Phosphate complexation model and its implications for chemical phosphorus removal

A phosphate complexation model is developed, in an attempt to understand the mechanistic basis of chemically mediated phosphate removal. The model presented here is based on geochemical reaction modeling techniques and uses known surface reactions possible on hydrous ferric oxide (HFO). The types of surface reactions and their reaction stoichiometry and binding energies (logK values) are taken from literature models of phosphate interactions with iron oxides. The most important modeling parameter is the proportionality of converting moles of precipitated HFO to reactive site density. For well-mixed systems and phosphate exposed to ferric chloride during HFO precipitation, there is a phosphate capacity of 1.18 phosphate ions per iron atom. In poorly mixed systems with phosphate exposed to iron after HFO formation, the capacity decreased to 25% of the well-mixed value. The same surface complexation model can describe multiple data sets, by varying only a single parameter proportional to the availability of reactive oxygen functional groups. This reflects the unavailability of reactive oxygen groups to bind phosphate. Electron microscope images and dye adsorption experiments demonstrate changes in reactive surface area with aging of HFO particles. Engineering implications of the model/mechanism are highlighted.     

Boundary Layer Emission Monitoring

A new methodology is described for determining the atmospheric emission rate of pollutants from large heterogeneous area sources, such as hazardous waste sites. The procedure hinges upon measuring average pollutant concentrations, at three or more different elevations, while traversing the plume downwind of the area source. A helium-filled tethersonde balloon is used to elevate the sampling lines to their appropriate height. During plume traversing the sampling rate is adjusted to be proportional to the sine of the angle between the wind vector and the direction of the traverse path. The average concentrations are corrected for any upwind, background concentration and then used to derive an average vertical concentration profile. This profile Is numerically integrated, with the wind velocity profile, over the pollutant boundary layer to yield the area source emission rate. The methodology was tested on several large industrial effluent lagoons and proved to be easy to use, robust, and precise.     

On the translation of uncertainty from toxicokinetic to toxicodynamic models--the TCDD example

When estimating human health risks from exposure to TCDD using toxicokinetic and toxicodynamic models, it is important to understand how model choice and assumptions necessary for modeling add to the uncertainty of risk estimates. Several toxicokinetic models have been proposed for the risk assessment of dioxins, in particular the elimination kinetics in humans has been a matter of constant debate. For a long time, a simple linear elimination kinetics has been common choice. Thus, it was used for the statistical analysis of the largest occupationally exposed cohort, the German Boehringer cohort. We challenge this assumption by considering, amongst others, a nonlinear modified Michaelis-Menten-type elimination kinetics, the so-called Carrier kinetics. Using the area under the lipid TCDD concentration time curve as dose metrics, we model the time to cancer-related death using the Cox proportional hazards model as toxicodynamic model. This risk assessment set-up was simulated in order to quantify uncertainty of both the dose (TCDD body burden) and the risk estimates, depending on the use of the kinetic model, variations of carcinogenic effect of TCDD and variations of latency period (lag time). If past exposure is estimated assuming a linear elimination kinetics although a Carrier kinetics actually holds, then high exposures in reality will be underestimated through statistical analysis and low exposures will be overestimated, respectively. This bias will carry over on the estimated individual concentration-time curves and the therefrom derived TCDD dose metric values. Using biased dose values when estimating a dose-response relationship will finally lead to biased risk estimates. The extent of bias and the decrease of precision are quantified in selected scenarios through this simulation approach. Our findings are in concordance with recent results in the field of dioxin risk assessment. They also reinforce the general demand for the scheduled uncertainty assessments in risk analyses.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 4. A Three-Parameter Averaging-Time Model

Urban air pollutant concentration data often tend to fit a two-parameter averaging-time model having three characteristics: (1) pollutant concentrations are (two-parameter) lognormally distributed for all averaging times; (2) median concentrations are proportional to averaging time raised to an exponent; and (3) maximum concentrations are approximately inversely proportional to averaging time raised to an exponent. Concentration data obtained near many isolated point sources and in some urban areas often do not fit a two-parameter lognormal distribution. An increment (either positive or negative) can be added to each such concentration in order to fit the data instead to a three-parameter lognormal distribution. This increment has been incorporated as the third parameter in a new three-parameter averaging-time model that can be used in both point-source and urban settings. Examples show how this new model can be used to analyze SO₂ concentration data obtained near a point source to determine the degree of emission reduction needed to achieve the national ambient air quality standards.     

Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits

Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to three key services, focusing on the regional species pool in the Norrström area (central Sweden) and three main wetland types. Our method predicts proportional shifts toward faster growing, more productive and taller species, which tend to increase CWMT values of specific leaf area and canopy height, whereas changes in root depth vary. The predicted changes in CWMT values suggest a potential increase in flood attenuation services, a potential increase in short (but not long)-term nutrient retention, and ambiguous outcomes for carbon sequestration.     

Cohesion of Precipitated Dust Layer in Electrostatic Precipitators

One of the important cohesive forces acting on the precipitated layer in an electrostatic precipitator Is that due to the effect of the electric field established in the air gaps between adjacent particles by the corona current as it flows through the layer. A theoretical expression for this force is developed for an idealized dust layer which takes into account the increase in effective contact area between adjacent particles due to elastic deformation and the limiting of the electric field in the airgap to a maximum allowable value. It is shown that the cohesive force is approximately proportional to the electric field established across the layer. This relationship is in general agreement with measurements made in the laboratory using industrially produced dust samples.     

Photocatalytic oxidation of xenobiotics in water with immobilized TiO2 on agitator

A novel photocatalytic oxidation reactor, using Degussa P-25 TiO2 as a stationary phase with a thickness of 1.5-2.0 um on the blades of agitator, was developed to study the photocatalytic oxidation of xenobiotics. Particularly in this device, separation of photocatalyst from the purified water after oxidation reaction was not necessary, and no other aeration equipment was required to supply oxygen. To examine the efficiency of this device, photocatalytic degradation of xenobiotic organics such as carbofuran was studied as an example. Results indicated that carbofuran could be degraded completely with mineralization efficiency of 20% after 6 hours of oxidation under the imposed conditions. The mineralization rate of carbofuran was found to follow the pseudo-first order reaction kinetics. Moreover, the rate constant of mineralization was found to be proportional to TiO2 film area and the square root of UV light intensity. These results implied the mineralization efficiency of carbofuran could be improved through increasing TiO2 film area and UV light intensity. Accordingly, this novel device showed potential application for degrading xenobiotics in water.     

Harmonic analysis of flow in open boreholes due to barometric pressure cycles

Barometric pressure changes can induce airflow in an open borehole or well screened in the vadose zone, thereby ventilating the soil surrounding the borehole. This paper presents an analytic model of the induced airflow and compares the predictions of the model with experimental measurements. This model may be useful for the design of passive soil vapor extraction as applied to the remediation of soil contaminated by volatile organic compounds (VOCs). Based on harmonic analysis, the model predicts the time-dependent flow in agreement with measurements at a borehole in strata of differing permeability. The model uses no adjustable parameters, but proceeds from first principles based upon known or estimated values of soil properties as a function of depth. In an approximation, the calculated flow is determined by the difference between barometric pressure and the attenuated pressure that would propagate vertically into the vadose zone in the absence of an open borehole. The attenuated vertical propagation of pressure can be calculated by a corresponding harmonic method presented previously. The model reveals that the flow in the borehole is approximately proportional to the horizontal permeability in the formation, and depends only weakly on the soil porosity and borehole radius.     

The relationship between elimination rates and partition coefficients

Rate constants for uptake and elimination of chemicals in organisms are often related to partition coefficients (typically the octanol-water partition coefficient). We show that the well-mixed one-compartment model for toxico-kinetics implies that the elimination rate is inversely proportional to the square root of the partition coefficient. When chemical exchange is limited by diffusion in the boundary layers adjacent to the interface, two-film models are appropriate, which have more complex implications for the relationships between the exchange rates and the partition coefficient. We also show that the popular steady-flux approximation of the two-film model is not a conceptual generalization of the one-compartment model, although it shares the first-order kinetics. We compare the kinetics of a series of models with an increasing number of well-mixed compartments for exchange, such that the two-film model results for an infinite number of compartments. The latter model formulation in terms of partial differential equations, and more in particular its boundary condition at the interface of the two media, is believed to be new. In the steady-flux approximation and in the model with single well-mixed boundary layers and low diffusivities, the elimination rate depends hyperbolically on the partition coefficient. The available data for abiotic systems (SPME fibers) supports a hyperbolic relationship, whereas the data for aquatic biota are less discriminating between a hyperbolic or a square root relationship with the partition coefficient. The daphnia data showed less scatter than the fish data, possibly due to the small variance in body sizes, since elimination rates are inversely proportional to body length. The square root relationship fitted these data best.     

An extended self-organizing map network for modeling and control of pulse jet fabric filters

Pulse jet fabric filters (PJFFs) have become an attractive option of particulate collection utilities, because they can meet stringent particulate emission limits regardless of variation in operating conditions. Despite their wide applications, the present control algorithm for PJFFs can best be described as rudimentary. In this paper, a modeling and control strategy based on the local model network (LMN) is proposed. An extended self-organizing map (ESOM) network is developed to construct the LMN model of the filtration process using the filter's input-output data. Subsequently, these ESOM local models are incorporated into the design of local generalized predictive controllers (GPC), and the proposed controller design is obtained as the weighted sum of these local controllers. Simulation results show that the proposed controller design yields a better performance than both conventional GPC and proportional plus integral (PI) controllers yield.     

Bioconcentration of cadmium in water hyacinth (Eichhornia crassipes) in relation to thiol group content

To study the bioconcentration of cadmium in water hyacinth, the plants were exposed to water containing 2 microg Cd2+/ml for extended periods of time. Three strains from several exposures during a 30-day period were sampled for the analyses of cadmium and thiol group. The data showed that the plant concentrates cadmium mainly in the roots and that the cadmium uptake is proportional to the increase of the thiol group content. The latter suggests the possibility of using the thiol group content to assess the bioconcentration of heavy metal ions in water hyacinth and as a general parameter for monitoring the heavy metal pollution of water. A simple two-compartmental model was used to simulate the kinetics of cadmium uptake. The calculated bioconcentration factor matches the one derived directly from experimental data, indicating the adequacy of the model.     

An Extended Self-Organizing Map Network for Modeling and Control of Pulse Jet Fabric Filters

ABSTRACT

Pulse jet fabric filters (PJFFs) have become an attractive option of particulate collection utilities, because they can meet stringent particulate emission limits regardless of variation in operating conditions. Despite their wide applications, the present control algorithm for PJFFs can best be described as rudimentary. In this paper, a modeling and control strategy based on the local model network (LMN) is proposed. An extended self-organizing map (ESOM) network is developed to construct the LMN model of the filtration process using the filter's input-output data. Subsequently, these ESOM local models are incorporated into the design of local generalized predictive controllers (GPC), and the proposed controller design is obtained as the weighted sum of these local controllers. Simulation results show that the proposed controller design yields a better performance than both conventional GPC and proportional plus integral (PI) controllers yield.     

Estimating first-order reaction rate coefficient for transport with nonequilibrium linear mass transfer in heterogeneous media

A travel-time based approach is developed for estimating first-order reaction rate coefficients for transport with nonequilibrium linear mass transfer in heterogeneous media. Tracer transport in the mobile domain is characterized by a travel-time distribution, and mass transfer rates are described by a convolution product of concentrations in the mobile domain and a memory function rather than predefining the mass transfer model. A constant first-order reaction is assumed to occur only in the mobile domain. Analytical solutions in Laplace domain can be derived for both conservative and reactive breakthrough curves (BTCs). Temporal-moment analyses are presented by using the first and second moments of conservative and reactive BTCs and the mass consumption of the reactant for an inverse Gaussian travel-time distribution. In terms of moment matching, there is no need for one to specify the mass transfer model. With the same capacity ratio and the mean retention time, all mass transfer models will lead to the same moment-derived reaction rate coefficients. In addition, the consideration of mass transfer generally yields larger estimations of the reaction rate coefficient than models ignoring mass transfer. Furthermore, the capacity ratio and the mean retention time have opposite influences on the estimation of the reaction rate coefficient: the first-order reaction rate coefficient is positively linearly proportional to the capacity ratio, but negatively linearly proportional to the mean retention time.     

Kinetic study and modeling on photocatalytic degradation of para-chlorobenzoate at different light intensities

In order to clarify the dependence of apparent adsorption constant Ks in the Langmuir-Hinshelwood (L-H) model on the incident light intensity, photocatalytic degradation kinetic characteristics were experimentally investigated at different light intensities using para-chlorobenzoate (4-CBA) as a model compound. In all cases 4-CBA initial degradation rates showed dependence on 4-CBA initial concentration, which can be described by the L-H model. However, the adsorption constant Ks and rate constant kr obviously varied with light intensity. To account for the experimental finding, slight modification of the classic kinetic model developed by Turchi and Ollis was tentatively proposed by assuming insufficiency of H2O/OH- available for photo-activated holes' scavenging. Such a kinetic model predicts that both k(r) and Ks(-1) are linearly proportional to the square root of the intensity in a rather large intensity range. The validity of the modified model was proved by fitting it to the experimental data.     

Sensitivity Analysis of Dispersion Models for Point and Area Sources

The body of information presented in this paper is directed to air quality managers in industry and government contemplating modeling emissions from complex sources under the bubble concept.

Point and area source algorithms of PAL, RAM, and ISC-ST were analyzed to show the effect of various input assumptions on model output. Several important parameters were varied individually; receptor grid spacing, emission release height, area source size and source type. Each of these parameters was varied over a range of values while all other modeling parameters, both physical and meteorological, were held constant. The outputs of each model are plotted for easy comparison.

Results indicate that it would be inappropriate to make certain assumptions regarding source characteristics without knowing the behavior of each model. The graphs show how the model predictions can vary for different input parameters when applied to point and area sources. The paper presents general rules of thumb for evaluating model results for many applications such as the bubble concept, emissions banking, offsets, and new source reviews. The results serve as a guide in selecting and using models for both point and area sources.     

Ammonium Nitrate,Nitric Acid,and Ammonia Equilibrium in Wintertime Phoenix,Arizona

A secondary aerosol equilibrium model, SEQUILIB, is applied to evaluate the effects of emissions reductions from precursor species on ambient concentrations during the winter in Phoenix, Arizona. The model partitions total nitrate and total ammonia to gas-phase nitric acid and ammonia and to particle-phase ammonium nitrate. Agreement between these partitions and ambient measures of these species was found to be satisfactory. Equilibrium isopleths were generated for various ammonium nitrate concentrations corresponding to high and low humidity periods which occurred during sampling. These diagrams show that ammonia is so abundant in Phoenix that massive reductions in its ambient concentrations would be needed before significant reductions in particulate ammonium nitrate would be observed. When total nitrate is reduced by reductions in its nitrogen oxides precursor, proportional reductions in particulate nitrate are expected. Many of the complex reactions in SEQUILIB do not apply to Phoenix, and its ability to reproduce ambient data in this study does not guarantee that it will be as effective in areas with more complex chemistry. Nevertheless, the nitrate chemistry in SEQUILIB appears to be sound, and it is a useful model for addressing the difficult apportionment of secondary aerosol to its precursors.     

A Simulation Model for Air Pollution over Connecticut

A different approach to mathematically modeling large-scale atmospheric processes is presented. Whereas past approaches have been to develop a model based on an accumulation of information from a specific geographical area, resulting in a model applicable to that area only, we have developed a general mathematical model applicable to any geographical area. The model’s applicability is controlled by specifying the input information describing the meteorological situation and pollution source configuration. A rectangular array of grid points is used to specify both the wind field, by using stream functions, and the average source strength of some pollutant for the area represented by the grid. The diffusion problem is divided into two areas: transport by the mean wind field, and dispersion based on travel time and distance as described by empirical equations. Trajectories of pollutants are traced backwards from the points of interest in the course of the calculations and the contributions of all sources that affect the points of interest are accumulated. The model requires an array of source strength information. An inventory of pollution sources in the State of Connecticut was compiled and maps of source strengths were prepared for five pollutants on a 5000-ft grid-square array. Maps of sulfur dioxide and carbon monoxide source strengths are presented with the resulting concentration distribution for “typical” meteorological conditions. The model permits the changing of meteorological or source values at predetermined intervals so that diurnal changes are incorporated in the calculations. The model has not been verified, but the values of pollution concentration are the right order of magnitude and the resulting patterns are as expected.     

A multi media load model for the Baltic Sea

The background of this work is the international decision process with regard to the selection of chemicals to be assessed with priority. In order to stress the precautionary principle, mass flows were analysed rather than concentrations, threshold values, etc., as preferred by the chemical legislation (which still excludes the marine area). Lindane, hexachlorobenzene (HCB), trichloroacetic acid and its sodium salt, medium-chained chlorinated paraffins and tributyltin (TBT) were selected due to their great relevance for the marine area. Trichloroacetic acid is an interesting model compound on account of its accidental formation by degradation of volatile chlorinated hydrocarbons and during chlorination processes. In addition, a hypothetical compound was modelled, representing a highly water-soluble substance with low vapour pressure. The balancing area is the Baltic Sea and its catchment area. In order to model the substance flows, the 'Input/Output-load model' has been developed. The model quantifies the shift and the distribution of a yearly load of the substance investigated from the terrestrial-limnic into the marine compartment (Baltic Sea). Water-soluble substances, which are usually considered to be of no concern, may enter the sea in great amounts and, if not degradable, remain there. It turned out to be necessary to take into account remobilisation, unintended formation and point as well as line-sources.     

An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

Modeling of potential power plant plume impacts on Dallas-Fort Worth visibility

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called "white haze." The objective of this work was to assess whether reductions in the emissions of SO2 from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF6 tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO2 from the modeled power plant.