Journal of Environmental Engineering

A dialogue concerning potential future directions for the wastewater profession is initiated by identifying four principal challenges. The first is the perception by many (at least in the United States) that water pollution and water quality problems have largely been solved. Dramatic improvements during the 20th century (by the founders of our profession, not by us!) have eliminated many of the obvious public health and environmental issues associated with wastewater management. The second is population growth and the associated added stress on water resources. The third is the potential (at least perceived) conflict between providing improved water and wastewater service to the poor (especially in developing countries) and reducing the environmental impacts of our systems. The fourth is to determine whether we are wastewater managers, or more broadly water managers. These challenges can be addressed by adopting a broader, more holistic view of urban water management incorporating water supply, wastewater management, and storm water. A toolkit of existing and evolving technologies could be assembled and grouped into example systems. Improved methods for evaluating alternate urban water management systems based on sustainable development principles need to be developed. Achieving the vision of more sustainable urban water management systems requires that our professional organizations speak with one voice. Our profession must also reach out and engage a wide range of interests in defining and implementing dramatically improved solutions.

Since 1984, the major water reclamation plants discharging to the Chicago Waterway System (CWS) have not disinfected their effluents. The possible addition of disinfection at these plants is the subject of an ongoing use attainability analysis (UAA). For the UAA, Escherichia coli (E. coli) is used as the indicator of bacterial contamination. However, only a few years of E. coli data are available for the CWS and the treatment plants discharging to the CWS. Thus, it was decided to develop a model based on fecal coliforms for which more data are available and to develop a relation between fecal coliform and E. coli counts for the CWS. A 1:1 relation was found between fecal coliform and E. coli counts in the CWS by Limnotech (2004, written communication) as part of the UAA. In order to evaluate the effects of possible disinfection measures on fecal coliform and related E. coli counts in the CWS, a simple first-order fecal coliform decay model was added to the continuous-simulation flow-water quality model DUFLOW applied to the CWS system. Due to the limited amount (monthly samples) of measured fecal coliform concentration data for the CWS, a reasonable calibration of the model would have been difficult to achieve based on the traditional trial and error method. In this paper, a new concept of model parameter estimation based on historical data analysis and its application to model calibration is presented. The fecal coliform decay rate $k$ was estimated for every reach of the CWS based on analysis of historical data (1990–2003) between each two consecutive sampling locations and the related travel time between these stations. The fecal coliform decay rate then was determined on the basis of many years (14 years, in this case) of monthly fecal coliform samples rather than the few monthly samples taken in a typical calibration period. The results obtained indicate that the calibration process was successful, and a good match between measured and simulated fecal coliform concentrations at almost all locations along the CWS is achieved with one model run for several multiple month periods in 1998, 1999, 2001, and 2002.

We developed a stream classification system that is based on stream’s susceptibility to algal growth using a two-step approach. The model portrays algal biomass as a result of stream’s response to nutrient concentrations and the response is governed by various stream factors. In the first step, a nutrient-chlorophyll $a$ relationship was developed to characterize nutrient’s effects on algal biomass. Residuals of the relationship were attributed to stream’s susceptibility to algal growth in response to nutrients and referred to as “observed” susceptibility. In the second step, conditions of other contributing factors were used to explain the variation in the residuals and the developed relationship was used to generate “predicted” susceptibility. Existing data compiled from various monitoring projects of Illinois streams and rivers were used to illustrate the approach. Streams were classified into three (high, medium, and low) categories based on their observed and predicted susceptibility values, respectively. With the available data, the model showed a 40-50% success rate for classifying the streams based on three observed and predicted susceptibility categories. Model entropy also was calculated for selecting the best model. The results show the important role of both nutrients and other contributing factors in explaining the variation of algal biomass. The study also suggests ways to fine tune the model and improve its accuracy, which would make the presented model a more viable tool for stream classification for establishing nutrient criteria to prevent surface streams from eutrophication.

A common difficulty in stream health assessments is the scarcity of real-time dissolved oxygen (DO) data. Discrete DO measurements, collected at times often imposed by sampling constraints, are difficult to use in assessments because of diurnal variations. An empirical model is developed here to adjust these discrete measurements to a common time-reference value using an extended stochastic harmonic analysis (ESHA) algorithm, which was originally formulated with a fraction of DO saturation model by the authors. The model was calibrated and validated for different stream sites across Minnesota, incorporating effects of different ecoregions and variable drainage areas. Data were normalized to increase the general applicability of the fitted parameters. Model calibration for five long record stations accurately represented observed diurnal variations in DO. The root-mean-square error (RMSE) for predicting hourly DO ranged from $0.53\text{to}0.80\mathrm{mg}∕\mathrm{L}$ and for predicting DO at a standard time ranged from $0.44\text{to}0.91\mathrm{mg}∕\mathrm{L}$ . Estimated model parameters were robust in terms of both spatial and temporal variations. Analytical as well as numerical analyses of parameter uncertainties were performed using sensitivity coefficients. Model validation with independent data for eight different Minnesota streams was performed using three different approaches for estimating parameters. The best approach considered both ecoregional location and watershed size to select representative model parameters. The RMSE for predicting hourly DO and standard DO respectively ranged from $0.53\text{to}1.65\mathrm{mg}∕\mathrm{L}$ and $0.00\text{to}1.83\mathrm{mg}∕\mathrm{L}$ . The developed model is a useful tool for total maximum daily load assessment of aquatic ecosystem health across a range of temporal and spatial scales. It is more elegant and simpler than the application of the ESHA algorithm for the fraction of DO saturation model.

A water quality and ecosystem model is developed to simulate nutrients, heavy metals, and aquatic plants in the Erh-Chung Flood Way wetland in Taiwan. A sediment system was incorporated into the model. The RMA2 and WASP/EUTRO5 models were adopted as the basic framework with modifications and enhancement of kinetics to incorporate ecosystem dynamics and sediment-water interactions. Hydrodynamic results from the RMA2 model were used to quantify mass transport for the EUTRO5 model. The major effort in this study was adding four water quality variables; macrophyte biomass, suspended solids, heavy metals in macrophytes, and heavy metals in the water column and sediment were incorporated into EUTRO5 to form the water quality and ecosystem model. Site-specific water quality data were collected to support the model calibration and verification analyses.

This work investigated the washout of dissolved nutrients from beaches due to waves by conducting tracer studies in a laboratory beach facility. The effects of waves were studied in the case where the beach was subjected to the tide, and that in which no tidal action was present. The following may be inferred: (1) waves created a steep hydraulic gradient in the swash zone and a mild one landward of it; (2) waves increased the residence time of a plume when they broke seaward of it. They also created additional pathways for transport of the tracer to the beach surface; and (3) in the presence of a tide that completely covered the solute plume, overall, the waves increased the washout of the tracer from the intertidal zone of the beach in comparison with the no-wave case. The residence time of the tracer plume due to waves superimposed on the tide was estimated as 75% of that resulting from the tide with no waves. Discussion on scaling up the results and implications for bioremediation are also presented.

The interactions between acid mine drainage (AMD) and three tropical clayey soils have been studied through hydraulic conductivity and batch sorption/dissolution testing. After 19–24 pore volumes of AMD flow through the soils, the measured final hydraulic conductivity ranged between $1.1\times {10}^{-11}$ and $3.3\times {10}^{-11}\mathrm{m}∕\mathrm{s}$ . The pH, electrical conductivity, and solute breakthrough curves obtained suggested the soils had low acid-buffering capacities. Also, several chemical species were released from the soils due to AMD attack of soil grains and mineral. The batch tests revealed high dissolution of species such as sodium, cobalt, and sulfate from the soils by AMD. The results also indicated dissolution of metals from soil constituents, desorption of chemical species, and transformation and dissolution of soil minerals due to AMD attack. The results of the study showed that, in general, the soils were not effective in attenuating contaminants present in the AMD. Thus, they may not be used alone to construct liners for acid-generating waste mine containment facilities.

The objective of this study is to analyze health effects of arsenic pollution of drinking water using a geographical information system (GIS). The paper reports the regional impact of arsenic contamination in six administrative blocks of the central part of the Murshidabad district, West Bengal, India. In this area about 1,248,580 people are exposed to arsenic pollution out of whom 388,316 people are exposed to arsenic concentrations above $0.05\mathrm{mg}∕\mathrm{L}$ , the WHO maximum permissible level of arsenic in drinking water. The study estimates that 65% of the total area of the six blocks has arsenic concentrations below $0.05\mathrm{mg}∕\mathrm{L}$ , 26.12% of the area has arsenic concentrations above $0.05\mathrm{mg}∕\mathrm{L}$ , and for the rest of the area no arsenic distribution data available. The total number of expected death cases has been estimated considering the percent of risk involved in a concentration range and corresponding total population using such water for drinking purpose. The analysis forecasts that 11,890 people may risk death due to arsenic pollution in the whole life span. The maximum number of death cases is expected in Domkal and Beldanga 1 blocks and the minimum number of death cases is expected in Block Bhagabangola 2. This study also reports a comparison between the theoretical expectation of death cases and actual reported arsenicosis cases for the Domkal block. The areas of theoretical expectation and the areas of actually reported cases match fairly well except in a few cases. The present study helps planning and implementing of priority-based arsenic mitigation options.

The mobility of pollutants from air pollution control (APC) residues is strongly influenced by its contact with water. This study aims to verify the applicability of time-domain reflectometry (TDR) to infer water and solute movement in situ in an APC residue–compost mixture in a laboratory column. The calibrated dielectric permittivity–volumetric water content relationship $(K-{\theta }_v)$ for the material shows a distinct plateau at midrange volumetric water contents, which are underestimated by Topp’s $K-{\theta }_v$ model throughout the studied range. The coating of probes enables a clear TDR signal collection and analysis up to electrical conductivity values of $280\mathrm{mS}{\mathrm{cm}}^{-1}$ . Heterogeneities in packing and channel flow in the column are revealed by TDR measurements. Water contents inferred by TDR signal analysis require careful interpretation when used in materials such as APC residues, due to the high amount of water bound in the hydration shells of ions released into the pore water.

Secondary clarifiers are a vital component of the activated sludge process. Previous studies have showed that operation factors such as surface overflow rate (SOR) and solids loading rate have an essential impact on secondary clarifier performance. However, the impact of these factors on sludge blanket formation and the effect of blanket on clarifier performance have not been studied thoroughly. In this study, a series of stress tests was conducted and the sludge blanket was allowed to accumulate during the tests for elucidating the relationships between sludge blanket and other critical operational parameters. It was found that the sludge blanket has a strong linear correlation with SOR and the linear models have the $R^2$ values of 0.89 and 0.85. High blanket levels show a stronger positive linear correlation with effluent suspended solids (ESS) compared to low blanket levels. A sharp increase in ESS will occur regardless of the blanket height if SORs are high enough. In addition, low initial blanket levels do not lead to lower blanket levels. Moreover, a strong negative linear correlation was observed between the initial blanket level and the blanket increment.

A conceptual neural-fuzzy model based on adaptive-network-based fuzzy inference system (ANFIS) was proposed to estimate effluent chemical oxygen demand (COD) of a full-scale anaerobic wastewater treatment plant for a sugar factory operating at unsteady state. The fitness of simulated results was improved by adding two new input variables into the model; phase vectors of operational period and effluent COD values of last five days (history). In modeling studies, individual contribution of each input variable to the resulting model was evaluated. The addition of phase vectors and history of five days into the input variable matrix in ANFIS modeling for anaerobic wastewater treatment was applied for the first time in literature to increase the prediction power of the model. By this way, the correlation coefficient between estimated and measured values of output variable (COD) could be increased to the value of 0.8940, which is considered a good fit.

This paper describes the application of a genetically engineered microorganism, Pseudomonas putida mt-2 KG1206, to monitor toluene analogs in groundwater collected from petroleum hydrocarbon contaminated sites. KG1206 contains the intact TOL plasmid and a second plasmid with the $P_m$ -lux gene allowing it to produce bioluminescence in the presence of toluene analogs and their derivatives such as toluene, xylenes, and $m$ -toluate. The simple bioluminescence assay consisted of mixing one volume of groundwater sample with four volumes of broth culture followed by bioluminescence measurement after $30\min$ . The maximum bioluminescent response with pure chemicals followed the order: $m$ -methyl benzyl $\text{alchohol}>m\text{-}\text{toluate}>\text{toluene}>m\text{-}\text{xylene}>\text{benzoate}>p\text{-}\text{xylene}>o\text{-}\text{xylene}$ . The bioluminescence production was well correlated to the $m$ -toluate concentrations $(R^2>0.97)$ in field samples, with concentrations predicted from the bioassay falling within 75–158% of true concentration. However, no strong correlation was observed between the bioluminescence intensity and the total inducer concentration in the groundwater. Results from this study demonstrate the potential of using recombinant bioluminescent bacteria as a rapid and simple tool for monitoring specific pollutants at contaminated sites.

In 1993 P. F. Boulos and T. Altman developed an efficient explicit scheme for determining steady state water quality in a distribution system for conservative and zero-order reacting constituents. This approach is extended here to first- and second-order reactions and a general reaction relationship is discussed. Mass balance relationships and nonconservative reaction kinetics lead to a general matrix for constituent analysis. The directed graph that results in steady flow conditions permits single equations to be solved sequentially providing the water quality distribution throughout the system. The method can be used to solve for linear and nonlinear conditions and is demonstrated for first-order decay and growth and second-order decay on a 13-pipe system.