WASTE MANAGEMENT, Vol. 13, pp. 97-101, 1993 0956-053X/93 $6.00 + .00 Printed in the U.S.A. All rights reserved. Copyright © 1993 Pergamon Press Ltd.

COMPUTERS

USING PC-BASED AIR DISPERSION MODELS TO PREDICT POLLUTANT CONCENTRATIONS

Laura Redmon and Dan Lipsher Trinity Consultants, Inc., 12801 N. Central Expressway, Suite 1200, Dallas, TX 75243, U.S.A.

EDITORIAL NOTE. Why a computer column? Because the new Editor-in-Chief wants one. Actually, the reason is not so simple. Bill Cawley and I feel that computers and PCs (and all the many capabilities that accompany them) are quickly becoming an integral part of today's society. Industrial-waste management professionals have to reflect that society to ad- dress the problems that arise from it, and they should utilize all the tools and technologies that society makes available to them in addressing these problems. Hopefully, this column will be a resource to you in addressing some of the problems you are facing.

I would like to address two audiences with this column. The first audience is that group of senior engineers, scientists, and managers who learned their trade and developed their work habits before the current proliferation of computers. I have noticed that this group has a reluctance to change established work methods, has trouble visualizing how effective a tool the computer can be in the work place, and has no place to become knowledgeable on the capabilities and uses of computers. Yet they are often the same people who are responsible for authorizing the purchase and use of computers for work group members. I would like this column to help them make an informed decision.

The second audience is that group of professionals who routinely use computers in their work. For them, I want this column to provide information on other methods of applying computers to the hazardous waste management area, includ- ing descriptions of environmentally oriented programs that are available from various sources. I also want this column to address the many diverse problems (not just those unique to waste management) that computers can be employed to handle within a professional work group.

To meet these goals I 'm going to need your help. I invite anyone who is interested to submit articles for inclusion in the column. The ground rules are to meet the goals as stated above with the addition that the article should not be a sales pitch. So, let me hear from you.

Now, on to what I will usually be doing, i.e., introducing this issue's article. One of the strengths of computers is math- ematical modeling, and as the capability of PCs increases so will the amount of modeling that is being conducted. This issue's article is an introduction to one use of PC-based models and the programs one company has developed that use them in the industrial-waste management field. I hope you find it interesting.--Tom Pinson

As a result o f federal and state regulations arising f rom the 1990 Clean Air Act Amendments , managers of industrial facilities must meet increasingly strin- gent reporting requirements in order to operate plants that emit air pollutants. A facility usually must obtain an air quality operating permit f rom the ap- propriate state or local regulatory agency, and if the pol lutant in question is federally controlled, compli- ance with national air quality standards must also be demonstra ted. Moreover, in geographic regions where specific air quali ty deficiencies exist (known as nona t t a inmen t areas), analyses must be performed to indicate a facility's contr ibut ion to the ambien t pol- lution levels in the a tmosphere. Finally, state and local air toxics regulations require the est imation of chronic risk associated with emissions of known car- cinogens or designated toxics.

Over the past 20 years, computer ized versions of

97

air dispersion models have been developed under the direction of the United States Environmenta l Protec- tion Agency (U.S. EPA) and private industry. PC- compat ib le versions of these models, such as the B R E E Z E series f rom Trinity Consultants, Inc., allow users with basic compute r skills and a sufficient sci- entific background to produce estimates of ground- level concentrat ions that result f rom pollutants re- leased to the atmosphere. These models take into account specific emission variables such as effluent flow rate, stack exit velocity, and release temperature, and use meteorological conditions generally repre- sented by an historical set of data to estimate concen- trations at user-specified receptor locations. The pre- dicted concentrat ions are averaged over a specific period of interest, ranging f rom one hour to several years. These concentrat ions are compared to regula- tory standards for ambien t air quality or to health risk

98 L. REDMON AND D. LIPSHER

levels expressed in terms of the probability of an in- dividual developing cancer (in the case of carcino- gens) as a result of exposure to a toxicant (1).

Waste management applications of air quality dis- persion models include predicting pollutant concen- trations from sludge ponds, landfills, and waste incin- erators. The emissions from sewage and chemical plant treatment ponds are generally modeled as area sources. Models such as the Industrial Source Com- plex-Short Term (ISCST2) and the Point Area Line (PAL) programs can be used to analyze these sources. Municipal landfills are primarily concerned with fu- gitive dust emissions. The Fugitive Dust Model (FDM) incorporates refinements of the algorithms in ISCST to predict both concentrations and total de- position of fugitives from point, area, and line sources. Incinerators produce emissions from a stack, which is represented as a point source in models such as ISCST2.

In a typical modeling application, an environmen- tal engineer at a large waste incinerator is charged with performing an air dispersion modeling analysis to calculate maximum pollutant concentrations of the chronic toxicant chromium. Modeled results can then be used to establish the waste feed limits or pol- lution control requirements for the facility, in com- pliance with local air toxics guidelines.

The air dispersion model most appropriate for this analysis is the Industrial Source Complex-Long Term (ISCLT2) model, developed by the U.S. EPA (2). The model uses three files to create a single input file con- taining parameters for the algorithms used to esti- mate ground-level concentrations. The source file (Fig. 1) contains data about the location, height, emis- sion rate, and size (diameter of a stack, square area,

or initial horizontal and vertical dimensions) of each source. The data file (Fig. 2) contains information about the receptors at which concentrations are to be calculated, regulatory options to be used in the model run, the period over which concentrations are to be averaged, meteorological data, and various output options. Finally, the model uses direction-specific di- mensions of structures in the vicinity of the source that will alter the wind flow, and thus ground-level concentrations of the modeled pollutant. To simplify the calculation of these building dimensions, Trinity has developed BREEZE WAKE (Fig. 3), which au- tomatically determines which buildings influence the wind flow around each source in each of 16 direc- tions.

In the present example, the facility's waste incin- erator (the source) is 70 ft tall, with a stack diameter of 1.5 ft. The emission rate for chromium is 0.05102 g/sec with an exit velocity of 5680.6 ft/min. The re- lease temperature is 145°F. The incinerator stack is located adjacent to a building that is 194.5 ft tall with a maximum width (i.e., longest diagonal) of 100 ft. The building will disturb the wind flow, affecting the plume, so building downwash is included in the anal- ysis.

The model is run with two receptor grids, centered around the source, to evaluate the distribution of chromium concentrations. In the coarse grid, recep- tors are spaced one km apart; in the fine grid, used to locate the point of maximum concentration, recep- tors are spaced at 100-m intervals.

The model results indicate a maximum annual chromium concentration of 0.019 #g/m 3, occurring 100 m west of the source. When compared with the l-in-10,000 and 1-in-100,000 cancer risk levels for

General Source In format ion

Src Source Source X-Coord. V-Coora. Base E l e v . He i gh t # T�pe <H> D e s c r i p t i o n (H) (H) (F t ) (F t )

1 '.~ I nc i n e r a t o r 362211.0 308674Z 1139.980 70, ~000 tacI

FIGURE 1. Example of a source data-entry screen in the B R E E Z E version of ISCLT.

U S I N G P C - B A S E D AIR D I S P E R S I O N M O D E L S 99

General Information

Number Of Source Groups NGBOUP Calculate Concentrations Or Depositions? <?> ISW(1) Concentrations Dispers ion Hode <T> ISM(2O) Urban Use Begulatory Defaul t Option7 ISW(ZS) Yes

Spec i fy Wake Option For Each Source?

Specify Gravitational Settling Categories?

Specify Scaling Factors For Each Source?

Use Annual STAR F i l e Only?

No

Ha

No

i~ i i~ i~ ~ ~t~iHiH! ~ i i i i i [ i i ] i [ ] ! i! l l ][ i i [ i ] i [ ]H~IHiii[ii I~H~H][[iii ~jIHtjHIiHi]iHiJ]I'I iiiiiiiii!iiiiii!!!~!~!~!~!i!iiiiiijiii!~i~i~i!iiiiii~!~!~i~ii!~*i!i!~i~!~!~!~!~!~!~!~!~iiiiiiiiii!!!~!r!i!i!~!~!i~iii~i!jiiii!i!!!~!~!!i@!!i~i!ii~i~i~i~!i!!!!!!!~!~i!~i~@i~!i!i!~!~!!!!!i!~!!~!i@ii~i~iii~!i!~!!!i!~!~!~!

FIGURE 2. Example of a data-entry screen in the BREEZE version of ISCLT. On this screen, the user specifies whether the model should use various regulatory default options or if parameters other than those specified by the EPA should be used.

chromium (0.00833 #g /m 3 and 0.000833 pg/m 3, re- spectively), it is apparent that the modeled facility's emissions of chromium are well above the acceptable risk levels established by the EPA ( 1 ).

Standard tabular output generated by Trinity's ISCLT model includes a representation of all of the input and meteorological data, the direction-specific building dimensions used for downwash analysis, and the annual ground-level concentrations at each recep- tor. An optional table also provides the 10 highest concentrations and the receptor locations for those

values. In order to increase the interpretive value of the modeling results, the user can generate multidi- mensional plots illustrating concentrations at recep- tor points, contouring of concentration values, and surface elevations. Figure 4, for example, shows a contour plot, using the fine grid, of the annual chro- mium concentrations surrounding the incinerator. Figure 5 superimposes risk levels on a post plot of chromium concentrations, indicating outlying areas at certain risk levels. (The area of impact of the l-in- 100,000 risk factor, 83.3 X 10 s #g /m 3, extends ap-

FIGURE 3. Example of a BREEZE WAKE data-entry screen. BREEZE WAKE automatically determines which buildings influence wind flow, and thus ground-level concentrations, from nearby sources.

100 L. R E D M O N A N D D. L I P S H E R

ANNUAL CHROMIUM CONCENTRATIONS -1 .10 -0 .93 -0 .75 -0 .58 -0 .40 - 0 2 3 -0.05 0.13 0.30 0.48 0.65 0.83 1.00

1,00 ~ I I F ' ~ I / I / I I I I I I ~ 1 1 I I I I I ] ~ 1.00 v

% 0,83 ~ ~ 0.83

0.65 0.65

0.1,5 0.13

-0 .05 0.05

£ -0.23 / 0.23

-0 .40 "%° -0 .40

-0 .75 -0 .75

-0 .93 - 0 9 3

- 1 . 1 0 1 1 I I I I I ~ / ~ I I I I I I I ~ , L _1.10 -1 10 -0.93 -075 ~058 - 0 4 0 -023 -0.05 0.13 0.30 0.48 0.65 0.83 1.00

KILOMETERS EAST

FIGURE 4. Plot of the fine receptor grid ( 100-m spacing) used in the example. The plot indicates the concentration isopleths as well as the property boundary. On-property receptors were removed with a utility included in the graphics package. Note: All concentrations and contour levels must be divided by 100,000 to obtain micrograms per cubic meter.

ANNUAL CHROMIUM CONCENTRATIONS - 1 1 0 0 -9 ,25 - 7 5 0 5.75 -4 .00 225 - 0 5 0 1.25 3.00 4.75 6.50 8.25

10.00 I I I I I I I I --I I I [ I I I I I I I I I I I 0 .0 .0 .0 0 .0 .0 .0 .0 .0 .0 0 .0 .0 .0 o. 0 0 0 .0

8.25 0 .0 0 .0 0 .0 .0 .0 .0 0 ~0 .0 .0 0 .o o. 0 0 .0 0

680 10 10 ~.0--- ~N ~ " ~ \ 1 0 to 1.0 1 .0 \~4~ p 10 17 1.0,,,,,,~ 0 0 0 0 0 0 0

10 10 10 10 10 10 10 10 10 10 10 10 10 0 1 10 0 0 0 0

10 10 10 10 10 10 10 10 10 10 0 0 0

3.00 10 10 1.0 10 20 20 20 20 20 20 20 20 10 1.0 1.0 10 .~ 0 0 0 X ' x 10 10 20 20 20 20 30 50 30 30 40 30 20 10 10 10 10~x~10

~0 1.25 1 2 4 0 0 1 1 1

r - 20 20 20 30 30 40 60 1 40 20 20 10 10 10

2; ;0 2o io io 2o , 0 - ,io ,;o ~,o 1; 50 20 20 ~o ,; 1;

~' L . . . . . . . . . . . . . . . . . -2 .25 10 20 20 20 30 40 50 ~ 4 0 20 20 10 1.0 19 1,

~_//10 20 20 20 20 50 30 30 30 20 30 20 20 20 10 10 10 10 1

-4 .00 1 10 10 20 20 20 20 20 20 20 20 20 20 10 10 10 10 10 10 1

10 10 10 10 20 20 20 10 10 10 20 10 10 10 10 10 10 10 1

-5 .75 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1,

10 10 10 10 10 10 10 10 10 10 10 10 1 ~ 0 ~ 1 D 10 1' 33"rl . . . . . . . . . . . . .~J .

/o ; ;T- ,o , o lO , o , o lO ,o o o o o

1 l 10 10 10 10 10 0 0 c l / 110 10 1 0 0 0 0 0 0 0 0 0

10 10 10 10 0 0 0 0 10 10 10 0 0 0 0 0 0 0 0

- 11 O 0 I I I I I I ~ [ l I - 1 1 . 0 0 -9 .25 - 7 50 5 7 5

10.00 10.00

8.25

6.50

4.75

3.00

1.28

-0.50

-2.25

-4 .00

-5.78

-7 .50

-9 .25

- I 1 0 0 -4 .00 2.25 - 0 5 0 1.25 3 O0 4.75 6.50 8.25 10.00

KILOMETERS EAST

FIGURE 5. Post plot showing concentrations at the coarse-grid receptor locations superimposed with contours indicating the area where concentrations exceed acceptable risk values. Note: All concentrations and contour levels must be divided by 100,000 to obtain micrograms per cubic meter. 8.33 contour represents l : 1,000,000 risk level; 83.3 contour represents l: 100,000 risk level.

USING PC-BASED AIR DISPERSION MODELS 101

ANNUAL CHROMIUM CONCENTRATIONS 1.10 - 0 9 3 -0.75 -0.58 -0.40 -0.23 -0.05 0.13 0 . 3 0 0.48 06~ 0.8.3 1.OC

1.00 I l I I I I I ~" I I I I I ] I I N~---------~ [ f I I 120 110 120 120 120 110 tO0 110 120 130 1,1.0 1.50 110 100 90 80 8D 80 70

0.65 190 200 200 2]0 200 2]0 200 190 190 2!0 240 2]0 170 160 150 140 1.30 1]C 100 90~ 1 065

220 2.30 250 26O 2,60 2-60 2-6O 2.40 2]0 260 2.90 250 290 1.90 180 160 140 120 110 9O 0.48

2-6O 2.70 2.90 3]0 330 340 3.30 3.30 2.90 3]0 370 3]0 250 2:'0 2]0 1.80 1.60 I:C ~.20 ~00

0..}0 3]0 `3.30 3-60 3-80 4]0 4:'0 ',-80 4-60 '-!0 3.7o 4.90 3.90 `3-30 2.90 2-60 2!o ~.7o ~:O ~?0 1!0

3-60 ,a.0 4:'0 4-80 5.30 ~-60 5-30 4~0 3-60 290 2?0 2O0 ~,70 ~-80 L3o

410 '$60 530 600 680 760 8 480 380 310 250 210 170 150

4-60 520 6!0 710 8 ~ , ~ 500 370 2.90 23C 1901-60

450 5!0 590 6-80 7~91.0 ~0401 , .50124~*~ / / 490 4]0 340 2.70 230 190 160 f

,.30 ,,'90 5-60 6:'o ~'4o ' ~ ~ ' - ~ . o 6,7o ,,:'0 ,.70 ,,!o 3-60 2'9o 2.5o 2]0 ,.8o ,.6o

4!o ,.70 5?0 590 6.so 690 7]0 6-80 5:'0 490 5.20 3-60 3.60 3.90 `3:'0 2.80 2:'0 2 ~ ~,7o ~.~o

390 ,?o 4-60 5o0 5?0 5-60 .~:'0 ,,-80 ..,-60 3?0 ,,,:'0 3.:,0 2.7o 3]0 `3.20 2.7o 2.30 2.Oc ~90 Lso

3-60 `3.70 490 420 4.30 A,~ 4.00 3.30 2'40 3]0 .}.70 2'90 220 2:'0 2~0 2'60 2.20 1.90 170 ~:'0

`3]0 ,320 3:'0 3~0 3'60 3.30 300 2'40 2.20 2.70 `3]0 2'60 290 1.90 200 2]0 2] 0 1.~0 1-60 140

2.70 2.80 2-80 2.9o 2-60 2,60 220 ~70 190 2.30 27o 2.20 1-60 Lso 1-60 L70 ~.70 ~,7c ~-60 ~}0

2.30 2'40 2:'0 #.30 2.2o 2o0 1,70 ~'4o LTo 2o0 2.~o 2o0 ~,6o ~.3o ~.zo ~fo ~:'o ~:'o ,fo 1.3o

2.oo 2.0o 20o ~.90 ~0 1-60 ~.20 ~0 ~-60 1.60 20o ~,70 ~-60 ~.20 1]0 ~.20 1.20 1.20 1.20 ~20

170 170 1,70 1-60 1'40 1.20 100 1.20 1'40 1~0 1,70 1~0 1.30 1] 0 90 100 I.O0 1] c 110 110

I I I I I I ] I [ I I I I I I ] / ~ J ; I I I -O.93 -0.75 -0.58 - 0 4 0 -0.23 -0.05 0. t3 0.30 0.48 0.65 0.83

K I L O M E T E R S E A S T

I 0.13

-0.05

0 0 .23

0 4 0

-0.58

- 0 . 9 3

-1.10 -11,

C.48

C.30

- - C . 1 3

-0 05

-0.23

0.40

-0.58

-- -0.75

- - -0.93

-1 10 1.00

FIGURE 6. Post plot showing the area where concentrations exceed acceptable risk levels for the fine receptor grid. Note." All concentrations and contour levels must be divided by 100,000 to obtain micrograms per cubic meter. 8.33 contour represents 1 : 1,000,000 risk level; 83.3 contour represents 1:100,000 risk level.

proximately 2.55 km from the source.) Finally, Fig. 6 shows the areal extent of the l-in-10,000 risk level, which extends 470 m from the source.

Computer models such as ISCLT can perform the iterative calculations necessary to estimate concen- trations from numerous sources at hundreds of recep- tors in a fraction of the time in which they could be solved by hand. And modeling the effects of a pollut- ant release is far more economical than measuring ac- tual concentrations: a computerized model run can be set up and executed for a small percentage of the cost of placing ambient air quality instrumentation and a network of receptors around a source.

Trinity Consultants' BREEZE line of dispersion modeling software adds a user-friendly interface, graphics capability, and postprocessing utilities to models available from the EPA. The BREEZE HAZ models include products such as DEGADIS+ for dense gas releases, SPILLS for ground-level liquid re- leases, and INPUFF for "instantaneous" releases of hazardous pollutants. The BREEZE WAY models comprise a line of products for use in mobile source emissions studies such as CALINE3 (for emissions

near roadways), CAL3QHC (for emissions near sig- nalized intersections), and MOBILE5.1 (for emis- sions produced by gasoline- and diesel-powered ve- hicles). The BREEZE AIR models include products such as ISC2, COMPLEX-I (which predicts concen- trations in areas of complex terrain), and SCREEN (for screening analyses of pollutant releases). All of these models operate on 80286-, 80386-, and 80486- based personal computers, can take advantage of the increased processing capabilities of math coproces- sors, and come with comprehensive documentation. BREEZE software is used by regulatory agencies, in- dustrial companies of all sizes, and air quality con- sultants around the world.

REFERENCES

1. U.S. EPA. Cancer Risk from Outdoor Exposure to Air Toxics, Vol. 1. Office of Air Quality Planning and Standards, document reference number EPA-450/1-90-004a (1990).

2. U.S, EPA. Guideline on Air Quality Models (Revised). Office of Air and Radiation and Office of Air Quality Planning and Stan- dards, document reference number EPA-450/2-78-027R (1986).

Open for discussion until 30 April 1993.