From: Hector.Ybanez@holcim.com To: Keith Barnett/RTP/USEPA/US@EPA, Sharon Nizich/RTP/USEPA/US@EPA Date: 12/18/2011 06:35 PM Subject: follow up on UPL

Keith and Sharon During our December 6th meeting we discussed the ability of the UPL to predict the 99th percentile. Holcim used PM CEM data from four kilns and showed that the UPL underestimates the actual 99th percenti le by more than 50 percent. EPA pointed out that Holcim was making an incorrect comparison. EPA believes if the entire data set is used then the actual 99th percentile would most likely be found in the worst performer within the floor. EPA, further stated, that the UPL does not predict the 99th percentile of the data set but rather the 99th percentile of the best performers within the floor. Based on this “new information”, Holcim recalculated the actual 99th percentile and the UPL of the best performers wi thin the data set. Once again, it was concluded the UPL significantly underestimates the actual 99th percentile for the best performers between 40 and 50 percent.

Holcim has provided examples using long

- term THC CEM data, PM CEM data from 6 European kiln s, and most recently 4 Holcim kilns to show that the UPL does not work. In addition, the utility sector provided EPA a similar comparison using long

- term Hg CEM data to show that the UPL underestimates the real value. Therefore, we can conclude that the UP L equation only works in two occasions. The first is when the long

- term data set is calculated as 30

- day averages and the UPL is used the predict the 99th percentile (i.e., m=1). In this configuration, the UPL is most accurate plus or minus 1 to 5 percent. The second instance is when there is no long

- term data to verify the UPL and one has to assume it works.

If EPA continues to use the UPL to predict the 99th percentile of 30

- day average from daily averages, they should provi de a CEM data set to prove the equation works. Otherwise, EPA should reconsider the use of such a flawed and grossly underestimating empirical method.

The four kilns used in the most recent example might be a mixture of LLL, CISWI and EEE kilns; however, the type of kiln is not important, Holcim’s point is the inability of the UPL equation.

If you have any questions or comments please contact me.thank you

(See attached file: UPL Evaluation.ppt)

----------------------------

Hector Yba nez Corporate Manager, Environmental 122 West Carpenter Freeway Suite 535 Irving, Texas 75039 Phone (214) 524

- 2814 Cell (972) 268

- 1139 hybanez@gmail.com mailto:Hecto r.Ybanez@holcim.com

http://www.holcim.us

# UPL and the 99th Percentile2

28.06.2012 /Ad Holcim Group Support



# Holcim PM CEM Example

N Mean Variance EPA UPL % Difference * All hourly Data 9824 0.020 0.00043 0.030 -53.1 Random A Set 1 631 0.020 0.00036 0.029 -55.1 Random A Set 2 561 0.020 0.00036 0.029 -54.1 Random A Set 3 611 0.021 0.00042 0.031 -52.3 Random B Set 1 1213 0.020 0.00039 0.029 -54.0 Random B Set 2 1195 0.020 0.00043 0.030 -52.8 Random B Set 3 1191 0.020 0.00040 0.030 -53.9 Random C Set 1 1810 0.020 0.00039 0.030 -53.6 Random C Set 2 1822 0.020 0.00049 0.031 -52.1 Random C Set 3 1807 0.020 0.00039 0.029 -54.6 Random D Set 1 2339 0.020 0.00041 0.030 -53.3 Random D Set 2 2323 0.020 0.00040 0.029 -54.2 Random D Set 3 2247 0.020 0.00041 0.030 -53.4 Random E Set 1 3908 0.020 0.00041 0.030 -53.5 Random E Set 2 3821 0.020 0.00049 0.031 -51.7 Random E Set 3 4048 0.020 0.00040 0.029 -53.9

* The column represents the percent differences between the UPL value and the actual 99th percentile.3

28.06.2012 /Ad Holcim Group Support



# UPL Using 30

- day Averages

0.020286

0.000266

N 4

m 1

SQRT(Variance*(1/n+ 0.016322

t 2.586536 UPL 0.0625 Actual 99th Percenti 0.0640 Overall Mean

Variance4

28.06.2012 /Ad Holcim Group Support



# UPL

– EPA’s Approach

a b c d e a(i) b(i) c(i) d(i) e(i)

99th
a(n) b(n) c(n) d(n) e(n) Mean (i) 1 1.5 2.5 4 4.5

Overall Mean 2.7

Overall Variance

Actual 99th Percentile

UPL Only Sources better than 2.7 So the UPL is predicting the 99th percentile for only source a, b, and c EPA states that the difference is between the actual 99th percentile and the UPL 99th of the best performers Kiln Floor Sources5

28.06.2012 /Ad Holcim Group Support



# Holcim PM CEM Data applying EPA “thinking”

 

# UPL still under

- estimated by significant percent Only Best Performers All Data 0.01193317 0.020286

0.000145771 0.000428

3 4

30 30

0.00220856 0.003784

2.576460585 2.57633 0.0176 0.0300 0.0434 0.063966 -59.39% -53.05% Percent Differences (%) Mean

Variance

N

m

SQRT(Variance*(1/n+1/m))

t UPL Actual 99th Percentile of 30-day Average6

28.06.2012 /Ad Holcim Group Support



# Holcim PM CEM Data applying EPA “thinking UPL Using 30

- day Averages

0.020286203

9.89704E-05

N 3

m 1

SQRT(Variance*(1/n+ 0.009960663

t 2.588114378 UPL 0.0461 Actual 99th Percentil 0.0434 Overall Mean

Variance