A Simple Technique for Stack Design in Complex Terrain

The main objective of this study is to apply neutral electrolyzed water (NEW) spraying to inactivate bioaerosols. We evaluated the inactivation efficiency of NEW applied to inactivate two airborne bacterial Escherichia coli and Bacillus subtilis aerosols inside an environmental-controlled chamber in the study. Generated with electrolyzing 6.15 M sodium chloride brine, the NEW with free available chlorine (FAC) concentration 50, 100, and 200 ppm was pumped with an air pressure of 70 kg/cm² through nozzle into the chamber to inactive E. coli and B. subtilis aerosols precontaminated air (initial counts of 3?×?10⁴ colony-forming units [CFU]/m³). Bacterial aerosols were collected and cultured from chamber before and after NEW spray. The air exchange rate (ACH, hr^?1) of the chamber was set to simulate fresh air ventilating dilution of indoor environment. First-order concentration decaying coefficients (Ka, min^?1) of both bacterial aerosols were measured as an index of NEW inactivation efficiency. The result shows that higher FAC concentration of NEW spray caused better inactivation efficiency. The Ka values under ACH 1.0 hr^?1 were 0.537 and 0.598 for E. coli of FAC 50 and 100 ppm spraying, respectively. The Ka values of FAC 100 ppm and 200 ppm spraying for B. subtilis were 0.063 and 0.085 under ACH 1.0 hr^?1, respectively. The results indicated that NEW spray is likely to be effective in inactivation of bacterial airborne contamination. Moreover, it is observed in the study that the increase of ventilation rate and the use of a larger orifice-size nozzle may facilitate the inactivation efficiency.

Implications: Bacterial aerosols have been implicated in deterioration of air quality and occupational health. Effective, safe, and economic control technology is highly demanded, especially for agricultural and food industries. In the study, NEW mist spraying performed effectively in controlling E. coli and B. subtilis modeling bioaerosols contamination. The NEW revealed its potential as an alternative airborne disinfectant worth being discovered for improving the environmental quality in the future.     

Experimental Characterization of Atmospheric Diffusion in Complex Terrain with Land-Sea Interactions

The body of information presented in this paper is directed to scientists working in atmospheric dispersion research and model development. Two years of field measurements in the coastal area of Bilbao in northern Spain show that the diffusion behavior in this complex terrain can be classified into several well defined patterns, which correspond to certain meteorological conditions. The approach taken has been the systematic use of SO₂ remote sensors (COSPEC) and ground level monitors in moving platforms which are used to follow and document the flow of the air mass. Results to date show that complex reentry cycles can occur and that synoptically different flows may be indistinguishable by wind sensors at ground level (affected by channeling), and yet result in totally different observed pollution levels by a fixed monitoring network (affected by topographical effects). These results are being used to parameterize the cause-effect relationships and guide the modeling efforts in this area of complex terrain.     

A Multivariable Model for Atmospheric Dispersion Predictions

In conjunction with a 15-month air quality survey of Jacksonville, Fia., a mathematical model has been developed to describe the dispersion of atmospheric pollutants. The source inventory used with the model was compiled, in part, from the data obtained from the sampling of all major sources within the area. The major sources were considered separately from the one-mile square area sources which accounted for the remainder of the emissions. Meteorological data was recorded continuously in the city including vertical temperature observations to 750 ft. The model was compiled in FORTRAN and can be used for both gaseous and particulate pollutants, by utilizing proper decay rates. The variant nature of meteorological parameters and emission rates are considered. The ground level concentrations of several pollutants which were determined for 24 hr periods at 11 sites and continuously at two other sites were used to check the model. A limited tracer study was carried out in conjunction with the project.     

Comparison of Predicted and Measured Concentrations for 58 Alternative models of Plume Transport in Complex Terrain

The purpose of this study was to evaluate alternative prediction models for the SO₂ concentrations produced in the vicinity of the Ohio Edison Company Sammis Power Plant. The plant is situated in the northeastern portion of the Ohio River Valley in complex terrain. Comparisons of the 16 highest predicted and measured short-term SO₂ concentrations were conducted for a one year period for 58 alternative models. Several models were found to predict reasonably accurately the 16 highest measured 24-hour SO₂ concentrations. Each of these models requires an upward adjustment in the plume centerline location as the plume is transported downwind in rising terrain. These same models overpredict by substantial margins the 16 highest measured 3-hour SO₂ concentrations. Improvements in emissions inventory data and improvements in the prediction models used are believed necessary to increase prediction accuracy further.     

Evaluation of a Probabilistic Exposure Model Applied

The probabilistic National Ambient Air Quality Standards (NAAQS) Exposure Model applied to carbon monoxide (pNEM/CO) was developed by the U.S. Environmental Protection Agency (EPA) to estimate frequency distributions of population exposure to carbon monoxide (CO) and the resulting carboxyhemoglobin (COHb) levels. To evaluate pNEM/CO, the model was set up to simulate CO exposure data collected during a Denver Personal Exposure Monitoring Study (PEM) conducted during the winter of 1982-1983.

This paper compares computer-simulated exposure distributions obtained by pNEM/CO with the observed cumulative

relative frequency distributions of population exposure to CO from 779 people in the Denver PEM study. The subjects were disaggregated into two categories depending upon whether they lived in a home with a gas stove or an electric stove. The observed and predicted population exposure frequency distributions were compared in terms of 1-hr daily maximum exposure (1DME) and 8-hr daily maximum moving average exposure (8DME) for people living in homes with gas stove or an electric stove. For 1DME, the computer-simulated results from pNEM/CO agreed most closely within the range of 6-13 ppm, but overestimated occurrences at low exposure (<6 ppm) and underestimated occurrences at high exposure (>13 ppm). For 8DME, the predicted exposures agreed best with observed exposures in the range of CO concentration between 5.5 and 7 ppm, and over-predicted occurrences below 5.5 ppm and under-predicted occurrences above 7 ppm.     

Control of Ozone Precursors in a Complex Industrial Terrain by Using Multiscale-Nested Air Quality Models with Fine Spatial Resolution (1 km2)

Abstract

The location of the northeastern Iberian Peninsula (NEIP) in the northwestern Mediterranean basin, the presence of the Pyrenees mountain range (with altitudes >3000 m), and the influence of the Mediterranean Sea and the large valley canalization of Ebro river induce an extremely complicated structure for the dispersion of photochemical pollutants. Air pollution studies in very complex terrains such as the NEIP require high-resolution modeling for resolving the very complex dynamics of flows. To deal with the influence of larger-scale transport, however, high-resolution models have to be nested in larger models to generate appropriate initial and boundary conditions for the finer resolution domains. This article shows the results obtained through the utilization of the MM5-EMICAT2000-CMAQ multiscale-nested air quality model relating the sensitivity regimes for ozone (O₃)-nitrogen oxides (NO_x)-volatile organic compounds (VOCs) in an area of high geographical complexity, like the industrial area of Tarragona, located in the NEIP. The model was applied with fine temporal (one-hour) and spatial resolution (cells of 24 km, 2 km, and 1 km) to represent the chemistry and transport of tropospheric O₃ and other photochemical species with respect to different hypothetical scenarios of emission controls and to quantify the influence of different emission sources in the area. Results indicate that O₃ chemistry in the industrial domain of Tarragona is strongly sensitive to VOCs; the higher percentages of reduction for ground-level O₃ are achieved when reducing by 25% the emissions of industrial VOCs. On the contrary, reductions in the industrial emissions of NO_x contribute to a strong increase in hourly peak levels of O₃. At the same time, the contribution of on-road traffic and biogenic emissions to ground-level O₃ concentrations in the area is negligible with respect to the pervasive weight of industrial sources. This analysis provides an assessment of the effectiveness of different policies for the control of emission of precursors by comparing the modeled results for different scenarios.     

Determination of Setback Distances for Livestock Operations Using a New Livestock Odor Dispersion Model (LODM)

ABSTRACT

Setback distance has been used as an effective tool to avoid odor nuisance from livestock operations. Many setback distances were guidelines that were determined by empirical methods that are considered to be lack of science base. Air dispersion models have been used to determine setback distances; however, these models do not consider the short-time fluctuations of odor. A livestock odor dispersion model (LODM) was developed to consider the short-time variations of odor and predict occurrence frequency for certain levels of odor. In this study, this model was used to predict the occurrence frequency for various levels of odor in the vicinity (10 km) of a swine farm. Using selected odor criteria, setback distances between the swine farm and nearby communities were defined. Results indicate that the LODM can be used as an effective tool to determine setback distances.

IMPLICATIONS One of the more important applications of odor dispersion models is to determine setback distances for major odor sources, such as intensive livestock operations, from nearby communities. This study provided a case study in determining directional setback distances from a typical swine farm using a newly developed livestock odor dispersion model (LODM). It is also the first study in using hourly odor frequency to determine setback distances.     

A Finite Line Source Dispersion Model for Mobile Source Air Pollution

The body of information presented in this paper is directed to individuals interested in dispersion modeling, and in particular to those concerned with evaluation of air quality in the vicinities of airports and roadways. The paper describes briefly the formulation and application of a finite line source dispersion model constructed on the basis of a Gaussian-type transport kernel. The formulation is sufficiently general that any arbitrary orientation of the line can be handled. For cases where the line is at small angles with respect to the wind, approximate expressions as well as segmentation of the line, if necessary, are used. These are Integrated into the general algorithmic scheme by means of a series of geometric tests. The general capabilities of the model are tested first with some hypothetical cases and then with actual air quality data. The latter case studies correspond to three separate periods of air quality monitoring at O’Hare Airport during which the aircraft emissions and the ground vehicle emissions play alternately important roles. The generally good agreement between model predictions and air quality data provides support for the validity of the approach. The overall efficiency of the model in terms of computer time as well as its limitations are briefly discussed.     

On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.     

Plume Dispersion in a Mountainous River Valley during Spring

The dispersion of hot plumes emitted from a smelter complex located In the Columbia River Valley, British Columbia, was evaluated under stable and neutral conditions during two mornings In spring. Spatial measurements of SO₂ and temperature within the plume were obtained by immersion probing using fast response helicopter and automobile mounted Instrumentation. In addition, meteorological measurements of vertical wind and temperature profiles at, and downwind from, the smelter were obtained from minisonde balloon releases. With weak down-valley winds, it was found that the plume axis elevations were generally lower during both stable and neutral conditions than would be predicted by Briggs plume-rise formulae. In contrast, plume dispersion, although confined in the horizontal by the steep valley walls during both stability regimes, was significantly enhanced by exceptionally good lateral mixing, particularly close to the source.     

A Tracer Study of Dispersion Over a City

The planning and conduct of series of tracer experiments carried out in St. Louis in the period between 1963 and 1965 is described. Tentative results indicate that horizontal dispersion over an urban area does not differ greatly from that observed over open country, except for a much greater initial spreading of the tracer plume. Vertical dispersion during the daytime does not appear to differ greatly from that observed over open country, and can be best expressed in terms of travel time rather than travel distance. Vertical dispersion during the evening over an urban area is much greater than that observed over open country; the limited results obtained suggest the formation of a slightly unstable layer as the air flows over the city.     

Air Quality Model Evaluation and Uncertainty

The many advances made in air quality model evaluation procedures during the past ten years are discussed and some components of model uncertainty presented. Simplified statistical procedures for operational model evaluation are suggested. The fundamental model performance measures are the mean bias, the mean square error, and the correlation. The bootstrap resampling technique is used to estimate confidence limits on the performance measures, In order to determine if a model agrees satisfactorily with data or if one model is significantly different from another model. Applications to two tracer experiments are described.

It is emphasized that review and evaluation of the scientific components of models are often of greater Importance than the strictly statistical evaluation. A necessary condition for acceptance Of a model should be that it is scientifically correct. It Is shown that even in research-grade tracer experiments, data Input errors can cause errors In hourly-average model predictions of point concentrations almost as large as the predictions themselves. The turbulent or stochastic component of model uncertainty has a similar magnitude. These components of the uncertainty decrease as averaging time increases.     

A sensitivity study of separation distances calculated with the Austrian Odour Dispersion Model (AODM)

The Austrian Odour Dispersion Model (AODM) is a Gaussian model adapted for the prediction of odour sensation. It estimates the daily and seasonal variation of the odour emission, the average, ambient odour concentration and the momentary (peak) concentration for the time-interval of a single human breath (approx. 5 s). Peak concentrations, further downwind, are modified by use of an exponential attenuation function for which the ratios of the standard deviations of the wind components to the average wind speed have either to be taken from the literature or to be calculated, e.g. from ultrasonic anemometer data.AODM calculates direction-dependent separation distances for a combination of odour threshold and exceedence probability, which are a function of the prevailing wind velocity and atmospheric stability conditions. Meteorological time series from one site in Styria in southern Austria and one site in the Austrian flatlands, North of the Alps, both rural, are used for a sensitivity study of separation distances. One aspect is, how two different schemes to determine atmospheric stability influence the separation distances. Another source of uncertainty of the calculated separation distances results from the use of measured or literature values for the ratios mentioned above. Decisions on which schemes or ratios to be used have a decisive influence on the separation distances.     

Dispersion modelling: a tool for local air quality management

A local air quality management system, and the use of dispersion modelling as a tool for the system, are described. The Turkish town of Gehze is used as a model.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Dispersion of volatile hydrocarbons in urban street canyons

Volatile hydrocarbons (VHCs) were monitored in two urban street canyons for 16 days. Measurements of 15 selected VHCs were performed simultaneously at three different sampling heights: at street level (2 m), at 8 m, and at the rooftop (25 m above the ground). The aim of the study was to investigate the factors responsible for the horizontal and vertical changes in VHC concentrations. Physical parameters controlling the concentration gradients (wind flow and speed) were enabled. It was concluded that dilution and dispersion decrease the concentrations of HCs emitted at street level by approximately a factor of 6 between rooftop and street levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured VHC concentrations gave an insight into their fate. An empirical relationship between CO and benzene was established. These results may have important implications in planning monitoring studies to support research on population exposure in urban areas.