P.1 

OAR Box 1252 

Prepped by Candice Davis 

Document Number: 

50) ll-B-10 

Docket Number: 

A-90-22 

Printed 5/21/2008 11:46:01 AM Sheet 50 of 184 
P.2 

A=S©= 

DH-i-1© 

MEMORANDUM 

Date: 

To: 

From: 

E iiu j 

Ul 

P— 

October 7, 1991 

David Markwordt, EPA/CPB 

I $ EPA AIR DOCKET David Ocamb and Thomas R. Olsen, RadiianF m M m u ^^^—--

Subject: Revised HON Transfer Model Loading Racks Development 

The purpose of this memorandum is to document the 

development of the model racks for HON transfer and to describe 

the methodology for generating loading rack vent stream 

characteristics. Model loading racks were developed to 

facilitate the control impacts analysis for HON Transfer. Model 

loading racks were developed for tank trucks and tank cars. 

Emission estimates were calculated based on the loading rack vent 

stream characteristics. Emission reductions, costs, increased 

energy usage, and other environmental impacts were calculated 

based on a control device which would achieve a 98 percent 

reduction in HAP emissions for each rack. The development of the 

model racks and model assignment procedures are presented in 

Section 1.0 and the approach for generating loading rack vent 

stream characteristics presented in Section 2.0 

1.0 MODEL LOADING RACK DEVELOPMENT 

Section 114 questionnaires were sent to nine corporations 

requesting data on the loading practices for HAP's or HAP 

1-18 

mixtures. The collected data was compiled and analyzed to 

develop model loading racks for tank trucks and tank cars. The 

model racks resulting from this analysis were judged by the EPA 

to be representative of the range of practices commonly employed 

within the synthetic organic chemical manufacturing industry 

(SOCMI). Due to the fact that the majority of the Section 114 

data is classified as business confidential, the site-specific 

information on transfer operations is not presented in this 

memorandum. 

lrtoetno / htmO 1 (Is) 
P.3 

The Section 114 questionnaire responses were reviewed to 

develop a relationship between rack size (number of loading arms) 

and two quantifiable loading parameters: the number of materials 

loaded and the total volume of material loaded. The model rack 

development is discussed in Section 1.1. Section 1.2 presents 

the development of the throughput allocation factors. Section 

1.3 presents the discussion on model loading rack assignment. 

1.1 NUMBER AND VOLUME OF MATERIALS LOADED 

Model loading racks were developed by first reviewing the 

rack size dependency on the number of materials loaded and then 

developing volumetric throughput constraints to correspond to 

actual transfer rack operations. An average throughput was 

developed for each rack size within each range of number of 

materials transferred. Table 1-1 presents the model loading 

racks for tank car loading operations and Table 1-2 presents the 

model racks for tank truck loading operations. 

In order to determine the validity of the model tank truck 

and tank car loading racks, the models were applied to the 

transfer data base to compare the predicted number of racks and 

loading arms to the reported number of racks and loading arms. 

The final models are presented for each rack size in Table 1-1 

and Table 1-2. Overall, the final models prediction for the 

number of arms reported in the Section 114 responses is high by 

approximately 20 percent and the number of individual racks is 

low by 10 percent. Specifically, the number of model racks 

predicted was slightly low for facilities producing a large 

number of materials but with a small total material throughput. 

In addition, for facilities producing a small number of materials 

with extremely large total material throughput, the number of 

predicted racks was slightly larger than the number of racks 

reported. However, for the SOCMI as a whole, the number of 

lnneoo/htaOHls) 
P.4 

TABLE 1-1. HON TRANSFER RAILCAR MODEL 

Number of 

Chemicals Throughput (TP) Range 

Loaded (IO6 gal/yr) 

1 to 3 0 < TP < 10 

10 < TP < 40 

40 < TP < 80a 

4 to 9 0 < TP < 10 

10 < TP < 20 

20 < TP < 30 

30 < TP < 60b 

10 to 22 0 < TP < 3 

3 < TP < 80c 

> 23 0 < TP < 10 

10 < TP < 20d 

aFor throughputs above the maximum value, add 

3-arm rack per 10 x IO6 gal. 

^For throughputs above the maximum value, add 

3-arm rack per 10 x IO6 gal. 

cFor throughputs above the maximum value, add 

3-arm rack per 3 x IO6 gal. 

dFor throughputs above the maximum value, add 

4-arm rack per 10 x IO6 gal. 

Lrmemo/htmOHls) 3 

LOADING RACKS 

Number 

of Arms 

3 

8 

16 

3 

6 

10 

16 

3 

10 

4 

9 

an additional 

an additional 

an additional 

an additional 
P.5 

aFor 

rack 

TABLE 1-2. 

Number of 

Chemicals 

Loaded 

1 to 4 

5 to 12 

13 to 20 

> 21 

throughputs 

per 3 x IO6 

bFor throughputs 

1-arm rack per 3 

cFor 

rack 

dpor 

rack 

throughputs 

per 15 x 10( 

throughputs 

per 12 x 10* 

lrmemo/htmO1(Is) 

HON TRANSFER TANK 

above 

gal. 

Throughput 

(IO6 ga 

the 

TRUCK MODEL LOADING RACKS 

(TP) Range 

il/yr) 

0 < TP < 3 

3 < TP 

12 < TP 

0 < TP 

< 12 

< 70a 

< 3.5 

3.5 < TP < 7.5 

7.5 < TP < 21 

21 < TP 

0 < TP 

0 < TP 

12 < TP 

maximum 

above the maximum 

.5 x IO6 gal. 

above 

5 gal. 

above 

5 gal*. 

the 

the 

maximum 

maximum 

4 

< 54b 

< 30c 

< 12 

< 24d 

value, 

value, 

value, 

value, 

add 

add 

add 

add 

an 

an 

an 

an 

Number 

of Arms 

1 

2 

4 

1 

2 

4 

6 

2 

3 

4 

additional 1-

additional 

additional 1-

additional 3-

-arm 

-arm 

-arm 

i 

1 

1 
P.6 

predicted racks and loading arms from the models corresponds to a 

realistic representation of actual loading operations and 

practices. When both the predicted number of arms and racks are 

considered together, the number of emission points is within 

about 10 percent. Further improvement of the model racks would 

require extensive plant-specific data to be collected and 

incorporated into the loading rack models. Because the developed 

model transfer racks are considered representative, the 

collection of additional information on transfer racks was deemed 

unnecessary. The results of the comparison of model racks to 

actual information are presented in Attachment A. 

1.2 Throughput Allocation Factors 

Chemical manufacturing facilities were questioned about the 

loading practices for tank truck, tank car, and marine vessels in 

a Section 114 survey. Follow-up calls were made to each facility 

concerning the percentage of the total process unit production 

capacity for every process unit which is transferred by tank 

truck, tank car, and marine vessel. This information was used to 

develop the different throughput allocation factors. Marine 

vessel loadings are not included under the HON, but under a 

separate standard. The data collected for marine vessel loading 

operations was included in the model analysis only to accurately 

characterize the percent capacity transferred by tank car and 

tank truck loading operations. 

The development of allocation factors which were used to 

estimate emissions was performed by sorting the facilities into 

two groups: those facilities with marine loading and those 

facilities without marine loading. Facilities with marine 

loading include those facilities which are located in cities near 

a body of water such as a lake, river, or an ocean. For each 

facility within each group, the total quantity loaded by each 

process unit to each vehicle type was summed, and the total 

process unit production capacities were also summed. The 

fraction loaded by each vehicle was calculated by dividing the 

total quantity loaded by each vehicle by the total production 

lrmemo/htmOKls) 5 
P.7 

capacity. The overall allocation factors were then estimated by 

averaging the fraction loaded for each facility included in each 

group. Therefore, the quantity of material loaded by each 

vehicle type at a facility that is calculated using the 

allocation factors represents the average quantity loaded at each 

facility. Marine vessels are included in this part of the 

analogy, because the tank truck and tank car allocation factors 

for marine and nonmarine facilities are different. The quantity 

used captively on-site and the quantity transferred by pipeline 

were included in the total production capacity. 

As part of the HON Framework, two scenarios were developed 

to represent the type of transfer vehicles loaded. Scenario one 

represents facilities which load only tank trucks and tank cars. 

Scenario two represents facilities which load tank trucks, tank 

cars, and marine vessels. Table 1-3 presents the overall 

allocation factors for each scenario. Under Scenario one, the 

tank truck allocation factor is 2.78 percent and the tank car 

allocation factor is 4.22 percent. Under scenario two, the tank 

truck allocation is 4.28 percent, the railcar allocation factor 

is 9.76 percent, and the marine vessel allocation factor is 12.96 

percent. Marine chemicals loaded at marine facilities use marine 

allocation factors. All other chemicals use nonmarine allocation 

factors. This includes nonmarine chemicals transferred at marine 

facilities and all chemicals transferred at nonmarine facilities. 

A marine chemical is a chemical which is potentially transferred 

by marine vessels and a list of this type of chemical was 

developed by Midwest Research Institute for the EPA. 

The allocation factors for both tank cars and tank trucks at 

marine facilities are higher than the respective allocation 

factors at nonmarine facilities. Therefore, marine facilities 

transfer a higher percentage of the production capacity by tank 

cars and tank trucks than nonmarine facilities. Facilities which 

produce a large quantity or number of chemicals that require 

transportation are usually strategically located near a waterway 

allowing transportation by marine vessels as well as tank cars 

lrmemo/htmOlds) 6 
P.8 

and tank trucks. Therefore, these facilities will also typically 

transfer more by tank cars and tank trucks than facilities which 

are not located near a waterway. 

Table 1-3. HON Transfer Throughput Allocation Factors 

Scenario Tank Truck Tank Car Marine Vessel 

Onea 2.78 percent 4.22 percent N/A 

Tu° 4.28 percent 9.76 percent 12.96 percent 

aScenario one corresponds to facilities which load tank trucks 

and tank cars. 

bScenario two corresponds to facilities which load tank trucks, 

tank cars, and marine vessels. 

1.3 Model Loading Rack Assignment 

The transfer rack models are assigned based upon the total 

number of materials loaded at a facility and the total cumulative 

throughput for each vehicle type from all product processes. 

Once the number of materials loaded and the total throughput 

for tank trucks and tank cars is determined, the actual number of 

racks assigned for each vehicle type is determined. Incremental 

rack sizes for assignment to each range of number of materials 

are listed in Tables 1-1 and 1-2. When physically assigning the 

models, the initial rack is assigned based upon the largest rack 

possible for that number of materials and cumulative throughput. 

Next, if appropriate, additional racks are assigned based upon 

the throughput increment for each material range as shown on 

Table 1-1 and Table 1-2. 

2.0 LOADING RACK VENT STREAM CHARACTERISTICS DEVELOPMENT 

Stream characteristics are necessary for developing the cost 

impacts of controlling emissions from transfers operations. The 

stream characteristics required are volumetric flow rate, annual 

hours of operation, molecular weight, and heat content. 

lrmemo/htmO1(Is) 

um 
P.9 

2.1 Loading Rack Emission Rate 

The loading losses are estimated using the vent stream 

. . 20 . • . 

characteristics. The loading loses are multiplied by the 

total quantity loaded (in 1000 gallons) to calculate the 

uncontrolled emissions. The emission rates are estimated for 

each specific product process. 

2.2 Vent Stream Flow Rate 

The vent stream flow rate directed from the model loading 

rack to the control device is a function of the loading rate and 

the number of arms loading simultaneously. From the information 

gathered on transfer operations, the average filling rate per arm 

for each vehicle type was estimated to be used with all tank 

truck and tank car models. For tank truck racks, the average 

filling rate per arm was 170 gallons per minute. For tank car 

racks, the average filling rate per arm was 190 gallons per 

minute. For the purposes of this analysis, all available arms at 

a facility are assumed to be loading simultaneously at the 

average rate per arm. The loading rack vent stream flow rate was 

estimated by multiplying the average filling rate per arm times 

the number of arms: 

Flow rate=(average filling rate)x(number of arms) 

It was assumed that the volume of liquid pumped into the vehicle 

was equal to the volume of vapor displaced from the vehicle and 

there was no vapor expansion or contraction. 

2.3 Loading Rack Annual Operating Hours 

By applying the average filling rate for each rack type 

(tank truck or tank car), the annual hours the rack is in 

operation are estimated. The annual hours loading was generated 

by applying the filling rate to the total quantity of material 

ioaded for the model rack. 

lrmemo/htmO1(Is) 
P.10 

Operating hours=Total throughput (gallons) x 1 hour 

Average filling rate (gallons) 60 minutes 

(minute) 

The operating hours are necessary for estimating operating costs 

for the control device which reduces emissions from the loading 

operation. 

2.4 Vent Stream Molecular Weight 

To estimate control costs for combustion devices, an average 

HAP molecular weight is required. It was assumed that the rack 

molecular weight should represent a composite molecular weight of 

all HAP's loaded at the loading rack. For example, if a 1-arm 

tank truck model is assigned to a location which loads 4 

chemicals, the composite molecular weight will be calculated 

using the molecular weight of each chemical loaded. Using a 

composite molecular weight which considers all materials loaded 

provides a more representative molecular weight for cost 

estimation than using the molecular weight for a single chemical, 

even though the facility can only load 1 of the 4 chemicals at a 

time. It is assumed that the resulting cost is representative 

for all product processes loading at the location. 

2.5 Vent Stream Heat Content 

The composite heat content for the vent stream was estimated 

in the same manner as was used to estimate the stream composite 

molecular weight. The natural gas requirement for the combustion 

control devices is a function of the vent stream heat content. 

As with the cost dependency on the vent stream molecular weight, 

a composite heat content is used because the natural gas 

requirement should not be biased high or low by using the heat of 

combustion of a single material. 

lrmemo/htmO1(Is) 
3.0 References 

1. Memorandum from Baker, J. M. Borden Packaging and Industrial 

products, to Markwordt, D. OAQPS/ESD/CPB. April 6, 1990. 

Response to request for information for the Fayetteville, NC 

facility. 

2. Memorandum from Coleman, I. 0. Hoechst Celanese Corporation 

Chemical Group, to Farmer, J. R. OAQPS/ESD. April 6, 1990. 

Response to request for information for the Bay City, TX 

facilities' loading operations. 

3. Memorandum from Ziehler, A. M. PPG Industries, to J. R. 

Farmer, OAQPS/ESD, April 6, 1990, Response to request for 

information for the Barberton, OH facilities' loading 

operations. 

4. Memorandum from Piercy, W. E. Hoechst Celanese Corporation 

Polyester Film Division, to J. R. Farmer, OAQPS/ESD, April 

9, 1990, Response to request for information for the Greer, 

SC facility. 

5. Memorandum from Takacs, L. Occidental Chemical Corporation, 

to J. R. Farmer, OAQPS/ESD, April 9, 1990, Response to 

information request for the Belle, WV and Deer Park, TX 

facilities' loading operations. 

6. Memorandum from Berg, R. E. Borden Chemicals and Plastics, 

to J. R. Farmer, OAQPS/ESD, April 10, 1990, Response to 

information request for BCP ammonia barges and tankcars: 

methanol barges, tankcars, and trucks; formaldehyde tankcars 

and trucks; vinyl chloride tankcars; and UF85 tankcars and 

trucks. 

7. Memorandum from Armstrong, H. G. Borden Packaging and 

Industrial Products , to J. R. Farmer, OAQPS/ESD, April 10, 

1990, Response to request for information for the 

Louisville, KY facility. 

8. Memorandum from Wyche, J. E. PPG Industries, Inc., to J. R. 

Farmer, OAQPS/ESD, April 11, 1990, Response to request for 

information on loading operations at the Lake Charles, LA 

facility. 

9. Memorandum from Samelson, R. J. PPG Industries, Inc., to 

J. R. Farmer, OAQPS/ESD, April 11, 1990, Response to request 

for information on loading operations at the Natrium, WV 

facility. 

10. Memorandum from Newman, D. K. Vulcan Chemicals, to J. R. 

Farmer, OAQPS/ESD, April 17, 1990, Response to information 

lrmemo/htjnOKls) 1 0 

i mi mWMI mmmimmm»mmmmmmammmmmmmmmmMmmwmmmmam^Bmt^BammM\ui\i\iMiiiit MI 
request for the Wichita, KS and Geismar, LA facilities 

loading operations. 

11. Memorandum from Taranto, B. L. Exxon Chemicals, to J. R. 

Farmer, OAQPS/ESD, April 20, 1990, Response to request, for 

information for the Baton Rouge, LA chemical plant, plastic 

plant, and resins finishing plant, and the Baytown TX 

chemical plant. 

12. Memorandum from Salinas, F. L. Celanese Engineering 

Corporation Chemical Group, to J. R. Farmer, OAQPS/ESD, 

April 23, 1990, Response to request for information for the 

Bishop, TX facilities. 

13. Memorandum from Wood, R. G. Hoechst Celanese Corporation 

Chemical Group, to J. R. Farmer, OAQPS/ESD, April 25, 1990, 

Response to request for information for the Clear Lake plant 

in Houston, TX. 

14. Memorandum from Gray, W. T. Union Carbide Chemicals and 

Plastics Company, Inc., to J. R. Farmer, OAQPS/ESD, May 11, 

1990, Response to request for information for the Taft, LA 

facility. 

15. Memorandum from Mullins, J. A. Shell Oil Company, to J. R. 

Farmer, OAQPS/ESD, June 6, 1990, Response to information 

request for the Deer Park, TX and Norco, LA facilities. 

16. Memorandum from Arnold, S. L. Dow Chemical USA, to J. R. 

Farmer, OAQPS/ESD, June 6, 1990, Response to request for 

information for the facilities in Plaquemine, LA; Midland, 

MI; Freeport, TX; and LaPorte, TX. 

17. Memorandum from Mikowski, E. J. Union Carbide Chemicals and 

Plastics Company, to J. R. Farmer, OAQPS/ESD, June 7, 1990, 

Response to request for information for the TX City, TX 

facility. 

18. Memorandum from Kraftchick, B. J. Exxon Chemical Americas, 

to T. R. Olsen, Radian Corporation, August 7, 1990, Response 

to request for information for the Baton Rouge, LA facility. 

19. Ocamb, David D., Radian, to Markwordt, David, EPA/CPB, 

"Summary of Chemicals Potentially Transferred by Marine 

Vessel." October 3, 1990. 

20. U. S. Environmental Protection Agency. Compilation of Air 

Pollution Emission Factors, Volume I: Stationary Point and 

Area Sources Location. EPA/AP-42. Research Triangle Park, 

NC. September 1985. pp. 4.4-1-4.4-17. 

Lrmemo/htmOKls) H 

^teSgl.^.^Ui..... .^mui^mm^^auM 
P.13 

) 

ATTACHMENT A 

lrmemo/htmO1(Is) 12 
P.14 

Hon Transfer Model Racks Verification 28-Aug-90 

3333333333X3X3333B333S3SXSB33aSSS333333333333S3333333333333333333S3333333333333333333S3333X5333333 

Plant 

Designation 

and 

Vehicle Type 

Questional re 

Response 

Reported 

Racks Arms 

S3B«3»l3331333Sasa»l»3IllllS83HS383asai3S33St3aai t 

Plant 1 TT 

Plant 1 RC 

Plant 1 Total 

Plant 2 TT 

Plant 2 RC 

Plant 2 Total 

Plant 3 TT 

Plant 3 RC 

Plant 3 Total 

Plant 4 TT 

Plant 4 RC 

Plant 4 Total 

Plant 5 TT 

Plant 5 RC 

Plant 5 Total 

Plant 6 TT 

Plant 6 RC 

Plant 6 Total 

Plant 7 TT 

Plant 7 RC 

Plant 7 Total 

Plant 8 TT 

Plant 8 RC 

Plant 8 Total 

PI ant-9 TT 

Plant 9 RC 

Plant 9 Total 

Plant 10 TT 

Plant 10 RC 

Plant 10 Total 

0 

1 

1 

0 

3 

3 

0 

1 

I 

1 

1 

2 

2 

0 

2 

5 

4 

9 

3 

2 

5 

3 

6 

9 

2 

3 

S 

6 

6 

12 

3 

38 

10 

6 

8 

14 

Chemical and 

Throughput 

Preliminary Models 

Predicted 

Racks Arms 

33333333333333333 3 

1 

1 

2 

1 

1 

2 

1 

I 

2 

1 

1 

2 

1 

1 

2 

1 

1 

2 

1 

. 1 

2 

2 

4 

6 

87 

44 

131 

1 

16 

17 

4 

6 

10 

2 

3 

5 

7 

25 

32 

88 

132 

220 

6 

48 

54 

Chemical and 

Throughput 

Final Models 

Predicted 

Racks Arms 

4 

18 

22 

1 

1 

2 

4 

6 

10 

2 

3 

5 

7 

34 

41 

9 

61 

70 

2 

10 

12 

Plant 11 TT 
P.15 

Hon Transfer Model Racks Verification 28-Aug-90 

• 3 3 3 3 3 3 33 3 3333 3 33 3 3 3 3 3 3 3 3 3 3 3 93333333333=3333 3 

Plant 

Designation 

and 

Vehicle Type 

Questionaire 

Response 

Reported 

Racks Arms 

Chemical and 

Throughput 

Preliminary Models 

Predicted 

Racks Arms 

Chemical and 

Throughput 

Final Models 

Predicted 

Racks Arms 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

PlantPlant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

11 RC 

11 Total 

12 TT 

12 RC 

12 Total 

13 TT 

13 RC 

13 Total 

14 TT 

14 RC 

14 Total 

15 TT 

15 RC 

15 Total 

16 TT 

16 RC 

16 Total 

17 TT 

17 RC 

17 Total 

18 TT 

18 RC 

18 Total 

19 TT 

19 RC 

19 Total 

20 TT 

20 RC 

20 Total 

21 TT 

21 RC 

5 

11 

7 

6 

13 

3 

13 

13 

4 

4 

8 

4 

4 

8 

9 

25 

34 

7 

22 

29 

4 

7 

11 

9 

6 

15 

7 

25 

32 

7 

35 

3 

4 

1 

5 

6 

35 

30 

65 

1 

6 

7 

1 

14 

15 

20 

26 

46 

20 

26 

46 

1 

2 

3 

1 

2 

3 

2 

4 

6 

4 

6 

9 

11 

2 

15 

17 

36 

90 

126 

2 

18 

20 

2 

42 

44 

21 

78 

99 

21 

78 

99 

4 

13 

21 

4 

13 

17 

5 

21 

26 

7 

29 

1 

3 

4 

1 

2 

3 

2 

6 

8 

4 

10 

10 

12 

2 

10 

12 

3 

19 

22 

2 

10 

12 

2 

10 

12 

3 

10 

13 

3 

10 

13 

4 

17 

21 

4 

13 

17 

5 

29 

34 

7 

45 
P.16 

Hon Transfer Model Racks Verification 28-Aug-90 

=333S53=S33833SaS3333S33X3SS33SS3333Z.333S3=33333SS33S33S&3=333333333 3 isazssi: 

Plant 

Designation 

and 

Vehicle Type 

Questional re 

Response 

Chemical and 

Throughput 

Preliminary Models 

Reported Predicted 

Racks Arms Racks Arms 

3333355333383333833333333333333533333333333333333:5333333353533333553333333333 : 

Chemical and 

Throughput 

Final Models 

Predicted 

Racks Arms 

Plant 21 Total 11 42 10 36 14 52 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

Plant 

22 

22 

22 

23 

23 

23 

24 

24 

24 

25 

25 

25 

26 

TT 

RC 

Total 

TT 

RC 

Total 

TT 

RC 

Total 

TT 

RC 

Total 

TT 

26 RC 

26 Total 

Grand Total 

Total Excluding Outliers 

Percent 'redlcttd Excluding 

Percent Predicted Based on 

6 

8 

14 

3 

4 

7 

30 

16 

46 

21 

38 

59 

14 

10 

24 

273 

132 

Outliers 

Total 

10 

70 

80 

4 

17 

21 

31 

21 

52 

39 

37 

76 

29 

46 

75 

622 

405 

7 

9 

16 

2 

3 

5 

1 

2 

3 

8 

9 

17 

3 

4 

7 

427 

N/A 

156 

10 

41 

51 

5 

17 

22 

3 

13 

16 

11 

41 

51 

6 

21 

27 

1024 

N/A 

165 

6 

16 

22 

2 

5 

7 

1 

2 

3 

7 

17 

24 

3 

7 

10 

162 

123 

93 

59 

9 

69 

78 

5 

25 

30 

3 

13 

16 

10 

73 

83 

6 

33 

39 

624 

474 

117 

100 

Note: Outlier plants are defined as those with the number of predicted racks outside the range 

of plus or minus 10 racks of the total number reported for tank truck and rail car.