### 1 

## Appendix 4 :

Analysis of data on short-term emission rates relative to long-term emission rates

### 2 

## Analysis of data on short-term emission rates relative to long-term emission rates

Ted Palma Roy Smith EPA/OAQPS/SBAG

1. Introduction

1.1. The problem

The process of listing hazardous air pollutants (HAPs) provided by the Clean Air Act (CAA, section 112(b)(2)) explicitly includ es acute toxicity as a listing criterion. For this reason, in addition to chronic exposures, EPA considers ac ute exposures in risk-based decision-making for the HAP regulatory program. Estimating acute exposures via dispersion modeling requires input data on hourly meteorological c onditions (available for most ar eas of the US) and short-term emission rates of individual facilities (almost universally absent from the National Emissions Inventory (NEI), the Toxic Release Invent ory (TRI), and state emission databases).

Lacking short-term emission rates, we must estimate peak short-term rates based on annual average rates, which are available. For Ri sk and Technology Review (RTR) rulemakings, we have assumed that the 1-hour emission rate for each facility could exceed the annual average hourly emission rate by as much as tenfold, and fu rther assumed that this tenfold emission spike could coincide with worst-case meteorological conditions and the presen ce of a human receptor at the facility boundary, as a means of screen ing for potentially signifi cant acute exposures.

In a consultation on the “RTR Assessment Plan”, a panel of the EPA’s Science Advisory Board (SAB), several reviewers questioned the appropri ateness of the factor of ten; some even suggested that this tenfold a ssumption may underestimate actual maximum short-term emissions for some facilities, and thereby also unde restimate maximum acute risks. The SAB recommended an analysis of available short-term emissions data for HAP to test this assumption. This analysis responds to that SAB recommendation and attempts to test th e protectiveness of the tenfold assumption using a database of “event emissions” collected from facilities in the Houston-Galveston area, to compare events repres entative of HAP releases to long-term release rates. We welcome comments from the public on the methods used and the conclusions reached by this analysis.

2. Methods

2.1. Texas Commission on Environmental Qu ality event emissions database

The Texas Commission on Environmental Quality (TCEQ) collects emissions data using online reporting required of any facility releasing 100 pounds or more of a listed chemical (primarily ozone-forming VOCs) during a non-r outine event. The TCEQ data are intended to improve the state’s knowledge of how short-term releases affect tropospheric ozone levels in that area. The database we utilized in our analysis was a subset of the TCEQ data covering emission events that

### 3 occurred in an eight-county area in eastern Texas during a 756-day period between January 31, 2003 and February 25, 2005.

The complete emissions event data were obtained in April 2007 from Cynthia Folsom Murphy, a research scientists with the University of Texas at Austin (UTA) Center for Energy and Environmental Resources. The da ta were provided in four Excel spreadsheets generated from an original MS Access file. We used these Excel files to recons truct a MS Access database in order to facilitate selection of a representati ve subset of record s for this analysis.

Although some of the released s ubstances were HAPs, this was incidental to the database’s primary purpose of enhancing the TCEQ’s knowledge of photochemical activity. Thus, more than 80% of the released ma ss was ethene and propene, neither of which are HAPs. The database included release events caused by accidents, equipment fa ilures, maintenance, startup, and shutdown. It also contained facility names, information on amounts of individual compounds released. To provide a basis for co mparing the event releases with “typical” emissions, the UTA staff included total VOC emissions data for each facility for calendar year 2004, obtained from the EPA Toxic Release Inventory (TRI). The database did not contain any records for facilities that did not experien ce any reportable events during this period.

2.2. Data filtering

Because the event release data were intended for modeling short-term releases of ozoneproducing VOCs, the database includes releas es from accidents (which are regulated under section 112(r) of the CAA and are therefore not considered in residual risk assessments) and releases of light hydrocarbon compounds that ar e not HAPs and are much more volatile than most HAPs. This intent of this analysis, on the other hand, was to evaluate short-term releases of HAPs due to normal process variability or sche duled startups, shutdowns, and maintenance, relative to long-term release rates. Because the full emi ssion events database was not representative of likely HAP em issions normally considered under the residual risk program, we filtered the release data as follows in an attempt to improve its representativeness:

1. Hydrocarbons of C5 or less were droppe d, except that all HAPs (including non-VOCs) were retained regardless of molecular structure;

2. Accidental releases were dropped, but all others (including st artup, shutdown, and maintenance) were retained;

3. Only facilities whose long-term VOC releases exceeded 0.068 tons per day (25 tons per year) were retained, to approximate the populat ion of facilities likely to be subject to residual risk standards (i .e., major facilities);

4. A few release records had to be dropped because their facility number s did not link to any facility in the database;

5. A few facilities had to be dropped because the database did not include their 2004 TRI VOC release information.

2.3. Analysis

### 4 Annual VOC emissions and emission event release data were both converted to lb/hr. In order to conform to our atmospheric dispersion models, which estimate ambient concentrations for periods of 1 hour or more, amounts released duri ng events shorter than 1 hour were assigned to the whole hour. For example, a release of 100 lb in ten minutes was converted to 100 lb/hr. Events longer than 1 hour were converted norm ally, e.g., a release of 100 lb in 120 minutes was converted to 50 lb/hr. The ev ent release rates for individual compounds were summed, yielding a total release rate for each event. This to tal release rate for each event was divided by the annual VOC release rate for the facility to derive the ratio of peak-to-mean emission rate for the
event.

3. Results and Discussion

3.1. Database filtering

The original database contained 505 individual contaminants, including multiple redundancies. These redundancies did not affect this analysis, so we did not re solve them. After filtering out light, non-HAP, VOCs, 317 contaminants remained (Table 1).

The database contained release records for 150 unique facilities. Of these, 48 facilities (Table 2) were major VOC emitters that reported releases of at least one of the contaminants in Table 1.

The database contained 3641 individual release events reported by the original 150 facilities. Of these, 319 events involved a Table 1 contaminant released by a Table 2 facility during startup, shutdown, or maintenance. For evaluating short- term releases for residual risk assessments, these 319 events comprise the most representative subset of the full database.

3.2. Descriptive statistics

For this subset of emission events, ratios of even t release rate to long-te rm release rate varied from 0.00000004 to 74. Distribution statistics appear in Tables 3 and 4. The 99 th 

### percentile ratio was 9 (i.e., an event release rate nine times the long-term average). Only 3 ratios exceeded our default assumption of 10, and of these only one exceeded 11. The full cumulative probability density of the ratios is shown in Figure 1.

Figure 2 shows the relationship between ratio and event duration. As expected, the ratio declined as duration increased. Only 18 events lasted less than 2 hour s, but these events produced the three highest ratios. Figure 3 is a similar ratio vs. duration plot, but with duration as a percentage of total time. Only 35 events exceeded 1% of the to tal period covered by the database. Figure 4 shows the relationship betwee n ratio and total amount released, and suggests that the highest ratios were pr oduced by facilities whose routine VOC emissions were relatively small. Thus, the events themselves also tended to be relatively small in absolute terms.

3.3. Discussion

These results suggest that the te nfold ratio assumption for short-te rm releases is protective, and that the facilities for which it may underestimate event releases may tend to be smaller emitters.

However, this analysis is limited in the followi ng ways by the nature of the database and the filtering that we applied:

### 5 1. The only long-term release data available fr om the database were total VOC emissions for 2004. Ideally, we would have preferred to have routine release rates for each individual contaminant. However, retrievi ng these data from other sources and linking them to this database was not feasible.

2. Removing VOCs that are not representative of HAPs, and comparing the releases against all VOCs, would tend to underestimate the true ra tios. This effect could be quantitatively large.

3. Retaining HAPs that are not VOCs (such as toxic metals), and including them in the total to be compared against all VOCs, would tend to overestimate the true ratios. The size of this effect is not known, but seems li kely to be less than for (2) above.

4. The database contains only facilities that had at least one re lease event during the reporting period. The number of facilities in the statistical popul ation that did not experience an event is not known. The lack of data for these facilities (whose ratios in this analysis would have been zero) would cause the descript ive statistics to be skewed toward an overestimate. The size of this effect is unknown.

Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD 2-Methyloctane No 3221-61-2 90008 2-Methylpentane No 107-83-5 43229 2-methylhexane No 591-76-4 43263 2-Methylpentane No 107-83-5 43229 2,2,3-Trimethylpentane No 564-02-3 2,2,4-Trimethylpentane Yes 540-84-1 43250 dimethyl butane No 75-83-2 43291 2,3-Dimethylbutane No 79-29-8 43276 2,3,4-Trimethylpentane No 565-75-3 43252 2,3-Dimethylbutane No 79-29-8 43276 2,4-Dimethylpentane No 108-08-7 43247 2-methylheptane No 592-27-8 43296 2-methylhexane No 591-76-4 43263 2-Methylpentane No 107-83-5 43229 3-Methylhexane No 589-34-4 43295 3-Methylpentane No 96-14-0 43230 3-Methylhexane No 589-34-4 43295 3-Methylpentane No 96-14-0 43230 3-Methylheptane No 589-81-1 43253 3-Methylhexane No 589-34-4 43295 3-Methylpentane No 96-14-0 43230

### 6 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD Acetaldehyde Yes 75-07-0 43503
Acetic Acid No 64-19-7 43404
Acetonitrile Yes 75-05-8 70016 Acetophenone Yes 98-86-2
Acrolein Yes 107-02-8 43505 Acrylic acid Yes 79-10-7 43407 Acrylonitrile Yes 107-13-1 43704 alkylphenol No none Benzene Yes 71-43-2 45201 Benzo[a]anthracene Yes 56-55-3 46716 Benzo[a]pyrene Yes 50-32-8 46719 Benzo[b]fluoranthene Yes 205-99-2 46717 Biphenyl Yes 92-52-4 45226
Butanol No 35296-72-1 Butyl Acrylate No 141-32-2 43440 t-Butyl Alcohol No 75-65-0 43309 butylcyclohexane No 1678-93-9 90101 Butyraldehyde No 123-72-8 43510
C9 Aromatics No none Naphthalene Yes 91-20-3 46701
Nonane No 111-84-2 43235
C9+ No none Carbon tetrachloride Yes 56-23-5 43804 Carbonyl Sulfide Yes 463-58-1 43933
Chloral No 75-87-6
Trichloromethane Yes 67-66-3 43803
Chlorothalonil No 1897-45-6
Petroleum No 8002-05-9
Petroleum No 8002-05-9
Cumene Yes 98-82-8 45210 Cyclohexane No 110-82-7 43248 Cyclohexanol No 108-93-0 43317 Cyclohexanone No 108-94-1 43561 Cyclohexanone No 108-94-1 43561
Decane No 124-18-5 43238
Decane No 124-18-5 43238 1,2-Dichloroethane No 107-06-2 43815 Diethylbenzene (mixture) No 25340-17-4 45106 Methyl Ether No 115-10-6 43350 Dimethylcyclohexane No 27195-67-1 98059 Dimethylcyclopentane No 28729-52-4 90064

### 7 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD Dimethylcyclopentane No 28729-52-4 90064 Dimethyl formamide Yes 68-12-2 43450 Dimethylhexane No 28777-67-5 90067 Dimethyl pentane No 38815-29-1 90063 Epichlorohydrin Yes 106-89-8 43863 Ethyl Alcohol No 64-17-5 43302 Ethyl Acrylate Yes 140-88-5 43438 Ethyl Alcohol No 64-17-5 43302 Ethyl Benzene Yes 100-41-4 45203 Ethyl Chloride Yes 75-00-3 43812 Ethylcyclohexane No 1678-91-7 43288 ethylacetylene No 107-00-6 43281 Ethyl Benzene Yes 100-41-4 45203 Ethylene Oxide Yes 75-21-8 43601 ethylmethylbenzene No 25550-14-5 45104 formaldehyde Yes 50-00-0 43502
Furfural No 98-01-1 45503 straight-run mi ddle distillate No 64741-44-2
Gasoline No 86290-81-5
Gasoline No 86290-81-5 Heavy Olefins No none n-Heptane No 142-82-5 43232 n-Heptane No 142-82-5 43232 Heptylene No 25339-56-4
hexane Yes 110-54-3 43231
hexane Yes 110-54-3 43231 2-Methylpentane No 107-83-5 43229
hexane Yes 110-54-3 43231
Hexene No 25264-93-1 43289 Indeno[1,2,3-cd]pyrene Yes 193-39-5 46720 Isobutyraldehyde No 78-84-2 43511 2-Methyl-1-propanol No 78-83-1 43306 2-Methyl-1-propanol No 78-83-1 43306 Isobutyraldehyde No 78-84-2 43511 Isoheptanes (mixture) No 31394-54-4 43106 2-Methylpentane No 107-83-5 43229 2,2,4-Trimethylpentane No 540-84-1 43250 2,2,4-Trimethylpentane No 540-84-1 43250 Isopar E No Isoprene No 78-79-5 43243 2-Propanol No 67-63-0 43304

### 8 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD 2-Propanol No 67-63-0 43304
Cumene Yes 98-82-8 45210 Isopropylcyclohexane No 696-29-7 90128 Diisopropyl ether No 108-20-3 85005
Kerosene No 64742-81-0 Methyl ethyl ketone No 78-93-3 43552 Methyl isobutenyl ketone Yes 141-79-7
Methanol Yes 67-56-1 43301 Methyl Acetylene No 74-99-7 43209
Cresol Yes 1319-77-3 45605 Methyl Chloride Yes 74-87-3 43801 methyl cyclohexane No 108-87-2 43261 Methyl ethyl ketone No 78-93-3 43552
Iodomethane No 74-88-4 86025 Methyl Mercaptan No 74-93-1 43901 methyl cyclohexane No 108-87-2 43261 Methylcyclopentane No 96-37-7 43262 2-Methyldecane No 6975-98-0 98155 Methylheptane No 50985-84-7 90045 2-methylheptane No 592-27-8 43296 2-Methyl nonane No 871-83-0 90047 Tert-butyl methyl ether No 1634-04-4 43376 meta-xylene No 108-38-3 45205
Nonane No 111-84-2 43235 Naphtha No 8030-30-6 45101 Naphthalene Yes 91-20-3 46701 Naphtha No 8030-30-6 45101 Naphthalene No 91-20-3 46701 Butyl acetate No 123-86-4 43435 Butyraldehyde No 123-72-8 43510
Nonane No 111-84-2 43235
Nonane No 111-84-2 43235
Octadecene No 27070-58-2
n-Octane No 111-65-9 43233 Octene (mixed isomers) No 25377-83-7 ortho-xylene No 95-47-6 45204
Parathion Yes 56-38-2 4-Aminohippuric Acid No 61-78-9
Phenol Yes 108-95-2 45300
Silicone No 63148-62-9 Naphtha No 8030-30-6 45101

### 9 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD Naphtha No 8030-30-6 45101 Polyethylene No 9002-88-4 Poly(Isobutylene) No 9003-27-4 Chloromethyl pivalate No 18997-19-8 Process fuel gas No none Propionic Acid No 79-09-4 43405 Propylene oxide No 75-56-9 43602 para-xylene No 106-42-3 45206 Styrene Yes 100-42-5 45220
Sulfolane No 126-33-0 t-Butyl Alcohol No 75-65-0 43309 t-Butyl Alcohol No 75-65-0 43309 tert-butyl hydroperoxide No 75-91-2
Toluene Yes 108-88-3 45202 Aqualyte(TM), LSC cocktail No 25551-13-7 45107 1,3,4-Trimethylbenzene No 95-63-6 45208 trimethylcyclopentane No 30498-64-7 98058 trimethylpentane No 29222-48-8 90092
Undecane No 1120-21-4 43241 Vinyl acetate Yes 108-05-4 43453 Vinyl acetate Yes 108-05-4 43453 Vinyl chloride Yes 75-01-4 43860 vinyl resin No none Vinylcyclohexane No 695-12-5 xylenes Yes 1330-20-7 45102 xylenes Yes 1330-20-7 45102 meta-xylene Yes 108-38-3 45205 ortho-xylene Yes 95-47-6 45204 para-xylene Yes 106-42-3 45206 Mineral spirits No 64475-85-0 43118 Propylene glycol No 57-55-6 43369 Vinyl chloride Yes 75-01-4 43860
1-Decene No 872-05-9 90014 2-Ethyl-1-hexanol No 104-76-7 43318 2-Pyrrolidone No 616-45-5
Aromatic No none Decene No 25339-53-1 90014 2-N,N-Dibutylaminoethanol No 102-81-8 86007 Diisopropanolamine No 110-97-4 86004 N,N-Dimethylethanolamine No 108-01-0 84004
trifluoroethane No 27987-06-0

### 10 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD 2,2'-Oxybisethanol No 111-46-6 43367 Hydrocarbons No none Methyl Formate No 107-31-3 43430 Isopropylamine No 75-31-0 86014
n-Butanol No 71-36-3 43305 Polypropylene glycol ether No N-Vinyl-2-Pyrrolidinone No 88-12-0 1,1-Di(t-Amylperoxy) Cyclohexane No 15667-10-4 1,2,3-Trimethyl-4-ethylbenzene No none 2-Methyldecane No 6975-98-0 98155 2-methylheptane No 592-27-8 43296 2-Methyl nonane No 871-83-0 90047 2,5-Dimethylhexane-2,5- dihydroperoxide No 3025-88-5 Butyl ether No 142-96-1 43372 1,2-Dichloroethane Yes 107-06-2 43815 Hydrindene No 496-11-7 98044 Methylheptane No 50985-84-7 90045 methyl methacrylate No 80-62-6 43441 Naphtha No 8030-30-6 45101
hexane Yes 110-54-3 43231 tert-amyl hydroperoxide No 3425-61-4 1,3,4-Trimethylbenzene No 95-63-6 45208
n-Butanol No 71-36-3 43305 2-Butoxy ethanol Yes 111-76-2 43308
hexane Yes 110-54-3 43231 cycloheptane No 291-64-5 43115 n-Heptane No 142-82-5 43232
n-Octane No 111-65-9 43233 Hexyl Carbitol No 112-59-4
Nonene No 27215-95-8 Silane, ethenyltrimethoxy No 2768-02-7 tetrahydrofuran No 109-99-9 70014 Vinyl chloride Yes 75-01-4 43860 Methyl Formate No 107-31-3 43430 Phenyl ether No 101-84-8 phosgene Yes 75-44-5 1,2-Dichloroethane No 107-06-2 43815 2-Butoxy ethanol Yes 111-76-2 43308
Gasoline No 86290-81-5
1-Tridecanol No 112-70-9

### 11 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD 1,2,4-Trichlorobenzene Yes 120-82-1 45208 2-(2-Butoxyethoxy)ethanol Yes 112-34-5 43312 2,3,4-trihydroxybenzophenone Ester No 1143-72-2 Methyl n-amyl ketone No 110-43-0 43562 4,4-Cyclohexylidenebis[phenol] No 843-55-0
Anisole No 100-66-3 2-Butoxy ethanol Yes 111-76-2 43308 Cresol-Formaldehyde novolac Resin No proprietary
Decane No 124-18-5 43238 gamma-Butyrolactone No 96-48-0 Dimethyl pentane No 38815-29-1 90063 Dodecyl Benzenesulfonic Acid No 27176-87-0
Ethanol Amine No 141-43-5 43777 ethyl lactate No 687-47-8 Hexamethyldisilazane No 999-97-3 Methyl ethyl ketone No 78-93-3 43552
Cresol Yes 1319-77-3 45605 Naphthalene Sulfonic Acid Resin No Naphthalene Sulfonic Acid Resin No
n-Butanol No 71-36-3 43305
Decane No 124-18-5 43238 1-Methyl-2-pyrrolidinone No 872-50-4 70008 Pentyl Ester Acetic Acid No Phenol Formaldehyde Resin, Novolac No Phenol Formaldehyde Resin, Novolac No Propylene Glycol Monomethyl Ether No 107-98-2 70011 Pyrocatechol No 120-80-9
Carbon Disulfide Yes 75-15-0 43934
Hexene No 592-41-6 43245
VOC No none Methacrylic acid No 79-41-4 84009 Methyl 3-hydroxybutyrate No 1487-49-6 t-Butyl Alcohol No 75-65-0 43309 methyl valeraldehyde No 123-15-9 Butyl Methacrylate No 97-88-1 85008 dipropyl ether No 111-43-3 n-Propanol No 71-23-8 43303 Propyl propionate No 106-36-5 86052

### 12 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD 1,2-Epoxybutane Yes 106-88-7 Methylamine No 74-89-5 1,1-Dimethylcyclohexane No 590-66-9 1,1-Dimethylcyclopentane No 1638-26-2 2-Methylpentane No 107-83-5 43229 dimethyl butane No 75-83-2 43291 2,3,3-Trimethylpentane No 560-21-4 2,3-Dimethylhexane No 584-94-1 2,3-Dimethylpentane No 565-59-3 2,4-Dimethylhexane No 589-43-5 2,5-Dimethyl-hexane No 592-13-2 2-Butoxy ethanol Yes 111-76-2 43308 2-mercaptoethanol No 60-24-2 Bisphenol A No 80-05-7 straight-run mi ddle distillate No 64741-44-2 4-Vinylcyclohexene No 100-40-3 straight-run mi ddle distillate No 64741-44-2 Allyl alcohol No 107-18-6 xylenes Yes 1330-20-7 45102 Naphthalene Yes 91-20-3 46701 3-Methylethylcyclohexane No
VOC No none Gasoline No 86290-81-5 Butyl ether No 142-96-1 dimethyl butane No 75-83-2
Dodecene No 25378-22-7 Styrene Yes 100-42-5 45220 tetrahydrofuran No 109-99-9 70014
hexane Yes 110-54-3 43231 2-Propanol No 67-63-0 43304 liquified petroleum gas No 68476-85-7 Methyl acetylene propadiene No methyl isobutyl ketone Yes 108-10-1 Methyl n-amyl ketone No 110-43-0 43562 Methylpentane No 43133-95-5 Tert-butyl methyl ether Yes 1634-04-4 43376
Toluene Yes 108-88-3 45202
Mineral oil No 8012-95-1
Gasoline No 86290-81-5 2,2-Dimethylpropane No 463-82-1 43222 n-propylbenzene No 103-65-1

### 13 Table 1. Event emissions in the Houston-Galveston area. Representative contaminants included in the analysis, selected because they are either HAPs or VOCs with more than 5 carbon atoms. (These data were retrieved directly from t he original database, which included multiple redundancies that did not affect the analysis and were left intact.)
Contaminant HAP CAS SAROAD propylcyclohexane No 1678-92-8
n-Octane No 111-65-9 43233 ortho-xylene No 95-47-6 45204
Gasoline No 86290-81-5 propylenimine No 75-55-8
Gasoline No 86290-81-5
Technical White Oil No Total Alkylate - non-speciated No Trichloroethylene Yes 79-01-6 Di(2-ethylhexyl) peroxydicarbonate No 16111-62-9 trimethylcyclopentane No 30498-64-7 98058
Ultraformate No 4-Vinylcyclohexene No 100-40-3

### 14 Table 2. Event emissions in the Houston-Galveston area. Major emitters reporting at least one release event of a representative substance.

Company Name 2004 VOC Emission Rate (lb/h) ATOFINA PETROCHEMICALS LA PORTE PLANT 47.88 BALL METAL BEVERAGE CONTAINER CONROE FACILITY 24.18

BASF FREEPORT SITE 46.47 BELVIEU ENVIRONMENTAL FUELS 112.3 BOC GROUP CLEAR LAKE BOC GASES PLANT 9.52 BP AMOCO CHEMICAL CHOCOLATE BAYOU PLANT 130.4 BP AMOCO CHEMICAL PASADENA PLANT 36.92 BP AMOCO POLYMERS 57.18 BP PRODUCTS NORTH AMERICA TEXAS CITY 737.4 BP TEXAS CITY CHEMICAL PLANT B 112.2 CELANESE BAY CITY PLANT 17.12 CELANESE CLEAR LAKE PLANT 53.11 CELANESE PASADENA PLANT 5.934 CHEVRON PHILLIPS CEDAR BAYOU PLANT 105.3 CHEVRON PHILLIPS CHEMICAL SWEENY COMPLEX 106.7 CHEVRON PHILLIPS HOUSTON CHEMICAL COMPLEX 215.7 CROWN BEVERAGE PACKAGING 18.05 CROWN CENTRAL PETROLEUM PASADENA PLANT 114.3 CROWN CORK & SEAL 18.10 DEER PARK LIQUID STORAGE TERMINAL 124.8 DOW CHEMICAL LA PORTE SITE 5.902 DOW TEXAS OPERATIONS FREEPORT 203.2 E I DUPONT DE NEMOURS AND COMPANY - LA PORTE PLANT 51.30

EQUISTAR CHEMICALS CHANNELVIEW COMPLEX 275.4 EQUISTAR CHEMICALS CHOCOLATE BAYOU COMPLEX 84.87

EQUISTAR CHEMICALS LA PORTE COMPLEX 90.97 EXXON MOBIL CHEMICAL BAYTOWN OLEFINS PLANT 84.73 EXXONMOBIL CHEMICAL BAYTOWN CHEMICAL PLANT 313.7

EXXONMOBIL CHEMICAL MONT BELVIEU PLASTICS PLANT 40.64

GOODYEAR HOUSTON CHEMICAL PLANT 85.68 ISP TECHNOLOGIES TEXAS CITY PLANT 22.12 KANEKA TEXAS CORPORATION 20.55 KINDER MORGAN LIQUID TERMINALS PASADENA 913.9 KINDER MORGAN LIQUIDS TERMINALS 132.7 LBC HOUSTON BAYPORT TERMINAL 12.83 LYONDELL CHEMICAL BAYPORT PLANT 30.04 LYONDELL CHEMICAL CHANNELVIEW 74.15 MARATHON ASHLAND PETROLEUM TEXAS CITY REFINERY 111.8

MOBIL CHEMICAL HOUSTON OLEFINS PLANT 26.29 MORGANS POINT PLANT 31.03 PASADENA PLANT 13.40

### 15 Table 2. Event emissions in the Houston-Galveston area. Major emitters reporting at least one release event of a representative substance.

Company Name 2004 VOC Emission Rate (lb/h) SHELL OIL DEER PARK 405.2 SOLUTIA CHOCOLATE BAYOU PLANT 53.09 STOLTHAVEN HOUSTON TERMINAL 7.347 SWEENY COMPLEX 157.1 UNION CARBIDE TEXAS CITY OPERATIONS 174.4 VALERO REFINING TEXAS CITY 260.1 WHARTON GAS PLANT 7.552

Table 3. Frequency distribution for ratio of event emission rate to long-term emission rate

Bin Frequency Cumulative Frequency 1.00E-08 0 0 3.16E-08 0 0 1.00E-07 2 2 3.16E-07 1 3 1.00E-06 0 3 3.16E-06 2 5 1.00E-05 1 6 3.16E-05 2 8 1.00E-04 5 13 3.16E-04 9 22 1.00E-03 15 37 3.16E-03 28 65 1.00E-02 33 98 3.16E-02 41 139 1.00E-01 59 198 3.16E-01 38 236 1.00E+00 33 269 3.16E+00 31 300 1.00E+01 16 316 3.16E+01 2 318 1.00E+02 1 319 3.16E+02 0 319

### 16 Table 4. Statistics for ratio of event emission rate to long-term emission rate Statistic for Ratio Value Median 0.043923 75th %ile 0.342655 90th %ile 2.204754 95th %ile 3.344422 96th %ile 3.400832 97th %ile 3.8126 98th %ile 4.790098 99th %ile 8.973897 Max 74.37138 Average 0.815352



### Figure 1. Cumulative probability density for ratio of event to routine emission rates.

Cumulative probability of event ratios

0 50 100 150 200 250 300 350

1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 Ratio of event emission rate to long-term emission raten

### 17 Figure 2. Relationship between ratio of ev ent to duration emissi on rate and emission duration.

Event ratio vs. duration

1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

1 10 100 1,000 10,000 100,000 Event duration (min)Ratio -- event emission rate to long-term emission rate



### Figure 3. Relationship between ratio of event to duration emission rate and emission duration, as percentage of total time.

Event ratio vs. duration

1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

0% 1% 2% 3% 4% 5% 6% 7% 8% Event duration (as % of total time)Ratio -- event emission rate to long-term emission rate

### 18 Figure 4. Relationship between ratio of event to duration emission rate and total amount emitted during the event.

Event ratio vs. 2004 VOC releases -- by event

1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

1 10 100 1,000 Long-term VOC releases (lb/hr)Ratio -- event emission rate to long-term emission rate

# Technical Memorandum

TO: EPA Docket No. EPA

- HQ

- OAR -2010-0682

FROM: Brenda Shine , Environmental Engineer Refining and Chemicals Group, SPPD (E143-01)

DATE: March 15 , 2012

SUBJECT: Derivation of Hourly Emission Rates for Petroleum Refinery Emission Sources Used in the Acute Risk Analysis

I. Purpose:

This memorandum documents the assumptions used to derive the hourly emission rates used to estimate acute risks from emissions of petroleum refinery emission sources. In past Risk and Technology (RTR) rulemakings, when we have lacked hourly emissions data or other specific information about the source category processes, we assumed that the 1

- hour emission rate for any emission poin t could be 10 times higher than its average hourly emissions, calculated by dividing annual emissions by 8760 hours per year. The basis for this assumption was derived from an analysis of short term release information collected from facilities in the Hou ston

Galveston area and a comparison against routine emission rates for an entire facility. The conclusions of this analysis were that the hourly emissions from any single release event to the average annual VOC release rate for an entire facility was seldom greater than a factor of 10. For the petroleum refinery source category, we have a dditional knowledge of the emission point release characteristics that enable us to refine the default factor of 10 to something more realistic for this source category.

II. Acute Factors for the Petroleum Refinery Source Category:

Instead of using the default factor of 10 described above, we estimated variability of hourly emissions based on the operating characteristics of refinery emission sources in the following

manner :

a. For many sources that are associated with continuous operations and are essentially steady state, such as Fluid Catalytic Cracking Units (FCCU), and sulfur recovery plants (SRU), we would not expect significant variability in hourly emissions. Typical sou rce test variablility is typically ±30 to 50%. We have applied an hourly multiplier of 2 to estimate maximum hourly rates as an upper range of the expected variability. This assumption was used for the following types of sources: FCCU, SRU, Chemical
Proc esses, miscellaneous process vents, refinery processes (not specified) and
incinerators.

b. For delayed cokers, we considered the average venting cycle time in calculating our hourly emission rate. The process cycle for delayed cokers is 1 day (24 hours), w ith the

### 2 depressurization vent having an average venting cycle time of, on average, 2 to 3 hours per cycle. Since the depressurization vent opens for 730 to 1,095 hours per year, a factor of 8 to 12 times the annual average emission rate could be used to a ccount for this emission process. The emissions are expected to be somewhat variable, with higher emissions at the start of the venting cycle. We therefore applied an hourly multiplier of 20 to estimate maximum hourly rates for delayed coker emissions.

c. T here are three types of catalytic reformers: Continuous, cyclic, and semi

- regenerative. Continuous reformers (SCC 30601602) are expected to have stable operations (much like the FCCU and SRU), so a factor of 2 is appropriate for estimating the maximum ho urly emissions rate. Cyclic reformers (SCC 30601603) typically vent for 2,000 to 4,000 hours per year, suggesting a factor of 2 to 4 for these units. However, their emissions over the venting period are expected to be somewhat variable, so a factor of 10 is applied as a
conservative estimate. Semi

- regenerative reformers (SCC 30601604) are expected to vent approximately 10

- 15 days per year, suggesting a factor of 30 or 40. The venting is not expected to be uniform over this period, so a factor of 60 is a pplied for these units.
d. For evaporative loss sources such as wastewater, we expect moderate variability in maximum hourly emissions from annual average emissions. Emissions from wastewater are dependent on organic loading to the unit and on the mass transfer (volatilization) rate from the wastewater surface (which is dependent on the wastewater temperature and air wind speed). The loading rates are expected to vary by a factor of 2 during normal operations and the mass transfer rates are expected to va ry by a factor of 2 due to seasonal/meterological variations. We therefore applied an hourly multiplier of 4 to estimate maximum hourly rates from wastewater sources.

e. For fugitives from equipment leaks, we note that the current methods of estimating
emis sions make use of correlation equations in conjunction with Method 21 readings that ultimately provide an hourly emission rate for the monitoring period in question. The actual emission rates estimated based on the direct Method 21 readings are commonly
d ivided by two to estimate the average emission rate between monitoring intervals (i.e., assuming the leak started mid

- way between monitoring intervals as described in the emissions protocol). We expect the emission estimates from the direct Method 21
readi ngs to provide a direct measure of the maximum hourly emissions (as leak repair will be applied to reduce hourly emissions immediately after a monitoring cycle). Therefore, we applied an hourly multiplier of 2 to estimate maximum hourly rates from
the annu al average emission rates.
f. For storage vessels, higher hourly rates from loading operations can occur; however, the majority of tanks are floating roof tanks; emissions from these tanks are associated with
wind

- driven losses from fitting controls and clingage from exposure of external floating roof tank shells. These emissions would not be expected to vary as significantly as fixed roof tanks, but the emissions from floating roof tanks are expected to be dependent on temperature (seasonal variability) and, in the case of external floating roofs, wind speed.

### 3 There may also be variability in the crude oil processed or the intermediates and products stored in a given tank. As with wastewater sources, each of these factors is expected to
cause a factor of 2 variability. We therefore applied an hourly multiplier of 4 to estimate maximum hourly rates from storage tanks.

g. For other transfer and loading operations, maximum hourly rates can be approximated from pumping rates; a factor of 2 for these sources would not adequately account for higher maximum hourly emissions in most cases. Considering the hours of actual product loading during the year (commonly 1,000 to 2,000 hours per year), we applied a
factor of 10 to these emission sources.