Filter Layer Research Articles

MFF-Net: A multitask feature fusion network in dual-frequency domains for detecting smoke from one single picture

The industrial smoke detection is extreme significant for sustainable development and human health, but up to date, its related technologies have not met the real-time and accurate requirements, particularly in the memory-constrained conditions. Towards detecting smoke from one single picture more accurate and efficient, in this paper we present a multitask feature fusion network, dubbed MFF-Net. To specify, according to the characteristics of imbalance found in the frequency distribution of numerous smoke pictures, our MFF-Net is set up with a dual-channel framework, which is composed of the high-frequency and low-frequency channels that process different frequency components respectively. The high-frequency channel is built based on a stream of cross-level fusion inverted residual (CFIR) blocks, each of which encompasses the expansion layer, filtering layer, combination layer, and fusion layer, while the low-frequency channel is formed by embedding the attention mechanism into CFIR blocks. We concatenate the dual channels mentioned above to establish the MFF-Net, in order to systematically fuse high- and low-frequency features of a single smoke picture. As compared with the existing relevant detection models, the depthwise and pointwise convolutions are utilized to make networks more efficient with respect to size and speed, while the dense skip connection is used behind to fuse cross-level features (i.e., semantic and visual features) for keeping high accuracy. Experimental results show that our proposed MFF-Net can trade off multiple tasks in accuracy, memory and computational efficiency.

Effect of Fe(II) on manganese removal in biofilters: Microbial community, formation of manganese oxide and related mechanisms

In this study, different concentrations of Fe(II) (0, 1.00, 7.00 mg/L) were introduced to investigate the effect on the removal of Mn(II) in the biofilter. Fe(II) significantly inhibited the removal of Mn and prolonged the start-up of biofilters, the start-up periods for the biofilters with different Fe(II) concentrations (0, 1.00 and 7.00 mg/L) were 24, 30 and 46 days, respectively. The study showed that Fe(II) and the Fe(III) oxyhydroxides generated from Fe(II) oxidation inhibited the removal of Mn(II) by affecting the proliferation of manganese-oxidizing bacteria (MnOB) and the activity of manganese oxides (MnOx) in the biofilter. On day 20, the total MnOB genera proportions were 13.44 %, 13.35 % and 20.09 % with different Fe(II) concentrations (0, 1.00, 7.00 mg/L), respectively. The addition of Fe(II) significantly impeded the proliferation of Pseudomonas, Acinetobacter and Arthrobacter, but enhanced the proliferation of Hyphomicrobium and Sphingopyxis. On day 60, the abundance of total MnOB was reduced obviously in three biofilters (6.95 %, 6.44 % and 9.76 %). This indicated that the biological oxidation of Mn dominates during the initial operation stage of the filter layer, while the chemical auto-catalytic oxidation of active MnOx dominates in the later stages. The contribution of Mn removal by biological oxidation was positively correlated with the abundance of MnOB, and batch experiments confirmed this conclusion. Moreover, the addition of Fe(II) reduced MnOx activity by suppressing the production of high-reactivity intermediate-Mn(III), and Fe(III) oxyhydroxides hindered the formation of mature MnOx films on the surface of the filter media.

Importance of process design on carbon footprint from drinking water treatment by enhanced coagulation-filtration

Abstract There are several process design options for enhanced coagulation-filtration in drinking water treatment plants (DWTPs). This study compares the carbon footprint and economic impact of two common process designs based on enhanced coagulation-filtration with pH, Ca, and alkalinity adjustment for corrosion control. The process designs are direct filtration (DF) using Al coagulant with limewater (DF-Al) and contact filtration (CF) using Fe coagulant with alkaline filter layers (CF-Fe). The operational data are retrieved from full-scale DWTPs. The results show that the carbon footprint from operations is five times larger for the DF-Al compared to the CF-Fe. Operational costs covering chemicals and energy are almost 30% higher for the DF-Al. Simplified material intensity estimations for the construction phase show that the carbon footprint and investment cost increase with increasing process area, which are larger for the DF-Al. Therefore, to reduce environmental impacts and costs, the design of drinking water treatment processes should be carefully considered even for very similar processes. The results should motivate both water professionals and decision-makers to include a carbon footprint evaluation as a routine step in the DWTP selection and design phases.

Numerical simulation of dual-layer granular bed filtration based on particle collision rebound effect

This article established a dual-layer granular bed filtration model based on the dust collision rebound effect and investigated the influence of dust properties and filtration air velocity on the collision rebound effect and grade efficiencies of the filter layers. The results indicated that the characteristics of dust particle size, density, and effective Young's modulus had a significant impact on the critical adhesion velocity and collision rebound effect. Large dust particle size, density, and small effective Young's modulus resulted in a larger collision rebound effect. The collision rebound effect led to a decrease in grade efficiencies of each filter layer and the dual-layer granular bed with an increase in filtration velocity. To reveal the impact of the collision rebound effect on the movement of dust in the filter material layer, the trajectory and velocity changes of dust in the granule layer were simulated and calculated. The results show that the collision rebound effect caused the dust to repeatedly collide and rebound within the granular bed, penetrating deeper into the granular bed and increasing dust escape.

Research on flow and heat transfer at different positions in CDPF channel based on three-dimensional thermal LBM

To explore the flow, heat transfer and oxidative regeneration mechanism of the porous media of the catalytic diesel particulate filter at the pore scale, catalytic diesel particulate filter and particulate layer structure were built using three-dimensional reconstruction technology of Micro-CT and the Quartet Structure Generation Set. A heat source term was added to the mathematical model to simulate the temperature field during the oxidative regeneration of the particulate layer. The effects of different wall structures at five different positions, air inlet velocities and particulate layer parameters on the porous media were analyzed. The results show that in the clean cordierite porous medium structures, the larger the structural porosity, the greater the average velocity at the inlet of the porous medium wall. In the porous medium wall structures loaded with particulate layers, the particulate layer has a weakening effect on the velocity field above the particulate layer porous media. As the porosity of the particulate layer decreases, the temperature rise increases. When the particulate layers are oxidized, a temperature peak is generated at the inlet of the wall porous media. As the porosity of the particulate layer decreases, the temperature peak increases during oxidative regeneration.

Capturing the diffusive behavior of the multiscale linear transport equations by Asymptotic-Preserving Convolutional DeepONets

In this paper, we introduce two types of novel Asymptotic-Preserving Convolutional Deep Operator Networks (APCONs) designed to solve the multiscale time-dependent linear transport equations. We observe that the vanilla physics-informed DeepONets with modified MLP may exhibit instability in maintaining the desired limiting macroscopic behavior. Therefore, this necessitates the utilization of an asymptotic-preserving loss function. Drawing inspiration from the heat kernel in the diffusion equation, we propose a new architecture called Convolutional Deep Operator Networks, which employs multiple local convolution operations instead of a global heat kernel, along with pooling and activation operations in each filter layer. Our APCON methods possess a parameter count that is independent of the grid size and are capable of capturing the diffusive behavior of the linear transport problem. Finally, we validate the effectiveness of our methods through several numerical examples.

Study on denitrification of hydroponic wastewater reverse osmosis concentrate using sulfur-autotrophic denitrification

Hydroponic agriculture is one of the sectors that generate the highest amounts of nitrogen-containing wastewater. Sulfur-autotrophic denitrification is considered a promising technology due to its stable and excellent denitrification performance, cost-effectiveness, and operational advantages. In order to investigate the denitrification performance and the contribution of the filter layer under high NO3--N concentration (600 mg·L−1), this experiment designed a denitrification system using Na2S2O3 as an electron donor. The results showed that the reactor achieved the highest denitrification efficiency with a hydraulic retention time of 12 h, pH of 7, and sulfur to nitrogen ratio of 2, maintaining a stable NO3--N removal efficiency of 99%. The majority of NO3--N was removed by the bottom filter layer (0–300 mm), accounting for 86% of the total denitrification. The microbial community in the lower part of the filter column was dominated by Proteobacteria, with relatively high abundances of the genera Chryseobacterium, Thiobacillus, and Sulfurimonas. Similarly, the microbial community structure in the upper filter layer was dominated by Proteobacteria, with an increased abundance of the genus Chryseobacterium and a significant reduction in the abundance of Sulfurimonas. The study indicates that SAD can achieve stable and efficient denitrification of wastewater from hydroponic reverse osmosis concentrate. Moreover, higher NO3--N concentrations can influence the bacterial community structure within the reactor.

Filtration efficiency and breathability of selected face masks

Face masks have been used as physical barriers to stop respiratory infections for many years. Due to insufficient and low supply of certified masks, alternative face covers such as face shields, neck gaiters, and fabric reusable masks gained attention during the COVID-19 pandemic. However, for these alternate face masks to fulfill their intended function, they must be effective. Additionally, the level of breathability provided by the makeshift masks must be at a certain level. The work reported in this paper was carried out to determine the relationship between filtration efficiency (FE), breathability, and important physical characteristics of mask substrates. The fiber diameter of the core filter layer was determined using a scanning electron microscope. Five types of face masks (two types of N95, two types of surgical masks, and a 100% knitted cotton fabric) were tested for their FE and breathability using moisture vapor transmission rate (MVTR). The cotton knitted mask had the lowest FE (5.10%–26.47%), while the National Institute for Occupational Safety and Health (NIOSH)-certified N95 mask had the highest FE values (92.10%–99.65%). However, the cotton mask outperformed the N95 in terms of the pressure drop, meaning higher comfort. In general, the N95 face mask provided the best protection against aerosolized particles. According to the regression analysis, the fiber diameter of the mask filter substrate serves as an important predictor of FE of mask substrates. In this study, it was confirmed that fiber diameter is inversely related to the filtration ability. Results show that compact structure with finer fibers will enable higher filtration efficiency. The study lends itself to developing layered face masks to obtain optimum filters with good filtration, better fit, and acceptable comfort for the wearer.

Ingestion and biodegradation of disposable surgical masks by yellow mealworms Tenebrio molitor larvae: Differences in mask layers and effects on the larval gut microbiome

During the COVID-19 pandemic, the usage and production of face masks considerably increased, resulting in large quantities of mask waste accumulating in the natural environment. To investigate whether masks of polypropylene (PP) material could be ingested and degraded by insect worms like PP foam plastic, yellow mealworms were provided with different layers of disposable surgical masks as sole diets for 30 d. Although mask layers, especially the middle layer of melt-blown filter, could be ingested by yellow mealworms, sole mask layer diets had adverse effects on the larval survival and growth. Analyses of Fourier transform infrared spectroscopy, differential scanning calorimeter and thermogravimetric, and gel permeation chromatography demonstrated the changes of functional groups, thermostability and molecular weights in frass compared to original masks, indicating the partial oxidation and degradation of masks. And the depolymerization of the middle layer of masks by yellow mealworms was different from that of other layers. The larval gut bacterial and fungal microbiomes were assessed by Illumina MiSeq, indicating that both of them shifted upon sole layer mask diets. Changes in relative abundances of dominant bacterial and fungal genera demonstrated the strong association between gut microbiome and mask degradation. For instance, unclassified Enterobacteriaceae was closely associated with outer layers degradation. Lactococcus and unclassified Ascomycota were responsible for middle layers degradation, while Lactococcus and Morganella for inner layers degradation. In conclusion, disposable surgical masks of PP material could be ingested and biodegraded by yellow mealworms. The diversities of gut bacterial and fungal microbiomes were associated with the differences in rigid crystalline structures of the layer masks.

Anti-influenza Activity of Povidone-Iodine-Integrated Materials.

Personal protective equipment (PPE), including medical masks, should be worn for preventing the transmission of respiratory pathogens via infective droplets and aerosols. In medical masks, the key layer is the filter layer, and the melt-blown nonwoven fabric (NWF) is the most used fabric. However, the NWF filter layer cannot kill or inactivate the pathogens spread via droplets and aerosols. Povidone-iodine (PVP-I) has been used as an antiseptic solution given its potent broad-spectrum activity against pathogens. To develop PPE (e.g., medical masks) with anti-pathogenic activity, we integrated PVP-I into nylon-66 NWF. We then evaluated its antiviral activity against influenza A viruses by examining the viability of Madin-Darby canine kidney (MDCK) cells after inoculation with the virus strains exposed to the PVP-I-integrated nylon-66 NWF. The PVP-I nylon-66 NWF protected the MDCK cells from viral infection in a PVP-I concentration-dependent manner. Subsequently, we found to integrate PVP-I into nylon-66 and polyurethane materials among various materials. These PVP-I materials were also effective against influenza virus infection, and treatment with PVP-I nylon-66 NWF showed the highest cell survival among all the tested materials. PVP-I showed anti-influenza A virus activity when used in conjunction with PPE materials. Moreover, nylon-66 NWF integrated with PVP-I was found to be the best material to ensure anti-influenza activity. Therefore, PVP-I-integrated masks could have the potential to inhibit respiratory virus infection. Our results provide new information for developing multi-functional PPEs with anti-viral activity by integrating them with PVP-I to prevent the potential transmission of respiratory viruses.

Phosphate adsorption from water and wastewater using non-devulcanised and devulcanised tyre rubber

The secondary use of tyre rubber is a potentially sustainable environmental solution. However, the sorption properties of used-tyre rubber have not yet been fully investigated. In this study, the rubber type (vulcanised or devulcanised part-worn tyre rubber) that can sorb phosphate phosphorus from aqueous solutions or wastewater more effectively is determined. The capacity of granules (0.3–1.0 mm in diameter) of non-devulcanised ground tyre rubber and uniquely chemically devulcanised rubber to adsorb phosphorus is evaluated under laboratory conditions. The results show that under the filtration of an aqueous solution or biologically treated wastewater at a flow rate of 0.75 m/h (1.2 L/h), 1 g of the devulcanised rubber medium accumulates 5.16 mg of phosphorus, which is five times more than that accumulated by the non-devulcanised rubber medium. The surface structure of the non-devulcanised rubber medium is more suitable for the sorption of devulcanised rubber granules. The sorption capacity and effectiveness of non-devulcanised rubber for phosphorus removal are more favourable compared with those of the tested natural and waste-prepared sorbents. Further research into this material as a medium for filter layers and for accumulating drainage should be conducted. The findings of this study are important for addressing issues associated with the secondary use of tyre rubber.

Effective Suppression of LSCF Air Electrode Degradation by Air Cleaning

The performance degradation of air electrodes in solid oxide cells is strongly affected by impurities such as sulfur dioxide. Air filters are applied in most fuel cell systems to avoid poisoning and subsequent degradation of fuel cell stacks [1, 2]. Filtering solutions designed for the high air purity demands of proton-exchange membrane fuel cells (PEMFC) are commercially available.This study evaluates the applicability of such a filter for the LSCF air electrode in an electrolyte-supported SOC. Three different air qualities were applied in single-cell tests to distinguish the degradation mechanism caused by the ambient air impurities from the intrinsic aging phenomena of the cell. The utilized gases are (i) compressed air, (ii) filtered compressed air, and (iii) synthetic air. The compressed air (i) consists of ambient air supplied by a conventional compressor with a downstream particle filtering and oil removal system. In (ii), an additional filter layer was applied between the mass flow controller and the cell housing to filter the compressed air. The filter consisted of specially modified activated carbons designed to remove harmful gases and was operated at ambient temperature and pressure. The active area of the filter was 0.95 cm², corresponding to an air velocity of 0.088 m s-1 at an airflow rate of 500 sccm. The synthetic air is a mixture of 21% oxygen (99.95% O2, the main impurities are H2O and Ar) and 79% nitrogen (99.999% N2) provided by the Air Liquide company. Symmetrical cells based on a 3YSZ substrate coated with GDC buffer layers and LSCF electrode applied on both sides with an active surface area of 1 cm2 were applied in this study.Figure 1 shows the polarization resistance of the LSCF electrode operated in different types of air. Similar to previous reports [3-5], a significant degradation rate is recorded within the first 300 hours of operation. Filtering the air reduces the degradation rate significantly. The performance degradation of the cell with filtered air is comparable to that of the cell with synthetic air, demonstrating the capability of the filter to adsorb the gas impurities. Fig. 1 polarization resistance of the LSCF-cathode of 3 symmetrical cells operated at 750 °C with unfiltered and filtered compressed air and synthetic air, respectively.To better understand the degradation mechanism in the LSCF air electrode, we analyzed the impedance spectra measured during aging tests using the distribution of relaxation times (DRT) and then a complex nonlinear least squares (CNLS) fit. This contribution discusses differences in the temporal development of air electrode impedance and degradation mechanisms related to surface poisoning and subsequent changes in LSCF bulk.Keywords: LSCF air electrode, Impedance spectra, Degradation mechanisms, Air filtration.[1] M. Harenbrock, A. Korn, A. Weber, E. Hallbauer, in, SAE Technical Paper, 2020.[2] M. Harenbrock, E. Hallbauer, T. Heilmann, M. Hanselmann, ATZheavy duty, 14 (2021) 34-37.[3] C. Endler, A. Leonide, A. Weber, F. Tietz, E. Ivers-Tiffée, Journal of the Electrochemical Society, 157 (2010) B292-B298.[4] C. Endler-Schuck, A. Leonide, A. Weber, S. Uhlenbruck, F. Tietz, E. Ivers-Tiffée, Journal of Power Sources, 196 (2011) 7257-7262.[5] C. Endler-Schuck, J. Joos, C. Niedrig, A. Weber, E. Ivers-Tiffée, Solid State Ionics, 269 (2015) 67-79. Figure 1

Enhancement of sand filtration performance by titanium-chitosan micro-flocculation coupled with ferrate(VI) pre-oxidation

Due to seasonal algal outbreaks in source water, the sand filtration (SF) suffering high load exhibited poor performance in turbidity and organic matter (OM) removal. However, the filtration performance is highly dependent on the state of contaminants. This study aims to improve removal efficiency of turbidity, algae and DOM by coupling a novel green titanium sulfate-chitosan (TS-CTS) compound filter aids with/without ferrate (VI) pre-oxidation. The results indicated that the turbidity decreased to 0.25 NTU and chlorophyll a removal up to 73.5% with TS/CTS (0.8/0.3 mg/L) filter aids were utilized, while the filtration cycle was not significantly shortened. The introduced Fe(VI) (5 mg/L, 10 min) before micro-flocculation realized moderate pre-oxidation and formed in-situ Fe(III), improved algae cells removal and effectively controlled of 2-methylisoborneol (＜10 ng/L) as well as the disinfection by-product precursors as polysaccharides and amino acid-like proteins. Positively charged in-situ Fe(III) as a dual-coagulant facilitated Ti hydrolysis and promoted the clustering, cross-linking, formed Ti-AOM/NOM-Fe complexes. Under the adsorption bridging and adsorption electro-neutralization of TS-CTS and in-situ Fe(III), the microflocs were formed, migrated, adhered and ultimately retained in filter layer media. This study can provide guidance for technological and agent selection in algae-laden surface water treatment.

A new diagnostic autism spectrum disorder (DASD) strategy using ensemble diagnosis methodology based on blood tests

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disease that impacts a child’s way of behavior and social communication. In early childhood, children with ASD typically exhibit symptoms such as difficulty in social interaction, limited interests, and repetitive behavior. Although there are symptoms of ASD disease, most people do not understand these symptoms and therefore do not have enough knowledge to determine whether or not a child has ASD. Thus, early detection of ASD children based on accurate diagnosis model based on Artificial Intelligence (AI) techniques is a critical process to reduce the spread of the disease and control it early. Through this paper, a new Diagnostic Autism Spectrum Disorder (DASD) strategy is presented to quickly and accurately detect ASD children. DASD contains two layers called Data Filter Layer (DFL) and Diagnostic Layer (DL). Feature selection and outlier rejection processes are performed in DFL to filter the ASD dataset from less important features and incorrect data before using the diagnostic or detection method in DL to accurately diagnose the patients. In DFL, Binary Gray Wolf Optimization (BGWO) technique is used to select the most significant set of features while Binary Genetic Algorithm (BGA) technique is used to eliminate invalid training data. Then, Ensemble Diagnosis Methodology (EDM) as a new diagnostic technique is used in DL to quickly and precisely diagnose ASD children. In this paper, the main contribution is EDM that consists of several diagnostic models including Enhanced K-Nearest Neighbors (EKNN) as one of them. EKNN represents a hybrid technique consisting of three methods called K-Nearest Neighbors (KNN), Naïve Bayes (NB), and Chimp Optimization Algorithm (COA). NB is used as a weighed method to convert data from feature space to weight space. Then, COA is used as a data generation method to reduce the size of training dataset. Finally, KNN is applied on the reduced data in weight space to quickly and accurately diagnose ASD children based on new training dataset with small size. ASD blood tests dataset is used to test the proposed DASD strategy against other recent strategies [1]. It is concluded that the DASD strategy is superior to other strategies based on many performance measures including accuracy, error, recall, precision, micro_average precision, macro_average precision, micro_average recall, macro_average recall, F1-measure, and implementation-time with values equal to 0.93, 0.07, 0.83, 0.82, 0.80, 0.83, 0.79, 0.81, 0.79, and 1.5 s respectively.

Design of PTFE/PP multilayer composite membrane as mask filter layer with steady filtration efficiency and high dust holding capacity

Currently, commercially available mask filter materials, such as electrostatic electret polypropylene (PP) melt-blown cloth and polytetrafluoroethylene (PTFE) nanofiber membranes, always suffer a compromise between filtration efficiency and dust holding capacity, when used alone during air purification. In this study, a novel multilayer composite membrane was designed by thermally laminating a PP melt-blown filter layer (as the dust-holding layer) and a PTFE (Polytetrafluoroethylene) nanofiber layer (as the filtration layer), to improve filtration stability and capacity. The performance of the composite membrane was examined in relation to the effect of key laminating parameters (i.e., temperature, pressure and speed) on the dust holding capacity, filtration efficiency and resistance. NaCl aerosol was used as the model dust source. Results show that the composite membrane, prepared at a lamination temperature of 120 °C, a lamination pressure of 0.2 MPa and a lamination speed of 4 m/min, had a dust-holding capacity of 12.21 g/m2, which was over six times higher than that of the PTFE nanofiber membrane alone. During ten repeated cycles of NaCl aerosol filtration, water washing and alcohol disinfection, the composite membrane exhibited a steady filtration efficiency of above 99.9% over the NaCl aerosol. Meanwhile, the dust holding capacity was maintained above 8 g/m2 over the multiple cycles, while the resistance was smaller than 70 Pa.

Potential use of biodegradable polymers for facemask filter inserts produced using electrospinning methods

AbstractThe elevated use of petroleum‐based polymers to manufacture single‐use disposable face masks is a serious environmental concern that has detrimental effects on the ecosystem. The research on using biodegradable facemasks is promising to reduce the environmental impacts of the single‐use non‐degradable facemask. A reusable cloth‐based facemask with effective filtration could benefit society. Many studies suggest polyvinyl alcohol (PVA), polybutylene adipate terephthalate (PBAT), and polylactic acid (PLA) as viable biopolymers for facemask filter layer fabrication. In this work, an electrospun filter layer inserts with PVA, PBAT, and PLA polymers were produced by depositing electrospun nanofibers on non‐woven cotton layers followed by conventional sealing. The fabricated filter inserts were used in cloth‐based facemasks and were tested for filtration efficiencies and breathability. PVA facemask insert showed the best performance with 66.7% filtration efficiency and breathability of 0.66 m bar, whereas the lowest filtration efficiency was found for PBAT electrospun filter medium. The relation between filter membrane morphology and facemask performance indicates that a smaller diameter and uniform morphology results in better filtration and breathability of the facemask filter inserts.Highlights Petroleum‐based facemasks harm ecosystems. Biodegradable facemasks reduce environmental impact. Electrospun nanofibers of polyvinyl alcohol (PVA), polybutylene adipate terephthalate, and polylactic acid on cotton. PVA insert showed 66.7% filtration and 0.66 m bar breathability. Smaller, uniform fibers enhance filtration and breathability.

Meandering Flow Filter for Phosphorus Removal as a Component of Small Wastewater Treatment Plants—A Case Study

Chemical phosphorus removal in wastewater treatment plants can be carried out by precipitation with iron or aluminum salts or by filtering wastewater through a bed of active sorptive material. This work aimed to investigate whether using a meander flow filter filled with the sorption material Rockfos® would improve phosphorus removal efficiency in a selected wastewater treatment plant. Tests were performed under laboratory conditions using a model of a meander flow filter and a similar filter under field conditions at full technical scale. This filter was the final element of a hybrid constructed wetland located in the village of Białka in the municipality of Dębowa Kłoda in southeastern Poland. A laboratory model of a phosphorus removal filter with vertical incomplete baffles forcing a meandering water flow was constructed to determine the hydraulic conditions of the flow. After one year of operation, the filter with horizontal wastewater flow operating at its full technical scale (without meanders) was modified by inserting appropriate baffles that were analogous to those in the laboratory model. The analysis of the hydraulic conditions in the laboratory model showed that, under the assumed conditions, wastewater flows through the filter layer in a laminar motion, so such filters can be modeled using the Kozeny–Carman formula. It was shown that, after approximately a year of operation in a filter operating at full technical scale, before modification, dead spaces formed, thus causing the channel and primarily surface flow of wastewater. The phosphorus removal efficiency during this test period averaged 9.4%. After introducing baffles and forcing meander flow in the filter chamber, the efficiency increased to 40.6%. The results indicate that meander flow filters can improve phosphorus removal efficiency in small wastewater treatment plants.

Influence of Temperature on the Removal Efficiency of Organic Matter and Ammonia from Micro-Polluted Source Water

Temperature is an important factor influencing the treatment effect of biological aerated filters (BAFs). In this study, BAFs incorporating biological manganese oxides (BMOs) were used to treat micro-polluted source water containing organic masses and ammonia, and the influence of temperature on the removal efficiency of the pollutants was investigated. The results showed that after the formation of biogenic manganese oxides (BMOs) in the filter layer, the removal efficiency of CODMn significantly improved. When the water temperature was approximately 24 °C, 16 °C, and 6~8 °C, the removal rates of CODMn, ammonia, and manganese were 60.64, 42.55, and 20.48; 98.40, 95.58, and 85.04; and 98.70, 97.63, and 96.38%, respectively. The influence of water temperature on the removal efficiency of the pollutants was hierarchically structured as follows: CODMn > ammonia > manganese. Analysis of the removal efficiencies of the pollutants along the filter layer showed that CODMn had been eliminated in every filtration layer, and ammonia and manganese were mainly removed in the 0~0.4 m and 0~0.8 m regions of the filter layer, respectively. With a decreasing water temperature, the concentrations of CODMn, ammonia, and manganese along the filter layer increased. The biological CODMn, manganese, and ammonia removal processes were all first-order kinetic reactions. With a decreasing water temperature, the kinetic constant k gradually decreased, and the reaction half-life (t1/2) gradually increased.

Toxic effects of aging mask microplastics on E. coli and dynamic changes in extracellular polymeric matter

Contamination of disposable medical masks has become a growing problem globally in the wake of Covid-19 due to their widespread use and improper disposal. Three different mask layers, namely the outer layer, the meltblown (MB) filler layer and the inner layers release three different types of microplastics, whose physical and chemical properties change after prolonged environmental weathering. In this study, physical and chemical changes of mask microplastics before and after aging were characterized by different characterization techniques. The toxic effect and mechanism of aged mask microplastics on Escherichia coli (E. coli) were studied by measuring the growth inhibition of mask microplastics, the change in ATPase activity, the change in malondialdehyde content and reactive oxygen species production, and the release of the chemical composition of exopolymeric substances (EPS). The microplastics of the aged MB filter layer had the most significant inhibitory effect on E. coli growth, reaching 19.2 % after 36 h. Also, under the influence of mask microplastics, ATPase activity of E. coli was inhibited and a large amount of EPS was released. The chemical composition of EPS has also changed. This study proposed the possible toxicity mechanism of mask microplastics and the self-protection mechanism of E. coli, and provided a reference for future research on the toxic effects of mask microplastics on environmental organisms.

The growth of low-threading-dislocation-density GaAs buffer layers on Si substrates

Monolithic integration of III–V optoelectronic devices on Si platform is gaining momentum, since it enables advantages of low cost, less complexity and high yield for mass production. With the aim of achieving advances in monolithic integration, the challenges associated with lattice mismatch between III–V layers and Si substrates must be overcome, as a low density of threading dislocations (TDs) is a prerequisite for the robustness of the integrated devices. In this paper, we have investigated and compare different types of dislocation filter layers (DFLs) from InGaAs asymmetric step-graded buffer layer (ASG), InGaAs/GaAs strained-layer superlattices, and quaternary alloy InAlGaAs ASG, on the functionality of reducing TD density (TDD) for GaAs buffer layers on Si. Compared to other DFLs, the sample with InAlGaAs ASG buffer layer shows the lowest average TDD value and roughness, while the decrease of TDD in the sample with InAlGaAs ASG buffer layer can be understood in terms of the hardening agent role of aluminium in the InAlGaAs ASG. By further optimising the InAlGaAs ASG through thermal cyclic annealing, we successfully demonstrate a low surface TDD of 6.3 ± 0.1 × 106 cm−2 for a 2 μm GaAs/InAlGaAs ASG buffer layer grown on Si. These results could provide a thin buffer design for monolithic integration of various III–V devices on Si substrates.