Journal of Environmental Engineering

When a model is used to fit data containing dependent variables some of which are known only to be below some limit, special techniques must be employed. The present paper shows that ordinary regression, omitting those observations lacking measured values, results in biased estimation of the parameters in a model. The use of maximum‐likelihood estimation, frequently employed in the field of life testing, is found to yield estimates of less bias and greater precision for such data. The maximum‐likelihood estimation technique is also found to be at least as robust to deviations from normality as ordinary regression. Application of this technique is illustrated with reference to the problem of developing relationships for a non‐THM disinfection [trichloroacetic acid (TCAA)] by‐product of water chlorination. Diagnostic tests for goodness of fit of the resulting model are also shown. Finished water TCAA concentrations are shown to be described by a function including chloroform concentration, pH, and type of water‐treatment process (straight chlorination, chlorammoniation, etc.).

The motivation for this study was the need of transportation agencies to quickly evaluate the appropriateness of a wide variety of hazardous‐waste‐remediation technologies for a specific waste at a specific site. The strategy was to develop a user‐friendly computerized methodology for screening the most inappropriate treatment technologies for remediation of hazardous‐waste‐contaminated soil. The Soil Treatment Evaluation Program (STEP) model was developed using object‐oriented programming techniques to interface with multiple rule bases and data bases and to allow easy modification and expansion. The model was applied to a case study and the recommendation of the model was consistent with that of the findings of the case study. The technology‐screening guidelines utilized by the model are based on published literature. Based on this study it was found that the screening guidelines have to be modified. The model could be easily enhanced for use with proper modified guidelines.

Efficient and statistically sound sampling protocols for estimating the quantity and composition of solid waste over a stated period of time in a given location, such as a landfill site or at a specific point in an industrial or commercial process, are essential to the design of resource‐recovery systems and waste minimization programs, and to the estimation of the life of landfills and the pollution burden on the land posed by the generation of solid wastes. Unfortunately, traditional sampling plans are ill‐suited for the estimation of the quantity or composition of solid waste. The theory developed in this study takes an approach significantly different from the more traditional sampling plans, resulting in lower costs and more accurate and precise estimates of these critical entities. A desktop computer program, called PROTOCOL, has also been developed to perform the calculations required.

Explicit formulas for the steady‐state maximum saturated depth over a landfill liner are derived analytically from basic principles of unconfined seepage. The lateral drainage over the liner is described by an extended form of the Dupuit discharge formula. The liner is modeled as an impervious sloping plane. The factors that determine the maximum saturated depth over the liner are the rate of vertical inflow to the drainage layer, the hydraulic conductivity of the drainage layer, the slope of the liner, the maximum distance of flow, and the hydraulic condition at the downstream end of the drainage layer. Practical applications of these formulas include the analysis and design of drainage systems for landfill covers and bottom liners. An example illustrates the use of these formulas in the design of a cover drain for a hazardous‐waste landfill. A formula that appears in several technical guidance documents of the U.S. Environmental Protection Agency is shown to overestimate the maximum saturated depth over a landfill liner.

An analytical approach to the minimization of total active disc area $\left(A_T\right)$, required for organic carbon removal [i.e., biochemical oxygen demand (BOD)] by a multistage rotating biological contactor (RBC), is presented. RBC operation is simulated using semiempirical models based on a saturation‐type (Monod) removal rate, and on a first‐order kinetics removal rate. The parameters used in the predictive equations are considered to be different from one RBC stage to the next. The minimizations of $A_T$, based in turn on each of the two semiempirical models, lead to a relationship between the optimal soluble substrate concentration of any stage and those of the immediately preceding and succeeding stages. When used in design, these relationships allow the minimum $A_T$, as well as the optimal number of stages required for carbon removal, to be obtained. For the saturation model, two parametric ratios (${\Phi }_P$ and ${\Phi }_{K_S}$) are introduced, which define the change in the model parameters with stage. Application of the relationships to the determination of the optimal number of stages and the minimum $A_T$ is included.

The research described in this paper extended a deterministic screening model for ground‐water contamination to include specification of variability in water flux and soil and chemical properties. Uncertainty in these parameters was characterized by independent log‐normal probability distributions and a Monte Carlo simulation process was used to estimate the expected percentages of chemical mass reaching the water table. These Monte Carlo results were compared with a deterministic analysis that ignored hydrologic and soil spatial variability. For many of the 49 chemicals analyzed in this study, the Monte Carlo results produced substantially higher estimates of groundwater contamination than the deterministic analyses, indicating that neglecting hydrologic and soil spatial uncertainty may underestimate the potential for pollution. However, for those chemicals and site conditions most likely to produce major contamination, the Monte Carlo and deterministic analyses produced comparable results.

Biological degradation of 12 chlorinated aliphatic compounds (CACs) was assessed in bench‐top reactors and in serum bottle tests. Three continuously mixed daily batch‐fed reactor systems were evaluated: anaerobic, aerobic, and sequential‐anaerobic‐aerobic (sequential). Glucose, acetate, benzoate, and phenol were fed as growth substrates to both the anaerobic and aerobic systems. Methane and toluene were also added to the aerobic systems to induce cometabolic degradation of the feed CACs. The anaerobic culture degraded seven of the feed CACs. The specialized aerobic cultures degraded all but three of the highly chlorinated CACs. The sequential system outperformed either of the other systems alone by degrading 10 of the feed CACs: chloroform, carbon tetrachloride, 1,1‐dichloroethane, 1,1,1‐trichloroethane, hexachloroethane, 1,1‐dichloroethylene, trans‐1,2‐dichloroethylene, trichloroethylene, perchloroethylene, and 1,2,3‐trichloropropane, plus the anaerobic metabolites: dichloromethane and cis‐1,2‐dichloroethylene. Sequential treatment did not show significant removal of 2‐chloropropene, or 1,1‐dichloropropene. Cultures from each of the reactors were used in bottle tests to determine relative CAC degradation rates. Maximum degradation rates observed for individual CACs ranged from 20 to 150 μg per gram volatile suspended solids per day.

Experiments were performed to determine the degradation of acetate, propionate, and butyrate, and the maximum methanogenic activity of granular sludge from the thermophilic anaerobic digestion (55°C) of pure molasses under shock temperature conditions. The compositions of acetate, propionate, and butyrate that were used as substrates were 25:35:40, respectively. On two duplicate batch reactors (I and II) runnning in parallel and at a pH of 7, the tests were performed at 63°C during the first volatile fatty acid (VFA) addition (first feeding or first experiment) and at 55°C after the second VFA addition. During the first and second VFA additions, there was a lag phase. In the first experiment, by the end of 160 hours, after the initial concentrations of butyrate and acetate had been completely degraded, only 35–55% of the initial concentration of propionate was converted to acetate. The maximum methanogenic activities of the first feeding were not high because the population of propionate degrading bacteria was low and these bacteria were negatively affected from the shock temperature changes. In the second experiment, with the same sludge, the maximum methanogenic activities on second VFA additions were about 1.3 times higher than those of the first VFA additions. This increase may be due to a faster adaptation of the sludge and an increase of the population of the propionate degrading bacteria as a result of returning to the optimum temperature conditions.

Adsorption of cadmium by two powdered activated carbons (PAC) is investigated in single and binary adsorbent systems. Both PACs are effective in removing cadmium from solution. Cadmium adsorption increased with increased solution pH. The surface complex formation (SCF) model, a surface‐solution chemical equilibrium model, successfully simulated the individual pH‐adsorption edges. Cadmium adsorption decreased with increased cadmium surface loading. This phenomenon was attributed to the surface sites having a range of binding energies. Reflecting this phenomenon, several of the complexation constants decreased with the cadmium/carbon ratio. The SCF model successfully simulated the cadmium surface loading versus soluble cadmium curves for the entire range of cadmium and carbon concentrations studied when the cadmium‐carbon complexation constants are modified to account for their variation with the cadmium/carbon ratio. Cadmium adsorption in the binary PAC system was observed to follow ideal behavior. The SCF model, using complexation constants determined from single PAC experiments, successfully predicted cadmium removal from solution.

The Safe Drinking Water Act and its Amendments (SDWAA) will pose a massive challenge for the drinking‐water industry in the United States. As the SDWAA regulations reach implementation, increasing effort will be devoted to understanding the factors causing deterioration of water quality between treatment and consumption. A cooperative study involving the U.S. EPA, the University of Michigan, and the South Central Connecticut Regional Water Authority (RWA) demonstrated and validated the use of modeling techniques in the RWA distribution system. Models are used to predict the propagation of chlorine residual in one portion of the RWA system. It is found that residuals varied widely both spatially and temporally. Long residence times in storage tanks caused residual disinfection concentrations to be low or nonexistent during discharge cycles. It was found that system operation has a significant effect on the distribution and concentration of chlorine residuals in the system.

In this technical note, the results on adsorption of acid and basic dyes by sulfonated coal are presented. A mathematical model based on adsorption isotherm was developed to predict the desorption of dyes from the sorbent. There was a good agreement between the predicted and experimentally determined values for basic dyes only. An attempt to understand the nature of binding of dyes was made from the desorption pattern of dyes from sulfonated coal using different eluants

Copper(II) uptake by Ganoderma lucidum, a wood-rotting mushroom, Aspergillus niger, a waste biomass originating from citric acid fermentation industry, and surplus sludge from a laboratory-activated sludge unit was studied. Using 4$g/L^{-1}$sorbent concentration and 0.5 mM Cu(II), the maximum uptake was by G. lucidum (97%) followed by waste sludge (42%) and A. niger (14%) at pH 5.0. The increased metal binding by biosorbents after strong alkali treatment was marginal for mushroom, signficant for A. niger (31%), and dramatic for sludge (99%). The sorption equilibria were used to quantitatively compare the capacities of sorbents. Variations in metal removal in the presence of different anionic ligands by biosorbents were observed.

The issue of leachate storage for landfill leachate-recirculation systems is addressed in this note. Basic design equations are developed for the volumetric sizing of the leachate storage facility. The sizing approach is based on two conditions: (1) The determination of the storage volume to provide leachate recirculation during interevent periods between precipitation events; and (2) the determination of the storage volume to provide storage capacity for the leachate volumes resulting from precipitation events. The design volume is the maximum of the two storage volumes determined for the two conditions. The sizing methodology is applied to a range of Canadian locations, and is shown to yield reasonable results.

As part of a study of the effects of varying aeration patterns and diffuser types on an extended aeration wastewater treatment system, researchers employed float-type rotameters with a range of 0-80 L/min (0-2.9 cfm) operating between 0 to 138 kPa (0-20 psi). During operation of the system, it was discovered that readings on the influent air meter and internal flow meters showed a consistent discrepancy of over 16 L/min (30% loss). This error did not occur when the air system was run without water in the tank. The simple structure and basic principle of operation should have made the flowmeters reliable and easy to work with. This discrepancy led the researchers to investigate several possible problems, including leaks, defects in the flowmeters and pressure, and temperature effects and pulsation. It was determined that pulsation from the compressor was the source of the discrepancy. Flow measurement errors in the system were corrected by installing a small, inexpensive accumulator.