Journal of Environmental Engineering

The study aims to understand when the effort required to run a distributed and detailed water balance model leads to effective better results, when compared with a lumped, data-parsimonious, and easier-to-apply hydrological model. The study compares the results obtained from a lumped hydrological model with the results from soil water assessment tool (SWAT) when used to estimate stream flow values from precipitation and climate data. Both models use the curve number (CN) concept, determined from land use, soil hydrologic group, and antecedent soil moisture conditions, and were run with a daily time step. The lumped model input variables and parameters are considered to be uniformly distributed throughout the watershed, while the SWAT model requires an extensive and detailed spatial data, including weather data (rainfall, temperature, humidity, wind, and solar radiation), physical characteristics of the basin (topography and drainage network), as well as soil and land use data. The effort required to fully understand SWAT formulation, to obtain the needed data and to calibrate the model, is time consuming and does not lead to significant better results, when compared with the lumped model results. The results confirm that in many situations, the simpler lumped model leads to reliable values of hydrological variables, both at a daily and monthly scale. The models’ predictability power is higher at a monthly time step, because both models fail to reproduce the daily flow values fully in a consistent way, although they are able to reproduce the overall variability. Lack of data to describe the precipitation accurately may explain the poorer model performance at the daily time step. The study concludes that when available data fail to represent the spatial distribution of the input variables and model parameters, there is little advantage in using the more complex distributed model.

The control of biofilm thickness is one of the challenges of using the membrane aerated biofilm reactor (MABR) because high thicknesses block oxygen and substrates transferred to the biofilm layers, resulting in MABR performance decay. This research used two recirculation flow velocities for biofilm thickness control: $0.025\mathrm{m}/\mathrm{s}$ in the first experiment and $0.065\mathrm{m}/\mathrm{s}$ in the second experiment, and activity was evaluated through the chemical oxygen demand (COD) removal rate. In the MABR operated in sequential batches using raw domestic sewage, COD removal efficiencies of 56 and 83% were reached for the first and second recirculation velocities, with COD concentration in influent and effluent of 440 and $190\mathrm{mg}/\mathrm{L}$ in the first experiment and 420 and $70\mathrm{mg}/\mathrm{L}$ in the second experiment, respectively. Thus, the variation of the recirculation velocity was shown as an option for biofilm thickness control in MABR.

Degradation by high frequency ultrasound (US) of the endocrine disruptor, benzophenone-3 (BP-3) is a promising treatment process as it does not need additives and does not generate waste. In this paper the variables affecting this process were studied. The frequency effect on initial degradation rates was analyzed for various frequencies between 215 and 1,134 kHz, and an optimum frequency of 574 kHz was found in this range. Power density had a positive effect on degradation rates over the whole work range. Kinetics adjusted statistically well to a pseudolinear kinetic model. According to these results and those for degradation in presence of radical scavengers, a conclusion was made that US BP-3 degradation was taking place in the bubble/liquid interphase. Toxicity test was conducted by Microtox methods, finding an $E{C}_{50}$ for 5 min of $1.7\mathrm{mg}/\mathrm{L}$, and for 15 min of $2.07\mathrm{mg}/\mathrm{L}$. Toxicity profile along degradation path showed a decrease at the beginning growing after 30% of BP-3 degradation. Four possible degradation byproducts were found by gas chromatography–mass spectrometry (GC-MS) analysis, and a degradation path was proposed.

The performance of the anaerobic ammonium oxidation (ANAMMOX) process was investigated in two identical sequencing batch reactors (SBRs) [designated as SBR1 (tourmaline addition) and SBR2 (check reactor)] at nitrogen loading rates (NLRs) varying from 0.73 to $4.90\mathrm{g}\mathrm{N}/(\mathrm{L}·\mathrm{d})$ and constant hydraulic retention time of 6 h. Both of the removal efficiency of ammonia nitrogen and total nitrogen were higher in SBR1 than that in SBR2 with increased NLR. The specific ANAMMOX activity (SAA) of the ANAMMOX sludge increased from 3.23 to 12.87 and from 2.83 to $8.53\mathrm{mg}\mathrm{N}/[\mathrm{g}\mathrm{volatile}\mathrm{suspended}\mathrm{solids}(\mathrm{VSS})/\mathrm{h}]$ in the SBR1 and SBR2, respectively, which increased approximately 4.0- and 3.0-fold. As compared with SBR2, SBR1 possessed the ANAMMOX sludge with higher yield coefficient and decay constant, i.e., $0.2608\mathrm{g}\mathrm{biomass}/\mathrm{g}$ substrate and $0.011/\mathrm{d}$, respectively. According to the modified Stover–Kincannon model, the maximal substrate removal rate ($U_{\max }$) and saturation rate constant ($K_b$) of SBR1 were suggested as $125.0\mathrm{g}\mathrm{N}/(\mathrm{L}·\mathrm{d})$ and $151.7\mathrm{g}\mathrm{N}/(\mathrm{L}·\mathrm{d})$, respectively, which were much higher than $21.6\mathrm{g}\mathrm{N}/(\mathrm{L}·\mathrm{d})$ and $26.2\mathrm{g}\mathrm{N}/(\mathrm{L}·\mathrm{d})$ of SBR2. Results showed that SBR1 obtained the excellent and stable performance, and the modified Stover–Kincannon model could be used to describe the kinetic behavior or design ANAMMOX reactor enhanced by tourmaline.

Two biopolymers were prepared by reaction of chestnut and quebracho tannins with gelatin extracted from untanned hide wastes. Obtained biopolymers were evaluated as adsorbents for removing Cr(VI) from water using the batch equilibrium technique. Adsorption of Cr(VI) by gelatin–chestnut (GC) and gelatin–quebracho (GQ) biopolymers was investigated as a function of initial pH, adsorbent mass, contact time, and initial metal ion concentration. Maximum Cr(VI) uptake was obtained at pH 4 and the percentage of Cr(VI) adsorbed increased significantly by increasing the biopolymer mass. The contact times that were enough to reach equilibrium were 90 and 150 min using GC and GQ, respectively. The pseudo-second-order equation provided the best kinetic model for the biosorption process ($R^2=0.9999$ for GC and $R^2=0.9916$ for GQ). The intraparticle diffusion model was also investigated to describe the adsorption kinetics of Cr(VI) onto synthesised biopolymers. Langmuir and Freundlich isotherms were applied to describe the experimental equilibrium data obtained at $25\pm 2°\mathrm{C}$. The process was well described by Langmuir isotherm and the maximum uptake values, $Q_{\max }$, were 80.64 and $26.25\mathrm{mg}/\mathrm{g}$ for dry GC and GQ biopolymers, respectively.

The US Environmental Protection Agency (EPA) proposed a new “Effluent Limitations Guidelines” for construction site runoff management in 2009, which required that stormwater effluents be sampled and that the daily average turbidity must not exceed 280 NTU. Although this numeric limitation was removed from its final amendment in 2014, the EPA still reserves the right to reconsider it in future regulations. To better understand the limits of the turbidity in the effluent, stormwater runoff samples were collected at different times during storms from five highway construction sites in Wisconsin. Measured turbidity in grab samples taken during or after storms ranged from 20 to 2,300 NTU. Sample analyses showed that a power law relation can well describe the correlation between turbidity and the total suspended solids in construction site effluent. Automated turbidity sampling devices were deployed at outfalls of four selected sites to continuously record the time series of turbidity. Statistical analyses were conducted on turbidity data and the precipitation time series. Both the peak and the maximum daily average turbidity values were found to be linearly correlated with the total precipitation, while they are not correlated with either the average or the peak rainfall intensity. It is also demonstrated that a characteristic unit runoff turbidity function, which represents the response of turbidity with respect to a unit precipitation depth, can be reconstructed from a measured time series. Reconstruction of the turbidity response function and the observed statistical correlations suggest that it is possible to develop models to predict the daily maximum turbidity and the total turbidity load of construction site runoff for designated storm events. Models of this kind are valuable for future management practice and for evaluating new regulation policies.

Regenerative stormwater conveyance (RSC) is an open-channel, sand-filtering system composed of a series of shallow aquatic pools, riffles and weirs, native vegetation, and underlying media beds. Surface runoff entering a RSC is conveyed as nonerosive surface flow or subsurface seepage through the media, and exits the system as surface flow, seepage out, exfiltration into the parent soil, or evapotranspiration (ET). While RSCs are expected to perform similarly to other sand-media-based low-impact development (LID) stormwater control measures (SCMs), little field research on this emerging technology have been published to date in peer-reviewed literature. Hydrologic and water quality of a RSC in the Piedmont (Alamance County) ecoregion of North Carolina was monitored from July 2013–June 2014. The Alamance RSC reduced volume and peak flow by a median 78 and 76%, respectively, while mimicking both predevelopment hydrograph shape and hydrologic flow pathways. RSC outflow matches the modeled predevelopment hydrograph shape and pathway components, including both pre-event and event water, as determined by deuterium isotope concentrations. Optimal storm mitigation performance is expected when RSCs include (1) a minimum of three pool/riffle cells, (2) established vegetation, and (3) exfiltration trenches to promote exfiltration into parent soils through extended subsurface ponding. By combining seep out water with surface flow from the RSC, the practice reduced incoming total suspended solids (TSS), total phosphorus (TP), and total nitrogen (TN) loads by a median of 70, 20, and 26%, respectively, likely due to filtration. The potential exists for further nutrient reduction if vegetated, wetlandlike conditions are present. Moreover, locating the RSC over more permeable soils would likely improve hydrologic performance.

${\mathrm{MnO}}_{\mathrm{x}}\text{-}\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$ composite is prepared and characterized by X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), X-ray fluorescence (XRF), ultraviolet–visible (UV-vis) spectroscopy, and surface area analysis. The prepared ${\mathrm{MnO}}_{\mathrm{x}}\text{-}\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$ composite is used as a catalyst to examine the performance of visible light photocatalytic ozonation. The results prove that the ${\mathrm{MnO}}_{\mathrm{x}}\text{-}\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$ composite has good catalytic activity for oxalic acid removal during the photocatalytic ozonation process. Compared with bare $\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$, the $1:20{\mathrm{MnO}}_{\mathrm{x}}\text{-}\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$ increases the removal of oxalic acid from 24.8 to 91.2% in 60 min. The manganese combined in the $\mathrm{g}\text{-}{\mathrm{C}}_3{\mathrm{N}}_4$ mainly exists in the form of oxide with valences of III and IV. The oxalic acid removal is partly through the oxidation by reactive oxygen species such as ${}^{·}{\mathrm{O}}_2^{-}$ and partly through the charge transfer between different valences of manganese species, whereas ${}^{·}\mathrm{OH}$ accounts for only a negligible part of the oxalic acid removal.

Bioleaching is a process that uses microorganisms to perform dissolution of sulfide minerals. Actually, most copper is found as chalcopyrite ore, which is the most abundant form of copper sulfide, but it is recalcitrant to dissolution. The biggest challenge for biohydrometalurgy is the microorganisms involved in it. This study aims to obtain mutants of Acidithiobacillus ferrooxidans by using a methodology that uses classical genetic tools [ultraviolet radiation (UV)], and evaluates its efficiency by using mathematical tools (mathematical modeling and desirability). The mutant strains were evaluated considering their kinetics of initial velocity of ferrous ions oxidation. The selective pressure of UV caused different profiles in the consumption kinetics of strains’ energy sources. The cells with higher consumption kinetics than the wild strain were submitted to shake flask experiments in the presence of chalcopyrite and evaluated by mathematical models. The cell culture irradiated for 1 minute outperformed the wild strain in copper solubilization according to the desirability parameters. The mathematical tools allowed confirming that the UV protocol improved the bioleaching capability of Acidithiobacillus ferrooxidans.

Compost is a self-heating process in which organic matters are stabilized by microorganisms. Fungi are one of the suitable indicators of compost stabilization, but many parameters affect their growth. The aim of this paper was to determine the correlation between fungal density and some operational parameters during the composting process. We quantified taxonomic composition of the fungi in the compost. Compost mass was divided into four thermal phases and sampled over 100 days. Sabouraud dextrose agar medium was used for growth colonies. The samples were incubated at 37°C (thermotolerant) and 45°C (thermophilic) for 3–7 days. The colonies were counted and identified by slide culture methods. Then, the correlation between fungal communities and physicochemical parameters was determined by Pearson’s test. Data were analyzed with Excel 2007 and SPSS 19. The density of thermotolerant and thermophilic fungi were $0.5\times {10}^6$ and $0.25\times {10}^6$ colony-forming unit/gram (CFU/g), respectively. However, there was an adequate linear correlation between the thermophilic fungal density and temperature ($r=0.456$, $p<0.001$) and thermophilic fungal density and pH ($r=-0.5$, $p<0.001$), and there was not a significant correlation between thermophilic fungal density and moisture ($r=0.2$, $p=0.12$) or fungal density and heavy metals ($p>0.05$). Moreover, the strength of correlation between pH or moisture with fungal density was lower than that of temperature. Although there was no significant correlation between the density of fungi and concentration of heavy metals, only species resistant to heavy metals (i.e., A. fumigatus and Paecilomyces) were isolated. With regard to the results of this paper, thermophilic fungal communities were correlated to operational parameters such as temperature and pH. Only the effects of temperature and pH were significant.

In the present study, adsorbents of zeolite and peat were modified in two ways, one using cationic surfactant of hexadecyltrimethylammonium bromide (HDTMABr) and sodium hydroxide (NaOH), and the other using hydrochloric acid (HCl). Adsorbents were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, and Brunauer–Emmett–Teller analysis. The modified adsorbents were applied to remove salinity ions from irrigation saline water. Batch experiments were used to evaluate the adsorption capacity of salinity ions and the effects of contact time, concentration, and adsorption on irrigation water quality parameters. Then, kinetics and adsorption isotherms were evaluated. The adsorption capacity of salinity ions by modified adsorbents in different electrical conductivity ($EC$) was between 26.13 and $212.25\mathrm{mg}/\mathrm{g}$. Between adsorbents, modified peat with HDTMABr and NaOH had the best effect in adsorption of salinity ions. The average reductions in electrical conductivity ($EC$) of 5.58, 10.41, and $20.4\mathrm{dS}/\mathrm{m}$ for different adsorbents were 1.24, 2.65, and $4.96\mathrm{dS}/\mathrm{m}$, respectively. For all adsorbents, the kinetic data were described better by the pseudo-second-order kinetic model than by the pseudo-first-order kinetic model, and isotherm data were fitted better by the Freundlich model than by the Langmuir model.

The Northwest Regional Water Reclamation Facility (NWRWRF) in Hillsborough County, Florida, is considering whether to switch from disinfection via ultraviolet (UV) radiation to disinfection via chlorination. To aid in this decision, chlorine demand and trihalomethane (THM) formation potential were assessed following chlorination of NWRWRF effluent at different temperatures, chlorine doses, and contact times. A chlorine dose of $9\mathrm{mg}/\mathrm{L}$ was adequate to meet the strict disinfection guidelines ($C·t\ge 120\mathrm{mg}·\min /\mathrm{L}$) at 16 or 23°C, but a dose of $12\mathrm{mg}/\mathrm{L}$ was required at 30°C. Chloroform, bromodichloromethane, and dibromochloromethane were formed as disinfection by-products following chlorination; bromoform was not observed. Semiempirical equations were developed that can adequately predict the concentration of chloroform, bromodichloromethane, and total THMs as functions of temperature, chlorine dose, and contact time. THM formation in NWRWRF effluent followed the same general trends as had been observed previously in other studies on chlorination of wastewater, but specific details or dependencies are site specific. For instance, THM formation in NWRWRF effluent was much less sensitive to chlorine dose than had been observed previously. The authors conclude that changing from UV disinfection to chlorination may be a viable option for NWRWRF, especially under new regulatory limits (recently promulgated by the Florida Department of Environmental Protection) for THMs discharged to Class II or III receiving waters. Bromodichloromethane is the THM of principal concern because all other THMs were formed at concentrations considerably below prior and current regulatory limits.

Anthropogenic activities are continually transforming the Earth’s surface and resulting in significant disturbances of ecosystem services including those provided by soil resources. However, advances in chemical, biological, and material sciences make it possible to develop both preventive and corrective solutions to soil pollution problems. Here we present the results of preliminary studies on the elimination of the bioavailable fraction of copper (Cu) and zinc (Zn) from contaminated soils, by taking advantage of enhanced corrosion of zero-valent iron (ZVI) particles and their strong magnetic characteristics to retrieve the formed heavy metal-ZVI complexes from treated soils. The 48-h Ceriodaphnia dubia acute toxicity assay and MetPLATE were used to assess the ability of the tested remediation approach to eliminate Cu and Zn toxicity as a function of soil types and contact time between metals and soils, with or without wet-dry cycles. In sandy soils, the toxicity associated with the water extractable Cu and Zn decreased by two orders of magnitude after treatment. In organic-rich soils, differences in the affinity of Cu and Zn for soil organic matter drove the observed toxicity removal trends, with Cu toxicity mitigation linked primarily to its high affinity for soil organic matter. Trends of the removal of Zn toxicity in organic-rich soil mimicked those observed in sandy soil, but with the removed toxicity units varying just within one order of magnitude.

There is increasing demand on operators of small-scale wastewater treatment plants (WWTPs) to improve biological nutrient removal and energy efficiency while being subject to unique challenges, including reduced resources. Automated monitoring and control strategies of WWTPs can provide the necessary tools to improve plant performance and energy efficiency. However, online sensors for key parameters such as ammonium can require excessive maintenance, are unreliable unless frequently maintained, and often are not affordable. In addition, control techniques such as machine learning may not be financially or technically compatible within the constraints of small-scale WWTPs. This study analyzes the use of low-cost, reliable surrogate sensors in association with inexpensive and robust programmable logistic controllers to improve WWTP performance and energy efficiency through automation. The paper presents three novel methodologies for control of batch WWTPs using pH and oxidation reduction potential (ORP) trends. Applying and optimizing these methodologies enabled an average reduction in cycle time and energy consumption of 60 and 43%, respectively, when compared to the fixed-time treatment cycle and an average effluent ammonium concentration of $1.9\mathrm{mg}/\mathrm{L}$. The automated system proposed has significant potential to enhance the performance of small-scale WWTPs in terms of environmental compliance and energy consumption.

In this study, a novel adsorbent process was developed using a deep eutectic solvent (DES) system based on benzyltriphenylphosphonium chloride (BTPC) as a functionalization agent of carbon nanotubes (CNTs) for arsenic ion removal from water. The nonlinear autoregressive network with exogenous inputs (NARX) neural network strategy was used for the modeling and predicting the adsorption capacity of functionalized carbon nanotubes. The developed adsorbent was characterized using zeta potential, Fourier transform infrared (FTIR), and Raman spectroscopy. The effects of operational parameters such as initial concentration, adsorbent dosage, pH, and contact time are studied to investigate the optimum conditions for maximum arsenic removal. Three kinetic models were used to identify the adsorption rate and mechanism, and the pseudo-second order best described the adsorption kinetics. Four statistical indicators were used to determine the efficiency and accuracy of the NARX model, with a minimum value of mean square error, $6.37\times {10}^{-4}$. In addition, a sensitivity study of the parameters involved in the experimental work was performed. The NARX model prediction was consolidated with the experimental result and proved its efficiency at predicting arsenic removal from water with a correlation coefficient $R^2$ of 0.9818.

In this study, the advanced oxidation process for dye removal from textile wastewater treatment was investigated by means of an experimental setup in which the effect of several parameters on dye removal efficiency [peroxydisulfate concentration, ultraviolet (UV) irradiation, temperature, dye concentration, and time] was examined. In order to predict the removal efficiency, two types of artificial neural networks were used: an adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network determined with differential evolution called hybrid self-adaptive differential evolution with neural networks (hSADE-NN). After the successful development of ANFIS, its ability to predict test data was checked. Also, a series of models of the process was determined with hSADE-NN. Comparison of the two approaches indicates that both methods provide good results, the average absolute relative error for hSADE-NN being 3.61% and that for ANFIS 5.18%. After that, a process optimization was performed, the scope being to determine the conditions for maximum dye removal efficiency under various constraints, considered as a means to reduce resources consumed.

A petroleum contaminant plume, Diesel No. 2 in this case, atop shallow groundwater had been under cleanup for more than two decades using traditional methods of bailing, skimmers, and other techniques that reduced the plume-free product depth to mostly sheen over the plume footprint of about $\mathrm{1,300}{\mathrm{m}}^2$. It was assumed that the plume had been essentially cleaned up and was no longer a risk in the shallow poor-quality groundwater, which was perched atop an aquitard, protecting potable aquifers below. After this long period of cleanup, the petroleum pool began to significantly thicken as the shallow groundwater surface levels began to rise. Based on this field case, it is shown that the significant plume increase in thickness was attributable to the capillary fringe behavior.

In this paper, a simple derivation of the space fractional advection-diffusion equation (fADE) under the steady condition is proposed from a generalized mixing length concept. The obtained equation is a fractional Fickian-type diffusion equation in the steady-state condition. The space fADE is solved and an analytical solution is obtained in terms of the generalized two-parameter Mittag-Leffler function. The model has been applied to investigate the suspension distribution of sediment particles in open-channel turbulent flows over erodible sediment beds. The obtained results show that the fADE is able to predict the Type II profile (where the maximum concentration appears at some distance above the bottom of suspended-load layer) of the suspension concentration distribution in such flows, unlike the standard advection-diffusion equation. Apart from this, the model also describes the Type I profile (where the maximum concentration appears at the bottom of the suspended-load layer) of the suspension concentration distribution of particles well. The outcome of this study indicates that underlying diffusion of particles can be anomalous and exchange of momentum can happen within nonadjacent layers in the Type II distribution. The model is validated with experimental data available in the literature, and the results are satisfactory. Validation results show that the parameter $\beta$ in the Type II profile depends on specific gravity, diameter, and settling velocity of particles. A nonlinear regression analysis is carried out to express the dependency and practical application of the model.