Journal of Environmental Engineering

In the present study, carbon nanotubes (CNTs) are synthesized using the chemical vapor deposition method modified by growing the CNTs on alumina (CNT/alumina). The maximum Congo red (CR) dye removal of 96.4% and 94% is obtained using CNT/alumina and CNTs, respectively, as adsorbents for $10\mathrm{mg}/\mathrm{L}$ initial dye concentration and an adsorbent dose of 15 mg at pH 2 and 30°C. For Direct red (DR) 80 dye, the maximum removal of 90.5% and 87% is achieved using CNT/alumina and CNTs as adsorbents, respectively, for an initial dye concentration of $10\mathrm{mg}/\mathrm{L}$ with an adsorbent dose of 25 mg at pH 4 and 303 K. The adsorption process fits the Langmuir isotherm. For CR dye, the enthalpy ($\mathrm{\Delta }H$) is $13.39\mathrm{kJ}·{\mathrm{mol}}^{-1}$ for CNTs and $25.9\mathrm{kJ}·{\mathrm{mol}}^{-1}$ for CNT/alumina. For DR 80 dye, the value of $\mathrm{\Delta }H$ ($12.446\mathrm{kJ}·{\mathrm{mol}}^{-1}$ for CNTs and $24.086\mathrm{kJ}·{\mathrm{mol}}^{-1}$ for CNT/alumina) indicates that adsorption of both the dyes onto both adsorbents is endothermic. The values of Gibbs free energy for both dyes are negative for the temperature range between 303 and 323 K, confirming that adsorption is spontaneous and thermodynamically favorable.

In regulated rivers downstream of hydropower facilities, understanding how supersaturated total dissolved gases (TDGs) are distributed and dissipated is crucial, as they can negatively impact the aquatic environment. The objective of this study was to quantify the rate of dissipation of supersaturated TDG in the regulated Columbia and Kootenay Rivers and to evaluate whether it can be predicted by surface reaeration theories. Detailed measurements of TDG and river hydraulics were collected during two individual spill events conducted at the Hugh L. Keenleyside Dam (HLK) on the Columbia River and the Brilliant Dam on the Kootenay River. To estimate the dissipation rate, an analytical approach was used that incorporated transverse mixing between the spill and generation flow as well as tributary inflow. For four different gate operations at the HLK Dam, the average rate in the two hydraulically different reaches upstream and downstream of Kootenay River confluence was 0.004 and $0.021{\mathrm{h}}^{-1}$, respectively. In the downstream reach, the rate was $0.038{\mathrm{h}}^{-1}$ during the spill operation at the Brilliant Dam. These rates were about 1.5–3 times higher than the surface transfer predicted by some well known reaeration models. Some potential causes of these higher rates were discussed, particularly the large variation in the downstream reach. Because of limited data availability, a conceptual argument based on gas transfer theories was presented, which indicated that the dissipation rates were likely enhanced by bubble-mediated transfer caused by liquid phase supersaturation.

Microbiologically unsafe drinking water remains a leading cause of child morbidity and mortality in the world despite high investment in water-treatment infrastructure. This study explores the antimicrobial potential of Ag, Cu, Zn, Ni, and Co, at concentrations below the World Health Organization drinking standards, to inactivate a nonpathogenic strain of E. coli in synthetic groundwater (SGW). Disinfection capabilities of Ag and Cu are also tested against bacteria in natural surface water (NSW) to test the effect of a natural and more-complex water chemistry. The influence of changes in pH, ${\mathrm{Cl}}^{-}$, ${\mathrm{HCO}}_3^{-}$, ${\mathrm{Mg}}^{2+}$, and ${\mathrm{Ca}}^{2+}$ concentrations on bacterial inactivation in SGW are also studied. The MINTEQ equilibrium model is used to study the speciation of the metals in solution. The Chick–Watson model is employed for kinetic modelling of the data. The results show that greater than 99.99% bacterial inactivation occurs within 12 h of contact time by Ag and Cu. Concentration and time played a major role in the disinfection process. Co and Ni are ineffective disinfectants. Higher inactivation of E. coli by Ag and Cu is recorded in SGW than in NSW. The inactivation efficiencies of the metals studied follow the trend $\mathrm{Ag}>\mathrm{Cu}>\mathrm{Zn}>\mathrm{Ni}\approx \mathrm{Co}$.

A natural substrate prepared with shellfish shells (Venerupis pulastra) is used for adsorption of orthophosphate (${\mathrm{PO}}_4^{3-}$) from synthetic solutions and effluents in batch essays. Tests of synthetic solutions with varying pH, temperature, rotational speed, substrate mass and particle size obtain 50%–98% phosphorus removal efficiency, which is increased by mass increment (2 g) and minor particle size ($Ø=200–520\mathrm{\mu m}$). Tests with two effluents ($C_{i,{\mathit{PO}}_4^{3-}}=0.5$ and $3.9\mathrm{mg}{\mathrm{L}}^{-1}$) achieve removal efficiencies of 86% and 91%, respectively, demonstrating the potential of the substrate as a green and low-cost technology for the tertiary treatment of effluents and phosphorus recovery.

This study demonstrates the importance of selecting an appropriate liquid-to-solid ratio ($\mathrm{L}:\mathrm{S}$) for batch sorption study (BSS) of bentonite (BE). The current recommended $\mathrm{L}:\mathrm{S}$ is 20 for BSS of soils and sediments, which works well for most of the soils/sediments. However, for expansive soil like BE, $\mathrm{L}:\mathrm{S}=20$ was found to be inadequate due to the formation of thick gel like consistency preventing proper interaction of metal ion with solid surface. This resulted in considerable underestimation of sorption capacity of BE. Effort was made to identify appropriate $\mathrm{L}:\mathrm{S}$ for BE for which there is no specific guideline available in the literature. Under controlled pH condition and ${\mathrm{Pb}}^{2+}$ as the model heavy metal ion, it was noted that the sorption capacity of BE increases with $\mathrm{L}:\mathrm{S}$ beyond 20 and with an increase in initial metal ion concentration. The highest percentage removal of ${\mathrm{Pb}}^{2+}$ was observed at $\mathrm{L}:\mathrm{S}=50$ and lowest at $\mathrm{L}:\mathrm{S}=100$ for initial concentration greater than $300\mathrm{mg}/\mathrm{L}$. The minimum $\mathrm{L}:\mathrm{S}$ possible for BE is 20, below which the interaction between the solution and soil solids becomes difficult due to formation of a thick gel like consistency. The interaction of BE with ${\mathrm{Pb}}^{2+}$ was further investigated from the results of field emission scanning electron microscopy (FESEM) integrated with energy dispersive X-ray spectroscopy (EDX). Fourier transform infrared (FTIR) spectrometer was used to identify the variations in interaction between the ${\mathrm{Pb}}^{2+}$ ions and functional group present on BE for various $\mathrm{L}:\mathrm{S}$. It was concluded that for all practical purposes, $\mathrm{L}:\mathrm{S}=50$ is a suitable ratio for determining sorption capacity of expansive soil like BE.

The performance of ultraviolet (UV) disinfection reactors using experimental data poses major challenges to the water treatment industry, and a regression model has been developed in the water treatment industry to predict UV reactor performance. Genetic programming (GP) can be applied using a process of symbolic regression to create empirical models of data describing a process or system. While classical regression analysis specifies the model structure a priori, GP automatically evolves both the structure and numeric coefficients of the model. GP-derived equations are often computationally complex, however, and do not generalize well for new data sets. This research develops a new model identification procedure that simultaneously identifies an equation to describe a system and hierarchical parameters that are fit for separate data sets. A coupled genetic algorithm (GA) and genetic programming approach (GA-GP) is developed to search for the best-fitting model structure and hierarchical parameter values. Modifications were made to the GA-GP approach to reduce model error while limiting the growth of complex tree structures. The GA-GP method is applied here to identify models for multiple UV reactors by training a model for three data sets. The GA-GP method identified a model with lower error across multiple data sets compared to GP alone, linear regression, and the industry regression model. Including hierarchical terms allowed the search to identify a model that generalizes across multiple data sets.

The present investigation describes the feasibility of modified nanocellulose platelet-shaped gels toward recovery of pyrocatechol violet (PV) dye from aqueous solution. Batch analyses demonstrated that the dye uptake was highly influenced by different process factors which include solution pH, agitation speed, contact time, and temperature. A maximum recovery efficiency of $\ge 90.0\%$ ($\approx 180.38\mathrm{mg}/\mathrm{g}$) was achieved. Optimization attempts were explored via response surface methodology (RSM) and artificial neural network (ANN) models to best predict optimal removal conditions of PV dye. The effect of process variables was investigated by RSM through a three-level, four-factor central composite design matrix. The same design matrix was also applied to achieve the training set for ANN. The results of the two models, on the basis of the experimental data, were compared for their predictive accuracy in terms of coefficient of determination ($R^2$), Chi square (${\chi }^2$), and sum of squared error (SSE). Results proved that ANN design possesses higher prediction accuracy as compared with RSM. Furthermore, adsorption thermodynamics and kinetic evaluations revealed that the process was exothermic, spontaneous in nature, and was best described by a pseudo 2nd order kinetic model ($R^2>0.990$). These environment-friendly platelet-shaped gels could be potential promising candidates for dye removal from industrial effluent.

Street sweeping is a routine roadway maintenance activity that functions as a nonstructural stormwater best management practice. Further, the road-deposited sediment collected during sweeping operations has the potential for beneficial reuse in a number of different applications but first must be characterized in terms of its toxicity to ensure that it is safe to do so. This study provides a chemical characterization of this material regarding heavy metals, polycyclic aromatic hydrocarbons, and oil and grease, and attempts to predict the concentration of these contaminants using average daily traffic, land cover, and particle size. Seventy-nine locations were selected from six average daily traffic (ADT) categories ranging from 1–400 to greater than 10,000 vehicles per day and four land cover categories including developed, open space; developed, low intensity; developed, medium intensity, and developed, high intensity. Average concentrations of As, Pb, Se, Ba, Cr, Ag, Cd, Cu, and Zn were 0.39, 7.3, 0.32, 14, 6, 0.046, 0.83, 0.89, and $30\mathrm{mg}/\mathrm{kg}$, respectively. The average total polycyclic aromatic hydrocarbons (PAH) concentration of all 79 sites was $\mathrm{17,000}\mathrm{\mu g}/\mathrm{kg}$. Oil and grease concentrations in the material ranged from 34 to $\mathrm{3,400}\mathrm{mg}/\mathrm{kg}$. The results showed that both average daily traffic and land cover cannot be used to predict the contaminant load of this material. However, a strong correlation was observed between particle size and the concentrations of all heavy metals and PAHs.

Municipal solid waste landfills utilize drainage material (oftentimes a sand with high-hydraulic conductivity) to prevent the accumulation of leachate on the bottom liner. The drainage media must meet specification criteria to ensure adequate performance. At a Florida landfill site, the mine tailings meeting all specification criteria were used as drainage media, and after heavy rainfall prior to waste placement, humic substances washed from the media into unlined stormwater collection ponds, causing elevated turbidity levels. Effluent turbidity of landfill drainage sand can have negative impacts on leachate collection and stormwater systems, but may not be adequately addressed by typical material specifications. Tests were performed on impacted stormwater and the mine tailings, as well as several control materials, and while all met the standard material specification requirements, differences in organic material content and effluent turbidity were noted. Stricter organic content specifications and/or additional test specifications for effluent turbidity are recommended to prevent turbidity impacts caused by organic material in drainage sand.