Unit Energy Consumption Research Articles

Investigation of boiler energy consumption in the gas refinery units using RSM ANN and Aspen HYSYS.

In order to lower total energy consumption, this study focuses on optimizing energy use in refinery boilers. Using Aspen HYSYS simulations and modeling approaches like Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM), data from 579 days of boiler operation was gathered and examined. Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) techniques were used in the ANN modeling. Under the same operating circumstances, Aspen HYSYS estimated an energy usage of 1,355m³, whereas the actual consumption was 986m³. While the R2 values for the ANN models were 0.98 for the RBF model and 0.99 for the MLP model, the R2 value derived using RSM was 0.97. Furthermore, the RBF model's performance metrics were 0.0034, whereas the MLP model's were 0.0018. The MLP model is the best choice, according to these findings. It is estimated that burning 26,000m³ of fuel with an air supply of 23m³/h at 25.5°C will result in a steam flow of 525.5 tons per day at 10.5 barg and 256.5°C. According to actual statistics, these circumstances might prevent the release of 27 tons of carbon dioxide by reducing fuel usage by over 10,000m³ per hour. By optimizing the combustion stack's air supply, this decrease is accomplished.

Exploring the Relationship between CO2 Emission, Economic Growth, and Energy Consumption at Aggregate Level: A Panel Data Analysis

This article explores the relationship between CO2 emissions, economic growth, energy consumption, and, other control factors for the eight highest CO2-emitting countries (USA, Russia, Iran, China, Germany, India, Japan, and Canada) in 1995-2023. The m objective of the study is to determine how economic growth (GDP), energy consumption (EC), industrial production (IP), and other macroeconomic factors influence CO2 emissions. Using panel data analysis, this study applies various econometric techniques, including fixed and random effects models, Multicollinearity tests, heteroscedasticity tests, and cross-sectional dependence tests. Independent variables include GDP, Total energy use, Industrial output, Density of the population, and Trade while the dependent variable is CO2 emission. The results suggest that energy consumption positively correlates with CO2 emission, where, for each unit of energy consumption, CO2 emission increases by 0.0024 units. The outcomes also reveal a negative correlation of international trade with CO2 emissions implying that trade inhibits emissions. However, the relationship between GDP and, carbon emissions was formed to be statistically insignificant. Population density and industrial production have mixed effects on emissions, with industrial production showing a positive impact. The study emphasizes the importance of adopting cleaner energy sources, enhancing energy efficiency, and considering trade policies that might reduce emissions. The findings suggest that transitioning from coal and oil to cleaner energy sources, such as natural gas, could be an effective strategy for reducing carbon emissions without significantly hindering economic growth. The study provides valuable insights for policymakers in high-emission countries aiming to balance economic development with environmental sustainability.

Experimental Study on the Influence of Rotational Speed on Grinding Efficiency for the Vertical Stirred Mill

The rotational speed of the agitator is one of the important parameters that affect the grinding efficiency of the vertical stirred mill. Increasing the speed will improve the grinding effect, but it will increase energy consumption, and determining a reasonable speed setting is a system issue. The effects of different speeds on energy consumption, product particle size, and grinding efficiency were analyzed in this study. An experimental vertical stirred mill was used to grind iron ore, and five different speed parameters from 175 rpm to 350 rpm were set as variables. It was found that increasing the rotational speed will increase the grinding effect, but it will trigger more energy consumption. A new evaluation index to comprehensively reflect the grinding efficiency of the mill, which was defined as the ability of a mill to grind the same product per unit of time and energy consumption, was proposed. The grinding efficiency was calculated when the particle size of iron ore powder decreased to −45, −38, and −28 μm at different speeds. It can be seen that the growth rate of energy consumption is faster than that of the percentage of particle size, which leads to a continuous decrease in grinding efficiency with the increase in rotational speed. If high processing capacity is pursued within a certain period of time, high speed can be chosen, but it will result in energy loss. On the contrary, the low speed can be chosen, if considering grinding economy.

An experimental study on the erosion of solid propellant by cavitation water jet in submerged environment

The submerged cavitation water jet (SCWJ) is a promising technology for removing solid propellant from old solid rocket engines and recycling them. In this study, the feasibility of using SCWJ to break solid propellant is investigated. The structure of the cavitation cloud was captured by a high-speed camera and then analyzed using the Proper Orthogonal Decomposition (POD) and Frame Difference Method (FDM) method for exploring the unsteady characteristic of SCWJ, the HTPB propellant erosion experiments were performed, and the relationship of the SCWJ unsteady characteristic and the erosion results on HTPB propellant was analyzed. The results show that the SCWJ develops in the flow field including inception, development, shedding, and collapse stages, the maximum density of cavitation cloud changes exponentially, and the cavitation cloud length grows as the cavitation numbers increase. Lower cavitation number is always beneficial to high penetration rate and low energy consumption when erosion on the HTPB propellant. When the erosion time of 120 s, in high cavitation number under the least amount of energy consumed, the unit energy consumption minimum. The mass loss curve is double peak, the first peak is caused by water jet effect, standoff distance is located on the stage of development, the formation of erosion pit diameter is small, the depth is larger, the second peak is caused by cavitation effect, and its standoff distance is located on the shedding phase, forming the erosion pit diameter is bigger, the depth is shallow. The optimum standoff distance for the cavitation effect for the cavitation numbers 0.0135, 0.0081, 0.0058 and 0.0045 is 35 mm, 50 mm, 60 mm and 70 mm in order, and the mass loss rate of HTPB propellant is 90 mg s−1, 200 mg s−1, 277 mg s−1 and 521 mg s−1, respectively. At best cavitation effect standoff distance, cavitation number by 2 times, mass loss rate can increase 3 times. The matrix brittle fractures occur when the SCWJ strikes the HTPB propellant at a high strain rate. Besides, the erosion mechanism of HTPB propellant is discussed.

Numerical simulation and energy consumption analysis of ventilation patterns in grain silo

Mechanical ventilation is an effective method to ensure the security of grain storage, which directly impacts the storage duration and storage quality. In this work, considering the coupling effect of grain physical parameters and gas-solid phase interaction on ventilation, the porous media, non-thermal equilibrium and turbulence models were employed to investigate the variation of velocity field and temperature field under four ventilation patterns: vertical ventilation duct (VD), transverse ventilation duct (HD), combined roof inhalation duct (CRD), and combined bottom inhalation duct (CBD). The relative standard deviation (RSD) and unit energy consumption were used to evaluate the performance of different ventilation patterns quantitatively. The results show a relative deviation of 5.12 % between simulation and experiments. Compared with VD and HD, CRD and CBD exhibit higher velocity values and gradient in the center of grain silo. The physical parameters of grain have obvious impacts on velocity field, and paddy has the highest velocity values due to its higher porosity. CRD has a significant advantage in cooling speed and effect, with the grain surface temperature at 12 m and 25 m lower than other patterns by 1.2 °C and 1.8 °C, respectively. The large porosity of paddy can advance cooling time by up to 5–10 h, while the lower specific heat capacity and higher thermal conductivity of peanut result in cooling temperatures 1.5 °C–2.4 °C lower than other grain. The temperature RSD of VD is lower than other ventilation patterns, and the unit energy consumption of CRD and CBD is better.

Design and optimization for a longitudinal-flow corn ear threshing device of low loss and low energy consumption

The traditional corn grain harvester threshing device has the problems of high grain breakage rate, high unthreshed grain rate and high energy consumption when harvesting high water content corn ears. A longitudinal-flow corn ear threshing device and its measurement and control system were proposed to overcome these problems. The working performance and energy consumption of the threshing device were optimized by conducting three factors and five levels corn ear threshing experiments. The experiments took the threshing cylinder speed (X1), threshing gap (X2), and guide vane angle (X3) as the experimental factors, and the grain breakage rate (Y1), unthreshed grain rate (Y2), unit energy consumption (Y3), and threshing concave pressure (Y4) as the experimental indicators. According to the experimental results, the quadratic polynomial regression models between experimental indicators and experimental factors were established. Through models optimization, the optimal working parameters for the threshing device were obtained as X1 at 392.40 r/min, X2 at 40.70 mm, and X3 at 33.16°. Through conducting verification experiment, it was found that under the optimal parameters, the experimental indicators were Y1 at 2.32 ± 0.06 %, Y2 at 0.48 ± 0.04 %, Y3 at 2.14 ± 0.10 kJ/kg, and Y4 at 46.28 ± 3.23N. The errors between the experimental results and the quadratic polynomial regression models were less than 5 %, which indicated that the models had high prediction accuracy. Compared with the unoptimized experimental indicators, the optimized experimental indicators Y1, Y2, Y3 and Y4 decreased by 36.26 %, 39.24 %, 14.74 % and 16.27 %, respectively. The working performance of the threshing device was significantly improved, and the energy consumption was significantly reduced. The relevant research could provide reference for the optimization of the mechanical structure and working parameters of the corn ear threshing device.

Activation of peroxymonosulfate by MnOOH/g-C3N5: Study on highly selective removal of phenolic pollutants and its non-radical pathway

In this research, the MnOOH/g-C3N5 material was successfully synthesized, demonstrating its efficacy in selectively removing phenolic organic pollutants. This material outperformed traditional free radical pathways, exhibiting higher selectivity, enhanced persulfate utilization efficiency, and strong resistance to background anions and complex organic matter. Using phenol as the target pollutant, the MnOOH/g-C3N5/PMS system achieved 81 % mineralization, a PMS utilization efficiency of 88 %, and a 75 % process unit energy consumption value in degrading phenol. This efficient degradation is attributed to the synergistic effects of high-valence metal oxides (MnV(O)/MnIV(O)), singlet oxygen (1O2), and electron transfer complexes, as confirmed by electrochemical analysis and In-situ EPR. Additionally, Transmission Electron Microscopy observations disclosed the development of an amorphous shell on the MnOOH/g-C3N5 surface post-reaction. Electrochemical Impedance Spectroscopy analysis suggested an enhanced charge transfer resistance, further affirming the role of MnOOH/g-C3N5 as an "electron transfer station" in the electron transfer process, accompanied by the formation of electron transfer complexes. This study provides crucial scientific insights and theoretical guidance for applying MnOOH/g-C3N5 materials in environmental engineering.

Designing Intensive Care Unit Windows in a Mediterranean Climate: Efficiency, Daylighting, and Circadian Response

Hospital intensive care units (ICUs) frequently experience inadequate lighting conditions, with low daytime and excessive nighttime illuminance, which can negatively affect patient recovery and the work performance of health personnel. This study examines the impact of window design parameters—specifically, window-to-wall ratio (WWR) and window position—and interior surface reflectance on visual comfort, lighting performance, energy consumption, and human well-being in intensive care units (ICUs) in Mediterranean climates, according to orientation. Using dynamic lighting metrics, such as daylight autonomy (DA) and circadian stimulus autonomy (CSA), this research quantifies the influence of these design factors. The results suggest that a WWR of 25% is optimal for achieving sufficient DA and CSA values, with centered window configurations preferred for uniform daylight distribution and circadian stimulus. This study further emphasizes the significance of interior reflectance, recommending bright coatings to maximize outcomes, while advising against dark finishes, particularly in north-facing rooms or with smaller WWRs. Although Seville shows slightly better performance than Barcelona, the proposed configurations are effective across both locations, highlighting the prioritization of window sizing, positioning, and reflectance over Mediterranean geographical differences. These findings offer practical guidance for ICU design to enhance natural lighting, supporting patient recovery and overall well-being through improved circadian alignment.

A multi-objective dual dynamic genetic algorithm-based approach for thermoelectric optimization of integrated urban energy systems

In order to reduce the loss of energy in the process of conversion and utilization, and to improve the energy utilization effect and economic benefits of urban integrated energy system, a thermoelectricity optimization method of urban integrated energy system based on multi-objective double dynamic genetic algorithm is proposed. The method analyzes the operation characteristics of the urban integrated energy system through its operation model, constructs a multi-objective optimization model for the thermoelectricity of the urban integrated energy system, determines the optimization multi-objective function that minimizes the operation cost, minimizes the carbon emission, minimizes the technical dissatisfaction and the related constraints, and then solves the optimization model by using the dual dynamic genetic algorithm to output the results of the optimization of the thermoelectricity of the urban integrated energy system.The test results show that the algorithm has a crowding distance of 0.75 or above when solving, and the overall unit energy consumption cost reduction ratio is about 22.97 %. The state of charge results of the four energy storage power stations are all below 10 %, and the lowest convergence speed is only 7 seconds, effectively improving energy utilization efficiency.

Disaggregated Impact of Non-Renewable Energy Consumption on the Environmental Sustainability of the United States: A Novel Dynamic ARDL Approach

While there is a vast body of literature on environmental sustainability, the disaggregated impact of major non-renewable energy (NRE) consumption on the environmental sustainability of the United States (U.S.) is understudied, particularly in terms of using a load capacity factor (LCF) perspective. In this study, the above research gap is addressed using a dynamic autoregressive distributed lag (DYNARDL) model to analyze the heterogeneous impact of NRE consumption on the environmental sustainability of the U.S. from 1961 to 2022. Given the U.S.’s heavy reliance on energy consumption from NRE sources, this analysis provides an in-depth examination of the long-term effects of this energy consumption on the environment. Based on the analysis of the DYNARDL model, it is found that an increase of one unit of coal, natural gas, and petroleum energy consumption reduces environmental sustainability by 0.007, 0.006, and 0.008 units in the short-run and 0.006, 0.004, and 0.005 units in the long-run, respectively. However, one unit of nuclear energy consumption increases environmental sustainability by 0.007 units in the long-run. The kernel-based regularized system (KRLS) result reveals that coal and petroleum energy consumption have a significantly negative causal link with environmental sustainability, while nuclear energy consumption demonstrates a significant positive causal relationship. The research suggests the expansion of the use of nuclear energy by gradually reducing the utilization of coal and petroleum-based forms of energy, then natural gas, to improve environmental sustainability in the U.S., while considering the social and economic implications of efforts aimed at shifting away from the use of fossil fuels.

Pilot-scale capacitive deionization for water softening: Performance, energy consumption, and ion selectivity

Capacitive deionization (CDI) has emerged as an efficient process for hardness control than traditional water-softening technologies. However, few systematic studies have been conducted on water softening using pilot-scale CDI systems. For industrial applications, it is essential to investigate deionization performance, energy consumption, and selectivity for divalent cations through pilot-scale studies. In this study, we examined the deionization performance and energy consumption of a pilot-scale CDI process for effective water softening. The key operational variables analyzed were the applied voltage (200–300 V (i.e., 1.0–1.5 V per pair)), feed concentration (550–1250 mg/L), recovery ratio (50–80 %), flow rate (3–5 L/min), and adsorption/desorption time (80–180 s). Within this range, a high voltage, low feed concentration, low recovery ratio, high flow rate, and long adsorption/desorption times are advantageous for the total dissolved solids (TDS) removal ratio. In terms of energy efficiency, expressed as TDS removal per unit energy consumption, a low voltage, low feed concentration, low recovery ratio, fast flow rate, and long adsorption/desorption time are beneficial. Additionally, we investigated the selective removal of Ca2+ over Na+ under various operating conditions, as well as its impact on enhancing energy efficiency. The pilot CDI system achieved a Ca/Na selectivity coefficient of approximately 2.4 and it was analyzed to achieve up to 45 % energy-saving efficiency compared to nonselective systems (i.e., selectivity coefficient = 1). The results of this study are expected to provide valuable data for the application of CDI to water softening and hardness control processes.

An experimental study on the effect of room setpoint temperature, and evaporator/condenser fouling on performance of a ductless split type air conditioner

Ductless splits can have several advantages over conventional systems including energy saving, improved thermal comfort, and performance. A deep understanding of the effect of changes in operating conditions of the unit is required to estimate the energy saving in the field. In this paper, a reference guide is created to classify the effects of different parameters on the performance of the ductless split unit. The experiments are categorized into three main topics: 1- The effect of setpoint temperature on the performance and energy consumption, 2- The effect of evaporator fouling on energy consumption, and 3- The effect of condenser fouling on energy consumption of a ductless split unit. Results show that one degree Celsius increment in room setpoint temperature reduces power consumption approximately 57 W and in annually energy consumption about 279 kWh. Furthermore, covering 30 % of the evaporator coil surface area and comparing with the normal case (evaporator coil with no coverage), parameters of Energy Efficiency Ratio, energy consumption, and cooling capacity drops 13.5 %, 6.4 % and 19.1 %, respectively. Likewise, by covering 1/3 of the condenser coil surface area and comparing with the normal case, Energy Efficiency Ratio, and cooling capacity drops 9.8 % and 2.4 %, respectively. The mentioned data indicate that the effect of the evaporator dirtiness on reducing the cooling load of the device is much higher than that of condenser.

Multi-scale closed-loop coupled real-time water quantity optimization scheduling of cascade pumping station in water supply canal systems

Closed-loop control is an effective control method to deal with uncertain disturbance in water supply canal system (WSCS). However, previous researches mainly focus on closed-loop control with a single time scale, and it is difficult to solve the uncertainty problem with a long time dimension. In this paper, a multi-scale closed-loop coupled real-time scheduling framework is established and solved by considering both large and small scale closed-loop scheduling models, so as to improve the performance of real-time scheduling in a longer time dimension under uncertain perturbations. The framework is applied to the virtual simulation test of the Xuhong River WSCS of the east route of the South-to-North Water Diversion project under different water distribution disturbances. The results show that the closed-loop control method can update the system status regularly through rolling optimization, and effectively reduce the prediction error of water level and energy consumption. In the two water distribution disturbance scenarios, the proposed method reduces the average relative deviation of water supply plan execution by 3.4 % and 5.9 %, and the unit energy consumption of cascade pumping station operation by 1.7 kWh/104m3 and 1.5 kWh/104m3, respectively, compared with the single-scale closed-loop scheduling method. In addition, the proposed method can effectively deal with the uncertainty of water distribution disturbance in limited computing time, and can meet the requirements of real-time scheduling in a long time dimension under uncertain disturbance.

Energy consumption prediction of coal-fired unit boiler system based on different operating states

ABSTRACT The energy consumption of the coal-fired unit’s boiler system varies significantly when accommodating flexible peak shaving demands. To aid staff in comprehending the boiler’s operational status and optimize its performance, a prediction model of the energy consumption of the boiler system was established based on the different states of the unit operation. First, a dataset of boiler energy consumption under variable load was established based on theory of fuel-specific consumption, and the Mean Impact Value (MIV) algorithm was used to simplify the input features of the model. Second, the Aquila Optimizer (AO) with tent map, adaptive t-distribution, and opposites learning mechanism was introduced to determine the parameters in the prediction model. On this basis, the sliding-window method was used to classify the operating states based on the load of the unit, and the original dataset without operating state distinction, the steady state operating data, the load uplink data, and the load downlink data were used to establish Models 1–4, respectively. The result shows that Model 1 outperforms Model 2 with 24.45% and 18.22% lower aMAE and aRMSE, respectively. compared to Model 3, it shows a decrease of 24.07% and 16.98%. Compared to Model 1, Model 4 shows a reduction of 20.52% and 18.91% in aMAE and aRMSE, respectively. This indicates that distinguishing different operating states to establish boiler energy consumption prediction models can obtain better prediction accuracy.

Comparison of devices used for continuous production of emulsions: Droplet diameter, energy efficiency and capacity

Liquid-liquid emulsions are used in various sectors, including food, health care, personal care, home care and nutrition. There is an increasing need for developing equipment and devices for producing emulsions with desired drop size distribution (DSD) in a continuous mode of operation to fulfil market demands. In this work, we experimentally investigated droplet size distributions of emulsions made using selected cavitation-based emulsion producing devices operated in a continuous mode. Emulsion production devices considered in this work are wet mill, Soldo cavitator, Dynaflow cavitator and different scales of vortex based hydrodynamic cavitation devices. The continuous emulsion production experiments were performed for generating 5 % rapeseed oil-in-water emulsions using different devices. Performance of different emulsion production devices based on energy efficiency of emulsification (η), energy consumption per kilogram of emulsion (E), interfacial area created per unit energy consumption (Anet)P, Sauter mean diameter (d32), other characteristic diameters (D10,D50,D90), and drop size distribution (DSD) was compared. Among all the devices, vortex based hydrodynamic cavitation (HC) devices showed excellent performance in terms of lower d32 and DSD with low E and high η. The smallest scale of vortex-based HC device exhibited the highest efficiency (∼0.16 % at E = 2.6 kJ/kg) over the entire range of E compared to the other devices considered in this study. The presented data and analysis will be useful for selection of emulsion producing devices for desired emulsion characteristics and production capacity.

Sensitivity analysis on heat pump - mechanical vapor recompression desalination system by recovering waste heat of offshore power converter station

Abstract Offshore wind power converter stations produce massive low-temperature waste heat, which can hardly be used constrained by their offshore location. Therefore, the recovery of the waste heat has been raising widespread concern. Meanwhile, a large amount of fresh water is needed for its cooling system. So, a novel system combining high temperature heat pump and a mechanical vapor recompression system (HP-MVR) was proposed, and sensitivity analysis was performed to optimize it. The heat pump was used to absorb the waste heat and to produce high temperature water. The mechanical vapor recompression system was adopted to produce fresh water and to recover the condensation heat from the steam. In order to determine the impact parameters on the two crucial performance indicators of freshwater production and unit energy consumption, this article introduces a sensitivity analysis method, focusing on analyzing the sensitivity of the three operating parameters of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature to these two performance indicators. The results show that the sensitivity coefficients of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature are 1.13, -0.26, and 1.56. So, the freshwater condensation temperature has the most significant effect on freshwater output. Their sensitivity coefficients to unit energy consumption are 1.02, 1.41, and -0.64. The saturated water vapor inlet temperature entering the compressor has the most significant impact on the required power consumption per unit of freshwater. It will give some guidance for the application of low-temperature waste heat in seawater desalination and the reduction of operating costs.

DECREASING ELECTRICAL ENERGY COST AND INDIRECT CO2 EMISSIONS OF AN AIR CONDITIONING UNIT AFTER PREVENTIVE MAINTENANCE

During the summer season in subtropical countries and the dry season in tropical countries, air temperature is high. To adapt this condition, an air conditioning (AC) unit is used. The air conditioning use, however, increases the electrical energy consumption which contributes to the increase of indirect CO2 emissions. For many buildings, a monthly electrical energy cost from the use of AC system can contribute up to 40% of a monthly utility expenditure. It is then a great motivation to decrease electrical energy consumption of the AC unit. In this work, an adaptable preventive maintenance for an AC unit shows an acceptable level of electrical energy decrease. An experiment was performed for 2 AC types. The first one is a wall mounted unit with a cooling capacity of 9,300 BTUH. The second unit is a split duct unit with a cooling capacity of 48,000 BTUH. The cleaning of evaporator in the wall-mounted AC unit decreased the hourly electrical energy consumption by 4.1% from 810 to 777 Watt-hour. In addition, cleaning of condenser for the similar AC unit decreased the electrical energy consumption by 6.2% from 810 to 760 Watt-hour. Meanwhile, the evaporator cleaning for a 48,000 split duct AC decreased the hourly electrical energy consumption by 2.4% from 4.64 to 4.53 kWh and cleaning of condenser decreased the energy consumption by 5.4% from 4.64 to 4.39 kWh. If this electrical energy decrease could be scaled up to the global energy consumption from the air conditioning use, this should be a significant decrease of the global energy consumption and the correlated indirect CO2 emissions from the air conditioning sector.

Energy efficiency evaluation and optimization for wastewater treatment plant

Wastewater treatment plants (WWTPs) are considered as energy-intensive industries. A comprehensive assessment of energy efficiency in sewage treatment reveals issues of energy waste, offers insights into the energy consumption structure, fosters optimization of energy management, and enhances overall energy utilization. However, the mathematical modeling for energy efficiency evaluation becomes challenging due to the ambiguity and uncertainty of the parameters regarding energy consumption and various indicators. In this paper, the newly constructed evaluation method was used to quantify the energy efficiency. This method employs dimensional reduction, projecting the numerical values of unit energy consumption for various pollutants onto a lower-dimensional space, and then computing the projected eigenvalues. Larger eigenvalues indicate higher energy efficiency. Based on the evaluation results, the back propagation (BP) neural network is used to simulate the sewage treatment process. The results demonstrated that when the inflow load is small and the concentration of pollutants is high, the energy efficiency of sewage treatment plants performs well. When the inflow load is high and the concentration of pollutants is low, the energy efficiency of sewage treatment plants is poor. Meanwhile, the energy consumption could be decreased by 11.61 %, 14 %, and 15.26 % respectively in different scenarios.

Leachate treatment via electrocoagulation–coal‐based powdered activated carbon process: Efficiencies, mechanisms, kinetics, and costs

AbstractThis study aims to improve COD, NH3‐N, and turbidity removal from Bingöl's leachate using a single‐reactor integrated electrocoagulation (EC)–coal‐based powdered activated carbon (CBPAC) process under various experimental conditions. In the EC‐CBPAC process, three stainless‐steel cathodes and three aluminum electrodes were connected to the negative and positive terminals of the power supply, respectively. The initial concentrations in the leachate were 1044 mg O2/L for COD, 204 mg/L for NH3‐N, and 57 NTU (or 71.25‐mg (NH2)2H2SO4/L) for turbidity, respectively. After a 40‐min EC‐CBPAC process, with a CBPAC dosage of 5 g/L and pH of 5 for COD and turbidity, and 9.5 for NH3‐N, the optimum removal efficiencies for COD, NH3‐N, and turbidity were achieved at 92%, 40%, and 91%, respectively. When the EC process was applied without CBPAC under the same experimental conditions, the removal efficiencies of COD, NH3‐N, and turbidity were 87%, 28%, and 54%, respectively. Before and after the EC‐CBPAC process, the Brunauer–Emmett–Teller (BET) surface area, pore volume, and mean pore diameter of the CBPAC were found to be (888 m2/g, 0.498 cm3/g, and 22.28 Å) and (173 m2/g, 0.18 cm3/g, and 42.8 Å), respectively. The optimum pseudo‐first‐order (PFO) rate constants for COD, turbidity, and NH3‐N were determined to be 3.15 × 10−2, 4.77 × 10−2, and 8.8 × 10−3 min−1, respectively. With the current density increasing from 15 to 25 mA/cm2, energy consumption, unit energy consumption, and total cost increased from 68.7 to 122.4 kWh/m3, 6.948 to 15.226 kWh/kg COD, and 0.85 to 1.838 $/kg COD, respectively.Practitioner points EC‐CBPAC process has greater COD, NH3‐N, and turbidity removal efficiency than EC process. COD and turbidity achieved their optimum disposal efficiencies at 92% and 91%, respectively, at pH 5 The most efficient disposal efficiency for NH3‐N was observed to be 40% at pH 9.5. EC‐CBPAC process increased removal efficiencies for COD, NH3‐N, and turbidity by 20%, 19%, and 38%, respectively, compared with EC alone. The turbidity, NH3‐N, and COD disposal fitted PSO model due to high correlation values (R2 0.94–0.99).

Low-maintenance anti-scaling of nanofiltration pretreated by bipolar-induced electrolysis for decentralized water supply

Nanofiltration (NF) offers an effective solution to ensure a decentralized water supply. However, its reliance on dosing for pre-precipitation and anti-scaling severely complicates its maintenance, adding to its cost and limiting its application, especially in rural areas. In this study, a bipolar-induced electrolysis (BIE) pretreatment method was developed to reduce the NF membrane scaling potential without the need for additional reagents. The water flux of the BIE-NF increased by 24.2 ± 6.5 % compared to traditional NF. This benefits from the synergistic effects of electrocoagulation (EC) and electro-precipitation (EP) of BIE to remove hardness ions (36.8 ± 0.7 g CaCO3 m−2 h−1), 26.2 ± 2.6 % and 16.1 ± 4.7 % faster than that of traditional EP and EC, respectively, exhibiting robust resistance to the interfering ions and organics. The unit energy consumption of BIE was only 18.9 ± 1.0 kWh/(kg CaCO3), 11.8 ± 1.9 % and 67.0 ± 1.4 % lower than that of EP and EC, respectively. After BIE electrolysis, the Ca, humic acid, and Mg contents were dramatically reduced, and a uniformly loose fouling layer formed on the NF membrane, demonstrating alleviated membrane scaling. Remarkably, BIE softening demonstrated its stability and feasibility in sustaining 120.0 m3/d of drinking water to rural populations without requiring additional reagents or manual maintenance, minimizing the operation and maintenance cost to 5.1 US cents/m3 water, 29.0 % lower than the cost of conventional dosing pretreatment. This study offers a low-cost and sustainable method for water supply through decentralized membrane purification.