Journal of Environmental Engineering

The impact of the assumption of linear sorption on retardation of nonlinearly sorbed solutes in porous media is numerically explored in this paper. Breakthrough data of nonlinearly sorbed solutes are generated using the BIO1D simulation code along with the Freundlich-type nonlinear sorption model. Retardation coefficients $\left(R\right)$ from generated breakthrough curves are estimated using first-moment analysis. Variations of $R$ with experimental conditions revealed that $R$ of a nonlinearly sorbed solute is a function of the input concentration, the injection period and the pore-water velocity but is independent of the length scale. This study also showed that it is appropriate to estimate $R$ of a nonlinearly sorbed solute using a linearized isotherm if all soil particles experience sorption with liquid concentration equal to the induced concentration. Otherwise, the estimated linearized $R$ will be either under- or overestimated depending on the applied experimental conditions and Freundlich parameters. The study further revealed that inability to account for sorption nonlinearity may in some cases erroneously be interpreted as evidence of the presence of transport nonequilibrium. A method is suggested to determine nonlinear sorption parameters from miscible displacement experiments.

Ground and surface water contamination due to leaching of trace elements from ash ponds is a major environmental challenge for thermal power plants. Leaching of trace elements from the ash ponds indicated significant concentration of nine trace elements (Na, K, Mg, Ca, Fe, Pb, Mn, Cu, and Zn) in the leachates of various thermal power plants. The empirical models developed for the prediction of various trace elements i.e., Mn, Cu, Fe, Zn, and Pb, followed first-order reaction rate kinetics. The empirical models derived from the laboratory scale models were subsequently modified to account for the changes in the chemistry, mineralogy, and morphology of fly ash with respect to time which correlated well with the real field data with regression coefficients varying from 0.93 to 0.98. The modified empirical models predicted concentrations of the trace elements within $\pm 3\%$ of the observed values for four thermal power plants with standard deviation varying from 0.001 to 0.032.

Survival characteristics of total coliform bacteria in soil samples, with different moisture contents (24–49%) and at different temperatures (from $-28$ to $20°\mathrm{C}$ ), were studied. The study showed that a significant fraction of coliform bacteria survive for more than six months in soil at subfreezing temperatures. Survival of total coliform bacteria at subfreezing temperatures decreased with an increase in moisture content and an increase in temperature. For 24% moisture, approximately 66% of the coliforms survived at $-28°\mathrm{C}$ after 170 days, whereas less than 0.1% survived at room temperature. First-order die-off rate constants varied between 0.041/day at room temperature and 0.002/day from $-15$ to $-28°\mathrm{C}$ (for 24% moisture). The impact of temperature on the die-off rate constant was described by the Arrhenius equation. The high survival at subfreezing temperatures indicates that fecal bacteria at honeybucket dumpsites may survive throughout the Alaskan winter which may lead to the contamination of water sources during spring thaw.

Devils Lake in North Dakota is a terminal, multibasin, saline lake with an overall surface area that is currently approximately $\mathrm{44,520}\mathrm{ha}$ $\left(\mathrm{110,000}\text{acres}\right)$ . Lake elevation has increased by more than $7\mathrm{m}$ within $10\text{years}$ , and vast areas of prairie and cropland have been flooded. The lake is rich in sulfate, and water column sulfate concentrations are relatively uniform within each of the five major basins, but increase from $3.1\mathrm{mM}$ $(300\mathrm{mg}∕\mathrm{L})$ in West Bay to $31\mathrm{mM}$ $(\mathrm{3,000}\mathrm{mg}∕\mathrm{L})$ in East Devils Lake. Sediment cores were collected from three of the basins at different water depths, and used in laboratory studies to evaluate the spatial distribution of sulfate-reducing bacteria (SRB) activity in the lake sediments. The high sulfate concentrations within the experimental sediment cores suggest that the activity of SRB is limited by the availability of suitable electron donors rather than by the availability of sulfate and that SRB activity can be defined by a zero-order volumetric rate constant $\left(K_0\right)$ . Experimentally determined $K_0$ values ranged from $11\text{to}88\mathrm{mmol}$ $\mathrm{S}{\mathrm{O}}_4^{2-}$ ${\mathrm{m}}^{-3}{\text{day}}^{-1}$ . The water depths from which sediment cores were collected in Devils Lake are related to the elapsed time since inundation by the rising lake level. It was found that time since inundation influences the observed $K_0$ value. Mean $K_0$ values for cores from an average depth of $4.8\mathrm{m}$ (submergence time of about $5\text{years}$ ), and $9.4\mathrm{m}$ (submergence time of about $28\text{years}$ ) were 62 and $17\mathrm{mmol}$ $\mathrm{S}{\mathrm{O}}_4^{2-}$ ${\mathrm{m}}^{-3}{\text{day}}^{-1}$ , respectively. The significant difference (two-tailed $t$ -test, $p<0.05$ ) suggests that SRB activities in the Devils Lake sediments change with submergence times. A uniform sulfate reduction rate applied to all Devils Lake sediments is therefore only a crude approximation of reality.

Waste acclimation and batch microcosm studies containing digested municipal solid waste were conducted at different temperatures (22, 35, and $45°\mathrm{C}$ ) and gas-phase oxygen concentrations (0.7–100%, by volume) to provide guidance for field-scale implementation of in situ nitrogen removal processes. Results demonstrate that in situ ammonia–nitrogen is feasible in decomposed aerated solid waste environments at the gas-phase oxygen concentrations and temperatures evaluated and the potential for simultaneous nitrification and denitrification in field-scale bioreactor landfills is significant due to the presence of both aerobic and anoxic areas. Small amounts of oxygen were found sufficient for nitrification/ammonia removal to proceed, although removal rates increase with oxygen concentration. Laboratory results suggest field-scale implementation of in situ nitrogen removal occur in small dedicated treatment zones containing previously degraded waste (later in the life of a bioreactor landfill). Model simulations indicate removal of ammonia–nitrogen to low levels can occur with relatively short aeration depths (depth estimates ranged from 1.6 to $7.2\mathrm{m}$ below the point of leachate injection). Field-scale verification of these depth estimates is required prior to routine acceptance.

This paper proposes an automatic process model induction system using an evolutionary computational intelligence, called grammar-based genetic programming, that is specially designed to automatically discover multivariate dynamic process models that best fit observed process data. This automatic process model induction system combines an evolutionary self-organizing system of genetic programming paradigm with various mathematical functions for a multivariate nonlinear model evolution using a grammar system via the mechanism of genetics and natural selection. The results demonstrate how the automatic process model induction system based on grammar-based genetic programming can be used to develop accurate and relatively cost-effective multivariate dynamic process models for the full-scale biological nutrient removal process. Multivariate dynamic process models are derived automatically in the form of understandable mathematical formulas that enable engineers to extract important knowledge hidden in the data and develop better operation and control strategies.

Truckee Meadows Water Reclamation Facility (TMWRF) is a $\mathrm{150,000}{\mathrm{m}}^3∕\text{day}$ $\left(40\mathrm{mgd}\right)$ tertiary wastewater treatment facility that serves the cities of Reno and Sparks, Nev. The effluent from TMWRF is discharged into the Truckee River which flows to Pyramid Lake—a very sensitive ecosystem and habitat for endangered species. Reverse osmosis (RO) and nanofiltration (NF), in conjunction with ultrafiltration (UF) pretreatment, were evaluated for total dissolved solids (TDS) and nutrient removal from the effluent of TMWRF at bench and pilot scale. Results from short-term pilot-scale tests showed that RO and NF membrane processes can successfully remove both TDS and nutrients from the effluent when paired with coagulation-enhanced UF pretreatment. NF membranes were able to achieve the necessary removal while maintaining higher fluxes and lower specific power consumption.

In this work, linoleic acid (LA), a long chain fatty acid bearing 18 carbons and two double bonds, inhibited hydrogen consumption in a mixed anaerobic culture acclimated to glucose. At $\mathrm{pH}=7.6$ , a metabolic shift from methane to hydrogen formation was observed in cultures maintained at $37°\mathrm{C}$ and fed $\mathrm{5,000}\mathrm{mg}{\mathrm{L}}^{-1}$ glucose in the presence of $500–\mathrm{2,000}\mathrm{mg}{\mathrm{L}}^{-1}$ LA. The hydrogen yield increased with increasing LA levels while the quantity of methane decreased. The major volatile fatty acids produced were acetate and butyrate with greater levels observed in cultures fed with LA. Acetate, butyrate, and hydrogen accumulation suggests inhibition of aceticlastic methanogens, hydrogenotrophic methanogens, and butyrate degrading microorganisms, respectively, in the presence of LA. A maximum hydrogen yield of $1.71\pm 0.22\text{mole}{\text{mole}}^{-1}$ glucose was observed only when glucose was reinjected into cultures receiving $\mathrm{2,000}\mathrm{mg}{\mathrm{L}}^{-1}$ LA plus $\mathrm{5,000}\mathrm{mg}{\mathrm{L}}^{-1}$ glucose.

Woven straw has been demonstrated to be a cheap and effective method to prevent fugitive particular matter (PM), which is a typical air pollution source emitted from the exposed area, like farmland or a construction site. From the engineering application point of view, an approach using dimensionless analysis with a multivariable regression method based on experimental data would be worth exploring to predict the prevention efficiencies of woven straw to reduce the fugitive ${\mathrm{PM}}_{10}$ (PM sized less than $10\mu \mathrm{m}$ ). A series of field-analogous experiments were carried out to continuously measure ${\mathrm{PM}}_{10}$ using $\beta$ -attenuation particle monitors in an artificial wind tunnel system. It was found that the prevention efficiencies of woven straw to reduce ${\mathrm{PM}}_{10}$ is significantly dependent on the coverage ratio of woven straw, and the maximum prevention efficiency of ${\mathrm{PM}}_{10}$ is about 42%. It is emphasized that the prevention efficiency approaches zero as the coverage ratio is less than about 40%. This implies that ${\mathrm{PM}}_{10}$ reduction was inefficient if the exposed area was not covered enough with woven straw. Another point of interest is that total elimination of ${\mathrm{PM}}_{10}$ emission is not possible using full coverage woven straw. The effects of wind velocity, silt content, and moisture on prevention efficiency are also discussed in this paper. Correlated with major parameters, a useful equation is proposed to estimate the prevention efficiencies that would be valid under the appropriate conditions suggested by this work.