John S. Irwin

Estimating Plume Dispersion-A Comparison of Several Sigma Schemes

Abstract The lateral and vertical Gaussian plume dispersion parameters are estimated and compared with fieldtracer data collected at II sites. The dispersion parameter schemes used in this analysis include Cramersscheme, suggested for tall stack dispersion estimates, Draxiers scheme, suggested for elevated and surfacereleases, Pasquills scheme, suggested for interim use in dispersion estimates, and the Pasquill-Gifford schemeusing Turners technique for assigning stability categories. The schemes suggested by Cramer, Draxler andPasquil estimate the dispersion parameters using onsite measurements of the vertical and lateral windvelocity variances at the effective release height. The performances of these schemes in estimating the dispersion parameters are compared with that of the Pasquill-GitFord scheme, using the Prairie Grass andKarlsruhe data. For these two experiments, the estimates of the dispersion parameters using Draxiers schemecorrelate better with the measurements than did estimates using th...

Statistical evaluation of centreline concentration estimates by atmospheric dispersion models

Within the American Society for Testing and Materials (ASTM), a standard practice (Z6849Z1) is being developed to provide an objective statistical procedure for comparing air quality simulation modelling results with tracer field data. The practice is limited to steady state, local-scale transport from isolated point sources in simple terrain. Evaluation data having similar external conditions are grouped together, and comparisons are made of the models ability to replicate without bias the average of the centreline maximum concentrations for each group. Centreline concentrations measured during three field studies are compared with estimates from three steady-state plume models: Industrial Source Complex (ISC), Hybrid Plume Dispersion Model (HPDM) and AMS/EPA Regulatory Model (AERMOD). These results, combined with those presented in Irwin and Rosu (1998), provide a complete examination of the draft ASTM standard practice under development. It is concluded that the evaluation methodology is capable of objectively discerning differences in skill between models in their ability to estimate the centreline maximum concentration.

Application of ASTM D6589 to evaluate dispersion model performance

During the development phase of an air quality dispersion model and in subsequent upgrades, model performance is constantly evaluated. These evaluations generally compare simulation results using simple methods that do not account for the fact that models only predict a portion of the variability seen in the observations. To fill a part of this void, the US Environmental Protection Agency (EPA) developed a standard that has been adopted by the American Society for Testing and Materials (ASTM), designation D6589 Standard Guide for the Statistical Evaluation of Atmospheric Dispersion Model Performance. Within the annex to this standard is an example test method that tests the ability of dispersion models to simulate the average centreline concentration. The method involves grouping observed data into groups or regimes, in which the dispersion is expected to be somewhat similar. The average centreline concentration is then derived for each group using bootstrap resampling. It is this average centreline concentration that is then compared with the modelling results. By this means, the focus is on testing the ability of models to replicate the first moment (the average) of the centreline concentration distribution, which for most operational models is the only feature in the centreline concentration distribution they are capable of simulating. This paper will focus on recent work to further test the ASTM example test method. This work involved the application of the test method to the results from ADMS (version 3.1), AERMOD (versions 98022 and 02161), HPDM (version 4.3, level 920605) and ISCST3 (version 00101). Three atmospheric dispersion field studies are analysed - Prairie Grass (in 1956, rural, low level release), Kincaid (1980, rural, elevated release) and Indianapolis (1985, urban, elevated release).

Improvements to the EPA Industrial Source Complex Dispersion Model

Air quality models are a key component in determining air pollution control requirements. The Industrial Source Complex (ISC2) model is a steady-state Gaussian plume model that is used for modeling point, area, volume, and line sources. Since its development in the 1970s by the U.S. Environmental Protection Agency, this widely used model has undergone several updates as state-of-the-science techniques have become available. Some of the recent modifications to the ISC2 model include a numerically efficient area-source algorithm tested in wind tunnel experiments, a dry-deposition algorithm that can account for a full range of particle size distributions, an algorithm for calculating wet-deposition flux using the scavenging coefficient approach, and an algorithm for modeling open-pit sources. These modifications, which are part of the current ISCST3 model, are described in detail within this paper. In addition, a plume depletion model demonstration was performed to compare observed and estimated crosswind integrated concentrations of a depositing tracer as functions of travel time and stability.

Characterising uncertainty in plume dispersion models

For management decisions related to effects of releases of toxic chemicals, it is useful to consider not only the expected or most likely impact of the release, but also the envelope of possible outcomes, the latter of which involves an assessment of the uncertainty in the modelling results. In this paper, we provide quantitative estimates of major sources of uncertainty in plume dispersion modelling and then provide a preliminary assessment of their effects. The sources of uncertainty investigated are wind speed and direction, plume rise, dispersion parameters, and stochastic effects not simulated by dispersion models.

Improving Concentration Measures Used for Evaluating Air Quality Models

An unfortunate difficulty in model evaluation is that the concentration measure that most models predict, namely the ensemble mean concentration under the plume centerline (or at some location relative to the plume centerline), cannot be measured directly. The problem can be ameliorated by judicious selection of a concentration measure against which to compare model predictions. Insufficient attention has been given in the past to the selection of an appropriate measure for use in air quality model evaluation studies, which may have resulted in biases in the results of those studies. Some studies have used the maximum concentrations along the arc (arc maximum) as the measure of choice. In this paper, the authors have considered two additional candidate measures, the fitted maximum concentrations and the near-centerline concentrations, which, intuitively, relate more closely to the ensemble mean concentrations. This study shows that the maximum concentrations along the arc are significantly higher than either the fitted maxima or the near-centerline concentrations. In addition, of the latter two measures, the authors conclude that use of the near-centerline concentration is preferable to the use of fitted maximum for the purposes of evaluating model performance.

A Review of Procedures for Updating Air Quality Modeling Techniques for Regulatory Programs

Abstract Air quality models are a key component in determining pollution control requirements. To ensure that the best techniques are used, modeling guidance must be flexible and include better techniques as they become available. Revisions to modeling guidance require an assessment of the scientific basis, a model performance evaluation using observed data, sensitivity analysis for impact on design concentrations and data input requirements, and public review and comment before formal adoption in regulatory programs. The procedures used in reviewing new techniques are examined in this paper, and past actions are discussed. The appropriateness of adopting a new method for modeling area sources characterized by low-level releases with little buoyancy is provided as an example of the revision review process. While this process is lengthy, it ensures that decisions on potentially costly pollution controls are based on full public participation and sound scientific developments.

Comparison of Two Sampling Procedures for the Statistical Evaluation of the Performance of Atmospheric Dispersion Models in Estimating Centerline Concentration Values

Based on tests using sampling results from three tracer field studies of dispersion, it was ascertained that the criteria for selection of observed centerline concentration values needed to be restricted to the one to three values that are nearest to the computed center of mass and are within ±0.67σy. The redesigned bootstrap sampling provides sample averages of observed and modeled centerline concentration values from each group on each pass of the bootstrap sampling. This allows computation of any number of standard statistics for comparison measures, with the added benefit of being able to test whether differences seen are statistically significant. The redesigned bootstrap sampling procedure was tested using modeling results from three models for three tracer field studies. The NMSE statistic is seen to provide a robust assessment of which model’s values are nearest on average to that observed, and it is seen that other comparison measures are in reasonable accord with the conclusions one might reach based on the NMSE.

Summary of the 19-Th NATO/CCMS International Technical Meeting (ITM) Round Table Discussion on the Harmonization of Atmospheric Dispersion Models

Research groups have recognized a need for devising a means for sharing of information of new approaches to atmospheric dispersion modeling and model evaluation. Responding to this need, a meeting was convened on June 13, 1991 by the Institute of Prospective Technical Studies at the Joint Research Centre (JRC) at Ispra, Italy. Following a brief review of current developments and practices in dispersion modeling and a discussion of views on harmonization, it was agreed by the participants of the meeting that a ‘Round Table’ discussion followed by a series of workshops would foster the desired sharing of information and provide a basis for developing an approach towards harmonization. The Round Table discussion was held on October 2, 1991 at the 19-th NATO/CCMS Conference on Atmospheric Dispersion. Approximately 50 scientists involved with various aspects of air quality assessment from over 15 countries participated in the Round Table discussion.