprehend the mechanisms by which WWTP effluent discharge influences the distribution and diffusion of ARGs in downstream waterbodies. In this study, we examine the latest researches on the antibiotic resistome in various waterbodies that have been exposed to WWTP effluent, highlighting the key influencing mechanisms. Furthermore, recommendations for future research and management strategies to control the dissemination of ARGs from WWTPs to the environment are provided, with the aim to achieve the “One Health” objective.
● The VBNC pathogens were quantified for the first time in public tap water. ● The VBNC pathogens ranged from 1 to 103 cell equivalent/100 mL in tap water. ● Regrowth of pathogenic bacteria was found after long stagnation of tap water. ● Spatial and temporal factors explained 17.1% and 26.0% of the community variation.
Viable but non-culturable (VBNC) bacteria have been detected in source water and effluent of drinking water treatment processes, leading to significant underestimation of viable cell counts. Limited information exists on VBNC bacteria in tap water, particularly in public places. To address this gap, a comprehensive nine-month study was conducted in a major city in south-eastern China, using culture-based and quantitative PCR with propidium monoazide (PMA) dye methods. Forty-five samples were collected from five representative public places (railway station, campus, hospital, shopping mall, and institution). The findings revealed that culturable bacteria represented only 0–17.51% of the viable 16S rRNA genes, suggesting that the majority of viable bacteria existed in an uncultured or VBNC state. Notably, opportunistic pathogens such as Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Salmonella sp., and Shigella sp. were primarily detected as VBNC cells, with concentrations ranging from 1.03 × 100 to 3.01 × 103, 1.20 × 100 to 1.42 × 102, 1.32 × 100 to 8.82 × 100, 1.00 × 100 to 6.71 × 101, and 2.07 × 100 to 1.93 × 102 cell equivalent/100 mL, respectively. Culturable P. aeruginosa was observed in tap water after prolonged stagnation, indicating potential risks associated with bacterial regrowth. Spatial and temporal factors accounted for 17.1% and 26.0%, respectively, of the variation in tap water community structure during the sampling period, as revealed by 16S rRNA amplicon sequencing. This study provides quantitative insights into the occurrence of VBNC bacteria in tap water and highlights the need for more sensitive monitoring methods and microbial control techniques to enhance tap water safety in public locations.
● The appropriate enrichment method for wastewater was assessed. ● Mono-P and Di-P were efficiently removed in biological treatment. ● Mechanism of P-components migration and transformation were established in WWTP.
The migration and transformation of phosphorus components in wastewater treatment plants (WWTPs) play a crucial role in the convergence and circulation of phosphorus. However, the composition and variation of dissolved organic phosphorus (DOP) in WWTPs were unclear because of its complex nature, hindering its efficient detection. In this study, the DOP species and their transformation during the treatment process in WWTP were comprehensively analyzed. First, two enrichment methods were assessed for their effectiveness at facilitating wastewater analysis: lyophilization and aluminum salt precipitation. Aluminum salt precipitation was found to be better because its application allowed 31P nuclear magnetic resonance (31P NMR) spectroscopy to identify more species in the secondary effluent: orthophosphate (Ortho-P) (81.1%–89.3% of the dissolved total phosphorus), pyrophosphates (Pyro-P) (0%–2.3%), orthophosphate monoesters (Mono-P) (7.0%–10.77%), orthophosphate diesters (Di-P) (1.0%–2.96%), and phosphonate (Phos-P) (1.7%–5.16%). Furthermore, the variation and transformation mechanism of phosphorus, particularly those of DOP, during the entire sewage-treatment process were elucidated. Among the treatment steps, biological treatment combined tertiary treatment achieved better DOP removal efficiencies. Therein, biological treatment mainly removed Mono-P and Di-P with removal efficiencies of 33.3% and 41.7% compared with the effluent of the grit chamber. Di-P has higher bioavailability and is more easily converted and utilized by microorganisms than Mono-P. However, Phos-P, with low bioavailability, was hardly utilized by microorganisms, which showed only 18.4% removal efficiency in biological treatment. In tertiary treatment, coagulation process exhibited higher removal ability of Ortho-P (69.1%) and partial removal efficiencies of DOP, resulting in an increase in the DOP proportion in TP. In addition, Phos-P could not be effectively removed through the biological treatment and was only partially reduced via the adsorption process by large particles, zoogloea or multinuclear hydroxyl complexes. The results of this study can provide a theoretical basis for efficient phosphorus removal in WWTPs.
● 83% ± 13% E. coli and 59% ± 27% Enteroco ccus were removed by partial nitrification. ● FNA exposure leads to surface collapse of E. coli and Enterococcus . ● Bacteria inactivation was due to the breakdown of cell walls and cell membranes. ● Enterococcus was more resistant to FNA treatment than E. coli .
Digested wastewater contains pathogenic microorganisms and high ammonia concentrations, which can pose a potential risk to public health. Effective removal of pathogens and nitrogen is crucial for the post-treatment of digested wastewater. Partial nitrification-anammox is an energy-saving nitrogen removal process. Free nitrous acid (FNA), an intermediate product of partial nitrification, has the potential to inactivate microorganisms. However, the efficiency and mechanisms of FNA-related inactivation in pathogens during partial nitrification remains unclear. In this study, Enterococcus and Escherichia coli (E. coli) were selected to investigate the efficiency and mechanisms of FNA-related inactivation in partial nitrification process. The results revealed that 83% ± 13% and 59% ± 27% of E. coli and Enterococcus were removed, respectively, in partial nitrification process at FNA concentrations of 0.023−0.028 mg/L. When the concentration of FNA increased from 0 to 0.5 mg/L, the inactivation efficiencies of E. coli and Enterococcus increased from 0 to 99.9% and 89.9%, respectively. Enterococcus exhibited a higher resistance to FNA attack compared to E. coli. 3D-laser scanning microscopy (3D-LSM) and scanning electron microscopy (SEM) revealed that FNA exposure caused the surface collapse of E. coli and Enterococcus, as well as visible pore formation on the surface of E. coli cells. 4',6-Diamidino-2-phenylindole dihydrochloride n-hydrate (DAPI)/propidium iodide (PI) and biomolecule leakage confirmed that inactivation of E. coli and Enterococcus occurred due to breakdown of cell walls and cell membranes. These findings indicate that partial nitrification process can be used for the removal of residual pathogenic microorganisms.
● Simultaneous water recovery and salt separation from hypersaline brine is feasible. ● Water recovery shows an obvious boundary at saline concentration of 115 g/L. ● Cl– removal is exponentially correlated with specific water extraction efficiency. ● Radical precipitation of Mg2+ and Ca2+ leads to more amine residues in raffinate.
The feasibility of simultaneous water recovery, salt separation and effective descaling of hypersaline brine was investigated by diisopropylamine (DIPA)-based directional solvent extraction (DSE), using diluted/concentrated seawater with initial saline concentration range of 12–237 g/L at extraction temperatures of 5 and 15 °C, respectively. The water recovery shows an obvious boundary at saline concentration of 115 g/L under dual effect of specific water extraction efficiency and extraction cycles. High Cl– ion concentration in product water is in sharp contrast to the nearly complete removal of SO42– and hardness ions, indicating that DIPA-based DSE process indeed achieved efficient separation and purification of Cl– ion from hypersaline brines. Especially, the radical precipitation of Mg2+ and Ca2+ ions in form of Mg(OH)2 and CaCO3 demonstrates effective descaling potential, although it leads to more DIPA residues in dewatered raffinate than product water. Moreover, an exponential correlation between the Cl– removal efficiency and specific water extraction efficiency further reveals the intrinsic relationship of water extraction process and transfer of Cl– ion to the product water. Overall, the study provides a novel approach for integrating the water recovery and separation of Cl– ion from ultra-high-salinity brines with radical precipitation of Mg2+ and Ca2+ ions in one step.
● A novel brain-inspired network accurately predicts sewage effluent quality. ● Sewage-surface images are utilized in data analysis by the model. ● The developed method outperforms traditional ones by reducing error by 23%. ● The model offers the potential for cost-effective monitoring.
Efficiently predicting effluent quality through data-driven analysis presents a significant advancement for consistent wastewater treatment operations. In this study, we aimed to develop an integrated method for predicting effluent COD and NH3 levels. We employed a 200 L pilot-scale sequencing batch reactor (SBR) to gather multimodal data from urban sewage over 40 d. Then we collected data on critical parameters like COD, DO, pH, NH3, EC, ORP, SS, and water temperature, alongside wastewater surface images, resulting in a data set of approximately 40246 points. Then we proposed a brain-inspired image and temporal fusion model integrated with a CNN-LSTM network (BITF-CL) using this data. This innovative model synergized sewage imagery with water quality data, enhancing prediction accuracy. As a result, the BITF-CL model reduced prediction error by over 23% compared to traditional methods and still performed comparably to conventional techniques even without using DO and SS sensor data. Consequently, this research presents a cost-effective and precise prediction system for sewage treatment, demonstrating the potential of brain-inspired models.
● Heterogeneous HONO reactions significantly improve HONO simulation in summer. ● Heterogeneous HONO reactions increase the formation of winter SNA and summer O3. ● NO x emission reduction in BTH both cut down winter SNA and summer MDA8 O3. ● HONO heterogeneous reactions improve NO x reduction benefits in SNA and O3 control.
Substantial NOx emission mitigation is crucial for the synergistic reduction of particulate matter and ozone (O3) pollution in China. The traditional air quality model does not consider heterogeneous HONO chemistry, leading to uncertainties in estimating the benefits of NOx control. Previous studies have shown that the parameterization of heterogeneous HONO formation increases both the simulated value of sulfate–nitrate–ammonium (SNA) and that of O3, thus adding the heterogeneous reactions of HONO into air quality models inevitably leads to changes in the estimated benefits of NOx abatement. Here we investigated the changes in SNA and O3 concentrations from NOx emission reduction before and after adding heterogeneous HONO reactions in the Community Multi-Scale Air Quality (CMAQ) model. Including heterogeneous HONO reactions in the simulation improved the benefits of NOx reduction in terms of SNA control in winter. With 80% NOx reduction, the reduction in SNA increased from 36.9% without considering heterogeneous HONO reactions to 42.8% with heterogeneous HONO chemistry. The reduction in the maximum daily 8h average (MDA8) O3 in summer caused by NOx reduction increased slightly from 4.7% to 5.2% after adding heterogeneous HONO reactions. The results in this study highlight the enhanced effectiveness of NOx controls for the reduction of SNA and O3 after considering heterogeneous HONO formation in a complex chemical ambient, demonstrating the importance of NOx controls in reducing PM2.5 and O3 pollution in China.
● The application of ML in groundwater quality assessment and prediction is reviewed. ● Bibliometric analysis is performed and summarized to promote application. ● The details of the application of ML in GQAP are comprehensively summarized. ● Challenges and opportunities of using ML models in GQAP are discussed.
Groundwater quality assessment and prediction (GQAP) is vital for protecting groundwater resources. Traditional GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally demanding. Recently, the application of machine learning (ML) in GAQP (GQAPxML) has been widely studied due to ML’s reliability and efficiency. While many GQAPxML publications exist, a thorough review is missing. This review provides a comprehensive summary of the development of ML applications in the field of GQAP. First, the workflow of ML modeling is briefly introduced, as are data preparation, model development, model evaluation, and model application. Second, 299 publications related to the topic are filtered, mainly through ML modeling. Subsequently, many aspects of GQAPxML, such as publication trends, the spatial distribution of study areas, the size of data sets, and ML algorithms, are discussed from a bibliometric perspective. In addition, we review in detail the well-established applications and recent findings for several subtopics, including groundwater quality assessment, groundwater quality modeling using groundwater quality parameters, groundwater quality spatial mapping, probability estimation of exceeding the groundwater quality threshold, groundwater quality temporal prediction, and the hybrid use of ML and physics-based models. Finally, the development of GQAPxML is explored from three perspectives: data collection and preprocessing, model building and evaluation, and the broadening of model applications. This review provides a reference for environmental scientists to better understand GQAPxML and promotes the development of innovative methods and improvements in modeling quality.
● Engineered E. coli can use wastewater as the only feedstock to product isoprene. ● Glucose, maltose, glycerol and lactate can be used for isoprene biosynthesis. ● Starch, protein and acetate can’t feed the E. coli growth. ● The optimum C/N ratio and essential nutrients addition enhance isoprene yield. ● The cost and CO2 emission are significantly reduced by using wastewater.
The biosynthesis of isoprene offers a more sustainable alternative to fossil fuel-based approaches, yet its success has been largely limited to pure organic compounds and the cost remains a challenge. This study proposes a waste-to-wealth strategy for isoprene biosynthesis utilizing genetically engineered E. coli bacteria to convert organic waste from real food wastewater. The impact of organic compounds present in wastewater on E. coli growth and isoprene production was systematically investigated. The results demonstrated that with filtration pretreatment of wastewater, isoprene yield, and production achieved 115 mg/g COD and 7.1 mg/(L·h), respectively. Moreover, even without pretreatment, isoprene yield only decreased by ~ 24%, indicating promising scalability. Glucose, maltose, glycerol, and lactate are effective substrates for isoprene biosynthesis, whereas starch, protein, and acetate do not support E. coli growth. The optimum C/N ratio for isoprene production was found to be 8:1. Furthermore, augmenting essential nutrients in wastewater elevated the isoprene yield increased to 159 mg/g COD. The wastewater biosynthesis significantly reduced the cost (44%–53% decrease, p-value < 0.01) and CO2 emission (46%–55% decrease, p-value < 0.01) compared with both sugar fermentation and fossil fuel–based refining. This study introduced a more sustainable and economically viable approach to isoprene synthesis, offering an avenue for resource recovery from wastewater.
● Temperature variability is an independent risk factor of cardiovascular diseases. ● Considerable cardiovascular disease burden can be attributed to HTV. ● The unmarried elderly is more susceptible, particularly in cold seasons. ● The effect of upward TV was acute while the impact of downward TV generally lags.
Relationships between nonoptimal temperatures and cardiovascular disease (CVD) mortality have been well documented. However, evidence of the association between temperature variability (TV) and CVD morbidity is limited. This study aimed to quantify the risk and burden of CVD-related hospitalization associated with the magnitude and direction of TV. Data on meteorology and population-based hospitalizations for myocardial infarction (MI) and stroke were collected in Guangzhou, China, from 2013 to 2017. Hourly temperature variability (HTV) was measured as the standard deviation of hourly temperature records over specific exposure days. The direction (upward or downward) of HTV was defined as the average daily mean temperature change relative to that of the previous day during the exposure period. Quasi-Poisson regression was applied to assess the impact of HTV after adjusting for the daily mean temperature, and the hospitalization fractions attributable to HTV were calculated. A 1 °C-increase in HTV was significantly associated with a 2.24% and 1.72% increase in hospitalizations for MI and hemorrhagic stroke (HS) at lag 0–1 d, respectively, and a 1.55% increase in hospitalizations for ischemic stroke (IS) at lag 0–3 d. During the study period, 5.99%, 4.64%, and 4.53% of MI, HS, and IS hospitalizations, respectively, were attributable to HTV. The upward TV exerts acute effects on CVD hospital admissions, whereas the impact of downward TV generally lags. These findings highlight the importance of the magnitude and direction of temperature fluctuations, in addition to the mean level, in assessing the adverse health impacts of temperature variations.
