Journal of Environmental Engineering

Abstract

Human activities and atmospheric deposits on highways have led to an increase of pollutants in highway stormwater runoff. The reduction of these pollutants to a minimum acceptance level has been a great subject of concern for the US Department of Transportation and US Environment Protection Agency. Researchers have investigated several methods; however, biochar utilization, an environmentally and economically favorable way for pollutant removal from highway stormwater runoff, has not been studied extensively. Biochar has been intensively used for soil improvement and water treatment. Its unique carbon structure, large surface area, and higher pore structure have made it a potential candidate for water retention and contaminant removal. This literature review focused on the removal of highway stormwater runoff pollutants such as suspended solids (dust, sludge, and leaves), heavy metals (Ni, Zn, Pb, Cr, Cd, and Cu), nutrients (nitrate and phosphate), and organic contaminants (paraffin, nitrobenzene, and p-nitrotoluene) using biomass-derived biochar. This comprehensive literature review introduces biochar production and the effect of the production process operating temperature on biochar’s structure and performance. It also analyzes the impact and efficiency of biochar on pollutant removal and illustrates its potential in the treatment of highway stormwater runoff.

Practical Applications

Highway networks impact water bodies and watersheds by collecting and transporting pollutants through stormwater runoff. These pollutants are detrimental to aquatic lives and water quality and include solids (dissolved and suspended), heavy metals (zinc, lead, copper, and so on), and nutrients (nitrogen and phosphorus, and so on). Biochar has advanced properties that allow the treatment of pollutants in water through physical, chemical, and biological adsorption processes. Biochar is generally produced using waste sources such as biosolids, wood, or farm manure. Hence, biochar is considered a cost-effective and sustainable method for highway stormwater runoff treatment. Biochar is used as performance-enhancing devices (PEDs) for best management practices (BMPs) to enable high pollutant removal performance. Biochar can be added to topsoil on highway bioslopes and filter strips to amend the topsoils and increase pollutants removal through infiltration. Biochar is incorporated as PED with other BMPs such as bioretention ponds and gardens for stormwater quality improvement. In addition, biochar is used to decrease hydraulic conductivity and increase water holding capacity of topsoil. Ultimately, topsoil application allows the use of biochar on agricultural lands for specialized crop cultivation.

Bioremediation with immobilized enzymes has been established as the method for restoring contaminated ecosystems with the help of biological tools on a global scale. The purpose of this work is to immobilize the laccase enzyme for increasing the biocatalyst′s ability in order to remove bisphenol A (BPA). Initially, the nanocatalyst was prepared by immobilizing laccase on chitosan using carbon nanotubes decorated with zinc oxide. Subsequently, Fourier transformed infrared (FTIR) spectroscopy, X-ray diffraction (XRD), field emission scanning microscopy (FE-SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and dot mapping were employed to characterize the prepared nanocomposites. Laccase activity, immobilization yield (%), thermal and storage stability, and reusability of laccase immobilized on chitosan-coated carbon nanotubes (CNTs)/ZnO nanocomposites were also measured. The chitosan (CS)-CNTs/ZnO@laccase nanocatalyst performance in different operational conditions (initial concentrations of bisphenol A, amount of nanobiocatalyst, pH, and irradiation time) on the photodegradation process of bisphenol A were also investigated and optimized using the response surface methodology (RSM)-central composite design (CCD) model. The RSM design and experiments demonstrated that 94.51% of BPA was removed under optimal conditions (initial BPA concentration of $100\mathrm{mg}{\mathrm{L}}^{-1}$, nanocatalyst amount of $1\mathrm{g}{\mathrm{L}}^{-1}$, $\mathrm{pH}=9$, and 40 min of contact exposure). Laccase was a critical factor in this process, and after five recycling cycles, immobilized laccase retained 61% of its original activity, indicating that this nanobiocatalyst can be used in purification processes as a durable and robust catalyst.

Fouling of reverse osmosis (RO) systems to produce clean drinking water is a major problem. Organo-selenium inhibition is an attractive solution for this application because biofilm prevention has been shown in medical devices, water filtration systems, and plastics. This study examined whether selenium-coated polymers would have positive effects in controlling RO fouling. This study included an analysis of modified feed spacers’ performance on reduction of total biomass concentration, average biofilm thickness on the surface of RO membranes versus real wastewater sources, the impact of selenium catalytic activity on the reduction of RO membrane chemical scaling, and the performance of fouling and biofilm formation. A 1.5% organo-selenium was copolymerized into spacer elements used in an RO system. These systems were then tested with both city and industrial wastewater with different total dissolved solids (TDS) concentrations for effects on (1) flux, (2) biofilm formation, and (3) inorganic binding. The comparison of an organo-selenium spacer with a control spacer yielded the following for RO membranes: (1) lower calcium and magnesium binding; (2) better flux at high TDS concentrations in both city and industrial water; (3) lower biofilm thickness and volume; and (4) a decrease in both dead and viable bacteria. Testing of varying solids concentrations resulted in greater log inhibition of fouling as a result of operating the RO system with selenium copolymerized feed spacer. The impact of selenium catalytic activity versus divalent foulants (magnesium and calcium) is important because of their ability to create bridges between biological cells and membrane surface, leading to increased possibility of biofouling.

High levels of fecal-indicator organisms (FIOs) at bathing water sites can cause disease and impose threats to public health. There is a need for predicting FIO levels to inform the public and reduce exposure. Data-driven models are one of the main tools being considered as predictive models. However, identifying the main inputs of the data-driven models is a major challenge in developing FIO predictor models. This paper develops a data-driven model for FIO concentration prediction based on a limited number of critical input variables. Essential variables were identified with be a combination of the gamma test and Genetic Algorithm (Gamma-GA test). Artificial neural networks (ANNs) and linear regression models were developed using these two variable identification approaches for comparison. The models were applied to a case study, and it was found that the model using the Gamma-GA test has a high potential to predict FIO levels more accurately, although this requires further investigation with different case studies. A correlation analysis was required prior to the variable identification approaches in this study. The need of this analysis highlights the significance of understanding the waterbody and the data set in the development and application of data-driven models. Models using a Gamma-GA test were more capable of predicting extreme (high) FIO concentrations, making a Gamma-GA test more suitable for a bathing water quality early warning system. The importance of nonlinearity in such predictive models was also demonstrated by the better performance of nonlinear ANN models compared with linear regression models regardless of the variable identification approaches used. This paper highlights the importance of nonlinearity in bathing water quality prediction and encourages further utilization of nonlinear models for this application.

Abstract

Despite being the major source of freshwater, groundwater is contaminated with hardness, fluorides, salinity, and so on, and hence, its application for domestic/industrial purposes is severely limited. Existing remediation technologies demand both chemical and energy inputs. Therefore, in this study, an osmotic microbial fuel cell (OsMFC) was developed as an energy-positive and chemical-free technology to achieve simultaneous groundwater softening, defluoridation, salinity reduction, and bioelectricity production. High-quality water was extracted from wastewater in the OsMFC and was applied to reduce groundwater contaminants by dilution. The effects of feed/draw solution (FS/DS) ratio, membrane area, reactor volume, and time on water flux, energy production, and reduction efficiencies of ${\mathrm{Na}}^{+}$, ${\mathrm{Cl}}^{-}$, total hardness (TH), and ${\mathrm{F}}^{-}$ were studied. The increase in FS/DS ratio and membrane area resulted in considerable improvement in the water flux, energy production, and contaminant reduction. However, an increase in the reactor volume had little effect on the overall performance. A maximum water flux of 9.81 litres per square meter per hour [LMH (L/m²/h)] with reduction efficiencies of 75.81%, 76.27%, 72.22%, and 65.76% for ${\mathrm{Na}}^{+}$, ${\mathrm{Cl}}^{-}$, TH, and ${\mathrm{F}}^{-}$, respectively, were obtained with an extended operating time of 168 h. Maximum chemical oxygen demand (COD) removal of 86.6% and current density of ${0.34\mathrm{mA}/\mathrm{m}}^3$ were achieved simultaneously. The study demonstrated a sustainable approach of extracting high-quality water from wastewater and its application in groundwater remediation along with energy production.

Practical Applications

In the present study, we have developed an osmotic microbial fuel cell (OsMFC), which is an in-house treatment system where groundwater remediation and wastewater treatment can be accomplished simultaneously with bio electricity generation. Compared with existing treatment techniques, OsMFC does not require the supply of chemicals and energy. It is a self-driven process with applications such as (1) water recovery; (2) bioelectricity generation; and (3) contaminant dilution using recovered water. The study established a sustainable methodology for extracting better-quality water from wastewater and its application in groundwater contaminant reduction.

Chlorine is commonly used in disinfection processes in wastewater treatment plants. The chlorine solution is typically dosed by turbulent mixing through multiport jet diffusers. The chlorine reacts with the inorganic and organic nitrogenous compounds at a fast rate (in the order of 1 s or less), and a significant portion of the dosed chlorine can be rapidly consumed by the reactions instead of destroying the pathogens. Despite extensive previous research, the chlorine consumption in the complex sewage flow remains an elusive problem. Field-scale experiments have been carried out to study the chlorine consumption in the turbulent mixing of dense chlorine jets with the primary treated sewage effluent of the Stonecutter’s Island Sewage Treatment Works (serving a population of 5.7 million). Based on jet theory and the field tests, it is proposed to discharge the chlorine jets at a location of highest velocity to minimize the contact time of the sewage with high concentration chlorine. Full-scale in-plant experiments demonstrated that significant savings in chlorine can be achieved with optimal jet diffuser design and placement; at nominal applied chlorine dosages of 12 and $20\mathrm{mg}/\mathrm{L}$ in winter and summer, respectively, the chlorine demand can be reduced by up to 30% compared with the conventional dosing design. The relatively simple dosing reconfiguration results in significant savings in chlorine and energy, reduces harmful impact to the environment, and improves plant operation reliability. The chlorine demands from daily operations are well-correlated with the results of the field-scale models. Predictions of the chlorine demand as a function of applied dosage and temperature were obtained from the collective field data.