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Computer Concentration

FDM FDM (Fugitive Dust Model) is an air quality model designed for computing concentration and deposition impacts from fugitive dust sources. Click the following filenames to download the file ... [Pg.332]

These equations identify the dominant source and loss processes for HO and H02 when NMHC reactions are unimportant. Imprecisions inherent in the laboratory measured rate coefficients used in atmospheric mechanisms (for instance, the rate constants in Equation E6) can, themselves, add considerable uncertainty to computed concentrations of atmospheric constituents. A Monte-Carlo technique was used to propagate rate coefficient uncertainties to calculated concentrations (179,180). For hydroxyl radical, uncertainties in published rate constants propagate to modelled [HO ] uncertainties that range from 25% under low-latitude marine conditions to 72% under urban mid-latitude conditions. A large part of this uncertainty is due to the uncertainty (la=40%) in the photolysis rate of 0(3) to form O D, /j. [Pg.93]

C17-0062. For a 1.50 M aqueous solution of hydrazoic acid, HN3, do the following (a) Identify the major and minor species, (b) Compute concentrations of all species present, (c) Find the pH. (d) Draw a molecular picture illustrating the equilibrium reaction that determines the pH. [Pg.1263]

In many risk analyses standard dispersion models, available from the EPA for regulatory compliance purposes, are used to compute concentration patterns for prototypes of a class of sources, and the patterns are convolved with population patterns that are characteristic of the source sites (5, 6). A similar level of analysis detail that relies on measured pollutant (ozone) concentration in each county of the Northeast Corridor rather than on modeled concentrations was used by Johnson and Capel ( 7). [Pg.72]

Estimation of the population pattern over the area of each computed concentration pattern. [Pg.75]

While the resulting concentration profiles, and in particular the computed spectra, seem to be reasonably close to the true ones, there are significant discrepancies, typical for model-free analyses, (a) The computed concentration profile for the intermediate component reaches zero at the end of the measurement, (b) The initial part of the concentration profile for the final product is wrong it does not start with zero concentration. Both discrepancies are the result of rotational ambiguity. The minimal ssq, reached after relatively few iterations, reflects the noise of the data and not a misfit between CA and Y. ssq does not improve if the correct matrices C and A are used. [Pg.288]

Therefore, by including the mean ionic activity coefficient into the calculation, the real concentration is seen to be the same as the apparent concentration without the mean ionic activity coefficient, the apparent (computed) concentration is about 2.4 times too small. [Pg.54]

The DigiSim program probably represents the current state of the art which is achievable for simulating and analysing cyclic voltammograms. This package can perform cyclic voltanunetry for a wide range of mechanisms at planar, spherical, cylindrical or rotated disc electrodes. It also computes concentration profiles. [Pg.299]

X Obterved pc utant conoentratioa. > Model concentration. [Pg.221]

Figure 1. UOg solubility from thermochemical computations concentration of U in a saturated aqueous solution at 25°C as a function of pH showing influence of redox potential (expressed in terms of eqilibrium hydrogen pressure) and dissolved CO,. (O) 10 Pa H, (n) Fa H, (A) 10 M CO, and 10 Pa H,. Figure 1. UOg solubility from thermochemical computations concentration of U in a saturated aqueous solution at 25°C as a function of pH showing influence of redox potential (expressed in terms of eqilibrium hydrogen pressure) and dissolved CO,. (O) 10 Pa H, (n) Fa H, (A) 10 M CO, and 10 Pa H,.
A cross-sectional mean is the mean value of a quantity over a cross section. We will use the cross-sectional means to compute concentration in a system with dispersion. An illustrative example is given in Figure 1.7. For the system visualized in this figure, the cross-sectional mean velocity, U x, t), and cross-sectional mean concentration, C(x, f),would be given by... [Pg.12]

Fig. 2.3. Computed concentration histories for the cubic autocatalytic model with rate data from Table 2.1 except for the uncatalysed reaction rate constant feu = (a) the exponential... Fig. 2.3. Computed concentration histories for the cubic autocatalytic model with rate data from Table 2.1 except for the uncatalysed reaction rate constant feu = (a) the exponential...
Fig. 2.4. Computed concentration.histories for autocatalytic model with rate constants given exactly as in Table 2.1 (a) exponential decay of precursor (b) intermediate concentrations a(t) and 6(r), showing initial pseudo-stationary-state behaviour but subsequent development of an oscillatory period of finite duration, 1752 s < t < 3940 s. Fig. 2.4. Computed concentration.histories for autocatalytic model with rate constants given exactly as in Table 2.1 (a) exponential decay of precursor (b) intermediate concentrations a(t) and 6(r), showing initial pseudo-stationary-state behaviour but subsequent development of an oscillatory period of finite duration, 1752 s < t < 3940 s.
If the value of the reactant decay rate e is not very small, higher-order correction terms will become significant more quickly. Exact (i.e. precisely computed) concentration histories will not be well appproximated by the pseudo-stationary forms (3.72) and (3.73) even when the state is locally stable. During any possible period of oscillatory behaviour, the number of oscillations will naturally decrease as e increases, as expressed by eqn (3.79). In addition to this, however, the time for the first excursion to develop, which... [Pg.81]

Fig. 4.1. Computed concentration and temperature histories for the thermokinetic model with parameters given in Table 4.1 showing monotonic decay of precursor reactant p but oscillations in the concentration of intermediate A and the temperature excess A7 (a) p(r), (b) a(t), and... Fig. 4.1. Computed concentration and temperature histories for the thermokinetic model with parameters given in Table 4.1 showing monotonic decay of precursor reactant p but oscillations in the concentration of intermediate A and the temperature excess A7 (a) p(r), (b) a(t), and...
Even if we know all reactions and equilibrium constants for a given system, we cannot compute concentrations accurately without activity coefficients. Chapter 8 gave the extended Debye-Huckel equation 8-6 for activity coefficients with size parameters in Table 8-1. Many ions of interest are not in Table 8-1 and we do not know their size parameter. Therefore we introduce the Davies equation, which has no size parameter ... [Pg.254]

Figure 13-3 puts everything together in a spreadsheet. Input values for FKH,P04, FNaiHPOj, pA i, pKn, pK3, and pA w are in the shaded cells. We guess a value for pH in cell H15 and write the initial ionic strength of 0 in cell Cl9. Cells A9 H10 compute activities with the Davies equation. With pi = 0, all activity coefficients are 1. Cells A13 H16 compute concentrations. [HT] in cell B13 is (10 PH)/yH = (10A-H15)/B9. Cell El 8 computes the sum of charges. [Pg.255]

Uses of ionization constants to compute concentrations of the ions present in solution and the pH of the solution are illustrated in the following problems. First we consider the dissociation of a monoprotic acid, using acetic acid as an example. Later we examine the dissociation of a diprotic acid, H2S, in connection with precipitation of metal sulfides. [Pg.350]

However, according to Little (1969), polyethyleneoxide solutions of different molecular weights gave the same drag reduction when their concentration was proportional to the critical concentration at each molecular weight (i.e., the computed concentration for the polymer coils to touch each other). Kinnier obtained similar results but used the concept of equivalent concentrations . He found that to have equal drag reduction for different molecular weight polymer solutions, one has to have equal volumes of polymer based upon the hydrodynamic sphere considerations. [Pg.113]

The different ionic forms of PPt which are present in significant amounts at pH 6-9 in the presence of Mg2, as activating cation, and KC1, to adjust the ionic strength, are shown in Fig. 1. Moe and Butler have attempted to assess the catalytic significance of these forms and of free Mg2 which is also present (9). The values of the equilibrium constants for all these interactions have been evaluated under conditions similar to those of the pyrophosphatase assay (SI), and a computer program has been devised to calculate the concentration of each of these ionic species as a function of pH and of total added PPi and MgCl2 (9). Rates of PPi hydrolysis were determined over a wide range of Mg2 and PP, concentrations at pH 7.4, 8.1, and 9.0. The observed rates of PP, hydrolysis and computed concentrations of the ionic species... [Pg.535]

For our specific data the computed concentrations Xj and Yj of component A in the jth tray appear in the first column of the on-screen output matrix for the liquid phase and in the second column for the gaseous phase, respectively, after calling linearcolumn(6,0.72, 0.01,750,7000,0.001,1.4). [Pg.358]

Both studies showed a fast reaction between IO and DMS. In their study, Barnes et al. (161 obtained reasonable agreement between experimental and calculated concentration-time profiles tor the NO2/I2/N2/DMS photolysis system. Within the experimental error limits, they found mat for every molecule of NO2 photolyzed, one molecule of DMS is consumed and one molecule each of NO and DMSO are formed and concluded that the reaction IO + DMS —> DMSO + I occurs. A best fit between experimental and computed concentration-time profiles including the formation of DMSO was obtained for a value of kj = (3.0 1.5) x 10 11 cm molecule V1 for reaction (1). [Pg.467]

Leistra, M., Smelt, J.H., Verlaat, J.G., Zandvoort, R. (1974) Measured and computed concentration patterns of propyzamide in field soils. Weed Res. 14, 87-95. [Pg.512]

Hines and Maddox (1985) found that the Edmister method gives a close approximation to observed or rigorously computed concentration gradients in many multicomponent absorbers. [Pg.17]

Systematic studies of reaction energies for the abstraction of H2 from MH4 (equation 5) for M = Si, Ge, Sn and Pb were reported by Dyall who also compared the results of the DHF calculations with those of other methods (ECP, PT)126, by Schwerdtfeger and coworkers48b who included also the eka-lead element 114 and by Thiel and coworkers105 who studied also the activation barriers for this reaction. More recent computations concentrated on the evaluation of the quality of the various theoretical approaches103106. The results of the calculations are collected in Table 4 and are shown graphically in Figure 3a. [Pg.17]

Step 10. Determine the concentration of the uranium isotopes in the uranium samples. Data collection, processing, and print-out usually are done by computer. Concentrations usually are reported in parts per billion (ppb, or pg/L). Some hand calculation is desirable to understand the process. [Pg.155]

In the case of the ultramicroelectrodes such as the disk electrode, it is necessary to integrate over the surface, and sometimes there will be unequally spaced points along the surface, as for example, in direct discretisation on an unequal grid in the example program UME DIRECT. As mentioned in Chap. 12, it is found that due to the errors in the computed concentration values, the local fluxes are so inaccurate that any integration method better than the simple trapezium method is not justified. The routine U TRAP is thus recommended here. It integrates local current densities, precalculated by using the above routine U DERIV. [Pg.304]

Figure 2 presents a typical exemple of computed concentration profiles obtained with the software using or not a pressure gradient [14],... [Pg.431]

Fig. 9.3 Comparison among O3 observed (black dots) and computed concentration with Kz... Fig. 9.3 Comparison among O3 observed (black dots) and computed concentration with Kz...

See other pages where Computer Concentration is mentioned: [Pg.154]    [Pg.130]    [Pg.221]    [Pg.80]    [Pg.243]    [Pg.181]    [Pg.697]    [Pg.83]    [Pg.360]    [Pg.553]    [Pg.57]    [Pg.151]    [Pg.148]    [Pg.243]    [Pg.183]    [Pg.151]    [Pg.204]   
See also in sourсe #XX -- [ Pg.692 ]




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