Inhalation of Fugitive Dust:

A Screening Assessment of the Risks Posed by

Coal Combustion Waste Landfills

DRAFT

U.S. Environmental Protection Agency

Office of Solid Waste and Emergency Response

1200 Pennsylvania Avenue, N.W.

Washington, DC 20460

 May 2010
This draft document has been prepared by the Office of Resource Conservation and Recovery in 

the U.S. Environmental Protection Agency (EPA). Any opinions, findings, conclusions, or 

recommendations do not change or substitute for any statutory or regulatory provisions. This 

document does not impose legally binding requirements, nor does it confer legal rights, impose 

legal obligations, or implement any statutory or regulatory provisions. Mention of trade names or 

commercial products is not intended to constitute endorsement or recommendation for use. This 

document is being provided to other government agencies and to the public. As a draft, EPA may 

change any part of this document in the future, as appropriate. 

 
Table of Contents 

Section Page 

1.0 Introduction............................................................................................2 

 

2.0 Inhalation of CCW Emitted from Landfilling Operations.......................................3 

 

2.1 Initial Scenario...............................................................................4 

 

2.2 Emission Factors.............................................................................4 

 

2.3 Length/Width, Distance to Receptor.......................................................5 

 

2.4 Other Input Parameters for SCREEN3....................................................6 

 

2.5 SCREEN3 Outputs..........................................................................7 

 

3.0 Secondary Scenarios..................................................................................7 

 

3.1 Model Runs and Outputs....................................................................9 

 

4.0 Results and Discussion.............................................................................10 

 

4.1 Controls Applied Yearly...................................................................11 

 

4.2 Controls Applied Monthly................................................................11 

 

4.3 Controls Applied Weekly.................................................................11 

 

4.4 Controls Applied Daily....................................................................11 

 

5.0 Conclusion............................................................................................11 

6.0 References............................................................................................13 

 

Appendix A Landfill Size Data........................................................................A-1 

 

Appendix B Distance to Receptor Data...............................................................B-1 

 

Appendix C Sensitivity of Results to Inputs.........................................................C-1 

 

Appendix D SCREEN3 Model Runs..................................................................D-1 

 

Appendix E Excerpts from the SCREEN3 Manual.................................................E-1 

 

 
 
1.0 Introduction

Inhalation of Fugitive Dust is intended to be a companion document to the U.S. Environmental

Protection Agency’s (EPA) 2009 Human and Ecological Risk Assessment of Coal Combustion

Wastes (U.S. EPA, 2009). In 2007, EPA released its draft risk assessment (U.S. EPA, 2007).

This document was released to a panel of five peer reviewers, and to the public via a notice of

data availability (NODA) in the Federal Register.1In both the peer review and NODA, EPA

received comments regarding fugitive dust. These comments pointed out that fugitive dust

emissions during the operation of a coal combustion waste (CCW) management unit (WMU)

were not addressed in the draft risk assessment (RA). However, since there was anecdotal

evidence that fugitive dust was often emitted from WMUs, EPA decided to examine the potential

for uncontrolled emissions from dry handling to lead to significant human health risks.

Figure 1 and Figure 2

Fugitive dust associated with CCW landfilling operations.

Top: Gambrills, MD; Bottom: Four Corners, NM.2

1 Docket ID: EPA-HQ-RCRA-2006-0796. Document ID: EPA-HQ-RCRA-2006-0796-0042.

2

Photos courtesy of Lisa Evans, Earthjustice

 

2
2.0 Inhalation of CCW Emitted from Landfilling Operations

When dry-handled, CCW will be emitted into the air by loading, transport, unloading, and wind

erosion. Once in the air, it will likely migrate off-site as fugitive dust. As a result, workers and

nearby residents could be exposed to significant amounts of coarse particulate matter (PM10) and

fine particulate matter (PM2.5). The purpose of this assessment is therefore to assess whether the

national ambient air quality standards (NAAQS) for particulate matter could be violated through

CCW landfilling operations3 without fugitive dust controls. This will be accomplished through a

conservative screening analysis. Figure 3 below shows the conceptual model for the type of

landfilling operation relevant here. If the inhalation pathway cannot be screened out, then it is

possible for fugitive dust to pose a threat to human health, and regulation addressing fugitive

dust should be considered. Conversely, if the inhalation pathway can be screened out, then it is

highly unlikely that the inhalation of particulates from CCW landfills poses a significant risk to

human health. However, there are two uncertainties inherent in this bright line screen evaluated

in this report. First, there may be background levels of particulates which, when added to the

levels calculated here may still pose significant risks. Second, it would still be possible for

constituents adsorbed onto CCW particulates to pose a risk to human health. This screening

evaluation does not address either background levels of particulates or a constituent-based

exposure pathway.

Figure 3 – Fugitive Dust Conceptual Model for Dry Handling of CCW

Source Release, Fate, & Transport Exposure Pathways Receptors

Transportation of

CCW from Power

Plant to Landfill

Loading of CCW at

Power Plant

Unloading of CCW at

Landfill

Storage of CCW at

Landfill

Loading Particulate

Emissions

Inhalation

Human:

Resident

Nearby

Landfill

Transportation

Particulate Emissions

Unloading Particulate

Emissions

Windblown Particulate

Emissions

Human:

Resident

Nearby

Roadway

Human:

Resident

Nearby

Power Plant

Inhalation

Inhalation

Human:

Worker

Inhalation

Inhalation

3 This does not include activities such as minefilling, reclamation of sand and gravel pits, or beneficial use.

 

3
2.1 Initial Scenario

Three groups of residents are likely to be exposed to fugitive dust as a result of the dry handling

of CCW.4 Residents living near a coal power plant could be exposed to emissions resulting from

loading of the CCW. Residents near roads could be exposed to emissions during transportation.

Finally, residents living near CCW landfills could be exposed from both the unloading and

windblown emissions.

Residents living near a CCW landfill will often be exposed to more fugitive dust, and for longer

periods of time, than those living near the roads or power plants themselves. This is the case

because these residents would be exposed to emissions from both unloading of CCW and

windblown emissions of CCW. Thus, only the residents living near CCW landfills will be

considered further as they represent a highly exposed population. In addition, as a landfill gets

closer to capacity, the less relative influence unloading emissions would have on total emissions.

In the preliminary scenario considered, the entire landfill is left exposed to wind until the end of

its useful life. Thus, windblown emissions could be considered representative of total emissions

as they would dominate.

To estimate the concentration of fugitive dust in the air near a CCW landfill, the SCREEN3

model was used.

5

SCREEN3 (a screening version of ISC3) is a single source Gaussian plume

model which provides maximum ground-level concentrations for point, area, flare, and volume

sources. It was developed to provide an easy-to-use method of obtaining pollutant concentration

estimates based on Screening Procedures for Estimating the Air Quality Impact of Stationary

Sources (U.S. EPA, 1995c). A technical description of the SCREEN3 model is provided in

Appendix E. The SCREEN3 outputs will then be compared to the relevant NAAQS as presented

in Table 1 below.

Table 1 – NAAQS for Particulate Matter

Pollutant Standard Averaging Time

PM10 150 g m-324-hour

PM2.5 15.0 g m-3 Annual

PM2.5 35 g m-324-hour

See 40 C.F.R. 506

2.2 Emission Factors

In order to model the concentration of the particulate matter in the air, it is necessary to estimate

the emission rate for the CCW managed in landfills. A point estimate for the windblown

emission factor was calculated below using the equation for “Continuous Fugitive/Windblown

Dust Emissions” (U.S. EPA, 1992):

4 Workers who handle CCW would also be exposed to fugitive dust, but they are protected by OSHA regulations.

5

SCREEN3 is publicly available at http://www.epa.gov/scram001/dispersion_screening.htm

6 NAAQS available at http://www.epa.gov/air/criteria.html

 

4
 











 















235 15

365

1.5

1.9

s p w

E

where:

E = emission factor (kg d-1ha-1)

s = material silt content (%)

p = number of days per year with more than 25 mm of precipitation (N/A)

w = percent of time wind speed exceeds 5.4 m s-1(%)

The material silt content of 80% for fly ash was taken from Table 13.2.4-1 in AP-42, chapter 13

(2006). The default values in the workbook (U.S. EPA, 1992) of 0 for p and 20% for w were

used in calculating this emission factor. The result (209.85 kg d-1ha-1) was converted to g s-1m

-2

,

with a final emission rate of 2.43 x 10-4g s-1 m

-2

. While there are likely a range of emission

factors, this screening assessment was not designed to evaluate all possible fugitive dust

scenarios. Rather, the purpose is only to see if fugitive dust from dry-handling of CCW would

likely pose a significant risk to human health. Thus, EPA believes its use of a best estimate

emission factor is appropriate.

2.3 Length/Width, Distance to Receptor

Two other factors necessary to model fugitive dust are the length/width of the landfill and the

distance to the receptor. Unlike the emission factor, EPA decided to use a range for these inputs.

While it would have been possible to use a point estimate, there were orders of magnitude of

difference between the smallest and largest CCW landfills and between the shortest and furthest

distances to receptors. Thus, EPA used a range of percentiles to model the upper end of

particulate matter that could reasonably be expected in the air breathed by a receptor. In keeping

with the conservative nature of this assessment, the 50th through 90th percentiles of size and

10th through 50th percentiles of distance were used. The maximum size and minimum distance

were excluded as they would be too conservative to be considered reasonable.

To be as realistic as possible, EPA based the landfill dimensions on actual CCW landfill data

provided by the Council of Industrial Boiler Owners (CIBO, 1997) and Electric Power Research

Institute (EPRI, 1997). Of the data available in those reports, 124 WMUs were landfills. These

landfills were arranged to form a size distribution (in acres), and percentiles were calculated.

These can be seen in Table 2 below. These distributions were converted from acres into square

meters. The assumption was then made that the landfills were square. This allowed the

calculation of the length and width of the landfills, reported as the side length in Table 2 below.

For a further discussion of the landfill size distribution, see Appendix A – Landfill Size Data.

Table 2 – Distribution of Landfill Sizes

Percentile in Acres in m2 side length (m)

50th 66.5 269,116 518.8

60th 85.0 343,983 586.5

70th 121.4 491,288 700.9

80th 208.4 843,365 918.3

90th 297.6 1,204,344 1,097.4

Raw data and percentiles are provided in Appendix A.

 

5
Distance to the nearest receptor, on the other hand, was not based on actual CCW landfill

distances as no such data exists. While EPA acknowledges that this data would be useful, there

is not sufficient time and resources to collect this data. Instead, because the receptors of interest

are residents living near a CCW landfill, it is assumed that the distribution of closest receptors

here would be the same as the distribution used in the RA. These can be seen in Table 3 below.

For a further discussion of the landfill size distribution, see Appendix B – Distance to Receptor

Data.

Table 3 – Distribution of Receptor Distances

Percentile Distance (m)

10th 104

20th 183

30th 305

40th 366

50th 427

Further discussion and percentiles are provided in Appendix B.

Taken together, the combinations of sizes and distances to be modeled will attempt to provide

both a true median (50th, 50th) and upper tail (90th, 10th) of the input distribution that would be

modeled in a probabilistic assessment. Thus, although the model itself has a conservative bias,

the results endeavor to present both a typical and upper tail risk.

2.4 Other Input Parameters for SCREEN3

In addition to the emission rates, the following input parameters are also required for the

SCREEN3 modeling runs.

 Source Type: Area was chosen because the emissions would be coming off a

landfill and not from a smokestack or other point source.

 Height of CCW Landfill: A height of 0m was chosen based on the assumption

that the landfill would be dug into the ground, and not elevated. It was also a

conservative assumption as elevated landfills actually generate lower particulate

matter emissions for nearby receptors. This issue is addressed further in

Appendix C.

 Receptor Height: 1.75m was chosen to be protective of a typical human receptor.

(This is approximately the height in meters of a 5’9” individual.) This assumption

is addressed further in Appendix C.

 Urban or Rural: Rural was chosen because CCW landfills are much more likely

to be located in a rural setting. In addition, it is more conservative than the urban

option. This issue is addressed further in Appendix C.

 Search for Maximum Direction: A positive setting was chosen as a conservative

assumption so that the maximum air concentration would be located.

SCREEN3 requires the user to specify the modeling area. This area is the range of distances

from the center of the source where SCREEN3 will estimate maximum concentrations. For this

 

6
study, the modeling area was defined as the region from 0 to 1,500m (just under a mile) from the

center of the source to ensure that the 50th percentile distance listed above would be included. In

addition, there is a user option to specify discrete distances. These are specific distances from

the center of the source where the user can request SCREEN3 to estimate maximum

concentrations. This specific distance is the distance to the receptor that is chosen from the

distribution in Table 3 above.

Table 4 – Input parameters for SCREEN3

Parameter Description Value

Source type Area

Emission rate (g/s-m

2

) 0.0002431

Height of storage pile (m) 0

Length of storage pile (m) Variable2

Width of storage pile (m) Variable2

Receptor height (m) 1.75

Urban or Rural Rural

Search for maximum direction Yes

Choice of meteorology Full

Automated distance array Yes

Minimum distance (m) 0

Maximum distance (m) 1500

Use discrete distances Yes

Distance (m) Variable3

1 Calculated using the workbook (U.S. EPA, 1992)

2 Based on EPRI landfill size data (EPRI, 1995)

3 Based on landfill to well distances (U.S. EPA, 1988)

2.5 SCREEN3 Outputs

Using the inputs listed in Table 2, 3, and 4, SCREEN3 was used to estimate the concentration of

CCW in the air at ground level under the windblown erosion scenario. After running the model

with both 50th percentile values plugged in, a result of 13,390g m-3 was obtained. Since the

values generated by SCREEN3 are maximum values, they should be compared to the 24-hour

NAAQS. However, even under the assumption that 100% of the CCW was PM10, this would still

violate the 24-hour NAAQS for PM10 of 150 g m-3by nearly two orders of magnitude. This

indicates that the risks posed by fugitive dust cannot be screened out if no dust controls are

applied before closure, and therefore it was unnecessary to run the screen with other percentiles.

3.0 Secondary Scenarios

Given that the risks of uncontrolled fugitive dust emissions could not be screened out, the next

logical question was whether or not the risks given particular management options could be

screened out. Perhaps covering or spraying the CCW on a regular basis to prevent emissions

 

7
could be adequate to protect human health. The appropriate question then is how frequently

these controls should be applied to ensure the NAAQS are not exceeded. Some possible time

frames might be yearly, monthly, weekly, and daily. To model these scenarios, caveats and

additional information are required. First, assuming that a landfill is operated consistently over

its life time, the life will affect how much of the landfill is being used over any period of time.

In a previous groundwater risk assessment, EPA estimated that the operating life of a CCW

landfill is 40 years (U.S. EPA, 1998a). EPA believes that this is still an accurate estimate, and

thus, it is assumed for this assessment that all landfills will operate for 40 years. Since a landfill

is assumed to operate consistently over a 40-year life, then the area of the landfill that is operated

during any year can be stated as:

40

total

yr

A

A 

where:

Ayr = the area of the landfill in use over a year (m2)

Atotal = the total landfill capacity (m2)

40 = life of a CCW landfill (N/A)

Once the portion of the WMU used over a single year is estimated, then it is also possible

calculate the area of the landfill used monthly, weekly, and daily as follows:

12

yr

month

A

A 

52

yr

wk

A

A 

365

yr

d

A

A 

where:

Amonth = the area of the landfill in use over a month (m2)

Awk = the area of the landfill in use over a week (m2)

Ad = the area of the landfill in use over a day (m2)

Ayr = the area of the landfill in use over a year (m2)

12 = the number of months in one year (N/A)

52 = the number of weeks in one year (N/A)

365 = the number of days in one year (N/A)

Performing these calculations on each percentile from Table 2 above, the areas and side lengths

for the portion of the WMU operated over each period of time is as follows:

Table 5 – Area (m2) and Side (m) Distributions

Yearly Monthly Weekly Daily

%ile Area Side Area Side Area Side Area Side

50th 6,728 82.0 561 23.7 129 11.4 18 4.3

60th 8,600 92.7 717 26.8 165 12.9 24 4.9

70th 12,282 110.8 1024 32.0 236 15.4 34 5.8

80th 21,084 145.2 1757 41.9 405 20.1 58 7.6

90th 30,109 173.5 2509 50.1 579 24.1 82 9.1

All values based on assumption that a WMU operates consistently for 40 years.

 

8
Here again, the size of the operating portion of the landfill is assumed to be a square, so each

side is the square root of the area. One final assumption that must be made is the location of this

operating portion of the landfill with respect to the receptor. For simplification, it will be

assumed that the operating portion is in the very center of the landfill. Using the center will give

results that estimate an average concentration over the entire lifetime of the landfill for a receptor

located in any direction. This assumption is consistent with EPA’s previous risk assessment

where the air pathway was modeled (U.S. EPA, 1998b).

3.1 Model Runs and Outputs

The model was first run entering the 50th percentile values for both side length and distance to

receptor. If this median exposure could not be screened, then higher risk scenarios were not

evaluated. The results of these screens are presented in Table 6 below.

Table 6 – Median Scenario Outputs (g m-3)

Period Particulates Pass Screen? 1

Yearly 1388 NO

Monthly 159.4 NO

Weekly 38.0 YES

Daily 5.4 YES

1 The screen was passed if the NAAQS would not be exceeded.

Since weekly and daily controls for fugitive dust passed the screen using the median scenario

inputs, further permutations of inputs were entered into the model to determine the likelihood

that operating with this frequency of controls would be adequate to protect human health. These

results are reported in Tables 7 and 8 below.

Table 7 – SCREEN3 Outputs (μg m

-3

), Weekly Fugitive Dust Controls

Distance to Nearest Receptor

Landfill Size 50th 40th 30th 20th 10th

50th 38.0 44.3 52.5 78.3 107.5

60th 44.9 51.9 60.9 88.4 118.4

70th 56.6 64.3 74.2 104.0 134.6

80th 78.0 87.1 98.1 129.1 159.5

90th 95.9 105.9 117.8 149.1 178.4

See Appendix D for raw inputs and outputs.

 

9
4.0 Results and Discussion

As seen in Tables 6, 7, and 8, the risks posed by fugitive dust inhalation could not be screened

out for every management time frame. However, certain conclusions can be drawn for each

management consideration. The discussion of each time frame is below, but should be

interpreted with several overarching uncertainties in mind.

 The SCREEN3 model is a conservative screening model. Thus, in most instances, the

levels of particulate matter calculated here are likely higher than they actually would be.

 As the area of the landfill exposed to wind erosion decreases due to more frequent

controls, unloading emissions would become a much more significant proportion of total

emissions. Hence, the more frequently controls are used, the more important it would be

to include unloading emissions to calculate an accurate concentration.

 Background levels of particulates were not factored into these calculations. Thus, the

particulates calculated here could actually underestimate total particulates.

 The distances to the nearest receptor are not based on recent CCW landfill survey data

and may therefore lead to an underestimate or overestimate of particulate levels.

 In the secondary scenarios, the operating portion of the landfill was assumed to be in the

center of the landfill and not on the downwind edge. This may lead to an underestimate

of particulate levels when that edge portion is used.

 A single emission factor was calculated based on national default inputs. For particular

sites, the calculated emission factor could be higher or lower.

Finally, there are a few general trends between the inputs and outputs examined in Appendix C.

With respect to the location of WMUs, those located in rural settings will cause much higher

particulates concentrations than those in urban settings. Since a rural setting was assumed here,

it is possible that some WMUs would present much lower risks to human health through the

inhalation of fugitive dust. In addition, it was shown that landfills that are built up, as opposed to

dug into the ground, would actually lead to lower particulates concentrations nearby. Thus, in

the case of built up landfills, nearby residents would be presented with less risk than what was

modeled here. However, receptors may be at ground level, presenting slightly higher risks.

Table 8 – SCREEN3 Outputs (μg m-3), Daily Fugitive Dust Controls

Distance to Nearest Receptor

Landfill Size 50th 40th 30th 20th 10th

50th 5.4 6.4 7.6 11.3 15.7

60th 6.5 7.6 8.9 13.0 17.6

70th 8.1 9.2 10.7 15.1 19.7

80th 11.3 12.7 14.3 19.0 23.6

90th 13.9 15.42 17.2 21.9 26.4

See Appendix D for raw inputs and outputs.

 

10
4.1 Controls Applied Yearly

Even at the median risk, yearly management leads to a PM10 concentration almost an order of

magnitude above the NAAQS. Although larger landfills and closer receptors were not modeled,

they would have resulted in even higher exceedences. Therefore, controls applied only at the

end of each operating year fail the screen, and have the potential to pose a significant risk to

human health.

4.2 Controls Applied Monthly

At the median risk, monthly management leads to a PM10 concentration barely above the

NAAQS. Although larger landfills and closer receptors were not modeled, they too would have

resulted in exceedences. Consequently, controls applied each operating month fail the screen as

run, and have the potential to pose a significant risk to human health.

4.3 Controls Applied Weekly

At the median risk, weekly management did not exceed the NAAQS for PM10. Only if most or

all of the particulates were PM2.5 would there be any exceedance. However, this is not the case

because CCW typically consists of only a few percent of PM2.5 (EPRI, 1995). When larger

landfills and closer receptors were modeled, most did not result in excess risk. Only when

receptors were within the closest 10% of the distribution (within about 100m), and landfill sizes

were large (over about 200 acres) did levels above the NAAQS result. Thus, in isolation, it is

relatively likely that the median would not lead to excessive levels of particulates but that the

upper tail could. Thus, the results are mixed, and it is uncertain whether these emissions alone

would have the potential to pose a significant risk to human health.

4.4 Controls Applied Daily

At the median risk, daily management did not exceed the NAAQS for PM10 or PM2.5. Even when

larger landfills and closer receptors were modeled, most concentrations fell well below the

NAAQS. Taken in isolation, it is certain that neither the median nor the upper-tail scenario

would lead to excessive levels of particulates. Thus, without considering background levels, a

weekly fugitive dust control would be sufficient to protect human health.

5.0 Conclusion

The purpose of this screening assessment was to determine whether the NAAQS could be

violated through dry handling of CCW, and if so, what management options might be

appropriate. Indeed, it was found that there is not only a possibility, but a strong likelihood that

dry-handling would lead to the NAAQS being exceeded absent fugitive dust controls. Yearly

and monthly controls were also found to have the potential to lead to significant risks. However,

with this screen, it was uncertain whether weekly controls would have the potential to cause

NAAQS exceedences, and even the most conservative evaluation of daily dust controls led to

particulate concentrations well below the NAAQS. Thus, without further, more precise

 

11
evaluation, only daily controls can definitively be said not to cause excess levels of particulates

in isolation.

 

12
6.0 References

CIBO (Council of Industrial Boiler Owners). 1997. Report to the U.S. Environmental

Protection Agency on Fossil Fuel Combustion Byproducts form Fluidized Bed Boilers. Prepared

by the CIBO Special Project on Non-Utility Fossil Fuel Ash Classification and ICF Kaiser

Consulting Group. November.

EPRI (Electric Power Research Institute). 1995. Coal Ash Disposal Manual (3rd Edition).

EPRI, Palo Alto, CA. January.

EPRI (Electric Power Research Institute). 1997. Coal Combustion By-Products and LowVolume Wastes Comanagement Survey. EPRI, Palo Alto, CA. June.

U.S. EPA (Environmental Protection Agency). 1988. National Survey of Solid Waste

(Municipal) Landfill Facilities (Draft). EPA/530-SW88-034. Office of Solid Waste and

Emergency Response, Washington, DC. S September.

U.S. EPA (Environmental Protection Agency). 1992. Workbook of Screening Techniques for

Assessing Impacts of Toxic Air Pollutants. EPA-454/R-92-024. Office of Air Quality Planning

and Standards, Research Triangle Park, NC.

U.S. EPA (Environmental Protection Agency). 1995a. Compilation of Air Pollutant Emission

Factors: Volume I: Stationary Point and Area Sources. Available at

http://www.epa.gov/ttn/chief/ap42/index.html.

U.S. EPA (Environmental Protection Agency). 1995b. SCREEN3 Model User's Guide. EPA

Document no. EPA-454/B-95-004. Available at

http://www.epa.gov/scram001/userg/screen/screen3d.pdf.

U.S. EPA (Environmental Protection Agency). 1995c. Screening Procedures for Estimating the

Air Quality Impact of Stationary Sources, Revised. EPA Document no. EPA-450/R-92-019.

U.S. EPA (Environmental Protection Agency). 1998a. Technical Background Document for the

Supplemental Report to Congress on Remaining Fossil Fuel Combustion Wastes: Ground-Water

Pathway Human Health Risk Assessment (Revised Draft Final). Office of Solid Waste,

Washington, DC 20460. June.

U.S. EPA (Environmental Protection Agency). 1998b. Non-groundwater Pathways, Human

Health and Ecological Risk Analysis for Fossil Fuel Combustion Phase 2 (Draft Final Report).

Office of Solid Waste, Washington, DC 20460. June.

U.S. EPA (Environmental Protection Agency). 2007. Human and Ecological Risk Assessment

of Coal Combustion Wastes (Draft). Office of Solid Waste, Washington, DC 20460. August.

U.S. EPA (Environmental Protection Agency). 2009. Human and Ecological Risk Assessment

of Coal Combustion Wastes (Draft). Office of Solid Waste, Washington, DC 20460. September.

 

13
Appendix A – Landfill Size Data

The source of the data provided below was the compiled data set of CCW landfills and surface

impoundments from Appendix B of the RA (U.S. EPA, 2007). That data set was derived from

two voluntary industry surveys. The first was an EPRI comanagement survey for conventional

utility coal combustion WMUs (EPRI, 1997). The second was a CIBO fluidized bed combustion

(FBC) survey for FBC WMUs (CIBO, 1997). The EPRI survey included responses from 323

WMUs. These WMUs served 238 power plants in 36 states, and represented 62 million tons of

CCW disposal annually. The CIBO survey included 45 responses from the estimated 84

facilities using FBC technology. While most of these facilities reported beneficially using CCW,

8 of those facilities reported disposing of CCW, and those that landfilled were included in this

analysis.

Rank LF Acres

1 3.4

2 4

3 4.61

4 8

5 9

6 9

7 10

8 11.77391

9 12

10 12

11 13

12 14

13 14

14 15

15 16.4

16 17

17 17

18 18

19 18

20 20

21 20

22 21.3

23 22

24 22

25 22

26 23

27 25

28 25.24

29 25.75

30 26

31 26

32 27

33 28.68322

 

A-1
34 30

35 30

36 30

37 33

38 35

39 36

40 36

41 37

42 38

43 39

44 40

45 40

46 40

47 41.2

48 45

49 45

50 48

51 49.20163

52 51

53 54

54 55

55 57

56 58

57 60

58 60

59 60

60 61

61 61

62 65

63 68

64 68

65 69

66 70

67 70

68 70

69 72

70 79

71 80

72 80

73 85

74 85

75 85

76 96

77 96

78 99

79 100

80 100

81 105

 

A-2
82 106

83 109

84 110

85 112.5

86 120

87 121

88 125

89 125

90 128.6242

91 130

92 150

93 155

94 174

95 176

96 200

97 200

98 200

99 206

100 212

101 220

102 230

103 241

104 246

105 247

106 250

107 250

108 255

109 280

110 290

111 292

112 300

113 300

114 309

115 312

116 315

117 320

118 339

119 400

120 434

121 540

122 596

123 825

124 900

 

A-3
Percentile in Acres in m2 side (m)

Min 3.4 13,759 117.3

5th 10.3 41,545 203.8

10th 14.3 57,870 240.6

15th 18.9 76,486 276.6

20th 22.6 91,459 302.4

25th 26.8 108,253 329.0

30th 34.8 140,831 375.3

35th 40.0 161,874 402.3

40th 48.2 195,222 441.8

45th 58.7 237,550 487.4

50th 66.5 269,116 518.8

55th 71.3 288,541 537.2

60th 85.0 343,983 586.5

65th 104.8 423,908 651.1

70th 121.4 491,288 700.9

75th 159.8 646,485 804.0

80th 208.4 843,365 918.3

85th 248.7 1,006,251 1,003.1

90th 297.6 1,204,344 1,097.4

95th 336.2 1,360,351 1,166.3

Max 900.0 3,642,170 1,908.4

 

A-4
Appendix B – Distance to Receptor Data

The residential scenario for the fugitive dust pathway analysis calculates exposure from a CCW

landfill’s emissions to the air. The receptor distances used were based on the distances used for

residential wells in the RA (U.S. EPA, 2007). This assumes that the residence closest to a

landfill would be the same residence that has the closest downgradient well. EPA believes this

to be an adequately protective assumption since the closest distance is less than a meter, or

directly against the edge of a landfill.

The well distances themselves were derived from sampling a nationwide distribution of the

nearest downgradient residential well distances taken from a survey of municipal solid waste

landfills (U.S. EPA, 1988). EPA recognizes that this is a significant uncertainty in the analysis.

Based on an assumption that population densities around CCW landfills are roughly comparable

to population densities that existed near the municipal landfills surveyed in U.S. EPA (1988),

EPA believes that the MSW well distance distribution is a roughly representative of actual

distances between CCW landfills and nearby residences. However, since not all residences have

downgradient wells, there could be closer residences in other instances. While further data on

the distances to the nearest residence would be useful to the analysis, such data is not readily

available at this time.

Distribution of Receptor Distances

Percentile Distance (m)

Min 0.6

10th 104

20th 183

30th 305

40th 366

50th 427

60th 610

70th 805

80th 914

90th 1,220

Max 1,610

Source: U.S. EPA (1988)

 

B-1
 

B-2
Appendix C – Sensitivity of Results to Inputs

Several assumptions about WMUs were made in Section 2.4. Among these were three

assumptions that do not always hold true. The first was that WMUs will be located in rural

locations. In fact, some coal power plants are located in or adjacent to major metropolitan areas.

Second, it was assumed that the landfills would be dug into the ground, and would therefore have

a height of 0m. However, there are landfills that are built up meters or tens of meters. Finally, it

was assumed that the receptor was a standing individual of a typical height. Yet, this ignores

situations where individuals are sitting, laying down, or even where infants are crawling.

Therefore, to ensure that the model remained properly conservative, further runs were conducted

to determine what affect (if any) altering these inputs would have on the modeled particulate

matter concentrations.

The assumptions made in the actual screen turned out to be conservative, with the exception of

the receptor height. As seen in the table below, air particulate matter concentrations in an urban

setting tend to be much lower than those in a rural setting. Also evident is that piles that elevated

tend to decrease the air concentrations to nearby receptors. However, the receptor at 0m would

have slightly elevated particulates concentrations. While these tend to be very small percentage

changes, they could underestimate the particulates lower receptors would be exposed to.

Comparison of Outputs Changing Rural/Urban and Height Inputs (μg m-3)

Percentiles

(size/distance) as Modeled in Urban Setting with 10mHeight

with 0m

Receptor

50/50 5.4 0.6 3.6 6.8

60/40 7.6 0.8 4.8 7.7

70/30 10.7 1.1 6.8 10.8

80/20 19.0 1.9 11.9 19.3

90/10 26.4 2.7 17.8 26.8

All outputs were calculated under the daily management scenario

 

C-1
 

C-2
Appendix D – SCREEN3 Model Runs

The SCREEN3 model was run a total of 65 times to generate the data in this report. Below are

the inputs and outputs for each model run. Table D.1 lists all of the common inputs used for all

65 model runs and Tables D.2 through D.7 list all of the uncommon inputs and the resulting

outputs for each combination. It is important to note that the discrete distances entered here were

calculated by adding the distance from the center of the landfill to the edge and the distance from

the edge of the landfill to the receptor. The distance from the center of the landfill to the edge of

the landfill was 1⁄2 the side length from the Table 2 distribution, and the distance from the edge of

the landfill to the receptor was the Table 3 distribution.

Table D.1 – Common Inputs for SCREEN3

Parameter Description Common Value

Source type Area

Emission rate (g/s-m

2

) 0.0002431

Height of storage pile (m) 02

Receptor height (m) 1.75

Urban or Rural Rural3

Search for maximum direction Yes

Choice of meteorology Full

Automated distance array Yes

Minimum distance (m) 0

Maximum distance (m) 1500

Use discrete distances Yes

1 Calculated using the workbook (U.S. EPA, 1992).

2 10m was selected for the five model runs in Table D.6.

3 Urban was selected for the five model runs in Table D.7.

Table D.2 – Variable Inputs and Outputs for Whole WMU Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

518.8 518.8 686.4 13,390

Table D.3 – Variable Inputs and Outputs for Table 6 Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

82.0 82.0 686.4 1388

23.7 23.7 686.4 159.4

11.4 11.4 686.4 38.0

4.3 4.3 686.4 5.4

 

D-1
Table D.4 – Variable Inputs and Outputs for Table 7 Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

11.4 11.4 606.4 38.0

12.9 12.9 720.3 44.9

15.4 15.4 777.5 56.6

20.1 20.1 886.2 78.0

24.1 24.1 975.7 95.9

11.4 11.4 625.4 44.3

12.9 12.9 659.3 51.9

15.4 15.4 716.5 64.3

20.1 20.1 825.2 87.1

24.1 24.1 914.7 105.9

11.4 11.4 564.4 52.5

12.9 12.9 598.3 60.9

15.4 15.4 655.5 74.2

20.1 20.1 764.2 98.1

24.1 24.1 853.7 117.8

11.4 11.4 442.4 78.3

12.9 12.9 476.3 88.4

15.4 15.4 533.5 104.0

20.1 20.1 642.2 129.1

24.1 24.1 731.7 149.1

11.4 11.4 363.4 107.5

12.9 12.9 397.3 118.4

15.4 15.4 454.5 134.6

20.1 20.1 563.2 159.5

24.1 24.1 652.7 178.4

 

D-2
Table D.5 – Variable Inputs and Outputs for Table 8 Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

4.3 4.3 606.4 5.4

4.9 4.9 720.3 6.5

5.8 5.8 777.5 8.1

7.6 7.6 886.2 11.3

9.1 9.1 975.7 13.9

4.3 4.3 625.4 6.4

4.9 4.9 659.3 7.6

5.8 5.8 716.5 9.2

7.6 7.6 825.2 12.7

9.1 9.1 914.7 15.42

4.3 4.3 564.4 7.6

4.9 4.9 598.3 8.9

5.8 5.8 655.5 10.7

7.6 7.6 764.2 14.3

9.1 9.1 853.7 17.2

4.3 4.3 442.4 11.3

4.9 4.9 476.3 13.0

5.8 5.8 533.5 15.1

7.6 7.6 642.2 19.0

9.1 9.1 731.7 21.9

4.3 4.3 363.4 15.7

4.9 4.9 397.3 17.6

5.8 5.8 454.5 19.7

7.6 7.6 563.2 23.6

9.1 9.1 652.7 26.4

Table D.6 – Variable Inputs and Outputs for Urban Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

4.3 4.3 606.4 0.6

4.9 4.9 659.3 0.8

5.8 5.8 655.5 1.1

7.6 7.6 642.2 1.9

9.1 9.1 652.7 2.7

 

D-3
Table D.7 – Variable Inputs and Outputs for 10m Height Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

4.3 4.3 606.4 3.6

4.9 4.9 659.3 4.8

5.8 5.8 655.5 6.8

7.6 7.6 642.2 11.9

9.1 9.1 652.7 17.8

Table D.8 – Variable Inputs and Outputs for 0m Receptor Runs

Length of Storage Pile (m) Width of Storage Pile (m) Distance (m) Output (μg m-3)

4.3 4.3 606.4 6.8

4.9 4.9 659.3 7.7

5.8 5.8 655.5 10.8

7.6 7.6 642.2 19.3

9.1 9.1 652.7 26.8

 

D-4
Appendix E – Excerpts from the SCREEN3 Manual

The following excerpts selected below have been taken from the SCREEN3 Model User’s Guide

(U.S. EPA, 1995b). Pages 43-56 provide a technical description of the air modeling equations

that are used by SCREEN3.

 

E-1
43

3. TECHNICAL DESCRIPTION

Most of the techniques used in the SCREEN model are based on

assumptions and methods common to other EPA dispersion models.

For the sake of brevity, lengthy technical descriptions that are

available elsewhere are not duplicated here. This discussion

will concentrate on how those methods are incorporated into

SCREEN and on describing those techniques that are unique to

SCREEN.

3.1 Basic Concepts of Dispersion Modeling

SCREEN uses a Gaussian plume model that incorporates sourcerelated factors and meteorological factors to estimate pollutant

concentration from continuous sources. It is assumed that the

pollutant does not undergo any chemical reactions, and that no

other removal processes, such as wet or dry deposition, act on

the plume during its transport from the source. The Gaussian

model equations and the interactions of the source-related and

meteorological factors are described in Volume II of the ISC

user's guide (EPA, 1995b), and in the Workbook of Atmospheric

Dispersion Estimates (Turner, 1970).

The basic equation for determining ground-level

concentrations under the plume centerline is:

 X = Q/(2%us)y)z){exp[-1⁄2((zr-he)/)z)2]

 + exp[-1⁄2((zr+he)/)z)2]

 k

 +( [ exp[-1⁄2((zr-he-2Nzi)/)z)2] N=1

 + exp[-1⁄2((zr+he-2Nzi)/)z)2]

 + exp[-1⁄2((zr-he+2Nzi)/)z)2]

 + exp[-1⁄2((zr+he+2Nzi)/)z)2] ] } (1)

where:

 X = concentration (g/m3)

 Q = emission rate (g/s)

 % = 3.141593

 us = stack height wind speed (m/s)

)y = lateral dispersion parameter (m)

)z = vertical dispersion parameter (m)

 zr = receptor height above ground (m)

 he = plume centerline height (m)

 zi = mixing height (m)

 k = summation limit for multiple reflections of plume

off of the ground and elevated inversion, usually

4.

 

E-2
44

Note that for stable conditions and/or mixing heights greater

than or equal to 10,000m, unlimited mixing is assumed and the

summation term is assumed to be zero.

Equation 1 is used to model the plume impacts from point

sources, flare releases, and volume releases in SCREEN. The

SCREEN volume source option uses a virtual point source approach,

as described in Volume II (Section 1.2.2) of the ISC model user's

guide (EPA, 1995b). The user inputs the initial lateral and

vertical dimensions of the volume source, as described in Section

2.7 above.

The SCREEN model uses a numerical integration algorithm for

modeling impacts from area sources, as described in Volume II

(Section 1.2.3) of the ISC model user's guide (EPA, 1995b). The

area source is assumed to be a rectangular shape, and the model

can be used to estimate concentrations within the area.

3.2 Worst Case Meteorological Conditions

SCREEN examines a range of stability classes and wind speeds

to identify the "worst case" meteorological conditions, i.e., the

combination of wind speed and stability that results in the

maximum ground level concentrations. The wind speed and

stability class combinations used by SCREEN are given in Table 

2. The 10-meter wind speeds given in Table 2 are adjusted to

stack height by SCREEN using the wind profile power law exponents

given in Table 3-1 of the screening procedures document. For

release heights of less than 10 meters, the wind speeds listed in

Table 2 are used without adjustment. For distances greater than

50 km (available with the discrete distance option), SCREEN sets

2 m/s as the lower limit for the 10-meter wind speed to avoid

unrealistic transport times. Table 2 includes some cases that may

not be considered standard stability class/wind speed

combinations, namely E with winds less than 2 m/s, and F with

winds greater than 3 m/s. The combinations of E and winds of 1 -

1.5 m/s are often excluded because the algorithm developed by

Turner (1964) to determine stability class from routine National

Weather Service (NWS) observations excludes cases of E stability

for wind speeds less than 4 knots (2 m/s). These combinations

are included in SCREEN because they are valid combinations that

could appear in a data set using on-site meteorological data with

another stability class method. A wind speed of 6 knots (the

highest speed for F stability in Turner's scheme) measured at a

typical NWS anemometer height of 20 feet (6.1 meters) corresponds

to a 10 meter wind speed of 4 m/s under F stability. Therefore

the combination of F and 4 m/s has been included.

E-3
45

______________________________________________________________________________

_________________

 | |

 | Table 2. Wind Speed and Stability Class Combinations |

 | |

 | Used by the SCREEN Model |

|_____________________________________________________________________________

________________|

 | | |

 | | 10-m Wind Speed |

 | Stability | (m/s) |

 | Class | 1 1.5 2 2.5 3 3.5 4 4.5 5 8 10 15 20 |

|____________|_________________________________________________________________

_______________|

 | | |

 | A | * * * * * |

 | | |

 | B | * * * * * * * * * |

 | | |

 | C | * * * * * * * * * * * |

 | | |

 | D | * * * * * * * * * * * * * |

 | | |

 | E | * * * * * * * * * |

 | | |

 | F | * * * * * * * |

|____________|_________________________________________________________________

_______________|

The user has three choices of meteorological data to

examine. The first choice, which should be used in most

applications, is to use "Full Meteorology" which examines all six

stability classes (five for urban sources) and their associated

wind speeds. Using full meteorology with the automated distance

array (described in Section 2), SCREEN prints out the maximum

concentration for each distance, and the overall maximum and

associated distance. The overall maximum concentration from

SCREEN represents the controlling 1-hour value corresponding to

the result from Procedures (a) - (c) in Step 4 of Section 4.2. 

Full meteorology is used instead of the A, C, and E or F subset

used by the hand calculations because SCREEN provides maximum

E-4
46

concentrations as a function of distance, and stability classes

A, C and E or F may not be controlling for all distances. The

use of A, C, and E or F may also not give the maximum

concentration when building downwash is considered. The second

choice is to input a single stability class (1 = A, 2 = B, ..., 6

= F). SCREEN will examine a range of wind speeds for that

stability class only. Using this option the user is able to

determine the maximum concentrations associated with each of the

individual procedures, (a) - (c), in Step 4 of Section 4.2. The

third choice is to specify a single stability class and wind

speed. The last two choices were originally put into SCREEN to

facilitate testing only, but they may be useful if particular

meteorological conditions are of concern. However, they are not

recommended for routine uses of SCREEN.

The mixing height used in SCREEN for neutral and unstable

conditions (classes A-D) is based on an estimate of the

mechanically driven mixing height. The mechanical mixing height,

zm (m), is calculated (Randerson, 1984) as

 zm = 0.3 u*/f (2)

where: u* = friction velocity (m/s)

 f = Coriolis parameter (9.374 x 10-5 s-1 at 40( latitude)

Using a log-linear profile of the wind speed, and assuming a

surface roughness length of about 0.3m, u* is estimated from the

10-meter wind speed, u10, as

 u* = 0.1 u10 (3)

Substituting for u* in Equation 2 we have

 zm = 320 u10. (4)

The mechanical mixing height is taken to be the minimum daytime

mixing height. To be conservative for limited mixing

calculations, if the value of zm from Equation 3 is less than the

plume height, he, then the mixing height used in calculating the

concentration is set equal to he + 1. For stable conditions, the

mixing height is set equal to 10,000m to represent unlimited

mixing.

3.3 Plume Rise for Point Sources

The use of the methods of Briggs to estimate plume rise are

discussed in detail in Section 1.1.4 of Volume II of the ISC

user's guide (EPA, 1995b). These methods are also incorporated

in the SCREEN model.

Stack tip downwash is estimated following Briggs (1973, p.4)

E-5
47

for all sources except those employing the Schulman-Scire

downwash algorithm. Buoyancy flux for non-flare point sources is

calculated from

 Fb = gvsds2(Ts-Ta)/(4Ts), (5)

which is described in Section 4 of the screening procedures

document and is equivalent to Briggs' (1975, p. 63) Equation 12.

Buoyancy flux for flare releases is estimated from

 

 Fb = 1.66 x 10-5 x H, (6)

where H is the total heat release rate of the flare (cal/s). This

formula was derived from Equation 4.20 of Briggs (1969), assuming 

Ta = 293K, p = 1205 g/m, cp = 0.24 cal/gK, and that the sensible

heat release rate, QH = (0.45) H. The sensible heat rate is

based on the assumption that 55 percent of the total heat

released is lost due to radiation (Leahey and Davies, 1984). The

buoyancy flux for flares is calculated in SCREEN by assuming

effective stack parameters of vs = 20 m/s, Ts = 1,273K, and

solving for an effective stack diameter, ds = 9.88 x 10-4(QH)0.5.

The momentum flux, which is used in estimating plume rise

for building downwash effects, is calculated from,

 Fm = vs2ds2Ta/(4Ts). (7)

The ISC user's guide (EPA, 1995b) describes the equations

used to estimate buoyant plume rise and momentum plume rise for

both unstable/neutral and stable conditions. Also described are

transitional plume rise and how to estimate the distance to final

rise. Final plume rise is used in SCREEN for all cases with the

exception of the complex terrain screening procedure and for

building downwash effects.

The buoyant line source plume rise formulas that are used

for the Schulman-Scire downwash scheme are described in Section

1.1.4.11 of Volume II of the ISC user's guide (EPA, 1995b). 

These formulas apply to sources where hs  Hb + 0.5Lb. For

sources subject to downwash but not meeting this criterion, the

downwash algorithms of Huber and Snyder (EPA, 1995b) are used,

which employ the Briggs plume rise formulas referenced above.

3.4 Dispersion Parameters

The formulas used for calculating vertical ()z) and lateral

()y) dispersion parameters for rural and urban sites are

described in Section 1.1.5 of Volume II of the ISC user's guide

(EPA, 1995b).

3.5 Buoyancy Induced Dispersion

E-6
48

Throughout the SCREEN model, with the exception of the

Schulman-Scire downwash algorithm, the dispersion parameters, )y

and )z, are adjusted to account for the effects of buoyancy

induced dispersion as follows:

 )ye = ()y2 + (h/3.5)2)0.5 (8)

 )ze = ()z2 + (h/3.5)2)0.5

where h is the distance-dependent plume rise. (Note that for

inversion break-up and shoreline fumigation, distances are always

beyond the distance to final rise, and therefore h = final plume

rise).

3.6 Building Downwash

3.6.1 Cavity Recirculation Region

The cavity calculations are a revision of the procedure

described in the Regional Workshops on Air Quality Modeling

Summary Report, Appendix C (EPA, 1983), and are based largely on

results published by Hosker (1984).

If non-zero building dimensions are input to SCREEN for

either point or flare releases, then cavity calculations will be

made as follows. The cavity height, hc (m), is estimated based

on the following equation from Hosker (1984):

 hc = hb (1.0 + 1.6 exp (-1.3L/hb)), (9)

where: hb = building height (m)

 L = alongwind dimension of the building (m).

Using the plume height based on momentum rise at two building

heights downwind, including stack tip downwash, a critical (i.e.,

minimum) stack height wind speed is calculated that will just put

the plume into the cavity (defined by plume centerline height =

cavity height). The critical wind speed is then adjusted from

stack height to 10-meter using a power law with an exponent of

0.2 to represent neutral conditions (no attempt is made to

differentiate between urban or rural sites or different stability

classes). If the critical wind speed (adjusted to 10-meters) is

less than or equal to 20 m/s, then a cavity concentration is

calculated, otherwise the cavity concentration is assumed to be

zero. Concentrations within the cavity, Xc, are estimated by the

following approximation (Hosker, 1984):

 Xc = Q/(1.5 Ap u) (10)

where: Q = emission rate (g/s)

 Ap = Hb·W = cross-sectional area of the building normal

to the wind (m2)

E-7
49

 W = crosswind dimension of the building (m)

 u = wind speed (m/s).

For u, a value of one-half the stack height critical wind speed

is used, but not greater than 10 m/s and not less than 1 m/s. 

Thus, the calculation of Xc is linked to the determination of a

critical wind speed. The concentration, Xc, is assumed to be

uniform within the cavity.

The cavity length, xr, measured from the lee side of the

building, is estimated by the following (Hosker, 1984):

 (1) for short buildings (L/hb  2),

 xr = (A)(W) (11)

 1.0 + B(W/hb)

 (2) for long buildings (L/hb  2), 

 xr = 1.75 (W) (12)

 1.0 + 0.25(W/hb)

where: hb = building height (m)

 L = alongwind building dimension (m)

 W = crosswind building dimension (m)

 A = -2.0 + 3.7 (L/hb)-1/3, and

 B = -0.15 + 0.305 (L/hb)-1/3.

The equations above for cavity height, concentration and

cavity length are all sensitive to building orientation through

the terms L, W and Ap. Therefore, the entire cavity procedure is

performed for two orientations, first with the minimum horizontal

dimension alongwind and second with the maximum horizontal

dimension alongwind. For screening purposes, this is thought to

give reasonable bounds on the cavity estimates. The first case

will maximize the cavity height, and therefore minimize the

critical wind speed. However, the Ap term will also be larger and

will tend to reduce concentrations. The highest concentration

that potentially effects ambient air should be used as the

controlling value for the cavity procedure.

3.6.2 Wake Region

The calculations for the building wake region are based on

the ISC model (EPA, 1995b). The wake effects are divided into

two regions, one referred to as the "near wake" extending from

3Lb to 10Lb (Lb is the lesser of the building height, hb, and

maximum projected width), and the other as the "far wake" for

distances greater than 10Lb. For the SCREEN model, the maximum

projected width is calculated from the input minimum and maximum

E-8
50

horizontal dimensions as (L2 + W2)0.5. The remainder of the

building wake calculations in SCREEN are based on the ISC user's

guide (EPA, 1995b).

It should be noted that, unlike the cavity calculation, the

comparison of plume height (due to momentum rise at two building

heights) to wake height to determine if wake effects apply does

not include stack tip downwash. This is done for consistency

with the ISC model.

3.7 Fumigation

3.7.1 Inversion Break-up Fumigation

The inversion break-up screening calculations are based on

procedures described in the Workbook of Atmospheric Dispersion

Estimates (Turner, 1970). The distance to maximum fumigation is

based on an estimate of the time required for the mixing layer to

develop from the top of the stack to the top of the plume, using

Equation 5.5 of Turner (1970):

 xmax = u tm

= (u pa cp/R) (/z) (hi - hs) [(hi + hs)/2] (13)

where:

 xmax = downwind distance to maximum concentration (m)

 tm = time required for mixing layer to develop from top of

stack to top of plume(s)

 u = wind speed (2.5 m/s assumed)

 pa = ambient air density (1205 g/m3 at 20(C)

 cp = specific heat of the air at constant pressure (0.24

cal/gK)

 R = net rate of sensible heating of an air column by

solar radiation (about 67 cal/m2/s) /z = vertical potential temperature gradient (assume 0.035

K/m for F stability)

 hi = height of the top of the plume (m) = he + 2)ze (he is

the plume centerline height)

 hs = physical stack height (m).

 )ze = vertical dispersion parameter incorporating buoyancy

induced dispersion (m)

The values of u and /z are based on assumed conditions of

stability class F and stack height wind speed of 2.5 m/s for the

stable layer above the inversion. The value of hi incorporates

the effect of buoyancy induced dispersion on )z, however, elevated

terrain effects are ignored. The equation above is solved by

iteration, starting from an initial guess of xmax = 5,000m.

The maximum ground-level concentration due to inversion

break-up fumigation, Xf, is calculated from Equation 5.2 of Turner

(1970).

E-9
51

Xf = Q/[(2%)0.5u()ye+he/8)(he+2)ze)] (14)

where Q is the emission rate (g/s), and other terms are defined

above. The dispersion parameters, )ye and )ze, incorporate the

effects of buoyancy induced dispersion. If the distance to the

maximum fumigation is less than 2000m, then SCREEN sets Xf = 0

since for such short distances the fumigation concentration is not

likely to exceed the unstable/limited mixing concentration

estimated by the simple terrain screening procedure.

3.7.2 Shoreline Fumigation

For rural sources within 3000m of a large body of water,

maximum shoreline fumigation concentrations can be estimated by

SCREEN. A stable onshore flow is assumed with stability class F

(/z = 0.035 K/m) and stack height wind speed of 2.5 m/s. 

Similar to the inversion break-up fumigation case, the maximum

ground-level shoreline fumigation concentration is assumed to

occur where the top of the stable plume intersects the top of the

well-mixed thermal internal boundary layer (TIBL).

An evaluation of coastal fumigation models (EPA, 1987b) has

shown that the TIBL height as a function of distance inland is

well-represented in rural areas with relatively flat terrain by an

equation of the form:

 hT = A [x]0.5 (15)

where: hT = height of the TIBL (m)

 A = TIBL factor containing physics needed for TIBL

parameterization (including heat flux) (m1⁄2)

 x = inland distance from shoreline (m).

Studies (e.g. Misra and Onlock, 1982) have shown that the TIBL

factor, A, ranges from about 2 to 6. For screening purposes, A is

conservatively set equal to 6, since this will minimize the

distance to plume/TIBL intersection, and therefore tend to

maximize the concentration estimate.

As with the inversion break-up case, the distance to maximum

ground-level concentration is determined by iteration. The

equation used for the shoreline fumigation case is:

 xmax = [(he + 2)ze)/6]2 - xs (16)

where: 

 xmax = downwind distance to maximum concentration (m)

 xs = shortest distance from source to shoreline (m)

 he = plume centerline height (m)

 )ze = vertical dispersion parameter incorporating buoyancy

induced dispersion (m)

Plume height is based on the assumed F stability and 2.5 m/s wind

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52

speed, and the dispersion parameter ()ze) incorporates the effects

of buoyancy induced dispersion. If xmax is less than 200m, then no

shoreline fumigation calculation is made, since the plume may

still be influenced by transitional rise and its interaction with

the TIBL is more difficult to model.

The maximum ground-level concentration due to shoreline

fumigation, Xf, is also calculated from Turner's (1970) Equation

5.2:

Xf = Q/[(2%)0.5u()ye+he/8)(he+2)ze)] (14)

with )ye and )ze incorporating the effects of buoyancy induced

dispersion.

Even though the calculation of xmax above accounts for the

distance from the source to the shoreline in xs, extra caution

should be used in interpreting results as the value of xs

increases. The use of A=6 in Equations 15 and 16 may not be

conservative in these cases since there will be an increased

chance that the plume will be calculated as being below the TIBL

height, and therefore no fumigation concentration estimated. 

Whereas a smaller value of A could put the plume above the TIBL

with a potentially high fumigation concentration. Also, this

screening procedure considers only TIBLs that begin formation at

the shoreline, and neglects TIBLs that begin to form offshore.

3.8 Complex Terrain 24-hour Screen

The SCREEN model also contains the option to calculate

maximum 24-hour concentrations for terrain elevations above stack

height. A final plume height and distance to final rise are

calculated based on the VALLEY model screening technique (Burt,

1977) assuming conditions of F stability (E for urban) and a stack

height wind speed of 2.5 m/s. Stack tip downwash is incorporated

in the plume rise calculation.

The user then inputs a terrain height and a distance (m) for

the nearest terrain feature likely to experience plume impaction,

taking into account complex terrain closer than the distance to

final rise. If the plume height is at or below the terrain height

for the distance entered, then SCREEN will make a 24-hour average

concentration estimate using the VALLEY screening technique. If

the terrain is above stack height but below plume centerline

height, then SCREEN will make a VALLEY 24-hour estimate (assuming

F or E and 2.5 m/s), and also estimate the maximum concentration

across a full range of meteorological conditions using simple

terrain procedures with terrain "chopped off" at physical stack

height, and select the higher estimate. Calculations continue

until a terrain height of zero is entered. For the VALLEY model

concentration SCREEN will calculate a sector-averaged ground-level

concentration with the plume centerline height (he) as the larger

of 10.0m or the difference between plume height and terrain

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53

height. The equation used is

 X = 2.032 Q exp [-0.5(he/)ze)2]. (17)

 )ze u x

Note that for screening purposes, concentrations are not

attenuated for terrain heights above plume height. The dispersion

parameter, )ze, incorporates the effects of buoyancy induced

dispersion (BID). For the simple terrain calculation SCREEN

examines concentrations for the full range of meteorological

conditions and selects the highest ground level concentration.

Plume heights are reduced by the chopped off terrain height for

the simple terrain calculation. To adjust the concentrations to

24-hour averages, the VALLEY screening value is multiplied by

0.25, as done in the VALLEY model, and the simple terrain value is

multiplied by the 0.4 factor used in Step 5 of Section 4.2.

3.9 Non-regulatory Options

 3.9.1 Brode 2 Mixing Height Option

The Brode 2 Mixing Height (Brode, 1991) option calculates a

mixing height that is calculated based on the calculated plume

height, the anemometer height wind speed and a stability-dependent

factor which is compared to a stability-dependent minimum mixing

height. The algorithm is expressed as:

 ZI = MAX (ZImin, HE*(1.0 + ZIfact * U10)

where ZImin is 300m for A, 100m for B, and 30m for both C and D

stabilities, and ZIfact is 0.01 for A, 0.02 for B, 0.03 for C, and

0.04 for D stability. Brode found that the results of using this

algorithm appear to provide a fairly consistent level of

conservatism relative to the ISCST model.

 3.9.2 Variable Anemometer Height Option

The anemometer height is used in adjusting the wind speed to 

stack height wind speed for cavity calculations based on the

following power law function:

 U0 = U0TEN*(AMAX1(10,HS)/ZREF)**0.20

 U1 = U1TEN*(AMAX1(10,HS)/ZREF)**0.20

 where: U0TEN - initial wind speed value set to 20 m/s.

 U1TEN - initial wind speed value set to 1 m/s.

 HS - stack height

 ZREF - anemometer height

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54

U0TEN is adjusted downward in speed and U1TEN is adjusted upward

in speed in an iterative process until the minimum wind speed, UC,

that will entrain the plume into a building's cavity is found. 

The critical wind speed is then adjusted to the anemometer height,

using the reverse of the power law above, as follows: 

 UC10M = UC * (ZREF/AMAX1(10,HS))**0.20

where: UC10M - represents the critical wind speed at 

 anemometer height, ZREF.

The variables HANE and ZREF are used interchangeably.

 3.9.3 Schulman-Scire Building Downwash/Cavity Option

A non-regulatory building downwash/cavity algorithm (Schulman

and Scire,1993) has been added as a non-regulatory option. This

option is based on the diffusing plume approach with fractional

capture of the plume by the near-wake recirculation cavity. 

Extensive parameterization is used to define a building

length scale, roof recirculation cavity, maximum height of the

roof cavity, and the length of the downwind recirculation cavity

(as measured from the lee face of the building). 

A building length scale for flow and diffusion is defined as:

R = BS exp(2/3) * BL exp(1/3)

where: BS is the smaller of the building height and

projected width for the minimum side orientation

BL is the larger of the building height and projected

width for the maximum side orientation.

The length of the roof recirculation cavity is estimated as:

LC = 0.9 * R

The roof cavity will reattach to the roof if LC < L where L

is the downwind length of the roof.

The maximum height of the roof cavity is defined as:

HC = 0.22 * R at x = 0.5 * R

where x is the downwind distance.

The program uses two algorithms to determine the height and

width of the downwind recirculation cavity or near-wake. If the

roof cavity reattaches to the roof, the height and width are:

HR = H where H is the building height

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55

WR = W where W is the projected width normal to the wind.

If the roof cavity does not reattach, the height and width are:

HR = H + HC

WR = 0.6 * H + 1.1*W

and measured from the lee face of the building.

The length of the recirculation region is calculated using

the formula:

LR = 1.8W/[(L/H)0.3 * (1.0 + 0.24W/H)]

with the restriction that L/H is set equal to 0.3 if L/H < 0.3,

and L/H is set equal to 3.0 if L/H > 3.0.

The ground level concentration in the recirculation region is

calculated assuming the mass fraction of the plume, below HR at

the downwind end of the region, is captured into the region. The 

calculation assumes a Gaussian distribution of the vertical mass

of the plume at that point using the following formula:

)z = 0.21R0.25 x0.75

The cavity concentration, C, is then calculated as a fraction

of the plume content using the following empirical formula:

 C = fc * B0 Q/(B0w0A0 + uHs2)

where: fc is the mass fraction of the plume captured in the 

recirculation region

B0 is an empirical constant approximately equal to 16

w0 is the stack exit speed

A0 is the stack exit face area 

uH is the upwind wind speed at roof level 

s2 is the "stretched string" distance between the 

stack base and the receptor.

The position of the stack on the roof is taken into

consideration. A ratio is calculated based on the distance of the

stack from a centerline of the building perpendicular to the wind

flow for each of two orientations divided by the along wind flow

length of the building. Below is an example where the along wind

flow length is HW and the distance of the stack from the

centerline is "x"; producing a ratio of .4. Note that the ratio

is always a positive number. Ratios greater than .5 indicate that

the stack is not on the roof.

 v------------ HW --------------v

 +--------------.---------------+

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56

 | . |

 (x/HW = .4)--> | S . |

 | ^-----x-----^ | HL

 | . |

 +--------------.---------------+

 .5 0 .5

 HL

 +------.------+

 | . |

 (x/HL = .15)---> | . S |

 | . |

 | . |

 | . | HW

 | . |

 | . |

 | . |

 | . |

 +------.------+

 .5 0 .5

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