Sensitivity of the AERMOD air quality model
to the selection of land use parameters
Thomas G. Grosch<» and Russell F. Lee<*>
( Trinity Consultants, 79 T.W. Alexander Drive, Building 4201, Suite 207
Research Triangle Park, NC 27709, USA
77 CoWznWgz Cbwrf, Dwr&zm, 7VC2777J-949J,
Email: tgrosch @ trinity consultants, com
Abstract
AERMOD is a new, advanced plume dispersion model that the U.S. EnvironmentalProtection Agency (EPA) is expected to propose for regulatory use. It is intended toreplace ISCST3 for most modeling applications. AERMOD is the result of an effortto incorporate scientific knowledge gained over the last three decades into regulatoryplume models.
AERMOD requires, as input, three site-specific land use parameters. These arethe Bowen ratio (a measure of moisture available for evaporation), the albedo(portion of sunlight that is reflected), and surface roughness length. These parametersare functions of ground cover (land use), and affect the concentration calculations.It is important to know how sensitive the model results are to these parameters, sothat their input values are characterized with sufficient accuracy for modelingpurposes. This study evaluates the effect on design concentration predictions fromAERMOD, for a range of sources, of variations of the albedo, Bowen ratio, andsurface roughness length individually and in combination over the ranges of valuesone would expect to encounter in realistic modeling scenarios. The sources includea ground level source, and stacks ranging from 35 meters to 200 meters in height.The effects of variations of combinations of these parameters on design concentrationpredictions is further evaluated by selecting the land use parameters that arecharacteristic of each of four types of ground cover. The sensitivity of the designconcentration predictions by the AERMOD model to these input parameters isdiscussed. Recommendations are provided as to the accuracy needed for values ofthe Bowen ratio, albedo, and surface roughness length that are used in the AERMODmodel.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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Introduction
In 1991 the American Meteorological Society (AMS) and the United StatesEnvironmental Protection Agency (EPA) formally initiated a project to introducerecent scientific advances into applied dispersion models. A working group, theAMS/EPA Regulatory Model Improvement Committee (AERMIC), was formed,which developed the new air quality model, AERMOD (AERMIC model), largelywith EPA support.
AERMOD calculates convective (daytime) turbulence based on the amount ofsolar heating available to drive the turbulent processes. To make these calculations,AERMOD requires three land use" parameters not used in current regulatorymodels. These are the albedo, the Bowen ratio, and the surface roughness length. Thealbedo is the proportion of the sunlight that is reflected back into space. The Bowenratio is an indicator of the amount of moisture available to drive turbulent processes.The surface roughness length is an indicator of the amount of drag the ground surfaceexerts on the wind. These all have the potential to affect concentration calculations.
The importance and accuracy of these parameters depend on how sensitive themodel is to variations in those values. The purpose of this study is to determine howmuch the calculation of design concentrations can be affected by changes in albedo,Bowen ratio, and surface roughness length over their normal ranges. The study wasconducted for four sources (stacks) ranging from a surface release with no plume riseto a 200 meter high stack with plume rise. Stack diameter, gas temperature, and gasexit velocity were set at values that might reasonably be used for a small, medium,and large boiler, respectively.
Model Description
AERMOD is a steady-state plume model that is designed to estimate near-field (lessthan 50km) concentrations from most types of industrial sources. The AERMODmodeling system consists of three programs, the model itself (AERMOD), ameteorological preprocessor (AERMET), and a terrain preprocessor (AERMAP).BREEZE AERMOD SUITE, developed by Trinity Consultants, was used to aid inthe model setup, execution, and analysis of the scenarios modeled in this study.
AERMOD makes use of two continuous stability parameters, the frictionvelocity and the Monin-Obukhov length to characterize the atmosphere. The frictionvelocity is a measure of mechanical effects alone, i.e., wind shear at ,ground level.The Monin-Obukhov length indicates the relative strengths of mechanical andbuoyant effects on turbulence. Thus, AERMOD can account for turbulence bothfrom wind shear and from buoyancy effects due to solar heating during the day andradiational cooling at night. To properly account for these effects, AERMODrequires three land use parameters: albedo, Bowen ratio, and surface roughness.Modem planetary boundary layer theory is used to scale turbulence and otherparameters to the height of the plume. The AERMOD system (specifically, theAERMET meteorological preprocessor) derives hourly mixing heights based on the
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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morning upper air sounding and the surface meteorology, including available solarradiation.
The role of land use parameters in AERMOD
Three land use parameters, albedo, Bowen ratio, and surface roughness length, arerequired by the AERMOD system to properly calculate turbulent dispersion of airpollutants. The effects of these parameters are accounted for in AERMET, themeteorological preprocessor portion of the AERMOD system.
During convective (daytime) conditions, albedo, Bowen ratio, and surfaceroughness all play significant rolls in calculating the friction velocity and theMonin-Obukhov length. The proportion of the incoming solar radiation that isreflected back into space is defined by the albedo. Some of the remaining radiationis used to evaporate moisture from the ground and from plant leaf surfaces. Theremaining radiation heats the earth's surface. This drives much of the turbulence(and, thus, dispersion) in the atmosphere during convective (daytime) conditions.The increased turbulence directly affects air pollutant concentrations by increasingdispersion, and indirectly by causing the mixing height to increase by altering theprofiles of wind speed, turbulence, and other parameters with height. Surfaceroughness affects the amount of drag the ground exerts on the wind. This createsshear which, in turn, generates turbulence, affects mixing height, and alters theprofiles of various meteorological parameters. During stable (nighttime) conditions,only the effects of surface roughness length are used.
Model input data
To test the effects of varying the land use parameters, albedo, Bowen ratio, andsurface roughness length, on the resulting modeled design concentrations, AERMODwas run for each of four point sources for receptor distances ranging from 125 metersto 16 kilometers from the source. The land use parameters were varied over a rangethat one might expect to encounter in real life modeling situations. All runs weremade with one year of meteorology from a single site. The meteorology used in thisexercise was from the surface observations at Wichita, KS, and the upper air(rawinsonde) observations from Topeka, KS, for the year 1987 and processedthrough BREEZE AERMET Pro (see Figure 1).
Table 1 provides the characteristics of the four point sources that were modeled.These sources represent a surface source with no buoyant plume rise, and stacksources that could represent a small, medium, and large boiler, respectively. In allcases, the emission rate was set at 100 grams per second, and model outputconcentrations are given in micrograms per cubic meter.
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Table 1. Source characteristicsStack Height
035100200
Stack Diameter2.42.44.65.6
Gas Exit Velocity0.0111.718.826.5
Gas Temperature293432416425
The AERMET Users Guide (U.S. EPA) suggests values of albedo, Bowenratio, and surface roughness length to be applied for eight different land usecategories, by season of the year. The land use categories are water, deciduous forest,coniferous forest, swamp, cultivated land, grassland, urban, and desert shrubland.
In the first part of this study, all three parameters were altered simultaneously.Because these parameters are interrelated (e.g., a surface roughness length of 0.0001, found only over water, cannot be combined with a Bowen ratio of 10, whichrepresents a very dry surface), it would be inappropriate to combine them randomly.In order to retain realistic combinations of land use parameters, four land usecategories were selected from those given in the AERMET User's Guide (U.S.EPA1). The recommended seasonal values of those land use parameters were usedas presented in Table 2. These include the most extreme values of albedo, Bowenratio, and surface roughness, except for the extremely dry Bowen ratio for desertunder the driest conditions (the Bowen ratios for "average moisture conditions" forall categories, including desert were used).
Table 2. Land use parameters used in the first part of the study(based on U.S. EPA')
Land UseCategoryGrassland
Desert
ConiferForest
Water
Land UseParameter
AlbedoBowen RatioRoughnessAlbedoBowen RatioRoughnessAlbedoBowen RatioRoughnessAlbedoBowen RatioRoughness
SeasonWinter
0.601.50.0010.456.00.150.351.51.300.201.50.0001
Spring
0.180.40.050.303.00.300.120.71.300.120.10.0001
Summer
0.180.80.100.284.00.300.120.31.300.100.10.0001
Autumn
0.201.00.010.286.00.300.120.81.300.140.10.0001
In the second part of this study, one parameter was altered at a time, by selectingtypical, minimum, and maximum values of albedo, Bowen ratio, and surfaceroughness length, which were selected from the tables in the AERMET Users Guide.While the tables do not give the most extreme conditions that can be found, they doprovide a reasonable estimate of the range of conditions one might encounter inrealistic modeling scenarios. Table 3 shows the values of albedo, Bowen ratio, and
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surface roughness length that were selected for each scenario. The "Base Case"represents approximate mid-range values of each parameter.
Table 3. Values of land use parameters used in the second part of the study(based on ranges of values suggested in U.S. EPA ).
Scenario
Base CaseLow AlbedoHigh AlbedoLow Bowen RatioHigh Bowen RatioLow Roughness LengthLow Roughness Length
Albedo
0.20.10.450.20.20.20.2
Bowen Ratio
1.01.01.00.110.01.01.0
RoughnessLength
0.10.10.10.10.10.00011.3
Analysis and Results
AERMOD was applied to each source type, surface, 35-meter stack, 100-meterstack, and 200-meter stack, to produce estimates of design concentrations of interestfor regulatory applications. The specific design concentrations of interest are thehigh-second high (HSH) 1 -hour, 3-hour, and 24-hour concentrations, and thehighest annual average concentration. The phrase "high-second high" refers to thehighest of the second highest concentrations at each receptor, which is the criterionfor most regulatory standards in the United States. These design concentrations werecompared for four ground cover types, which provide a large range of combinationsof the land use parameters. The four types are grassland, desert, conifer forest, andwater surface. The specific values of albedo, Bowen ratio, and surface roughnesslength are specified in Table 3 above. The design concentrations were also comparedwhile varying individual parameters between their lowest and highest tabulatedvalues from the AERMET User's Guide (U.S. EPA).
Surface Source
Changes in ground cover cause changes in the design concentrations of approximatelytwo orders of magnitude for all averaging times (see table 4). The highestconcentrations occur with values of the land use parameters appropriate for water,and the lowest with those appropriate to conifer forest. Results shown in tables 5-7reveal that only the surface roughness length affects the design concentrationssignificantly. Tables 5 and 6 show that the albedo and Bowen ratio have little or noeffect on the annual design concentrations. A close look at the results indicates thatthe high and high-second high concentrations for the I- and 3-hour averaging times
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occurred at night. Albedo and Bowen ratio only affect the retention of incoming solarradiation, and therefore have no effect at night. Albedo has some slight effect on themodel results for the 24-hour and annual design concentrations, because of theinclusion of daytime hours, although nighttime hours clearly dominate the results.
Over the range of surface roughness lengths considered, the modeled 1-, 3-,24-hour, and annual design concentrations all decreased by about two orders ofmagnitude (table 7). This accounts for the changes observed over the four groundcover types. This is reasonable, since the surface roughness length affects modelingin both daytime and nighttime conditions. The increased turbulence associated withhigher roughness lengths increases the dispersion of the plume away from thecenterline height (which is at ground level).
35-meter Stack
The effects of ground cover type on the design concentrations for the 35-metersource are quite different from the effects for the surface source (table 4). Thedifferences in the design concentrations are much smaller, with changes rangingfrom about a 3 0% change for the 1 -hour HSH to more than an order of magnitudechange for the highest annual average. However, the water surface now provides thelowest design concentrations while the conifer forest provides the highest in all butone averaging time, the reverse of that seen with the surface source. Comparing thedata in tables 5-7 reveals that all three land use parameters are substantially affectingthe design concentrations. This is to be expected, since all the design concentrationsfrom the 35-meter stack occur near midday. Nevertheless, the effect of albedo onthese concentrations (table 5) is still relatively small, with the design concentrationsless than 20% lower for the more than a factor-of-four increase of the albedo.Changes of design concentrations over the range of the Bowen ratio are somewhathigher, though in the opposite direction. As table 6 shows, the design concentrationsincrease from a few percent for the 24-hour averaging time to about 50% for theannual average, as the Bowen ratio is increased from 0. 1 (typical of a swamp, forexample) to 10 (typical of a desert). The surface roughness length has the largesteffect (table 7). The range from 0.0001 (smooth water) to 1.3 (conifer forest)increases concentrations by 30% for the 1 -hour, a factor of two for the 3-hour, andby more than a factor of five for the 24-hour and the annual design concentrations.This trend is the reverse of that seen for the surface source, since the increaseddispersion resulting from the increased roughness transfers material away from thecenter of the plume, increasing concentrations at ground level. While the change isnot orders of magnitude as seen with the surface source, it is still substantial.
100-meter Stack
The effects of ground cover type on design concentrations from the 100 meter stack(table 4) are somewhat less, with highest and lowest values ranging from 25% to afactor of 5.6 different. The patterns for the 24-hour and annual design concentrationsare similar to those of the 35-meter stack, with the highest design concentrations
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being associated with the conifer forest and the lowest with the water surface.However, the 1 -hour and 3 -hour design concentrations show thehighest concentrations for the water surface and desert, respectively. This underscoresthe complex relationships between groundcover and dispersion, which makes theresults seem sometimes counterintuitive. Changes in albedo (table 5) resulted in thedesign concentrations changing by as much as about 50%, while the Bowen ratio(table 6) resulted in a factor of two difference and the roughness length (table 7) ina factor of three difference. Note that for one case, the 1 -hour HSH, the mid-rangevalue (base case) of the Bowen ratio produced a lower design concentration thaneither the highest or lowest Bowen ratio.
200-meter Stack
The effect of ground cover on the highest design concentrations is shown in table 4.The design concentration results vary by up to a factor of three to four for the 1 -hourand annual design concentrations, but less than a factor of two for the intermediateaveraging times. Note that the four averaging times show the highest designconcentrations from three of the four ground cover types, respectively. This furtheremphasizes the complexities of the relationships between the land use parametersand concentrations. The sensitivity of design concentrations from the 200-meterstack to albedo (table 5) and Bowen ratio (table 6) are qualitatively similar to the caseof the 1 00-meter stack for all but the 1 -hour averaging time. The designconcentrations decrease up to about 30% between the cases for the highest andlowest and highest albedo. Interestingly, for the 1 -hour case, the highest designconcentration occurs with the mid-range value of the albedo. The effect of theBowen ratio on design concentrations is similar, except that the design concentrationsincrease up to almost a factor of three. The sensitivity of design concentrations tosurface roughness length appears even more complex. The 1 -hour designconcentration decreases by a factor of 4.5 as the roughness is increased from itsminimum to its maximum value (table 7). The 3-hour design concentration showsa similar trend, with concentrations decreasing by 45% over the range of theroughness lengths. For the 24-hour case, the lowest design concentrations occurredwith the mid-range value of roughness length. For the annual average case, designconcentrations increased with roughness by somewhat over a factor of two.
Conclusions
The effects of changes in albedo, Bowen ratio, and surface roughness lengths,in combination and individually, on regulatory design concentrations predicted byAERMOD were studied. The effects that these parameters have on the modeleddesign concentrations in AERMOD are sufficiently complex that it cannot beaccurately anticipated what effect any changes in those values will have on designconcentrations for a given source configuration. This study shows that modeleddesign concentrations can vary substantially due to normal ranges of variations inthe albedo, Bowen ratio, and surface roughness length. Changes in albedo, Bowen
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ratio, and surface roughness length can result in changes in design concentrations offactors of 1.5, 2.7, and 160, respectively. Changes in design concentrations can beeven greater when these parameters are varied in combination, for example, by usingparameters characteristic of a swamp instead of those characteristic of a desert.
One can conclude that reasonably accurate estimates of albedo, Bowen ratio,and surface roughness lengths are necessary for AERMOD to provide accurateresults. In particular, the suggested values of roughness length in the AERMETUser's Guide (U.S. EPA), based on eight land use categories, may not be adequateto obtain the best possible concentration estimates from AERMOD. More detailedsuggestions have appeared in the technical literature from time to time. Modelers areencouraged to make use of such recommendations if available. A more detailedsensitivity analysis would be required to determine whether the suggested values ofalbedo and Bowen ratio found in the U. S. EPA should be improved upon as well.
Table 4. Effects of ground cover type on design concentrations.
Stack
Surface
35-meter
100-meter
200-meter
Ground Cover
WaterGrasslandDesert
Conifer ForestWaterGrasslandDesertConifer ForestWaterGrasslandDesertConifer ForestWaterGrasslandDesertConifer Forest
1-hrHSH
45742971794422
365985
36433463437522552114
93565338493112
3-hr HSH
26992571183718179521
21139
2193604305394039494418161110
24-hr HSH
62302521775741051
5839451272023867
1117243.73.54.14.5
Annual
89346225455579
12435183472
0.711.402.543.990.300.360.640.90
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Table 5. Effects of albedo on design concentrations.
Stack
Surface
35-meter
100-meter
200-meter
Albedo
Base case
Low albedo
High albedoBase case
Low albedo
High albedoBase case
Low albedo
High albedoBase case
Low albedoHigh albedo
1-hrHSH
642132642132
642132
449
468
4106152
8039
3735
3-hr HSH
404567
404567
404567367
371
3484542
3113.1
12.3
11.6
24-hr HSH
65772
6579566130
13513813212
139
3.1
3.32.4
Annual
11814
11709
12010
24
2521
1.7
1.91.50.46
0.510.35
Table 6. Effects of Bowen ratio on design concentrations.
Stack
Surface
35-meter
100-meter
200-meter
Bowen Ratio
Low BowenHigh BowenLow BowenHigh BowenLow Bowen
High BowenLow BowenHigh Bowen
1-hrHSH
642132642132
35649678
642033
3-hr HSH
404567404567
29637529
49813
24-hr HSH
6584965859
130137
9
1524
Annual
1205711681
1726
1.23
2530.250.67
Table 7. Effects of surface roughness length on design concentrations.
Stack Roughness 1-hrHSH 3-hr HSH 24-hr HSH AnnualLength
Surface
35-meter
100-meter
200-meter
Low
HighLow
HighLow
HighLow
High
4574297
36433
420
552
108
55
58
13
269925721139
273
53941
4719.210.6
6233305836
72386
924
4.40
4.59
88564
1232
1172
1.26
4.200.40
0.93
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812 Air Pollution
mmmi
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Figure 1. BREEZE AERMET User Interfacedisplaying site-specific land use parameters.
References
1. U.S. EPA, 1998: Revised Draft User's Guide for the AERMODMeteorological Preprocessor (AERMET), U.S. Environmental ProtectionAgency.
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