Making RMP Hazard Assessment Meaningful John F. Murphy and Keith A. Zimmennann Rh4T Inc., Austin, TX

The Brazoria County Petrochemical Council, 13 com- panies that are working together to enhance relations between industy and the community, united in a joint effort at complying with the EFA’s Risk Management Program. One of the significant issues the group had to address was the need to develop meaningful hazard assessment for presentation to the public. The EPA’s “Table Look-Up Approach” found in the Offsite Come quence Analysis Guidance document is certainly a good tool; however, the built-in conservatism results in over- estimates ofpotential hazard areas. Much more mean- ingful results are shown to be obtained using one of the hazard release models.

The value of using a credible scenario with realistic meteorological data is demonstrated through the con- sistently smaller amas predicted ly the PHASTModel for planning purposes. Realistic scenarioq failure modes and realistic modelparameters are important so that the risk to the public is not overstated. Proprieta y models such as PHAST are invaluable in providing more meaningful consequences for planning purposes.

INTRODUCTION

The Brazoria County Petrochemical Council, 13 compa- nies that are working together to enhance relations be- tween industry and the community, have initiated a joint effort at complying with the EPAs Risk Management Pro- gram. One of the significant issues the group is addressing is hazard assessment. Some of the issues regarding hazard assessment include choice of models, (or tables), model parameters, and alternative release scenarios. While the EPAs “Table Look-Up Approach” found in the Offsite Consequence Analysis Guidance document is good and can satisfy the legal requirements of RMP, much more mean- ingful results can be obtained using one of the hazard re- lease models.

Background on RMP

The Risk Management Program rules were finalized on June 20, 1996. Companies that are affected have three years to comply with the regulation. The regulation specifies re- quirements based on the level of process risk. Hazard as- sessment is used to help determine the level of process risk. The EPAs regulatory approach encourages risk communi- cation and dialogue at the local level. This will allow the public to drive industry action based on information. Meaningful hazard assessment is necessary to accomplish these objectives.

HAZARD ASSESSMENT REQUIREMENTS

The Risk Management Program hazard assessment re- quires calculation of potential exposure impact distances to specific toxic or flammable substances “endpoints.” The results of these calculations are of key interest to nearby communities. The hazard assessment results are also used to develop the prevention program and the emergency re- sponse plan.

The Risk Management Program requires one worst-case scenario for each Program 1 process. For Program 2 and 3 processes, the rule requires one worst-case scenario for each toxic substance and one worst-case scenario for flammable substances and at least one alternative release scenario for each toxic substance and one alternative re- lease scenario to represent all flammables. More scenarios may be required if different off site areas are affected.

The “worst-case release” scenario is well-defined by the regulation. It is the largest quantity of a regulated sub- stance resulting from a failure from a single vessel or process piping failure. It assumes ,a 10 minute release un- der the worst case meteorology (i.e., F stability and 1.5 m/sec wind speed). Passive mitigation measures can be considered if they are capable of withstanding destructive events. The maximum possible inventory must be used with consideration of written administrative controls. Other parameters are also specified for worst-case scenarios re- garding toxic and flammable substances.

The meaningful hazard assessments are the alternative release scenarios. They are important because of their higher credibility. These scenarios are the ones the com- munity must understand and the ones for which a facility operator should prepare. The prevention and mitigation measures that have been implemented to address these scenarios must be clearly communicated and understood. The alternative release scenarios can be selected from acci- dent history or process hazard analysis. They must show offsite endpoint values. The following release/failure sce- narios are suggested because of their frequency of occur- rence in the chemical process industry:

transfer hoses sight glasses/flexible joints/fragile devices process piping/flanges/welds/valves vessel or pump crack/seals emergency relief valves/rupture disk shipping container mishaps

Both passive and active mitigation can be considered when modeling alternative release scenarios. Passive miti- gation may include diking or buildings. Active mitigation

Process Safety Progress (Vol. 17, NO. 4) 238 Winter 1998

may include emergency block valves, deluge systems, alarm systems or other systems that require human inter- vention or mechanical or electrical activation.

MEANINGFUL EXPLOSION MODELING

For flammable chemicals, the endpoints of concern are 1 psi overpressure (for vapor cloud explosions), the lower flammability limit (for flash fires or vapor cloud explo- sions), 5 kW/m2 for 40 secs (for pool fires), radiant heat effects for BLEVE (Boiling Liquid Expanding Vapor Explo- sion) or other considerations such as vapor cloud deflagra- tions, detonations, and jet fires.

For flammability limits, dispersion model calculations are used. For radiant endpoints appropriate dispersion model scenarios are considered. For overpressure, the TNT equiv- alency or alternative methods are used.

For a worst-case release scenario for flammables, it is as- sumed that the material vaporizes instantly and results in a vapor cloud explosion. If the TNT equivalency model is used, then a 10% yield factor for efficiency must be used, although the multi-energy methods can be used as an al- ternative.

For the more meaningful alternative release scenario, specific parameters are used for modeling. For example in- stead of the 10% yield factor for TNT equivalency, a more realistic 2 to 30/0 yield factor can be used if substantiated with historic data. Also instantaneous vaporization of the flammable substance does not have to be assumed if typi- cal scenario parameters indicate that this is not physically possible. Also the quantity involved in the scenario can be limited by safety interlock systems and/or emergency block valves. It is important that the more meaningful parameters and mitigation systems are communicated to the public so that they have a more realistic perception of the risk.

MEANINGFUL METEOROLOGICAL DATA FOR MODELING

Worst Case Scenario Parameters

The RMP program rules strictly require the use of certain meteorological parameters for modeling the worst case scenario analysis. These parameters include F stability, 1.5

m/s wind speed, and the maximum temperature that has occurred in the area for the past 3 years. Each of these pa- rameters are important in determining the amount of turbu- lent dispersion that will take place. A brief examination of the parameters often helps to understand how each one af- fects the outcome of the offsite consequence analysis.

Atmospheric Stability Class

The “F stability” parameter refers to a simple system of classlfying the stability of the lower layer of the atmo- sphere (see Table 1). By stability, we refer primarily to the degree of turbulence (both thermal and mechanical driven turbulence) present in the atmosphere that can disperse airborne material. Atmospheric stability classes A, B, and C are daytime stability classes. Class A is the most unstable and will occur during daylight hours when maximum in- coming solar radiation is occurring with little or no cloud cover and with relatively light wind speeds. Under these conditions, the ground will be warming rapidly and trans- ferring heat to the lowest layer of air near the surface of the ground. This warmed air will then transfer this heat up- ward through turbulent mixing of the air. Under these con- ditions, material released into the air will be rapidly dis- persed. Stability classes B and C also refer to unstable at- mospheric condition; however, B is only moderately unsta- ble and C is considered only slightly unstable. Atmospheric stability class D refers to a “neutral” atmosphere. This con- dition may occur either during the daytime or during the nighttime. Class D is almost always the most likely stability class that occurs at a given location. Often, class D occurs more than 50 percent of the time. Stability class E and F are nighttime stability classes. They refer to atmospheric condi- tions in which little energy is available in the atmosphere to cause rapid dispersion to occur. Class F stability is the most stable condition.

Wind Speed

Wind speed is an important factor that affects the evapo- ration of liquids spilled on the ground, the rate at which material released into the air moves downwind, and the degree to which the material is mixed and dispersed in the atmosphere. The RMP rules require a wind speed of 1.5 m/s

TABLE 1. Atmospheric stabilii Classes

Surface Wind Speed Night Thinly Overcast at 10 Meters Day

Meters per Miles per or 24/8Low I 3 / 8 Incoming Solar Radiation Second Hour Strong* Moderate Slight** Cloud Cloud

< 2 < 4.5 A A-B B 2-3 4.5-5 A-B B C 3-5 5-11 B B-C C 5-6 11-13 C C-D D > 6 > 13 C D D

E D D D

F E D D

Class A is the most unstable, class D is neutral, class F is the most stable. The neutral class D should be assumed for overcast conditions during day or night. *Sun high in the sky with no clouds. Solar radiation would be reduced to moderate with broken middle clouds (5/8 to 7 8 cloud cover) and to slight with broken low clouds. Sun low in the sky with no clouds. **

Source: D. Bruce Turner [ Z ] .

Process Safety Progress (Vol. 17, No. 4) Winter 1998 239

(3.4 miles per hour). This is an extremely low wind speed. While this low wind speed would tend to maximize the concentration of material in a plume or puff as it moves downwind, it would also tend to minimize the evaporation of spilled liquid on the ground.

Ambient Air Temperature

The ambient air temperature affects the rate of evapora- tion of spilled liquid on the ground. A greater ambient air temperature would tend to enhance the evaporation rate of the liquid. In addition, the air temperature affects the buoyancy of gases released into the air. If a warm or hot gas is released into an atmosphere that is cooler than the gas, then the gas will have a certain degree of buoyancy that will cause it to rise and disperse at a greater height above the ground. This would tend to lower ground level concentrations. As a result, the greater the ambient temper- ature, the less the effect of buoyancy.

Summary of Worst Case Scenario Parameters

As stated above, the worst-case scenario must be mod- eled with F stability class, 1.5 m/sec wind speed, and the maximum temperature that has occurred over the most re- cent 3 year period. The combination of F stability and 1.5 m/s wind speed is a logical one. Stability class F cannot occur with much greater wind speeds than 1.5 m/sec be- cause the greater wind speed result in more mechanical turbulent mixing and a less stable atmosphere. However, the use of the highest temperature over the last 3 years tends to hurt the credibility of the worst-case scenario. Since the F stability class can only occur during the nighttime hours, it is not correct to combine it with the maximum hourly temperature that has occurred in a given area. The maximum ambient air temperature would have occurred at a time during the day when maximum incoming solar radi- ation was occurring. Clearly, this would not coincide with a nighttime F stability case. However, there is no option to adjust the meteorological data when modeling the worst case scenario.

Alternative Release Scenario Parameters

The alternative release scenario becomes the more cred- ible scenario to study because of the more realistic release situations that are considered and because of the more re- alistic meteorological parameters that are allowed. The RMP rules only provide general guidance on the meteorological data that may be used in the alternative release scenario modeling. The definition given in 40 CFR 868.3 for typical meteorological data is:

“Typical meteorological conditions” means the tempera- ture, wind speed, cloud cover, and atmospheric stabil- ity class, prevailing at the site based on data gathered at or near the site or from a local meteorological station.”

In 40 CFR 568.22, relatively little additional guidance is given:

“For analysis of alternative scenarios, the owner or oper- ator may use the typical meteorological conditions for the stationary source.”

Atmospheric Stability Class

As shown above, the RMP rules do not specifically de- fine what typical meteorological conditions mean. Every reference to meteorological data for the alternative release scenario simply refers back to the term “typical meteoro- logical conditions.” In 40 CFR §68.22(b), in which guidance for the appropriate atmospheric stability class is given, the rule again just states:

“For analysis of alternative scenarios, the owner or oper- ator may use the typical meteorological conditions for the stationary source.”

If the term “typical condition” is taken to mean, “the most likely to occur condition,” then the most appropriate atmo- spheric stability class condition to model would be “Class D” or neutral atmospheric conditions. As previously men- tioned, class D can occur either during the daytime or dur- ing the nighttime. Class D is always the recommended sta- bility class to model under wind speed conditions greater than 6 m/sec. In addition, anytime overcast conditions oc- cur, Class D is the recommended stability class to use.

An examination has been made of ten National Weather Service stations located in Texas. In every case, the occur- rence of D stability has been greater than 50% of the time. As a result, one can assume that Class D stability is typical for a given site.

Wind Speed

The appropriate wind speed for the alternative release scenario gives the same guidance as stated in 40 CFR §68.22(b) for the atmospheric stability class. That is, one should use “typical meteorological” data. In this case, typi- cal meteorological data generally means “average” data for a site. The annual average wind speed for a site would provide a good fit to the requirement to use “typical” data.

Ambient Air Temperature

The appropriate ambient air temperature for the alterna- tive release scenario has identical guidance provided in the rules. In 40 CFR §68.22(c), the rule states:

“For analysis of alternative scenarios, the owner or oper- ator may use typical temperature/humidity data gath- ered at the stationary source or at a local meteorologi- cal station.”

For ambient air temperature, the “typical” data could mean the “average” ambient air temperature for a site. This would provide a good alternative to the use of the maxi- mum air temperature as required in the rules for worst-case scenario.

Sources of Alternative Release Scenario Meteorological Data

One of the most onerous burdens for a facility operator is locating a source of meteorological data for their site. In some cases, a facility may already be collecting on-site me- teorological data for other purposes. If enough data has been collected at the site and if the data has been quality assured at a regular interval, then this data could be an ex- cellent source of meteorological data for NvfP modeling. Since a three-year period is mentioned in the RMP rules

Process Safety Progress (Vol. 17, No. 4) 240 Winter 1998

with respect to determining the maximum ambient air tem- perature for a site, it is reasonable to assume that a three year period of on-site data would be acceptable to EPA for determining typical meteorological conditions. For Preven- tion of Significant Deterioration (PSD) modeling, EPA will accept one year of meteorological data from an on site sta- tion.

In many cases, a facility does not have on site meteoro- logical data. Or, the data has not been routinely quality as- sured. In this case, the facility operator must obtain the nearest appropriate meteorological data. The source of this data may be:

National Weather Service station State or local government air monitoring station University meteorological station Television or school weather network

In general, the order of preference of meteorological data is that given above. The U.S. National Weather Service pro- vides the most reliable collection of meteorological data that is available. The quality assurance procedures are rig- orously followed and in most cases, data has been col- lected for many decades from a given location. The use of other data should always be preceded by a close examina- tion of their quality assurance procedures and the quality of their data collection devices.

If the National Weather Service station is chosen to be used as the source of meteorological data, then there are several avenues available for obtaining the data. The Na- tional Climatic Data Center is the archive of all National Weather Service data. Generally a summary of the climato- logical data for a given site can be obtained through a phone call order or through an order placed on their Inter- net web site. Summaries of the climatological data from a given station can be found in a publication called the “Lo- cal Climatological Data” or “LCD” for short. This four page summary will give a facility operator the annual average wind speed, temperature, and barometric pressure for the area.

Another less well known source of meteorological data is the U S . National Renewable Energy Laboratory (NREL). This agency has compiled a complete data set of “typical meteorological years” for every Class 1 National Weather Service station in the United States. The purpose of the data set is to assist persons developing solar energy systems or wind power systems at various locations in the U.S. This data set consists of hourly meteorological data for a com- plete “typical” year. The data set used to develop a typical year was 1961 through 1990. A CD (compact disk) contain- ing this data is available, free of charge, from the National

Renewable Energy Laboratory. The data for a single station may be easily read from the CD by a spreadsheet program. Then, a simple average can be obtained for the ambient air temperature, wind speed, and barometric pressure for the site. This annual average value from the “typical” year of data will provide a suitable modeling parameter for the al- ternative release scenario.

Example Scenario for Sulfur Dioxide Release

As previously mentioned, the worst-case scenario re- quires the entire contents of a vessel to be emptied in a 10 minute period and be dispersed under the worst meteoro- logical conditions with respect to dispersion. The predicted toxic end point results can vary considerably from the worst case scenario to the alternative release scenario.

The example considered here is a vessel containing 25,000 pounds (lbs) of sulfur dioxide (SO,). It is assumed that this vessel is not refrigerated and that the sulfur diox- ide is liquefied under pressure. It is further assumed that the area is a complex industrial facility such that the area is determined to be “urban” with respect to modeling.

The EPA Offsite Consequence Analysis Guidance pro- vides simple tables for calculating the toxic endpoint. Us- ing these tables, the predicted toxic endpoint for this ex- ample for the worst case scenario would be 16.0 miles. If we now switch and use the EPA tables assuming a neutral atmospheric stability class and 3.0 m/s wind speed and 2500 pound per minute release over 10 minutes, the pre- dicted toxic endpoint is approximately 6.8 miles.

Next, this same scenario was modeled using the PHAST model. The parameters in the PHAST model were devel- oped so that they would match the Table look-up ap- proach, as much as possible. Assuming a worst case sce- nario with F stability and 1.5 m/s, the PHAST model pre- dicted a toxic endpoint of 7.3 miles. This is less than half of what the EPA tables predicted. Next, the PHAST model was used to simulate the same release using D stability class and 3.0 m/s wind speed. The predicted distance to the toxic endpoint was 4.9 miles for the scenario.

Finally, the process involving the sulfur dioxide vessel was examined and a realistic alternative release scenario was developed (see Table 2). In this scenario, a 1 inch hole was assumed to open that allowed the contents of the ves- sel to escape. The PHAST model was used for this scenario and the predicted toxic endpoint was 4.7 miles.

CONCLUSIONS

The EPA Table look-up approach can yield extremely conservative results for some scenarios. Overestimating a

TABLE 2. Comparison of Results for Example Scenario

Predicted Toxic Endpoint Distance (miles)

F Stability D Stability Method Scenario 1.5 m/s 3.0 m/s

Worst case release 16 n/a

PHAST model Worst case release 7.3 4.9 PHAST model Alternative release n/a 4.7

EPA Table look-up value EPA Table look-up value Alternative release n/a 6.8

Process Safety Progress (Vol. 17, No. 4) Winter 1998 241

toxic endpoint distance by over a factor of two will result in the overestimation of the area of concern by a factor of four (the square of the diameter of the circle). The value of using a credible scenario with realistic meteorological data can .be shown through the more consistent smaller areas predicted for planning purposes.

Realistic scenarios/failure modes and realistic model pa- rameters are important so that the risk to the public is not overstated. Also, it is important that the prevention pro- grams and emergency response programs required by the Risk Management Program are developed to address events that could happen. Proprietary models such as PHAST can be invaluable in modeling more meaningful consequences.

LITERATURE CITED

1. PHAST Professional Process Hazard Analysis Software Tools, DNV Techica, Inc., 16340 Park Ten Place, Suite 100, Houston, TX 77084-5143.

2. Turner, D. Bruce, Workbook of Atmospheric Disper- sion Estimates, U.S. Department of Health, Education, and Welfare, Cincinnati (1970).

3. Environmental Protection Agency, Offside Come quence Analysis Guideline, RMP (May 24, 1996).

4. Risk'Management Program Rule, Clean Air Act Amend- ments, Part 68, Accidental Release Prevention Provi- sions (1996).

5. National Renewable Energy Laboratory, User's Manual for ~MYZS, William Marion and Ken Urban, 1617 Cole Blvd., Golden, Colorado 80401-3933 (June 1995).

mis paper (Id, was presented at the AIChE 32nd Annual Loss Pre vention Symposium in New Orleans, LA, March 9-11, 1998.

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