MEMORANDUM

DATE: August 6,2010

FROM: Keith Bamett, EPA/OAR/OAQPS/SPPD/MMG

TO: Docket EPA-HQ-OAR-2002-0051, National Emissions Standards for Hazardous Air

Pollutants for Portland Cement Manufacturing.

Record of contacts with HectorYbanez concerning calculation of mercury floors. Note

that Mr. Ybanez is an employee of Holcim, USA. However, during much of this

discussion he was acting as a representative of the Portland Cement Association (PCA)

charged by the PCA to work with EPA on variability issues.

On March 25,210 Hector Ybanez of Holcim USA sent an email (attached) proposing a

simplified version of the mercury floor calculation. In this version, the daily mercury

numbers would be adjusted to account for intra-quarry variability and local coals.

I held subsequent conversations and meetings with Mr. Ybanez and Dr. Mills, a

statistician who was consulting for the Portland Cement Association. The outcome of

that meeting was a July 22,2010 email which contained Mr. Ybanez's final calculations.

In their original public comments (#2845), the Portland Cement Association stated that

an upper tolerance limit (UTL) was the proper statistical calculation to use to develop a

MACT floor. EPA's response was that an upper predictive limit (UPL) was the more

appropriate statistical calculation. Our reasoning was that the upper predictive limit is a

better indicator when you are trying to determine future averages. The UTL is more

appropriate when you are trying to determine the highest future value.

The industry did correctly note that there was an error in the UPL equation that EPA us at

proposal. In this final rule, we corrected this error.

EPA rnet with PCA and Industry representatives on May 5,2010, including Mr. Ybanez,

Dr. Mills, John Holmes (consultant to the PCA). The information presented is attached.

In this meeting industry still suggested the UTL was a better predictor of the 99'r'

percentile, but they also indicated that the UPL could be used if the variance was

correctly accounted for in the underlying data to which the UPL equation is applied. (See

slide 11).

EPA representatives including myself also discussed these issues with Mr. Ybanez on

April 4, May 6, and May 12 of 2010.

On June 25,2010, Mr. Ybanez send an email (attached). In that email he indicated that

in his view there were three main sources of variability that need to be accounted for,
which were intra-quaffy variability, variability of local coal mines, and auto-correlation

(which accounts for the fact that the mercury measurements are on consecutive days). In

that email, he again claimed that the UPL being used by EPA underestimated variability.

However, at that time he was unaware that EPA had changed our calculation n to a

pooled variance, which increased the UPL, and he had dropped his contention that the

UTL should be used.

The frnal calculations prepared by PCA were sent to EPA on July 22,2010. (Attached).

In this calculation, the mercury floor was calculated using a proportional variance and

including a factor for intra-quarry variability of 0.45. It also included a variance to

account for varying mercury contents of local coals.

In EPA's final mercury floor calculation we included pooled variance and a factor for

intra-quarry variability, but we used a value of 0.57, versus the 0.45 factor used by Mr.

Ybanez. We did not include variability of local coals for reasons discussed in the

preamble to the fïnal rule. Because we pooled the variance, the form of the UPL

equation EPA used would produce essentially the same result as the form used by Mr.

Ybanez.

My Ybanez's ftnal result was a mercury MACT floor of 78 lb/MM tons feed. But this

number included variance for the different mercury contents present in local coals.

Attached to this memo in reverse chronological order are three emails and the

presentation from the May 7,2010 meeting. The email attachments are included behind

the three emails.
(y. 

-= Final HG Floor for Existing Kilns - lN DOCKET ..--'ãr Hector.Ybanez to: Keith Bainett o7t22t2o1o12:38PM

History: This message has been fon¡rarded.

Keith

I have attached two excel- fil-es - one is the autocorreLation for Hg using

over one year of kil-n feed data for each Hg Fl-oor source.

The other file is the variability calculations which lncl-ude the

variabil-ity f or:

intra-quarry for each of the lL sources,'

the variability of nearby coaL mines that supply each of the Ll"

sources; and

auto-correlation.

Subsequent to our submittal, RTI provided comments on Hol-cim's proposal-.

Holcim incorporated most of the RTI comments in to our caLculations.

Basically, w€'ve worked cooperatively with EPA/RTI, and I think that

significant progress has been made. I want to thank you for giving us

Chat opportunity

Currentl-y, al-l- issues have been resol-ved with the exception of how the

"totaL variance" is cal-cul-ated. RTI assumes that the variation in the data

set is equal between sources, and hence this assumption does not al-l-ow for

between source variability to be considered. Furthermore RTI assumes that

the variance become smaller as more data 1s col-Iected. In reality, as more

data is col-l-ected the J-arger the variance - we have demonstrated that point

to EPA and RTI using reaL data.

Conversely, to RTI assumptions, the sources which make up the mercury

floors al-so contain an unequal- or unbal-ance dataset. In an effort to

determine the best approach of cal-culating an overaLÌ variance, we

contacted SAS Institute and inquired as to the best statistical approach to

use when determining an overall- variance for such a data set. The SAS

Institute indicated the correct way of handl-ing an unbal-ance dataset was

through use of the Proc Mixed or Proc Varcomp procedures (in other wordsthe variance needs to be weighted to account for variability between

sources and within source variability). This issue has been discussed with

RTI but it remains unresol-ved.

To aid j-n this discussion, we decided to test RTI's UPL and assumptions

using avail-abl-e long-term THC CEM data. Testing such a model- shouLd

provide reaÌ confirming evidence as to it functionality in a real worl-d

situation. What we discovered j-s that RTI's UPL and assumptions grossJ-y

underestimate the actual- 99th percenti.i-e. That in itseLf ; should force RTI

to re-eval-uate their assumptions.
Once again, I would like to thank you for your efforts and we are willing

to continue to work on this matter with EPA and RTI.

(See attached fil-e: Hg Auto Correlation.xls) (See attached file: HG Floors

for Exisiting Kilns with Varabil-ity Included.xls)

Hector Ybanez

Corporate Manager, EnvironmentaL

I22 West Carpenter Freeway

Suite 485

Irving, Texas 75039

Phone (21,4) 524 - 28L4

CeIt (9'72l, 268-tL39

Hector. Ybanez@holcim. com

hybanezGgmail. com

www. holcim. com,/us

This e-mail- is confidential and intended only for the use of the above

named addressee. If you have received this e-mail in error, please delete

it immediately and notify us by e-maiL or telephone.
From:

To:

Cc:

Date:

Subject:

Heetor.Ybanez@holcim.com

Peter Tsirigotis/RTP/USEPA/US@EPA

Keith BarnetURTP/USEPA/US@EPA

0612512010 04:16 PM

follow-up PUT lN DOCKET

Peter

I would like to thank you for taking time from your hectic schedul"e to meet

and discuss Mercury floors and the UPL. The purpose of this email is to

provide you wit,h a cursory summary of Lhe major take-a-ways from our

discussion.

As you know, Holcim took iE upon iLself to offer you a simpJ-e method to

accounÈ for most, of the variability associated with the 11 sources which

make up the mercury fLoor. The approach incLuded Ehe variability for:

intra-quarry for each of Èhe L1 sources;

the variability of nearby coal mines that supply each of the 11

sources; and

auto-correlation.

SubsequenE to our submiÈEal, RTI provided comments on HoLcim's proposal.

Holcim incorporaEed most of thê RTI commenÈs in to our calculations.

Basically, w€'ve worked cooperatively with EPA/RTI, and I think that

significant progress has been made. I want to thank you for giving us

thaE opporEuniEy.

Currently, aLl issues have been resolved wit.h the exception of how the

"total variance" is calculaEed. RTI assumes that the variation in the data

set is equal between sources, and hence t,his assumption does not allow for

beEween source variability to be considered. Furthermore RTI assumes that

the variance become smaLler as more data is collected. In reality, as more

data is col-l-ected Èhe larger the variance - we have demonstrat,ed that point

Eo EPA and RTI using real data.

Conversely, to RTf assumptions, the sources which make up the mercury

floors also contain an unequal or unbaLance dat,aset.' In an effort Èo

determine the best apprgach of caLculating an overalJ- variance, h¡e
contacted SAS InstiÈute and inquired as to the besL statistical approach to

use when determining an overall variance for such a data set. The SAS

Instit,ute indicated tshe correct way of handling an unbalance daÈaset was

through use of the Proc Mixed or Proc Varcomp procedures (in other wordsthe variance needs to be weighÈed to accounE for variabilit,y between

sources and wit.hin source variability) . This issue has been discussed with

RTI but it remains unresoLved.

To aid in this discussion, we decided to test RTI's UPL and assumpÈions

using available long-term THC CEM data. Testing such a modeL should

provide real confirming evidence as Èo it functionality in a real world

situation. I¡Ihat we discovered is that RTI's UPL and assumptions grossly

underestimate the acÈual 99th percentile. That in it,self,. should force RTI

Lo re-evaLuate their assumpÈions.

Once again, I would like to thank you for your efforts and r^¡e are willing

t,o continue to work on this matter with EPA and RTI.
PCA Presentation

IJpper Predictive Limit (IJPL)

and

IJpper Tolerance Limit (IJTL)

NESHAP Rulemaking

May 7,2010
Contents

o Statistical Intervals

o lJtilizinglong-term THC CEM datato test

UPL and UTL Approach

o Conceptual Discussion on Mercury

Slide 1
Statistical Intenrals

' Statistical intervals are common practice in working with data. There is

a difference between a confidence interval (CI), a p-rediction interval

(PI), and a tolerance interval (TI).

A CI contains a value, such as the mean, with a specified degree of

confidence.

A PI contains a certain number (k) of future observations with a specified

probability.

A TI contains aspecified proportion of a population with a specified

degree of confidence.

. Therefore:

a. a 95o/o CI for an unknown quantity is a range which has a 95o/o chance

of containing the true value of the quantity;

b. a 99% PI will contain a value with gg%probability; and

c. a99o/o TI contains 99% of the values with a stated confidence (such as

es%).

Slide 2
Distributions Testing Using

Long-teffn CEM data

Slide 3
99th Percentile of Long-Te{m

THC CEMDATA

This data set is used to calculate the UPL and UTL in the following slides.

Rankino RndmKilnCo Name DataField Counl Mean 99th lhrcentile

1 t520 Lehieh Union Bridse E02-001 30-Dav Rolline Averaee 668 4.69007

,\

23.65'\

2 THC-1 Suwannee Bradford, FL 1 30-Dav Rollins Averase 274 5.68426 \,,,0.u0 i ,,j

3 L226 Holcim Trident 30-Day Rolling Average 762 5.69003 'ffi€--/

4 L239 TXI Midlothian Kiln 5 30-Dav Rolline Averaee 444 s.8292 10.17

5 1316 Holcim Mason Citv Kiln 2 30-Dav Rolline Averaee 70L 10.9063 28.57

Top 2 30-Dav Rolline Averase 942 4.97925 23.7

Too 5 30-Dav Rollino Averaoe 2183 7.39371 27.4

?ßr.i

Slide 4
EPA UPL Equations

Equation Assumption Calculated

THC ppmvd @7% O2

JPL Equation in Proposal [?l = ¡ndûn * ktft, ilf,.i

n (future values)=f,Q

îean=average of group

îeans 10.43

UPL=meüil+tü

mfuturevalues

tlew UPL Equation (EPA

evised)

n (future values)=36

nean=average of group

neans 8.29

\./

Slide 5
Issues with'New UPL"

o EPA "new IJPL equation" appears to have

corrected the issue within-source variability

o EPA "new UPL Equation" does not change

the calculation of the between-source

o Additionally, it wrongly divided twice by N

variúility.

which attenuates the emissions standard

deviation between best performing units by

an extra factor of 1/sqrt(N)-3.3.

Slide 6
Corrected IJPL Equation

Calculated

THC ppmvd (õ.7o/o 02

rrected UPL Equation (2009 EPA Unified Guidance)

P L : rr* an* fi-*/*",-, t'¡[=)

for wrtransformed dzta

assumed normally distributed

m future r¡alues

(future values)=1

n-grand mean

-alm= 0.99

dence limit

(future values)=39

s¿¡=grârìd mean

-olm= 0.9996

nce limit

The above PL is calculating the one data point which represents the 99th

percentile, therefore, "m." should be 1. Slide 7
Corrected UPL Equation

THC ppmvd @.7% 02

UPL Equation (2009 EPA Unified Guidance)

PL: meãn+ å*,o_r$

foruntransformed data

assrmed normal distrib ute d

me¿uì of p futr.rre values

(future values) =1

s¿¡=grâhd mean

-a=99o/o cumulative

bility

of p future

(future values)=tQ

¡=grârìd mean

-a=99o/o cumulative

robability

n of p future

The above equation is the same equatio.n used in Boiler MACT.

s

th Slide 8
IJTL

Calculation (2009 EPA Unified Guidance)

TL = mean +-r(¡¡, y, 1 - c).s

for untransficrrned data

. &)Ìn oJî squaretotal r,,(tota¡ varrañce)

r(n,f ,l- ar) : one sided norma!. tolerance factor

y : cov erage coefficient

1- ø: cor¡fidence level

TL: explmean+ r(n,y,7- a).sl

fornatural log transformed data

. St¡tnqf squnretotal yr(total eattætce)

K<n,f ,7- a): one sided normal tolerance faclor

/ : coverage coefficient

1 - a: cor¡fidencre lev el

g¿¡=gfâfìd mean

-q=95% Cl, y-99%

n-grand mean

transformed data

-q=95% Cl, y-99%

Slide 9
Conclusions

UPL equations in the proposal and the most

recent IJPL are in effor

EPA should utilize the correct IJPL (Slide

7) where the "future value" is equal to one

(1). A future value of 1 should be used

because the UPL is calculating the one data

point which represents the future value of

99thpercentile.

Utilizationof the log transformed IJTL is a

much better estimator of the 99th percentile

Slide 10
Mercury

o EPA should used either the UPL on SlidesT or 8

o EPA could use the tlTL to obtaiÍtabetter

estim ate of th e 99th percentile

o Regardless if EPA uses the UPL or UTL

EPA should make allowances to adjust the variance

term in the above equations so variances not capfure

during the 3O-days of data collection can be inlcuded

. Those variances should include at a minimum; Kiln feed;

Intra-quarry; and Coal Mine ICR Data.

Slide 11
q{1. _r variability .-.,'Ü Hector.Ybanez to: Peter Tsirigotis, Steve Fruh, Keith Barnett O3l25l2O1O 11:26 AM

H¡story: This message has been forwarded.

Regarding Peter's invitation to provide an exampJ-e of how variabil-ity couJ-d

be incorporated without creating a "Franken-Limit"; Hol-cim offers a simpJ-e

approach that incl-udes variability encountered as part of kiJ-n feed,

intra-quarry, and coal from numerous coal- mines. In very simple terms,.

Limestone mercury content of the 11 sources is 11".75 lblMil-Lion tons

of kil-n feed incl-uding any controls, such as mercury removed via CKD

and,/or scrubber.

Kiln feed standard deviation for each source i-s converted to a

relative standard deviation (RSDkiln feed)n

Intra-quarry variability is based on the 458 (RSDintra-quarry)n which

was developed as part of our comnents for Location A and Location B

CaLcul-ate relative standard deviation for coal- mj-nes (RSDcoat mines)n identified at each sources. These are the coal- mines that were identified by John Hol-mes for each source.

Therefore, the RSDoverall is caLcuLated for each source using the folJ.owing

equat ion :

Overall- RSDn : { (RSDkiln feed)2n +(RSDintra-quarry)2n +(RSDcoal

mines ) 2n )

Once an overal-L RSD per source is cal-cul-ated, the total varj_ance is

calcul-ated by

@Total: ?{ ?L to 11(RSDn)}

The total- variance is converted back to an overal-l- standard deviation (S)

by multipJ-ying it by the average kiln feed Hg content of the 11 MACT

sources.

S : @TotaÌ x kiln feed HgJ-b HglMillion tons of kiln feed

This all-ows for the 99th percentile to be calcul-ated

MACT Floor lb HglMillion tons of kiln feed : ave. Limestone Hg lb HglMil]ion tons of kiln feed + t (S/?n)

MACT Floor J-b HglMillion tons of kiln feed = 11.'15 + 2.'7631 x

52.64 /?7r

MACT Floor lb HglMillion tons of kil-n feed = 55.6

The above equation woul-d generate a MACT FLoor of 55.6 Lb HglMilJ-ion tons of kiln feed.

PLease share with your statistlcal- contractors and if you a-lJ- have any questions or conments please contact me.
(See attached fil-e: Hg VARABILITY Cal-culations HY for EPA 03252010.xls)

Hector Ybanez

Corporate Manager, Environmental

l-22 West Carpenter Freeway

Suite 485

Irving, Texas 75039

Phone (21.4) 524 - 2814

CeLl (972) 268-L139

Hector. YbanezGhof cim. com

hybanezGgmaiL. com

www. holcim. com/us

This e-mail is confidentiaf and intended only for the use of the above

named addressee. If you have received this e-mail in error, please deLete

it immediately and notify us by e-mail or telephone.