Development and evaluation of the PRIME plume rise and building downwash model

A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations. The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.     

Development and Evaluation of the PRIME Plume Rise and Building Downwash Model

ABSTRACT

A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations.

The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.     

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.     

A review of the conditions leading to downwash in physical modeling experiments

Although stack downwash is not a widespread problem at modern fossil-fuel power plants and larger industrial stacks, it is a very important problem in simulating buoyant plumes in wind tunnels and towing tanks. Scaling criteria for avoiding downwash in ten subcritical model experiments have been reviewed. A comparison was made between data on the occurrence of downwash from 10 modeling studies to the theory proposed by Tatom (1986). In general, there was good agreement of Tatom's theory with the occurrence of downwash.     

Maximum Ground-Level Concentrations with Downwash

Equations are derived from the Gaussian plume mode! and prescribe the critical downwind distance, wind speed, and plume rise values that result in maximum ground-level concentrations (MGLC) under downwash conditions. The derivations apply to bent-over plumes and encompass the Schulman-Scire and Huber-Snyder building downwash treatments.     

Critical review of the building downwash algorithms in AERMOD

The only documentation on the building downwash algorithm in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), referred to as PRIME (Plume Rise Model Enhancements), is found in the 2000 A&WMA journal article by Schulman, Strimaitis and Scire. Recent field and wind tunnel studies have shown that AERMOD can overpredict concentrations by factors of 2 to 8 for certain building configurations. While a wind tunnel equivalent building dimension study (EBD) can be conducted to approximately correct the overprediction bias, past field and wind tunnel studies indicate that there are notable flaws in the PRIME building downwash theory. A detailed review of the theory supported by CFD (Computational Fluid Dynamics) and wind tunnel simulations of flow over simple rectangular buildings revealed the following serious theoretical flaws: enhanced turbulence in the building wake starting at the wrong longitudinal location; constant enhanced turbulence extending up to the wake height; constant initial enhanced turbulence in the building wake (does not vary with roughness or stability); discontinuities in the streamline calculations; and no method to account for streamlined or porous structures.

Implications: This paper documents theoretical and other problems in PRIME along with CFD simulations and wind tunnel observations that support these findings. Although AERMOD/PRIME may provide accurate and unbiased estimates (within a factor of 2) for some building configurations, a major review and update is needed so that accurate estimates can be obtained for other building configurations where significant overpredictions or underpredictions are common due to downwash effects. This will ensure that regulatory evaluations subject to dispersion modeling requirements can be based on an accurate model. Thus, it is imperative that the downwash theory in PRIME is corrected to improve model performance and ensure that the model better represents reality.     

Pseudo-source parameters for flares: Derivation,implementation, and comparison

The United States Environmental Protection Agency (US EPA) flare pseudo-source parameters are over 30 years old and few dispersion modellers understand their basis and underlying assumptions. The calculation of plume rise from the user inputs of pseudo-stack diameter, temperature and velocity have the most influence on air dispersion model predictions of ground-level concentrations. Regulatory jurisdictions across Canada, the United States and around the world have adopted their own approach to pseudo-source parameters for flares; all relate buoyancy flux to the heat release rate, none consider momentum flux and flare tip downwash as adopted by the Alberta Energy Regulator (AER). This paper derives the plume buoyancy flux for flares burning a gas in terms of combustion variables readily known or calculated without simplifying assumptions. Dispersion model prediction sensitivity to flared gas composition, temperature and velocity, and ambient conditions are now correctly handled by the AER approach. The AER flare pseudo-source parameters are based on both the buoyancy and momentum flux, thus conserving energy and momentum. The AER approach to calculate the effective source height for flares during varying wind speeds is compared to the US EPA approach. Instead of a constant source for all meteorological conditions, multiple co-located sources with varying effective stack height and diameter are used. AERMOD is run with the no stack tip downwash option as flare stack tip downwash is accounted for in the effective stack height rather than the AERMOD model calculating the downwash incorrectly using the pseudo-source parameters. The modelling approaches are compared for an example flare. Maximum ground level predictions change, generally increasing near the source and decreasing further away, with the AER flare pseudo-source parameters. It's time to update how we model flares.

Implications: What are the implications of continuing to model flare source parameters using the overly simplified US EPA approach? First, the regulators perpetuate the myths that the flare source height, temperature, diameter and velocity are constant for all wind speeds and ambient temperatures. Second, that it is acceptable to make simplifying assumptions that violate the conservation of momentum and energy principles for the sake of convenience. Finally, regulatory decisions based on simplified source modelling result in predictions that are not conservative (or realistic). The AER regulatory approach for flare source parameters overcomes all of these shortcomings. AERflare is a publicly available spreadsheet that provides the “correct” inputs to AERMOD.     

Development of a low-rise industrial source dispersion model

In Japan, with amendment of the Air Pollution Control Law in May 1996, various substances, including benzene and trichloroethylene, were newly designated as hazardous air pollutants, and environmental standards were established. In this situation, it is necessary to develop a dispersion model that is applicable to environmental impact assessment of industrial areas with a complex of factory buildings. To overcome this problem, modification of the ISC downdraught model was undertaken based on datasets from wind tunnel experiments by the Ministry of International Trade and Industries and Japan Environmental Management Association for Industry. This new model is called the METI-LIS model, and comparison shows that the performance of the model is better than that of the original ISC model.     

Maximum Ground-Level Concentrations with Downwash: The Urban Stability Mode

Abstract

Gaussian model-based equations for critical downwind distance, wind speed, and plume height that result in maximum ground-level concentrations (MGLC) under downwash conditions for the rural stability mode were presented in a previous paper. This paper presents general equations for the critical downwind distance xc for the urban stability mode. Specific examples are presented for Schulman-Scire and Huber-Snyder downwash treatments for building-enhanced and regular sigmas.     

An advanced integral model for cooling tower plume dispersion

An advanced integral model is developed for predicting cooling tower plume rise from single natural draft cooling towers. The theoretical formulation of the model is aimed at avoiding many of the pitfalls and unnecessary assumptions of existing models. The model is based on a careful integration of the three-dimensional partial differential equations of conservation across the plume cross-section; radial profiles of temperature, velocity, and total water are assumed to be Gaussian in shape. The model includes a treatment of plume thermodynamics and tower downwash effects. The model has been calibrated with a wide range of laboratory data. Verification of the model with single-tower field data from Chalk Point, Paradise, Lünen, Gardanne and Philippsburg reveals good results.     

Maximum ground-level concentrations with downwash--analysis

Equations derived previously for critical downwind distance xc' wind speed uc' and plume rise zc' the values that produce maximum ground-level concentrations (MGLC) chi c under downwash conditions, have been solved. Tables of chi c' xc' uc' and zc' and graphs of the relationships among uc and zc, for a range of stack heights hs' and building heights hb' are presented. Results for two types of sources--a turbine and a reciprocating engine--are discussed. Some comparisons are made to the U.S. Environmental Protection Agency's (EPA) SCREEN3 model.     

Modeling Emissions from Elevated Cylindrical Bins

Abstract

This paper demonstrates how wind tunnel modeling data that accurately describe plume characteristics near an unconventional emission source can be used to improve the near-field downwind plume profiles predicted by conventional air pollution dispersion models. The study considers a vertical, cylindrical-shaped, elevated bin similar to large product storage bins that can be found at many industrial plant sites. Two dispersion models are considered: the U.S. Environmental Protection Agency's ISC2(ST) model and the Ontario Ministry of the Environment and Energy's GAS model. The wind tunnel study showed that plume behavior was contrary to what was predicted using conventional dispersion models such as ISC2(ST) and GAS and default values of input parameters. The wind tunnel data were used to develop a protocol for correcting the dispersion models inputs, resulting in a substantial improvement in the accuracy of the dispersion estimates.     

Flow and contaminant transport in an airliner cabin induced by a moving body: Model experiments and CFD predictions

The effects of a moving human body on flow and contaminant transport inside an aircraft cabin were investigated. Experiments were performed in a one-tenth scale, water-based model. The flow field and contaminant transport were measured using the Particle Image Velocimetry (PIV) and Planar Laser-Induced Fluorescence (PLIF) techniques, respectively. Measurements were obtained with (ventilation case) and without (baseline case) the cabin environmental control system (ECS). The PIV measurements show strong intermittency in the instantaneous near-wake flow. A symmetric downwash flow was observed along the vertical centerline of the moving body in the baseline case. The evolution of this flow pattern is profoundly perturbed by the flow from the ECS. Furthermore, a contaminant originating from the moving body is observed to convect to higher vertical locations in the presence of ventilation. These experimental data were used to validate a Computational Fluid Dynamic (CFD) model. The CFD model can effectively capture the characteristic flow features and contaminant transport observed in the small-scale model.     

Different parameterisation of a Gaussian scheme: intercomparison study

The aim of this work is to define the most efficient parameterisation of the PBL (planetary boundary layer) by using the simulation with a simple Gaussian dispersion model of the plume type and comparing it with the improved OML model. A different type of σ_y and σ_z parameterisation in a Gaussian dispersion scheme was introduced. The old Pasquill–Gifford scheme and the new boundary layer parameterisation based on Monin–Obukhov length and other convective scaling parameters were compared, using a classical Gaussian model. For this comparison, the hourly average concentration and the long-term concentrations generated by these models, using same input data, were computed. These computed values and the field observations clearly show the importance of the parameterisations used by the models and the necessity of improving them. With this new parameterisation, we can easily add in new phenomena, such as dry and wet deposition, building effects and stack tip downwash penetration.     

Cooling Towers and the Environment

Measurements of natural draft cooling tower plume behavior, as well as meteorological variables, were obtained from aircraft flights near major power plants of the American Electric Power System. Persistence of the visible plume to great distances depends essentially on ambient humidity. Atmospheric stability at plume elevation was also important. Cooling tower-induced fog at ground-level was never observed in any of the tests, and aerodynamic downwash of the visible plume was absent also. The cooling towers did cause modification of natural clouds and they occasionally shadowed some local areas from the sun. Merging of the stack and cooling tower plumes was a common occurrence.     

Flue gas discharge from cooling towers. Wind tunnel investigation of building downwash effects on ground-level concentrations

German power plants are required to meet new emission standards which limit the maximum sulfur dioxide (SOs) concentration in flue gas discharges to 400 mg m⁻³. To achieve this level of reduction in SO₂ concentration, wet scrubbing is necessary for large plants using lignite or hard coal.Wet scrubbing results in a significant reduction in the flue gas temperature leading to low effective stack heights. Instead of using stack gas reheating to achieve the plume rise necessary to satisfy local environmental standards, it was proposed to discharge the scrubbed flue gas from the existing natural-draft cooling towers (NDCT). This method should be effective in reducing local ground-level concentrations since NDCT-plumes are typically very buoyant (densimetric Froude number below 1 ) and normally reach considerable heights of rise. Only under strong wind conditions does the situation reverse itself. For such strong winds, the NDCT-plume is subject to tower and building downwash with the possibility of unacceptably high ground-level concentrations.For a 2700 MW_e lignite-fired power plant near Cologne, a wind tunnel study was carried out to investigate the effects of tower and building downwash effects on the ground-level concentrations of SO₂ produced by discharging the scrubbed flue gas from the natural-draft cooling towers. Also, a comparison was made between the ground-level concentrations produced by the cooling tower discharge method and those produced by a traditional stack. It was found that for low and intermediate wind speeds, the groundlevel concentrations are lower for the case of the cooling tower discharge. Only for strong winds, which occur only very rarely at most German sites, did the conventional stack discharge appear to be superior.     

Near-field dispersion modeling for regulatory applications

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex-Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model-Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Frank A. Chambers

Abstract

This work assessed the usefulness of a current air quality model (American Meteorological Society/Environmental Protection Agency Regulatory Model [AERMOD]) for predicting air concentrations and deposition of perfluorooctanoate (PFO) near a manufacturing facility. Air quality models play an important role in providing information for verifying permitting conditions and for exposure assessment purposes. It is important to ensure traditional modeling approaches are applicable to perfluorinated compounds, which are known to have unusual properties. Measured field data were compared with modeling predictions to show that AERMOD adequately located the maximum air concentration in the study area, provided representative or conservative air concentration estimates, and demonstrated bias and scatter not significantly different than that reported for other compounds. Surface soil/grass concentrations resulting from modeled deposition flux also showed acceptable bias and scatter compared with measured concentrations of PFO in soil/grass samples. Errors in predictions of air concentrations or deposition may be best explained by meteorological input uncertainty and conservatism in the PRIME algorithm used to account for building downwash. In general, AERMOD was found to be a useful screening tool for modeling the dispersion and deposition of PFO in air near a manufacturing facility.     

Near-Field Dispersion Modeling for Regulatory Applications

Abstract

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex–Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model–Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.