Akula Venkatram

AERMOD: A Dispersion Model for Industrial Source Applications. Part I: General Model Formulation and Boundary Layer Characterization

Abstract The formulation of the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) Improvement Committee’s applied air dispersion model is described. This is the first of two articles describing the model and its performance. Part I includes AERMOD’s characterization of the boundary layer with computation of the Monin–Obukhov length, surface friction velocity, surface roughness length, sensible heat flux, convective scaling velocity, and both the shear- and convection-driven mixing heights. These parameters are used in conjunction with meteorological measurements to characterize the vertical structure of the wind, temperature, and turbulence. AERMOD’s method for considering both the vertical inhomogeneity of the meteorological characteristics and the influence of terrain are explained. The model’s concentration estimates are based on a steady-state plume approach with significant improvements over commonly applied regulatory dispersion models. Co...

AERMOD: A Dispersion Model for Industrial Source Applications. Part II: Model Performance against 17 Field Study Databases

Abstract The performance of the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) Improvement Committee’s applied air dispersion model against 17 field study databases is described. AERMOD is a steady-state plume model with significant improvements over commonly applied regulatory models. The databases are characterized, and the performance measures are described. Emphasis is placed on statistics that demonstrate the model’s abilities to reproduce the upper end of the concentration distribution. This is most important for applied regulatory modeling. The field measurements are characterized by flat and complex terrain, urban and rural conditions, and elevated and surface releases with and without building wake effects. As is indicated by comparisons of modeled and observed concentration distributions, with few exceptions AERMOD’s performance is superior to that of the other applied models tested. This is the second of two articles, with the firs...

Estimating the Monin-Obukhov length in the stable boundary layer for dispersion calculations

Analysis of data collected during the Prairie Grass, Kansas and Minnesota experiments reveals the following empirical relationship between the Monin-Obukhov length L and the friction velocity u*: L = Au*2, A = 1.1 × 103s2m-1. This result combined with the formulation for the height of the stable boundary layer h suggested by Zilitinkevich (1972) leads to h ∫ u*3/2f−1/2 where f is the Coriolis parameter. Data from the Minnesota study (Caughey et al., 1979) provide ample support for this expression.These empirical equations for L and h are useful for routine dispersion estimates during stable conditions.

Evaluating Air-Quality Models: Review and Outlook

Abstract Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (σc about the mean concentration (C) over an ensemble—a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For σc∼C large residuals exist between predicted and observed concentrations, which confuse model evaluations. This paper addresses ways of evaluating model physics in light of the large σc the focus is on elevated point-source models. Evaluation of model physics requires the separation of the ...

The electrical analogy does not apply to modeling dry deposition of particles

Abstract The most commonly used expresion for dry deposition of particles is based on the electrical analogy. Because the electrical analogy is not consistent with the mass conservation equation, this expression for dry deposition velocity cannot be justified. This paper presents the correct expression.

The development and application of a simplified ozone modeling system (SOMS)

Abstract This paper describes the development and evaluation of a computationally efficient semi-empirical photochemical model that can be used as a screening tool to obtain quick estimates of the effect of a large number of VOC and NO x emission control strategies on ozone concentrations. Selected control strategies can subsequently be examined with a more complex model. The model is one component of an ozone management system, the regional ozone decision model (RODM), designed to examine the costs and environmental consequences of alternate ozone abatement strategies. The model was developed by systematic simplification of a detailed photochemical model. At each step of the simplification, the simplified model was tested against observations and against results from the detailed model. The first major simplification was the introduction of a highly parameterized chemistry mechanism, originally developed by Azzi et al. (1992 Proc. 11th Int. Clean Air Conf., 4th Regional IUAPPA Conf. ). This modification resulted in a factor of 5 improvement in the computational efficiency of the model. The model with the simplified chemistry was then tested by applying it to a photochemical oxidant episode in the San Joaquin Valley of California. Further improvements in computational speed and efficiency were obtained by uncoupling the chemistry from the transport of VOC and NO x .

A critique of empirical emission factor models : a case study of the AP-42 model for estimating PM10 emissions from paved roads

This paper provides a critical examination of empirical emission factor models by considering one model that typifies the class: the model used to estimate PM10 emissions from paved roads. We show that the model can yield highly uncertain emission estimates because (1) it lacks a mechanistic basis, (2) its formulation is highly dependent on the data set used to derive it, and (3) the accuracy of the model is completely determined by the methods used to measure emissions. The paper also describes a method to relate model performance statistics to statements about the uncertainty in emission estimates.

On the use of kriging in the spatial analysis of acid precipitation data

Abstract This paper examines a technique known as simple Kriging that is becoming popular in the spatial analysis of data pertinent to acid rain. In the first part of the paper, we provide a detailed derivation of the relevant equations in order to clarify the assumptions that underlie the technique. A major assumption is that a given set of observations can be represented as the sum of a constant mean and a stochastic fluctuation, which is governed by an isotropic and homogeneous spatial autocorrelation function. Because this assumption cannot be justified in the context of precipitation chemistry data that reflect inhomogeneous processes, we suggest a technique that combines deterministic modeling with the attractive features of Kriging. We demonstrate this technique by applying it to a data set consisting of annual averages of wet deposition of S. We also show that this simple spatial analysis method is a substantial improvement on simple Kriging.

A complex terrain dispersion model for regulatory applications

Abstract This paper demonstrates the development of a model designed to estimate concentrations associated with a source situated in complex terrain. The model is designed to provide estimates of concentration distributions and is thus primarily suitable for regulatory applications. The model assumes that the concentration at a receptor is a combination of concentrations caused by two asymptotic states: the plume remains horizontal, and the plume climbs over the hill. The factor that weights the two states is a function of the fractional mass of the plume above the dividing streamline height. The model has been evaluated against data from four complex terrain sites. The evaluation shows that the model performs at least as well as CTDMPLUS (Perry, S.G., 1992. CTDMPLUS, a dispersion model for sources near complex topography. Part I: technical formations. Journal of Applied Meteorology 31, 633–645), a more comprehensive model designed for complex terrain applications.

Vertical dispersion of ground-level releases in the surface boundary layer

By assuming that the eddy diffusivity of mass is proportional to that of heat, this paper derives simple expressions for the asymptotic behavior of cross-wind integrated ground-level concentrations under neutral, stable, and unstable conditions. We show that: • C∗y ∼ x∗−1 under neutral conditions; • ∼ x∗−13 under stable conditions; • ∼ x∗−2 under unstable conditions; where C∗y = Cyu∗ |L|Q and x∗ = x/|L|, and Cy is the cross-wind integrated concentration, u∗ is the surface friction velocity, L is the Monin-Obukhov length, and Q is the pollutant release rate. We show that simple interpolations between the asymptotic limits provide excellent fits to the Prairie Grass (Barad, 1958, Paper No. 59, Geophysics Research Directorate, MA) diffusion data. Our analysis of surface dispersion in unstable conditions indicates that the concentration decrease with distance is not consistent with that predicted by free convection theory (Yaglom, 1972, Atmos. Ocean Phys.8, 333–340). Under asymptotically unstable conditions, the concentration falls off as x−2 rather than as x−32 predicted by the theory.