Sensitivity of the AERMOD air quality model to the selection of land use parameters

Transcription

1 Sensitivity of the AERMOD air quality model to the selection of land use paras Thomas G. Grosch Trinity Consultants, 79 T.W. Alexander Dr., Building 4201, Suite 207, Research Triangle Park, NC 27709; Russell F. Lee 17 Cobbleridge Court, Durham, NC Abstract AERMOD is a new, advanced plume dispersion model that the U.S. Environmental Protection Agency (EPA) is expected to propose for regulatory use. It is intended to replace ISCST3 for most modeling applications. AERMOD is the result of an effort to incorporate scientific knowledge gained over the last three decades into regulatory plume models. AERMOD requires, as input, three site-specific land use paras. These are the Bowen ratio (a measure of moisture available for evaporation), the albedo (portion of sunlight that is reflected), and surface roughness length. These paras are functions of ground cover (land use), and affect the concentration calculations. It is important to know how sensitive the model results are to these paras, so that their input values are characterized with sufficient accuracy for modeling purposes. This study evaluates the effect on design concentration predictions from AERMOD, for a range of sources, of variations of the albedo, Bowen ratio, and surface roughness length individually and in combination over the ranges of values one would expect to encounter in realistic modeling scenarios. The sources include a ground level source, and stacks ranging from 35 s to 200 s in height. The effects of variations of combinations of these paras on design concentration predictions is further evaluated by selecting the land use paras that are characteristic of each of four types of ground cover. The sensitivity of the design concentration predictions by the AERMOD model to these input paras is discussed. Recommendations are provided as to the accuracy needed for values of the Bowen ratio, albedo, and surface roughness length that are used in the AERMOD model. Introduction In 1991 the American Meteorological Society (AMS) and the United States Environmental Protection Agency (EPA) formally initiated a project to introduce recent scientific advances into applied dispersion models. A working group, the AMS/EPA Regulatory Model Improvement Committee (AERMIC), was formed, which developed the new air quality model, AERMOD (AERMIC model), largely with EPA support.

2 AERMOD calculates convective (daytime) turbulence based on the amount of solar heating available to drive the turbulent processes. To make these calculations, AERMOD requires three land use paras not used in current regulatory models. These are the albedo, the Bowen ratio, and the surface roughness length. The albedo is the proportion of the sunlight that is reflected back into space. The Bowen ratio 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 surface exerts on the wind. These all have the potential to affect concentration calculations. The importance and accuracy of these paras depend on how sensitive the model is to variations in those values. The purpose of this study is to determine how much the calculation of design concentrations can be affected by changes in albedo, Bowen ratio, and surface roughness length over their normal ranges. The study was conducted for four sources (stacks) ranging from a surface release with no plume rise to a 200 high stack with plume rise. Stack dia, gas temperature, and gas exit 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 (less than 50km) concentrations from most types of industrial sources. The AERMOD modeling system consists of three programs, the model itself (AERMOD), a meteorological preprocessor (AERMET), and a terrain preprocessor (AERMAP). BREEZE AERMOD SUITE, developed by Trinity Consultants, was used to aid in the model setup, execution, and analysis of the scenarios modeled in this study. AERMOD makes use of two continuous stability paras, the friction velocity and the Monin-Obukhov length to characterize the atmosphere. The friction velocity is a measure of mechanical effects alone, i.e., wind shear at ground level. The Monin-Obukhov length indicates the relative strengths of mechanical and buoyant effects on turbulence. Thus, AERMOD can account for turbulence both from wind shear and from buoyancy effects due to solar heating during the day and radiational cooling at night. To properly account for these effects, AERMOD requires three land use paras: albedo, Bowen ratio, and surface roughness. Modern planetary boundary layer theory is used to scale turbulence and other paras to the height of the plume. The AERMOD system (specifically, the AERMET meteorological preprocessor) derives hourly mixing heights based on the morning upper air sounding and the surface meteorology, including available solar radiation. The Role of Land Use Paras in AERMOD Three land use paras, albedo, Bowen ratio, and surface roughness length, are required by the AERMOD system to properly calculate turbulent dispersion

3 of air pollutants. The effects of these paras are accounted for in AERMET, the meteorological preprocessor portion of the AERMOD system. During convective (daytime) conditions, albedo, Bowen ratio, and surface roughness all play significant rolls in calculating the friction velocity and the Monin-Obukhov length. The proportion of the incoming solar radiation that is reflected back into space is defined by the albedo. Some of the remaining radiation is used to evaporate moisture from the ground and from plant leaf surfaces. The remaining 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 increasing dispersion, and indirectly by causing the mixing height to increase by altering the profiles of wind speed, turbulence, and other paras with height. Surface roughness affects the amount of drag the ground exerts on the wind. This creates shear which, in turn, generates turbulence, affects mixing height, and alters the profiles of various meteorological paras. 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 paras, albedo, Bowen ratio, and surface roughness length, on the resulting modeled design concentrations, AERMOD was run for each of four point sources for receptor distances ranging from 125 s to 16 kilos from the source. The land use paras were varied over a range that one might expect to encounter in real life modeling situations. All runs were made with one year of meteorology from a single site. The meteorology used in this exercise was from the surface observations at Wichita, KS, and the upper air (rawinsonde) observations from Topeka, KS, for the year 1987 and processed through 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 stack sources that could represent a small, medium, and large boiler, respectively. In all cases, the emission rate was set at 100 grams per second, and model output concentrations are given in micrograms per cubic. Table 1. Source characteristics Stack Height Stack Dia Gas Exit Velocity Gas Temperature The AERMET Users Guide (U.S. EPA 1 ) suggests values of albedo, Bowen ratio, and surface roughness length to be applied for eight different land use categories, by season of the year. The land use categories are water, deciduous forest, coniferous forest, swamp, cultivated land, grassland, urban, and desert shrubland.

4 In the first part of this study, all three paras were altered simultaneously. Because these paras are interrelated (e.g., a surface roughness length of , found only over water, cannot be combined with a Bowen ratio of 10, which represents a very dry surface), it would be inappropriate to combine them randomly. In order to retain realistic combinations of land use paras, four land use categories were selected from those given in the AERMET User s Guide (U.S. EPA 1 ). The recommended seasonal values of those land use paras were used as presented in Table 2. These include the most extreme values of albedo, Bowen ratio, and surface roughness, except for the extremely dry Bowen ratio for desert under the driest conditions (the Bowen ratios for average moisture conditions for all categories, including desert were used). Table 2. Land use paras used in the first part of the study (based on U.S. EPA 1 ) Season Land Use Land Use Winter Spring Summer Autumn Category Para Grassland Albedo Bowen Ratio Roughness Desert Albedo Bowen Ratio Conifer Forest Water Roughness Albedo Bowen Ratio Roughness Albedo Bowen Ratio Roughness In the second part of this study, one para was altered at a time, by selecting typical, minimum, and maximum values of albedo, Bowen ratio, and surface roughness 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 do provide a reasonable estimate of the range of conditions one might encounter in realistic modeling scenarios. Table 3 shows the values of albedo, Bowen ratio, and surface roughness length that were selected for each scenario. The Base Case represents approximate mid-range values of each para.

5 Table 3. Values of land use paras used in the second part of the study (based on ranges of values suggested in U.S. EPA 3 ). Scenario Albedo Bowen Ratio Roughness Length Base Case Low Albedo High Albedo Low Bowen Ratio High Bowen Ratio Low Roughness Length Low Roughness Length Analysis and Results AERMOD was applied to each source type, surface, 35- stack, 100- stack, and 200- stack, to produce estimates of design concentrations of interest for regulatory applications. The specific design concentrations of interest are the high-second high (HSH) 1-hour, 3-hour, and 24-hour concentrations, and the highest annual average concentration. The phrase high-second high refers to the highest of the second highest concentrations at each receptor, which is the criterion for most regulatory standards in the United States. These design concentrations were compared for four ground cover types, which provide a large range of combinations of the land use paras. The four types are grassland, desert, conifer forest, and water surface. The specific values of albedo, Bowen ratio, and surface roughness length are specified in Table 3 above. The design concentrations were also compared while varying individual paras between their lowest and highest tabulated values from the AERMET User s Guide (U.S. EPA 1 ). Surface Source Changes in ground cover cause changes in the design concentrations of approximately two orders of magnitude for all averaging times (see table 4). The highest concentrations occur with values of the land use paras appropriate for water, and the lowest with those appropriate to conifer forest. Results shown in tables 5-7 reveal that only the surface roughness length affects the design concentrations significantly. Tables 5 and 6 show that the albedo and Bowen ratio have little or no effect on the annual design concentrations. A close look at the results indicates that the high and high-second high concentrations for the 1- and 3-hour averaging times occurred at night. Albedo and Bowen ratio only affect the retention of incoming solar radiation, and therefore have no effect at night. Albedo has some slight effect on the model results for the 24-hour and annual design concentrations, because of the inclusion 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 of

6 magnitude (table 7). This accounts for the changes observed over the four ground cover types. This is reasonable, since the surface roughness length affects modeling in both daytime and nighttime conditions. The increased turbulence associated with higher roughness lengths increases the dispersion of the plume away from the centerline height (which is at ground level). 35- Stack The effects of ground cover type on the design concentrations for the 35- source are quite different from the effects for the surface source (table 4). The differences in the design concentrations are much smaller, with changes ranging from about a factor of two change for the 1-hour HSH to more than an order of magnitude change for the highest annual average. However, the water surface now provides the lowest design concentrations while the conifer forest provides the highest, the reverse of that seen with the surface source. Comparing the data in tables 5-7 reveals that all three land use paras are substantially affecting the design concentrations. This is to be expected, since all the design concentrations from the 35- stack occur near midday, when the land use paras have the greatest effect. Nevertheless, the effect of albedo on these concentrations (table 5) is still relatively small, with the design concentrations less 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 somewhat higher, though in the opposite direction. As table 6 shows, the design concentrations increase from a few percent for the 24-hour averaging time to about 50% for the annual average, as the Bowen ratio is increased from 0.1 (typical of a swamp, for example) to 10 (typical of a desert). The surface roughness length has the largest effect (table 7). The range from (smooth water) to 1.3 (conifer forest) increases concentrations by 40% for the 1-hour, a factor of two for the 3-hour, and by 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 increased dispersion resulting from the increased roughness transfers material away from the center of the plume, increasing concentrations at ground level. While the change is not orders of magnitude as seen with the surface source, it is still substantial Stack The effects of ground cover type on design concentrations from the 100 stack (table 4) are somewhat less, with highest and lowest values ranging from 17% to a factor of 7.2 different. The patterns for the 24-hour and annual design concentrations are similar to those of the 35- stack, with the highest design concentrations being associated with the conifer forest and the lowest with the water surface. However, the 1-hour and 3-hour design concentrations show the highest concentrations for the water surface and desert, respectively. This underscores the complex relationships between groundcover and dispersion, which makes the results seem sometimes counterintuitive. Changes in albedo (table 5) resulted in the design concentrations changing by as much as about 30%,

7 while the Bowen ratio (table 6) resulted in up to a factor of two difference and the roughness length (table 7) in up to a factor of three difference. Note that for one case, the 1-hour HSH, the mid-range value (base case) of the Bowen ratio produced a lower design concentration than either the highest or lowest Bowen ratio 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-hour and annual design concentrations, but less than a factor of two for the intermediate averaging times. Note that the four averaging times show the highest design concentrations from two of the four ground cover types, respectively. This further emphasizes the complexities of the relationships between the land use paras and concentrations. The sensitivity of design concentrations from the 200- stack to albedo (table 5) and Bowen ratio (table 6) are qualitatively similar to the case of the 100- stack for all but the 1-hour averaging time. The design concentrations decrease up to about 36% between the cases for the lowest and highest albedo. Interestingly, for the 1-hour case, the highest design concentration occurs with the mid-range value of the albedo. The effect of the Bowen ratio on design concentrations results in an increase of up to almost a factor of three. The sensitivity of design concentrations to surface roughness length appears even more complex. The 1-hour design concentration decreases by a factor of 2.4 as the roughness is increased from its minimum to its maximum value (table 7). The 3-hour design concentration shows a similar trend, with concentrations decreasing by 20% over the range of the roughness lengths. For the 24-hour case, the lowest design concentrations occurred with the lowest value of roughness length. For the annual average case, design concentrations 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 by AERMOD were studied. The effects that these paras have on the modeled design concentrations in AERMOD are sufficiently complex that it cannot be accurately anticipated what effect any changes in those values will have on design concentrations for a given source configuration. This study shows that modeled design concentrations can vary substantially due to normal ranges of variations in the albedo, Bowen ratio, and surface roughness length. Changes in albedo, Bowen ratio, and surface roughness length can result in changes in design concentrations of factors of 1.5, 2.6, and 160, respectively. Changes in design concentrations can be even greater when these paras are varied in combination, for example, by using paras characteristic of a swamp instead of those characteristic of a desert.

8 One can conclude that reasonably accurate estimates of albedo, Bowen ratio, and surface roughness lengths are necessary for AERMOD to provide accurate results. In particular, the suggested values of roughness length in the AERMET User s Guide (U.S. EPA 1 ), based on eight land use categories, may not be adequate to obtain the best possible concentration estimates from AERMOD. More detailed suggestions have appeared in the technical literature from time to time. Modelers are encouraged to make use of such recommendations if available. A more detailed sensitivity analysis would be required to determine whether the suggested values of albedo and Bowen ratio found in the U.S. EPA 1 should be improved upon as well. Table 4. Effects of ground cover type on design concentrations. Stack Ground Cover 1-hr HSH 3-hr HSH 24-hr HSH Annual Water Surface Grassland Desert Conifer Forest Water Grassland Desert Conifer Forest Water Grassland Desert Conifer Forest Water Grassland Desert Conifer Forest

9 Table 5. Effects of albedo on design concentrations. Stack Albedo 1-hr HSH 3-hr HSH 24-hr HSH Annual Base case Surface Low albedo High albedo Base case Low albedo High albedo Base case Low albedo High albedo Base case Low albedo High albedo Table 6. Effects of Bowen ratio on design concentrations. Table 7. Effects of surface roughness length on design concentrations. Stack Bowen Ratio 1-hr HSH 3-hr HSH 24-hr HSH Annual Surface Low Bowen High Bowen Low Bowen High Bowen Low Bowen High Bowen Low Bowen High Bowen Stack Roughness Length 1-hr HSH 3-hr HSH 24-hr HSH Annual Surface Low High Low High Low High Low High

10 Figure 1. BREEZE AERMET User Interface displaying site-specific land use paras. References 1. U.S. EPA, 1998: Revised Draft User s Guide for the AERMOD Meteorological Preprocessor (AERMET), U.S. Environmental Protection Agency.