AERCOARE: An overwater meteorological preprocessor for AERMOD

AERCOARE is a meteorological data preprocessor for the American Meteorological Society and U.S Environmental Protection Agency (EPA) Regulatory Model (AERMOD). AERCOARE includes algorithms developed during the Coupled-Ocean Atmosphere Response Experiment (COARE) to predict surface energy fluxes and stability from routine overwater measurements. The COARE algorithm is described and the implementation in AERCOARE is presented. Model performance for the combined AERCOARE-AERMOD modeling approach was evaluated against tracer measurements from four overwater field studies. Relatively better model performance was found when lateral turbulence measurements were available and when several key input variables to AERMOD were constrained. Namely, requiring the mixed layer height to be greater than 25 m and not allowing the Monin Obukhov length to be less than 5 m improved model performance in low wind speed stable conditions. Several options for low wind speed dispersion in AERMOD also affected the model performance results. Model performance for the combined AERCOARE-AERMOD modeling approach was found to be comparable to the current EPA regulatory Offshore Coastal Model (OCD) for the same tracer studies. AERCOARE-AERMOD predictions were also compared to simulations using the California Puff-Advection Model (CALPUFF) that also includes the COARE algorithm. Many model performance measures were found to be similar, but CALPUFF had significantly less scatter and better performance for one of the four field studies. For many offshore regulatory applications, the combined AERCOARE-AERMOD modeling approach was found to be a viable alternative to OCD the currently recommended model.

Implications: A new meteorological preprocessor called AERCOARE was developed for offshore source dispersion modeling using the U.S. Environmental Protection Agency (EPA) regulatory model AERMOD. The combined AERCOARE-AERMOD modeling approach allows stakeholders to use the same dispersion model for both offshore and onshore applications. This approach could replace current regulatory practices involving two completely different modeling systems. As improvements and features are added to the dispersion model component, AERMOD, such techniques can now also be applied to offshore air quality permitting.     

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.     

A Comparison of Model Performance between AERMOD and AUSTAL2000

ABSTRACT

In this study the performance of the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD), a Gaussian plume model, is compared in five test cases with the German Dispersion Model according to the Technical Instructions on Air Quality Control (Ausbreitungsmodell gemäβ der Technischen Anleitung zur Reinhaltung der Luft) (AUSTAL2000), a Lagrangian model. The test cases include different source types, rural and urban conditions, flat and complex terrain. The predicted concentrations are analyzed and compared with field data. For evaluation, quantile-quantile plots were used. Further, a performance measure is applied that refers to the upper end of concentration levels because this is the concentration range of utmost importance and interest for regulatory purposes. AERMOD generally predicted concentrations closer to the field observations. AERMOD and AUSTAL2000 performed considerably better when they included the emitting power plant building, indicating that the downwash effect near a source is an important factor. Although AERMOD handled mountainous terrain well, AUSTAL2000 significantly underestimated the concentrations under these conditions. In the urban test case AUSTAL2000 did not perform satisfactorily. This may be because AUSTAL2000, in contrast to AERMOD, does not use any algorithm for nightly turbulence as caused by the urban heat island effect. Both models performed acceptable for a nonbuoyant volume source. AUSTAL2000 had difficulties in stable conditions, resulting in severe underpredictions. This analysis indicates that AERMOD is the stronger model compared with AUSTAL2000 in cases with complex and urban terrain. The reasons for that seem to be AUSTAL2000's simplification of the meteorological input parameters and imprecision because of rounding errors.

IMPLICATIONS This study contributes to the understanding of dispersion modeling and demonstrates the advantage of detailed meteorological data. It also helps air quality regulators and planners to identify the most appropriate model to use. It is indicated that AERMOD is more suitable for air quality planning and regulation, when all required meteorological information is available, because its predictions are mostly closer to field observations. Furthermore AUSTAL2000 predicted concentrations that showed a narrow range and triggered far less impacts from the source.     

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.     

The Validity of Several Plume Rise Formulas

The ground level concentration of pollutants downwind of a tall chimney decreases as the effective height of the stack increases. The effective height of the stack is the actual height plus the rise of the plume center-line due to momentum and buoyancy of the effluent. Over twenty formulas to predict plume rise from stack and meteorological parameters have been proposed; none is uniformly accepted. In this paper, 711 plume rise observations were used to test the ability of fifteen of the published and commonly used formulas to predict plume rise. The plume rise data were obtained from single stacks whose heat emission rate varied over four orders of magnitude. None of the formulas tested was found to be significantly better than the others. Research was performed under the auspices of the U.S. Atomic Energy Commission.     

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.     

海岸地区基于AERMOD的热力内边界层对大气污染物扩散影响的模拟研究

海岸地区热力内边界层(TIBL)对大气污染物扩散具有重要影响。选取杭州湾地区某区域为模拟区,采用一个TIBL高度的简单计算模式模拟模拟区的TIBL高度,将其耦合到空气质量模式AERMOD中,并对AERMOD的相关模块和参数进行了相应的修改,再分别利用原AERMOD和改进后的AERMOD,模拟了不同污染源情景下的大气污染物地面浓度分布。结果表明,在多数情况下,由于TIBL对于大气污染物扩散空间的限制,大气污染物的地面最大浓度有所升高,地面浓度的高值区范围也有所增加,具体影响特征取决于污染源与TIBL的相对高度以及污染源距离海岸的相对位置。     

Stable plume rise in a shear layer

Solutions are given for plume rise assuming a power-law wind speed profile in a stably stratified layer for point and finite sources with initial vertical momentum and buoyancy. For a constant wind speed, these solutions simplify to the conventional plume rise equations in a stable atmosphere. In a shear layer, the point of maximum rise occurs further downwind and is slightly lower compared with the plume rise with a constant wind speed equal to the wind speed at the top of the stack. If the predictions with shear are compared with predictions for an equivalent average wind speed over the depth of the plume, the plume rise with shear is higher than plume rise with an equivalent average wind speed.     

An evaluation of flare combustion efficiency using open-path Fourier transform infrared technology

Open-path Fourier transform infrared (OP-FTIR) technology was used to evaluate the combustion efficiency of a flare for comparison to several combustion models. Most flares have been considered an effective method for destroying organic compounds and anything that burns. As the Btu content of the flare gas is reduced, the combustion efficiency may also be reduced. Recent studies have suggested that lower Btu flares may have efficiencies as low as 65%. In addition, models have been developed to predict the effect of wind speed and stack discharge velocity on the combustion efficiency. This study was conducted on a low-Btu flare gas that is primarily CO. While the models would predict efficiencies as low as 30%, the sampling using OP-FTIR showed most combustion efficiencies well above 90%. Three methods were used to track combustion efficiency: monitoring the ratio of CO to CO2, monitoring the ratio of CO to tracer gas, and dispersion modeling. This study was complicated by the presence of two flare stacks, thus two tracer gases were used--SF6 and CF4. A method was developed for distinguishing between the two stacks and quantifying the efficiency in each stack.     

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.     

Comparison of the complex terrain algorithms incorporated into two commonly used local-scale air pollution dispersion models (ADMS and AERMOD) using a hybrid model

ADMS and AERMOD are the two most widely used dispersion models for regulatory purposes. It is, therefore, important to understand the differences in the predictions of the models and the causes of these differences. The treatment by the models of flat terrain has been discussed previously; in this paper the focus is on their treatment of complex terrain. The paper includes a discussion of the impacts of complex terrain on airflow and dispersion and how these are treated in ADMS and AERMOD, followed by calculations for two distinct cases: (i) sources above a deep valley within a relatively flat plateau area (Clifty Creek power station, USA); (ii) sources in a valley in hilly terrain where the terrain rises well above the stack tops (Ribblesdale cement works, England). In both cases the model predictions are markedly different. At Clifty Creek, ADMS suggests that the terrain markedly increases maximum surface concentrations, whereas the AERMOD complex terrain module has little impact. At Ribblesdale, AERMOD predicts very large increases (a factor of 18) in the maximum hourly average surface concentrations due to plume impaction onto the neighboring hill; although plume impaction is predicted by ADMS, the increases in concentration are much less marked as the airflow model in ADMS predicts some lateral deviation of the streamlines around the hill.     

Validation of ADMS against wind tunnel data of dispersion from chemical warehouse fires

Comparisons are presented of the predictions of the atmospheric dispersion modelling system (ADMS) and wind tunnel data for plume dispersion from chemical warehouse fires. The focus of the comparisons is dispersion from structurally intact buildings with open roofs and dispersion of plumes flush with the ground without obstacles, however, dispersion from building shells and doors is also considered. Both buoyancy driven and momentum driven flows are treated, although emphasis is on buoyancy driven flows as these are generally more likely to occur in warehouse fires. The study shows that the ADMS building module is able to reproduce many of the features of dispersion observed in the wind tunnel. These include a recirculating region behind the building in which material may be trapped, a main wake which brings material down towards the surface, and appropriate sensitivity to the buoyancy and momentum of the emitted material, and the location of sources on the building roof. The comparisons suggest that the ADMS building model can be used to predict dispersion from the stages of fire development studied. The precise level of agreement depends (but not in a systematic way) on the buoyancy flux parameter F_B, the momentum flux parameter F_M and the number of roof lights. There are some significant differences between the wind tunnel boundary layer and the simulated atmospheric boundary layer in ADMS which have to be considered when making wind tunnel model comparisons. These relate mainly to the near surface where the wind tunnel underestimates turbulent velocities, the boundary layer height which in the wind tunnel corresponds to an atmospheric boundary layer depth of 82.5 m (atmospheric boundary layers are frequently an order of magnitude deeper), and the boundary layer top where the ADMS boundary layer is capped by an inversion and has low turbulence levels whereas the wind tunnel boundary layer has higher levels of turbulence and no capping inversion.     

Observations Less than the Analytical Limit of Detection: A New Approach

Abstract

Solutions are given for plume rise assuming a power-law wind speed profile in a stably stratified layer for point and finite sources with initial vertical momentum and buoyancy. For a constant wind speed, these solutions simplify to the conventional plume rise equations in a stable atmosphere. In a shear layer, the point of maximum rise occurs further downwind and is slightly lower compared with the plume rise with a constant wind speed equal to the wind speed at the top of the stack. If the predictions with shear are compared with predictions for an equivalent average wind speed over the depth of the plume, the plume rise with shear is higher than plume rise with an equivalent average wind speed.     

An Evaluation of Flare Combustion Efficiency Using Open-Path Fourier Transform Infrared Technology

ABSTRACT

Open-path Fourier transform infrared (OP-FTIR) technology was used to evaluate the combustion efficiency of a flare for comparison to several combustion models. Most flares have been considered an effective method for destroying organic compounds and anything that burns. As the Btu content of the flare gas is reduced, the combustion efficiency may also be reduced. Recent studies have suggested that lower Btu flares may have efficiencies as low as 65%. In addition, models have been developed to predict the effect of wind speed and stack discharge velocity on the combustion efficiency. This study was conducted on a low-Btu flare gas that is primarily CO. While the models would predict efficiencies as low as 30%, the sampling using OP-FTIR showed most combustion efficiencies well above 90%. Three methods were used to track combustion efficiency: monitoring the ratio of CO to CO₂, monitoring the ratio of CO to tracer gas, and dispersion modeling. This study was complicated by the presence of two flare stacks, thus two tracer gases were used—SF₆ and CF₄. A method was developed for distinguishing between the two stacks and quantifying the efficiency in each stack.     

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.     

Panel Discussion

A stack design procedure is developed which accounts for the effect of plume interception by downwind buildings, and which provides information on effluent concentrations in a form useful to planning authorities. The information presented in this paper is directed to engineers carrying out stack designs for locations where downwind buildings are of comparable height to the stack. A wind tunnel investigation using tracer gas techniques indicates that, for a plume at building height, downwash on the upwind face of a building causes the high concentrations observed near the roof to be transported to ground level. The effect of a plume on elevated points is determined by the concept of the minimum descent height of the maximum allowable ambient concentration isopleth. This minimum descent height, computed using Gaussian plume dispersion theory, defines a building height below which pollutant concentrations will always lie within safe limits. A case study is presented for the use of the design procedure for a small thermal power plant in an urban area.     

Effective pollutant emission heights for atmospheric transport modelling based on real-world information

Emission data needed as input for the operation of atmospheric models should not only be spatially and temporally resolved. Another important feature is the effective emission height which significantly influences modelled concentration values. Unfortunately this information, which is especially relevant for large point sources, is usually not available and simple assumptions are often used in atmospheric models. As a contribution to improve knowledge on emission heights this paper provides typical default values for the driving parameters stack height and flue gas temperature, velocity and flow rate for different industrial sources. The results were derived from an analysis of the probably most comprehensive database of real-world stack information existing in Europe based on German industrial data. A bottom-up calculation of effective emission heights applying equations used for Gaussian dispersion models shows significant differences depending on source and air pollutant and compared to approaches currently used for atmospheric transport modelling.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Dry deposition to a uniform canopy: Evaluation of a first-order-closure mathematical model

A mathematical model is developed for the transport of momentum and matter within a canopy consisting of identical elements protruding vertically from a smooth substrate. Turbulent flux is modelled using a mixing-length approach. The loss of momentum (or matter) to individual elements is related to the mean wind speed, and the element-element interaction via the turbulent wind field is represented by a sheltering factor. Careful consideration is given to the formulation of lower boundary conditions. The model assumptions are compared with those of other models.The model predictions are compared with measurements on a vertically- and horizontally-uniform artificial canopy in a wind-tunnel. The model reproduces well the observed relationship between the parameters of the logarithmic wind speed profile above the canopy and the observed deposition velocities of thorium-B (ThB) atoms and particles in the diameter range 0.08–32 μm, using a sheltering factor which is little dependent on wind speed and has the same magnitude for momentum, gas and particles. The predicted dependences of deposition velocity on friction velocity and, for particles, on diameter shed light on the performance of semi-empirical correlations proposed in the literature. For ThB atoms, the calculated deposition velocities are compared with those of other mathematical canopy models: a comparable degree of agreement is obtained here with fewer free parameters.The fraction of deposit on the substrate is underpredicted by an order of magnitude in some cases, pointing to the limitations of the modelling of conditions near the substrate in terms of quasi-shear flow.