Journal of Environmental Engineering

Organic micropollutants (OMPs) are becoming more common in drinking water supplies worldwide. Vacuum-UV (VUV) radiation is an incipient chemical-free oxidation process that offers a potentially cost-effective technology for the removal of OMPs. Utilizing a pilot system consisting of two annular VUV reactors, the authors investigated continuous-flow degradation of atrazine, a widely used herbicide, as a model OMP in synthetic and natural surface water. Nearly complete removal (i.e., 97%) of 100 ppb atrazine in an inlet stream was attained for both synthetic and raw surface water samples at a Reynolds number below 4,500. To provide a better understanding of the feasibility of this VUV process for the effective elimination of OMPs, a complete descriptive computational fluid dynamics (CFD) model was developed and validated using the data obtained from the pilot study. The proposed model closely predicted the impact of varying flow rates and water matrix (natural organic matter and alkalinity) on atrazine degradation, with less than 2.8% average absolute relative deviation (AARD%). A sensitivity analysis of the operational variables indicated the critical role of flow rate and background water composition on degradation performance and energy efficiency of the VUV treatment systems. To assess cost-effectiveness of the pilot VUV system for remediation of atrazine-contaminated waters, an electrical energy-per-order (EEO) analysis was conducted, showing that a sequential installation of the two annular VUV reactors was up to 25% more energy efficient than a parallel configuration.

The processes by which oil-material appears suspended in the water column or becomes deposited on the sea floor is conventionally attributed to its attachment to marine solid particles. Since the 2010 Gulf oil spill, a significant volume has remained unaccounted for. The fraction volume of oil sinking resulting from dissolution of its lighter components is the subject of this work. An experimental study and theoretical development for the combined processes of oil-droplet dissolution/sinking (named SOLUTE-SINK) is based on a conceptual binary-component model for crude oil. The experiments were on buoyant pseudo-oils, a two-component (A and B) miscible hydrocarbon mixture formulated from a less-dense-than-water liquid hydrocarbon (Component A) and a more-dense-than-water hydrocarbon-like chemical (Component B). These were used in proof-of-concept experiments. A single, buoyant liquid drop surrounded by water was constrained from floating to the surface in a laboratory-scale microcosm dissolution tank. It was placed inside an inverted and submerged Petri dish so evaporation was not possible and weathering occurred by dissolution only. The heavier-than-water Component B was much less soluble; during the experiment, Component-A dissolution losses resulted in droplet sinking. This established proof-of-concept and the observed time period provided key data supporting the proposed oil binary-model theory. Experiments were performed with four binary chemical mixtures, each replicated 5–7 times. The dissolution time periods for achieving buoyancy inversion (i.e., sinking droplet) ranged from 2 to 4 days with the kinetics parameter dependent on the solubility of Component A. Concentration and bulk density measurements tracked the theoretical time-series behavior of the proposed model equations. Direct mathematical coupling the dissolution/buoyancy loss process for single liquid droplet in the water column is an original contribution of this work. In knowing the initial drop-size distribution, the field of oil-spill modeling is provided with an algorithm forecasting four oil-material produced fractions: dissolved, floating, suspended, and sinking. The SOLUTE-SINK model will find applications for deep-water blowout ejected droplets (constrained to dissolution weathering only) as well as breaking-wave-produced droplets for sea surface spills. In addition, it will aid the development of a laboratory method for the oil dissolution process.

Mixing or mixedness in ultraviolet (UV) wastewater reactors has been identified by many as a key factor in reactor performance. However, the current methods for determining mixing are either qualitative, and cannot be correlated directly with reactor performance, or use ideal mixing states that are not practical. In this paper, a modified Shannon entropy mixedness metric was used to quantify mixing in UV reactors. Contrary to the current literature which has shown that the mixedness only decreases when the number of regions into which the system is divided is increased, it is shown here numerically that mixedness can increase or decrease when the number of regions are increased. As well, it was proven numerically and theoretically that the mixedness will converge to a finite value with a sufficiently high number of regions. Furthermore, a highly simulated system that achieved perfect mixing under the modified mixedness equation produced a reduction equivalent dose (RED) almost 50% higher than the perfect mixing state under the original mixedness. The modification made to the mixedness equation suits the need of a UV reactor, but can also be applied to other process flow systems where mixing and reactor performance are linked. Finally, a very strong correlation between mixedness and UV reactor performance was found for two idealized single-lamp UV reactors. This means that the mixedness calculated here can be used as a proxy for reactor performance, allowing modelers to significantly reduce the computational cost required when comparing the performance of different reactors.

In this study, a central composite design (CCD) allowed the optimal operating conditions to be determined for a new continuous process of spa water disinfection based on an innovative silver composite material. This systemic approach investigated the combined influences of water flow rate, material, and salt concentrations on bactericidal performance at spa water temperature (37°C) using Escherichia coli and Staphylococcus epidermidis as surrogates. The silver desorption was also simultaneously characterized. This multiparametric study highlighted the major contribution of supported silver to the antibacterial action, compared with that of desorbed silver, and enabled a predictive model to be developed that proposed the best and worst process operating conditions regarding bactericidal performances. These conditions were experimentally validated. Antibacterial action was favored by high water flow rate, high material concentration, and low salt concentration. These conditions were shown to improve the contact frequency between microorganisms and active silver material surface. In such conditions, no significant influence from the presence of organic matter or lowered temperature was observed on the disinfection performance.

Accurate water quality prediction can support the early warning of water pollution in water resource management. However, it remains challenging because of hydrological uncertainties in the single scale. A multimodal water quality prediction model based on ensemble empirical mode decomposition (EEMD) and support vector regression (SVR) is proposed to address this problem. Based on the idea of decomposition and ensemble, dissolved oxygen (DO), one representation in water quality, is firstly decomposed into several intrinsic mode functions, which are then modeled by the SVR in each mode. According to the reconstruction theory of the EEMD, the subresults predicted by the SVR of each mode are summarized into the final results. The proposed model is evaluated by the weekly DO concentrations during 2014–2015 from one monitoring station of the Jialing River, China. A back propagation neural network and the standard SVR models are used for a comparison study. The results demonstrate that the addressed model, combining the mode representation capacity of the EEMD and the nonlinear mapping of the SVR, has the best prediction performance among the peer models.

Opencast mining disturbs large areas of land, resulting in a decline in the groundwater table, increased sedimentation rates, and groundwater contamination. The sediment yield from the mined areas can be several times greater than from undisturbed areas. The sediment yields can be greater in the regions with large overburden (OB) dumps, which facilitate surface erosion because they consist of unconsolidated loose materials and induce changes in surface morphology. The present study proposes a modified approach using geoinformatics to estimate the sediment yield in a microwatershed dominated by coal mines and OB dumps. A modified equation has been proposed that uses the drainage and the vegetative cover, the major inputs required for sediment yield estimation. The sediment yields have been estimated for the years 1989 and 2007, during which the OB dump area increased significantly. Land use classes were extracted for 1989 and 2007, using multispectral Landsat and Indian remote sensing (IRS) satellite data. Sensitivity analysis was carried out to examine the performance of the modified approach. The outcome of the study corroborates the utility of multidate, multiresolution satellite data for the estimation of sediment yield. In the absence of field data, the study reveals that satellite data provides the information on the impact of the OB dumps on the quantities of the sediment yields as a result of the enhanced erosion rates. The results obtained in the present study of a mining dominated microwatershed will help administrators and authorities to take the necessary preventive measures for controlling the erosion through proper mine management.

Detention ponds constructed in urban areas should perform two major functions: reduce flood flows and improve quality of runoff by trapping sediments and related pollutants. Providing tools for an efficient and low data–demanding assessment of pond performance can greatly support sediment management at the small catchment scale. This paper adopts the approach of a continuously stirred tank reactor (CSTR) to model the sediment concentration in the stormwater outflow from a small detention pond located in an urbanized catchment. The model is developed and tested using data sets of seven rainfall–runoff–suspended sediment events. Good agreement between observed and estimated outflow from the pond is achieved for both hydrographs and sediment graphs in calibration and validation. Thus results indicate that the present model due to its low data demand can predict sediment graphs at the outlet from such low-volume reservoirs.

In this study, the adsorption of granular activated carbon (GAC) was evaluated in the treatment of slop with the aim of reducing the organic matter concentration in terms of chemical oxygen demand (COD), dissolved organic carbon (DOC), and total petroleum hydrocarbons (TPH). The process was optimized for the oily wastewaters sampled from a floating tank of an oil coastal deposit in the Augusta Harbor (Sicily, Italy). In particular, both batch and dynamic tests were performed. Two different GACs were used and compared. In general, the application of the adsorption process was effective in the treatment of the slop. In fact, the percentages of removal, although rarely exceeding 65% in term of COD, reduced the overall organic load resulting from recalcitrant or poorly biodegradable substances (efficiency greater than 70–80% in terms of DOC and TPH). However, a pretreatment with $20{\mathrm{g}}_{\text{GAC}}/\mathrm{L}$ is also sustainable for the removal of the main contaminants and for the pretreatment of the wastewater, improving the treatment before a subsequent biological process.

The aims of the present study are to verify the performance of four first-order hydraulic models and identify the model that best described the kinetics of the chemical oxygen demand (COD) removal in constructed wetlands. Three horizontal subsurface-flow constructed wetlands (HSSFCWs) were examined: two were planted with Typha latifólia and one was left unplanted. Each HSSFCW received 50 L of secondary effluent daily, resulting in a hydraulic retention time of 3.2 days. The COD concentrations were determined throughout the HSSFCWs and compared in terms of the coefficient of determination with estimated values provided by hydraulic models. The performance of the models was verified under two different conditions: (1) without, and (2) with evapotranspiration (ET) effects. Among the studied models, the plug-flow hydraulic model revealed the poorest performance, whereas the modified plug-flow model (incorporating the coefficient of decay resistance) was the model that best described COD removal kinetics throughout the HSSFCW. The incorporation of water losses by ET improved the performance of all of studied models.