Filter Bed Research Articles

The Conversion of Ethanol to Syngas by Partial Oxidation in a Non-Premixed Moving Bed Reactor

An experimental investigation into the conversion of ethanol to syngas by partial oxidation in a non-premixed counterflow moving bed filtration combustion reactor was carried out. Regimes of conversion depending on the mass flow rates of fuel and air (separate feeding), as well as a granular solid heat carrier, were studied. Depending on the mass flow rate of the heat carrier, two combustion modes were realized—reaction trailing and intermediate—with different temperature patterns in the gas preheating, combustion, and cooling zones along the reactor. The product gas composition is far from the predictions of the equilibrium model; it contains substation fractions of methane and ethylene. Combustion temperature and conversion are limited by the relatively high level of heat loss from the laboratory-scale reactor. The effect of the heat loss can be reduced by enhancing the absolute flow rate of the reactants.

A method for measuring the critical pore diameter of a homogeneous microchannel separator based on image analysis and a simulation comparison of CFD-DEM

Fine particles being captured or escaping from particle beds (microchannel separator) is a widespread phenomenon, with the size and distribution of pores (microchannel) significantly affecting these phenomena. However, due to the complexity of the pore structure, accurately measuring and validating it poses challenges. This paper introduces a new method to calculate the critical pore diameter of homogeneous microchannel separators (three types of homogeneous separation media with particle sizes of 0.8 mm, 1.0 mm and 1.2 mm). Initially, particle bed units with a thickness twice the diameter of the separation media were captured from multiple orthogonal projection directions to obtain high-resolution images of the pore structure. Then, the Feret diameter distribution of the pores were analyzed to quantify pore size and distribution. Next, unresolved CFD-DEM method was used to simulate the capture of fine particles to optimize and supplement the results. The results show that the average Feret diameter of the pores differs by only 0.85 μm, 1.70 μm, and 2.46 μm from the simulation results, and it is noted that the critical pore diameter is approximately 0.153 times that of the separation media diameter, the numerical difference from the critical dimension ratio is only 0.0017. Additionally, when the diameter of the fine particles is 0.155 to 0.165 times the diameter of the separation media, the homogeneous microchannel separator exhibits the highest efficiency during the deep bed filtration process. The study also examines the separation of homogeneous fine particles at varying inlet liquid flow rates, which can offer theoretical guidance for analyzing the porosity of microchannel separators and the efficient removal of solid pollutants, thus contributing novel ideas to deep bed filtration research.

Mechanistic model advancements for optimal calcium removal in water treatment: Integral operation improvements and reactor design strategies

Drinking water softening has primarily prioritized public health, environmental benefits, social costs and enhanced client comfort. Annually, over 35 billion cubic meters of water is softened worldwide, often utilizing three main techniques: nanofiltration, ion exchange and seeded crystallization by pellet softening. However, recent modifications in pellet softening, including changes in seeding materials and acid conditioning used post-softening, have not fully achieved desired flexibility and optimization. This highlights the need of an integral approach, as drinking water softening is just one step in the drinking water treatment chain, which includes ozonation, softening, biological active carbon filtration (BACF) and sand filtration among others. In addition, pellet softening is often practiced based on operator knowledge, lacking practical key reactor performance indicators (KPIs) for efficient control. For that reason, we propose a newly and improved integral mechanistic model designed to accurately predict (1) calcite removal rates in drinking water through seeded crystallization in pellet softening reactors, (2) the saturation of the filter bed in the subsequent treatment step, (3) values for the KPIs steering the softening efficiency. Our new mechanistic model integrates insights from hydrodynamics, thermodynamics, mass transfer kinetics, nucleation and reactor engineering, focussing on critical variables such as temperature, linear velocity, pellet particle size and saturation index with respect to calcite. Our model was validated with data from the Waternet Weesperkarspel drinking water treatment plant in Amsterdam, The Netherlands, but implies universal applicability for addressing industrial challenges beyond drinking water softening. The implementation of our model proposes five effective KPIs to optimize the softening process, chemical usage, and reactor design. The advantage of this model is that it eliminates the application of numerical methods and fills a significant gap in the field by providing predictions of the carry-over (i.e., the produced CaCO3 fines leaving the fluidized bed) from water softening practices. With our model, the calcium removal rate is predicted with an average standard deviation (SD) of 40 % and the consequential clogging prediction of the BACF bed with an average SD of 130 %. Ultimately, our model provides crucial insights for operational management and decision-making in drinking water treatment plants, steering towards a more circular and environmentally sustainable process.

The Influence of Fibers from Domestic Laundry Wastewater on the Clogging Process of a Filter

This study presents the impact of the size and shape of particles in laundry wastewater on the clogging process of a porous material. Clogging can be defined as a mechanical limitation of flow through porous media. The process of mechanical clogging was investigated in this study. The research was conducted in laboratory conditions in a filter column filled with glass beads whose diameter corresponded to coarse sand. The results reveal the influence of graywater quality on filter hydraulic conductivity and bed clogging, showing the impact of fiber particles in wastewater (sewage from home laundry) on the clogging process in soil. The results confirm that fiber particles significantly reduce filter permeability, particularly due to the formation of a filter cake. As analyzed in this paper, the distribution of quantitative data on particles of different sizes found in laundry wastewater indicates that they mainly accumulate in the upper layer, where particles with fiber lengths ranging from 0 to 1600 µm can be found. The average length of the fibers decreased with increasing depth. At a depth of approximately 10 cm, fibers with dimensions in the range of 0 to 100 μm were predominantly observed.

Sintered Clays: Application in the Removal of Arsenic from Water by Filter Beds

Objectives: The main objective of the research was to build a ceramic filter bed, using red clay and diatomite, for the removal of arsenic in aqueous media and to propose an environmentally friendly and low-cost technique for rural communities in Peru that consume water contaminated with arsenic. Theoretical framework: Arsenic is a common contaminant in the drinking water of many rural communities in Peru, exceeding the limits allowed by the WHO. Prolonged exposure to arsenic can cause serious health problems. The use of low-cost non-metallic materials, such as thermally activated clay and diatomite, is proposed for its adsorption. Method: A filter bed composed of 5 cm layers of red clay and diatomite with particle sizes of 0.81, 0.31 and 0.20 mm was used. Both materials were thermally activated at 900°C and placed on a stainless steel support. The arsenic removal process was evaluated by passing a synthetic solution with 13.99 ppm of arsenic through the bed. Material characterization analyses were performed before and after the adsorption process, using techniques such as ICP-OES, SEM, FTIR, among others. Results and discussion: The filter bed composed of diatomite (83.31% SiO2) and red clay (8.23% Fe2O3) achieved an arsenic removal of up to 99.99%, highlighting the efficiency of particles with a size of 0.20 mm. This shows that the combination of these materials can be highly effective in removing arsenic in water, which is promising for its implementation in rural areas. Research implications: This research has important implications for water treatment in rural communities facing arsenic contamination problems. The technique developed is low-cost and uses abundant resources, which facilitates its application at the local level and promotes sustainable solutions for access to safe drinking water. Originality/Value: The research provides a novel approach through the use of red clay and diatomite, accessible resources, thermally activated for the removal of arsenic in water. In addition, the high removal effectiveness achieved provides a potentially scalable and replicable solution in other rural communities with similar problems.

Predicting the impact of underwater skimming on dissolved oxygen consumption in slow sand filters for potable water treatment

In a well-functioning slow sand filter (SSF), dissolved oxygen (DO) is crucial for enabling aerobic processes and microbiota growth. Given that DO supply is predominantly via the feed water, flow pauses (e.g., during cleaning) may trigger anoxic/anaerobic conditions in the stagnant filter bed. Underwater skimming (UWS) is an advanced cleaning technique that employs a skimmer with a shrouded blade, mounted on a mobile platform, to remove the fouling layer composed of sand and particles in order to improve the efficiency of slow sand filtration. As UWS results in changes to the flow pattern of the SSF, a mathematical model was developed to predict DO utilization after a flow perturbation associated with UWS operation. The model was based on a depth resolved measurement of specific oxygen utilization derived from a full scale SSF. Pilot plant experiments monitored DO in the feed and filtrate of SSFs cleaned using underwater and conventional dry skimming techniques. The highest oxygen utilization was in the Schmutzdecke layer, with additional demand imposed by the presence of a granular activated carbon (GAC) sandwich layer. It was observed that pseudo-steady state conditions occurred following filter ripening, where DO utilization, driven by biological activity, remained relatively constant regardless of filter cleaning technique. For flow pauses between three and 24 h, the pause duration's importance decreased, while the hydraulic loading rate became the critical factor for DO recovery in the filter. Additionally, introducing a ‘sweetening flow’ during UWS ensured a continuous DO supply, facilitating quicker DO replenishment post-cleaning. The model reliably predicted filtrate DO within ±0.6 mg/L, demonstrating its operational utility, especially in the optimisation of UWS methodology. As such, UWS can be applied to clean SSFs with the methodology modified to prevent any detrimental effects to DO management within the filter. This study predicted DO dynamics in SSFs, advancing UWS techniques and could be applied for enhancing water treatment strategies by filtration.

Using Artificial Neural Networks to Predict Operational Parameters of a Drinking Water Treatment Plant (DWTP)

The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the Aposelemis DWTP, where the plant operator had an estimation of the ANN output parameters for the required dosages of water treatment chemicals based on observed water quality and other operational parameters at the time. The estimated DWTP main operational parameters included residual ozone (O3) and dosages of the chemicals used: anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas (Cl2(g)). Daily measurable results of water sample analysis and recordings from the DWTP Supervisory Control and Data Acquisition System (SCADA), covering a period of 38 months, were used as input parameters for the artificial neural network (1188 values for each of the 14 measurable parameters). These input parameters included: raw water supply (Q), raw water turbidity (T1), treated water turbidity (T2), treated water residual free chlorine (Cl2), treated water concentration of residual aluminum (Al), filtration bed inlet water turbidity (T3), daily difference in water height in reservoir (∆H), raw water pH (pH1), treated water pH (pH2), and daily consumption of DWTP electricity (El). Output/target parameters were: residual O3 after ozonation (O3), anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas supply (Cl2(g)). A total of 304 different ANN models were tested, based on the best test performance (tperf) indicator. The one with the optimum performance indicator was selected. The scenario finally chosen was the one with 100 neural networks, 100 nodes, 42 hidden nodes, 10 inputs, and 4 outputs. This ANN model achieved excellent simulation results based on the best testing performance indicator, which suggests that ANNs are potentially useful tools for the prediction of a DWTP’s main operational parameters. Further research could explore the prediction of water chemicals used in a DWTP by using ANNs with a smaller number of operational parameters to ensure greater flexibility, without prohibitively reducing the reliability of the prediction model. This could prove useful in cases with a much higher sample size, given the data-demanding nature of ANNs.

Enhancing Greywater Treatment: High-Efficiency Constructed Wetlands with Seashell and Ceramic Brick Substrates

Constructed wetland (CW) systems have been recognized as a sustainable technology for wastewater treatment that can be easily integrated into the local natural environment, offering both low cost and high efficiency. In this study, synthetic greywater was treated using a vertical subsurface flow CW operated in batch mode with 7-day cycles across two phases, operated in parallel: I, non-vegetated, and II, vegetated, with Echinodorus subalatus. The mixed filter bed was composed of seashells, ceramic brick fragments, and sand. No statistically significant differences (p > 0.05) were observed between the non-vegetated and vegetated phases for most parameters. The removal efficiencies of organic matter, anionic surfactants, and total phosphorus in the non-vegetated versus vegetated phases were (91.0 ± 3.8)% versus (94.0 ± 1.1)%; (71.9 ± 14.1)% versus (60.0 ± 9.5)%; and (35.2 ± 4.6)% versus (40.2 ± 15.5)%, respectively. Phosphorus removal exceeded values reported in the literature for both phases, primarily due to the calcium present in the seashells, which increased the electrical conductivity and hardness of the effluent compared to the influent. The macrophyte exhibited leaf desiccation, possibly due to contact with greywater and its young age (30 days), which may have negatively impacted the system’s performance during the vegetated phase.

Removal of sulfamethoxazole using Fe-Mn biochar filtration columns: Influence of co-existing polystyrene microplastics

Emerging contaminants, particularly antibiotics and microplastics (MPs), present significant challenges in wastewater treatment and pose large ecological risks. This study investigates the removal efficiency of sulfamethoxazole (SMX) using Fe-Mn modified biochar (BFM) in fixed bed filtration columns, emphasizing the effect of the presence of polystyrene microplastics (PS-MPs) on SMX behavior in both water (pH ≈ 5.6) and selected wastewater (pH ≈ 8) systems. Batch sorption results show that 10 mg/L SMX in 50 mL water can be completely removed by 100 mg BFM sorbent. The Bed Depth Service Time model indicated the BFM column is feasible for SMX removal in scaled-up continuous wastewater flow operations, while the Yan model best elucidates SMX filtration behavior and suggests the dominant adsorption mechanisms include external mass transfer and intraparticle diffusion. The present of both 20 mg/L and 100 mg/L PS-MPs (pH ≈ 5.6) significantly reduced SMX retention due to competitive sorption. However, at pH 3.2, competitive sorption became negligible due to electrostatic interactions driving the PS-MPs sorption, while neutral charged SMX bound through hydrogen-bonds or π-π EDA interactions. Elevated pH shifted both PS-MPs and SMX sorption to non-electrostatic thus intensifying sorption competition, highlighting the influence of pH on their interaction dynamics. In wastewater, SMX filtration was slightly inhibited by 100 mg/L PS-MPs in BFM columns, whereas PS-MPs removal remained unaffected due to the high ionic strength and alkaline pH. These findings highlight the impact of MPs on pollution removal efficiency in filtration system, essential for enhancing biochar-based wastewater treatment strategies.

Microscale insights into deep bed membrane filtration: Influence of internal surface roughness

Deep bed filtration is widely applied in bioprocessing, virus filtration, and water purification to remove small impurities, such as particles or virus fragments. However, more needs to be understood about the parameters that influence particle capture and deposition. Detailed simulations and microfluidic filtration experiments with straight pores have been widely investigated, yet realistic membrane porosity features such as pore gradients and roughness have not been addressed in detail. The internal membrane morphology is assumed to have a strong effect on filtration performance. Therefore, this study introduces a new microfluidic membrane mimicking device (MMD) and methodology that analyzes spatio-temporal particle collections in a deep bed filtration MMD with gradually decreasing pore size toward the retentate side. The design allows us to systematically tailor an internal filter surface roughness to investigate its influence on differently sized soft particles and the consequences for filtration performance, in particular, particle capture. Optical investigation and quantitative evaluation show enhanced particle–pillar interactions for increased roughness. This results in a reduced penetration depth and reduced particle breakthrough. The modes of capture or filtration phenomena, such as pore blocking, bridging, or dendrite formation, differ significantly between smooth and rough membrane filter structures. In the case of rough inner filter surfaces, those phenomena lead to a less distinct decrease in volumetric flow, allowing a longer filtration process. The microfluidic study offers a detailed investigation of how microscale phenomena influence the filtration process. The results provide a fundamental understanding of microscale filtration effects based on roughness and, hence, motivate a tailoring of the internal membrane filter surface according to the filtration problem at hand.

Gravity‐driven packed bed filter, with copper‐impregnated activated carbon, for continuous water disinfection in absence of electricity

AbstractAvailability of safe drinking water is a major concern in many parts of the world. While many filtration units operating on various principles are available to combat this, most require electricity, which may not be consistently available in such areas. In the present study, we have designed and demonstrated a water disinfection system that can operate purely on gravity, without any electricity. For this, a potassium hydroxide modified copper‐impregnated activated carbon (KOH‐Cu‐AC) hybrid was used as a filter medium for disinfection, because it is less expensive, with performance comparable to previously reported hybrids containing silver. To maintain a constant water flow rate under gravity, during disinfection, a Mariotte bottle was used as the reservoir of the contaminated water. Using this and a constant head between the bottle and the treated water exit point, the required water‐filter contact time of 25 min (for decontamination) is maintained in the filter column, regardless of tank‐fill level. The demonstrated lab‐scale system can perform disinfection of simulated contaminated water (with an initial concentration of 104 CFU mL−1 Escherichia coli), for at least 6 h, with a flow rate of 150 mL h−1. The disinfection performance from the gravity‐based filter was further validated with the conventional pump‐driven filter, used for continuous disinfection of drinking water. Equivalence of results between pump‐ and gravity‐driven operations helps us to eliminate the need for power, without any compromise in disinfection efficacy. Finally, copper concentration from treated water (106 ppb at steady state) remains very well within the safe limit (1000 ppb as per USEPA guideline). Hence, the lab‐scale design of gravity‐based packed bed filter will be useful for domestic and community‐based supply of safe drinking water in resource‐constrained areas, because it eliminated electricity requirement of conventional power‐driven systems.Practitioner Points Cost‐effective KOH‐Cu‐AC hybrid is developed as a disinfection material. Mariotte bottle used for maintaining constant disinfected water flow rate works without any electrical power supply. This system can be used for getting on‐spot, continuous disinfected water supply. The concentration of copper in the treated water is well within the safety limit. It can be applicable in rural and remote areas (no electric power source) as well as natural calamity‐affected areas.

Iron and Manganese Removal through Adsortive Filtration based on Zeolites, at bank scale

The aim of the current study is to assess iron and manganese removal from water used for public supply through adsorptive filtration based on natural zeolites that were chemically prepared for metal removal purposes. The research was conducted at bench scale by using water samples from two water sources in Parana State. Full cycle studies were carried out; according to them, filtration was conducted, in separate, under four filter bed conditions, namely: sand, anthracite coal, zeolite without previous chlorine application and zeolite with previous chlorine application. The zeolite filtration test without previous chlorine application recorded high meaniron and manganese removal values, - 100% and 87.96%, respectively. Based on the filtration results, the zeolite filter without previous chlorine application was the best filter media among the tested beds, under the herein proposed conditions.

Comparative assessment of domestic wastewater treatment via Vermifiltration through various filter bed material.

Vermifilter (VF) is considered sustainable for rural areas; however, filter media is the most important but has been explored less. This study evaluated the performance of vermifilters in treating domestic wastewater (DWW) using various filter media, including areca nutshell (AS), rice straw (RS), dry leaves (DL), and chicken eggshells (ES). We compared the results with four different reactors: R1 (AS), R2 (RS), R3 (DL), and R4 (ES). DWW was applied with a hydraulic loading rate (HLR) of 1 m3/m2/d with Eisenia fetida earthworm species. The results showed the removal of biochemical oxygen demand (BOD) by 82%, 76%, 73%, and 87%; chemical oxygen demand (COD) by 75%, 73%, 72%, and 88%; phosphate by 36%, 25%, 27%, and 50%; sulfate by 56%, 54%, 53%, and 71% in R1, R2, R3, and R4, respectively. Simultaneously, R4 experienced a fivefold reduction in total bacteria and a sixfold reduction in total coliform. Moreover, the most exceptional filter media for vermifiltration is eggshells for the earthworm's growth and treatment efficacy.

Impact of forced aeration on vertical flow treatment wetland performances for combined sewer overflow

Combined Sewer Overflow Treatment Wetlands (CSO wetlands) are designed to remove pollutants under stochastic events with variable hydraulic loads. Upgrading them with forced aeration promises to increase the effectiveness and resilience of the treatment. We have tested two vertical CSO wetlands with forced aeration (CSOa and CSOb) to understand the effects of aeration on CSO treatment. Both filter beds have 0.95 and 0.80 m of saturated layer. CSOa uses gravel as top filtering layer, while CSOb utilizes sand and an additional transition layer. Tracer tests were conducted in both filters with and without aeration to assess the impact of aeration on hydraulic performance. CSOa operated with four different aeration conditions, with the optimal condition tested on both filters for comparison. Samples were taken for analysis of global parameters and the redox potential was monitored online. In the tracer test, CSOa allowed to observe the mixing impact of aeration, which avoids any preferential path when influent entered the filter. The addition of a sand layer at the surface (CSOb) allows for a more even distribution of water on the top, which limits preferential flows when aeration is off. In both filters, the results showed that aeration increased the residence time and mixing degree (NTIS <3). Testing different aeration strategies revealed the dependence of dissolved pollutant removal on oxygen supply. In CSOa, the median outlet concentration varied from 23 to 6.4 mg.L−1 in TSS, 153 to 32 mg.L−1 total COD (CODt), 124 to 20 mg.L−1 soluble COD (CODs) and 5 to 2.5 mg.L−1 NH4-N according to aeration strategy. The lower outlet concentrations were always under the highest aeration condition. Under the optimal condition (75 min on/15 min off), median removal of CSOa was 97% TSS, 85% CODt, 78% CODs and 75% NH4-N. Besides COD and TSS, outlet concentration and removal efficiency did not significantly differ between CSOa and CSOb. Pollutant removal demonstrated a linear correlation with organic surface load. Overall, forced aeration in CSO-TW distinctly affected filter dynamics and improved its performance.

How bioaugmentation for pesticide removal influences the microbial community in biologically active sand filters

Removing pesticides from biological drinking water filters is challenging due to the difficulty in activating pesticide-degrading bacteria within the filters. Bioaugmented bacteria can alter the filter's microbiome, affecting its performance either positively or negatively, depending on the bacteria used and their interaction with native microbes. We demonstrate that adding specific bacteria strains can effectively remove recalcitrant pesticides, like metaldehyde, yielding compliance to regulatory standards for an extended period. Our experiments revealed that the Sphingobium CMET-H strain was particularly effective, consistently reducing metaldehyde concentrations to levels within regulatory compliance, significantly outperforming Acinetobacter calcoaceticus E1. This success is attributed to the superior acclimation and distribution of the Sphingobium strain within the filter bed, facilitating more efficient interactions with and degradation of the pesticide, even when present at lower population densities compared to Acinetobacter calcoaceticus E1. Furthermore, our study demonstrates that the addition of pesticide-degrading strains significantly impacts the filter's microbiome at various depths, despite these strains making up less than 1% of the total microbial community. The sequence in which these bacteria are introduced influences the system's ability to degrade pesticides effectively. This research shows the potential of carefully selected and dosed bioaugmented bacteria to improve the pesticide removal capabilities of water filtration systems, while also highlighting the dynamics between bioaugmented and native microbial communities. Further investigation into optimizing bioaugmentation strategies is suggested to enhance the resilience and efficiency of drinking water treatment systems against pesticide contamination.

Treatment of Oily Effluents Using a Bacterial Cellulose Membrane as the Filter Bed

One of the main challenges in the treatment of industrial wastewater is the removal of oil-in-water emulsions, which are stable and therefore difficult to treat. Bacterial cellulose (BC) has structural characteristics that make it an ideal filtration membrane. Several research projects are underway to develop new materials, both biotechnological and traditional, for use in filter beds. The study examined the potential of a BC membrane filtration system for treating oily industrial wastewaters, an underexplored biomaterial in wastewater treatment. The results demonstrated that BC is highly effective at removing oily contaminants (~99%), reducing the colour and particulate matter of wastewater, as well as eliminating nearly the entire microbiological load (~99%). SEM, MEV, FTIR, XRD, and TGA confirmed the presence of oil in the interior of the membrane after filtration, characteristic peaks of its chemical composition, and a 40% reduction in crystallinity. TGA revealed an increase from three (pre-filtration) to five (post-filtration) stages of thermal degradation, indicating the retention of the contaminant in the BC. The mechanical tests demonstrated that the membrane has a tensile strength of 72.13 ± 8.22 MPa and tolerated elongation of up to 21.11 ± 4.81% prior to tearing. The BC membrane also exhibited excellent flexibility, as it could be folded &gt;100 times at the same point without exhibiting signs of tearing. The BC surpasses traditional methods, such as activated charcoal and effluent treatment stations, in the removal of emulsified oils. The findings demonstrate that BC is promising for the treatment of industrial wastewaters, which is a field that requires continual technological innovations to mitigate the environmental impacts of the oil industry.

Study on the operation effect of old and new process replacement based on denitrification deep bed filters

In order to study the effect of replacing old and new processes in denitrifying deep-bed filter, the water quality data before and after equipment upgrading at the same period were collected for comparative analysis. The results show that the new process has a desirable removal rates for COD (93.67%), BOD (96.82%), NH3-N (98.04%) and SS (97.47%) throughout the year, respectively, with the effective and feasible denitrification process. The average TN concentration in effluent was 6.1mg/L after process upgrading, which decreased by 41.69% compared with the same period before process upgrading. The average removal rate was 72.5%, which was much higher than that before replacement (58.8%). In general, the denitrification deep bed filter had a great nitrogen removal efficiency.

Enhancing submicron dust capture in high-temperature flue gases: A computational study on gradient pore-buried tube granular bed filters

Granular bed filters (GBF) represent a highly effective technology for purifying high-temperature dusty flue gases, although their efficiency in capturing submicron particles remains limited. A novel gradient porosity GBF model with varying bed structures and heat exchange capabilities was proposed. In this research, we employed CFD software to elucidate the movement and heat transfer process of 1 μm dust particles within gradient porosity GBFs and heat exchanger tubes. By optimizing the model under the conditions of a 0.5 m/s inlet flue gas flow rate and 1 μm dust particle size, we achieved a 345.62% increase in filtration efficiency and a 76.61% reduction in pressure drop. The findings indicate that the proposed GBF outperforms other models across various flue gas flow rates in terms of filtration efficiency. The impact of the flue gas flow rate on the combined filtration efficiency for submicron dust on the proposed GBF model was notably significant.

Experimental Dust Absorption Study in Automotive Engine Inlet Air Filter Materials.

The purpose of this study was to empirically evaluate the performance of fibrous materials that meet the criteria for inlet air filtration in internal combustion engines. The characteristics of filtration efficiency and accuracy, as well as the characteristics of flow resistance, were determined based on the mass of dust accumulated in the filter bed during the filtration process. Single-layer filter materials tested included cellulose, polyester, and glass microfiber. Multilayer filter media such as cellulose-polyester-nanofibers and cellulose-polyester were also examined. A new composite filter bed-consisting of polyester, glass microfiber, and cellulose-and its filtration characteristics were evaluated. Utilizing specific air filtration quality factors, it was demonstrated that the composite is characterized by high pre-filtration efficiency (99.98%), a short pre-filtration period (qs = 4.21%), high accuracy (dpmax = 1.5-3 µm) for the entire lifespan of the filter, and a 60-250% higher dust absorption coefficient compared to the other tested materials. A filtration composite bed constructed from a group of materials with different filtration parameters can be, due to its high filtration efficiency, accuracy, and dust absorption, an excellent filter material for engine intake air. The composite's filtration parameters will depend on the type of filter layers and their order relative to the aerosol flow. This paper presents a methodology for the selection and testing of various filter materials.

Polystyrene composite system: An alternative for wastewater treatment.

Rapid population growth intensifies water scarcity, highlighting the importance of treatment technologies such as reverse osmosis and membrane filtration to ensure safe drinking water and preserve resources. The use of polystyrene as a filter for polluted water is valuable due to its porous surface, efficiently retaining impurities. The system, a tubular reactor with a mixed polystyrene bed, underwent evaluations with varying particle sizes, flow rates and times, operating in dead-end mode and series system without recirculation with theoretical residence times between 180 and 360 min. The study, divided into two phases, optimized the system in the first phase, characterizing the filter bed and carrying out maintenance for 360 min at 0.5 L/min. Phase two evaluated the performance of the reactor in treating wastewater with flow rates of 0.5 and 1 L/min for 180 min. Under the best conditions of Phase I, 55% of Escherichia coli and turbidity were deactivated, not meeting potability standards. In Phase II, there was efficiency in the removal of several parameters, such as chemical oxygen demand (78.26%), total phosphorus (75%), nitrate (73.42%), ammonia (73.13%), nitrite (69.33%), potassium (70.83%), and sodium (68.75%). In addition, 98.32% of E. coli was deactivated, meeting CONAMA Class 2 and 3 irrigation standards.