Micro(nano)plastics from synthetic oligomers persisting in Mediterranean seawater: Comprehensive NMR analysis, concerns and origins.

The presence in seawater of low-molecular-weight polyethylene (PE) and polydimethylsiloxane (PDMS), synthetic polymers with high chemical resistance, has been demonstrated in this study for the first time by developing a novel methodology for their recovery and quantification from surface seawater. These synthetic polymer debris (SPD) with very low molecular weights and sizes in the nano- and micro-metre range have escaped conventional analytical methods. SPD have been easily recovered from water samples (2 L) through filtration with a nitrocellulose membrane filter with a pore size of 0.45 µm. Dissolving the filter in acetone allowed the isolation of the particulates by centrifugation followed by drying. The isolated SPD were analysed by 1H nuclear magnetic resonance spectroscopy (1H NMR), identifying PE and PDMS. These polymers are thus persisting on seawater because of their low density and the ponderal concentrations were quantified in mg/m3. This method was used in an actual case study in which 120 surface seawater samples were collected during two sampling campaigns in the Mediterranean Sea (from the Gulf of Salerno to the Gulf of Policastro in South Italy). The developed analytical protocol allowed achieving unprecedented simplicity, rapidity and sensitivity. The 1H and 13C NMR structural analysis of the PE debris indicates the presence of oxidised polymer chains with very low molecular weights. Additionally, the origin of those low molecular weight polymers was investigated by analysing influents and effluents from a wastewater treatment plant (WWTP) in Salerno as a hot spot for the release of SPD: the analysis indicates the presence of low molecular weight polymers compatible with wax-PE, widely used for coating applications, food industry, cosmetics and detergents. Moreover, the origin of PDMS debris found in surface seawater can be ascribed to silicone-based antifoamers and emulsifiers.

Bead-Containing Superhydrophobic Nanofiber Membrane for Membrane Distillation.

This study introduces an innovative approach to enhancing membrane distillation (MD) performance by developing bead-containing superhydrophobic sulfonated polyethersulfone (SPES) nanofibers with S-MWCNTs. By leveraging SPES's inherent hydrophobicity and thermal stability, combined with a nanostructured fibrous configuration, we engineered beads designed to optimize the MD process for water purification applications. Here, oxidized hydrophobic S-MWCNTs were dispersed in a SPES solution at concentrations of 0.5% and 1.0% by weight. These bead membranes are fabricated using a novel electrospinning technique, followed by a post-treatment with the hydrophobic polyfluorinated grafting agent to augment nanofiber membrane surface properties, thereby achieving superhydrophobicity with a water contact angle (WCA) of 145 ± 2° and a higher surface roughness of 512 nm. The enhanced membrane demonstrated a water flux of 87.3 Lm-2 h-1 and achieved nearly 99% salt rejection efficiency at room temperature, using a 3 wt% sodium chloride (NaCl) solution as the feed. The results highlight the potential of superhydrophobic SPES nanofiber beads in revolutionizing MD technology, offering a scalable, efficient, and robust membrane for salt rejection.

Integrating artificial intelligence modeling and membrane technologies for advanced wastewater treatment: Research progress and future perspectives.

Membrane technologies have become proficient alternatives for advanced wastewater treatment, ensuring high contaminant removal and sustainable resource recovery. Despite significant progress, ongoing research efforts aim to further optimize treatment performance. Among the challenges faced, membrane fouling persists as a relevant obstacle in membrane technologies, necessitating the development of more effective mitigation strategies. Mathematical models, widely employed for predicting treatment performance, generally exhibit low accuracy and suffer from uncertainties due to the complex and variable nature of wastewater. To overcome these limitations, numerous studies have proposed artificial intelligence (AI) modeling to accurately predict membrane technologies' performance and fouling mechanisms. This approach aims to provide advanced simulations and predictions, thereby enhancing process control, optimization, and intensification. This literature review explores recent advancements in modeling membrane-based wastewater treatment processes through AI models. The analysis highlights the enormous potential of this research field in enhancing the efficiency of membrane technologies. The role of AI modeling in defining optimal operating conditions, developing effective strategies for membrane fouling mitigation, enhancing the performance of novel membrane-based technologies, and improving membrane fabrication techniques is discussed. These enhanced process optimization and control strategies driven by AI modeling ensure improved effluent quality, optimized resource consumption, and minimized operating costs. The potential contribution of this cutting-edge approach to a paradigm shift toward sustainable wastewater treatment is examined. Finally, this review outlines future perspectives, emphasizing the research challenges that require attention to overcome the current limitations hindering the integration of AI modeling in wastewater treatment plants.

Electro living membrane bioreactor for highly efficient wastewater treatment and fouling mitigation: Influence of current density on process performances.

The next generation of the self-forming dynamic membrane, referred to in this study as the "Living Membrane (LM)", is a new patented technology based on an encapsulated biological layer that self-forms on a designed coarse-pore size support material during wastewater treatment and acts as a natural membrane filter. Integrating electrochemical processes with wastewater treatment using the LM approach has also been recently studied (the reactor is referred to as the Electro-Living Membrane Bioreactor or e-LMBR). This study investigated the effects of varying current densities, i.e., 0.3, 0.5, and 0.9 mA/cm2, on the performance of an e-LMBR. The results were also compared with those of the Living Membrane Bioreactor or LMBR (without applied current density). Higher pollutant removals were observed in the presence of the electric field. However, the effect of varying applied current densities on the COD (98-99 %), NH3-N (97-99 %), and PO43-P (100 %) removals was not statistically significant. The more prominent differences (p < 0.05) were observed in the decrease of NO3--N concentrations from mixed liquor to effluent, with increasing current density resulting in lower mean NO3--N effluent concentrations (0.3 mA/cm2: 6.13 mg/L; 0.5 mA/cm2: 4.38 mg/L; 0.9 mA/cm2: 3.70 mg/L). The reduction of NO3--N concentrations as wastewater permeated through the LM layer also confirmed its role in removing nitrogen-containing compounds. Higher current densities resulted in lower concentrations of fouling substances, particularly those of microbial extracellular polymeric substances (EPS) and transparent exopolymer particles (TEPs). The average values of the temporal variation of transmembrane pressure (d(TMP)/d(t)) in the e-LMBR were extremely low, in the range of 0.013-0.041 kPa/day, throughout the operation period. The highest (d(TMP)/d(t)) was observed for the highest current density. However, the TMP values remained below 2 kPa in all the e-LMBR runs even after the initial LM formation stage.

Microalgae to biodiesel: A novel green conversion method for high-quality lipids recovery and in-situ transesterification to fatty acid methyl esters.

Greenhouse gases (GHGs) emissions due to increasing energy demand have raised the need to identify effective solutions to produce clean and renewable energy. Biotechnologies are an effective platform to attain green transition objectives, especially when synergically integrated to promote health and environmental protection. In this context, microalgae-based biotechnologies are considered among the most effective tools for treating gaseous effluents and simultaneously capturing carbon sources for further biomass valorisation. The production of biodiesel is regarded as a promising avenue for harnessing value from residual algal biomass. Nonetheless, the existing techniques for extracting lipids still face certain limitations, primarily centred around the cost-effectiveness of the process.This study is dedicated to developing and optimising an innovative and cost-efficient technique for extracting lipids from algal biomass produced during gaseous emissions treatment based on algal-bacterial biotechnology. This integrated treatment technology combines a bio-scrubber for degrading gaseous contaminants and a photobioreactor for capturing the produced CO2 within valuable algal biomass. The cultivated biomass is then processed with the process newly designed to extract lipids simultaneously transesterificated in fatty acid methyl esters (FAME) via In Situ Transesterification (IST) with a Kumagawa-type extractor. The results of this study demonstrated the potential application of the optimised method to overcome the gap to green transition. Energy production was obtained from residuals produced during the necessary treatment of gaseous emissions. Using hexane-methanol (v/v = 19:1) mixture in the presence KOH in Kumagawa extractor lipids were extracted with extraction yield higher than 12% and converted in fatty acid methyl esters. The process showed the enhanced extraction of lipids converted in bio-sourced fuels with circular economy approach, broadening the applicability of biotechnologies as sustainable tools for energy source diversification.

Carbon neutrality in wastewater treatment plants: An integrated biotechnological-based solution for nutrients recovery, odour abatement and CO2 conversion in alternative energy drivers.

Wastewater treatment plants play a crucial role in water security and sanitation, ensuring ecosystems balance and avoiding significant negative effects on humans and environment. However, they determine also negative pressures, including greenhouse gas and odourous emissions, which should be minimized to mitigate climate changes besides avoiding complaints. The research has been focused on the validation of an innovative integrated biological system for the sustainable treatment of complex gaseous emissions from wastewater treatment plants. The proposed system consists of a moving bed biofilm reactor coupled with an algal photobioreactor, with the dual objective of: i) reducing the inlet concentration of the odourous contaminants (in this case, hydrogen sulphide, toluene and p-xylene); ii) capturing and converting the carbon dioxide emissions produced by the degradation process into exploitable algal biomass. The first reactor promoted the degradation of chemical compounds up to 99.57% for an inlet load (IL) of 22.97 g m-3 d-1 while the second allowed the capture of the CO2 resulting from the degradation of gaseous compounds, with biofixation rate up to 81.55%. The absorbed CO2 was converted in valuable feedstocks, with a maximum algal biomass productivity in aPBR of 0.22 g L-1 d-1. Dairy wastewater has been used as alternative nutrient source for both reactors, with a view of reusing wastewater while cultivating biomass, framing the proposed technology in a context of a biorefinery within a circular economy perspective. The biomass produced in the algal photobioreactor was indeed characterized by a high lipid content, with a maximum percentage of lipids per dry weight biomass of 35%. The biomass can therefore be exploited for the production of alternative and clean energy carrier. The proposed biotechnology represents an effective tool for shifiting the conventional plants in carbon neutral platform for implementing principles of ecological transition while achieving high levels of environmental protection.

The concept of food waste and food loss prevention and measuring tools.

Food waste (FW) has become a global concern, with an estimated 1.3 billion tonnes lost annually, costing about $1 trillion. Environmental and social consequences of FW are significant, contributing to 6% of European Unions' greenhouse gasemissions and affecting global food security. FW occurs is a complex issue occurring at various stages of the food supply chain (FSC) and is influenced by multiple factors such as infrastructure, available knowledge and socio-economic conditions. Developed countries FW is more prevalent at the consumption stage, whereas in the developing countries losses occur in agricultural production, post-harvest and distribution stage. Accurate quantification of FW across the supply chain is crucial and monitoring key performance indicators helps identify areas for improvement. The European Union mandates FW measurement, aligning with sustainable development goals, emphasizing the need for effective waste prevention measures. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach was utilized to conduct a systematic literature review on FW key performance indicators (KPIs) and monitoring tools. The research identified 22 KPIs, categorized into three levels of the FSC: primary, secondary and tertiary. The most common KPIs included FW per capita, FW per portion and FW percentage. The study further discusses FW prevention measures and essential monitoring tools for addressing FW throughout the supply chain.

Mobilisation of textile waste to recover high added value products and energy for the transition to circular economy.

The textile industry is a major contributor to global waste, with millions of tons of textiles being discarded annually. Material and energy recovery within circular economy offer sustainable solutions to this problem by extending the life cycle of textiles through repurposing, recycling, and upcycling. These initiatives not only reduce waste but also contribute to the reduction of the demand for virgin materials (i.e. cotton, wool), ultimately benefiting the environment and society. The circular economy approach, which aims to recreate environmental, economic, and societal value, is based on three key principles: waste reduction, material circulation, and ecological restoration. Given these difficulties, circularity incorporates the material recovery approach, which is focused on the conversion of waste into secondary raw resources. The goal of this notion is to extract more value from resources by prolonging final disposal as long as feasible. When a textile has outlived its functional life, material recovery is critical for returning the included materials or energy into the manufacturing cycle. The aim of this paper is to examine the material and energy recovery options of main raw materials used in the fashion industry while highlighting the need of close observation of the relation between circularity and material recovery, including the investigation of barriers to the transition towards a truly circular fashion industry. The final results refer to the main barriers of circular economy transition within the industry and a framework is proposed. These insights are useful for academia, engineers, policy makers and other key stakeholders for the clear understanding of the industry from within and highlight beyond circular economy targets, SDGs interactions with energy and material recovery of textile waste (SDG 7, SDG 11, SDG 12 etc.).

Novel eco-friendly polylactic acid nanocomposite integrated membrane system for sustainable wastewater treatment: Performance evaluation and antifouling analysis.

Water contamination caused by heavy metals, nutrients, and organic pollutants of varying particle sizes originating from domestic and industrial processes poses a significant global challenge. There is a growing concern, particularly regarding the presence of heavy metals in freshwater sources, as they can be toxic even at low concentrations, posing risks to human health and the environment. Currently, membrane technologies are recognized as effective and practical for treating domestic and industrial wastewater. However, these technologies are hindered by fouling issues. Furthermore, the utilization of conventional membranes leads to the accumulation of non-recyclable synthetic polymers, commonly used in their production, resulting in adverse environmental consequences. In light of our previously published studies on environmentally friendly, biodegradable polylactic acid (PLA) nanocomposite mixed matrix membranes (MMMs), we selected two top-performing PLA-based ultrafiltration nanocomposite membranes: one negatively charged (PLA-M-) and one positively charged (PLA-M+). We integrated these membranes into systems with varying arrangements to control fouling and eliminate heavy metals, organic pollutants, and nutrients from raw municipal wastewater collected by the local wastewater treatment plant in Abu Dhabi (UAE). The performance of two integrated systems (i.e., PLA-M+/PLA-M- and PLA-M-/PLA-M+) was compared in terms of permeate flux, contaminant removal efficiencies, and fouling mitigation. The PLA-M+/PLA-M- system achieved removal efficiencies of 79.6 %, 92.6 %, 88.7 %, 85.2 %, 98.9 %, 94 %, 83.3 %, and 98.3 % for chemical oxygen demand (COD), nitrate (NO3--N), phosphate (PO43--P), ammonium (NH4+-N), iron (Fe), zinc (Zn), nickel (Ni), and copper (Cu), respectively. On the other hand, the PLA-M-/PLA-M+ system recorded removal efficiencies of 85.8 %, 95.9 %, 100 %, 81.9 %, 99.3 %, 91.9 %, 72.9 %, and 98.9 % for COD, NO3--N, PO43--P, NH4+-N, Fe, Zn, Ni, and Cu, respectively. Notably, the PLA-M-/PLA-M+ system demonstrated superior antifouling resistance, making it the preferred integrated system. These findings demonstrate the potential of eco-friendly PLA nanocomposite UF-MMMs as a promising alternative to petroleum-based polymeric membranes for efficient and sustainable wastewater treatment.

Membrane reciprocation and quorum quenching: An innovative combination for fouling control and energy saving in membrane bioreactors.

Membrane bioreactors (MBRs) play a crucial role in wastewater treatment, but they face considerable challenges due to fouling. To tackle this issue, innovative strategies are needed. This study investigated the effectiveness of membrane reciprocation and quorum quenching (QQ) to control fouling in MBRs. The study compared MBRs using membrane reciprocation (30 rpm) and QQ (injecting media containing 100 or 200 mg/L BH4) with conventional MBRs employing different air-scouring intensities. The results demonstrated that combining membrane reciprocation (30 rpm) with QQ (200 mg/L BH4) significantly extended the service time of MBRs, making it approximately six times longer than conventional methods. Moreover, this approach reduced physically reversible resistance. The reduction in signal molecules related to biofouling due to QQ showcased its critical role in controlling biofouling, even under high shear caused by membrane reciprocation. However, the impact of QQ on microbial community structure appeared relatively insignificant when compared to factors such as operation time, aeration intensity, and membrane reciprocation. By combining membrane reciprocation and QQ, the study achieved a remarkable 81 % energy saving compared to extensive aeration (103 s-1 in velocity gradient), in addition to the extended service time. Importantly, this combined antifouling approach did not negatively affect microbial characteristics and wastewater treatment, emphasizing its effectiveness in MBRs. Overall, the findings of this study offer valuable insights for developing synergistic fouling control strategies in MBRs, significantly improving the energy efficiency of the wastewater treatment process.

Insights into the structures and properties of dyes in the Fenton catalytic process for treating wastewater effluent.

A notable level of apprehension exists over the adverse impacts of dye pollution on aquatic ecosystems and human well-being. The primary objective of this research is to assess the effectiveness of Fenton catalytic reactions in degrading 14 different commercial azo dyes (both single and double) present in aqueous solutions. The investigation focused on the function of dye structures, using a combination of experimental data and examination of theoretical factors. Dye degradation process was carried out at pH 3, and the concentrations of Fe2+ (10-4 mol/L), H2 O2 (2 × 10-3 mol/L), and dye (0.05 g/L). The findings revealed that dyes with a larger molecular weight were more effective at degrading (D%), with the overall degradation efficiency varying from 0% to 94%. Functional groups played an important role in degradation efficiency; for example, dyes with higher aromatic rings led to less D%, while a higher number of sulfonic, methyl, and nitro groups was responsible for better D%. Notably, the presence of OH groups in the backbone of dyes (AB 24, ABE 113, and MB 9) formed the Fe complex during the catalytic process, and the D% was minimal. On the other hand, theoretical quantum calculations such as the greater the JCLogP, highest occupied molecular orbital, and Dipole moment value, the higher the degradation efficiency. And dyes with low lowest unoccupied molecular orbital tended to have a better degradation efficiency. To some extent, UV-Vis spectral analysis was investigated to determine the degradation pathway, and the pseudo-second-order kinetic model fitted better in the degradation process. The overall experimental and theoretical findings suggested that dye degradation efficiency by the Fenton process is structure-dependent. PRACTITIONER POINTS: Insights into the role of azo dye structures-properties on degradation efficiency. Higher molecular weight and sulfonic groups containing dyes showed better degradation efficiency. Hydroxyl groups play the formation of the Fe complex during the degradation process. Higher values of HOMO and lower values of LUMO enhanced degradation efficiency. The pseudo-second-order (PSO) kinetic model obeyed the Fenton process.

Effective stabilization of per- and polyfluoroalkyl substances (PFAS) precursors in wastewater treatment sludge by surfactant-modified clay.

The application of biosolids or treated sewage sludge containing per- and polyfluoroalkyl substances (PFAS) in agricultural lands and the disposal of sludge in landfills pose high risks to humans and the environment. Although PFAS precursors have not been regulated yet, their potential transformation to highly regulated perfluoroalkyl acids (PFAAs) may enable them to serve as a long-term source and make remediation of PFAAs a continuing task. Therefore, treating precursors in sewage sludge is even more, certainly not less, critical than treating or removing PFAAs. In this study, a green surfactant-modified clay sorbent was evaluated for its efficacy in stabilizing two representative PFAA precursors in sludge, e.g., N-ethyl perfluorooctane sulfonamido acetic acid (N-EtFOSAA) and 6:2 fluorotelomer sulfonic acid (6:2 FTSA), in comparison with unmodified clay and powdered activated carbon (PAC). Results showed N-EtFOSAA and 6:2 FTSA exhibited distinct adsorption behaviors in the sludge without sorbents due to their different physicochemical properties, such as hydrophobicity and functional groups. Among the three sorbents, the modified clay reduced the water leachability of N-EtFOSAA and 6:2 FTSA by 91.5% and 95.4%, respectively, compared to controls without amendments at the end of the experiment (47 days). Within the same duration, PAC decreased the water leachability of N-EtFOSAA and 6:2 FTSA by 60.6% and 37.3%, respectively. At the same time, the unmodified clay demonstrated a poor stabilization effect and even promoted the leaching of precursors. These findings suggested that the modified clay had the potential for stabilization of precursors, while negatively charged and/or hydrophilic sorbents, such as the unmodified clay, should be avoided in the stabilization process. These results could provide valuable information for developing effective amendments for stabilizing PFAS in sludge or biosolids. Future research should evaluate the long-term effect of the stabilization approach using actual sludge from wastewater treatment facilities.

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye.

There has been a lot of attention on water pollution by dyes in recent years because of their serious toxicological implications on human health and the environment. Therefore, the current study presented a novel polyethylene glycol-functionalized graphene oxide/chitosan composite (PEG-GO/CS) to remove dyes from aqueous solutions. Several characterization techniques, such as SEM, TEM, FTIR, TGA/DTG, XRD, and XPS, were employed to correlate the structure-property relationship between the adsorption performance and PEG-GO/CS composites. Taguchi's (L25) approach was used to optimize the batch adsorption process variables [pH, contact time, adsorbent dose, and initial concentration of methyl orange (MO)] for maximal adsorption capacity. pH = 2, contact time = 90 min, adsorbent dose = 10 mg/10 mL, and MO initial concentration = 200 mg/L were found to be optimal. The material has a maximum adsorption capacity of 271 mg/g for MO at room temperature. With the greatest R2 = 0.8930 values, the Langmuir isotherm model was shown to be the most appropriate. Compared to the pseudo-first-order model (R2 = 0.9685), the pseudo-second-order model (R2 = 0.9707) better fits the kinetic data. Electrostatic interactions were the dominant mechanism underlying MO sorption onto the PEG/GO-CS composite. The as-synthesized composite was reusable for up to three adsorption cycles. Thus, the PEG/GO-CS composite fabricated through a simple procedure may remove MO and other similar organic dyes in real contaminated water.

Optimization and prediction of the cotton fabric dyeing process using Taguchi design-integrated machine learning approach.

The typical textile dyeing process calls for a wide range of operational parameters, and it has always been difficult to pinpoint which of these qualities is the most important in dyeing performance. Consequently, this research used a combined design of experiments and machine learning prediction models' method to offer a sustainable and beneficial reactive cotton fabric dyeing process. To be more precise, we built a least square support vector regression (LSSVR) model based on Taguchi's statistical orthogonal design (L27) to predict exhaustion percentage (E%), fixation rate (F%), and total fixation efficiency (T%) and color strength (K/S) in the reactive cotton dyeing process. The model's prediction accuracy was assessed using many measures, including root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Principal component regression (PCR), partial least square regression (PLSR), and fuzzy modelling were some of the other types of regression models used to compare results. Our findings reveal that the LSSVR model greatly outperformed competing models in predicting the E%, F%, T%, and K/S. This is shown by the LSSVR model's much smaller RMSE and MAE values. Overall, it provided the highest possible R2 values, which reached 0.9819.

Electrospun nanofiber membrane diameter prediction using a combined response surface methodology and machine learning approach.

Despite the widespread interest in electrospinning technology, very few simulation studies have been conducted. Thus, the current research produced a system for providing a sustainable and effective electrospinning process by combining the design of experiments with machine learning prediction models. Specifically, in order to estimate the diameter of the electrospun nanofiber membrane, we developed a locally weighted kernel partial least squares regression (LW-KPLSR) model based on a response surface methodology (RSM). The accuracy of the model's predictions was evaluated based on its root mean square error (RMSE), its mean absolute error (MAE), and its coefficient of determination (R2). In addition to principal component regression (PCR), locally weighted partial least squares regression (LW-PLSR), partial least square regression (PLSR), and least square support vector regression model (LSSVR), some of the other types of regression models used to verify and compare the results were fuzzy modelling and least square support vector regression model (LSSVR). According to the results of our research, the LW-KPLSR model performed far better than other competing models when attempting to forecast the membrane's diameter. This is made clear by the much lower RMSE and MAE values of the LW-KPLSR model. In addition, it offered the highest R2 values that could be achieved, reaching 0.9989.

Biological desulfurization of biogas: A comprehensive review on sulfide microbial metabolism and treatment biotechnologies.

Hydrogen sulphide (H2S) removal from biogas is of high relevance as it damages combustion engines used for heat and power generation and causes adverse public health and environmental effects. Biological processes have been reported as a cost-effective and promising approach to desulfurize biogas. This review presents a detailed description of the biochemical foundations of the metabolic apparatus of H2S oxidizing bacteria, namely chemolithoautotrophs and anoxygenic photoautotrophs. The review focuses on the current and future applications of biological processes for biogas desulfurization and provides insights into their mechanism and main factors influencing their performance. The advantages, drawbacks, limitations, and technical improvements of the biotechnological applications currently based on chemolithoautotrophic organisms are covered extensively. Recent advances, sustainability and economical aspects of biological biogas desulfurization are also discussed. Anoxygenic photoautotrophic-bacteria-based photobioreactors were herein identified as useful tools to improve the sustainability and safety of biological biogas desulfurization. The review addresses gaps in the existing studies concerning the selection of the most suitable desulfurization techniques, their benefits and consequences. The research is useful for all stakeholders involved in the management and optimization of biogas and its findings are directly applicable in the development of new sustainable technologies for biogas upgrading processes on waste treatment plants.

Microbial Fuel Cell Construction Features and Application for Sustainable Wastewater Treatment.

A microbial fuel cell (MFC) is a system that can generate electricity by harnessing microorganisms' metabolic activity. MFCs can be used in wastewater treatment plants since they can convert the organic matter in wastewater into electricity while also removing pollutants. The microorganisms in the anode electrode oxidize the organic matter, breaking down pollutants and generating electrons that flow through an electrical circuit to the cathode compartment. This process also generates clean water as a byproduct, which can be reused or released back into the environment. MFCs offer a more energy-efficient alternative to traditional wastewater treatment plants, as they can generate electricity from the organic matter in wastewater, offsetting the energy needs of the treatment plants. The energy requirements of conventional wastewater treatment plants can add to the overall cost of the treatment process and contribute to greenhouse gas emissions. MFCs in wastewater treatment plants can increase sustainability in wastewater treatment processes by increasing energy efficiency and reducing operational cost and greenhouse gas emissions. However, the build-up to the commercial-scale still needs a lot of study, as MFC research is still in its early stages. This study thoroughly describes the principles underlying MFCs, including their fundamental structure and types, construction materials and membrane, working mechanism, and significant process elements influencing their effectiveness in the workplace. The application of this technology in sustainable wastewater treatment, as well as the challenges involved in its widespread adoption, are discussed in this study.

Unraveling microbial community by next-generation sequencing in living membrane bioreactors for wastewater treatment.

This study delves into the microbial community complexity and its role in self-forming dynamic membrane (SFDM) systems, designed to remove nutrients and pollutants from wastewater, by means of the analysis of Next-Generation Sequencing (NGS) data. In these systems, microorganisms are naturally incorporated into the SFDM layer, which acts as a biological and physical filter. The microorganisms present in an innovative and highly efficient aerobic, electrochemically enhanced, encapsulated SFDM bioreactor were studied to elucidate the nature of the dominant microbial communities present in sludge and in encapsulated SFDM, patented as living membrane® (LM) of the experimental setup. The results were compared to those obtained from the microbial communities found in similar experimental reactors without an applied electric field. The data gathered from the NGS microbiome profiling showed that the microbial consortia found in the experimental systems are comprised of archaeal, bacterial, and fungal communities. However, the distribution of the microbial communities found in e-LMBR and LMBR had significant differences. The results showed that the presence of an intermittently applied electric field in e-LMBR promotes the growth of some types of microorganisms (mainly electroactive microorganisms) responsible for the highly efficient treatment of the wastewater and for the mitigation of the membrane fouling found for those bioreactors.

Environmental and health impacts of PFAS: Sources, distribution and sustainable management in North Carolina (USA).

Poly- and perfluoroalkyl substances (PFAS) are a class of manufactured chemicals that have recently attracted a great deal of attention from environmental regulators and the general public because of their high prevalence, resistance to degradation, and potential toxicity. This review summarizes the current state of PFAS and its effects on the environment of North Carolina, USA. Specific emphasis has been placed to identify i) the sources of PFAS in North Carolina ii) distribution of PFAS in different environmental segments of North Carolina, including surface water, groundwater, air, and sediment iii) drinking water contamination iv) impact of PFAS on human health v) PFAS accumulation in fish and other biota vi) status of PFAS removal from drinking water and finally vi) socioeconomic impact of PFAS uncertainties. Continuous discharges of PFAS occur in the North Carolina environment from direct and indirect sources, including manufacturing sites, firefighting foam, waste disposal and treatment plants, landfill leachate, and industrial emissions. PFAS are widespread in many environmental segments of North Carolina. They are more likely to be detected in surface and groundwater sediments and can enter aquatic bodies through direct discharge and wet and dry deposition of emissions. Eventually, some adverse effects of PFAS have already been reported in North Carolina residents who could have been exposed to the chemicals through contaminated drinking water. Furthermore, PFAS were also found in blood samples from fish and alligators. PFAS were confirmed to be present in water, sediment, organic compounds, and aquatic species at all levels of the food web. However, there is still a substantial amount of work to be done to understand the actual contamination by PFAS in North Carolina comprehensively.