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Robert Paine and Carl Berkowitz
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Robert J. Paine

The tenth in a continuing series of joint conferences between the American Meteorological Society and the Air and Waste Management Association on meteorological aspects of air pollution was held 11–16 January 1998 in Phoenix, Arizona. Diverse topics in air dispersion modeling, boundary layer meteorology, cloud physics, atmospheric chemistry, fluid mechanics, and engineering were presented at the conference. A summary of the presentations made at the conference is provided.

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Frederick Sanders and Robert J. Paine

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On 14 May 1970 a cold front passed through the mesonetwork of the National Severe Storms Laboratory in central Oklahoma. As it did so, intense convection developed and thunderstorms produced more than 2 inches of rain at some points within the network. On this date a total of 58 rawinsonde observations were made at nine stations within the network, 42 of them during the period from about 1 h prior to frontal passage to 2 h afterward.

We have analyzed these as well as other data to arrive at a picture of the structure of the mesoscale system and of the thermodynamical processes operating in it. The front first encountered potentially unstable rnoist air as it passed through the network. As this air was lifted frontally the instability was released, with remarkable results. A mesoscale downdraft–updraft doublet developed in the warm air aloft, with peak speeds at 400 mb of 2–3 m sminus;1 over 10 km widths transverse to the front, the descent being above the surface frontal position and the ascent (which produced almost all the precipitation) being about 30 km toward the colder air to the northwest.

The downdraft appears to he driven by intense cooling due to evaporation of the initial deep cumulus clouds into the very dry air aloft. The updraft is due to condensational heating on the mesoscale, in saturated air of nearly neutral stability, with convective activity superimposed. We conjecture that these diabatic effects permit the Mesoscale vertical motions to proceed for several hours without large perturbation of the isentropic surfaces. The character of the convection, and of the mesoscale circulation, is not accounted for by a simple model of an entraining convective plume.

We present evidence that the balloons tended on the average to be drawn into the convective–scale updrafts and to avoid the downdrafts, thus yielding spurious indications of the percentage of volume occupied by active convective updrafts and downdrafts. We find, on the other hand, that deviations of balloon ascent rate and equivalent–potential temperature of individual soundings from the means of their neighbors can be used to estimate convective transports. The virtual source of equivalent potential temperature, thus determined, is in reasonable agreement with the apparent source independently obtained as a residual in the mesoscale budget.

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Steven R. Hanna and Robert J. Paine

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The Hybrid Plume Dispersion Model (HPDM) was developed for application to tall stack plumes dispersing over nearly flat terrain. Emphasis is on convective and high-wind conditions. The meteorological component is based on observational and modeling studies of the planetary boundary layer. The dispersion estimates for the convective boundary layer (CBL) were developed from laboratory experiments and field studies and incorporate convective scaling, i.e., the convective velocity scale, w *, and the CBL height, h, which are the relevant velocity and length scales of the turbulence. The model has a separate component to handle the dispersion of highly buoyant plumes that remain near the top of the CBL and resist downward mixing. For convective conditions, the vertical concentration distribution is non-Gaussian, but for neutral and stable conditions it is assumed to be Gaussian. The HPDM performance is assessed with extensive ground-level concentration measurements around the Kincaid, Illinois, and Bull Run, Tennessee, power plants. It was also tested with limited data during high-wind conditions at five other power plants. The model is found to be an improvement over the standard regulatory model, MPTER, during light-wind convective conditions and high-wind neutral conditions.

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Steven R. Hanna, Robert Paine, David Heinold, Elizabeth Kintigh, and Dan Baker

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The uncertainties in simulations of annually averaged concentrations of two air toxics (benzene and 1,3-butadiene) are estimated for two widely used U.S. air quality models, the Industrial Source Complex Short-Term, version 3, (ISCST3) model and the American Meteorological Society–Environmental Protection Agency Model (AERMOD). The effects of uncertainties in emissions input, meteorological input, and dispersion model parameters are investigated using Monte Carlo probabilistic uncertainty methods, which involve simultaneous random and independent perturbations of all inputs. The focus is on a 15 km × 15 km domain in the Houston, Texas, ship channel area. Concentrations are calculated at hypothetical receptors located at the centroids of population census tracts. The model outputs that are analyzed are the maximum annually averaged maximum concentration at any single census tract or monitor as well as the annually averaged concentration averaged over the census tracts. The input emissions uncertainties are estimated to be about a factor of 3 (i.e., covering the 95% range) for each of several major categories. The uncertainties in meteorological inputs (such as wind speed) and dispersion model parameters (such as the vertical dispersion coefficient σz) also are estimated. The results show that the 95% range in predicted annually averaged concentrations is about a factor of 2–3 for the air toxics, with little variation by model. The input variables whose variations have the strongest effect on the predicted concentrations are on-road mobile sources and some industrial sources (dependent on chemical), as well as wind speed, surface roughness, and σz. In most scenarios, the uncertainties of the emissions input group contribute more to the total uncertainty than do the uncertainties of the meteorological/dispersion input group.

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Alan J. Cimorelli, Steven G. Perry, Akula Venkatram, Jeffrey C. Weil, Robert J. Paine, Robert B. Wilson, Russell F. Lee, Warren D. Peters, and Roger W. Brode

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. Complex terrain influences are provided by combining a horizontal plume state and a terrain-following state. Dispersion algorithms are specified for convective and stable conditions, urban and rural areas, and in the influence of buildings and other structures. Part II goes on to describe the performance of AERMOD against 17 field study databases.

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Steven G. Perry, Alan J. Cimorelli, Robert J. Paine, Roger W. Brode, Jeffrey C. Weil, Akula Venkatram, Robert B. Wilson, Russell F. Lee, and Warren D. Peters

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 first describing the model formulations.

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