Prediction of pressure drop in an orifice scrubber based on a Lagrangian approach

A mathematical model has been developed to predict pressure drop in an orifice scrubber. This model is based on a Lagrangian approach for droplet movement and a particle-source-in-cell (PSI-CELL) model for calculating droplet concentration distribution. The k-epsilon turbulent model including body force due to the drag force between fluid and droplets was used to evaluate the fluid velocity distribution. The effect of orifice size on pressure drop and the correlations for mean droplet diameter have been studied. The results from the model have been compared with experimental data. This comparison shows excellent agreement between the calculated results and the experimental data.     

Effects of droplet density and concentration on the efficacy of bacillus thuringiensis and carbaryl against gypsy moth larvae (Lymantria dispar L.)

Abstract

The feeding behavior of gypsy moth larvae exposed to two pesticide deposits (Bt and carbaryl) on oak leaf disks was monitored to determine the relationships between its efficacy and application parameters (droplet density and pesticide concentration). A range of pesticide concentrations and droplet densities (from 9 to 149 droplets/cm²) was used to simulate high and low application rates produced by different methods of application in the field.

The LD₅₀ and the LC₅₀, appeared to be affected by the spatial distribution of the deposit on the leaf surface. Both Bt and carbaryl showed a decreasing LD₅₀ at increasing time after spray. The LD₅₀ of Bt decreased from 14.1 BIU/liter to 3.1 BIU/Iiter between 48 and 144 hours after spray. The results show that feeding inhibition by Bt is more closely related to concentration than to droplet density and dose per unit area with the highest feeding inhibition occurring at 10 BIU/liter at 9 droplets/cm². With carbaryl, an increase in both concentration and droplet density was necessary to cause a decrease in leaf area eaten by larvae.     

Theoretical study of liquid droplet dispersion in a venturi scrubber

The droplet concentration distribution in an atomizing scrubber was calculated based on droplet eddy diffusion by a three-dimensional dispersion model. This model is also capable of predicting the liquid flowing on the wall. The theoretical distribution of droplet concentration agrees well with experimental data given by Viswanathan et al. for droplet concentration distribution in a venturi-type scrubber. The results obtained by the model show a non-uniform distribution of drops over the cross section of the scrubber, as noted by the experimental data. While the maximum of droplet concentration distribution may depend on many operating parameters of the scrubber, the results of this study show that the highest uniformity of drop distribution will be reached when penetration length is approximately equal to one-fourth of the depth of the scrubber. The results of this study can be applied to evaluate the removal efficiency of a venturi scrubber.     

Droplet trajectories and deposition with an airblast forestry sprayer

Abstract

The characteristics of the air pattern and spray droplet trajectories from the Algonquin airblast forestry sprayer were investigated. An experiment with water and Rhodamine tracer dye was conducted in a shelterwood location to evaluate droplet deposition on Kromekote^® card targets above and within a canopy of poplar saplings. Computer simulation of a free jet was used to model the airblast in order to investigate droplet trajectories. Measured deposits indicated that the effective swath width is 14 m from the blower outlet. Mean simulated droplet trajectory data were in good agreement with the droplet density data observed in the field. Both sets of results predicted a very low level of spray deposition beyond 14 m.     

Mathematical prediction of imidacloprid persistence in two Croatian soils with different texture,organic matter content and acidity under laboratory conditions

In the present laboratory study, persistence of imidacloprid (IMI) as a function of initial insecticide concentration and soil properties in two Croatian soils (Krk sandy clay and Istria clay soils) was studied and described mathematically. Upon fitting the obtained experimental data for the higher concentration level (5 mg/kg) to mathematical models, statistical parameters (R ², scaled root mean squared error and χ ² error) indicated that the single first-order kinetics model provided the best prediction of IMI degradation in the Krk sandy clay soil, while in the Istria clay soil biphasic degradation was observed. At the lower concentration level (0.5 mg/kg), the biphasic models Gustafson and Holden models as well as the first-order double exponential model fitted the best experimental data in both soils. The disappearance time (DT₅₀) values estimated by the single first-order double exponential model (from 50 to 132 days) proved that IMI can be categorized as a moderately persistent pesticide. In the Krk sandy clay soil, resulting DT₅₀ values tended to increase with an increase of initial IMI concentration, while in the Istria clay soil, IMI persistence did not depend on the concentration. Organic matter of both experimental soils provided an accelerating effect on the degradation rate. The logistic model demonstrated that the effect of microbial activity was not the most important parameter for the biodegradation of IMI in the Istria clay soil, where IMI degradation could be dominated by chemical processes, such as chemical hydrolysis. The results pointed that mathematical modeling could be considered as the most convenient tool for predicting IMI persistence and contributes to the establishment of adequate monitoring of IMI residues in contaminated soil. Furthermore, IMI usage should be strictly controlled, especially in soils with low organic matter content where the risk of soil and groundwater contamination is much higher due to its longer persistence and consequent leaching and/or moving from soil surface prior to its degradation.     

Comparison of Computer Simulations of Total Lung Deposition to Human Subject Data in Healthy Test Subjects

ABSTRACT

A mathematical model was used to predict the deposition fractions (DF) of PM within human lungs. Simulations using this computer model were previously validated with human subject data and were used as a control case. Human intersubject variation was accounted for by scaling the base lung morphology dimensions based on measured functional residual capacity (FRC) values. Simulations were performed for both controlled breathing (tidal volumes [V_T] of 500 and 1000 mL, respiratory times [T] from 2 to 8 sec) and spontaneous breathing conditions. Particle sizes ranged from 1 to 5 um. The deposition predicted from the computer model compared favorably with the experimental data. For example, when V_T = 1000 mL and T = 2 sec, the error was 1.5%. The errors were slightly higher for smaller tidal volumes. Because the computer model is deterministic (i.e., derived from first principles of physics), the model can be used to predict deposition fractions for a range of situations (i.e., for different ventilatory parameters and particle sizes) for which data are not available. Now that the model has been validated, it may be applied to risk assessment efforts to estimate the inhalation hazards of airborne pollutants.     

Mathematical modelling of flue-gas desulphurisation using lime slurry in a turbulent contact absorber

A mathematical model has been developed for absorption of SO₂ from flue gases using lime slurry in Turbulent Contact Absorbers (TCA). In this model, the TCA was simulated by considering it as a falling film absorption system. Turbulent effects were taken into account by using eddy viscosity and eddy diffusivity. The system of partial differential equations of mass transfer with moving boundaries was solved numerically in order to obtain the concentration profiles of the reactants, the thickness of the reaction zone and the outlet gas concentration. A bench-scale TCA was built up, and the mathematical model was evaluated against experimental data obtained from the built device. The model predictions showed good agreement with the experimental data and literature data.     

Removal of carbon disulfide via coupled reactions on a bi-functional catalyst: Experimental and modeling results

A mathematical model describing the rate of carbon disulfide (CS₂) removal due to coupled reactions has been developed. Kinetic studies were carried out in a fixed bed reactor under atmospheric pressure and a range of temperatures (85–125 °C). The effects of flow rate, CS₂ inlet concentration, temperature and relative humidity were analyzed. A kinetic model based on axial dispersion, external and internal mass-transfer resistances, as well as effects of S deposition on the inner-face of the catalyst was in agreement with the CS₂ experimental breakthrough curves. The mathematical model can be used for process design and scale up of similar systems.     

Heterogeneous Oxidation by Ozone of Naphthalene Adsorbed at the Air-Water Interface of Micron-Size Water Droplets

Abstract

The mass transfer of naphthalene vapor to water droplets in air was studied in the presence of ozone (O₃) in the gas phase. A falling droplet reactor with water droplets of diameters 55, 91, and 182 μm was used for the study. O₃ reacted with naphthalene at the air-water interface, thereby decreasing the mass transfer resistance and increasing the rate of uptake of naphthalene into the droplet. A Langmuir-Hinshelwood reaction mechanism at the air-water interface satisfactorily described the surface reaction. The first-order surface reaction rate constant, k_s, increased with decreasing droplet size. Three organic intermediates were identified in the aqueous phase as a result of ozonation of naphthalene at the surface of the droplet indicating both peroxidic and nonperoxidic routes for ozonation. The presence of an organic carbon surrogate (fulvic acid) increased both the partition constant of naphthalene and the surface reaction rate of O₃. The heterogeneous oxidation of naphthalene by O₃ on the droplet was 15 times faster than the homogeneous oxidation by O₃ in the bulk air phase, whereas it was only 0.08 times the homogeneous gas-phase oxidation by hydroxyl radicals under atmospheric conditions.     

Analysis of a Farquhar-von Caemmerer-Berry leaf-level photosynthetic rate model for Populus tremuloides in the context of modeling and measurement limitations

The balance of mechanistic detail with mathematical simplicity contributes to the broad use of the Farquhar, von Caemmerer and Berry (FvCB) photosynthetic rate model. Here the FvCB model was coupled with a stomatal conductance model to form an [A,g_s] model, and parameterized for mature Populus tremuloides leaves under varying CO₂ and temperature levels. Data were selected to be within typical forest light, CO₂ and temperature ranges, reducing artifacts associated with data collected at extreme values. The error between model-predicted photosynthetic rate (A) and A data was measured in three ways and found to be up to three times greater for each of two independent data sets than for a base-line evaluation using parameterization data. The evaluation methods used here apply to comparisons of model validation results among data sets varying in number and distribution of data, as well as to performance comparisons of [A,g_s] models differing in internal-process components.     

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: A case study in Taiyuan City,China

Primary fine particulate matters with a diameter of less than 10 µm (PM₁₀) are important air emissions causing human health damage. PM₁₀ concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM₁₀ pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM₁₀ yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM₁₀ yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM₁₀ from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM₁₀ pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

Implications The PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m³, was higher than the 65 μg/m³ recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM₁₀ yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM₁₀ spatial distribution. The results indicated that the artificial neural network was an effective method for PM₁₀ pollution modeling.     

Development of a chemical kinetic model for a biosolids fluidized-bed gasifier and the effects of operating parameters on syngas quality

In an effort to decrease the land disposal of sewage sludge biosolids and to recover energy, gasification has become a viable option for the treatment of waste biosolids. The process of gasification involves the drying and devolatilization and partial oxidation of biosolids, followed closely by the reduction of the organic gases and char in a single vessel. The products of gasification include a gaseous fuel composed largely of N₂, H₂O, CO₂, CO, H₂, CH₄, and tars, as well as ash and unburned solid carbon. A mathematical model was developed using published devolatilization, oxidation, and reduction reactions, and calibrated using data from three different experimental studies of laboratory-scale fluidized-bed sewage sludge gasifiers reported in the literature. The model predicts syngas production rate, composition, and temperature as functions of the biosolids composition and feed rate, the air input rate, and gasifier bottom temperature. Several data sets from the three independent literature sources were reserved for model validation, with a focus placed on five species of interest (CO, CO₂, H₂, CH₄, and C₆H₆). The syngas composition predictions from the model compared well with experimental results from the literature. A sensitivity analysis on the most important operating parameters of a gasifier (bed temperature and equivalence ratio) was performed as well, with the results of the analysis offering insight into the operations of a biosolids gasifier.

Implications:

As gasification becomes a more prominent waste disposal option, understanding the effects of feedstock composition and gasifier parameters on the production of syngas (rate and quality) becomes increasingly important. A model has been developed for the gasification of dried sewage sludge that will allow for prediction of changes in syngas quality (and energy recovery from the waste), and should be helpful in assessing the benefits of new gasification projects.     

Aerosol Measurement: The Use of Optical Light Scattering for the Determination of Particulate Size Distribution,and Particulate Mass,Including the Semi-Volatile Fraction

Abstract

The GRIMM model 1.107 monitor is designed to measure particle size distribution and particulate mass based on a light scattering measurement of individual particles in the sampled air. The design and operation of the instrument are described. Protocols used to convert the measured size number distribution to a mass concentration consistent with U.S. Environmental Protection Agency protocols for measuring particulate matter (PM) less than 10 μm (PM₁₀) and less than 2.5 μm (PM_2.5) in aerodynamic diameter are described. The performance of the resulting continuous monitor has been evaluated by comparing GRIMM monitor PM_2.5 measurements with results obtained by the Rupprecht and Patashnick Co. (R&P) filter dynamic measurement system (FDMS). Data were obtained during month-long studies in Rubidoux, CA, in July 2003 and in Fresno, CA, in December 2003. The results indicate that the GRIMM monitor does respond to total PM_2.5 mass, including the semi-volatile components, giving results comparable to the FDMS. The data also indicate that the monitor can be used to estimate water content of the fine particles. However, if the inlet to the monitor is heated, then the instrument measures only the nonvolatile material, more comparable to results obtained with a conventional heated filter tapered element oscillating microbalance (TEOM) monitor. A recent modification of the model 180, with a Nafion dryer at the inlet, measures total PM_2.5 including the nonvolatile and semi-volatile components, but excluding fine particulate water. Model 180 was in agreement with FDMS data obtained in Lindon, UT, during January through February 2007     

Computational fluid dynamics modeling of laboratory flames and an industrial flare

A computational fluid dynamics (CFD) methodology for simulating the combustion process has been validated with experimental results. Three different types of experimental setups were used to validate the CFD model. These setups include an industrial-scale flare setups and two lab-scale flames. The CFD study also involved three different fuels: C₃H₆/CH₄/Air/N₂, C₂H₄/O₂/Ar, and CH₄/Air. In the first setup, flare efficiency data from the Texas Commission on Environmental Quality (TCEQ) 2010 field tests were used to validate the CFD model. In the second setup, a McKenna burner with flat flames was simulated. Temperature and mass fractions of important species were compared with the experimental data. Finally, results of an experimental study done at Sandia National Laboratories to generate a lifted jet flame were used for the purpose of validation. The reduced 50 species mechanism, LU 1.1, the realizable k-? turbulence model, and the EDC turbulence–chemistry interaction model were used for this work. Flare efficiency, axial profiles of temperature, and mass fractions of various intermediate species obtained in the simulation were compared with experimental data and a good agreement between the profiles was clearly observed. In particular, the simulation match with the TCEQ 2010 flare tests has been significantly improved (within 5% of the data) compared to the results reported by Singh et al. in 2012. Validation of the speciated flat flame data supports the view that flares can be a primary source of formaldehyde emission.

ImplicationsValidated computational fluid dynamics (CFD) models can be a useful tool to predict destruction and removal efficiency (DRE) and combustion efficiency (CE) under steam/air assist conditions in the face of many other flare operating variables such as fuel composition, exit jet velocity, and crosswind. Augmented with rigorous combustion chemistry, CFD is also a powerful tool to predict flare emissions such as formaldehyde. In fact, this study implicates flares emissions as a primary source of formaldehyde emissions. The rigorous CFD simulations, together with available controlled flare test data, can be fitted into simple response surface models for quick engineering use.     

Trends and Variability of Ground-Level O3 in Connecticut over the Period 1981–1997

Abstract

The temporal and spatial characteristics of ground-level (tropospheric) O₃ measured at 10 monitoring stations in Connecticut were studied from 1981 to 1997. To detect the O₃ trend caused by changes in precursor emissions, moving average filters and a linear least-squared regression model were used to eliminate the short-term variation and effects of temperature from raw time-series O₃ data. The results showed a significant decrease in the number of days exceeding the National Ambient Air Quality Standards (NAAQS) and a small change in total O₃ concentration. The analysis indicated that the variation of daily maximum O₃, caused by changes in emissions, explained more than 10% of the total O₃ variation in Bridgeport and East Hartford during the past 17 years. Meanwhile, a strong weekly cycle was also found in O₃ time-series data, resulting in lower O₃ concentration in urban areas than in nonur-ban areas, implying that land use and land cover have impacts on the spatial distribution of ground-level O₃ in Connecticut.     

An Atmospheric Dispersion Model for the Environmental Impact Assessment of Thermal Power Plants in Japan—A Method for Evaluating Topographical Effects

Abstract

An atmospheric dispersion model was developed for the environmental impact assessment of thermal power plants in Japan, and a method for evaluating topographical effects using this model was proposed. The atmospheric dispersion model consists of an airflow model with a turbulence closure model based on the algebraic Reynolds stress model and a Lagrangian particle dispersion model (LPDM). The evaluation of the maximum concentration of air pollutants such as SO₂, NO_x, and suspended particulate matter is usually considered of primary importance for environmental impact assessment. Three indices were therefore estimated by the atmospheric dispersion model: the ratios (α and β, respectively) of the maximum concentration and the distance of the point of the maximum concentration from the source over topography to the respective values over a flat plane, and the relative concentration distribution [γ(x)] along the ground surface projection of the plume axis normalized by the maximum concentration over a flat plane. The atmospheric dispersion model was applied to the topography around a power plant with a maximum elevation of more than 1000 m. The values of α and β evaluated by the atmospheric dispersion model varied between 1 and 3 and between 1 and 0.4, respectively, depending on the topographical features. These results and the calculated distributions of γ(x) were highly similar to the results of the wind tunnel experiment. Therefore, when the slope of a hill or mountain is similar to the topography considered in this study, it is possible to evaluate topographical effects on exhaust gas dispersion with reasonable accuracy using the atmospheric dispersion model as well as wind tunnel experiments.     

Predicting Particulate (PM10) Personal Exposure Distributions Using a Random Component Superposition Statistical Model

ABSTRACT

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless “attenuation factor” between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM₁₀ measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities.     

83rd Annual Meeting & Exhibition

Abstract

The estimation of odor production and dispersion from landfill sites is a very complicated task because of the different chemical species that exist in biogas. To site a new landfill, it is necessary to know the distance that odors can travel around the landfill under atmospheric conditions that increase the concentration of pollutants. Although CH₄ is an odorless gas, it can be used as an index to determine the dispersion of low-reactivity odorous species around a landfill site. Methane production rates, estimated by biogas production models, were used by an air dispersion model to determine the spatial distribution of CH₄ around landfill sites. By utilizing dispersion models under extreme atmospheric conditions, a maximum CH₄ concentration around the landfills was determined. Based on the ratio between CH₄ and odorous chemical species, the spatial distribution of the concentration of an odorous species was determined for those species with low reactivity in the atmosphere. For odorous species with high reactivity in the atmosphere, a dispersion-reaction model must be used. In this way, the acceptable distance between new landfills and residential areas can be determined. The proposed methodology could be used as a design tool for those who are interested in landfill siting.     

冬季沈阳市典型源排放PM_(10)浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月~2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明:冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。     

Washing of Marine Coastal Sand in a Batch Reactor: Sorption and Desorption of BTEX

ABSTRACT

This study addresses the issues related to decontamination of marine beach sand accidentally contaminated by petroleum products. Sorption and desorption of BTEX (i.e., benzene, toluene, ethylbenzene, and xylene) onto the sand from Uran Beach, located near the city of Mumbai, India, were studied, and isotherms were determined using the bottle point method to estimate sorption coefficients. Alternatively, QSARs (i.e., quantitative structure activity relationships) were developed and used to estimate the sorption coefficients. Experiments for kinetics of volatilization as well as for kinetics of sorption and desorption in the presence of volatilization were conducted in a fabricated laboratory batch reactor. A mathematical model describing the fate of volatile hydrophobic organic pollutants like BTEX (via sorption and desorption in presence of volatilization) in a batch sediment-washing reactor was proposed. The experimental kinetic data were compared with the values predicted using the proposed models for sorption and desorption, and the optimum values of overall mass transfer coefficients for sorption (K_sa_s) and desorption (K_da_d) were estimated.This was achieved by minimization of errors while using the sorption coefficients (K_p) obtained from either laboratory isotherm studies or the QSARs developed in the present study. Independent experimental data were also collected and used for calibration of the model for volatilization,and the values of the overall mass transfer coefficient for volatilization (K_ga_g) were estimated for BTEX. In these exercises of minimization of errors, comparable cumulative errors were obtained from the use of K_p values derived from experimental isotherms and QSARs.