Journal of Environmental Engineering

In this study, a factorial dual-interval programming (FDIP) approach is proposed through integrating factorial analysis and dual-interval linear programming into a general framework. The developed FDIP approach can handle uncertainties (i.e., single-interval and dual-interval) that exist in the left-hand side and right-hand side of the system objective function and in the associated constraints. Moreover, it has the advantages in identifying significant parameters along with their joint effects on the system outputs. A case study of municipal solid waste (MSW) management is adopted to demonstrate the applicability of the proposed approach. Reasonable results have been generated for the waste flow allocation schemes with minimized system costs; impact factors and their interactive effects have been identified and analyzed for the lower bound and upper bound of the system outputs under various scenarios. It is indicated that the effect of operational costs of the waste-to-energy (WTE) facility during the first period is most influential and positive to the system costs; such operation costs have a slightly larger effect on the lower bound of the system costs than that on the upper bound of the system costs, providing valuable information when it comes to decision making.

A study of sorption of aqueous organics by aquifer materials was undertaken with an objective to correlate sorption parameters with the octanol-water partition coefficient ($K_{OW}$) of aqueous samples. In the first phase, synthetic samples were equilibrated with the aquifer material collected from the river bank filtration (RBF) site located on the bank of the river Alaknanda at Srinagar, Uttarakhand, India. In the second phase, water from the river Hindon at Barnawa, Uttar Pradesh, India, was stirred with the Srinagar aquifer material, and a sample of water from the Elbe River was mixed with the aquifer material from the RBF site in Torgau, Germany. The fraction of organic carbon content ($f_{oc}$) in the aquifer material from Srinagar and Torgau was 0.018 and $0.0027\mathrm{mg}/\mathrm{mg}$, respectively. The hydrophilic and hydrophobic nature of the synthetic samples and the water samples from the rivers Hindon and Elbe were determined by measuring $K_{OW}$ and specific ultraviolet absorbance (SUVA). Empirical correlations between log $K_{OW}$ and (1) adsorption capacity ($Q_m$), (2) soil-water partition coefficient ($K_d$), and (3) organic carbon-water partition coefficient ($\log K_{OC}$) for hydrophilic and hydrophobic samples have been developed. The values predicted from the model and experimental observations were statistically analyzed by the regression analysis model (RAM) and analysis of variance (ANOVA). The analysis did not indicate a significant difference between the experimental data and computed data of sorption parameters from log $K_{OW}$. The similarity between log $K_{OC}$ from (1) $K_d$ (slope of the sorption isotherm) and (2) log $K_{OW}$ was within a 95% confidence limit. The Freundlich isotherm constant ($K_F$) has been found to increase with an increase in $K_{OW}$, whereas no such correlation was noted for the Langmuir isotherm constant ($K_L$). A correlation between the sorption parameters ($Q_m$, $K_d$, and $K_{OC}$) and SUVA was not observed.

Emerging contaminants traditionally have not been measured in the environment, but they recently have been detected in various water systems as a result of advancements in analytical methods. These contaminants pose potential threats to ecosystems and public health, but are generally not regulated, nor are they required to be routinely monitored. This paper presents the implementation of watershed-scale monitoring-site selection as an effective monitoring design for emerging contaminants. The study aimed to identify critical areas of emerging contaminants for both point and nonpoint sources in five selected watersheds in the United States with different land-use compositions and climate conditions. Spatial association analysis using the Getis-Ord’s $G{i}^{*}$ statistic was employed to identify clusters of point and nonpoint emerging contaminants considering the impact of neighboring subwatersheds. This analysis identified subbasins containing major wastewater treatment systems as point-source hotspots and those containing and surrounded by concentrated agricultural activities or urban residential areas as nonpoint-source hotspots The results, supported by the measurement data, indicated that the outlets of these identified hotspots should be monitored during both dry- and wet-weather periods in order to understand their impacts on receiving waters. The significance of monitoring point- and/or nonpoint-source pollution was dictated by the pollution source distribution, watershed characteristics, and climate settings. The approach in this study provides a quantitative basis for selecting monitoring locations and managing emerging contaminants that can be applied to other watersheds.

This study investigated the impact of model form and flexibility on estimates of constituent loads to a water-supply reservoir. A series of load-estimation regression models were calibrated and used to predict nutrient (nitrate-nitrogen and total phosphorus) and organic carbon loads from three major tributaries of a water-supply reservoir. These models included traditional linear models (LMs) as well as semiparametric generalized additive models (GAMs). The relative performance of each model was determined using cross-validation. GAMs, which employ more flexible model structures, outperformed LMs in most cases, explaining an additional 2% of load variance and 5% of concentration variance in validation data on average. Resulting point load estimates from the 1.5-year study period were similar between the two modeling approaches, yielding overlapping 95% confidence intervals in all nine cases modeled. A novel graphical method was developed to present relative agreement between the two model types as a function of the time interval over which the load is estimated. This revealed relative differences between the two modeling approaches in excess of 100% depending on the time interval of the load estimate. The time-dependent disagreement between similarly well-performing models highlights an aspect of model uncertainty not visible in more structurally restrictive modeling approaches.

A process model was developed using a lifecycle approach to estimate the cost and energy use associated with municipal solid waste collection, which is the most fuel-intensive and often the most costly aspect of solid waste management. The model divides collection service areas into single-family residential, multi-family residential, and commercial sectors with sector-specific, user-defined characteristics, including population, waste generation, and waste composition. Waste is collected by a set of processes (e.g., residual waste, recyclables collection) defined by costs, collection activity parameters, and energy use. The model overpredicted fuel use by $~25\%$ compared with data obtained from actual single-family residential collection routes and their average fuel efficiencies, but was within 10% when modal fuel efficiencies (e.g., driving, idling) were considered. Adding recyclables or yard waste collection to a mixed waste collection program increased fuel consumption by approximately 75% per metric ton (Mg) and doubled cost, whereas adding both services more than doubled fuel use and tripled cost. Increasing recyclables and residual collection frequency from biweekly to weekly resulted in a predicted 53% increase in fuel consumption and 39% increase in cost. Sensitivity analysis illustrated the relative impact of changing individual parameters (e.g., route to disposal facility distance, average time at each stop) and highlighted the need for a mechanistic model that is responsive to variations in input values.

A field experiment was conducted to assess the effect of wastewater irrigation and various amendments on the bioavailability of metals to crops and its yield. Alfalfa was sown in $2\times 1\text{-}\mathrm{m}$ plots receiving different amendments in a randomized complete block design with three replications. Five different amendments, farmyard manure (FYM; $10t/\mathrm{ha}$), poultry manure (PM; $10\mathrm{t}/\mathrm{ha}$), humic acid (HA; $2.5\mathrm{kg}/\mathrm{ha}$), di-ammonium phosphate (DAP; $120\mathrm{kgP}/\mathrm{ha}$), and triple superphosphate (TSP; $120\mathrm{kgP}/\mathrm{ha}$) were applied to the soil prior to sowing crop along with a control receiving either wastewater or tubewell without amendments. The plants’ biomass results indicated that wastewater irrigation, when supplied with or without amendment, produced significantly higher yield (56% increase due to HA and wastewater application) than tubewell irrigation, indicating its nutritive value. Concentrations of Cu, Ni, Pb, and Fe accumulated by crop from wastewater were higher (84%, 94%, 112%, and 45%, respectively) and may cause phytotoxicity if untreated wastewater is used in the long term. Application of FYM, HA, and DAP reduced the uptake of metals, probably by forming insoluble complexes with metals; thus, they are recommended as amendments where wastewater is applied to decrease the possibility of heavy metals entering food chain.

Rainwater harvesting (RWH) systems provide the dual, but often opposing, benefits of acting as alternate water supply sources and providing detention/retention of roof runoff that would otherwise become stormwater runoff. A major challenge that exists when using a RWH system to simultaneously accomplish stormwater and water-conservation benefits in nonarid regions is that these systems are often underutilized, thus remaining full a large portion of the time. For a system to mitigate stormwater runoff, however, there must be sufficient room available in the tank to store a runoff event. Two novel approaches were implemented to improve the ability of RWH systems to serve as both water-conservation practices and stormwater-management practices: an active release technology and a passive release technology. Two locations in Craven County, North Carolina, had RWH systems installed to capture roof runoff and store it for nonpotable uses. One system was equipped with the passive release mechanism, which divided the storage tank into a detention storage volume that was slowly drained between storm events, and a retention storage volume, which was retained for harvesting. The other system included an active release mechanism that automatically released harvested water based on real-time forecasted precipitation and current RWH system conditions. Despite minimal usage, both systems provided substantial stormwater mitigation. The passive release system averaged 82 and 90% volume and peak flow reductions, respectively, while the active release system reduced volumes and peak flows by an average of 91 and 93%, respectively. Both of these mechanisms exhibit great promise in revolutionizing rainwater harvesting system use to meet both water-conservation and stormwater-management goals.

The aim of this paper is to propose a step by step method to establish and validate a relevant, dynamical model of the activated sludge process for the paper mill industry. The model is established by considering the specificities of the effluent to be treated. It uses the biochemical oxygen demand (BOD) measurement, which allows a direct correlation between the state variables of the model and the measurements. This model is validated on a pilot plant of semi-industrial size fed with industrial paper mill effluents. The parameter estimation is based on an analysis of the sensitivities. The results are compared with a model based on chemical oxygen demand (COD) partitioning which is issued from the simplification of the activated sludge model number 1 (ASM1) model. Finally, the model dealing with BOD measurements not only shows the best performances, but is also the easiest to implement, overcoming one main obstacle to efficient monitoring and control in paper mill wastewater treatment plants.

In this paper, degradation of bisphenol S (BPS) in spiked water and postsecondary-treated wastewater by a variety of oxidation processes was investigated in a flow-through reactor. Kinetics of degradation in ${\mathrm{O}}_3$, ultraviolet $(\mathrm{UV})/{\mathrm{O}}_3$, $\mathrm{UV}/{\mathrm{H}}_2{\mathrm{O}}_2$, and $\mathrm{UV}/{\mathrm{O}}_3/{\mathrm{H}}_2{\mathrm{O}}_2$ were determined and reported. The degradation of BPS by ${\mathrm{O}}_3$ alone was competitive with the UV-promoted methods. An increase in BPS loss with ${\mathrm{O}}_3$ was observed in postsecondary-treated wastewater, demonstrating its potential application as a treatment method for BPS. Total organic carbon (TOC) as an indicator of the extent of organic compound mineralization and sulfate as a by-product produced during degradation were measured. It was noted that although the loss of BPS was similar in the $\mathrm{UV}/{\mathrm{O}}_3/{\mathrm{H}}_2{\mathrm{O}}_2$ and the ${\mathrm{O}}_3$ processes, the overall mineralization rate was different, indicating that the combination technique offers a more efficient system in terms of overall mineralization rate. The $\mathrm{UV}/{\mathrm{O}}_3/{\mathrm{H}}_2{\mathrm{O}}_2$ process was the most effective and led to complete mineralization of $50\mathrm{mg}/\mathrm{L}$ BPS within 90 min in both spiked water and postsecondary-treated wastewater.