TECHNICAL BACKGROUND DOCUMENT FOR OFFSITE 

CONSEQUENCE ANALYSIS FOR 

ANHYDROUS AQUEOUS AMMONIA, CHLORINE, AND 

SULFUR DIOXIDE 

Chemical Emergency Preparedness and Prevention Office 

U.S. Environmental Protection Agency 
Prepared by: 

Geoffrey D. Kaiser, Joseph D. Price, and José Urdaneta 

Science Applications International Corporation 

11251 Roger Bacon Drive 

Reston, Virginia 20190 
Background Document for Offsite Consequence Analysis, April 1999 

TABLE OF CONTENTS

Page 

CHAPTER 1: INTRODUCTION ................................................................................................................... 1-1

1.1 BACKGROUND ................................................................................................................................. 1-1

1.2 PURPOSE ........................................................................................................................................... 1-1

1.3 GENERAL APPROACH ..................................................................................................................... 1-1

1.4 ASSUMPTIONS ................................................................................................................................. 1-2

CHAPTER 2: UNCERTAINTIES AND MODELS USED ............................................................................ 2-1

2.1 ANHYDROUS AMMONIA ................................................................................................................ 2-1

2.1.1 SAIC Proprietary Model ............................................................................................................ 2-1

2.1.2 USEPA RMP Offsite Consequence Analysis Guidance (OCAG) ................................................. 2-3

2.1.3 TFI ............................................................................................................................................ 2-3

2.1.4 DNV-UDM-Technica ................................................................................................................. 2-5

2.1.5 AWWARF Approach .................................................................................................................. 2-6

2.1.6 Additional ALOHA Run ............................................................................................................. 2-6

2.1.7 Comparison with Available Data ............................................................................................... 2-6

2.1.7.1 Data from Accidents ............................................................................................................................. 2-6

2.1.7.2 Experimental Data--Desert Tortoise ...................................................................................................... 2-9

2.1.7.3 Data from Modeling ........................................................................................................................... 2-10

2.1.7.4 Interpretation of Figures 2-2 and 2-3 ................................................................................................... 2-10

2.1.7.5 Choice of a Single Curve for AR and WWTP Guidance ....................................................................... 2-11

2.1.7.6 10-Minute vs. 60-Minute Releases ...................................................................................................... 2-11

2.1.8 Anhydrous Ammonia--Urban Site, Worst-Case ......................................................................... 2-13

2.1.9 Anhydrous Ammonia--Alternative Scenarios ............................................................................ 2-13

2.2 AQUEOUS AMMONIA .................................................................................................................... 2-17

2.3 CHLORINE ...................................................................................................................................... 2-17

2.3.1 Worst-Case Scenarios .............................................................................................................. 2-17

2.3.2 Alternative Scenario ................................................................................................................ 2-23

2.4 SULFUR DIOXIDE ........................................................................................................................... 2-23

2.5 BACKGROUND DESCRIPTION OF SENSITIVITY STUDIES ....................................................... 2-24

2.5.1 Dry Deposition ........................................................................................................................ 2-24

2.5.2 Puff Releases ........................................................................................................................... 2-25

2.5.3 Qualitative Uncertainties and Conservatisms .......................................................................... 2-25

2.5.3.1 Duration of Worst-Case Weather Conditions ....................................................................................... 2-25

2.5.3.2 Pooling ............................................................................................................................................... 2-25

2.5.3.3 Time Varying Toxic Endpoints ........................................................................................................... 2-25

2.5.4 Conclusion–Sensitivity Studies ................................................................................................. 2-26

CHAPTER 3: GASES LIQUEFIED UNDER PRESSURE ............................................................................ 3-1

CHAPTER 4: ADJUSTMENT OF MEAN CONCENTRATION FOR AVERAGING TIME ..................... 4-1

CHAPTER 5: AMMONIA/MOIST-AIR THERMODYNAMICS ................................................................ 5-1

5.1 CALCULATION OF THERMODYNAMIC PROPERTIES OF MIXTURES OF

AMMONIA AND AIR ........................................................................................................................ 5-1

5.1.1 Methods ..................................................................................................................................... 5-1

5.1.1.1 Physical Property Data .......................................................................................................................... 5-2

5.1.1.2 Algorithm for Determination of Final Cloud Conditions ........................................................................ 5-5

5.1.2 RESULTS ................................................................................................................................ 5-10

5.2 EFFECT ON PREDICTION OF DISTANCES TO TOXIC ENDPOINT ............................................ 5-12

5.3 POTENTIAL FOR LIFT-OFF ........................................................................................................... 5-13

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Background Document for Offsite Consequence Analysis, April 1999 

CHAPTER 6: EFFECT OF AMMONIA RELEASES ON STRUCTURES .................................................. 6-1

6.1 PROLONGED RELEASES ................................................................................................................. 6-1

6.1.1 Building Structural Response ..................................................................................................... 6-2

6.1.2 Building Attenuation of Release ................................................................................................. 6-2

6.2 SUMMARY OF CONCLUSIONS ....................................................................................................... 6-3

REFERENCES .....................................................................................................................................................

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Background Document for Offsite Consequence Analysis, April 1999 

LIST OF FIGURES

Page 

Figure 2-1. Sensitivity Studies for Worst-Case Anhydrous Ammonia Scenarios - Predicted 

Distances to Toxic Endpoint, Rural Site, Atmospheric Stability F, Windspeed 

1.5 m/s ...................................................................................................... 2-4

Figure 2-2. Ammonia Dispersion Data Accidents and Desert Tortoise Experiments ........ 2-8

Figure 2-3. Ammonia Dispersion Data (Enlarged) ....................................................... 2-12

Figure 2-4. Sensitivity Studies For Worst-Case Anhydrous Ammonia Scenarios Predicted

Distances To Toxic Endpoint, Urban Site, Atmospheric Stability F,

Windspeed 1.5 m/s .................................................................................. 2-14

Figure 2-5. Sensitivity Studies for Alternative Anhydrous Ammonia Scenarios Predicted

Distances to Toxic Endpoint, Rural Site, Atmospheric Stability Category D,

Windspeed 3 m/s ..................................................................................... 2-15

Figure 2-6. Sensitivity Studies for Alternative Anhydrous Ammonia Scenarios Predicted

Distances To Toxic Endpoint, Urban Site, Atmospheric Stability Category D, 

Windspeed 3 m/s ..................................................................................... 2-16

Figure 2-7. Sensitivity Studies for Worst-Case Aqueous Ammonia Scenarios Predicted 

Distances to Toxic Endpoint, Rural Site, Atmospheric Stability F, Windspeed 

1.5 m/s .................................................................................................... 2-18

Figure 2-8. Sensitivity Studies For Worst-Case Aqueous Ammonia Scenarios Predicted 

Distances to Toxic Endpoint, Urban Site, Atmospheric Stability F, Windspeed 

1.5 m/s .................................................................................................... 2-19

Figure 2-9. Sensitivity Studies for Alternative Aqueous Ammonia Scenarios Predicted

Distances to Toxic Endpoint, Rural Site, Atmospheric Stability D, Windspeed

Figure 2-10. Sensitivity Studies for Alternative Aqueous Ammonia Scenarios - Predicted

Distances to Toxic Endpoint, Urban Site, Atmospheric Stability Category D,

3 m/s ....................................................................................................... 2-20

Windspeed 3 m/s .................................................................................... 2-21

Figure 3-1. Fraction of Liquid Chlorine Falling to the Ground as a Function of Superheat3-2

Figure 5-1. Algorithm for Determination of Final Cloud Conditions for Mixing of Ammonia

Figure 2-11. Sensitivity Study Predicted Distances To Toxic Endpoint For Chlorine ... 2-22

Figure 4-1. Illustration of Meandering ........................................................................... 4-3

and Moist Air Clouds ................................................................................ 5-6

Figure 5-2. Algorithm for Calculation of Dew Point Pressure ...................................... 5-10

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Background Document for Offsite Consequence Analysis, April 1999 

LIST OF TABLES

Page

Table 2-1. Maximum Center Line Concentrations Measured in the Desert Tortoise

Experiments (ppm) .................................................................................. 2-9

Table 2-2. Comparison of Worst-Case Hazard Assessments for Anhydrous Ammonia2-10

Table 2-3. Examples of AWWARF and SACRUNCH/AR Predictions Worst Case, Urban

Table 4-1. Example of Effect of Meandering of Anhydrous Ammonia Releases, WorstTable 4-2. Example of Effect of Meandering of Anhydrous Ammonia Releases, WorstTable 5-3. Comparison of Measured and Predicted Vapor Pressures Above

Table 5-5. Final Cloud Conditions for a Worst-Case Scenario, Two-Phase Release with

Table 5-6. Final Cloud Conditions for a Worst-Case Scenario, Two-Phase Release with

Table 5-8. Example of the Effect of New Thermodynamic Model and Meandering of

Table 6-1. Ten-Minute Building Release Attenuation Factors for Continuous Releases of

Table 6-2. Ten-Minute Building Release Attenuation Factors for Prolonged Releases of

Site ........................................................................................................ 2-13

Table 2-4. Ratios of AWWARF Alternative Case Predictions .................................. 2-13

Table 2-5. Distances to Toxic Endpoint (ft)--Sensitivity Studies for Chlorine ........... 2-23

Case, Rural Conditions ............................................................................ 4-4

Case Urban Conditions ............................................................................ 4-5

Table 5-1. Comparison of Measured and Predicted Vapor Pressure of Water ............. 5-4

Table 5-2. Comparison of Measured and Predicted Vapor Pressure of Ammonia ....... 5-4

Ammonia/Water Solutions ....................................................................... 5-4

Table 5-4. Heat Capacity and Heat of Vaporization Data ........................................... 5-5

Moist Air* ............................................................................................. 5-11

Dry Air* ................................................................................................ 5-11

Table 5-7. Final Cloud Conditions for All Vapor Release with Dry Air* .................. 5-12

Anhydrous Releases, Worst-Case, Rural Conditions, 75% RH ............... 5-12

Table 5-9. Illustration of the Potential for Lift-Off ................................................... 5-13

Ammonia ................................................................................................. 6-4

Chlorine and Sulfur Dioxide ..................................................................... 6-5

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Background Document for Offsite Consequence Analyses, May 1999 

CHAPTER 1: INTRODUCTION

1.1 BACKGROUND 

Following the publication of the US Environmental Protection Agency’s (EPA’s) Risk 

Management Program (RMP) regulations, 40 CFR Part 68, EPA developed generic guidance for 

the offsite consequence analyses required by the regulation. This document, RMP Offsite 

Consequence Analysis Guidance (OCAG), is intended to provide simple methods and reference 

tables for determining distances to toxic and flammable endpoints for worst-case and alternative 

release scenarios. The generic approach is based on parameters required by the rule and on 

conservative assumptions about other conditions and may not reflect site-specific conditions. Use 

of the guidance is not required; facilities may conduct their own air dispersion modeling, provided 

that they use the parameters specified in the rule and a model appropriate for the substance. 

EPA also developed industry-specific guidance for ammonia refrigeration (AR) and 

wastewater treatment plants (WWTPs). In developing these documents, EPA conducted 

chemical-specific modeling for anhydrous ammonia, aqueous ammonia, chlorine, and sulfur dioxide, 

including consideration of liquid droplet formation (except in the case of aqueous ammonia). This 

chemical-specific modeling was incorporated into the OCAG. The modeling for these four toxic 

substances is different from, and less conservative than, the generic modeling that applies to other 

regulated substances covered in the OCAG. 

1.2 PURPOSE 

The purpose of this document is to provide the technical background of the methodology and 

assumptions used to develop the chemical-specific tables. 

1.3 GENERAL APPROACH 

Modeling the consequences of large-scale accidental releases of toxic vapors involves many 

uncertainties. These uncertainties may arise from the capability of different models to describe the 

physical phenomena, the selection of input parameters, and the lack of data to validate the models. 

When the same inputs are used, different models may produce widely varying results; the same 

model may also produce widely varying results if the input parameters are varied across their 

range of uncertainty. The range of predicted distances can be as much as a factor of 10. 

The modeling conducted to develop the chemical-specific tables differs from the modeling for 

the generic tables found in the OCAG in the following ways: 

(1) Models developed by SAIC (referred to as SACRUNCH and SADENZ) were used rather 

than SLAB. Sensitivity analyses were conducted using various models, experimental data, and 

accident data to evaluate the reasonableness of the results. Chapter 2 provides the results of these 

analyses, which illustrate the range of outcomes possible when performing analyses of the type 

required by EPA. Because SACRUNCH, SADENZ, and SAPLUME (1994) are proprietary 

1
Background Document for Offsite Consequence Analyses, May 1999 

dispersion models, and thus not readily available for review, some information about these models 

is provided in Appendix A. 

(2) Liquid anhydrous ammonia, chlorine, and sulfur dioxide are frequently stored as gases 

liquefied under pressure. In the OCAG, for the worst-case release, gases liquefied under pressure 

are assumed to behave similarly to gases. Based on relevant studies, absent obstacles, liquid 

anhydrous ammonia, chlorine, and sulfur dioxide released at typical ambient temperatures are 

assumed to become and remain airborne as a mixture of vapor and fine liquid droplets and, for the 

purposes of RMP, can be modeled as a gas. Chapter 3 discusses this issue. 

(3) The effect of averaging time on plume spread was considered and a method for adjusting 

the predicted mean concentration for averaging time developed. Chapter 4 discusses this issue. 

(4) The thermodynamics of mixtures of moist air and anhydrous ammonia were analyzed using 

the techniques reported by Wheatley (1987). (See Chapter 5, which also discusses whether the 

ammonia/moist air mixing will generate enough heat to cause the plume to become buoyant.) 

(5) For scenarios in which the release from a vessel is indoors, the effect of hold-up of vapors 

within a building has been incorporated into the industry-specific models, but not the OCAG, 

which uses a simpler approach. Chapter 6 discusses this issue. 

1.4 ASSUMPTIONS 

As previously mentioned, the RMP rule requires that certain parameters be used in the offsite 

consequence analysis modeling (40 CFR 68.22). The analyses presented in this document use 

these required assumptions. 

• For anhydrous ammonia, chlorine, and sulfur dioxide (i.e., gases liquefied under 

pressure), the worst-case scenario consists of the sudden release of the whole contents of 

the largest vessel or pipeline. For the purposes of the modeling, it is assumed that the 

release is spread over 10 minutes, whether the release is outside or inside a building. 

• The worst-case weather conditions consist of Atmospheric Stability Category F, with a 

windspeed of 1.5 m/s, unless it can be shown that such conditions have not occurred at the 

site during the past three years. 

• The toxic endpoints are 200 ppm for ammonia, 3 ppm for chlorine, and 3 ppm for sulfur 

dioxide, irrespective of the duration of exposure. EPA is currently developing Acute 

Exposure Guideline Levels (AEGLs), which will consist of different values of toxic endpoint 

for a number of exposure times. However, until the AEGLs have been published and the rule 

has been changed, toxic endpoints are fixed. 

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Background Document for Offsite Consequence Analyses, May 1999 

CHAPTER 2: UNCERTAINTIES AND MODELS USED 

Developing offsite consequence analysis guidance that is simple and easy to use, yet 

scientifically defensible, is difficult because a large range of uncertainty exists for predictions of 

distances to the toxic endpoint. For example, 40 CFR Part 68 requires that worst-case modeling 

be carried out assuming atmospheric stability category F and a windspeed of 1.5 m/s. However, 

very few experimental data exist for these weather conditions with which to validate models. To 

develop an understanding of the plausible uncertainty range, a comparative study was conducted 

in which the same input parameters were used in the different available models, release rate 

varied, and the outputs compared. The following is a description of analyses performed to support 

the reference tables and provides an explanation of how reference tables, plots, and formulas were 

selected from within the range of possibilities. Anhydrous ammonia is discussed first because, for 

this particular chemical, there are many examples and calculations available from which to develop 

an understanding of the range of uncertainties. 

2.1 ANHYDROUS AMMONIA 

In many parts of a typical refrigeration system, ammonia is liquefied under pressure. If the 

pressure and temperature are sufficiently high, and if there is a sudden release of ammonia, it will 

become and remain airborne as a mixture of vapor and very fine liquid droplets that do not fall to 

the ground. The droplets evaporate quickly cooling the air so that a cold mixture of air and 

ammonia vapor is formed. The mixture is initially denser than air. 

The comparative study was conducted for a worst-case scenario release of anhydrous 

ammonia at a rural site. The toxic endpoint for ammonia as specified in the RMP Rule is 0.14 

mg/L (200 ppm). For the purposes of the RMP, this is a fixed value no matter the duration of 

release. The worst-case weather conditions consist of Atmospheric Stability Category F, with a 

windspeed of 1.5 m/s. The worst-case scenario consists of an outdoor, sudden release of the 

whole contents of the largest vessel or pipeline. For the purposes of this comparative study, the 

worst-case release was varied from 1,000 to 400,000 lbs. It is assumed that the release is spread 

over 10 minutes, therefore, the rate of release varied from 100 to 40,000 lbs./min. 

Figure 2-1 displays several different answers to the question: “For worst-case scenarios at a 

rural site, what is the predicted distance to the toxic endpoint as a function of the rate of release 

of anhydrous ammonia?” The various models used to prepare Figure 2-1 are described below. 

[On the tables and plots in this chapter, it was sometimes necessary to extrapolate data presented 

by other authors. This was done by assuming a linear relationship between distance and release 

rate on a log-log plot.] 

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Background Document for Offsite Consequence Analyses, May 1999 

2.1.1 SAIC Proprietary Model 

The May 1996 draft guidance for ammonia refrigeration (USEPA, 1996b) made use of two 

SAIC proprietary computer models—SACRUNCH, which is suitable for the modeling of groundlevel, horizontal releases of denser-than-air vapors, and a companion model, SADENZ, for 

denser-than-air puffs. These models are described in SAIC (1994), and a summary is provided in 

Appendix A. These models were used because they allow the easy use of sensitivity studies, 

including the phenomenon of dry deposition, a highly effective mechanism for depleting clouds of 

reactive gases such as ammonia, and because they allowed the easy insertion of an ammonia/moist 

air thermodynamics module. 

1. The models are 2-D “box” models with gravitational slumping, edge entrainment, and top 

entrainment of air given by simple but reasonably well-established formulas in the initial, 

heavier-than-air phase. The model was essentially “tuned” by comparison with the 

Thorney Island experiments (McQuaid, 1986). 

2. The model finally evolves from being denser-than-air to being neutrally buoyant when 

)r/ra = 0.001, where ra is the density of air and )r is the difference between the density 

of the vapor cloud (averaged across a continuous-plume cross section or throughout a 

puff) and the density of the surrounding air1. 

3. In the neutrally buoyant phase, the models evolve to the “Green Book” horizontal and 

vertical standard deviations of sy and sz (i.e., the rural or urban parameterizations 

proposed by Briggs (1973a) and reproduced in the “Green Book.” The “Green Book” is 

EPA’s Technical Guidance for Hazards Analysis (USEPA, 1987), which contains a 

Gaussian model with vertical and horizontal standard deviations from Briggs (1973a). 

4. For ammonia, chlorine, and sulfur dioxide released from the liquid space of vessels in 

which they are liquefied under pressure at 25 o

C or at the highest daily temperature, it is 

assumed that a portion of the released liquid immediately flashes to vapor (e.g., 20 

percent). The user calculates the percentage outside the model from thermodynamic 

principles. The remaining liquid atomizes and remains airborne. See Chapter 3 for 

justification of this assumption. See Chapter 6 for a discussion of how buildings could 

mitigate this effect. 

5. SACRUNCH makes a simplifying assumption: the turbulence generated by the flash 

atomization process is such that, almost immediately, the mass mixing ratio is 10 (i.e., the 

ratio of entrained air to airborne ammonia, chlorine, or sulfur dioxide mass is 10). For 

anhydrous ammonia, the density and temperature of this mixture are calculated using the 

ammonia/moist air thermodynamic model described in Chapter 5. For chlorine and sulfur 

dioxide, the mixture is assumed to be air and Cl2 vapor or air and SO2 vapor, respectively, 

at their atmospheric boiling points. The initial horizontal momentum of the escaping liquid 

1

 Some reviewers criticized this assumption because it is a simpler transition criterion than is found in other 

models. However, as is shown in Appendix A, the models do a reasonable job of fitting the large-scale 

experimental data-bases. They evolve in the far field into a well-established Gaussian model with well-known 

standard deviations provided by Briggs (1973a). In addition, sensitivity studies (not shown here) indicate that the 

results do not change significantly when the )r/ra criterion is varied between 0.01 and 0.001. 

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Background Document for Offsite Consequence Analyses, May 1999 

jet and the entrained air is conserved to define the initial conditions for SACRUNCH. A 

similar assumption is made for an instantaneous puff release in SADENZ. The predictions 

of the model at distances at which the toxic endpoints of Cl2 or SO2 are encountered 

(3ppm) are not sensitive to this assumption, although it does mean that predictions near 

the source may not be accurate. 

6. In SACRUNCH, the toxic endpoint is compared to the peak centerline concentration, 

which, for worst-case scenarios, is assumed to jump up to that value when the puff arrives 

and to remain constant for exactly 10 minutes, independent of location. In SADENZ, the 

model calculates the average centerline concentration over the duration of cloud passage. 

This duration is a function of distance downwind. 

7. SACRUNCH and SADENZ have simple dry deposition modeling algorithms (see Section 

2.5.1). None of the other computer programs discussed herein have these capabilities, 

which is one of the reasons the authors consider it useful to use SACRUNCH and 

SADENZ. 

8. There is an issue concerning the use of models such as SACRUNCH with high surface 

roughness length (this issue is discussed below in some detail in the context of the use of 

DEGADIS). The concern is that, at a truly urban site, a heavy vapor will flow in among 

the obstructions on the surface (e.g., large buildings) and will not be exposed to the 

turbulence in the atmosphere above those obstructions. For the present work, it has been 

assumed that, while in the denser-than-air phase, the surface roughness length is 10 cm at 

both urban and rural sites. When )r/ra < 0.001, the model is a Gaussian one in which sy 

and sz are different for urban and rural sites. This approach should be somewhat 

conservative for the urban site. 

Three sensitivity studies are shown on Figure 2-1: 

A. A conservative case, in which SACRUNCH defaults into the “Green Book” rural

dispersion model in the far field, when the initial denser-than-air behavior has been

“forgotten”. 

B. A case in which a dry deposition velocity of 1 cm/sec has been used. See Section 2.5.1 for 

further discussion of dry deposition. The authors also looked at a case in which the dry 

deposition velocity was 0.3 cm/sec, but that case is not reproduced on Figure 2-1. 

C. A case in which the puff model SADENZ has been used. 

2.1.2 USEPA RMP Offsite Consequence Analysis Guidance (OCAG) 

The OCAG (USEPA, 1996a) was developed using the SLAB model (Ermak, 1989). It is 

intentionally conservative. The distances are obtained simply by reading from tables provided in 

the OCAG. The nearest entry in the OCAG table that is conservative is the one that is chosen. In 

addition, a second OCAG curve has been provided – one that has been interpolated between the 

discrete values of release rate and toxic endpoint that are given in the OCAG lookup tables. This 

gives somewhat less conservative predictions. 

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Background Document for Offsite Consequence Analyses, May 1999 

0.10 

1.00 

10.00 

100.00 

WORST-CASE 

RURAL 

ANHYDROUS AMMONIA 

2.1.3 TFI 

The Fertilizer Institute (TFI) has produced its own guidance on large-scale releases of 

anhydrous ammonia. TFI used the DEGADIS model (USEPA, 1989), with its transient option. 

In this option, the initial ten-minute “slug” of ammonia gradually evolves into a puff as it travels 

SACRUNCH, CASE B 

PUFF,SADENZ,CASE C 

OCA-generic 

AWWA 

TFI 

DNV-UDM 

ALOHA 

SACRUNCH CONSERV, CASE 

A 

100 1000 10000 100000 

Rate Of Release (lbs/min) 

Figure 2-1. Sensitivity Studies for Worst-Case Anhydrous Ammonia Scenarios - Predicted 

Distances to Toxic Endpoint, Rural Site, Atmospheric Stability F, Windspeed 1.5 m/s 

downwind because there is along-wind lengthening of the slug due to the action of atmospheric 

turbulence. This lengthening effect is most dramatic in Atmospheric Stability Category F 

conditions with a low windspeed. The transient release model that TFI has used is conceptually 

realistic. 

Note that TFI uses roughness lengths of 3 cm and 1 m to characterize rural and urban areas, 

respectively. There are two potential concerns about this: 

1. The authors of DEGADIS have previously expressed the opinion that DEGADIS should 

not be used with surface roughness lengths in excess of 10 cm. This issue was extensively 

discussed in 1990/91 during the South Coast Air Quality Management Districts 

rulemaking on hydrogen fluoride storage and use (SCAQMD, 1991a,b). SCAQMD 

states: 

“The slumping and stably stratified flow characteristic of dense gas releases 

produces dense gas plumes that have height scales significantly less than the 

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Background Document for Offsite Consequence Analyses, May 1999 

height of the atmospheric boundary layer. The surface roughness parameter is 

used by the models to characterize the dense gas vertical dispersion. The 

mathematical concept of the surface roughness parameter dictates the use of a 

value that is much less than the height scale of the dispersing cloud. This is not a 

problem when simulating dense gas dispersion in a desert environment, but it 

becomes more complicated when applying the models in urban areas. 

“Since dense gas models have been developed to simulate test releases conducted 

in non-urban (desert) settings, most models, including DEGADIS, are designed to 

simulate rural dispersion when the cloud enters the passive phase. A surface 

roughness value characteristic of urban scale roughness elements is 

inappropriate unless the dense gas cloud height is approximately 30 times the 

height of the surface roughness elements. Until the issue of extrapolating the use 

of the models from non-urban settings to urban settings is better understood, a 

surface roughness value of 0.1 meter shall be used as the input to DEGADIS for 

the entire transport and dispersion calculation.” 

This limitation on the use of DEGADIS was supported by one of the original authors of 

DEGADIS, Jerry Havens, in testimony to SCAQMD. 

2. When moving from a rural to an urban area, increased intensity of atmospheric turbulence 

arises from two sources, mechanical (due to the presence of buildings) and convective 

(due to the presence of large heat sources). It is questionable whether a model in which 

changed surface roughness alone is responsible for the enhanced intensity of turbulence at 

urban sites correctly characterizes the physics of the situation (this comment also applies 

to SLAB). 

2.1.4 DNV-UDM-Technica 

The work presented by Woodward (1998) is of considerable interest because the model used 

is based on experimental data obtained at very low windspeeds in stable weather conditions. 

There are few such data available for any hazardous vapor; DNV made use of a database of largescale propane releases (Heinrich et al., 1988/1989). The releases ranged in size from a few 

hundred kilograms to several thousand kilograms, and the duration of release varied from 

40 seconds to 600 seconds. It is pertinent to try to understand why the DNV predictions on 

Figure 2-1 are relatively low. 

1. The model that DNV “tuned” based on the TUV experiments is known as UDM 

(Unified Dispersion Model). It has considerable merit because, as noted above, it was 

actually based on experiments at low windspeeds in stable weather conditions. However, 

the appreciably lower predictions of the UDM model in Figure 2-1 are, in part, due to an 

assumption about averaging. Basically, the author appears to have divided the model’s 

predicted concentrations by a factor of six to take account of the 10-minute duration of 

release, whereas the ammonia toxic endpoint of 200 ppm is valid for an exposure time of 

60 minutes. This amounts to assuming that Haber’s law is valid for ammonia. As noted 

above, such exposure time-dependent relationships for toxic endpoints are not permitted 

under the current rule. 

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Background Document for Offsite Consequence Analyses, May 1999 

2. The principal aim of the original TUV papers from the Journal of Hazardous Materials 

(Heinrich et al., 1988; 1989) was to examine the lower flammable distance (LFD) (i.e., the 

distance to the lower flammable limit, which is 2.1 v% [~ 20,000 ppm] for propane). 

Experimental measurements were taken down to concentration levels of a few thousand 

ppm. To make predictions for ammonia at 200 ppm, extrapolations of more than an order 

of magnitude are required. Therefore, it should be noted that the experimental results 

upon which the “tuning” of the UDM models is based are strictly near-field results and do 

not provide information about concentrations at or near the toxic endpoint of ammonia. 

(UDM is no different from any of the other models in this respect; however, it is also true 

to say that it is no better than the others, either.) 

3. Two types of instruments were used to record propane concentration – “catalytic-type” 

instruments (details not given) that were regularly distributed across the field, and infrared 

(IR) spectrometers that used the 3.7 m propane absorption band for detection. It turned 

out that, in the original publication (Heinrich et al., 1988), the IR measurements were 

incorrectly interpreted because the results were distorted by the presence of ice crystals, 

which led to considerable overestimates of the LFDs. These overestimates were corrected 

in 1989 (Heinrich et al., 1989). 

Woodward points out inconsistencies between the readings of the catalytic sensors and the 

IR sensors in experiments in which the rate of release and other conditions were nearly 

identical and, on this basis, states that the IR results are preferable. The IR results appear 

to be generally lower than the catalytic sensor results, presumably biasing the tuning of the 

UDM model towards lower predicted distances. It would seem that caution is advisable in 

ignoring one set of results just because the experimental fluctuations appear to be large, 

while accepting another set of results that required major post facto corrections. 

2.1.5 AWWARF Approach 

The American Water Works Association Research Foundation (AWWARF, 1998) approach is 

based on the ALOHA model (NOAA and USEPA, 1995) and is provided here as a representative 

application of that computer model. It is likely that many facilities that do their own modeling 

will use ALOHA. 

2.1.6 Additional ALOHA Run 

When preparing the RMP Guidance for Ammonia Refrigeration (USEPA, 1998), EPA 

engaged in continuous dialog with the International Institute of Ammonia Refrigeration (IIAR). 

Early in 1996, one of IIAR’s consultants provided an ALOHA output2, which is also shown on 

Figure 2-1. 

2

 IIAR, Private Communication, March 1996 

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Background Document for Offsite Consequence Analyses, May 1999 

2.1.7 Comparison with Available Data 

2.1.7.1 Data from Accidents 

No data set (or sets) was identified that unequivocally distinguishes among all of the models 

on Figure 2-1. However, there are sufficient data available to make some judgments about where 

to place reasonably conservative guidance. 

Markham (1986) provides an instructive review of the consequences of quite a large number 

of accidents that have resulted in the release of anhydrous ammonia. The results of Markham’s 

work are summarized on Figure 2-2, which is a little complicated, but which is worth further 

study. The letters A, B, - - - MM identify the estimated concentrations from a list of 12 accidents 

that Markham analyzed. The lengths of the bars represent the uncertainty in recovering data from 

accident descriptions. Note that these bars do not represent actual measured concentrations. 

They represent post-facto reconstructions from observations of effects on plants and birds. 

Markham defines the releases as follows: 

• A, B, C and D-45-ton release of cold product (presumably refrigerated) in approximately 30 

minutes, Bainesville, MN (6/10/81) 

• E-puncture in 82-ton railcar, ambient temperature, Belle, WV (1/21/70) 

• F and G-160 tons of cold product over 22 hours, Blair, NE (11/16/70) 

• H, J and K-truck train collision, 18 tons of anhydrous ammonia at ambient temperature 

released in a few minutes, Boitte, LA (12/15/70) 

• L, M and N-pipeline rupture, 230 tons at ambient temperature released in under eight hours, 

Conway, KS (12/6/73) 

• O-160 tons released instantaneously, presumably ambient temperature, Crestview, FL (4/8/79) 

• P-70 tons from train wreck, ambient temperature, Crete, NE (2/18/69) 

• Q and R-pipeline rupture, 400 tons over four hours, ambient temperature, Enid, OK (5/7/76) 

• U, V and W-train wreck, 50 tons rapidly released, ambient temperature, Pensacola, FL 

(11/9/77) 

• X, Y, Z, AA, BB and CC-bullet tank failure, instantaneous release of 30 tons, ambient 

temperature, Potchefstroom, South Africa (7/13/73) 

• DD and EE-railcar failure, 75-ton release, ambient temperature, Verdigis, OK (6/10/79) 

• FF, GG, HH, II, JJ, KK, LL and MM-19 tons instantaneous release from a tank truck, 

ambient temperature, Houston, TX (5/11/76) 

Thus, most of the data from accidents on Figure 2-2 are from spills of anhydrous ammonia at 

ambient temperature, with two releases of refrigerated ammonia. Markham does not specify the 

weather conditions associated with each specific release. 

7
Concentration (ppm)

Background Document for Offsite Consequence Analyses, May 1999 

1000000

100000

10000

1000

200100

10

GG 

J

 FF

 JJ 

O

 M G 

DD 

MM 

C 

EE 

Q 

N 

D 

R

 Data Points Denoted

 A, B, C, etc from 

Markham (1986) 

DNV 

TFI 

AWWARF 

AR 

OCA (Interpolated) 

OCA ( Not Interpolated) 

1 10,000 lb 

2 50,000 lb 

3 100,000 lb 

4 150,000 lb 

5 200,000 lb 

1 

1 

1 

1 

2 3 4 5 2 3 4 5

4 5 

4 5 

3 

1 2 3 5

3 2 1

 HH 

Z 

X 

E Y U AA 

P 

I I

 K 

BB CC

LL KK

 B 

A

 F 

V W

H 

4 5

2 

3 

4 

2 

DT4 

DT 

3 

DT2 

DT1 

Maximum Concentration 

in the Desert Tortoise 

Experiments 

DT1 

DT2 

DT3 

DT4 

10 100 1000 10000 100000

Di s t ance F r o m S pill Sou r ce ( me t ers)

Figure 2-2. Ammonia Dispersion Data Accidents and Desert Tortoise Experiments 

8
Background Document for Offsite Consequence Analyses, May 1999 

2.1.7.2 Experimental Data--Desert Tortoise 

The solid curves on Figure 2-2 are data from the so-called “Desert Tortoise” (DT) large-scale 

experimental releases of flashing liquid ammonia, which were carried out at the Nevada Test Site 

(Goldwire et al., 1985). The release rates in the experiments were about 100 kg/sec (220 lb/sec, 

13,200 lb/min), and the durations of release were a few minutes. The masses released in the four 

DT experiments were ~ 24,500 lb, 66,000 lb, 50,000 lb, and 90,000 lb in atmospheric stability 

classes D, D, D, and E, respectively, with windspeeds 7.42 m/s, 5.76 m/s, 7.38 m/s, and 4.5 m/s, 

respectively. The surface roughness length was 0.003 m. The actual data points are reproduced 

on Table 2-1. No estimates of experimental error were provided by Goldwire et al. 

Some pertinent observations are as follows: 

1. The solid curves connecting the Desert Tortoise data points on Figure 2-1 are drawn by 

eye to connect the points. They are not intended to be model fits to the data. 

2. The Desert Tortoise data points themselves are peak concentrations taken from plots in 

the Desert Tortoise Series Data Report (Goldwire et al., 1985). Comparisons with some 

other publications show the following: (1) in a comparison with the numerical computer 

model, FEM3, Chan et al. (1987), use almost the same concentrations as in Table 2-1 for 

DT4; (2) Spicer et al. (1987) use 75,000, 21,000, and 5,000 ppm for the three DT4 

measurements at 100, 800, and 2,800 m, respectively, in DT4, also close to the values 

given in Table 2-1. Therefore, there is precedent for the interpretation of the Desert 

Tortoise data in the way they are presented in Table 2-1. 

Table 2-1. Maximum Center Line Concentrations Measured in the 

Desert Tortoise Experiments (ppm)

Distance 

Downwind (m) DT1a DT2b DT3c DT4d 

100 50,000 80,000 80,000 65,000 

800 10,000 15,000 12,500 17,500 

1,400 --- 5,000 --- ---

2,800 --- --- 600 5,000 

3,500 650 --- --- ---

5,600 150 --- --- ---

a

24,500 lb over 2 minutes (12,250 lb/min), stability category D, windspeed 7.42 m/s 

b

66,000 lb over 4 minutes (16,500 lb/min), stability category D, windspeed 5.76 m/s 

c

50,000 lb over 3 minutes (16,700 lb/min), stability category D, windspeed 7.38 m/s 

d

90,000 lb over 6 minutes (15,000 lb/min), stability category E, windspeed 4.51 m/s 

3. Beyond 800 m, the ammonia concentration was measured by portable sensor stations. 

These data should be regarded as less reliable than those taken at 800 m and 100 m 

(with a full range of stationary instruments), but, nonetheless, do provide information that 

is helpful when making judgments. 

9
Background Document for Offsite Consequence Analyses, May 1999 

2.1.7.3 Data from Modeling 

Refer to Table 2-2 for a brief summary of some of the modeling data plotted on Figure 2-1. 

The predicted distance to the toxic endpoint is given for five discreet total masses, 10,000, 

50,000, 100,000, 150,000 and 200,000 lb, respectively. Note that, for OCAG, two columns are 

presented. One, “without interpolation,” consists of reading the predicted distances from the 

OCAG tables using the nearest conservative value that is directly tabulated therein. The other, 

“with interpolation,” involves interpolating between values in the OCAG tables, assuming linear 

relationships on log-log plots. The AR data is the SACRUNCH, Case B from Figure 2-1 and is 

close to the OCAG guidance published in 1996. 

The data from Table 2-2 are plotted on Figure 2-2. They should all lie along the 200-ppm 

line, but have been broken apart for greater clarity. For each model, the points labeled 1, 2, 3, 4, 

and 5 correspond to total mass released of 10,000, 50,000, 100,000, 150,000, and 200,000 lb, 

respectively. A portion of Figure 2-2 has been enlarged on Figure 2-3.

 Table 2-2. Comparison of Worst-Case Hazard Assessments for Anhydrous Ammonia 

Total Mass 

Released (lb) 

PREDICTED DISTANCE TO TOXIC ENDPOINT (m) 

OCAGa ARb AWWARFc TFId DNVe 

10,000 4,800f 5,800g 2,900 2,700 1,200 720 

50,000 9,200 11,000 6,500 5,300 2,400 1,500 

100,000 12,000 15,000 9,400 7,200 3,400 2,300 

150,000 14,300 17,700 11,600 8,500 4,200 3,100 

200,000 16,000 19,300 13,500 9,700 4,700 3,600 

a

OCAG – Offsite Consequence Analysis Guidance b

AR – Risk Management Program Guidance for Ammonia Refrigeration c

AWWARF – American Water Works Association Research Foundation d

TFI – Fertilizer Institute e

DNV – Det Norske Veritas-Technica f

OCAG with interpolation

g

OCAG without interpolation

2.1.7.4 Interpretation of Figures 2-2 and 2-3 

Recognizing that there is great uncertainty in the data on Figures 2-2 and 2-3, it is 

nevertheless pertinent to try to come to some tentative conclusions. 

• Bars F and G represent the farthest observed distance to which accidental releases of 

ammonia have been seen to generate vapor clouds in the 1,000 to 10,000 ppm range, 

namely about 2,000 m. The data from Markham represent a prolonged release of 

refrigerated ammonia-160 tons over 22 hours, or about 2,000 lb/min. This is the release 

rate that would be expected from an RMP worst-case release of 20,000 lb, although the 

comparison is not quite apt because bars F and G come from a steady-state release, 

whereas the worst-case release is transient. Nonetheless, one would expect worst-case 

releases with larger release rates than 2,000 lb/min (e.g., points 2, 3, 4, and 5 with release 

rates of 5,000, 10,000, 15,000, and 20,000 lb/min, respectively) to be farther to the right 

beyond bars F and G along the 200 ppm level. Therefore, at the 200-ppm level, the 

10
Background Document for Offsite Consequence Analyses, May 1999 

largest releases (e.g., 100,000 lb, representative of a railcar-sized release) ought to give 

predicted distances considerably in excess of this. For DNV and TFI, the predicted 

distances for a 100,000-lb release are 2,300 and 3,400 m, respectively. From this 

perspective, they seem a little low. 

• The Desert Tortoise experiments have provided some data, albeit uncertain, in the 100 to 

1,000 ppm range. These data were taken in Stability Categories D and E, with 

windspeeds considerably in excess of 1.5 m/s. If experiments had been performed in 

Atmospheric Stability Category F, with a windspeed of 1.5 m/s, the distances would be 

expected to increase. The surface roughness length at the Desert Tortoise was 0.003 cm, 

characteristic of a very smooth rural site (e.g., TFI gives rural terrain a surface roughness 

length of ~ 0.03 m, while DNV gives a surface roughness length of 0.003 m). Therefore, 

it seems reasonable that model predictions for releases of about the size of Desert Tortoise 

releases should propagate somewhat farther than do the Desert Tortoise curves on Figures 

1 and 2. Both the DNV and TFI models give predictions that seem a little low from this 

perspective (e.g., DT1 shows a 150-ppm result at 5,600 m). 

• In the 10 to 100 ppm range, the worst-case data from accident scenarios propagates out to 

about 12,500 m. Assuming that the worst-case accident data come close to the worst 

theoretically possible case, the predictions at the 200-ppm level should not propagate as 

far as (or, at least not much beyond) this distance. From the perspective, the OCAG 

predictions are perhaps too high. 

2.1.7.5 Choice of a Single Curve for AR and WWTP Guidance 

In conclusion, based on an analysis of what are admittedly highly uncertain data, it appears 

that the AWWARF and AR models fit well with what is observed. The OCAG model is more 

conservative (as intended), and the TFI and DNV models seem perhaps a little optimistic. 

Therefore, given the paucity of currently available data in the few hundred ppm range, it would 

seem reasonable to choose something in the region of the AWWARF/AR predictions. In the AR 

and WWTP guidance, the SACRUNCH, Case B, curve has been chosen. 

2.1.7.6 10-Minute vs. 60-Minute Releases 

In the OCAG, a distinction is drawn between releases that last for 10 minutes and releases that 

last for 60 minutes, and separate lookup tables are provided for each. However, in the guidance 

for WWTPs and ARs, no distinction is made. The main reason for this is that differences between 

the two are expected to be small relative to the uncertainties that have been identified in this 

section. 

11
Background Document for Offsite Consequence Analyses, May 1999 

10000

M

1000

200

100

MM

10

Concentration (ppm)

G F

 C

 EE

 Q

 N

R D

Data Points Denoted

 A, B, C, ect from 

Markham (1986)

 Curves are Maximum

 Concentration Measured

 in The Desert Tortoise

 Experiments 

DNV 

TFI 

AWWARF 

AR 

OCA (Interpolated) 

OCA (Not Interpolated) 

1 10,000 lb 

2 50,000 lb 

3 100,000 lb 

4 150,000 lb 

5 200,000 lb 

1 1 2 3 4 2 2 1 1 3 1 2 1 3 4 2 5 4 23 5 4 3 5 4 3 5 4 5

 DT4

 DT1 

Maximum Concentration

 in the Desert Tortoise 

Experiments 

DT1 

DT2 

DT4 

DT3

 DT3 

5 

500 2500 4500 6500 8500 10500 12500 14500 16500 18500

Distance From Spill Source (meters) 

Figure 2-3. Ammonia Dispersion Data (Enlarged) 

12
Background Document for Offsite Consequence Analyses, May 1999 

2.1.8 Anhydrous Ammonia--Urban Site, Worst-Case 

The discussion so far has been for a rural site. Figure 2-4 is similar to Figure 2-1, except that 

it is for worst-case anhydrous ammonia on an urban site. (There is no modeling available for 

DNV at an urban site.) The pattern is similar to that for the rural site, except that the range of 

uncertainties is not so great. Again, the SACRUNCH, Case B, has been chosen for the generic 

worst-case, urban-site guidance for AR and WWTPs. 

2.1.9 Anhydrous Ammonia--Alternative Scenarios 

There is alternative scenario guidance for flashing liquid releases of anhydrous ammonia in AR 

and WWTPs. This guidance is displayed on Figures 2-5 and 2-6 in comparison with data from 

TFI, AWWARF, and the OCAG. These curves do not lie as far apart as do the curves for the 

worst case and much less attention has been devoted to justifying the choice of the SACRUNCH 

curve than was done for the worst-case scenarios. However, it is pertinent to make the following 

observations. 

Examples of AWWARF and SACRUNCH/AR predictions from Figure 2-6 are given in 

Table 2-3. The distances generated by ALOHA as used by AWWARF are about a factor of 4 

higher. It is instructive to look at the additional examples of data taken from Figures 2-5 and 2-6 

and shown on Table 2-4. These show that, within the context of the large uncertainties that exist 

in the modeling, there is essentially no difference between the AWWARF predictions at rural and 

urban sites. For SACRUNCH, the corresponding ratios lie between 2 and 3 (i.e., SACRUNCH 

does show that there is a difference between an urban and a rural site in alternative-case weather 

conditions). 

Table 2-3. Examples of AWWARF and SACRUNCH/AR Predictions

Worst Case, Urban Site

Release Rate AWWARF SACRUNCH AWWARF/SACRUN 

CH Ratio 

100 lb/min 0.32 mi 0.08 mi 4.0 

1,000 lb/min 1.0 mi 0.24 mi 4.2 

3,000 lb/min 1.8 0.4 4.5 

Table 2-4. Ratios of AWWARF Alternative Case Predictions 

Release Rate AWWARF 

(Rural) 

AWWARF 

(Urban) 

Ratio 

Rural/Urban 

100 lb/min 0.4 mi 0.32 mi 1.25 

1,000 lb/min 1.2 mi 1.0 mi 1.2 

3,000 lb/min 2.0 mi 1.8 mi 1.1 

13
10.00 3-14 

WORST-CASE 

URBAN 

ANHYDROUS AMMONIA 

SACRUNCH, 

CASE B 

PUFF, SADENZ, 

CASE C 

OCA-generic 

AWWA 

1.00 

TFI 

ALOHA 

SACRUNCH 

CONSERV, 

CASE A 

0.10 

100 1000 10000 100000 

Rate Of Release (lbs/min) 

Figure 2-4. Sensitivity Studies For Worst-Case Anhydrous Ammonia Scenarios Predicted Distances To Toxic Endpoint, 

Urban Site, Atmospheric Stability F, Windspeed 1.5 m/s 

Background Document for Offsite Consequence Analysis May 1999 
0.01 

10 

3-15 

1 10 100 1000 10000 

Release Rate (lbs/min) 

ALTERNATIVE-CASE 

RURAL 

ANHYDROUS AMMONIA 

W W TFs/SACRUNCH CASE B 

AWWA 

1 

TFI 

OCA-generic 

0.1 

Figure 2-5. Sensitivity Studies for Alternative Anhydrous Ammonia Scenarios Predicted Distances to Toxic Endpoint, 

Rural Site, Atmospheric Stability Category D, Windspeed 3 m/s 

Background Document for Offsite Consequence Analysis May 1999 
16 2­

0.001 

0.01 

0.1 

1 

10 

WWTFs/SACRUNCH CASE B 

AWWA 

TFI 

OCA-generic 

ALTERNATIVE-CASE 

URBAN 

ANHYDROUS AMMONIA 

1 10 100 1000 10000 

Release Rate (lbs/min) 

Figure 2-6. Sensitivity Studies for Alternative Anhydrous Ammonia Scenarios Predicted Distances To Toxic 

Endpoint, Urban Site, Atmospheric Stability Category D, Windspeed 3 m/s 

Background Document for Offsite Consequence Analysis, May, 1999 
Background Document for Offsite Consequence Analysis, May 1999 

2.2 AQUEOUS AMMONIA 

Aqueous ammonia is sometimes found at WWTPs, but not at ammonia refrigeration facilities. 

In the WWTP guidance, it is assumed that a solution of 30 percent ammonia spills onto the 

ground: this is conservative for the range of concentrations found at such sites. Both diked and 

undiked areas are considered. The WWTP guidance contains methods for predicting the rate of 

evaporation. These methods are taken from the OCAG and are not discussed further here. The 

discussion that follows concerns how to predict the distance to the toxic endpoint, assuming that 

the rate of evaporation is known. 

The principal difference between aqueous and anhydrous ammonia, in the context of 

atmospheric dispersion modeling, is that the former evaporates relatively slowly from a pool, 

entirely as vapor, whereas the latter consists of a mixture of vapor and liquid droplets that is 

initially denser than air. By contrast, the vapor from a pool of aqueous ammonia is neutrally 

buoyant, or even marginally lighter than air. Therefore, it is appropriate to use the passive 

Gaussian dispersion model for a neutrally buoyant plume (which will be somewhat conservative if 

the plume is buoyant). 

Figure 2-7 shows the worst-case SACRUNCH Case B for aqueous ammonia at a rural site, 

and Figure 2-8 for that at an urban site. Here, the SACRUNCH Case B is the “Green Book” 

Gaussian model, modified by assuming a dry deposition velocity of 1 cm/s. The other models 

shown are those proposed by TFI, AWWARF, and OCAG. 

In Figure 2-9, the alternative scenario SACRUNCH case for aqueous ammonia is displayed, 

together with the AWWARF, TFI, and draft OCAG suggestions. Figure 2-10 is a similar plot for 

an urban site. 

2.3 CHLORINE 

2.3.1 Worst-Case Scenarios 

The results of various sensitivity studies are shown on Figure 2-11 and Table 2-5, taking 

chlorine with a 150-lb cylinder, a one-ton cylinder, a 17-ton cylinder, and a 90-ton railcar as 

examples. These are container sizes that are most common at WWTPs. 

None of the sensitivity studies on Table 2-5 is the “right” sensitivity study to choose for a 

“point estimate.” The approach adopted here has been to exclude the SACRUNCH conservative 

case and the OCAG as being too conservative, and then to choose values that are approximately 

in the middle of the range defined in the various sensitivity studies. This leads to the choice of the 

SACRUNCH case with 1 cm/s dry deposition velocity as the representative choice for the 

guidance tables, the same as was the case for anhydrous ammonia (SACRUNCH Case B). 

3-17
Background Document for Offsite Consequence Analysis May 1999 

2- 18

Figure 2-7. Sensitivity Studies for Worst-Case Aqueous Ammonia Scenarios Predicted Distances to Toxic Endpoint, 

Rural Site, Atmospheric Stability F, Windspeed 1.5 m/s

3-18 
19 2­

0.01 

0.1 

1 

10 

SACRUNCH 

CONSERVATIVE 

CASE A 

W W TFs 

AWWA 

TFI 

OCA-generic 

WORST-CASE 

URBAN 

AQUEOUS AMMONIA 

10 100 1000 10000 

Release Rate (lbs/min) 

Figure 2-8. Sensitivity Studies For Worst-Case Aqueous Ammonia Scenarios Predicted Distances to Toxic Endpoint, 

Urban Site, Atmospheric Stability F, Windspeed 1.5 m/s 

Background Document for Offsite Consequence Analysis May 1999 

3-19
0.01 

2- 20

Background Document for Offsite Consequence Analysis May, 1999

10.00 

1.00 

ALTERNATIVE-CASE 

RURAL 

AQUEOUS AMMONIA 

WWTFs 

AWWA 

TFI 

OCA-generic 

0.10 

10 100 1000 10000 

Release Rate (lbs/min) 

Figure 2-9. Sensitivity Studies for Alternative Aqueous Ammonia Scenarios Predicted Distances to Toxic Endpoint, 

Rural Site, Atmospheric Stability D, Windspeed 3 m/s

3-20
0.01 

2- 21

Background Document for Offsite Consequence Analysis May, 1999

10.00 

1.00 

ALTERNATIVE-CASE 

URBAN 

AQUEOUS AMMONIA 

WWTFs 

AWWA 

TFI 

OCA-generic 

0.10 

10 100 1000 10000 

Release Rate (lbs/min) 

Figure 2-10. Sensitivity Studies for Alternative Aqueous Ammonia Scenarios - Predicted Distances to Toxic Endpoint, 

Urban Site, Atmospheric Stability Category D, Windspeed 3 m/s 

3-21
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Background Document for Offsite Consequence Analysis May 1999

Distance To Toxic Endpoint (ft) 

100000 

U 

R 

B 

A 

N 

R 

U 

R 

A 

L 

U 

U N 

L R 

B 

R 

A

N 

R 

B 

A 

A 

U

R 

B 

A 

N 

R 

U 

R 

A 

L 

R 

U 

R 

A 

U 

R 

L 

Base Case 

0.3 cm/s Vg 

10000 

1.0 cm/s Vg 

Puff 

EPA 

AWWARF

1000 

100 

150 lb 1 Ton 17 Ton 90 Ton

Cylinder Cylinder Railcar Railcar 

Figure 2-11. Sensitivity Study Predicted Distances To Toxic Endpoint For Chlorine 

3-22
Background Document for Offsite Consequence Analysis, May 1999 

Table 2-5. Distances to Toxic Endpoint (ft)--Sensitivity Studies for Chlorine 

150-lb Cylinder 1-ton Cylinder 17-ton Tank Car 90-ton Cylinder 

Rural Urban Rural Urban Rural Urban Rural Urban

 ­ EPA OCAG1 10400 7800 36000 26000 **   **  

AWWARF2 6900 6200 16000 13600 > 6 mi > 6 mi > 6 mi > 6 mi 

• SACRUNCH 

Conservative Case3 

8200 2100 78000 7700 **   **  

o 0.3 cm/s vg 

4 6200 2000 36000 7400 **   **  

D 1.0 cm/s vg 

5 4500 1790 16000 6800 ** 29000  

 + Puff6 2500 1400 6600 3500 20400 8400 46700 15700 

**  Not evaluated or beyond limits of model 

1. From EPA’s 1996 OCAG Guidance 

2. From AWWARF Guidance for the Water Industry 

3. Conservative Case Run with SACRUNCH Model 

4. SACRUNCH with a dry deposition velocity of 0.3 cm/s 

5. SACRUNCH with a dry deposition velocity of 1 cm/s 

6. Puff Case 

Pertinent conclusions and observations are as follows: 

• The results of worst-case scenario modeling should not be quoted without a caveat that states 

the range of uncertainty. As can be seen from Figure 2-11 and Table 2-5, the range of 

uncertainty is not necessarily the same for each prediction, but a reasonable statement for the 

predictions made using the methods presented in the WWTP guidance is that the result is 

uncertain by up to a factor of 2-3 below and a factor of 2-3 above. However, based upon the 

analysis of uncertainties provided above, it is reasonable to choose a single, point estimate that 

is towards the middle or lower end rather than the higher end of the range. 

• The 17-ton tank truck and 90-ton railcar case illustrates a difficulty with essentially all models that 

are available for modeling worst-case scenarios at low toxic endpoints like the 3 ppm for chlorine, 

namely that the predicted distances become increasingly uncertain. 

2.3.2 Alternative Scenario 

As for ammonia and aqueous ammonia, the WWTP guidance for alternative scenarios for 

chlorine is simply based upon the SACRUNCH with vg = 1 cm/s case for alternative weather 

conditions, atmospheric stability category D and windspeed 3 m/s. See Section 2.5.1. for a 

definition of dry deposition velocity. 

2.4 SULFUR DIOXIDE 

Once the characteristics of the source term have been determined, vapor clouds formed from 

flashing liquid chlorine or sulfur dioxide releases should disperse in much the same way 

(the molecular weights are similar, and the toxic endpoints are the same (3 ppm)). Therefore, the 

sulfur dioxide guidance for WWTPs (for both the worst-case and alternative scenarios) has been 

calculated using the SACRUNCH case with a dry deposition velocity vg = 1 cm/s. 

3-23
Background Document for Offsite Consequence Analysis, May 1999 

2.5 BACKGROUND DESCRIPTION OF SENSITIVITY STUDIES 

As discussed above, the biggest single difficulty encountered when attempting to provide 

guidance on how to calculate the distance to the toxic endpoint is that there are large uncertainties 

in the predictions of atmospheric dispersion models. This section contains further background on 

uncertainties. 

2.5.1 Dry Deposition 

The toxic gases that are under discussion here — ammonia, chlorine, and sulfur dioxide — are 

highly reactive. They will interact with vegetation, moisture, and surfaces as they travel 

downwind. This mechanism depletes the vapor cloud and can effectively reduce predicted 

downwind distances. This phenomenon is known as dry deposition. 

Deposition is often expressed in terms of an empirical deposition velocity (Hanna and Hosker, 

1980). The dry deposition velocity is used as follows: 

CD = vgCA (2-1) 

where CD is the rate of deposition of the material onto unit area of the ground, and CA is the 

airborne concentration immediately above the ground. 

Erisman and Draaijers (1995) have published a book titled Atmospheric Deposition in 

Relation to Acidification and Eutrophication. They reviewed more than 30 experiments on the 

dry deposition of sulfur dioxide and concluded that “In the literature, average values for the 

deposition velocity range from 0.1 to over 2 cm/s with daytime values usually between 0.8 and 

1.2 cm/s. Large values (> 2 cm/s) are observed above water surfaces and forests and relatively 

small values (< 0.13 cm/s) are measured above snow and bare soil.” Therefore, a choice of 

0.3 cm/s or 1 cm/s is within the observed range. 

Sehmel (1984) has written a chapter on deposition and resuspension in Atmospheric Sciences 

and Power Production. He reports that measured dry deposition velocities for all gases range 

from 0.002 up to 26 cm/s. He quotes one result for chlorine in the range 1.2 – 2.1 cm/s. Erisman 

and Draaijers, in the reference cited above, quote a dry deposition velocity of 0.8 cm/s for 

ammonia, but with a large range of uncertainty that includes 1 cm/s. 

In SACRUNCH, the dry deposition model does not start until the plume has evolved out of 

the heavy vapor phase because very little work has been done on models for dry deposition in the 

denser-than-air phase. This approach should be conservative when predicting the distance to the 

toxic endpoint. 

3-24
Background Document for Offsite Consequence Analysis, May 1999 

2.5.2 Puff Releases 

The worst-case release is assumed to occur over a period of 10 minutes. Close to the source, 

a continuous release model is a good approximation. However, as the vapor cloud travels further 

downwind, it begins to look more and more as it would if it had been released as a puff. As a puff 

travels downwind, the action of atmospheric turbulence lengthens it along the wind, as well as 

causing the width and height to grow. This causes the average concentrations seen by an 

individual far downwind to be lower than they would be if modeled as a quasi-continuous “slug” 

that goes by in 10 minutes. Some atmospheric dispersion computer programs, such as 

DEGADIS, model this transition explicitly. In the present work, a further sensitivity study has 

been undertaken in which the worst-case contents of a vessel are released as a puff. It shows that 

the case chosen for use as guidance has an element of conservatism to it. 

2.5.3 Qualitative Uncertainties and Conservatisms 

There are a number of other uncertainties that have not been explicitly modeled in this 

chapter, but which add strength to the proposition that many atmospheric dispersion models have 

considerable conservatisms built into them. 

2.5.3.1 Duration of Worst-Case Weather Conditions 

For the very largest releases (e.g., chlorine from a 90-ton railcar), almost all available models 

predict very large worst-case distances, usually 25 miles or more. However, traveling at 1.5 m/s, 

a plume would take ~ 7 hours to travel 25 miles. It is unlikely that atmospheric stability category 

F weather conditions with a windspeed of 1.5 m/s will persist for this long. Before the vapor 

cloud has traveled anything like 25 miles, the weather is likely to change to a condition that will 

cause more rapid dilution. 

2.5.3.2 Pooling 

In very low windspeeds, heavy vapor clouds often “pool” on the ground (this is not the same 

as a liquid pool). This was explicitly demonstrated in the early heavy vapor experiments at Porton 

Down (Picknett, 1978), consisting of puff releases of freon-12, which, at low windspeeds, 

slumped until they were only a few inches deep and then remained on site, barely moving. This 

might well happen to some or all of the vapor clouds in worst-case conditions. 

2.5.3.3 Time Varying Toxic Endpoints 

The toxic endpoint established by the rule is valid for an exposure time of one hour, but used 

even if the duration of exposure is much less than one hour, as it would be for a worst-case gas 

release that takes place in 10 minutes. As a general rule, for a given health effect, an individual 

can withstand higher concentrations at smaller exposure times. Consequently, using a 60-minute 

endpoint adds to the conservatism of the predictions. 

EPA has begun the process of developing concentrations that will have different toxic 

endpoints for various exposure times. These alternatives are known as Acute Exposure Guideline 

Levels (AEGLs) for Hazardous Substances. Proposed AEGLs for 12 chemicals have been 

published in the Federal Register (62 FR 58839-58851, October 30, 1997) (notice published by 

the National Advisory Committee for Acute Exposure Guideline Levels for Hazardous 

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Background Document for Offsite Consequence Analysis, May 1999 

Substances). The 12 chemicals are 1,1-dimethylhydrazine; methylhydrazine; aniline; ethylene 

oxide; hydrazine; 1,2-dichloroethene; 1,2-dimethylhydrazine; nitric acid; fluorine, chlorine, arsine; 

and phosphine. The only one of these relevant to the present work is chlorine. 

For chlorine, the proposed AEGL-1 is 1 ppm for a one-hour exposure (the same as ERPG-1); 

the proposed AEGL-2 is 2 ppm (just below the toxic endpoint [ERPG-2] of 3 ppm); and the 

proposed AEGL-3 is 20 ppm (the same as the ERPG-3). Thus, AEGLs and ERPGs are roughly 

equivalent. To incorporate exposure-time dependence, the National Advisory Committee for 

AEGLs states that 

C2t = k (2-2) 

where k is a constant that has different values for AEGL-1, AEGL-2, and AEGL-3, C is the 

average airborne concentration and t is the exposure time. For AEGL-1, C2

t = 60 ppm2-min; for 

AEGL-2, C2t = 240 ppm2-min; and for AEGL-3, C2t = 24,000 ppm2-min. Focusing on the 

AEGL-2 as being closest to the EPA’s toxic endpoint, C for chlorine is 2 ppm for t = 1 hour (as 

noted above), 2.8 ppm for t = 30 minutes and 4.9 ppm for t = 10 minutes. 

It is also pertinent to address the question of whether Haber’s law applies to substances such 

as chlorine, sulfur dioxide, and ammonia. Gephardt and Moses (1989) looked at published 

literature and focused on the effects of airborne concentrations of 3-20 ppm of chlorine over a 

duration of exposure of 1 hour (i.e., concentrations in the ERPG-2 to ERPG-3 range). They 

concluded that Haber’s law is valid as an extrapolation of the 3 ppm/1 hour exposure (i.e., the 

ERPG-2) with Ct = 180 ppm-min. 

Gephardt and Moses expressed the caveat that Ct = k is not expected to apply for C > 100 

ppm, where different types of more severe health effects begin to occur. For ERPG-2, C = 100 

ppm corresponds to an exposure time of less than 2 minutes. For t = 10 min, C = 18 ppm and for 

t = 30 min, C = 6 ppm. 

Gephardt and Moses also consider ammonia, for which the Haber’s law constant k for the 

ERPG-2 is Ct = (200)(60) = 12,000 ppm-min, provided that C < 5,000 ppm (equivalent to t < 2.4 

min.) 

2.5.4 Conclusion–Sensitivity Studies 

The qualitative sensitivities discussed above would reduce the predicted distances to the toxic 

endpoint, if they were analyzed quantitatively. This gives added confidence that the choice of 

guidance for AR and WWTPs still contains some elements of conservatism. 

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Background Document for Offsite Consequence Analysis, May 1999 

CHAPTER 3: GASES LIQUEFIED UNDER PRESSURE 

The purpose of this chapter is to discuss how the phenomenon of aerosolization from liquid 

chlorine, sulfur dioxide, or anhydrous ammonia releases is handled in the AR and WWTP 

guidance documents. 

Chlorine, sulfur dioxide, and anhydrous ammonia in WWTPs and anhydrous ammonia in such 

vessels as the high-pressure receiver in ammonia refrigeration facilities are kept liquefied under 

pressure. If the pressure and temperature are sufficiently high, if there is a sudden liquid release 

of one of these materials, and if there are no obstructions, it will all become and remain airborne 

as a mixture of vapor and very fine liquid droplets that do not fall to the ground. Experimental 

results clearly show that this is a real physical phenomenon (Goldwire et al., 1985; Kaiser, 1989). 

The airborne droplets evaporate quickly as air is entrained. The evaporation process cools the air 

so that a cold mixture of air and vapor is formed. The mixture is denser than air, even in the case 

of ammonia, and a heavy vapor dispersion model is required to adequately predict airborne 

concentrations downwind of the point of release. 

Figure 3-1 shows the results of some experiments that were carried out on liquid chlorine and 

reported by Johnson (1991). Similar experiments were not performed for ammonia, but ammonia 

results should look similar because chlorine and ammonia have similar density ratios of liquid to 

vapor and have similar atmospheric boiling points. It is also a reasonable assumption that sulfur 

dioxide will exhibit the same type of behavior. 

Figure 3-1 shows the percentage of liquid chlorine that falls to the ground as a function of 

superheat, which is the difference between the temperature of the chlorine initially in the vessel 

and its atmospheric pressure. Figure 3-1 also shows for comparison the results of the Dow Model 

(Dow, 1993), which predicts that the fraction of airborne liquid droplets is five times the vapor 

flash fraction (the fraction of chlorine that immediately vaporizes as it is released to the 

atmosphere). As can be seen, the Dow Model appears to be non-conservative (i.e., it predicts 

that too much chlorine falls back to the ground). 

Figure 3-1 also shows the results of a model (Ianello 1989), known as the “RELEASE” 

model, that was used by Johnson (1991) to try to reproduce the experimental results. As can be 

seen, agreement is poor3

. Other models that take into account this evaporation lead to better 

agreement with experiments (e.g., Woodward and Papadourakis, 1991; Woodward et al., 1995). 

The principal conclusion is that, even at superheats of only 10 oC (which would be a 

temperature of only about -23 oC for ammonia and chlorine and about 0 o C for sulfur dioxide), 

only a small fraction of released liquid would fall to the ground. Therefore, at most, a small 

degree of conservatism is introduced if it is assumed that, for superheats exceeding 10 o

C, all of 

the released chlorine, sulfur dioxide, or ammonia remains airborne as a mixture of vapor and fine 

liquid droplets. 

CCPS has been funding further development of the RELEASE model. A private communication from Johnson, 

D.J., Quest Consultants, Norman Oklahoma (October 1997) indicates that RELEASE has been modified so that 

agreement with experiment is much improved. However, at the time of writing, RELEASE was not available to the 

authors. 

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3 
Liquid Capture (Fallout) 

%

Background Document for Offsite Consequence Analysis, May 1999 

20 

40 

60 

80 

100 

X - Experimental Results from Johnson (1991) 

Dow Model 

“Release” Model 

X 

X 

X 

X 

X 

X 

X 

X 

X X 

X 

10 20 30 40 50 60

Liquid Superheat 

Figure 3-1. Fraction of Liquid Chlorine Falling to the Ground as a Function of Superheat 

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Background Document for Offsite Consequence Analysis, May 1999 

If a jet of liquid droplets and vapor impinges upon a surface close to the point of release, there 

can be efficient recovery of droplets, which will form a relatively slowly evaporating pool on the 

ground. Experiments with ammonia have shown that up to 75 percent of the airborne droplets 

can be removed in this way (Resplandy, 1969: Kaiser, 1989). For worst-case scenario modeling, 

the use of this or similar reduction factors is probably not justified if it is possible that the release 

would not encounter obstructions. However, when considering mitigation, this phenomenon can 

be taken into account. For example, if vessels are indoors, there will almost certainly be a surface 

upon which the jet will impinge and the jet will likely change direction (e.g., impingement of the 

floor and subsequent upward movement of the vapor cloud). This arrangement is similar to the 

design of separators in chemical processes and would be expected to be very efficient at removing 

liquid droplets from the vapor stream. This issue is further discussed in Chapter 6. For the 

purposes of discussing the effects of obstacles, it is assumed that obstacles cause the recovery of 

75 percent of any airborne liquid droplets. Thus, if the initial airborne release consists of 20 

percent vapor and 80 percent liquid droplets, an obstacle-impeded release would consist of the 

original 20 percent vapor plus 20 percent liquid droplets (i.e., a mixture split equally between 

vapor and liquid and containing only 40 percent of the mass in an unobstructed release). 

The above amounts only to a rule of thumb. In fact, the percent capture of the liquid depends on 

several factors, among which is the path length of the jet before it encounters an obstruction. A model 

that shows this effect explicitly has been developed by Muralidhar et al. (1995). This model was 

specifically developed for escaping jets of a mixture of hydrogen fluoride and a proprietary additive. 

The mixture is being used as a catalyst in the alkylation unit at Mobil’s Torrance, CA, refinery. 

However, the general picture is applicable to all jet releases that consist of a mixture of fine droplets 

and vapor. The droplets present a very large surface area for evaporation; as long as they remain 

airborne, they evaporate rapidly. On encountering an obstacle, they run down to form a pool on the 

ground, which has a much smaller surface area to volume ratio, so the rate of evaporation is much 

decreased. Some typical results show that the airborne reduction factor (essentially the percentage of 

hydrogen fluoride that ends up on the ground) is 50-70 percent for a 40' travel distance, 75-85 percent 

for a 5' travel distance, and ~ 90 percent for a 3" travel distance. 

These figures cannot be directly applied to ammonia, chlorine, or sulfur dioxide, but illustrate 

the general idea. They show that the percentage collecting on the floor (or the percentage of the 

original release remaining airborne) is going to be highly configuration dependent. However, 

compressor rooms in ammonia refrigeration facilities and chlorine or sulfur dioxide rooms in 

WWTPs are often highly crowded. 

The rule-of-thumb presented above, that 60 percent of the initial flashing liquid release of 

ammonia, chlorine, or sulfur dioxide ends up on the floor as a slowly evaporating pool, is, 

therefore, offered as a simple means of taking some advantage of the presence of obstructions in 

buildings. This number is highly uncertain, but it is not possible to produce configuration-specific 

guidance that is also simple to use. 

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CHAPTER 4: ADJUSTMENT OF MEAN CONCENTRATION FOR AVERAGING TIME 

The work in this section is based on a monograph by D.J. Wilson (1995), Concentration

Fluctuations and Averaging Time in Vapor Clouds, that contains the most comprehensive

existing summary of the theories and experimental data relating to the subject of the effect of

averaging time on mean concentrations.

This issue is easily illustrated in the context of the Gaussian model, in which the cloud

centerline concentration C is inversely proportional to the crosswind standard deviation s :y

C a 1/sy (4-1) 

There is a widely used relationship for the dependence of sy on averaging time ta: 

sy a (ta)

p (4-2) 

There are few direct measurements of the exponent p. Wilson documents experiments by 

Yersel, Gobel, and Morrill (1983) in which the value of p close to the source varied from 0.0 to 

0.18. Studying releases from a high stack, Mueller and Reisinger (1986) found far downwind (25 

km) an average p = 0.25, with at least a factor of two variability in p from one test to another. 

Wilson has proposed a more realistic estimate of averaging time effects on plume spread using 

a power law model that accounts for initial source size and plume travel time on averaging time 

effects. Basically, a wide plume (with large sy) meanders less than does a narrow plume because

meandering is caused by turbulent eddies that are larger than the plume, and there are a wider 

range of turbulent atmospheric eddies to push the smaller plume around. Wilson’s recommended 

working equation is, for an atmospheric sampling time ts

 equal to the mean concentration 

averaging time t ,a

(4-3)

where sy,ref is the plume spread for a short 

sampling time, typically - ts,ref = 180s. As an approximation in the source size so term, use sy,ts = 4

 2 sy,ref to estimate the long-sampling-time plume spread. Equation 4-3 was derived for stationary 

processes and should be limited to sampling times less than about 3 hours in the atmosphere. The 

parameter rl is given by 

(4-4)

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Background Document for Offsite Consequence Analysis, May 1999 

The power law in Equation 4-3, with atmospheric sampling time ts equal to the averaging time 

ta is more physically realistic than the purely empirical one-parameter Equation 4-2. The major 

difficulty applying this power law is estimating the Lagrangian turbulent time scale TLv. Here, a 

value of TLv = 10,000 seconds is recommended, based on plume dispersion data for long travel 

times (Barr and Gifford (1987)). 

Surprisingly, considering the importance of averaging time effects, there is a lack of available 

data with statistically independent measurements of plume spread sy needed to validate (4-3). 

The only data used by Wilson for validation are from Briggs (1993) for plume spread 

measurements in unstable atmospheric conditions. Equation 4-3 gave a plausible fit to this data, 

but there was so much scatter that other functional forms would have done equally well. 

It has been conventional wisdom in models for dense gas dispersion that the strong density 

gradients across the top of a dense plume reduce its entrainment and suppress both meandering 

and vertical mixing inhomogeneities that produce concentration fluctuations. To refute this claim, 

Hanna, Chang, and Strimaitis (1993), in a review of hazard assessment models, showed that large 

one-second averaged concentration fluctuations were present in the repeat realizations of various 

dense vapor field test experiments. In fact, it is apparent that fluctuations caused by 

inhomogeneous mixing, excluding meandering, are as strong in dense plumes as they are in 

neutrally buoyant releases. 

In addition, dense plumes should also experience crosswind meandering, because they entrain 

atmospheric air with crosswind velocity fluctuations. These crosswind fluctuations should not be 

much affected by the density gradient that suppresses the vertical turbulence fluctuations and 

effectively reduces the rate of entrainment of air across the top surface of the vapor cloud (see 

Britter (1989)). Once the dense plume has been diluted by about a factor of five, it is mostly 

ambient air and should meander in much the same way as a passive plume. 

One important obstacle to applying meandering plume models to dense releases is the 

substantial difference in shape of crosswind velocity profiles between a dense plume and a passive 

plume. Gravity-driven spreading produces a wider, more uniform concentration across the center 

of a dense plume, as shown in Figure 4-1. 

Crosswind meandering simply flips this relatively uniform core back and forth across the 

centerline, causing considerably smaller fluctuations in the center and considerably more near the 

edges than would be caused by a Gaussian profile plume, shown superimposed on the dense 

plume developed. More work is needed in this area before an operational model can be 

recommended. 

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Figure 4-1. Illustration of Meandering 

5-3

4-

3
Background Document for Offsite Consequence Analysis, May 1999 

Tables 4-1 and 4-2 show how the implementation of Wilson’s meandering model affects 

predicted distances to the toxic endpoint for worst-case anhydrous ammonia releases. An 

exposure duration of 10 minutes has been assumed. In addition, to take account the lack of a 

good meandering model for dense plumes, the meandering effect is not allowed to start until the 

plume has essentially become neutrally buoyant, at which point so is determined from the halfwidth L of the plume at the transition point: 

so = L/2.14 (4-5) 

That is, at the transition to neutral buoyancy, the plume becomes Gaussian with the 10 percent 

edge at a crosswind distance L from the centerline. 

It can be seen that the distances are not much affected (the influence of meandering would be 

considerably larger for durations of exposure of an hour or more). The SACRUNCH Case B that 

was chosen as the guidance nevertheless contains the Wilson meandering correction. 

The predicted effect of meandering is smaller for chlorine and sulfur dioxide than it is for 

ammonia, given the same rate of release. This is because the toxic endpoints of chlorine and 

sulfur dioxide are much smaller than for ammonia (3 ppm vs 200 ppm). Therefore, a chlorine or 

sulfur dioxide plume has to travel much further to the toxic endpoint than does an ammonia 

plume. Equation 4-3 shows that the ratio sy/sy,ref tends to unity for very large travel times. 

Table 4-1. Example of Effect of Meandering of Anhydrous 

Ammonia Releases, Worst-Case, Rural Conditions

Rate of Release 

Distance to Toxic Endpoint 

(miles) 

(lbs/min) “Old” 

Model 

With Wilson 

Meandering 

10 0.19 0.19 

20 0.27 0.26 

50 0.41 0.40 

100 0.57 0.56 

200 0.80 0.78 

500 1.28 1.26 

1,000 1.85 1.82 

2,000 2.72 2.68 

5,000 4.59 4.54 

10,000 6.74 6.69 

20,000 9.59 9.55 

50,000 14.27 14.23 

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Background Document for Offsite Consequence Analysis, May 1999 

Table 4-2. Example of Effect of Meandering of Anhydrous 

Ammonia Releases, Worst-Case Urban Conditions

Rate of Release 

Distance to Toxic Endpoint 

(miles) 

(lbs/min) “Old” 

Model 

With Wilson 

Meandering 

10 0.10 0.10 

20 0.14 0.13 

50 0.21 0.20 

100 0.28 0.28 

200 0.39 0.39 

500 0.61 0.60 

1,000 0.84 0.83 

2,000 1.18 1.17 

5,000 1.86 1.84 

10,000 2.64 2.62 

20,000 3.89 3.83 

5-5
Background Document for Offsite Consequence Analysis, May 1999 

CHAPTER 5: AMMONIA/MOIST-AIR THERMODYNAMICS 

A rigorous consideration of ammonia/moist air thermodynamics will have some effect on 

predicted distances to the toxic endpoint. In this chapter, the basic thermodynamic model is 

described in Section 5.1, and the effect on predicted distances to the toxic endpoint is discussed in 

Section 5.2. 

A related issue is that of potential lift-off of the plume. A flashing liquid release of ammonia is 

initially denser than air, but could potentially become buoyant as it travels downwind and entrains 

air. This issue is addressed in Section 5.3. 

5.1 CALCULATION OF THERMODYNAMIC PROPERTIES OF MIXTURES OF 

AMMONIA AND AIR 

A quantity of material released into the atmosphere entrains air both during the release 

process and the atmospheric transport process. In the case of ammonia, the release may involve 

pure vapor or a mixture of vapor and liquid, and considerable turbulence is generated in the 

release process as ammonia storage pressures are usually well above atmospheric pressure. 

Estimation of cloud concentration, position, velocity, and dimensions during atmospheric 

transport involves consideration of a variety of physical processes, including rate of entrainment 

of air, gravitational slumping, transfer of heat from the atmosphere and the ground, and fall-out of 

entrained aerosols. Performance of these calculations is facilitated by independent analysis of the 

changes in thermodynamic properties that occur when ammonia is mixed with air containing water 

vapor. This chapter discusses calculation of the temperature, density, quantities, and 

compositions of vapor and liquid phases comprising a cloud formed by mixing known quantities 

of ammonia and moist air. In all cases, the total pressure is one atmosphere, and both the initial 

clouds and the final cloud are at thermodynamic equilibrium. 

5.1.1 Methods 

The equilibrium state of a mixture of known quantities of ammonia, air, and water is 

completely determined by specification of two independent variables. If the number of 

independent intensive variables4

 determined by Gibb’s phase rule5 is greater than two, 

specification of temperature and pressure determines the state of the system, including 

composition and quantities of vapor and liquid phases. If the number of intensive variables 

determined by Gibb’s phase rule is less than two, specification of pressure and relative quantities 

of vapor and liquid phases determines the state of the system for the cases considered in this 

analysis. Given specification of the properties of the initial ammonia cloud and the initial moist air 

cloud, the conditions of the final cloud may be calculated using vapor/liquid equilibrium 

relationships and mass and energy balances. The following sections describe physical property 

data and the algorithm combining mass and energy balances with vapor/liquid equilibrium 

relationships to determine the final cloud conditions. 

4

An intensive variable is a property of a system that does not depend on the quantity of material comprising the

system. Temperature and pressure are examples of intensive variables.

5

Gibbs’s Phase Rule determines the minimum number of independent variables that must be specified to uniquely

establish the intensive state of a system at equilibrium comprising given numbers of components and phases.

6-1
Background Document for Offsite Consequence Analysis, May 1999 

5.1.1.1 Physical Property Data 

Physical property data required to calculate the state of a system includes 

pressure/volume/temperature (PVT) relationships, vapor/liquid equilibrium data, and enthalpy 

data. Because the mixing process occurs at atmospheric pressure, the ideal gas law was used to 

represent PVT behavior for vapor phases. For liquid phases, densities were taken to be constant 

at a value of 690 kg/m3 for ammonia and 1,000 kg/m3 for water. 

The vapor pressure exerted by ammonia/water systems depends on temperature and the 

composition of the liquid phase. Correlations proposed to represent this dependence (Wheatley, 

1987) are: 

P1(X2,T) = (1-X2) Ps,1(T) EXP [-A1/T + B1] (5-1) 

and 

P2(X2,T) = X2 Ps,2(T) EXP (-A2/T + B2) (5-2) 

where: 

P1(X2,T) = partial pressure of water (component 1) as a function of 

temperature and liquid phase composition, Pa 

X2 = mole fraction of ammonia (component 2) in the liquid phase 

T = temperature, K 

Ps,1(T) = partial pressure of pure water as a function of temperature, Pa 

P2(X2,T) = partial pressure of ammonia as a function of temperature and liquid 

phase composition, Pa 

Ps,2(T) = partial pressure of pure ammonia as a function of temperature, Pa 

and A1, B1, A2, and B2 are estimated as: 

A1 = (1 + 3Ra/2 - RaX2) X2

2

 Wa (5-3) 

A2 = (1 + Ra - RaX2) (1-X2)

2

 Wa (5-4) 

B1 = (1 + 3Rb/2 - RbX2) X2

2

 Wb (5-5) 

B2 = (1 + Rb - RbX2) (1-X2)

2

 Wb (5-6) 

Ra, Rb, Wa, and Wb are empirically determined constants with recommended values of -14, ­

14, -174 and -0.74 (Wheatley, 1987). 

Pure component vapor pressures were estimated using Antoine’s equation (Smith and 

Van Ness, 1975): 

Ps,i(T) = exp [ Aa,i - Ba,i/(T + Ca,i) ] (5-7) 

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Background Document for Offsite Consequence Analysis, May 1999 

where: 

Ps,i(T) = equilibrium vapor pressure of pure component i at temperature T, Pa 

T = temperature, K 

and Aa,i, Ba,i and Ca,i are empirically determined coefficients with recommended values of 16.4981, 

2132.5 and -32.98 for ammonia and 18.3036, 3816.44 and -46.13 for water, respectively. The 

utility of these relations is supported by the comparison with pure component and mixture 

vapor/liquid equilibrium data presented in Tables 5-1, 5-2 and 5-3. The pure component 

predictions of Equation 5-7, which are summarized in Tables 5-1 and 5-2, are incorporated into 

the Wheatley model as indicated in Equations 5-1 and 5-2. The accuracy of the comparison of the 

mixture data (Table 5-3) is limited by interpolation of the reported measured data. 

The dependence of enthalpy on temperature for vapor phase components is represented as: 

hv,i = Cpv,i (T-T ) + DHv,i (5-8) r

where: 

hv,i = enthalpy per unit quantity of component i in the vapor phase, J/g-mole 

Cpv,i = heat capacity at constant pressure of component i in the vapor phase 

J/g-mole/K 

T = temperature of vapor phase, K 

Tr = reference temperature, K

DHv,i = latent heat of vaporization of component i, J/g-mole.

The enthalpy of pure liquid components was calculated as: 

hl,i = Cpl,i (T-T ) (5-9) r

where: 

hl,i = enthalpy per unit quantity of component i in the liquid phase, J/g-mole 

Cpl,i = heat capacity at constant pressure of component i in the liquid phase, 

J/g-mole/K 

T = temperature of the liquid phase, K 

Tr = reference temperature, K

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Background Document for Offsite Consequence Analysis, May 1999 

Table 5-1. Comparison of Measured and Predicted Vapor Pressure of Water 

Temperature Saturation Pressure (Pa) 

(K) Measured* Predicted 

273 611.3 593.1 

283 1,164.5 1,204.5 

293 2,290.4 2,313.3 

303 4,165.5 4,219.9 

313 7,253.4 7,358.8 

* data from Table 1 of Keenan and Keyes, 1969 

Table 5-2. Comparison of Measured and Predicted Vapor Pressure of Ammonia 

Temperature Saturation Pressure (MPa) 

(K) Measured* Predicted 

210 0.01775 0.01793 

230 0.06044 0.06091 

250 0.16496 0.16515 

270 0.38100 0.37841 

290 0.77413 0.76211 

310 1.4235 1.3873 

*data from Table 15 of ASHRAE, 1981 

Table 5-3. Comparison of Measured and Predicted Vapor Pressures Above 

Ammonia/Water Solutions 

T Liquid Phase Measured* Predicted 

(K) 

NH3 Mole 

Fraction 

Vapor Phase 

NH3 Mole 

Fraction 

Total 

Pressure(P 

a) 

Vapor Phase 

NH3 

MoleFraction 

Total 

Pressure(P 

a) 

273 0.06 0.74 2.0x103 0.73 2.0x103 

0.25 0.98 2.0x104 0.99 2.6x104 

253 0.29 1.0 9.8x103 1.0 1.2x104 

0.37 1.0 2.0x104 1.0 2.4x104 

0.50 1.0 4.9x104 1.0 5.6x104 

0.63 1.0 9.8x104 1.0 9.8x104 

233 0.28 1.0 2.0x103 1.0 2.6x103 

0.53 1.0 2.0x104 1.0 2.2x104 

0.74 1.0 4.9x104 1.0 4.9x104 

213 0.42 1.0 2.0x103 1.0 2.5x103 

0.63 1.0 9.8x103 1.0 1.0x104 

0.87 1.0 2.0x104 1.0 1.9x104 

*adapted by interpolation of Figure 3-17 of Perry and Chilton, 1973

Values of heat capacities and heats of vaporization are presented in Table 5-4.

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Background Document for Offsite Consequence Analysis, May 1999 

Table 5-4. Heat Capacity and Heat of Vaporization Data 

Component 

Vapor Phase Heat 

Capacity 

(J/g-mole/K) 

Liquid Phase 

Heat Capacity 

(J/g-mole/K) 

Heat of Vaporization 

(J/g-mole) 

Ammonia 23.0 77.1 21459.9 

Water 32.5 75.4 45009.2 

Air 29.0 -- --

The enthalpy of ammonia/water solutions was calculated as: 

hsoln = (1-X2) hl,H2O + X2 hl,NH3 + DHmix (5-10) 

where: 

hsoln = enthalpy per unit quantity of ammonia/water solution, J/g-mole 

X2 = mole fraction of ammonia in the final solution, dimensionless 

hl,H2O = enthalpy per unit quantity of pure liquid water, J/g-mole 

hl,NH3 = enthalpy per unit quantity of pure liquid ammonia, J/g-mole 

DHmix = enthalpy of mixing of ammonia and water per unit quantity of final solution, 

J/g-mole 

and DHmix is estimated as (Wheatley, 1987): 

DHmix = - (1 + Ra - RaX2/2) X2 (1-X2) R Wa (5-11) 

where R is the universal gas constants and all other terms are as defined above. 

5.1.1.2 Algorithm for Determination of Final Cloud Conditions 

Mixing of initial clouds of ammonia and moist air produces a final cloud whose temperature, 

composition, and physical state are initially unknown. In addition, the nature of the equilibrium 

relationships and mass and energy balances describing the mixing process is such that direct 

calculation of the final conditions is not possible. Thus, the iterative procedure represented in 

Figure 5-1 was adopted to solve this problem. The procedure involves three primary elements: 

calculation of final cloud conditions assuming that the final cloud contains solely vapor; 

calculation of dew point pressure for the all-vapor final cloud; and calculation of conditions for a 

final cloud containing both vapor and liquid phases. Calculation of the dew point pressure of the 

assumed all-vapor final cloud is used to identify the physical state of the final cloud. If the sum of 

the vapor pressures of ammonia and water in the all-vapor final cloud is less than their pressures 

at the dew point, the final cloud is all vapor. If the sum of the pressures of ammonia 

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5-

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Background Document for Offsite Consequence Analysis May 1999

Set Conditions of Initial 

Ammonia and Moist Air 

Clouds 

Assume Final Cloud 

All Vapor 

Calculate Final 

Cloud Temperature, Tf 

Calculate Dew 

Point Pressure 

Yes Is No 

Liquid 

Present? 

B A 

Figure 5-1. Algorithm for Determination of Final Cloud Conditions for Mixing of Ammonia and Moist Air Clouds 

6-6
(continued) 

B 

Guess Tf 

Guess liquid phase 

ammonia mole fraction, X2 

Solve mass and 

equilibrium relations 

New 

X2 = No 

Old X2 

Calculate new Tf

New X2 

A 

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Background Document for Offsite Consequence Analysis May 1999

New Tf 

No New Yes 

Tf = 

old Tf 

Calculate Final 

Cloud Density 

Figure 5-1. Algorithm for Determination of Final Cloud Conditions for Mixing of Ammonia and Moist Air Clouds 

(Continued) 

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and water in the all-vapor final cloud is greater than their dew point pressure, the final cloud 

contains both vapor and liquid phases. The following paragraphs describe execution of the three 

elements comprising the solution algorithm. 

For given initial conditions, the temperature and composition of a final cloud containing solely 

vapor may be determined using mass and energy balances. The mass balance for each component 

was expressed as: 

(Nv,i + Nl,i) -

final = (Nv,i + Nl,i) –-initial (5-12) 

where: 

Nv,i = number of moles of component i in the vapor phase, g-mole 

Nl,i = number of moles of component i in the liquid phase, g-mole 

and the vertical brackets indicate evaluation at initial and final conditions. For the case of no 

liquid present in the final cloud, Nl,i -final is equal to zero in each of Equations 5-12, and Nv,i 

–final can be calculated directly for each component. The energy balance for the mixing process 

was expressed as: 

S (Nv,ihv,i + Nl,ihv,i) –final + S (Nl,i) DHmix –final = S (Nv,ihv,i + Nl,ihl,i)–initial + S (Nl,i) DHmix –initial (5-13) 

where all quantities are as defined above, the summations are taken over components, and the 

vapor and liquid phase enthalpies are evaluated according to Equations 5-8 and 5-9. For the 

assumed conditions of an all-vapor final cloud and the final cloud component masses determined 

by Equation 5-12, Equation 5-13 can be directly solved for the final cloud temperature. 

Calculation of the dew point pressure is based upon specification of the temperature and 

vapor phase mole fractions of the cloud and identification of the liquid phase composition in 

equilibrium with the specified vapor phase composition. By definition, the liquid phase mole 

fractions sum to unity: 

S Xi = 1 (5-14) 

where Xi are liquid phase mole fractions. The vapor/liquid equilibrium constraints may be 

expressed as: 

Yi = Ki Xi (5-15) 

where Yi and Xi are vapor and liquid phase mole fractions, respectively, and the Ki are 

vapor/liquid equilibrium constants calculated as: 

Ki = (1/Xi) Pi/Pt (5-16) 

where the Pi are calculated using Equations 5-1 and 5-2, Pt is total pressure, and air is taken to be 

non-condensible. The dew point constraint, Equation 5-14, becomes: 

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S (Yi/Ki) = 1 (5-17) 

where the Yi are the specified vapor cloud mole fractions, and the Ki are functions of liquid phase 

mole fraction and the specified temperature. Because air is effectively non-condensible under 

conditions occurring in ammonia releases, the vapor phase mole fractions may be expressed on an 

air-free basis, and use of Equations 5-14, 5-15 and 5-16 was reduced to the condition of locating 

the liquid phase ammonia composition (X2) in equilibrium with the specified vapor phase at the 

specified temperature. The algorithm for this procedure is presented in Figure 5-2. If the 

calculated dew point pressure is less than the sum of the specified partial pressures of water and 

ammonia, the final cloud is solely vapor, and the density was calculated using the ideal gas law. If 

the sum of the partial pressures of water and ammonia is greater than the dew point pressure, a 

liquid phase will form, and the procedure described in the following paragraphs was used to 

determine final cloud conditions. 

For a final cloud containing both vapor and liquid phases, the algorithm presented in the 

portion of Figure 5-1 below connection point B was used to determine final cloud conditions. 

The mass balances of Equation 5-12 were combined with the vapor/liquid equilibrium 

relationships of Equations 5-15 to derive the constraint: 

F = S { [Zi (1-Ki)]/[1-(1-Ki)b] } = 0 (5-18) 

where: 

F = vapor/liquid equilibrium objective function, dim 

Zi = mole fraction of component i based on total quantity, dim 

Ki = vapor/liquid equilibrium constant, dim 

b = molar ratio of vapor to liquid in the final cloud, dim 

Ki is calculated using Equations 5-1, 5-2 and 5-16, and the summation is over components. 

As indicated in Figure 5-1, the solution procedure involves generation of initial estimates of 

final cloud temperature (Tf) and liquid phase ammonia mole fraction (X2), which allows 

calculation of the Ki

. After solving Equation 5-18 for b, the number of moles of each component 

in the vapor and liquid phases was calculated using the mass balances of Equations 5-12 and the 

equilibrium constraints of Equations 5-15. The composition of the liquid phase was then 

compared with the initial estimate and a new estimate of X2 generated to allow re-calculation of 

cloud composition. When the final cloud composition is successfully determined for a given 

estimate of cloud temperature, the cloud temperature is re-calculated using the energy balance of 

Equation 5-13. The mass and energy balance procedure is iterated until final cloud temperature 

and composition are determined. The density of the final cloud is calculated using the ideal gas 

law and the assumption of complete entrainment of the liquid phase. 

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Figure 5-2. Algorithm for Calculation of Dew Point Pressure 

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5.1.2 RESULTS 

Representative results were developed for three cases bounding potential conditions. The first 

case, representative of worst-case scenario conditions, involves release of vapor and liquid 

ammonia at the atmospheric pressure boiling point (240 K), with 80 percent of the ammonia in the 

liquid phase and mixing with warm, moist air (relative humidity = 50 percent). The results 

presented in Table 5-5 indicate that the final cloud initially experiences evaporative cooling and 

remains denser than ambient air even after entrainment of enough air to fully vaporize the 

ammonia. Liquid droplets, comprised primarily of condensed water, persist at high air-toammonia mixing ratios at moderate relative humidities. The second example, also a worst-case 

scenario, involves release of a two-phase cloud of ammonia and mixing with warm, dry air. The 

results presented in Table 5-6 show the evaporative cooling step, but indicate that the ammonia 

liquid phase is completely evaporated after mixing with 11 kilograms of air per kilogram of 

ammonia. Comparison of the results of Tables 5-5 and 5-6 indicates that heat of mixing offsets 

the evaporative cooling effect and decreases the density of the final cloud. The third case involves 

release of vapor ammonia into dry air of variable temperature. The results presented in Table 5-7 

indicate that the final cloud remains less dense than air even at relatively low ambient air 

temperatures. 

Table 5-5. Final Cloud Conditions for a Worst-Case Scenario,

Two-Phase Release with Moist Air*

Mass of Air 

Mass of Ammonia 

Final Cloud Conditions 

T (K) Density(k 

g/m3

) 

Fraction of NH3in 

Liquid Phase (%) 

Mole Fraction of 

NH3 in Liquid 

Phase 

1 221.5 2.053 67.1 0.986 

3 214.7 1.711 48.7 0.945 

6 214.0 1.597 23.7 0.808 

9 226.7 1.492 9.5 0.530 

11 238.8 1.424 6.8 0.397 

20 266.8 1.294 3.3 0.176 

100 293.3 1.190 0.6 0.021 

* Initial Conditions 

• 80% of ammonia in Liquid Phase, T = 240 

• air temperature = 298 K 

• relative humidity = 50% 

• air density = 1.186 kg/m3 

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Table 5-6. Final Cloud Conditions for a Worst-Case Scenario,

Two-Phase Release with Dry Air*

Mass of Air 

Mass of Ammonia 

Final Cloud Conditions 

T (K) Density 

(kg/m3

) 

Fraction of NH3 in 

Liquid Phase 

1 221 2.100 69.3 

5 209.3 1.689 41.6 

11 205.9 1.626 2.4 

20 243.1 1.407 0.0 

100 286.4 1.225 0.0 

*Initial Conditions 

• 80% of ammonia in Liquid Phase, T = 240 

• air temperature = 298 K 

• relative humidity = 0% 

• air density = 1.186 kg/m3 

Table 5-7. Final Cloud Conditions for All Vapor Release with Dry Air* 

Ambient Air Conditions Final Cloud Conditions 

T (K) Density 

(kg/m3

) T (K) Density 

(kg/m3

) 

263 1.344 249 1.048 

273 1.295 253 1.031 

283 1.249 258 1.014 

293 1.219 263 0.997 

*Initial Conditions 

• ammonia release all vapor, T = 240 K 

• air-to-ammonia mass mixing ratio equal to unity 

• 0% relative humidity 

5.2 EFFECT ON PREDICTION OF DISTANCES TO TOXIC ENDPOINT 

Table 5-8 shows an example of the effect on SACRUNCH runs of including the new 

thermodynamics, Wilson meandering, and both. As can be seen, the effect is small, but does lead 

to a small reduction in predicted distances, which has been taken into account in the AR and 

WWTPs guidance. 

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Table 5-8. Example of the Effect of New Thermodynamic Model and Meandering of

Anhydrous Releases, Worst-Case, Rural Conditions, 75% RH

Rate of Release 

(lbs/min) 

Distance to Toxic Endpoint (miles) 

Old 

Model 

With Wilson 

Meandering 

With New 

Thermodynamics 

With Wilson 

Meandering & 

New 

Thermodynamics 

* 

10 0.19 0.19 0.20 0.20 

20 0.27 0.26 0.28 0.27 

50 0.41 0.40 0.42 0.42 

100 0.57 0.56 0.58 0.58 

200 0.80 0.78 0.81 0.80 

500 1.28 1.26 1.27 1.25 

1,000 1.85 1.82 1.79 1.77 

2,000 2.72 2.68 2.54 2.52 

5,000 4.59 4.54 4.11 4.07 

10,000 6.74 6.69 5.94 5.90 

20,000 9.59 9.55 8.60 8.54 

50,000 14.27 14.23 13.8 13.74 

* These results do not exactly match those in the AR. Minor details of input have been changed. 

5.3 POTENTIAL FOR LIFT-OFF 

There are certain types of initially heavy plumes that can potentially become buoyant and may 

lift off the ground. These include hydrogen fluoride (HF) releases in moist air, where the heat 

liberated by condensation of HF/water droplets can cause the plume’s buoyancy to become 

positive as air is entrained. Another possibility is the uranium hexafluoride (UF6)/moist air system 

because the UF6-water reaction is highly exothermic. Finally, it is conceivable that initially 

denser-than-air ammonia plumes could become buoyant as they dilute. 

Briggs (1973b) has developed a simple approach that requires the calculation of a lift-off 

parameter: 

Lp = ghDr/(rau2

*) (5-19) 

where lift-off will occur if Lp > 30 (Meroney, 1984). Here, g is the acceleration due to gravity 

(m/s2), h is the height of the cloud (m), Dr is the difference in density between the air and the 

plume (kg/m3), ra is the density of air (kg/m3), and u* is the friction velocity (m/s). 

For UF6, HF, and ammonia, the SACRUNCH computer model calculates Lp at distances 

downwind of the transition point at which the plume ceases to be denser than air. If Lp exceeds 

30, in any weather condition, this information will be printed out, and the user must judge whether 

there will be more than trivial plume rise. Table 5-9 contains an illustration of the potential for 

lift-off for a 1,000 lb/min release of flashing liquid ammonia. As can be seen, there appears to be 

no potential for lift-off until the plume has diluted below the toxic endpoint 

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Table 5-9. Illustration of the Potential for Lift-Off 

Distance 

Downwind (m) Lp 

Average Concentration 

(kg/m3

) 

Peak 

Concentration 

(kg/m3

) 

1,950 6.4 2×10-4 5.9×10-4 

2,400 20.5 8.1×10-5 2.4×10-4 

3,000 31.9 4.4×10-5 1.3×10-4 

4,500 48.0 1.9×10-5 3.8×10-5 

Assumptions: 

Anhydrous Ammonia, flashing liquid release 

Release Rate 1,000 lb/min 

Worst-Case Weather Conditions, Rural Site 

RH = 75% 

Results: 

Cloud evolves out of denser-than-air phase ~ 1800 m downwind with mean 

concentration ~ 4×10-4 kg/m3 

Toxic endpoint: 1.4×10-4 kg/m3 (200 ppm) at ~ 2,900 m based on peak 

concentration 

Conclusion: 

No lift-off until after toxic endpoint 

No counter-examples found in sensitivity studies 

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Background Document for Offsite Consequence Analysis, May 1999 

CHAPTER 6: EFFECT OF AMMONIA RELEASES ON STRUCTURES 

The purpose of this chapter is to discuss the consequences of releases inside rooms, such as 

the compressor room in an ammonia refrigeration plant or a room containing chlorine or sulfur 

dioxide vessels at WWTPs. The work presented here has been used as the basis for building 

mitigation models in the AR and WWTP guidance, but not in OCAG. 

This chapter provides methods for prediction of pressures inside buildings and the subsequent 

rate of release to the atmosphere. Important parameters include the quantity of ammonia, 

chlorine, or sulfur dioxide available for release, the time over which the release takes place, the 

volume of the room, the presence of airborne liquid droplets, leakpaths in the structure, and the 

characteristics of the ventilation system. 

As discussed in Chapter 3, experimental evidence indicates that in the case of unobstructed 

releases, ammonia, chlorine, or sulfur dioxide droplets formed in the release remain suspended in 

the vapor phase and evaporate. Obstructions can be effective in facilitating the rain-out of 

droplets with removal efficiencies on the order of 75 percent of the liquid reported. The 

remaining 25 percent of the liquid release is assumed to be entrained in the vapor release. Chapter 

3 presents an approximate rule-of-thumb: if released inside a building as a flashing liquid release, 

60 percent collects on the floor as a relatively slowly evaporating pool, and 40 percent remains 

airborne as a 50:50 mixture of vapor and liquid droplets. 

Evaluation of building structural integrity and effectiveness of mitigation for intact structures 

was based on consideration of single-phase releases of vapor into buildings containing leakpaths 

and engineered vents capable of relieving pressure. The vapor release for the analysis included 

the contribution of vapor formed during depressurization of liquefied gas stored under pressure 

(flashing). Building release attenuation factors estimated in this chapter are applicable to both the 

entrained liquid and gaseous portions of the release. 

This document considers releases over 10 minutes. EPA also analyzed sudden releases. Its 

analysis indicated that for pressure-tight buildings, a sudden release could damage the building 

sufficiently to eliminate its ability to mitigate the release unless the size of the building is large in 

relation to the mass of the chemical. In the more likely case of a building with leakpaths and 

ventilation, a sudden release will generally not damage the building. 

6.1 PROLONGED RELEASES 

Gradual releases of stored material as vapor may not be capable of producing the pressure 

differentials predicted for instantaneous releases. Over periods of 10 minutes, ammonia, chlorine, 

or sulfur dioxide may escape through leakpath and ventilation system flowpaths at rates large 

enough to relieve the initial pressure disturbance. The potential magnitude of this behavior was 

investigated for a leakpath flow that would produce a room change-over rate of one-half volume 

per hour at undisturbed flow conditions. This assumption does not preclude the possibility that 

there may be significantly different change-over rates to be investigated on a case-by-case basis. 

The approach applied was to estimate leakpath resistance factors for representative conditions and 

use these resistance factor estimates to evaluate the building pressure response to a specified rate 

of either ammonia, chlorine, or sulfur dioxide release from a vessel inside the building. 

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Leakpath flow areas were estimated based on the assumption that one-half of a volume of the 

room is lost per hour (ASTM, 1986) and that the driving force for this loss is developed by air 

flow around the building. For a given windspeed, the pressure differential may be estimated using 

correlations based on experimental data (Blevins, 1984). The pressure differential may then be 

used in conjunction with the assumed normal condition leakage rate to estimate resistances for the 

in- and out-leakage paths. This leakage resistance calibration procedure also assumed that the 

cross-sectional area of each leakpath was proportional to the length of the building and that the 

building length was twice the building width. Engineered vent areas were estimated based on the 

assumption that linear air velocities through the vent were 8 m/s (1,600 ft/min), a value consistent 

with standard practice (ACGIH, 1986). Release rate of stored material into the room (i.e., Ri

) 

was represented as a piecewise continuous function, allowing simulation of transient release with 

variable dependence on time. Room density and pressure conditions and vent flow rates were 

estimated using FIRAC (Gregory and Nichols, 1986), a computer code capable of simulating 

ventilation system response to accident conditions. FIRAC is a node/branch network model in 

which nodes represent rooms and branches represent ducts, blowers, and filters. In this case, 

leakpaths were modeled as ducts of small size, and the ammonia release was represented as mass 

injection with associated evaporative energy loss. 

6.1.1 Building Structural Response 

Potential conditions that could be established were investigated for a 10-minute release of 

liquid ammonia stored at 310 K (98 oF) and 1.4 MPa (206 psia). The simulation estimated the 

ammonia injection rate required to produce an overpressure large enough to threaten structural 

integrity. An overpressure value of 6,895 Pa (1 psia) was adopted for this criterion. Release 

modeling predicted immediate evaporation of approximately 20 percent of the ammonia flow with 

subsequent evaporation of the remaining mass. High-accident condition leakpath flows were 

predicted for room volumes from 500 m3

 to 10,000 m3 with 6,710 kg/10 min (14,790 lb/10 min) 

required to produce the 6,895 Pa (1 psia) overpressure for the 500 m3 room. Very large release 

rates were required to approach the overpressure criterion for rooms in the 1,000 m3

 to 10,000 m3 

range. This general conclusion was verified using the single-room mass balance model. Because 

ammonia has lower density than either chlorine or sulfur dioxide, the results of this ammonia 

analysis also indicate that prolonged releases of chlorine or sulfur dioxide will not threaten 

building integrity. 

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6.1.2 Building Attenuation of Release 

Continuous release of either ammonia, chlorine, or sulfur dioxide into a ventilated room will 

produce an increase in concentration of gas which approaches a constant level determined by the 

gas injection rate, ventilation rate, and room volume. Once steady state conditions are established 

the removal rate equals the injection rate and the fractional release factor equals unity. For 

transient conditions occurring before establishment of a steady state, such as may occur for tenminute release periods, the fractional release factor (FR10) may be less than unity. A single-room 

mass balance model was used to estimate FR10 for set of values of q (ratio of room volume to the 

amount of ammonia, chlorine, or sulfur dioxide vapor release) and Nv (ventilation rate as number 

of room changes per hour) at constant rate of gas addition. The results of these calculations are 

presented in Table 6-1 for ammonia and Table 6-2 for chlorine and sulfur dioxide. Results for 

chlorine and sulfur dioxide are similar due to similarity in molecular weight of the gases. As 

expected, for high ventilation rates and small rooms, steady state is quickly established and 

fractional release factors approach unity. For larger rooms and lower ventilation rates, building 

attenuation of a release can be appreciable. For cases in which overpressurization effects are 

small, an analytical solution to Equation 6-1 may be used to corroborate the results presented in 

Tables 6-1 and 6-2. 

P1,i = Fsat(T1,i) (6-1) 

where: 

P1,i = equilibrium partial pressure of the i’th component, either ammonia, chlorine, or 

sulfur dioxide at temperature T1,i, Pa 

Fsat = equilibrium relation between pressure and temperature for the i’th component, 

either ammonia, chlorine, or sulfur dioxide 

T1,i = temperature of ammonia, chlorine, or sulfur dioxide at the end of the first step K 

The vapor/liquid equilibrium relationship is available in tabular form for ammonia (ASHRAE, 

1981), chlorine and sulfur dioxide (Perry and Chilton, 1973). 

For negligible overpressurization, constant gas addition and constant ventilation rate, 

fractional release rate is given by: 

FR = 1 - (1/Nvt){1 - exp (-Nvt)} (6-2) 

where all variables are as defined above. Evaluation of Equation 6-2 for time of 0.1667 hours (10 

minutes) and values of Nv of 1, 5, 10, 20, 30, and 40 hr-1 yields values of FR10 of 0.08, 0.32, 0.51, 

0.71, 0.80, and 0.85, respectively. These values are in agreement with the values of Tables 6-1 

and 6-2 for the high room volume to vapor mass release case (i.e., q = 10) which would produce 

the smallest overpressures. 

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6.2 SUMMARY OF CONCLUSIONS 

For prolonged releases, including those occurring over ten-minute periods, failure of buildings 

of industrial size would not be expected. The presence of the building serves to attenuate 

transient releases and attenuation is effective for relatively small buildings ventilated at low rates. 

Attenuation is small for buildings ventilated at high rates as would occur if emergency ventilation 

systems were used. 

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Background Document for Offsite Consequence Analysis, May 1999 

Table 6-1. Ten-Minute Building Release Attenuation Factors for Continuous 

Releases of Ammonia 

q* 

(m3

/kg) 

Nv 

(hr-1) 

FR10 

(dim) 

10.0 0 0.07 

1 0.08 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

5.0 0 0.13 

1 0.13 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

2.0 0 0.29 

1 0.29 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

1.0 0 0.47 

1 0.47 

5 0.47 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

q* 

(m3

/kg) 

Nv 

(hr-1) 

FR10 

(dim) 

0.5 0 0.67 

1 0.67 

5 0.67 

10 0.67 

20 0.71 

30 0.80 

40 0.85 

0.25 0 0.83 

1 0.83 

5 0.83 

10 0.83 

20 0.83 

30 0.83 

40 0.85 

0.05 0 0.97 

1 0.97 

5 0.97 

10 0.97 

20 0.97 

30 0.97 

40 0.97 

0.02 0 0.99 

1 0.99 

5 0.99 

10 0.99 

20 0.99 

30 0.99 

40 0.99 

* Values of q in m3/kg can be converted to values of q in ft3/lb by multiplying by 16. 

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Table 6-2. Ten-Minute Building Release Attenuation Factors for Prolonged Releases 

of Chlorine and Sulfur Dioxide 

q* 

(m3

/kg) 

Nv 

(hr-1) 

FR10 

(dim) 

10.0 0 0.02 

1 0.08 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

5.0 0 0.03 

1 0.08 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

2.0 0 0.08 

1 0.08 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

1.0 0 0.15 

1 0.15 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

q* 

(m3

/kg) 

Nv 

(hr-1) 

FR10 

(dim) 

0.5 0 0.28 

1 0.28 

5 0.32 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

0.25 0 0.46 

1 0.46 

5 0.46 

10 0.51 

20 0.71 

30 0.80 

40 0.85 

0.05 0 0.85 

1 0.86 

5 0.86 

10 0.86 

20 0.86 

30 0.86 

40 0.86 

0.02 0 0.94 

1 0.94 

5 0.94 

10 0.94 

20 0.94 

30 0.94 

40 0.94 

* Values of q in m3/kg can be converted to values of q in ft3/lb by multiplying by 16. 

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Britter, R.E. and S.T. Cole, “The Evaluation of Technical Models Used for Major Accident 

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Chamberlain, A.C. and R.C. Chadwick, “Deposition of Airborne Radio-iodine Vapour,” 

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Chan, S.T., H.C. Rodean and D.N. Blewitt, “FEM3 Modeling of Ammonia and Hydrofluoric Acid 

Dispersion,” in CCPS (1987) pp. 116-154, 1987. 

Clough, P.N., D.R. Grist and C.J. Wheatley, “The Mixing of Anhydrous Hydrogen Fluoride with 

Moist Air,” International Conference on Vapor Cloud Modeling, American Institute of Chemical 

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Cox, R.A. and R.J. Carpenter, “Cloud Dispersion Model for Hazard Analysis,” Proc. 1st Heavy 

Gas and Risk Assessment Symposium, Battelle Institute, Frankfurt, West Germany, 1979. 

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Ermak, D.L., “User’s Manual for the SLAB Model, An Atmospheric Dispersion Model for 

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