Lagrangian Dispersion Modeling of Vehicular Emissions from a Highway in Complex Terrain

Abstract

Transit traffic through the Austrian Alps is of major concern in government policy. Pollutant burdens resulting from such traffic are discussed widely in Austrian politics and have already led to measures to restrict traffic on transit routes. In the course of an environmental assessment study, comprehensive measurements were performed. These included air quality observations using passive samplers, a differential optical absorption spectroscopy system, a mobile and a fixed air quality monitoring station, and meteorological observations. As was evident from several previous studies, dispersion modeling in such areas of complex terrain and, moreover, with frequent calm wind conditions, is difficult to handle. Further, in the case presented here, different pollutant sources had to be treated simultaneously (e.g., road networks, exhaust chimneys from road tunnels, and road tunnel portals). No appropriate system for modeling all these factors has so far appeared in the literature. A prognostic wind field model coupled with a Lagrangian dispersion model is thus presented here and is designed to treat all these factors. A comparison of the modeling system with results from passive samplers and from a fixed air quality monitoring station proved the ability of the model to provide reasonable figures for concentration distributions along the A10.     

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.     

Evaluation of Downwash Modifications to the Industrial Source Complex Model

The Industrial Source Complex (ISC) model has been modified to account for Improved understanding of plume rise and downwash around buildings. Two sets of observations are used to compare the modified and the original ISC models, showing that the new model better simulates the observed concentrations during high-wind conditions when downwash usually occurs.     

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.     

KAPPA-G,A Non-Gaussian Plume Dispersion Model: Description and Evaluation Against Tracer Measurements

This paper presents a mixed methodology for the simulation of atmospheric disperson phenomena in which vertical diffusion is computed using an analytical solution of the K-theory equation, while horizontal diffusion is simulated by the Gaussian formula. This new formulation, while maintaining a simple analytical form for the concentration field, incorporates the effects of power-law vertical profiles of both wind speed and eddy diffusivity. The performance of this approach, which has been implemented into a full computer package (KAPPA-G), is evaluated by comparison with data from SF₆ tracer experiments.     

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.     

Dispersion climatology in a coastal zone

A crosswind integrated K-model with wind- and K-profiles described by Monin-Obukhov similarity expressions is solved for a continuous surface release to yield the vertical spread of the plume as a function of the surface roughness z₀ and the Monin-Obukhov length L for a given downwind distance. The vertical spread of the plume is translated into σ_z, and lines were traced in a (z₀, L⁻) plane for which the σ_z of the K-model matched the corresponding σ_z of Pasquill's system. By this technique a new classification scheme is constructed. Knowing z₀ and L, the scheme tells which σ_z curve in the Pasquill system should be used to describe the dispersion.This dispersion classification scheme is used to organize 3 years of data from two meteorological masts, one placed directly at a shoreline and the other roughly 1 km inland. Differences in the dispersion climatology over land and water are studied by averaging the data selectively. The large differences for water and land surfaces between the seasonal and diurnal variation of the dispersion class distributions are illustrated. It is found that the water surface influences the dispersion climatology as far as 20 km inland.     

Estimation of Pollutant Transport and Concentration Distributions over Complex Terrain of Southern California Using Airborne Lidar

Airborne lidar data collected during the South Coast Air Basin/Southeast Desert Oxidant Transport Study in summer 1981 were used to provide estimates of concentration distributions of particles and oxidants, and of pollutant transport in mountain passes and over mountain slopes. The results support the idea that for certain situations, given a few representative in situ measurements for use in calibration, airborne lidar might be used to develop detailed concentration fields. When combined with appropriate measurements of wind speed profiles with height, useful estimates of pollutant transport flux might also be provided.     

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.     

Development,Evaluation, and Application of a Primary Aerosol Model

ABSTRACT

The Segmented-Plume Primary Aerosol Model (SPPAM) has been developed over the past several years. The earlier model development goals were simply to generalize the widely used Industrial Source Complex Short-Term (ISCST) model to simulate plume transport and dispersion under light wind conditions and to handle a large number of roadway or line sources. The goals have been expanded to include development of improved algorithm for effective plume transport velocity, more accurate and efficient line and area source dispersion algorithms, and recently, a more realistic and computationally efficient algorithm for plume depletion due to particle dry deposition. A performance evaluation of the SPPAM has been carried out using the 1983 PNL dual tracer experimental data. The results show the model predictions to be in good agreement with observations in both plume advection-dispersion and particulate matter (PM) depletion by dry deposition. For PM_2.5 impact analysis, the SPPAM has been applied to the Rubidoux area of California. Emission sources included in the modeling analysis are: paved road dust, diesel vehicular exhaust, gasoline vehicular exhaust, and tire wear particles from a large number of roadways in Rubidoux and surrounding areas. For the selected modeling periods, the predicted primary PM_2.5 to primary PM10 concentration ratios for the Rubidoux sampling station are in the range of 0.39–0.46. The organic fractions of the primary PM_2.5 impacts are estimated to be at least 34–41%. Detailed modeling results indicate that the relatively high organic fractions are primarily due to the proximity of heavily traveled roadways north of the sampling station. The predictions are influenced by a number of factors; principal among them are the receptor locations relative to major roadways, the volume and composition of traffic on these roadways, and the prevailing meteorological conditions.     

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.