P.

. C) o

BEFORE THE

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

APPENDICES TO PETITION OF

THE CHEMICAL MANUFACTURERS ASSOCIATION

KETONES PANEL TO DELIST METHYL ETHYL KETONE

UNDER SECTION 313 OF THE EMERGENCY PLANNING AND

COMMUNITY RIGHT-TO-KNOW ACT OF 1986

VOLUMEIOFV

SUBMITTED BY

CHEMICAL MANUFACTURERS ASSOCIATION

1300 Wilson Blvd.

Arlington, VA 22209

(703) 741-5000

cB1

November 27, 1996
p. 2

LIST OF APPENDICES

Volume 1

A. Table of References

B. Exxon Chemical Company I~EK Technical Product Brochure

C. Report of the ENSR Air Dispersion Modeling Study

D. MEK emissions by zip code

E. Table of Ambient Air Concentration Levels of MEK (taken from a study conducted by

the New Jersey Department of Environmental Protection in 1978)

F. Houston Regional Monitoring Report (excerpts)

G. North Baton Rouge Volatile Organic Screening Study

H. IRIS Database entry for MEK

1 . 1988 EPA Memorandum from J.V. Nabholz to EPA Chemical Review and Evaluation

Branch

J. Table Summarizing Acute Toxicity of MEK to Aquatic Organism s

K. EPA Memorandum from Acting Assistant Administrator for Air and Radiation to EPA

Office of Toxic Substances

L. EPA TRI Information Collection Request Report (excerpts)

M. GAO Report on EPA Uses of TRI Dat a

N. EPA Public Release on 1994 TRI Data, Appendix D.

0. Comparison of MEK Ernissions in Ozone Nonattainment Areas to MEK Emissions in

a Areas

Volume 2

P. Legislative I-fistory of EPCRA Section 313

Volumes 3,4 and 5

Q. References
APPENDIX A

TABLE OF REFERENCES
p. 4

TABLE OF REFERENCES'

*Alderson M.R- and Rattan N. S. (1980). Mortality of workers on an isopropyl alcohol plant and two

MEK dewaxing plants. British J Indust. Med 37: 85-89.

*Altenldrch, H., Stoltenburg, G. and Wagner, H.M. (1978). Experimental Studies on Hydrocarbon

Neuropathies Induced by Methyl-Ethyl-Ketone (MEK). Journal ofNeurology 219: 159-70.

*Ambrose, D., Effender, J .H., Lees, E.B., Sprake, C.H.S. and Townsend, R. (1975). Thermodynamic

properties of organic oxygen compounds X3CKM . Vapour pressures of some aliphatic ketones . J

Chem. 7herm. 7 :453-72.

*BozzeUi, J. et al . (1980). New Jersey Institute of Technology Air Pollution Research Laboratory,

Analysis of Selected Toxic and Carcinogenic Substances in Ambient Air in New Jersey, prepared for

Office of Cancer and Toxic Substances Research, State of New Jersey, Department of Environmental

Protection.

*Bridie, A.L., Wolff, C.J.M. and Winter, M. (1979). BOD ano COD of Some Petrochemicals . Water

Research 13 : 627-30.

*Brooke, L.T. et al. (1984). Acute Toxicities of Organic Chemicals to Fathead Minnows (Pimephales

promelas), Center for Lake Superior Environmental Studies, University of Wisconsin - Superior, WI;

Vol. 1 : 99-100.

*Brooks, T.M., Meyer, A.L. and Hutson, D.H. (1988). The genetic toxicology of some hydrocarbon

and oxygenated solvents. Mutagenesis 3 : 227-32.

*Carpenter, C.P., Smyth, H.F., and Pozzani, U.C. (1949). The Assay of Acute Vapor Toxicity, and

the Orading and Interpretation of Results on 96 Chemical Compounds. Journal ofIndus. Hygiene and

Toxicol. 31 : 34346.

*Cavender, F.L. et al (1983). A 90-day Vapor Inhalation Study of Methyl Ethyl Ketone. Fundwn.

Appl. Toxicol. 3 : 264-70.

*Chou, W.L., Speece, R.E. and Siddigi, R.H. (1979). Acclimation and Degradation of Petrochemical

Wastewater Components by Methane Fermentation. Biotech Bioeng. Symp. 8: 391414.

*Corwin, J .F. (1969). Volatile Oxygen-Containing Organic Compounds in Sea Water : Determination . Bull. Marine Science 19(3): 504-09.

*Cox, R.A., Patrick, K.F. and Chant, S.A. (1981). Mechanism of Atmospheric Photooxidation of

Organic Compounds. Reactions of Alkoxy Radicals in Oxidation of n-Butane and Simple Ketones . EnWromnental Sci. Technol. 15(5): 587-92.

Two copies of all references denoted with an asterisk have been submitted with this petition .
p. 5

*Deacon, M.M. et al . (1981). Embryo- and Fetotoxicity of Inhaled Methyl Ethyl Ketone in Rats .

Toxicol andAppl. Phartnacol. 59: 620-22.

*Dick, R.B., Kreig, E.F., Jr., Setzer, J. and Taylor, B. (1992) Neurobehavioral Effects from Acute

Exposures to Methyl Isobutyl Ketone and Methyl Ethyl Ketone . Fundwn. Appl ToxicoL 19: 453-73 .

*Dick, R-B., Setzer J .V., Taylor B.J. and Shukla R. (1989). Neurobehavioral effects of short duration

exposures to acetone and methyl ethyl ketone . Brifish J Ind Med 46: 111-2 1 .

*Dietz, F.K. and Traiger, G.J. (1979). Potentiation of CCL4of Hepatotoxicity in Rats by a Metabolite

of 2-Butanone: 2,3-Butanediol . Toxicolog~ 14 : 209-15.

Dourson, M.L. and Stara, JR. (1983). Regulatory History and Experimental Support of Uncertainty

(Safety) Factors . Reg. Toxicol. Phamacol 3 : 224-38.

*Dumant J.P. and Adda J . (1978). Occurrence of Sesquiterpenes in Mountain Cheese Volatiles . J .

Agric. Food Chem . 26 : 364-67.

*ECETOC Technical Report #70: Chronic Neurotoxicity of Solvents (February 1996) . European

Centre for Ecotoxicology and Toxicology of Chemicals at pp. 147-5 1 .

*Elkins, H. (John Wiley & Sons 1959). The Chemistry of Industrial Toxicology at pp. 118-21 .

*Ewing, B.B. et al. (1977). Monitoring to Detect Previously Unrecognized Pollutants in Surface

Waters. EPA 560/6-77-15. USEPA, Office of Toxic Substances.

*Florin, I., Rutberg., L., Curvall, M. and Enzell, C .R. (1980). Screening of Tobacco Smoke

Constituents for Mutagenicity Using the Ames' Test . Toxicolosy 18: 219-32.

*Gordon, D.T. and Morgan ME. (1979). Principal Volatile Compounds in Feed Flavored Milk . J

Dairy Sci. 55: 905-12 .

*Grosjean, D. (1982). Formaldehyde and Other Carbonyls in Los Angeles Ambient Air. Environ. Sci.

Techn. 16: 254-62.

*Hamburger, S.J. (1980). CHDH Aquatic Static Acute Toxicity Test - First Nominees Complete .

Internal Exxon memorandum.

Heitrnuller, P.T., Hollister T.A. and Parrish, P .R. (198 1). Acute Toxicity of 54 Industrial Chemicals to

Sheephead Minnows (Cyprinodon varlegatus). Bull. Environ. Contam. Toxicol. 27: 596-604.

*Hewitt, L.A-, Ayotte, P. and Plaa, G.L. (1986). Modifications in Rat Hepatobiliary Function

following Treatment with Acetone, 2-Butanone, 2-Hexanone, Mirey, or Chlordecone and

Subsequently Exposed to Chloroform. Toxicol. andAppl. Phartnacol. 83 : 465-73 .

*Hewitt, W.R., Brown, E.M., and Plaa, G.L. (1983). Relationship Between the Carbon Skeleton

Length of Ketonic Solvents and Potentiation of Chloroform-Induced Hepatotoxicity in Rats . Toxicol.

Lett. 16: 297-304.

2
p. 6

*Howard, P.H. et al. (Lewis Publishers 1990). Handbook of Environmental Fate and Exposure Data

for Organic Chemicals. Vol. 11 : 33440.

*Isidorov V.A., Zenkevich I.G., Ioffe BV. (1985). Volatile Organic Compounds in the Atmosphere

of Forests. Atmos. Environ. 19: 1-8.

*Jungclaus, G.A., Lopez - Avila, V. and Hites, R.A. (1978). Organic Compounds in an Industrial

Wastewater: A Case Study of Their Environmental Impact . EnWron. Sci. Technol. 12(l): 88-96.

*Kimura, E., Ebert, D. and Dodge, P. (1971). Acute Toxicity and Limits of Solvent Residue for

Sixteen Organic Solvents . Toxicol, andAppl. Pharmacol 19: 699-704.

Knasko S.C., Gilbert, A.N., Sabini, J. (1990). Emotional state, physical well-being and performance in

the presence of feigned ambient odor . J Appl. Soc. Psychol. 20: 1345-57.

2 *Krasavage, W.J. O'Donohogue, J .L. and DiVincenzo, G.D. (John Wiley & Sons 3rd ed. 1982).

Ketones in: Patty's Industrial Hygiene and Toxicology at pp. 4728-33, 47874800.

*LaBeffe, C.W., and Brieger, H. (1955). The Vapor Toxicity of a Composite Solvent and its Principal

Components . Arch. Ind Health 12: 623-27 .

3

Lande, S., Durkin, P. Christopher, D., Howard, P., Saxena, J ., Syracuse Research Corp . (1976) .

Investigation of Selected Potential Environmental Contaminants ; Ketonic Solvents, prepared for Office

of Toxic Substances, Environmental Protection Agency .

*Lovegreen, N.V., Fisher, G.S ., Legendre, M.G. and Schuller, W.H. (1979). Volatile Constituents of

Dried Legumes . J Agric. Food Chem. 27: 851-53 .

*Lyman, W.J., Reehl, W.F. and Rosenblatt, D.H. (McGraw-Hill Book Co . 1982). Handbook of

Chemical Property Estimation Methods at pp. 15-1 to 15-34.

*Mariiett, L.J., Hurd, H. K., Hollstein, M. C., Levin, D. E., Esterbauer, H. and Ames, B. N. (1985).

Naturally occurring carbonyl compounds are mutagens in Salmonella tester strain TA104 . Mutation

Research 148: 25-34.

*Mast, T.J. et al . (1989). Inhalation Developmental Toxicology Studies : Teratology Study of Methyl

Ethyl Ketone in Mice. Prepared for the National Institute of Environmental Health Sciences, No . NIHY01-ES-70153.

4 *National Toxicology Program Fiscal Year 1987 Annual Plan. NTP-87-001 (May 1987). Salmonella

Data at p. 70; In Vitro Cytogenetics/Sister Chromatid Exchange Data at p. 87.

2 Only the chapter on Ketones has been submitted. 3 This is the same reference as EPA 560/02-76-003 (1976).

4 Only the cover page and pages 70 and 87 have been submitted.

3
p. 7

Nelson, B .K., Brightwell, W.S., Khan, A., Burg, JR. and Goad, P.T. (1988). Lack of Selective

Developmental Toxicity of Three Butanol Isomers Administered by Inhalation to Rats. Fundcan. Appl.

Toxicol. 12:469-79.

*Nelson, K.W., Ege, J .F., Ross, M., Woodman, L.E. and Silverman, L. (1943). Sensory Response to

Certain Industrial Solvent Vapors . J of Indus. Hygiene and Toxicol. 25 : 282-85 .

*Nestmann, E.R-, Lee, E., Matula, T.I., Douglas, G.R. and Mueller, J.C. (1980). Mutagenicity of

Constituents Identified in Pulp and Paper Mill Effluents Using the Salmonella/Mammalian-Microsome

Assay. Mutation Research 79: 203 -12.

*O'Donoghue, J .L., Haworth, S.R., Curren, R.D., Kirby, P.E., Lawlor, T., Moran, E.J ., Phillips, R.D.,

Putnam, D.L., Rogers-Back, AM., Slesinski, R.S. and Thilagar, A- (1988). Mutagenicity studies on

ketone solvents: methyl ethyl ketone, methyl isobutyl ketone, and Isophorone. Mutation Research

206:149-61 .

Opdyke, D.L.J. Monographs for Fragrance Raw Materials -- Methyl Ethyl Ketone (1977). Food

Cosmetic Toxicol. 15: 627-632.

*Patty, F.A., Schrenk, H .H., and Yant, W .P. (1935). Acute Response of Guinea Pigs to Vapors of

Some New Commercial Organic Compounds-VIII. Butanone.'U.S. Public Health Service Report .

*Perocco, P., Bolognesi, S. and Alberghini, W. (1983). Toxic Activity of Seventeen Industrial

Solvents and Halogenated Compounds in Human Lymphocytes Cultured In Vitro . Toxicol, Lett. 16:

69-75.

Pozzani U.C., Weil C.S. and Carpenter C.P. (1959). The toxicological basis of Threshold Limit

Values: 5. The Experimental Inhalation of Vapor Mixtures by Rats With Notes Upon the Relationship

Between Single Dose Inhalation and Single Dose Oral Data . Am. Ind Hyg. Assoc. J 20 : 364-69.

*Price, K. S., Waggy, G.T. and Conway, R .A. (1 974). Brine Shrimp bioassay and seawater BOD of

petrochemicals . J Water Pollut. Control Fed 46: 63-77.

*Ralston, W.H., Hilderbrandt, R-L ., Uddin, D.E., Andersen, M .E. and Gardier, R.W. (1985).

Potentiation of 2,5-hexanedione neurotoxicity by methyl ethyl ketone . Toxicol. andAppl. Pharmacol .

81 :319-27.

*Randall, T.L. and Knopp, P.V. (1980). Detoxification of specific substances by wet oxidation. Water

Res. 14: 2117-30.

*Saida, K., Mendell, J . and Weiss, H. (1976). Peripheral Nerve Changes Induced by Methyl n-Butyl

Ketone and Potentiation by Methyl Ethyl Ketone. J Neuropathol. andErperim. Neurology 35: 207-

25.

*Schwetz, BA-, Leong, B .K.J. and Gehring, P.J. (1974). Embryo- and Fetotoxicity of Inhaled Carbon

Tetrachloride, 1, 1 -Dichloroethane and Methyl Ethyl Ketone in Rats . Toxicol. andAppl. Pharmacol,

28 : 452-64.

4
p. 8

*Schwetz, B.A., Mast, T.J ., Weigel, R.J., Dill, JA. and MorTissey, R-E. (1991). Developmental

Toxicity of Inhaled Methyl Ethyl Ketone in Swiss Mice . Fundwn. Appl. Toxicol, 16: 742-48.

Shirasu, Y. (1976). Mutagenicity testing of pesticides . Kogia to Taisaku. J ofEnWron. Pollution

Control 12: 407-12.

Smyth H.F., Carpenter C.P., Weil C.S., Pozzani U.C. and Striegel J.A- (1962). Range-Finding

Toxicity Data: List VI. Am. Ind Hyg. Assoc. J 23 : 95-107.

*Snider, J.R- and Dawson, G.A- (1985). Tropospheric Light Alcohols, Carbonyls, and Acetonitrile

Concentrations in the Southwestem United States and Henry's Law Data . J Geophys. Res. D. Atmos.

90:3797-3805 .

*Specht, H., Miller, J .W., Valaer, P.J. and Sayers, R.R. (1940). Acute Response of Guinea Pigs to the

Inhalation of Ketone Vapors . U. S. Public Health Service, NIH Bulletin No. 176: 1-66.

*Spencer, P. S. and Schaumburg, H. (1976). Feline Nervous System Response to Chronic Intoxication

With Commercial Grades of Methyl n-Butyl Ketone, Methyl isobutyl Ketone, and Methyl Ethyl

Ketone. Toxicol. andAppl. Pharmacol. 3 7 : 3 0 1 -11 .

*Takeoka, G.R., Flath RA.and Guntert, M. (1988). Nectarine Volatiles : Vaccuum Steam Distillation

Versus Headspace Sampling J Agric. Food Chem. 36: 553-60.

*Takeuchi, Y., Ono, Y. Hisanaga, N., Iwata, M. Aoyarna, M., Kitoh, J. and Sugiura, Y. (1983). An

experimental study of the combined effects of n-Hexane and methyl ethyl ketone . British J Indust.

Medicine 40: 199-203.

Tanii, H., Tsuji, H. and Hashimoto, K. (1986). Structure - Toxicity Relationship of Monoketones .

Toxicol Lett. 30 : 13 -17.

*Traiger G.J. and Bruckner, J .V. (1976). The Participation of 2-Butanone in 2-Butanol-Induced

Potentiation of Carbon Tetrachloride Hepatotoxicity . J Pharmacol. Experim. Therapeutics 196: 494-

500.

*Traiger, G.J ., Bruckner, J .V., and Cooke, P.H. (1975). Effect of 2-Butanol and 2-Butanone on Rat

Hepatic Ultrastructure and Microsomal Drug Metabolizing Enzyme Activity . Toxicol, andAppl.

Pharmacol, 33 : 132.

*Tumbull, H. ; Demann, J.G. and Weston, R.F. (1954). Toxicity of Various Refinery Materials to

Fresh Water Fish . Ind & Eng. Chem. 46(2): 324-33 .

*Verschueren, K . (Van. Nostrand Reinhold Co . 2nd ed . 1983). Handbook of Environmental Data on

Organic Chemicals at pp. 850-5 1 .

Wen C.P., Tsai S .P., Weiss N. S., Gibson R.L., Wong 0. and McClellan W.A- (1985). Long-term

Mortality Study of Oil Refinery Workers. IV. Exposure to the Lubricating-Dewaxing Process . J

Nat/. Cancer Inst. 74: 11-18.

IN

5
P. 9

*Zimmerman, F.K., Mayer, V.W., Scheel, I . and Resnick, M .A. (1985) . Acetone, methyl ethyl

ketone, ethyl acetate, acetonitrile, and other polar aprotic solvents are strong inducers o f

aneuploidy in Saccharomyces Cerevisiae . Mutation Research 149: 3 39-5 1 .

6
P. 10

APPENDIX B

EXXON CHEMICAL COMPANY MEK TECHNICAL PRODUCT BROCHURE
N

CHEMICALS

METHYL ETHYL KETONE
Copyrighted page/s removed. Copyrighted material is not available in 

Regulations.gov since it may not be reproduced without consent of 

the copyright holder. 

Contact the EPA Docket Center’s Public Reading Room to view 

or receive a copy of this document. 

Requests for copies may be made as follows: 

In person/writing: 

Environmental Protection Agency, Docket Center 

1301 Constitution Ave NW, 2822T, Room 3334 

Washington, DC. 20004 

Telephone: 

202-566-1744 

Fax: 

202-566- 9744 

Email: 

docket-customerservice@epa.gov 
p. 13

METHYL ETHYL KETONE

(MEK)

0

11

CM3-C-CHaCM3

Methyl ethyl ketone (MEK) is a low-boiling . chemically stable compound similar

in properties to acetone . Sometimes referred toss butanoi MEKisaflammbble. colorless liQuid prossusing a typical ketonic odor . Not Quite as volatile as

acetone. 4 is neriienheless a fast evaporator, its evaporation rate being roughly

comparable to that of ethyl acetate . MEK is a good solvent for many natural and

synthetic resms . It is miscible with most organic solvents. MEK is only partially

miscible with water and forms a constant boiling rnixture at 73.69C (164.54F)

containing appipiximately 11 per cent by weight of water . The pure ketone boils

at 79 6*C (1 75-30F) .

low viscosity at high solids concentration . MEK is of

"To

speoftse~ 11111111110 %womeam high purity and has a toluene dilution ratio of 4.3;

Us 8W'C @gal WA % OMM" twon Chowrwof 1W 34 therefore it can tolerate a high percentage of low-cost

CAW . "aww"44101114 10 am Dim aromatic diluent without allowing the nitrocellulose

Dammen to precipitate. Its low specific gravity enables formuV40 2"W4 Pe" 78 STA1173-7r). M-_

orv pool 41 M177SPI. MW lators to produce larger volumes of base lacquers

0 ftnp iVC* ?-It) or thinners per pound of MEK than is possible with 79 VC

heavier solvents.

fto@~%Vftlftmw~ efloom 0 13 U

Dow CrWeeft"Oft. Dim

fte" ."NOWN Another use for MEK is in thinner blends for acrylic

Nray. I" G C . wt .% W6MM and acrylic-nitrocellulose lacquers. MEK is also a sol- smft 20 VC M h"

:W #AN vent for alkyds and other resins often used to modify

vow Comm 11" % 0 1 Wa . 13M nitrocellulose lacquers. Air-dried epoxy finishes with

physical properties similar to those of baked finishes

are obtained with the help of MEK

Applications as a Solvent This versatile solvent is also wad in surface coatings

based on eftl cellulose. cellulose acetate-butyrate,

MEK Js widely used as a cornpw*M of vinyl lacquer polyuretharm, and vinylidene chlorkle-acrylonitrile

solvent systems. ft powerful active solvency for vinyl copollymer. Other ussis for MEK are in fabric coatings,

acetate and vinyl chlofide-virryl acetate Copolymers and synthetic rubber coatings.

makes it possible lo formuhft high-solids lacquer s

containing large amoLrft of economical hydrocarbon In some arm, RLA9-66 type air pollution regulations.

diluents. Spray. dip. knife. bnjsK or roller techniques wtich restrict ttle use of corWn solvents . are still in force .

can be used to apply Own lacquers at room or 9W

vated temperatures. MEK is also used in vinyl type MEK is Mted n a non-restricted solvent by Rule 66-

protective strippable coatings foir equipment in type regulations. Therefore, it is used in ftreformulastorage- tion ofa wide variety of coatings, iinks. and adhesives to

rephlice Rule Wtype restricted solvents. MEK is particMEK is a strong active solvent for nitrocellulose and Warty useful in the solvency of weaker exempt

is extensively used in furniture and automotive lac- goWft ~often moist be employed to replace

quers. It has good blush resistance and helps .provide restricted solvents. such as aromatics.

4 jPWWW~ 0 140 &W "raw &"WMION Ty-M-11111116.
p. 14

MEK is a major solvent for adhesives . The excellent aliphatic hydrocarsolvent properties and fast evaporation of MEK ac- bon Solvents which

count for its wide use as a solvent in many com- are often used t o

pounded polyurethane, nitrile rubber and neoprene- replace the restric- %ower

based industrial cements . These include high- ted aromatics . MEK

strength, oil-resistant, resilient adhesives ; hesit-acti- is also finding applivated adhesives for lamination; low-temperature and Cation in fast dry

heat-activated curing cements used as general pur- traffic paints tormupose adhesives: and a number of specialty cements lated with chlorinsuch as those used for bonding vinyl to fabrics . and ated rubber.

paper coating cements . MEK also goes into viny l

solution formulations used as heat-sealable, grease- Clean" Rukk

resistant paper coatings and cellulose acetate lami- Many cleaning comnating adhesives . This versatile solvent is also used positions make use of Ar

in bonding cements for polystyrei4e, polyvinyl chlo- the powerful solvent

ride, and polyvinyl chloride-polyvinyl acetate copoly- action of MEK . It is

mers. Good shelf life is an added advantage of using widely used in paint-,

MEK in adhesive formulations. lacquer-, and vamish-removers . Industrial metal- and on- 111-6 Isis" as"1111,

The strong solvency and last evaporation rate of MEK gine-cleaning solmake it an important component of gravure printing vents also incorpoinks, particularly in Type C and Type V inks. It also rate MEK

finds some applications in silk screen printing .

selvem aft*~

D"aWn Agents

The selective solvency of MEK has promoted its use

In mixtures with benzene or toluene, MEK is used in

petroleum refineries for reducing the wax content of

as an extraction medium for fats, oils, waxes, and lubricating oils . The ketone precipitates the wax while

resins. Another use is in the concentration of fatty the aromatic solvent holds the oil in solution . This

acids in aqueous solutions. MEK is used in ft re- process can be adapted to a great variety of lubricovery of acetic acid from dilute solutions. Pharma- cating oils by varying the p4rcentage of MEK in the

coutical applications include use in the recovery and mixture .

concentration of penicillin. Spent absorption agents

used in the refining of oil can be reactivated by an Opel$

MEK-benzene mixture. MEK is also used in a process Methyll ethyl ketone is used as a solvent for various

for removing sulfur from oils. MEK does not hydrolyze dyes and for inks used in printing on cellulose-derivato form Corrosive products. This is an advantage over hve surfaces. Anthraquinone dyes for acetate fabric

*slars in solveft mcovery syftme . are prepared in a proem which uses MEK Oil and

Tram Mark" vs"

fat are removed from wool prior to dyeing by washing

in MEK

Millions of gallon of traffic pail am used by city.

county, and state governments every year . Much of this Nbeellamm

paint is a solvent-baeW, oU modified, a" resin type. Combined with chemicals such as mercuric oxide

Because of thesoh*R portion ofthe formiulation consti- or with chliorinated hydrocarbons . MEK is used in

Uift as much as 50%. w . concem about air pofiu- insecticides, fungicides, and germicides. MEK is also

lion has bow shown. MEK is an important component used in the manufacture of smokeless powder, It is a

in replacing air pollution regulation restricted solverits. solvent for various anti-oxidants. Photographic film,

such as toluene, which are used in these alkyd formula- artificial leather . and many types ot plastics are manutions. ft enhances the solvency of the weaker, exempt facturod with the help of this excellent solvent.
p. 15

Applications as a Chemical Intermediat e

Potentially, methyl ethyl ketone (MEK) can be as & UftGONS"00US Rose""$

widely utilized as acetone for chemical synthesis . Oxidation of MEK with oxygen produces diacetyl,

Reactivity centers around the carbonyl group and its a flavoring material . Chlorination yields mixtures of

adjacent hydrogen alois . Condensation. afnrro- several monochloro and dichloro derivatives in pernolysis, halogenation, and oxidation can be carried centages depending on reaction conditions . The reout under the proper conditions. Some typical re- action of MEK with hydrogen peroxide gives a mixture

actions are described below. of peroxides and hydro-peroxides which is used to

cure polyester resins at room temperature.

Aldol condensation of two moles of MEK yieldsa 6 10ON

hydroxy ketone which readily dehydrates to an un- CHICCHAC643 * 0441-WOUCCH10%

saturated ketone . 6014

This initial addition product is the unstable precursor

of seven stable peroxides and hydroperoxides . Of

these. 2.2'-dihydroperoxy-2,2'-dibutyl peroxide, is

CW4 C~b

CH3C"4 0 CHCCHSCP%

2. Cenftm"m wfth ONW CON"MrAft 4 CWS

Reiction with aldehydes gives higher ketones . as well present in largest amount (about 45 per cent) in the

as ketals and cyclic compounds, depending on re- peroxide mixture.

action conditions. 8-diketones are produced by the

condensation of MEK with aliphatic esters . MEK con- MEK peroxides are widely used as catalysts for the

denses with glycols and organic oxides to give deriva- polymerization of polyester resins at room temperatives of dioxolane. ture. The condensation product of MEK and m-phenyIons diamine is an efficient curing agent for epoxy

sec-Butylamine is formed by reacting MEK with resins. MEK and cobalt acetate function together as

aqueous ammonia and hydrogen . a specific WOW for the single stage oxidation of

p-xylene to terephthalic: acid. Aliphatic monoketones,

0 such as MEK also function as catalysts in the polyc".1c".0% merization of poly (ethylene terephthalate) where . it is

WHO claimed. they speed condensation times and cause

101 Wo P40 less yellowing of the polyrner than antimony trioxide . MEK is also used in the preparation of complex cataAn ss of MEK in this reaction will also produce tysts used in the syndkftctic polymerization of &-olethe secondary wnft &wc4atihnsira fin such as polypropylene.

Reacting MEK wNh acetylene gives methyl pentynol. a hypnotic compoun&

Ptwnol. glywAl, tirmaldehyde, acetaldehyde, fur0 c"S furaldehyde, and other chemicals can be made to

react with MEK to form resins useful for adhesives,

coatings. molded products, and eleclifical insulation .

MEK maM with acrylonitrile to produce a dinitrile,

which upon hydro"nation produces arnines .
p. 16

MINES

PitorcXMS OF THE

PURE COMPOUNDS*

(all valmlem am at 20"C' ezeept wbevv Dowd) AR*Wm MEN MISK Oxide bephorme

Autoignotion Tentperaluts . Vapor. IF 1000 900 864 - no

Amectrope with Water . D.P. . 'C - 73 .4 47.9 91.8 "s

vn . % Katons, in Vapor - ".7 76.0 65.2 16.1

Doiling Point T 133.0 176.3 241 .2 USA 419 .4

*C so.I 79.6 116.2 129.6 215.2

Cawicism of Cubic Expansion. per IC 0.00143 MOD119 0.00116 0.00109 0.0008s

crobw Pressure. offl. 47 43 32 - 35

Critical Temperature . IC 235 ago 2" - 441

Deneft . 91frA 0.7907 CAW ism 0.653 0.920

owisanc Constant 21.45 Iasi 13.11 15.4 -

cimamm miatios . Toiuww 4.5 4.3 3.6 3.7 6 .2

Alonstic Months 0 .7 0.9 1.1 0.9 1.0

Depoft Molnent. Det" units 2.72 2 .74 2.7 2 .7 4 .0

WC)

Electrical Conductivity. x I" mho 5.5 to - - -

Expiown Linvits . in air. val. %

upw L~ 2

12 .9 10.0 7.5 8.8 3.8

.6 1 .8 1 .4 1 .3 0.8

Plash Point. IF

Ime open cup 34 74 96 205

TooCWW CUP as so 83 200

Fiest no PowwrC -54 OF -09

.7 -a" _00.2 -53 -8. 1

.5 -123 .3 -112.4 -63 17 .4

GeNom par 100 pound* 15,16 14.90 14.07 14.04 13-02

"w of Combustion . BTU11b. 1&2@0 14j" 15400 - 15.630

"" Of Fusion . calig 2364 24.7 - - -

himmif of VapootmNom. BTU/Ib. a D.P. 219.70 190AS 15547 157, 139

Wolont Sao$? 72.104 100 .156 U.14 138.2

Poulage per gemon 6.00 6.71 ta 7 .12 7 .60

ftfnMkv Inclex no law 1 .3791 130516 1 .44" 1.4781

ftiatille f go" -ion Rate

(a4uto AcatsfiswIOD) 1140 572 In 90 3

Sako". WL %

-oflissam in NOW@ a" 1.7 3.1 1 .2

- 40 wow in ketem Infinite Ila 1.9 U 4.3

assmew" ftmwalw 1" 0.4 9.2 9.7

opmm 01111110V 0.7911 Ojai DAM GAM om

spoeft 14ML ow/01. or am Sim 6,490 GA20 0-426

samb"am""movem um 24.6 2m 2" 313

Town" OWAINIEft awoom

pw4m x W 491 m - -

vaw Pfusum, same, me ism 8021 14A 7.9 0.2

VMS, NPP awm4mise GAS GA GAS *A 2.6

.7fase ails PmP"w of Pwif aftemom oow*oww& ww shftw Rw he ohm se spooKkabons fair sommumemill pmdwu
p. 17

Vapor Pressures of

Ketones vs. Temperature

7-T-T

SAO

4MO

ACETONE

MIRK

n

no I A

o

I

"0 (,OF I

AT

E

E 400

'6ESITYL P OF

30

MM

190 -

hol 101 lnoiw7z '

M- AV I A' AN I I

I Aff A I AFI ffl

so

79

10

-20 -10 0 1# 40 N Of To 00 90 loo IN 140 100 1$$

OC
p. 18

Specific Gravities of

Ketones vs. Temperature

0.96

0.92

0.90 -

leophpfon

iftyl OxId

0.84

0 .82

-Methyl Ethyl Kotgne GAO QC*

0.78

Aeptone ISK

L76 -

0 5 10 is 20 25 30 $5 40 49

TOMPefetwe"IC
P. 19

Fim and physiological Properties of Ketone s

Acialiene Mar. I Ul@K Isophorene M0'tJ Ketones will ignite at ambient temperatures and can

be expected to form flammable mixtures upon

Highly

Flammable Flammable Combustible I Flammable '"'01 release to the air.

PHYSIOLOGICAL PROPERTIE S

Acetone MEK MIBK Isophorone M*sityl Oxide

EYE Markedly Severely Moderately severely Severely

CONTACT 'irritating irritating irritating irritating irritatin g

May cause injury to 9" tissues if not removed promptly . Do not got in eyes.

SKIN Low order of toxcity. Frequent or prolorqed Moderate irritation.

CONTACT contact may irritate skin and cause derrhatitis . AbsoMed in toxic

Avoid frequent or prolonged skin contact . amount on proiongied contact.

in high Concentration . vapor Negligible huwd Highly i. i t ing.

is irritating to @"a and at ambient *"I- Exposure to high

INHALATION mucous membranes, and is persture because of vapor concentration

anesthetic . low volistdity. resulits in loss of

Avoid breathing Vapor& Anesthetic at high consciousneall .

VAmp concentration billow TLV. concentration.

THRESHOLD

LIMIT VALUE* low 200

so S

(TLV), ppm in air

OSHA

TimetWeighted 1000 200 100 25 25

Avera"- (TWA).

VW in air

INGZSMN LOW older of toxie" Moderately"Ric

Pftcaudoow

Keep away from heat. speft and flames. Avoid breathing vapom.

Keep containers closed. Keep concentration in air below Threshold Limit Value .

Do not got m syn. Note Special PrecMions.

Avoid prolonged or repeated skin contact

Iftfol"NL~WMMOWWW woewwwwolom *I giosomoo . will opoew" ONW"m ~~ of a aglow" got --Mip so Werliews OW

so vognow iogneir aft em, lair w~ sowetio~. nre owso tow-- -Sao 98"Oftwolia for a r or 0~ aw"W &W do~

clififtivesse of COMMOMMI "ausgrot ftwesews. riet.

ftepw ftipaw W. SOL No. W. P. later, 8112,11
p. 2 0

First Aid Storage tanks should be located well away from other

buildings. and away from all possible sources of igniEyeCanted tion. Underground tanks may be necessary in some

Immediately flush eyes with plenty of water for at cases . Aboveground tanks should be surrounded by

least 15 minutes. Call a physician . firebanks sufficient to contain the tanks' contents .

Tanks. pipeline systems. and all other equipment

Skin Canted should be grounded to prevent the accumulation of

Flush with water. use soap if available . static electricity.

Inhalation Pressure buildup in tanks should be prevented by vent

Ifovercome by vapor. remove immediately from exposure

and call a physician. Administer artificial respira- lines equipped with flame arrestors . Such vent lines

tion if breathing is irregular or has stopped . should not discharge near doors, windows, Chimneys,

or any source of heat or sparks. The pipelines used

11111901114101111 for filling and discharge should extend almost to the

No hazard bythis route in normal, industrial use . Call a bottom. Centrifugal pumps can be used to draw liquid

physician if swallowed . from the tank. Drip pans should be provided wherever

solvents are transferred from drums or taps .

Spffis and Leaks Adequate ventilation in storage and work areas is

Eliminate all sources of ignition . Wam occupants of extremely important. Excess solvent vapor in the air

downwind areas of fire and explosion hazard . Prevent constitutes a serious explosion and fire hazard . In adliquid from entering sewers, streams or low areas . dition, if the Threshold Limit Value is exceeded, disKeep people away. Contain spilled liquid with sand comfort to workers along with possible toxic effects

or earth and recover by pumping or with a suitable may result. Publications of the National Board of Fire

absorbent. Cleanup personnel should be equipped Underwriters contain much useful information on the

with adequate protective equipment including chemi- design of ventilating systems .

cal safety goggles . self-contained breathing apparatus and protective clothing. Proper education of employees as .to the dangers involved in handling volatile solvents is the comerstone.,of good safety pracbce . Workers should be Waste Disposal trained to recognize and correct hazardous condiKetones may be disposed of by incineratitwO a man- tions . Fire extinguishers. masks, goggles, and other

ner conforming to local regulations . sal*V equipment should be strategically located and

workers should be taught how to use them. Men enterF-i-m- Fi Ming ing vals or tanks for inspection or cleaning should be

Alcohol-type ram is iscaninw-dii'd for fighting ke- provided veM the proper harness and should always

tone liquid fires. Aftemafively~ dry chemical, carbon be obeFerved by someone outside the entrance. Fir*

drills and safety inspections, should be carried out

doxide, or wateir bg rnay be und. Use water spray to regularly. Safety precautions should be suitable for cool fir"xpowd ca m to and to protect personnel .

the particular facilities. personnel, and operations of

each plaf t

Rom& and Handling

Ketonis solvents are flammable . volatile cternicals and

must be handled cautiousty. Users should farnililarize themselves with the Underwritivirs' cgrisil for

these malorials, and with applicable federal, state,

and local regulatiom.
p. 21

Special Precautions

Ketones should not be used with certain active chlorine compounds without attention being directed to

the possible formation of toxic chloroketones .

Shipping Information

powl"Perclevisti G"fftimat

at am losselen, w OC TM GF Deewbet" NOW

ACETONE 6.60 0.00137 0 Flammable Liquid

METHYL ETHYL 6.71 0.00130 21 Flammable Liquid

KETONE

METHYL ISOBLITYL 6.68 0.00113 62 Flammable Liquid KETONE

UESITYL OXIDE 7.11 0.00109 84 Flammable Liquid May form

peroxides

on long

storage

ISOPHORONE 7.68 0.00M 19D Combustible Liquid Freezes

at irF
p. 22

Wes Offices

Akma

3M W. Market Street

Akron, Ohio "313

C216) 83&791 1

Ado"

390 Interstate North, Suits 375

Atlanta, Georgia 30W

(4") 956-moo

Chicap Arms

suite 550

701 Lose Street

Des Plaines, Illimis 60016

(312) 2W1000

Dobvit Area

23M Northwestern Highway

Sou"eld , Michigan 4W75

(813)365-2000

Now York Am

P.O. Sol 201

Florham Park, Now Jersey 07932

001) 765-0100

P.O. Box 3272

Houston, Texas 77001

(713) 8704W

Lm Angdas Ain

Suite 410

5199 East Pacific Coast Highway

lmq Beach, California 90904

C213) W7-1020

NmOrleans

"W Genuml DeGaulle

summo

Now Orleans, LAWsions, 70114

(UK) 561-M

DL Leds Am

TM DombommmmeAvme, Bults M

clalltaffill Wissoull suas

(914) TA&M

Wh*41=

410 Wast NbM 9L

W010*000, Debavare ISM

006564M

E-ZFC%N EXXON CHEMICAL AMERICAS

A7V%F P. M am 3M NM$ftr4lrX77001

IMICALS
p. 23

APPENDIX C

REPORT OF THE ENSR AIR DISPERSION MODELING STUDY
p. 24

Chemical Manufacturer s

Association (CMA)

Ketones Panel

E K-%T

Dispersion Modeling to Estimate

Ambient Concentrations

Associated with Sources of 31EK

November 1996

Document Number 1410-016-100

LX
p. 25

Chemical Manufacturers

Association (CMA)

Ketones Panel

Dispersion Modeling to Estimate

Ambient Concentrations

Associated with Sources of -XIEK

November 1996

Document Number 1410-016-100
p. 26

EM

EXECUTIVE SUMMARY

Title III of the 1990 Clean Air Act Amendments (CAAA) identified 189 Hazardous Air Pollutants

(HAP) to be regulated under Section 112 of the Clean Air Act (CAA) . The CAAA contain

provisions for the HAP list to be modified through a petition process . The Ketones Panel of the

Chemical Manufacturers Association (CMA) is petitioning U.S. EPA to delete methyl ethyl ketone

(MEK) from the HAP list. As part of this petition, CMA is seeking to develop information

pertaining to ambient airborne concentrations in the vicinity of sources emitting MEK to the air .

ENSR, under contract to CMA, has estimated maximum off-site MEK concentrations through the

application of U.S. EPA recommended air dispersion modeling procedures .

The Toxic Release Inventory (TRI) database was used to identify the top emitters of MEK (annual

emissions of 200 tons per year or more), as well as classes of other facilities with annual MEK

emissions of more than 10 tons per year. Companies representing these top emitters were

contacted by CMA and requested to provide site-specific information for atmospheric dispersion

modeling. Dispersion modeling of facility MEK emissions from the top emitting facilities was

conducted by application of the EPA!s recommended approach for CAA HAP petitions (Tiered

Modeling- Arvroach for Assessing Risks Due to Sources of Hazardous Air Pollutants) . This

approach identifies three fiers of analysis that are progressively more agorous with each

successive ter, resulting in more realistic modeled concentrations . Dispersion modeling analysis

indicates that, with one exception not representative of human exposure, maximum annual off-site

concentrations of MEK around the highest emitting facilities are below I Mg/M3 and maximum 24-

hour concentrations are below 10 Mg/M3.

Other MEK facilities (emitting 10 to 200 tons per year) were sorted by SIC code and a

generalized modeling approach was applied. This generalized approach is based on dispersion

modeling previously conducted by EPA in support of Section 112(g) of the Clean Air Act.

Generalized dispersion modeling indicates that maximum annual off-site concentrations are below

1 Mg/M3 in the vicinity of these lesser emitting facilities and are likely to be well below 1 Mg/M3

in most cases .

An analysig was also conducted to determine whether multiple sources of MEK emissions in the

same area might result in significant air impacts . It was concluded that there is no significant

overlap of emissions and that combined impacts from multiple facilities emitting MEK will not

cause maximum annual concentrations greater than 1 .0 Mg/M3 or maximum 24-hour

concentrations greater than 10 MgIM3.

RAPUMPROJECM1410016\100ALL November, 1996

11
p. 27

EM

CONTENTS

1 .0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1 .1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1 .2 Identification and Selection of Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1 .3 Dispersion Modeling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1 .4 Summary of Study Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1 .5 Report Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1- 3

2.0 SOURCES SUBJECT TO SITE SPECIFIC MODELING . . . . . . . . . . . . . . . . . . . . . 2-1

2 .1 Identification of Top Emitters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2 .2 Solicitation of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2 .3 Source Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2- 7

3.0 DISPERSION MODELING METHODS FOR TOP EMITTERS OF MEK . . . . . . . . . . 3-1

3.1 Tier I Modeling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.2 Tier 2 Modeling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.3 Tier 3 modeling approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4

4.0 EVALUATION OF MAXIMUM OFF-SITE CONCENTRATIONS AT HIGHEST

EMITTING FACILITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

5.0 EVALUATION OF LESSER MEK SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1 Generalized Modeling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.2 Estimated Receptor Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5- 2

6.0 COMBINED IMPACTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

7.0 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1

RAPUMPROJECTS14100160000ALL November, 1996
p. 28

Elm

LIST OF TABLES

2-1 Listing of Top MEK Emitters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2

2-2 Basis for Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

2-3 Alternative Modeling Parameters for Non-Participants of Survey . . . . . . . . . . . . . . 2-5

2-4 Generically Modeled Non-Participants of survey . . . . . . . . . . . . . . . . . . . . . . . . . 2-6

3-1 Normalized Maximum Annual Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

4-1 MEK Dispersion Modeling Results for Top Emitters - Annual Average . . . . . . . . . . 4-2

4-2 MEK Dispersion Modeling Results for Top Emitters - 24-Hour Average . . . . . . . . . 4-3

4-3 MEK Dispersion Modeling Results for Top Emitters - Annual Average . . . . . . . . . . 4-4

4-4 MEK Dispersion Modeling Results for Top Emitters - 24-Hour Average . . . . . . . . . 4-5

5-1 MEK Facility Impacts for Lesser Emitters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

5-2 Evaluation of Top Emitting SIC Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

R:\PU8MPR0JECTS\1 41001alOOALL November, 1996
p. 29

On

LIST OF FIGURES

3-1 Sample Receptor Grid Used in Tier 3 Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6

4-1 Refined MEK Modeling Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

4-2 Refined MEK Modeling Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-8

RAPUMPROJECTS\1410016\100ALL November, 1996
p. 30

MR

1 .0 INTRODUCTION

1 .1 Purpose

Title III of the 1990 Clean Air Act Amendments (CAAA) identified 189 Hazardous Air Pollutants

(HAP) to be regulated under Section 112 of the Clean Air Act (CAA). The CAAA contain

provisions for the HAP list to be modified through a petition process . The Ketones Panel of the

Chemical Manufacturers Association (CMA) is petitioning U.S.EPA to delete methyl ethyl ketone

(MEK) from the HAP list. As part of this petition, CMA is seeking to develop information

pertaining to ambient airborne concentrations in the vicinity of sources emitting MEK to the air .

ENSR is under contract to CMA to estimate maximum off-site MEK concentrations through the

application of U .S.EPA recommended air dispersion modeling procedures .

1 .2 Identification and Selection of Sources

ENSR's analysis was divided into three parts . First, because airborne concentrations are likely

to be highest in the vicinity of the top emitters of MEK, ENSR conducted refined modeling for a

large number of major MEK emitters using site-specific information provided by the facilities or,

in a few cases, obtained from publicly available sources . The Toxic Release Inventory (TRI)

database was reviewed to identify all sources for which annual emissions equaled or exceeded

200 tons per year, since these facilities have the greatest potential for adverse off-site exposure . Twenty-six manufacturing facilities identified from the TRI review were contacted by CMA and

requested to provide detailed source information so that site-specific atmospheric dispersion

modeling of MEK emissions could be conducted .

Second, ENSR developed a generalized approach for analyzing maximum airborne

concentrations in the vicinity of lesser emitting facilities . AJI facilities that reported more than 10

tons of MEK emissions on the 1994 TRI were divided into source categories based on their twodigit SIC codes. ENSR developed parameters for each SIC code and then used a generalized

EPA model to predict likely maximum airborne concentrations based on the annual emission rates

for the highest and second highest emitting facilities in each SIC code.

Third, an analysis was conducted to determine whether multiple sources of MEK emissions in the

same area might result in significant air impacts. All facilifies emitting greater than 10 tons of

MEK were identified and sorted by postal ZIP code . Groups of sources were evaluated to

determine the potential for overlapping emissions.

RAPUBSPROJECTS\1 410016\1 WALL Navember, 1996
p. 31

11111ILLSIS

1 .3 Dispersion Modeling Approach

Dispersion modeling of entire facility MEK emissions from the top emitting facilities was conducted

by application of the EPA's Tiered Modeling Approach for Assessing Risks Due to Sources of

Hazardous Air Pollutants (EPA, 1992). This approach identifies three fiers of analysis that are

progressively more rigorous, with each successive tier resulting in more realistic modeled

concentrations. The first tier tends toward the most overprediction, requires the least detailed

input data and uses simple look-up tables. The second tier uses standardized EPA screening

modeling techniques that more realistically include plume rise and building downwash but are still

designed to be relatively conservative, i.e., to overestimate air quality impacts. The third tier uses

refined dispersion modeling following EPA's Guideline on Air Quality Models (Revised) (U .S. EPA,

1995) and provides the most realistic impacts . Facilities that were identified as "top emitters"

were first modeled using both Tier 1 and Tier 2 methods. Selected facilities among those with

higher Tier 2 modeled impacts were also modeled using the refined Tier 3 techniques.

For facilities below the 400,000 lb annual MEK emissions threshold, ENSR used a generalized

modeling approach based on the model developed by EPA as part of the Agency's rulemaking

under Section 112(g) of the Clean Air Act (EPA, 1993). The EPA model results in a dispersion

coefficient, based on a small number of input parameters, that is applied to an emission rate . ENSR adjusted the EPA model to incorporate worst-case meteorological conditions, and then

used it to predict maximum airborne concentrations for model facilities . These facilities were

selected to represent each SIC code, not otherwise represented by one or more of the top

emitters, that had at least one facility reporting more than 10 tons of MEK emissions in 1994.

The generalized approach was also applied to the remaining top emitters for which sufficient site

information could not be obtained .

1 .4 Summary of Study Findings

1 . Refined dispersion modeling estimates of emissions from all facilities reporting 400,000

pounds or more of MEK emissions in 1994 indicates that, with one exception, maximum

annual off-site concentrations of IVIEK around these facilities are below 1 Mg/M3 and

maximum 24-hour concentrations are below 10 Mg/M3

. For one facility, the maximum annual

off-site concentration was 1

.18 MgIM3 and the maximum 24-hour concentration was 12.82 Mg/M3

.- However, for this facility, the point of the highest predicted concentrations was not

at a location where 24-hour or annual exposure could occur .

2. Generalized dispersion modeling of lesser MEK emitters indicates that maximum annual offsite concentrations are likely to be below I Mg/M3 in all cases, and well below 1 MgIM3 in

most cases.

R\PUMPROJECTS141001bA100ALL 1-2 November, 1996
p. 32

EM

I There is little or no potential for significant air quality impacts from multiple sources of MEK

emissions in the same area. That is, combined emissions from multiple sources will not

cause maximum annual MEK concentrations greater than 1 .0 Mg/M3 or maximum 24-hour

concentrations greater than 10 Mg/M3.

1 .5 Report Organization

This report is organized as follows. A description of the approach used to identify and collect

pertinent modeling input data from sources is provided in Section 2 . Section 3 describes the

dispersion modeling methods applied to the top emitters . Modeling results for top emitters are

presented in Section 4 . Section 5 discusses the method used to model emissions from smaller

sources and presents the results of this analysis . Section 6 then addresses the issue of collective

emissions from multiple sources. Section 7 summarizes the study findings . Appendix A provides

the forms that were used to solicit source information for modeling and Appendix B provides

further information on the generic method used to model emissions from lesser MEK sources .

RAPUBMPROJECTS\14100IM100ALL 1-3 November, 1996
p. 33

1119116MIN

2.0 SOURCES SUBJECT TO SITE SPECIFIC MODEUN G

2.1 Identification of Top Emitters

The Ketones Panel has undertaken a program to gather data on the maximum airborne

concentrations of MEK to which the public may be exposed . As part of this program, the Panel

funded a study by ENSR to model the maximum off-site concentrations of MEK at the largest

sources of MEK emissions in the country . To identify the facilities to be included in this study,

the Ketones Panel used the methodology that EPA developed to set de minimis values for

hazardous air pollutants under Section 11 2(g) of the Clean Air Act (EPA, 1993). The de minimis

value for a chemical is the amount that an EPA model facility could emit without posing more than

a "trivial" risk to human health or the environment . EPA has proposed to "cap" de minimis levels

at 10 tons per year, but EPA's methodology may also be used to calculate true "uncapped" de

minimis values for different compounds. Using EPA's methodology, the uncapped value for MEK

is 2,000 tons (or 4,000,000 pounds) per year, calculated using an inhalation reference

concentration (RfC) of 1 .0 Mg/M3, which is the existing value in the IRIS database.' In order to

establish a meaningful cutoff point for its modeling exercise, the Panel decided that it would seek

to model all facilities with reported emissions that were 10 percent or more of the uncapped de

minimis value. Thus, it sought to model the maximum off-site concentrations for all facilities

reporting MEK emissions of 200 tons (400,000 pounds) or more per year . Based on 1993 TRI

data, the Panel identified 30 such facilities.

2.2 Solicitation of Data

The Panel also worked with ENSR to develop a detailed questionnaire to gather the information

that would be necessary to model the maximum off-site concentrations at each facility . This

questionnaire, along with a cover letter explaining the Panel's modeling program and the

protection of confidential information, was sent to the 30 facilities. Representatives from the

Panel also contacted each of the facilities to encourage their participation . By the time the Panel

received the necessary data and ENSR began its modeling exercise, the TRI data for 1994 had

become available. From 1993 to 1994, the number of facilities reporting MEK TRI emissions

greater thah 200 tons had dropped from 30 to 26. Table 2-1 lists each of the facilities that '

'Since the RfC: was established in the IRIS database, EPA has issued new guidelines for setting RfCs . Based on the new guidelines, the Ketones Panel has calculated that the correct

RfC for MEK is 3

.3 Mg/M3.

R :XPUBSkPROJEC'rS*\141001b\IOOALL 2-1 November,

1996
p. 34

Mrqft

TABLE 2-1

Listing of Top MEK Emitters

FadHty :199K4 2. Diet

COMP2 Location --- Bus Obs.) SIC Code . Gencorp Coliunbus, MS 2,026,760 22 (Nonwoven Fabrics)

O'Sullivan Winchester, VA 1,366,079 30(Plastics)

IPC Corinth, MS 1,256,755 30(Plastics)

Mobil Oil Beaumont TX 1,216,000 29 (Refining)

3M Specialties Hutchinson, MN 1,010,000 36 (Electronic)

Columbus Fabrics Columbus, OH 867,838 22 (Coated Fabrics)

Texas Recreation Corp Wichita Falls, TX 790,100 30(Plastics)

Uniroyal Stoughton, WI 714,199 22 (Nonwoven Fabrics )

Sun Refining Tulsa, OK 701,000* 29 (Refining)

Alcoa Riverxiale, IA 694,000 33 (Aluminum)

Resilitesports Northumberland. PA 648,757** 39 (Ivfisc . Wg.)

3M Specialties Kearneysville, W 626,360 35 (Ind. Machinery)

R.J . Reynolds Tobacco Winston-Salem, NC 609,594 21 (Cigarettes)

Reynolds Metals Sheffield, AL 578,000 34 (Metal Coating)

Amoco Corp. Whiting, IN 558,000 29(Refining)

Plastene Supply Co. Portageville, MO 550,373 34 (Metal Coating)

Sony Products Dothan, AL 540,291 36 (Electronic)

Shell Oil Deer Park, TX 536,370 29 (Refining)

Norandal USA Inc. Newport, AR 518,175 33 (Aluminum)

3M Specialties White City, OR 517,000 38 Qvleanwing hist.) Textileather Corp . -Toledo, OH 510,000 22 (Nonwoven Fabrics )

Allied Tube and Conduit Harvey, IL 506,000 33 (Aluminum)

Textrm Automotive Americus, GA 489,189 37(Mot. Veh. Parts)

Reynolds Metals Richmond, VA 405,000 33 (Aluminum)

Boeing Everett, WA 400,000 37 (Airline)

Sun Oil Co. Yabucoa, PR 400,000 29 (Refining)

Athol Corp. Butqer~ NC 397,000 22 CNonwoven Fabrics )

Siti-Re tfi4 Co~ has inforniM: dieXi Rinal # iatI

it recenW condik-ted. :

~'.-cmissiom to: ..tests)a&khin~that. :i.tsl994&MK.en3i~ the air were otmstated by

a and w= actually well below:

:400;WO pouad& The 1995 Form R for this

facilfty more .

ii*wiately SiVem M-ports : AMpounds pissions.:4 241 . B~ on this information

the: Panel :hkSlidt 11201wed: disOmiah modeling resultsIor this facility ~

F"iResffit6:pr*ykIedJ995. MEK-em2ssi.em

.

fwji-34. IW):tI6:be-.u

RAPUMPROJECM1410016NI00ALL 2-2 November,

1996
p. 35

VIIIIIJIMIN MR&M

reported MEK emissions of greater than 200 tons on the 1994 TRI, along with the SIC code for

each facility.

As noted in Table 2-1, three of the listed facilities have revised MEK emissions that are below the

200 ton criterion that is used to define the top-emitters . The rule of thumb applied is that such

a facility would be included in the top-emifter assessment if the revised annual MEK emissions

exceeded 90% of the 200 ton criterion . Thus , Resilite Sports was included in the analysis along.

with Athol Corporation, for which the MEK TRI emissions estimate dropped to just below 200 tons

in 1994.

The SIC codes indicate that the top-emitting facilities represent a wide variety of industries.

Facility-specific data needed for modeling was received from 14 facilities, including the 4 highest

emitters. In addition, one facility provided results of dispersion modeling for MEK emissions that

had already been conducted independent of this study . Thus, facility specific information or preexisting dispersion modeling results were obtained from 15 of the 26 highest-emiffing MEK

sources in the country, including 6 of the top 10.

In order to conduct dispersion modeling for the other 11 facilities identified as top emitters, the

Panel and ENSR attempted to obtain relevant facility data from public sources . For each facility,

we conducted a search on EPA's Aerometric Information Retrieval System (AIRS) database . In

addition, we contacted state and local regulatory officials to determine whether a Title V permit

application or similar document had been submitted by any of the remaining facilities. Title V

permit applications were obtained for 4 of the 11 remaining facilities . Based on the information

available from the AIRS database and permit applications, ENSR was able to conduct refined

dispersion modeling for 5 of the 11 facilities that did not provide information directly to ENSR.

In situations where detailed information on specific data elements (such as stack height, building

height, etc.) were not available from these sources, reasonable, conservative estimates of these

elements were made. For the other 6 facilities, no facility-specific data was available . For each

of these facilities, ENSR modeled maximum off-site concentrations using the generalized model

described in Section 5 .

Table 2-2 shows the basis for modeling each of the 26 top-emitting facilities . Table 2-3 shows

specific data elements that were obtained from publicly available sources for facilities that were

modeled b~sed on limited data, as well as the estimates that were made in the absence of such

data. Listed in Table 2-4 are facilities for which a generalized modeling approach was applied

because no relevant data were obtained .

RAPUMPROJECTS\14100M100ALL 2-3 November, 1996
p. 36

ENR

TABLE 2-2

Basis for Dispersion Modeling

Site $pecifiz Information Providedby the Following Companies:

Gencorp - Columbus, MS

O'Suffivan - Winchester, VA

IPC - Corinth, MS

Mobil Oil - Beaumont, TX

Columbus Fabrics - Columbus, OH

Uniroyal - Stoughton, WI

Resilite Sports - Northumberland, PA

Reynolds Metals - Sheffield, AL

Amoco Corp . - Whiting, IN

Sony Products - Dothan, AL

Shell Oil - Deer Park, TX

Textileather Corp . - Toledo, OH

Sun Oil Co . - Yabucoa, PR

Athol Corp . - Butner, NC

. . . . . . . . . . . . . . .. . .

-MW6-.~,ReWts;Pi-oVW.ed:by- ;he FOkrwm-&C0mOq*s .

R.J. Reynolds Tobacco - Winston-Salem, NC

.9 :S~ecifio~M6&66 Biiiiea g :. 66:Pu ii& b . Data fbr.

.

3M Specialties - Hutchinson, MN

3M Specialties - Kearneysvffle, WV

3M Specialties - White City, OR

Alhed Tube and Condtnt -H IL

Boeing - Everett, WA

EPA 112(g)U, dXXIC40gy- pofmmed

Texas Recreation Corp. - Wichita FaUs, TX

Alcoa - Riverdale, IA

Plastene Supply Co. - PortageviHe, MO

Norandal USA Inc . - Newport, AZ

Textron Automotive - Americus, GA

Reynolds Metals - Richmond, VA

RAPUMPROJECTSM41001MI00ALL 2-4 November, 1996

1~
p. 37

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CD C) CD ON

At

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RAPUBWROJECTS\141001alOOALL 2-5 November, 19%
p. 38

TABLE 2-4

Non -Participants for which Generalized

Modeling was Conducted

Gampmy . T.RI:1"4

fadIky.L*CatM- : .: : finktion

Texas Recreation Corp. 790,100

Wichita Falls, TX

Alcoa 694,000

Riverdale, IA

Plastene Supply Co. 550,373

Portageville, MO

Norandal USA Inc. 518,175

Newport, AR

Textron Automotive 489,100

Americus, GA

R olds Metals 405,000

Richmond, VA

RAPUMPROJECTS\1410016MOO .ALL 2-6 November, 1996
p. 39

EM

Facilities participating in the CIVIA program provided site-specific data for modeling based on

conditions of confidentiality. To this end, anonymity of modeling results was achieved by

assigning a code to each participating facility. In addition, tables providing model input

information which are normally provided in dispersion reports conducted, for example, in support

of permit applications, have not been included .

2.3 Source Characterizatio n

The questionnaire sent to participating companies requested the following information :

General information : facility plot plan showing property boundary, fenceline, source locations,

building and storage tank height, location indicated on a topographic ma p

Point source information : emission rate, release height, temperature, flow rate, effective

diameter, flow obstructio n

Area source information: emission rate, height, site of the area

This information was used to develop input for dispersion modeling of MEK emissions . The

actual annual emissions provided by the facilities were used to estimate annual average

concentrations. In 4 cases, emissions data provided by the companies were slightly (less than

3%) lower than the emissions reported in the TRI . In one case, modeling was based on 1993 TRI

emissions which exceeded 1994 TRI reported emissions by approximately 10%. For Reslite

Sports modeled emissions were 43% less than the 1994 TRI data .

To model maximum 24-hour off-site concentrations, ENSR used maximum daily MEK emissions

rates in the few instances where such information was provided by the facility. Otherwise, the

maximum 24-hour concentrations were computed applying a daily emission rate based on the

annual emissions divided by 260 days, (i .e., assuming that the facilities operate on a five-day-perweek schedule) .

RAPUMPROJECTS\1410016MOALL 2-7 November, 1996
p. 40

W&XqI% Wdllmkft

3.0 DISPERSION MODELING METHODS FOR TOP EM17TERS OF MEK

ENSR performed air quality modeling analyses for each of the top-emitting MEK facilities using

EPA's "Tiered Modeling Approach for Assessing Risks Due to Sources of Hazardous Air

Pollutants" (1992) . This approach uses three progressively more Hgorous modeling techniques . Tier 1, which requires only limited source information and a look-up table, provides the most

conservative predictions of maximum concentrations. Tier 2, which requires additional source

information and uses an EPA screening-level computer program, generates predictions that are

somewhat more realistic than Tier 1 predictions. Tier 3, which requires extensive data from the

source and uses EPA's refined dispersion modeling techniques, provides the most realistic

predicted concentrations . Because each successive tier provides a less conservative (and more

realistic) prediction, Tier 3 modeling was generally performed for a facility only if Tier 2 modeling

predicted maximum annual concentrations were above 2 MgIM3.

In all of these modeling methods, MEK is assumed to disperse in the atmosphere as a passive

tracer, not subject to removal through deposition or chemical reaction duiring transport . This is

a reasonable assumption given the typically short transport time (less than 10 minutes) from the

source to the point of maximum impact .

3.1 Tier 1 Modeling Approach

The Tiier 1 approach is based on a parameterization of EPA screening models. It is compirised

of a set of look-up tables . Information required for Tier 1 modeling include :

emission rate

point source height

size of area source

distance to nearest property line

The look-up tables provide emission-normalized 1-hour and annual concentrations for each

source. These concentrations are multiplied by the corresponding source-specific emission rate

to calculate the maximum off-site concentration . The maximum concentrations from individual

sources are then added to estimate an overall maximum annual and 1-hour concentrations . To

estimate maximum 24-hour MEK concentrations, the Tier 1 1 -hour concentrations were multiplied

by a time averaging factor of 0.4, as recommended in U.S. EPA's screening modeling guidance

(U .S. EPA, 1992a) . The Tier 1 estimate is highly conservative because it does not account for

RAPUBSPROJECTS1 4 1 DOI 6\1 OOALL 3-1

November, 1996
p. 41

EM

plume rise or above ground area sources and assumes that maximum contributions from all

sources are cumulative at a single receptor point .

Tier 1 Example

The Tier 1 method is illustrated by the following example provided in the EPA guidance

document. Consider the situation in which a toxic pollutant A is released at a rate of 14.6 ton/yr

f

rom a vent-pipe that is 40 m tall, and which is attached to a building that is 4 m tall, 10 m long,

and 5 m wide. The nearest boundary of the facility is located 65 m from the vent. Table 3-1 is

EPA's look-up table for determining Tier 1 maximum annual concentrations . A value of 35 m is

selected for the emission height, because all larger entries in the table exceed the actual release

height of 40 m. Concentrations are estimated for a distance -of 50 m, because once again, all

greater entries in the table exceed the actual distance of 65 m . The appropriate normalized

maximum annual concentration is 1 .13 (gg/M3)/(ton/yr). Multiplying by the emission rate of 14.6

ton/yr results in a maximum annual concentration estimate for screening purposes equal to gg/M3 16.5 .

3.2 Tier 2 Modeling Approach

Tier 2 uses a computerized U.S. EPA screening model, SCREEN3, to estimate maximum off-site

concentrations. SCREEN3 predicts maximum 1 -hour concentrations which are then multiplied

by a scaling factor of 0 .4 to estimate maximum 24-hour concentrations and 0.08 to estimate

maximum annual concentrations (U.S. EPA, 1992a) . In addition to the information required for

Tier I modeling, Tier 2 modeling requires :

inner stack diameter

stack gas exit velocity

stack gas temperature

worst-case building dimensions for aerodynamic downwash simulation

rural/urban dispersion environment classification

U.S .G.S.

topographic maps were examined to determine land use within a 3 krn radius of each

of the top-emitting facilities. If over 50% of the area has urban land use, then SCREEN3 was

applied witfi urban dispersion coefficients . Otherwise, rural dispersion was specified. If the

classification of an area was ambiguous, the model was run in both modes and the greater of the

two results was used in the assessment.

RAPUBSPROJECTSkI410016%100ALL 3-2

November, 1996
p. 42

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RAPUSSPROJECTSA141001M100ALL 3-3 November, 1996

9/
p. 43

EM

SCREEN3 simulates building downwash based on the dimensions of the structure, which result

in the highest Good Engineering Practice stack height, determined by the formula: GEP = building

height + 1 .5 x L (where L is the lesser of building height or width) .

All buildings within a distance of 5L are considered.

SCREEN3 modeling was performed separately for each point and area source with receptors

placed at a distance closest to the nearest fenceline and at 100 m intervals to 2 krn assuming flat

terrain . As was the case with the Tier 1 calculations, the maximum modeled impacts for multiple

sources were assumed to completely overlap, such that the Tier 2 modeled estimate is highly

conservative .

Tier 2 Example

To illustrate the Tier 2 long-term analysis, consider the Tier I example. To consider downwash

possibilities, the maximum horizontal dimension f(l OM)2 +

(5m)j"2 = 11 .2m) is first compared to

the 4 m building height. The dimension L is then the building height of 4m, such that the

maximum stack height for which downwash is possible would be 4m + 1 .5 X 4m = 1 Orn. Since

the actual stack height is 40 m, downwash need not be considered in the SCREEN3 simulation.

The emission rate specified in the example of 14 .6 ton/yr is converted to grams per second

(g1sec) to be used in the SCREEN3 simulation, resulting in an annual emission rate of 14.6/34.73

= 0.42 g/sec. In addition to the actual stack height (40m) and minimum fenceflne distance (65m),

input parameters for the SCREEN3 simulation are:

Inside stack diameter 0.5m

Stack gas exit velocity 5.6 m/s

Stack gas exit temperature 303 K

Plant location urban

The results from the SCREEN3 simulation indicate that the maximum 1 -hour concentration (based

on an annual emission rate) at or beyond 65m is 32.5 4M3, occurring 165m downwind. After

incorporating the recommended conversion factor of 0.08, the maximum annual concentration is

estimated as 2 .6 gg/m3 - a value that is a factor of 6 lower than the Tier 1 estimate of 16.5 RgIM3 .

3.3 Tier 3 modeling approac h

Tier I and 2 screening was used to predict maximum annual and maximum 24-hour

concentrations for all top emitting facilities for which adequate data were available . Refined Tier

3 modeling was applied only to those few facilities with the highest modeled Tier 2 concentrations .

RAPUMPROJECMI 41001V WALL 3-4 November, 1996
p. 44

z&Xq%

Modeling was performed in accordance with the EPA tiered approach and Guidelines on Air

Quality Models (EPA 1992, 1995). The modeling applied the U.S . EPA's Industrial Source

Complex Short Term Model (ISCST3), which is the guideline model for simulating point sources

subject to aerodynamic building downwash and area sources . ISCST3 incorporates information

on the facility layout with respect to property boundary, source location and building dimensions

and can compute concentrations for 24-hour and annual averaging periods . As shown in Figure

3-1, model receptors were placed along the property boundary and in a 100 m x 100 m square

grid out to 2000 m. Given that all of the sources modeled were either area sources or point

sources subject to building wake effects, maximum modeled off-site concentrations always

occurred adjacent to the property boundary . As such, variation in terrain surrounding the facility

was not considered in the assessment . Refined Tier 3 modeling used representative, National

Weather Service (NWS) surface and mixing height data, obtained from U .S. EPA's SCRAMS

Bulletin Board. Meteorological site selection was based on proximity and geographical setting .

Five years of meteorological data were modeled and the maximum annual and 24-hour

concentrations among each of the five years of data were used in the impact assessment . That

is, the annual concentration represents the highest average concentration occur7ing for any single

year over the five years modeled, and the 24-hour concentration is the highest concentration that

was modeled for any day over the entire 5 year period.

RAPUBSPROJECTSM410016MOALL 3-5 November, 1996
p. 45

w2jrqwb

2000- - -

1000

-1000

C)C)O

-2 Il I -F T I

-2000 -1000 0 1000 2000

X(M )

FIGURE 3- 1

Sample Receptor Grid Used in Tier 3 Modeling

3-6 November, 1996
p. 46

EM

4.0 EVALUATION OF MAXIMUM OFF-SITE CONCENTRATION S

AT HIGHEST EMITTING FACILITIES

Results of the tiered modeling for top MEK emission sources are provided in Tables 4-1 and 4-3

for maximum annual and 24-hour concentrations, respectively . Tables 4-2 and 4-4 present the

same data sorted according to how the information for modeling was obtained . Facilities are

ranked according to Tier 2 modeling results, in descending order . Of the top facilities, 19 had Tier

1 and 2 screening performed and 7 had additional Tier 3 refined modeling performed . One

facility had already conducted screening or refined modeling independently of this study . For the

6 top emitting facilities for which site information was not obtained, the values listed on the tables

are based on the generalized modeling approach discussed in Section 5.

It is important to recognize that the health benchmarks for MEK are based on continuous

exposure. The RfC (3.3 mg/m3) is specifically designed to be protective for continuous exposure

for a lifetime of 70 years, and the 24-hour benchmark (33.0 Mg/M3) is designed to be protective

for continuous exposure over a 24-hour period . The maximum off-site concentrations computed

in this assessment, however, are not intended to represent actual population exposure . In many

instances it is unlikely that locations where maximum off-site concentrations are modeled are

places where continuous exposure can actually occur. In every case, modeled maximum off-site

concentrations are located near the facility boundaries . The top MEK emitters are large facilities

which are likely to be surrounded by industrial and commercial properties. As such, receptors

close to the facility boundaries are areas where the exposure time is typically no more, and

probably significantly less, than 8 hours per day, 5 days per week rather than continuous . It is

also important to recognize that the off-site concentrations computed in this assessment are

maximum annual and 24-hour concentrations . Even at the worst-case fenceline locations, actual

off-site concentrations averaged over one-year and 24-hour periods are likely to be lower .

Table 4-1 shows that the highest modeled annual Tier 2 concentration, which occurs for facility

E17, is about 12 MgIM3 and the corresponding Tier 3 concentration is 1 .2 Mg/M3

. The model

receptor where the maximum concentration occurs is located across the roadway from facility

El 7, near the vehicular entrance to an industrial area. As such, it does not represent a receptor

where 24-hour exposure is possible . The modeled annual concentration at the second highest

off-site receptor at this facility is 0

.81 MgIM3

. Annual Tier 3 concentrations at WI other facilities

are Wso below I Mg/M3.

Tier 3 modeling was conducted for each facility at which the Tier 2 predicted concentration was

greater than 2.0 mg/m'. The highest Tier 2 concentration for which refined modeling was not

conducted is 1

.77 Mg/M3

. As anticipated, Tier 3 concentrabons are substantially lower than the

RAPUBSPROJECTSM 410016\100ALL 4-1 November, 1996
p. 47

IIIIIIWFI~

TABLE 4-1

MEK Dispersion Modeling Results for Top Emitters

Maximum Annual Averag e

M 3.3 mg/nr~+ .

~Tiet I. . . Tw'r2

E17 29.0 12.33 1.18

E9 33.0 11 .2 0.91

E28 13 .7 4 .75 0.81

E7 14.5 3 .97 0.50

E25 38.1 3 .37 0.42

E4 17 .1 2.99 0.55

E3 12 .3 2 .65 0.63

E20 19 .4 1 .77 -

E33* 5.5 1.56 -

E19* 8.5 1 .42 -

E21 14 .6 1 .37 -

E14* 6.9 1.23 -

E29 26.5 1 .13 -

E16* 6.9 0.69 -

E23 9.9 0.46 -

E8 9.7 0 .42

E32 6.2 0 .18

El 9.2 0 .12

Ell* 0.2 0. 1

E15 - - 0.03**

*Model input parameters for non-participating facilities have been estimated

from available data sources (see Table 2-2) .

** Based on dispersion modeling results provided by individual companies .

+ Based on RfC for MEK in EPA's IRIS database updated to reflect 1994 EPA guidance on

deriving RfCs . Updated RfC provided by CMA Ketones Panel .

4-2 November, 1996
p. 48

TABLE 4-2

MEK Dispersion Modeling Results for Top Emitters

Maximum Annual Averag e

nuaNSK: cmWentmtkit (mgfw):Ow 3.3 mgfw)

Site. TierI Tier 2 rier 3

~Site Specific Modeling Completed :

E17 29.0 12.33 1.18

E9 33.0 11 .2 0.91

E28 13 .7 4 .75 0.81

E7 14 .5 3 .97 0 .50

E25 38.1 3.37 0 .42

E4 17 .1 2.99 0 .55

E3 12.3 2.65 0.63

E20 19.4 1 .77 -

E21 14.6 1 .37 -

E29 26.5 1.13 -

E23 9 .9 0 .46 -

E8 9.7 0 .42 -

E32 1 6.2 1

0 .18

El 9 1

.2 0.12

~site~:SpecifioModeling~~-C6mpk~ed ;Bgsod .. . PubliciData . :

E33 5 .5 1 .56

E19 8.5 1 .42

E14 6.9 1 .23

E16 6.9 0 .69

Ell 0.2 0.1

Rists P m6ded .

. .

E15 0

:

~~ .03 :M~~.ResWts:

Table. 4TActor .DC xAnnuOlIN18K . Siw J.

:994 TRI Emissiowfdbl per. :0~6~(MgWY

E12 790,100 0.91 M 0.72

E2 694,000 0 .39 (M 0.27

ElO 550,373 0.91 M 0.50

E18 518,175 0.91 (M) 0.47

E34 489,189 0.39(14) 0.19

E35 405,000 0.39(1-1) 0.16

Dispersion Category

RAPUBSPROJECTS\14100M100ALL 4-3 November,

1996
p. 49

EM

TABLE 4-3

MEK Dispersion Modeling Results for Top Emitters

Maximum 24-Hour Averag e

ir Concentradon (mg/W) (Benichmark := 33.0 mgfm3,)+

site TierI TierI T+ier3

E17 186.8 86.3 12.82

E9 196.2 64.0 7 .42

E28 137.0 33.3 5 .24

E7 81 27.8 4 .67

E3 58

.9

.2 18

17n-

.5 2 .44

E25 232.3 16.85 2.77

E4 73.0 15.63 7.57

E20 108.5 12.39 -

E19* 47.6 9 .91 -

E21 146.3 9.57 -

E14* 38.3 8.58 -

E33* 35.0 8.27 -

E29 144.2 7 .91

E16* 38.5 4 .86 -

E23 115.2 3 .21 -

E8 54.4 2.93 -

E32 35.0 1 .23 -

Ell* 1 .2 0.72 -

El 36.7 0 .59

E15 - - LL*Lj 0 .35**

*Model input parameters for non-participating facilities have been estimated

from available data sources (see Table 2-2) .

** Based on dispersion modeling results provided by individual companies .

+ Based on updated RfC modified to eliminate uncertainty factor for extrapolating from

chronic to subchronic exposures. Value provided by CMA Ketones Panel .

RAPUBSAPROJECTSM 4100 1M100ALL 4-4 November, 1996
p. 50

EM

TABLE 4-4

MEK Dispersion Modeling Results for Top Emitters

Maximum 24-Hour Averag e

Max 24-hrCencelit!ttlLon,(VWM3)~:(Bmchmw*~= 0-.Iftghn"~ .

Tier. I Tier 2. L Tw-r-3

Site Specificl&deling Completed

E17 186.8 86.3 12 .82

E9 196.2 64.0 7.~2-

E28 13 33.3 5 .24

E7 81.9 27.8 4 .67

E3 58.2 18.5 2.44

E25 232.3 16.85 2.77

E4 73.0 15.63 7.57

E20 108.5 12.39 -

E21 146.3 9.57 -

E29 144.2 7 .91 -

E23 115.2 3 .21 -

E8 5 .4 2.93 -

E32 35.0 1 .23 -

El 36.7 0.59 -

site COmplOt6l : wPubh&Data..:, .

E33 35.0 10.89

3'

0

E19 47 .66 9 .91

E14 38.3 8.58

E16 38.5 4.86

Ell

1

.2 0.72

Re~ om.

E15

R.\PUBSAPROJECTSA1410016\100ALL 4-5 November, 1996

~~ 0
p. 51

EM

corresponding Tier 2 results . For the seven facilities for which Tier 3 modeling was performed,

the Tier 3 value was between 76% and 92% lower than the corresponding Tier 2 value, with an

average of 85%. Thus, it appears reasonable to anticipate that Tier 3 values will be lower than

corresponding Tier 2 values by at least 76%.

For illustrative purposes, this reduction factor has been applied to develop "adjusted Tier 2"

values for all of the remaining sites for which Tier 2 modeling (but not Tier 3 modeling) has been

conducted. The highest adjusted Tier 2 value is 0.42 Mg/M3 (1 .77 x 0.24). The predicted

maximum annual off-site concentrations for all the top emitting facilities are plotted on Figure 4-1,

with adjusted Tier 2 values shown where Tier 3 values were not computed . As indicated on

Figure 4-1, maximum off-site annual concentrations at all of the top emitting facilities are well

below the RfC of 3

.3 Mg/M3 and, in most cases, are well below 1 mg/M3. The average of the

maximum annual off-site concentrations at the top-emitting facilities (including adjusted Tier 2

values where Tier 3 values were not derived) is about 0

.3 Mg/M3.

Modeled maximum 24-hour average concentrations are provided in Table 4-3 . The highest offsite Tier 3 concentration of 13 MgIM3 (for facility El 7), occurs at the same isolated receptor as

has been noted for the annual modeling and is not representative of public exposure . The

second highest concentration among all other off-site receptors in the vicinity of that facility is 8.3

mg/m3. All other Tier 3 modeling results are below 10 Mg/M3 . Where Tier 3 modeling was

performed, the Tier 3 24-hour concentrations were between 51% and 91% lower than the

corresponding Tier 2 value, with an average of 80%. Thus, it appears reasonable to anticipate

that Tier 3 24-hour values will be lower than the corresponding Tier 2 values by at least 5 1

For facilities for which Tier 3 modeling was not performed, adjusted Tier 2 24-hour concentrations

were estimated by reducing the Tier 2 value by 51%. This results in a maximum adjusted Tier

2 24-hour concentration of about 6 Mg/M3

. Figure 4-2 shows Tier 3 and adjusted Tier 2 maximum

24-hour off-site concentrations for all of the top-emitting MEK facilities . As indicated on Figure

4-2, maximum 24-hour concentrations at all of the top emitting facilities are well below the health

benchmark of 33 Mg/M3 and, in most cases, are well below 10 Mg/M3.

In evaluating the maximum 24-hour concentrations, it is again important to recognize that they

are intended to represent maximum off-site concentrations, not actual human exposure . As noted

above, these concentrations were predicted to occur at or near the facility fenceline, where

continuous 24-hour human exposures are unlikely . The predicted maximum 24-hour

concentrations are also based on the worst-case dispersion meteorology occurring in the area

of the facility during any day over a 5 year period, and should therefore be viewed as being

conservative.

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5.0 EVALUAT10N OF LESSER MEK SOURCES

The second part of this study was designed to estimate maximum airborne concentrations in the

vicinity of lesser MEK emitting facilities . Because of the large number of facilities reporting more

than 10 ton/yr MEK emissions on the TRI (over 2300), it is not feasible to conduct facility-specific

modeling for even a significant portion of them . ENSR therefore applied a generalized approach

for estimating maximum off-site concentrations from lesser emitting facilities . As noted above in

Section 2 .2, this generalized approach was also used to estimate maximum annual off-site

concentrations for top-emitting facilities for which site-specified information was not obtained .

5.1 Generalized Modeling Approac h

ENSR developed a generalized approach for estimating maximum off-site concentrations from

smaller facilities with between 10 and 200 tons/yr of MEK emissions according to TRI data. First,

the TRI database was used to sort all facilities that reported more than 10 tons of MEK emissions

on the 1994 TRI into source categories based on their two-digit SIC codes. SIC codes for which

Tier 1, 2, or 3 modeling had already been performed were not considered . A generalized

dispersion modeling approach was then used to conservatively estimate the maximum annual

average concentrations in the vicinity of sources in each category. The annual MEK emissions

for the two facilities with the highest and second-highest emissions in each of the identified SIC

codes were used in the assessment.

The U .S . EPA dispersion modeling approach used in support of the proposed 11 2(g) rulemaking

was used in this categorical assessment (EPA, 1993) . EPA conducted dispersion modeling using

the Human Exposure Model (HEM) to estimate maximum annual concentrations as a function of

distance and source height. EPA's modeling assessment conservatively used the following

assumptions:

all facility emissions emanate from a single point source,

negligible exit velocity (10 cm/sec) ,

emitted at ambient temperature ,

source subject to worst-case aerodynamic building downwash .

HEM uses climatological data in the form of a joint frequency distribution of wind speed, wind

direction and atmospheric stability. EPA applied HEM using 314 separate climatological data sets

based on NWS stations located throughout the United States and a single stack heighttreceptor

distance combination (10 m stack, 200 m receptor) . Annual concentrations associated with a 1 0

RAPUBMPROJECTS\1 410016\1WALL 5-1 November, 1996
p. 55

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ton/yr release varied widely among the 314 data sets with the highest annual concentration (15.6

ug/m') being a factor of 3.1 greater than the median concentration (5 .0 Ug/M3). EPA then

conducted an additional sensitivity analysis, using the median dispersion climatology, to determine

how modeled annual concentrations would vary depending upon different combinations of source

height and receptor distance. The results of this sensitivity analysis are summarized in Table 4

of the EPA document and provided in Appendix B (EPA, 1993) .

For the MEK study, an upper limit concentration has been estimated for various combinations of

stack height, and receptor distance by multiplying the EPA Table 4 dispersion coefficients by a

factor of 3.1 . This approximates the highest annual average concentration that would occur at

the location (in the United States) that has the worst dispersion climatology .

This conservative method was used to estimate concentrations at nearby receptors for "model"

facilities representing the largest emitters in each of the SIC codes. To simplify the analysis, a

model facility (defined in terms of stack height and receptor distance) has been defined for the

following three "Dispersion Categories" to which each of the SIC codes is assigned.

Heavy: Major facilities typically located in highly industrialized areas with substantial building

dimensions on relatively large sites (stack height = 15 m, receptor = 200 m)

Medium: Moderate size facilities typically located in industrially or commercially zoned areas on

medium-sized properties (stack height = 10 m, receptor = 150 m)

Light: Smaller typically one-story facilities with roof vents and limited site acreage located in

mixed use areas (stack height = 5 m, receptor = 100 m)

EPA Table 4 dispersion factors (Appendix B) were estimated for each category (using linear

interpolation where necessary) and then multiplied by a factor of 3.1 to adjust for worst-case

dispersion climatology. This resulted in the following dispersion factors for each category, in units

of mg/m3 per million pounds of MEK emissions :

Light: 4.1

Medium: 0.91

Heavy:- 0.39

5.2 Estimated Receptor Concentrations

Table 5-1 provides the applicable SIC codes, representative dispersion category, and

corresponding dispersion factor. These dispersion factors were then multiplied by the emission

RAPUMPROJECTS\1410016\100ALL 5-2 November, 1996
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rates of the highest and second-highest MEK emitting facilities in each SIC code. As indicated

on Table 5-1, the resultant concentration estimates are all below 1 mg/M3 and well below 1 mg/M3

in most cases .

The Tier 3 results for the top emitters indicate that maximum 24-hour concentrations are a factor

of 4 to 14 times greater than the annual concentrations . If the upper limit annual to 24-hour

averaging time adjustment factor of 14 is applied, the highest estimated 24-hour concentration

among the SIC code is about 7 Mg/M3, well below the 30 mg1m' benchmark.

To verify the validity of this generalized approach, it has also been applied to the SIC codes of

the top emitters, for which refined modelling was already conducted . The facility with the

maximum emissions represented each SIC code and was modeled using the generalized

methodology and the results were then compared with the maximum refined modeled

concentration (both Tier 3 and adjusted Tier 2, as illustrated in Figure 4-1) among the sources

belonging to that SIC. The results are shown on Table 5-2-. For all SIC codes, the generalized

approach predicted higher concentrations than the refined assessment, thus demonstrating that

the generalized approach is conservative .

Generalized modeling results for several top MEK emitters provided in Table 4-2 also indicate

annual concentrations well below 1 Mg/M3. Given the demonstrated conservatism of the

generalized approach, actual off-site impacts are likely to be substantially lower.

Note that Table 5-2 shows the maximum annual emissions for the top-emitting facility in each

SIC code, along with the genedc annual off-site concentration estimate for that facility . However,

the column labeled "Maximum Refined Concentration (MgIM3) in SIC Codeu is not necessarily the

refined modeling result for the same facility . Rather, it represents the highest annual off-site

concentration modeled among all facilities in that SIC code, which may or may not correspond

to the facility with the highest annual emissions. As noted above, the facilities provided sitespecific data for modeling based on conditions of confidentiality, and this approach was necessary

to preserve the confidentiality of the refined modeling results .

RAPUMPROJECTS\141001WOOALL 5-4 November, 1996 ~
p. 58

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p. 59

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6.0 COMBINED IMPACTS

The dispersion analyses of both the top-emitting facilities and smaller sources have demonstrated

that maximum off-site concentrations at potentially exposed receptor locations are less than about

30% of the annual and 24-hour benchmarks (3.3 Mg/M3 for annual and 33 mg/M3 for 24-hour).

As such, there are no combinations of sources (unless three or more sources are virtually colocated) that could result in receptor concentrations exceeding the health protective benchmarks .

Hypothetically, for sources to contribute to off-site receptor concentrations above the RfC, at least

3 major MEK emitters would need to be side-by-side with a receptor located between them . As

can be noted from Table 2-2, none of the top MEK emitting facilities are located in the same

geographic area.

Although the modeling analysis indicates that combined impacts are highly improbable, an

investigation was made to identify clusters of MEK sources to review the potential for combined

impacts. As a first step, the 1994 TRI database was used to identify all MEK sources reporting

more than 10 tons of MEK emissions in 1994 . Of the 800 facilities identified, 709 facilities were

the only MEK source within the (5 digit) zip code area. The other 91 facilities are distributed fairly

evenly among 37 zip code areas. Of these areas, 34 had total annual MEK emissions of less

than 200 tons. One zip code contained as many as 5 facilities, but with combined annual

emissions of only about 100 tons. Refined dispersion modeling for top MEK emitters has

demonstrated that single facilities emitting 200 tons per year or more result in ambient annual

concentrations of less than 1 MgIM3

. For the 34 zip code areas, even if all the facilities in the

area were co-located, refined modeling suggests that off-site concentrations are highly unlikely

to exceed 1 .0 mg/m3.

One of the remaining 3 zip code areas had one facility among the top 26 emitters of MEK

(modeling indicated concentrations in the vicinity are well below benchmark concentrations) and

another facility emitting less than 15 tons per year. Because the smaller source represents only

about 5% of the total emissions in the area, concentrations would not increase appreciably even

if the 2 sources were co-located .

The remaining 2 zip code areas that had multiple sources collectively emitting more than 200 tons

were examined according to the following distance criterion. The modeling analyses of the top

emitting MEK sources were reviewed to determine the maximum separation distance for two

sources to potentially have a combined impact greater than 1 .0 mglm3. This distance was

conservatively estimated by doubling the maximum modeled distance corresponding to an annual

concentration of 0

.5 Mg/M3

. Refined modeling indicates that airborne concentrations fall off

RAP UBSPROJECTS\1 4 100 1 MIWALL 6-1 November, 1996

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p. 60

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rapidly with distance . Among the 7 top emitting facilities for which Tier 3 modeling was

conducted, annual concentrations exceeded this value out to a maximum distance of 175 m

(about one tenth of a mile) beyond the facility fenceline . Therefore, a receptor would have to be

located between two large MEK emitting facilities, located 350 m (about two tenths of a mile)

apart if there is to be a possibility of annual concentrations greater than 1 .0 mg/M3.

The 2 zip code areas evaluated with this criterion each contain two principal sources . Refined

modeling has indicated that 2 major sources separated by more than 350 m would avoid

significant overlapping impacts. The distance between sources within these 2 zip code areas

exceeded this distance. Therefore, it is concluded that combined impacts from multiple sources

of MEK will not result in ambient levels greater than either 1 .0 mg/M3 (annual average) or 10 Mg/M3 (24-hour average).

R :\PUESPROJECrS\1410016\100ALL 6-2 November, 1996
p. 61

7.0 CONCLUSIONS

A dispersion modeling analysis was conducted to evaluate maximum off-site concentrations of

MEK in the vicinity of both large and small sources of MEK emissions . Site specific modeling was

performed for 20 of the 26 facilities that reported MEK emissions of 400,000 pounds or more in

1994. The remaining 6 facilities were modeled using a generalized air dispersion modeling

approach used by EPA in its CAA Section 112(g) rulemaking.

The same generalized approach was used to estimate maximum off-site concentrations that result

from MEK emissions from smaller sources . For this analysis, all facilities that reported more than

10 tons of MEK emissions on the 1994 TRI were divided into source categodes based on their

two-digit SIC codes. Parameters were developed for each SIC code and the generalized

approach was then used to predict likely maximum airbome concentrations based on the

emissions rates for the highest and second-highest emitting facilities in each SIC code.

In evaluating this study, it is important to recognize that the modeling results are intended to

represent maximum off-site concentrations (averaged over one year or 24 hours) and are not

intended to represent actual human exposures . For each of the top-emitting facilities, the location

of the maximum modeled concentration was at or near the facility fenceline, where there are

unlikely to be continuous exposures for more than a few hours a day . On the other hand, the

health benchmarks used in this study are designed to be protective for continuous exposures .

In addition, the modeling itself (even Tier 3 analysis) incorporates certain assumptions that are

relatively conservative . Actual off-site concentrations are likely to be lower than maximum

modeled concentrations, and actual exposures are likely to be much lower.

The modeling study demonstr*ates that (1) maximum annual off-site concentrations of MEK are

expected to be less than 1 MgIM3 in all cases, and well below 1/Mg/M3 in most cases; and

(2) maximum 24-hour off-site concentrations of MEK are expected to be less than 10 Mg/M3 in

all cases, and well below 10/Mg/M3 in most cases. The one exception is a major emitter for

which the maximum annual off-site concentration was 1 .18 Mg/M3 and the maximum 24-hour

concentration was 12.82 Mg/M3

. At this facility, however, there were no receptors near the point

of the highest predicted concentrations .

Finally, there is no group of MEK emitting facilities that collectively would result in maximum offsite concentrations greater than 1 MgIM3 (annual average) or 10 gIM3 (24-hour average).

RAPUMPROJECTS\14100M100ALL 7-1 November, 1996
p. 62

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REFERENCES

EPA, 1992. A Tiered Modeling Approach for Assessing the Risks Due to Sources of Hazardous

Air Pollutants . EPA-450/4-92-001 . U.S. Environmental Protection Agency, Research Tringale

Park, NC.

EPA 1992a. Screening Procedures for Estimating the Air Quality Impact of Stationary Sources,

(Revised . EPA 454/R-92-019. U.S. Environmental Protection Agency, Research Triangle

Park, NC.

EPA, 1993. Documentation for DeMinimis Emission Rates for Proposed 40 CFR Part 63, Subpart

B (EPA-453/R-93-035) .

EPA, 1995. Guideline on Air Quality Models (Revised) . EPA-450/2-78-027R, including

Supplements A, B and C. U .S. Environmental Protection Agency, Research Triangle Park,

NC.

RAPUBMPROJECTSM 4100 16\100ALL November, 1996
p. 63

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APPENDIX A

DATA REQUEST FORMS

RAPUMPR0JECTS\1410016'%100.CVS NoveMber,1996
p. 64

CHEMICAL MANUFACTURERS ASSOCIATIO N

KETONE PANEL

Data Request for Air Quality Modeling

Your Name and rdJe:

Your Company's Name:

Your Voice Phone Number -Your FAX Number

Please complete Parts 1, 11, and III for your facility .

Pan I - Gworall Faaffity kftrmanon

Please provide the following information for your facility:

1 . Aplot plan of the facility showing the property boundary, fenceline, source

locations (by source names), building locations, and building heights (Hb) above

ground level. Include significant storage tank locations and heights .

hints . . . . .

* Multiple tiered buildings, Hb = height above ground of each tier

* Peaked roof, Hb = ground to the highest point of the roof

* Outdoor process equipment -

• May disturb the wind like a building

• ApproArnate the area of this equipment on the plot plan

• Hb = height that would represent about 90% of the process

equipment area.

2. A U.S.G.S. topographic map of the area, showing the location of the facility,

or

UTM coordinates or latitude and longitude, and average ground-level elevation .

Pan 11 - Poiffl Soume hdornudon

Please complete Table 1 for your facility.

Large number of (nearly) identical sources? List one representative source

plui a footnote indicafing the number of such sources and their identification

numbers which cross-reference their location on the plot plan .

Only know the total emissions for a group of sources? Do they have very

similar release characteristics? If yes, list a representative source, number of

sources, and identification for the plot plan.

Part 1111111 - Fugifte EnftWons llmmmtory

Please complete Table 2 for the sources of fugitive emissions at your facility .
p. 65

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APPENDIX B

TABLE 4 OF THE 11 2(g) PROPOSED

RULEMAKING SUPPORT DOCUMEN T

RAPUBSPROJECTS141001alGO.OVS November,19%
p. 68

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Table 4 . Sensitivity of ambient fence-line concentration to

stack height and fence-line distance for the "Model" Plant

Stack height Distance to nearest Median

(meters) residence (meters) concentration

(,Lg/M3)

200 16

3JC 100 S1

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is 200 2 .5

so 200 0 .1s

100 200 0 .026

These parameters are assumed in the model plant used t o

calculate ami sion rates for the proposed rule

Note: The model plant has :

Emission Rate = 10 tons per year,

Stack Hieght = 10 meters;

Stack Diameter = 1 meter;

Exit Velocity = 0.1 meters / second;

Stack Temperature = 295 Kelvin (ambient)

Distance to Nearest exposed individual = 200 meters ;

Worst case down-wash.
p. 69

APPENDIX D

MEK EMISSIONS BY ZIP CODE
p. 70

MEK EMISSIONS BY ZIP CODE

For the year 1994, there were 800 facilities that reported MEK releases to air of 20,000

pounds (10 tons) or more, including both point and non-point emissions . Of this number, 709 facilities

were located in ZIP codes in which there was no other facility reporting MEK emissions greater than

20,000 pounds during the year.

The following chart shows the remaining 91 facilities. It is organized to show the MEK

emissions by ZIP code for each ZIP code in which there were multiple facilities reporting MEK emissions

greater than 20,000 pounds in 1994 . All data is from the 1994 Toxics Release Inventory .

LOCATION BY ZIP CODE FACILITY NAME TOTAL AIR RELEASE

07095 Gentek Building Prods . 26,627

Middlesex, NJ Russell-Stanley Corp . 36,623

Total Air Release for Zip Code : 63,250

17402 York Casket Co. 28,700

York, PA Harley-Davidson Motor Co. 20,250

Total Air Release for Zip Code : 48,950

17847 Milton, PA ACF Ind. Inc . 28,740

Northumberland, PA Resilite Sports Prods . Inc . 648,757

Total Air Release For Zip Code: 677,497

19154 Allied Lube & Conduit Corp. 130,185

Philadelphia, PA Kurz-Hastings, Inc. 376,000

Total Air Release For Zip Code: 506,185

24012 Tread Corp. 25,200

Roanoke, VA Singer Furn. Co. Roan Plant 21,375

Total Air Release For Zip Code: 46,575

24055 JD Bassett Mfg. Co. 25,503

Bassett, VA Bassett Superior Lines 92,862

Bassett Table Co. 57,739

Bassett Mirror Co. Philpott Plant 24,050

Total Air Release For Zip Code: 200,154

24112 American Furniture Co. Inc . 50,852

Martinsville, VA W.M. Bassett Furniture Co . 34,757

Total Air Release For Zip Code: 85,609
p. 71

Atkins, VA Virginia House Furniture Corp

24311 Merillat Ind. Inc . 40,104

. Plant 1 25,300

Virginia House Furniture Corp . Plant 2 26,300

Total Air Release For Zip Code : 91,704

24333 EC Dodson Plant 36,463

Galax, VA TG Vaughn Plant 50,220

BC Vaughn Plant 34,238

Vaughn-Bassett Furniture Co . 67,467

Webb Furn . Ents. Inc. Plant1 22,800

Total Air Release For Zip Code : 211,188

24354 Marley Mouldings Inc. 39,755

Marion, VA Marion Composites 71,950

Total Air Release For Zip Code : 111,705

27261 Lilly Ind. Inc. 27,720

HighPoint, NC Marsh Furniture Co . 37,052

AKZO Nobel Coatings, Inc . 23,957

Total Air Release For Zip Code : 88,729

27292 TI Industries 117,542

Lexington, NC Lexington Furniture Ind . Plant 4&5 22,900

Lexington Furniture Ind. Plant 7 57,664

Lexington Furniture Ind . Plant 12 33-834

Total Air Release For Zip Code: 174,276

28043 Crellin Inc. 50,000

Forest City, NC AGInd

Total Air Release For Zip Code

. Inc. 44,250

: 94,250

28139 Broyhill Furniture Ind . Inc . 50,816

Rutherfordton, NC Reeves Intl . Grace Plant 30,135

Total Air Release For Zip Code : 109,090

Hickory,

28601

NC

Century Furn . Ind. Plant1 20,517

Hickory White Co . Casegoods Div. 31,246

Siecor Telecom. Cable Plant 42,365

Total Air Release For Zip Code: 94,128

28613 Decor Originals Inc. 25,062

Conover, NC Lackawanna Leather Co. 112,211

Total Air Release For Zip Code : 137,273
p. 72

28633 Broyhill Fum . Ind. Inc . Complex 195,801

Lenoir, NC Broyhill Fum . Inc. Inc . Lenoir 64,75 1

Total Air Release For Zip Code : 260,552

28645 P&xar Printed Label Group 179,264

Lenoir, NC Singer Furniture Co. 95,39 1

Thomasville Furniture Ind . 40,200

Broyhill Furniture Ind . Inc . Harper 55,402

Total Air Release For Zip Code: 370,257

28704 Crown Cork & Seal Co . Inc . 23,700

Arden, NC Day International 35,818

Phillips Consumer Electronics Co . 83,560

Total Air Release For Zip Code: 143,078

28777 Ethan Allen Inc. Spruce Pine Div. 20,436

Spruce Pine, NC Henredon Furniture Ind . Inc . 32,897

Total Air Release For Zip Code: 53,333

29150

Sumter, SC Vaugh-BassettfWilliams Fum

Kom Ind. Inc . 136,004

. Co. Inc. 28,169

Total Air Release For Zip Code : 164,173

29202 Kline Iron & Steel Co. Inc . 26,000

Columbia, SC Consolidated Systems Inc . 41,100

Total Air Release For Zip Code: 67,100

29605 Lockheed Aeromond Centers Inc. 26,750

Greenville, SC Crown Metro Inc. 20,455

Total Air Release For Zip Code: 47,205

31709 Woodgrain Millwork Inc. 378,865

Americus, GA Textron Automobile Exteriors 489,189

Total Air Release For Zip Code: 868,054

37303 P-1 Inc. 31,700

Athens, TN Athens Furniture Ind. Inc . Bed Plant 20,660

Textron Automobile Interiors 126,400

Total Air Release For Zip Code: 178,760

37814 Lea Ind. Plant #4 23,333

Morristown, TN Universal Bedroom Furniture Ltd. 53,850 Camelot, TN Rexam Metallising; 95,441

Pollyfibron Techs . Inc . 29,500

Total Air Release For Zip Code: 202,124
p. 73

Lawrenceburg,

38464, Ripley, TN

TN

Tennessee Electroplating Inc. 34,906

Murray Ohio Mfg. Co. 25,600

Total Air Release For Zip Code : 60,506

44805 National Latex Prods Co. 33,331

Ashland, OH Hedstrorn Prods Co. 112,112

Total Air Release For Zip Code: 145,443

46041 Crellin Inc

Frankfbrt~ IN Federal Mogul Corp

. 90,343

. 36,950

Total Air Release For Zip Code: 127,293

47201 Arvin Ind

Columbus, IN

. Inc . NAA Div. 17th St. 47,400

Toyota Indl. Equipment Mfg. Inc. 26,685

Total Air Release For Zip Code: 74,085

47546 Aristokraft Inc. Plant 2 22,250 Jasper, IN Aristokraft Plant3 20,250

Total Air Release For Zip Code: 42,500

49508, Grand Rapids, MI Steelcase Inc. 97,408

Kentwood, MI Steelcase Inc . 226,670

Total Air Release For Zip Code: 324,078

49512 Lacks Ind. Inc. Raleigh Plant 110,550

Kentwood, MI Plastics Plate Inc. Plant 2 61,100

Total Air Release For Zip Code: 171,650

60007 Clear Lam Packaging 25,162 Elk Grove village, iL Pre-Finish Metals Inc . 69,165

Pre Finish Metals Inc . 22039

Total Air Release For Zip Code: 116,366

70058

Harvey, LA

Sigma Coatings

Evans Contianer Corp

USA B

.

.V. 28,024

35,986

Total Air Release For Zip Code: 64,010

70805 Exxon Co. USA Baton Rouge Refg. 152,800 Baton Rouge, LA Exxon Chemical Baton Rouge Chemical 34,72 4

Total Air Release For Zip Code: 187,524

98055 Kenworth Truck Co . 26,200

Renton, WA Boeing Commercial Airplane Group 167,000

Total Air Release For Zip Code: 193,200
p. 74

APPENDIX F

TABLE OF AMBIENT AIR CONCENTRATION LEVELS OF MEK

(TAKEN FROM A STUDY CONDUCTED BY THE NEW JERSEY DEPARTMENT OF

ENVIRONMENTAL PROTECTION IN 1978)
p. 75

TABLE OF AMBIENT AIR CONCENTRATION LEVELS OF MEK

(TAKEN FROM A STUDY CONDUCTED

BY THE STATE OF NEW JERSEY

DEPARTMENT OF ENVIRONMENTAL PROTECTION

IN 1978)
p. 76

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APPENDIX F

HOUSTON REGIONAL MONITORING REPORT (EXCERPTS)
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APPENDIX G

NORTH BATON ROUGE VOLATILE ORGANIC SCREENING STUDY
p. 88

RADIAN

C 0 R P 0 R A T 1 0 H

DCN 88-203-085-0 2

RCN 203-085-DS-00

RESULTS OF A VOLATILE

ORGANIC SCREENING STUDY CONDUCTED

IN THE VICINITY OF THE

NORTH BATON ROUGE INDUSTRIAL COMPLEX

DRAFT FINAL REPORT

Submitted to :

Mr . Gordon B . Jolley

Environmental Coordinator

Exxon Chemical Americas

Baton Rouge Chemical Plant

P .O . Box 241

Baton Rouge, Louisiana 70821-0241

Prepared by :

Radian Corporation

8501 Mo-Pac Boulevard

P .O . Box 201088

Austin, Texas 7872D-1088

15 April 1988

8501 Mo-Pac Blvd ./PO. Box 201088/Austin, TX 78720-1088/(512) 45"797
p. 89

!MIAATIONN

2 .0 EXECUTIVE SMOLM

This report describes the results of an ambient screening study

which was conducted for Exxon Chemical Americas by Radian Corporation . The

study was conducted in the immediate vicinity of the Baton Rouge industrial

complex and van aimed at measuring ambient concentrations of selecte d

volatile organic compounds which are representative of emissions from both

industrial stationary and area sources . The measurem t program was

designed to gather simultaneous screening measurements for a list of 175

volatile organics Me) at four sites selected by Exxon Chemical Americas .

The sites were ropz~esentative of the following types of locations :

1 . Rural non-industrial .-

2 . An urban residential area situated near major transportation

arteries ;

3 . Urban industrial ; and

4 . Rural industrial .

The location of each of the four sampling sites are shown in

Figure 2-1 . Site 1 was a rural non-industrial site located 26 miles east of

the Baton Rouge industrial complex near the town of Livingston . Louisiana .

Site 2 was located in an urban area near tb* intersoction of Highway 61 and

Siegen Lane. This site. which was located 10 miles southeast of the Baton

Rouge industrial complex, was -dcainated by mobile source emissions due to

ite proximity to a major traffic intersection in Baton Rouge . Site 3 was

situated in an urban industrial area adjacent to the North Baton Rouge

refining and petrochemical complex . This site was situated approximately 1

mile east of the Exxon Chemical Americas plant on Evangeline Road . Site 4

was situated in a rural industrial setting in the town of Zachary .

2-1
P. 90

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2-2
P. 91

Louisiana . This site was located 5 miles north of the Exxon Chemical Co .

plastics plant .

Simultaneous 24-hour integrated whole air samples were collected

at each of the four site locations on three,consecutive sampling days

beginning 6 March 1988 and extending through 9 March 1988 . The samples were

collected in evacuated stainless steel canisters . and analyzed using a

multidetector San chromatography system . The first sampling period was

performed on a weekend (a Sunday) to gather samples during periods of low

vehicular traffic . The remainder of the samples were collected during

periods of normal weekday vehicular traffic . This sampling strategy vas

devised in an attempt to discriminate between impacts from stationary and

mobile sources .

The meteorology during the measurement program van characterized

by light winds which were predominately from a southeasterly direction. The

first sampling period which began at 6 :00 AM on the morning of 6 March 1988

was typified by light persistent westerly winds which gradually shifted

through north and stabilized as a southeasterly breeze in the early morning

of hours oi 7 March. The winds were generally light and persistent from the

southeast on 7-8 March ; gradually shifting to the northwest during the late

evening hours of 8 March. These conditions prevailed until sampling was

term.ziated on the morning of 9 March 1988.

Based on the meteorology which existed during the measurement

program. the urban and rural industrial sites (3 and 4) were positioned

downwind of industrial sources for brief periods during the first and third

sampling days. Sit* 2 (urban-rtsidential) which was situated near a major

traffic interxection. was exposed to missions from mobile sources an each

of the three sampling days . It should also be noted that light to moderate

precipitation began at about noon of the second sampling day. and continued

through the end of the third sampling day. The presence of precipitation

any have influenced the concentration of volatile organics MOO which were

present in the ambient environment at each site location.

2-3
p. 92

GOUPORAVIO IANN

Table 2-1 represents the list of compounds which were detected at

least once at each site during the screening study . The table shows the

concentration range . mean concentration. and frequency of observation for

each compound detected . These data can be used to make inferences about the

ambient levels of VO which were observed during the screening study (6-9

March 1988) . Figures 2-2 through 2-7 provide a graphic comparison of the

concentration levels which were observed at each site location for ethylene

and acetylene . ethane* propane, benzene . toluene, and total non-methane

hydrocarbons (TNMHC) . The following general observations can be made with

regard to the VO screening data :

• The concentration of TNMHC observed at each site during the

study was generally low. The TNMHC values ranged from 78 .8

to 239 .4 ppb-v .

• The urban sampling sites were characterized by TNMHC values

which were only slightly higher than that which was observed

at the rural sampling sites . This is not surprising given

the meteorological conditions which prevailed during the

screening study .

• Ethane, ethylene and acetylene . propane. toluene. and nheptane were present in at least 90% of all samples

collected .

• As expected. there were a number of compounds which were

generally present in higher concentrations at the urbanresidential . and urban industrial sites as compared to the

more isolated rural sites . These included benzene .'ethylene

and acetylene . toluene and ethane. These trends would be

expected given the proximity to and number of stationary and

mobile sources in the urban areas .

2-4
p. 93

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2-13
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• ThOre were fifteen (15) compounds which were deitected at the

urban and urban industrial site locations which were not

present at detectable concentrations at the rural locations .

Most notable were c-2-pentene . ethylbenzene . and 2-motbyl-2-

butene .

• The imajority of compounds which were identified were present

at concentrations of 5 ppb-v or less . Ethane . propane, nbutane . isopentane . and trichlorofluoromethane were observed

in some samples at concentrations greater than 20 ppb-v .

• Precipitation during the sampling program may have been

responsible for suppressing the VO concentration in the

ambient environment . In general . the TNMHC levels were lower

on days in which precipitation was measured .

• Given the limited number of samples collected and the

meteorology which ezisted during the screening program, it is

uncertain if the data collected are representative of the

highest concentrations of VOt which could be present in the

ambient air. The data. however are representative of short

duration screening measurements observed at each site under

similar sampling conditions .

• During the data validation process, it was discovered that

acetaldebyd*. acetone. metbylene chloride. and 3-methyl

hoptane were present in the field blanks . Measurement values

for these compounds were at levels which would normally not

be ezp*cted in the ambient air . For this reason. these data

were ezcludod from the summary presentation .

During the sampling program . two samplers failed to operate for

the entire 24-hour smpling period . This included a sample collected at

Site I an 6 March. and at Site 4 on the evening of 7 March. In the case of

2-14
P. 99

the sample collected at Site 1 . it was discovered that both the designate d

field and duplicate canisters had been tampered with and the valve on each

canister was turned off approximately midway through the sampling period .

The duplicate sample was repeated during the next sampling period . In the

second cast. sample flow ceastd as a result of excessive moistur e

accumulation in the vacuum flow delivery system during a time when moderate

rainfall was occurring . In both instances . the samplers operated for

periods of approximately 12 hours . It is difficult to assess if the aborted

samples are representative of samples collected over a full 24-hour sampling

period. Because the samples were collected in isolated areas . it could be

argued that the concentration of VOs in the ambient air would be relatively

constant over a 24-hour period . The data do provide useful information

concerning the composition of volatile organic compounds which were observed

at there sites . However. care should be exercised in interpreting there

data.

The ambient VO measurements made during this study provide a

"quick screen look" at the distribution of volatile organics in the Baton

Rouge industrial corridor over a limited time framt . These data are useful

in contrasting the composition and relative concentrations of volatile

organics which are present in urban/industrial settings to those found in

rural and rural industrial settings . As previously stated, the measurement

data presented in this report may not be representative of the highest

concentration values which would be expected to occur under different

meteorological scenarios . Therefor*, care should be taken in applying broad

interpretations to this limited database . These data, however, do provide

an indication of the general air quality which was observed at each

measurement site under the conditions which prevailed during the measurement

program. Additional data . however. are needed to accurately assess

community exposure to a variety of volatile indicator compounds which are

representative of missions from petroleum refining . petrochemical

production. and mobile sources in the North Baton Rouge industrial complex .

2-15
P. 100

APPENDIX H

IRIS DATABASE ENTRY FOR MEK