Column experiments modeling

Measured concentrations of As(lll) and As(V) in leachate from a column experiment are compared with simulated concentrations using the model PHAST in Figure 1. Arsenic concentrations in leachate were below detection for the first 50 pore volumes of contaminated groundwater eluted through the column. Although initial As(lll) concentrations were 650 ptg/L, oxidation of As(lll) to As(V) by manganese oxides resulted in leachate concentrations of As(lll) near detection limits for 270 pore volumes. All of the As... 

Fig. 1. Measured and modeled concentration of As(lll) and As(V) in leachate from column experiment. Initial As(lll) concentration = 650 pg/L initial As(V) concentration = 250 pg/L. (Note As(lll) modeled concentrations were <1 pg/L and plot along bottom of x-axis.)...

Fig. 10 a, b. Column experiments using different flow rates, first order model TOC concentration released vs a time b pore volume... 

Schuessler, W., Artinger, R., Kim, J. I., Bryan, N. D. Griffin, D. 2001. Numerical modeling the humic colloid borne Americium (III) migration in column experiments using the transport/speciatrion code KID and the KICAM model. Journal of Contaminant Hydrology, 47, 311-322. 

Angley, J.T., Brusseau, M.L., Miller, W.L. Delfino, J.J. (1992). Nonequilibrium sorption and aerobic biodegradation of dissolved alkylbenzenes during transport in aquifer material column experiments and evaluation of a coupled-process model. Environmental Science Technology, 26(7), 1404-10. 

Figure 2. Spatial contaminant distributions and simultaneous model calibrations for column experiments using SB amended with 5 percent humus (column conditions summarized in Table 2). Reprinted with permission from Khandelwal and Rabideau (2000). Copyright 2000, Elsevier Science B. V.

Our miscible-displacement modeling approach was modified in order to describe S04 effluent from the BS (as well as BC) layers. We adjusted the computer code to account for a variable concentration of the input pulse rather than a constant one as is commonly accepted in most column experiments and mathematical solutions. In all our simulations presented here, for each soil column, the S04 input concentrations from our experimental results were incorporated as inputs to the model. In addition, presentations of relative concentrations (C/C0) were based on the respective C0 of the applied solution to the top layer (E). 

The accumulation of calcium carbonate in deep ocean sediments is a complex process. It is primarily governed by the interplay between biological production of calcium carbonate in the nearsurface ocean and the chemistry of deep ocean waters. After over 100 years of study, the major problem of determining the saturation state of deep ocean water remains largely unresolved. It is currently possible, using recent laboratory measurements, to arrive at saturation states that differ by as much as a factor of 2. Both laboratory and water column experiments indicate that calcium carbonate dissolution kinetics are not simply related to saturation state. It is our opinion that the saturation state problem must be resolved and considerably more detail added to our present knowledge of calcium carbonate dissolution kinetics and accumulation patterns before attempts to model the accumulation of calcium carbonate in deep ocean sediments can be truly successful. 

The column experiments were carried out in a glass column of l.Scm internal diameter and 30cm length filled with Sg of ion exchange resin. Pd solution was percolated through the packed column at a flow rate of 1.0 ml/min controlled by a peristaltic pump (EYELA SMP-21, Japan). The effluent samples were collected at r ular intervals by the fraction collector (Model Adventec SF-2100) and analyzed for Pd concentration by ICP. 

Breakthrough curves from column experiments have been used to provide evidence for diffusion of As to adsorption sites as a rate-controlling mechanism. Darland and Inskeep (1997b) found that adsorption rate constants for As(V) determined under batch conditions were smaller than those necessary to model breakthrough curves for As(V) from columns packed with iron oxide coated sand the rate constants needed to model the breakthrough curves increased with pore water velocity. For example, at the slowest velocity of 1 cm/h, the batch condition rate constant was 4 times smaller than the rate constant needed to model As adsorption in the column experiment. For a velocity of 90 cm/h, the batch rate constant was 35 times smaller. These results are consistent with adsorption limited by diffusion of As(V) from the flowing phase to sites within mineral aggregates. Puls and Powell (1992) also measured more retardation and smaller rate constants for As(V) at slower flow velocities where there was sufficient time for diffusion to adsorption sites. 

The modeled pattern in Figure 11 shows the observed concentration trends, but, clearly, it does not match the details. Notably, the predicted As peaks arrive too early and they are too small. The column experiments of Isenbeck-Schroter (1995) and Darland and Inskeep (1997) required kinetic reactions for Freundlich or Langmuir sorption isotherms for As, but a kinetic model appears to spread out the As concentrations in Figure 11 only, and it does not shift the position of the peak to later arrival times. Therefore, other reactions might explain the discrepancy. 

Isenbeck-Schroter, M., 1995, Transportconditions of heavy metals and oxoanions - column experiments and their modeling Ber. Geowissenschaften Univ. Bremen (in German), v. 

Postma, D., and Appelo, C. A. J., 2000, Reduction of Mn-oxides by ferrous iron in a flow system Column experiment and reactive transport modeling Geochimica et Cosmochimica Acta, v. 64, p. 1237-1247. 

The equations presented above can be used (with or without modifications) to describe mass transfer processes in cocurrent flow. See, for example, the work of Modine (1963), whose wetted wall column experiments formed the basis for Example 11.5.3 and are the subject of further discussion in Section 15.4. The coolant energy balance is not needed to model an adiabatic wetted wall column and must be replaced by an energy balance for the liquid phase. Readers are asked to develop a complete mathematical model of a wetted wall column in Exercise 15.2.1. 

FIGURE 10.2 Heat map obtained from parallel virtual screening experiment. Rows Antiviral compounds Columns Pharmacophore models. Green signal compound is found with model built from correct target red signal compound is found with a model from another target. 

The determination of kinetic parameter values from column experiments is predicated upon the ability of the mathematical model to successfully simulate the experimental data. Confidence in the robustness of the parameter values so determined is attained only with a unique solution (i.e., when one suite of parameter values provides a solution that is significantly better than all others). For cases wherein a system is near equilibrium or under extreme nonequilibrium, attainment of a unique solution may prove difficult. A modified miscible-displacement technique, involving flow interruption, that enhances the potential for achieving unique solutions, and thus increases the robustness of optimized values of kinetic parameters, was presented by Brusseau et al. (1989a). In addition, the method has increased sensitivity to nonequilibrium, making it useful for process-level investigation of sorption kinetics. This method would appear to be especially useful for systems com-... 

Petrangeli-Papini, M. et al., Adsorption of lead at variable pH onto a natural porous medium Modeling of batch and column experiments. Environ. Sci. Technol., 33, 4457, 1999. 

A similar modeling study was conducted by Stollenwerk (1994) to interpret a column experiment on the acidic water and alluvium sediments interactions for Miami Wash and Pinal Creek, Arizona. He used minteqa2 to simulate the equilibrium states in column effluents. 

The authors found that the model-predicted As concentration is close to the leachate concentrations from the column packed with dust from the continuous reactor (1 120 H.gL-1 versus 1 330 xgL-1), when the solubility product of scorodite from Robins (1990) and the triple layer model is used. Only 11% As in the system was sorbed onto hydrous ferric oxide surfaces. Arsenic concentrations in the leachate are largely controlled by scorodite solubility. It should also be pointed out that simulations using solubility only and without including surface adsorption resulted in a closer match (1 270 n-gL-1 versus 1330 piglA1). For the simulation of the column experiments using wastes from the batch-reactor, the triple layer model predicted too low an As concentration (33 jigL-1 versus 120 pigL-1). 

Laboratory column experiments were used to identify potential rate-controlling mechanisms that could affect transport of molybdate in a natural-gradient tracer test conducted at Cape Cod, Mass. Column-breakthrough curves for molybdate were simulated by using a one-dimensional solute-transport model modified to include four different rate mechanisms equilibrium sorption, rate-controlled sorption, and two side-pore diffusion models. The equilibrium sorption model failed to simulate the experimental data, which indicated the presence of a ratecontrolling mechanism. The rate-controlled sorption model simulated results from one column reasonably well, but could not be applied to five other columns that had different input concentrations of molybdate without changing the reaction-rate constant. One side-pore diffusion model was based on an average side-pore concentration of molybdate (mixed side-pore diffusion) the other on a concentration profile for the overall side-pore depth (profile side-pore diffusion). 

Figures 4-5). Sorption was reversible, and was not affected by a lag of up to 60 days between sorption and desorption (e.g. Figure 4). Fitted parameters for 29 column experiments for which good convergence was obtained for the first-order and mobile-immobile models are presented in Table III. Equilibrium-model parameters are presented for an additional 11 experiments. The full data sets for these experiments can be found in Szecsody (8). 

The one-dimensional column experiments and parameter-estimation procedure described in this work provides rate constants, or time scales, for sorption/desorption that are independent of the flow and the large-scale media geometry. By using model sorbents the rate constants can be related to the dominant binding interaction, which helps define their applicability. 

Often, the availability of the pollutants is not a limiting parameter under such conditions. Therefore, complementary approaches using pot and column experiments and field experiments, where the availability of the trace elements is an important parameter, should be performed to quantify the potential beneficial effect of AM presence or inoculation in polluted soils, and to provide useful data to include in plant uptake models. 

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