A comparison of three highway line source dispersion models

This paper compares three idealized line source dispersion models that predict carbon monoxide concentrations near highways. The models are EPA HIWAY (Zimmerman, 1974), the original California Line Source (Beaton, 1972), and CALINE2 (Ward, 1975). The comparison includes a sensitivity analysis and model validation. A sensitivity analysis refers to an analysis of the dependence of normalized concentration to variations of several independent input parameters. Model validation is accomplished by comparing measured carbon monoxide concentrations with concentrations predicted by the models. The sensitivity analysis indicates that the EPA HIWAY model predicts higher pollutant concentrations than the two California models for oblique and crosswind cases. For parallel wind conditions, the California Line Source model predicts higher pollutant concentrations. A comparison of predicted and measured concentrations shows that all of the models overestimate concentrations for parallel wind conditions and underestimate concentrations for oblique and crosswind conditions.     

Algorithms and analytical solutions for rapidly approximating long-term dispersion from line and area sources

Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105–8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean dispersion are shown to produce results several orders of magnitude more efficiently with a loss of accuracy small compared to the absolute accuracy of advanced dispersion models near sources. The method can be readily incorporated into existing dispersion models, and may allow for additional computation time to be expended on modelling dispersion processes more accurately in future, rather than on accounting for source geometry.     

Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.     

Sensitivity analysis and evaluation of microFacCO: a microscale motor vehicle emission factor model for CO emissions

This paper presents a sensitivity analysis of a microscale emission factor model (MicroFacCO) for predicting real-time site-specific motor vehicle CO emissions to input variables, as well as a limited field study evaluation of the model. The sensitivity analysis has shown that MicroFacCO emission estimates are very sensitive to vehicle fleet composition, speed, and ambient temperature. For the present U.S. traffic fleet, the CO emission rate (g/mi) is increased by more than 500% at 5 mph in comparison with a speed greater than 40 mph and by approximately 67% at ambient temperatures of 45 degrees F and > or = 95 degrees F in comparison with an ambient temperature of 75 degrees F. The input variable "emission failure standard rate" is more sensitive to estimating emission rates in the 1990s than in the 2000s. The estimation of emission rates is not very sensitive to relative humidity. MicroFacCO can also be applied to examine the contribution of emission rates per vehicle class and model year. The model evaluation is presented for tunnel studies at five locations. In general, this evaluation study found good agreement between the measured and the modeled emissions. These analyses and evaluations have identified the need for additional studies to update the high-speed (>35 mph) air conditioning (A/C) correction factor and to add effects due to road grades. MicroFacCO emission estimates are very sensitive to the emission standard failure rate. Therefore, the model performance can be greatly improved by using a local emission standard failure rate.     

Sulfur dioxide dispersion and source contribution to receptors of downtown Patras, Greece

Background The development of the city of Patras, including harbour relocation, in conjunction with the protection of the regional ecosystems, requires air quality assessment and management. For this reason, a model applicable in the Patras area is necessary and valuable. The goal of this study was to validate a model suitable for predicting the dispersion of sulfur dioxide (SO₂), based on particular activity, topography and weather conditions. Methods We used the US-EPA ISCLT3 integral dispersion model to predict SO₂ concentrations for Patras, Greece. We assumed that the major contribution to Patras air pollution came from central heating, harbour and traffic. We calculated traffic emissions using COPERTIII. Results and Discussion Assigning suitable values of the mixing height, the model predicted the local and spatial distribution of the mean monthly SO₂ concentrations in downtown Patras, as well computed the contribution of the SO₂ emissions originating from each particular source at each receptor location on a seasonal and annual basis. The comparison between predictions and measurements shows that the model performance for estimating the SO₂ concentrations and period pattern is satisfactory. Conclusion The mixing height was the critical parameter for calibrating the model. Model validation promises satisfactory predictions for SO₂ pollution levels on monthly basis. Recommendations and Outlook The model could be used in predicting SO₂ concentrations and source contribution for several downtown Patras receptors using pertinent meteorological and emission information. It could be also extended to predict the dispersion of other primary air pollutants. The calibrated model predictions could be used to fill gaps in monitoring data, saving money and time, and help in assess and manage air quality as Patras develops.     

The long-range dispersion of a plume from an isolated point source

The dispersion of the plume from a sulphide smelter at Mount Isa, Australia, has been determined at distances of up to 1000 km from the source. Simultaneous measurements by an airborne correlation spectrometer, flame photometer and aitken counter have allowed accurate determinations of plume width at these large distances.Radiosonde and pilot-balloon data from four positions spanning the region have been used to calculate the trajectories of each of the plumes measured in the study. In each case the measured plume position was in good agreement with the position predicted on the basis of the wind data.A simple model based on the diurnal variation of the structure of the atmosphere, as well as the turning of the wind with height, is shown to account adequately for the measurements of plume width during well-mixed atmospheric conditions at distances of between 25 and 1000 km from the source.     

Sensitivity analysis and evaluation of MicroFacPM: a microscale motor vehicle emission factor model for particulate matter emissions

A microscale emission factor model (MicroFacPM) for predicting real-time site-specific motor vehicle particulate matter emissions was presented in the companion paper titled "Development of a Microscale Emission Factor Model for Particulate Matter (MicroFacPM) for Predicting Real-Time Motor Vehicle Emissions". The emission rates discussed are in mass per unit distance with the model providing estimates of fine particulate matter (PM2.5) and coarse particulate matter. This paper complements the companion paper by presenting a sensitivity analysis of the model to input variables and evaluation model outputs using data from limited field studies. The sensitivity analysis has shown that MicroFacPM emission estimates are very sensitive to vehicle fleet composition, speed, and the percentage of high-emitting vehicles. The vehicle fleet composition can affect fleet emission rates from 8 mg/mi to 1215 mg/mi; an increase of 5% in the smoking (high-emitting) current average U.S. light-duty vehicle fleet (compared with 0%) increased PM2.5 emission rates by -272% for 2000; and for the current U.S. fleet, PM2.5 emission rates are reduced by a factor of -0.64 for speeds >50 miles per hour (mph) relative to a speed of 10 mph. MicroFacPM can also be applied to examine the contribution of emission rates per vehicle class, model year, and sources of PM. The model evaluation is presented for the Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA, and some limited evaluations at two locations: Sepulveda Tunnel, Los Angeles, CA, and Van Nuys Tunnel, Van Nuys, CA. In general, the performance of MicroFacPM has shown very encouraging results.     

Minimizing the downwind concentration of pollutants from a line source by an appropriate choice of the shape of the line source

This paper considers the following problem. Suppose that:

• 1.(i) a motorway is to be constructed in the vicinity of a downwind point that is sensitive to the pollutants released by motor vehicles,
• 2.(ii) the motorway has to pass through two fixed points, and
• 3.(iii) permission is granted to build the motorway in the shape of a curve of prescribed length between the two fixed points.

Assuming that the motorway can be treated as a line source (i.e. the width of the motorway is small relative to the distance of the sensitive point), it is required to find the shape of the curve of the prescribed length such that the pollution concentration induced at the sensitive point will be a minimum, for a given source-strength density of the line source. The problem is solved by means of the variational calculus and by applying numerical techniques. As an example of the results we mention that, when the concentration-minimizing motorway is made 10% longer than the straight-line distance between the two fixed points, the concentration at the sensitive point is reduced by 20% compared to that induced by a straight-line motorway between the two fixed points, assuming the same line source-strength density.     

Nonpoint source pollution of urban stormwater runoff: a methodology for source analysis

The characterization and control of runoff pollution from nonpoint sources in urban areas are a major issue for the protection of aquatic environments. We propose a methodology to quantify the sources of pollutants in an urban catchment and to analyze the associated uncertainties. After describing the methodology, we illustrate it through an application to the sources of Cu, Pb, Zn, and polycyclic aromatic hydrocarbons (PAH) from a residential catchment (228 ha) in the Paris region. In this application, we suggest several procedures that can be applied for the analysis of other pollutants in different catchments, including an estimation of the total extent of roof accessories (gutters and downspouts, watertight joints and valleys) in a catchment. These accessories result as the major source of Pb and as an important source of Zn in the example catchment, while activity-related sources (traffic, heating) are dominant for Cu (brake pad wear) and PAH (tire wear, atmospheric deposition).     

Comparison of the industrial source complex and AERMOD dispersion models: case study for human health risk assessment

Air quality models are typically used to predict the fate and transport of air emissions from industrial sources to comply with federal and state regulatory requirements and environmental standards, as well as to determine pollution control requirements. For many years, the U.S. Environmental Protection Agency (EPA) widely used the Industrial Source Complex (ISC) model because of its broad applicability to multiple source types. Recently, EPA adopted a new rule that replaces ISC with AERMOD, a state-of-the-practice air dispersion model, in many air quality impact assessments. This study compared the two models as well as their enhanced versions that incorporate the Plume Rise Model Enhancements (PRIME) algorithm. PRIME takes into account the effects of building downwash on plume dispersion. The comparison used actual point, area, and volume sources located on two separate facilities in conjunction with site-specific terrain and meteorological data. The modeled maximum total period average ground-level air concentrations were used to calculate potential health effects for human receptors. The results show that the switch from ISC to AERMOD and the incorporation of the PRIME algorithm tend to generate lower concentration estimates at the point of maximum ground-level concentration. However, the magnitude of difference varies from insignificant to significant depending on the types of the sources and the site-specific conditions. The differences in human health effects, predicted using results from the two models, mirror the concentrations predicted by the models.     

An analytical model for the transport,dispersion and elimination of air pollutants emitted from a point source

The solution of the complete transport diffusion equation with a first order reaction term is obtained for a continuous source. A deposition velocity boundary condition is met at the ground and, optionally, a similar leakage velocity boundary condition can be met at the base of a superjacent layer. The identification of a preliminary transformation of the dependent variable that eliminates the transport and sink terms permits particularly simple analytic solutions to be obtained by means of conventional Laplace transform, Green's function methods. Prior solutions are compared with these results. A linearisation of the solution without an overlying layer provides a simple extension of the conventional Gaussian plume result that permits account to be taken of pollutant settling velocity, of absorption at the ground and of a first order reaction. The accuracy of this linearisation is assessed. Examples of the application of the methods to calculation of the distribution of particulates and of the formation of nitrogen dioxide in a plume are given.     

Turbulent diffusion modelling FQR wind flow and dispersion analysis

Within the framework of searching for relatively simple, reliable and universal eddy viscosity /diffusivity models, a new three dimensional general non-isotropic model is proposed applicable to any domain complexity and any atmospheric stability conditions. The model utilizes the transport equation for turbulent kinetic energy but introduces a new approach in effective length scale estimation based on the flow global characteristics and local atmospheric stability. The model is discussed in detail and predictions are given for flow field and boundary layer thickness. The results are compared with experimental data with satisfactory results.     

Simulating industrial emissions using atmospheric dispersion modeling system: model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp/Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOx, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.     

Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source

As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.     

A scintillation spectrometer with coincidence counting for aerosol analysis and source attribution

A single particle counter analyzer is described comprising a sodium scintillation detector, potassium scintillation detector and flame ionization detector grouped about a hydrogen-air flame as excitation source. A microprocessor controlled data-logger counts and classifies the particles on the basis of coincident signals from several detectors. Populations of particles of sea salt, soil dust and particles from vegetative-burning yield discrete signatures. The development of the method of using element-specific-detectors and coincidence counting at the single particle level as a method of aerosol source attribution is illustrated for samples of urban aerosols.     

Measurement and analysis of non-Fickian dispersion in heterogeneous porous media

Contaminant breakthrough behavior in a variety of heterogeneous porous media was measured in laboratory experiments, and evaluated in terms of both the classical advection-dispersion equation (ADE) and the continuous time random walk (CTRW) framework. Heterogeneity can give rise to non-Fickian transport patterns, which are distinguished by "anomalous" early arrival and late time tails in breakthrough curves. Experiments were conducted in two mid-scale laboratory flow cells packed with clean, sieved sand of specified grain sizes. Three sets of experiments were performed, using a "homogeneous" packing, a randomly heterogeneous packing using sand of two grain sizes, and an exponentially correlated structure using sand of three grain sizes. Concentrations of sodium chloride tracer were monitored at the inflow reservoir and measured at the outflow reservoir. Breakthrough curves were then analyzed by comparison to fitted solutions from the ADE and CTRW formulations. In all three systems, including the "homogeneous" one, subtle yet measurable differences between Fickian and non-Fickian transport were observed. Quantitative analysis demonstrated that the CTRW theory characterized the full shape of the breakthrough curves far more effectively than the ADE.     

Measurement of the dispersion of a smoke plume at large distances from the source

The width of a smoke plume from an isolated ore smelter in the tropics has been found from airborne measurements of total particle concentrations at distances up to 560 km from the source under cloudless, inversion-limited, convective conditions over flat terrain. Results are surprisingly similar to estimates derived from the few available relevant experiments, most of which were conducted in different meteorological circumstances and using quite different techniques.