Journal of Environmental Engineering

Congo red (CR), a harmful pollutant, is increasingly contaminating aquatic environments. The removal of CR from wastewater is important. This study developed a novel graphene–biochar composite (GR-BC) to enhance CR treatment. The physicochemical properties of GR-BC were studied using Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller techniques. The CR adsorption capacities of biochar (BC) and GR-BC were analyzed using batch adsorption experiments. The effect of the initial pH of the CR solution, CR concentration, and adsorption time of CR were determined. The SEM, XRD, and FT-IR results showed that graphene was loaded successfully onto the BC. The BET results showed that GR-BC had a larger surface area than BC. The adsorption experiments showed that the highest CR adsorption efficiency occurred at pH 2, and reached 99.6% and 99.5% for BC and GR-BC, respectively. The GR-BC treatment was better at removing CR dye than was BC. The highest Langmuir adsorptive capacity of GR-BC ($414.9\mathrm{mg}·{\mathrm{g}}^{-1}$) was double of that of BC ($193.8\mathrm{mg}·{\mathrm{g}}^{-1}$). The higher $R^2$ values for the Freundlich isotherm than for the Langmuir isotherm indicate that the Freundlich isotherm model best fit the experimental data for both BC and GR-BC. The pseudo-second-order model ($R^2>0.99$) successfully described the adsorption kinetics of CR dye by both BC and GR-BC. In addition, the influence of ionic strength and coexisting ions on CR adsorption by BC was greater than that on CR adsorption by GR-BC, indicating that GR-BC is more stable than BC. Recycling experiments showed that CR removal still 50% after the fifth cycle for GR-BC, which was higher than that for BC (35%), suggesting that GR-BC has better reusability than BC. Thus, the GR-BC composite is a potential adsorbent for CR dye removal.

Truck-wash facilities have become popularized globally on construction sites, and the wastewater was frequently treated by three-stage sedimentation basins. The wastewater and bacterial characteristics in three-stage sedimentation basins need to be studied, which might affect the treatment cost and reuse security. In this study, the wastewater characteristics, bacterial communities, and pathogenic bacteria distribution of three-stage sedimentation basins on four construction sites were investigated. Results indicated that truck-wash wastewater contained a high concentration of suspended solids ($29–211\mathrm{mg}/\mathrm{L}$) and bacteria ($4.2\times {10}^3$ to $2.7\times {10}^4$ colony forming $\mathrm{units}/\mathrm{mL}$). Proteobacteria (mean at 72.3%), Firmicutes (mean at 11.3%), and Bacteroidetes (mean at 10.6%) were the predominant bacterial phyla and Acinetobacter (mean at 18.4%), Chryseomicrobium (mean at 6.3%), and Paracoccus (mean at 6.1%) were the predominant bacterial genera. Truck-wash wastewater contained pathogenic bacteria, identified by the Illumina sequencing method. Acinetobacter, Shigella, or Escherichia (about 0.2%) and Legionella (about 0.2%) were the main pathogenic bacteria and Legionella should be a concern due to the wastewater reuse method. Traditional three-stage sedimentation basins should be simplified and further improved because of the lower suspended solids or pathogenic bacteria removal effect. The practical technology for suspended solids and pathogenic bacteria control in truck-wash wastewater should be further studied, and disinfection facilities should be applied to protect construction workers.

Sulfide generation rates in the force mains of four pump stations in Edmonton, Alberta, Canada, were evaluated in the field, and a continuous nitrate dosing was applied in the pump wet well of the Big Lake pump station to investigate its effectiveness on sulfide control. The sulfide production rates at these force mains were estimated to be $0.08–0.15\mathrm{g}/{\mathrm{m}}^2\mathrm{h}$ under 20°C, which could be modeled by using the $1/2$-order biofilm kinetics of dissolved chemical oxygen demand (DCOD). The modeled rate constant $a$ was obtained at around 0.006 using the field monitoring data. It was found that $20\mathrm{mg}/\mathrm{L}$ sulfide was formed in the force main of the Big Lake pump station, which resulted in 400–500 parts per million (ppm) ${\mathrm{H}}_2\mathrm{S}$ gas in the discharge manhole. It was found that a nitrate dosing concentration of $85\mathrm{mg}/\mathrm{L}$ could completely suppress the sulfide generation in the force main. A constant dosing rate resulted in nitrate overdosage at midnight and underdosage in peak hours. Injecting nitrate in the wet well led to a large portion of nitrate consumption where a heterotrophic denitrification process happened. The appropriate dosing location for this dosing strategy is at the beginning of force main instead of the wet well. The corresponding dosing rate is a flow-paced dosing rate instead of a constant dosing rate. A more cost-effective dosing strategy is to add the nitrate at downstream section of the force main where sulfide generated upstream could be removed in the presence of nitrate when passing downstream. This dosing strategy could significantly reduce the nitrate demand.

Graphene is expected to play a significant role as a capacitive deionization (CDI) electrode due to its exceptional characteristics. However, difficulties in achieving high specific surface area (SSA) reduces the sorption capacity and limits its usage in CDI. Effort taken toward improving the SSA of graphene by adding composites and through surface modification resulted in significant SSA with lower sorption capacity. Thus, the present study investigated the effect of the synthesis method and materials used to prepare electrode slurry (binder material) on SSA and specific capacitance. Graphene was synthesized employing Hummers, modified Hummers, and electrochemical exfoliation, and its quality was characterized based on X-ray diffraction, scanning electron microscope, and ultraviolet spectra analysis. The influence of binder type on specific capacitance was assessed by fabricating the electrode with commonly used two hydrophobic and two hydrophilic binders. Sorption analysis was also carried out to study the effect of SSA and specific capacitance of graphene with selected binders. The results revealed that electrochemically exfoliated graphene yield SSA of ${\mathrm{1,529.8}\mathrm{m}}^2/\mathrm{g}$ with a sorption capacity 64% and 52% greater than graphene synthesized using the Hummers and modified Hummers methods, respectively. Usage of polyvinylidene fluoride (PVdF) binder resulted in a specific capacitance of $974.45\mathrm{F}/\mathrm{g}$ and a sorption capacity of $32.73\mathrm{mg}/\mathrm{g}$. Thus, graphene’s increased sorption capacity implies that the suitable method of synthesis and fabrication of electrodes with a suitable binder offers adequate SSA and specific capacitance by suppressing pseudocapacitance.

The application of intelligent algorithms in the optimal design of a membrane bioreactor (MBR) is helpful in improving reactor performance. Our study constructed a numerical flow field model of a MBR. Membrane thickness, porosity, and inlet velocity were used as independent input variables. Flow field uniformity and turbulent kinetic energy were used as characteristic parameters to evaluate the flow field effect of the reactor. Based on the numerical calculation of samples, the back-propagation (BP) neural network model was used for prediction. Genetic algorithms (GA), artificial bee colony algorithms, and particle swarm optimization (PSO) algorithms were used to optimize the BP neural network. PSO–BP was screened out by error analysis as the best intelligent prediction algorithm. The function model between the reactor parameters and the flow field effect was derived by multivariate nonlinear regression analysis in combination with the results of computational fluid dynamics and PSO–BP prediction. The following optimal design parameters were determined using GA: membrane structure thickness of 45.6 mm, porosity of 76%, and inlet velocity of 2 V. A feasible intelligent optimal design method of MBR was established by combining fluid dynamics and modern intelligent algorithms to provide a new idea and method for the optimal design of an MBR.

Most developing countries still have various makes of petrol-driven cars dominating the overall passenger vehicle fleet. In such countries, the emission certification policy for in-use vehicles remains an area of concern, making the inspection and maintenance (I/M) program less effective. A thorough investigation of the exhaust emissions from such cars is required to explore and address this concern. This paper provides insights into the effects of vehicle variables on tailpipe emission parameters from an exclusively larger and heterogeneous dataset of in-use cars ($\mathrm{n}=\mathrm{1,580}$). Results showed that both vehicle variables such as age, mileage, emissions norm, and maintenance category, and two engine variables, i.e., aspiration type and fuel mixing conditions, had a significant and direct influence on tailpipe parameters, namely, CO, HC, ${\mathrm{CO}}_2$, ${\mathrm{O}}_2$, $\lambda$, and AFR (carbon monoxide, hydrocarbon, carbon dioxide, oxygen, lambda and air-fuel ratio respectively). Stronger correlations were found for the relatively larger (considering age, ${\mathrm{R}}^2$ for ${\mathrm{CO}}_{\mathrm{idle}}=0.88$, ${\mathrm{HC}}_{\mathrm{idle}}=0.73$, ${\lambda }_{\mathrm{f}.\mathrm{idle}}=0.74$, ${\mathrm{AFR}}_{\mathrm{f}.\mathrm{idle}}=0.73$ and considering mileage, ${\mathrm{R}}^2$ for ${\mathrm{CO}}_{\mathrm{idle}}=0.75$, ${\mathrm{HC}}_{\mathrm{idle}}=0.67$, ${\lambda }_{\mathrm{f}.\mathrm{idle}}=0.62$, ${\mathrm{AFR}}_{\mathrm{f}.\mathrm{idle}}=0.61$ for the whole dataset) and diverse make-wise (${\mathrm{R}}^2$ values fared even better, 0.87–0.93 for CO and 0.69–0.77 for HC) data collected during the study. The present research provides a first-hand and comprehensive analysis of the effects of the stringency of emission norms and maintenance category on the exhaust emissions from in-use cars. The polynomial emission equations generated by this study can reliably predict the emission levels for CO and HC based on the age and/or mileage of cars. Further, the results recommend revised policies to upgrade the existing emission certification infrastructure and phasing out policy of cars.

Secondary pollution control and rapid stabilization of municipal solid waste (MSW) landfills are closely associated with bacterial communities. The spatial variations in bacterial community structure and the environmental factors controlling it were studied by the 16S rRNA gene sequencing of MSW sampled at different depths in a large sanitary landfill (LSL) and a medium non-sanitary landfill (MNSL), respectively. The total nitrogen (TN) and total phosphorus (TP) content in the LSL and MNSL samples displayed a downward trend as the depth increased. However, the organic matter (OM) content followed the opposite trend. Diversity of microbes was highest in the middle layer of both the LSL and MNSL. Firmicutes and Proteobacteria were the dominant phylum both in the LSL and MNSL. In the LSL, the dominant bacteria genera succeeded from Psychrobacter, Pseudomonas to Clostridium, Savagea. However, in the MNSL, the genera succeeded from Uncultured, Pleomorphomonas to Hydrogenispora, Acetomicrobium. The type of landfill and the different environmental factors control the succession of the bacterial community in LSL and MNSL. The pH, OM, TN, and TP will change in the landfill as the landfill depth increased. The impact degree of landfill depth on pH, OM, TN, and TP content in the LSL was 15.3%, 16.1%, 4.9%, and 4.2%, respectively. These values were lower than those in the MNSL. In addition, depth and OM had the strongest correlations but no significance with the dominant bacteria both in the LSL (${|\mathrm{R}}_{\mathrm{depth}}{|}_{\mathrm{average}}{=0.48;|\mathrm{R}}_{\mathrm{OM}}{|}_{\mathrm{average}}=0.36$) and MNSL (${|\mathrm{R}}_{\mathrm{depth}}{|}_{\mathrm{average}}{=0.51;|\mathrm{R}}_{\mathrm{OM}}{|}_{\mathrm{average}}=0.36$). This indicated that bacterial community succession was mainly dependent on space, time, and MSW characteristics in different types of landfills.