# DRAFT

**Model	for	Pr edicting	In** 

**- Stack**  **Re sponse	F**  **unctions	for	Beta At**  **te nuation** 

**- Based	PM	CEMS	and**  **Pr oposed	Alt**  **ernati ve**  **s	t o	PS** 

**- 11	and** 

**P**

**- 2	Using	a	Q** 

**AG**

**EPRI Communication**

**– Working White**  **Paper**

**Cooper	Environmental	Service,	LLC**

**10180	SW	Nimbus	Avenue,	Suite	J6**

**Portland,	OR	97223**

**www.cooperenvironmental.com**



## Januar **y 10**  **, 2013**

# DRAFT

**Model	for	Pr edicting	In** 

**- Stack**  **Re sponse	F**  **unctions for	Beta**  **At te**  **nuation**

**- Based**  **PM CEMS**  **and Pr**  **oposed Alt**  **ernati ve**  **s	t o	PS** 

**- 11	and** 

**P**

**- 2	Using	a	Q** 

**AG**

**Prepared by**
Andrea Geiger, Troy Pittenger

, Jamie Berg , and John A. Cooper

Cooper Environmental Services, LLC

Portland, OR

and

Craig C l apsaddle Mechanical Systems, Inc. Raleigh, NC



## January **10 , 2013** **Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **3** of **28** 

### TABLE OF CONTENTS

**SUMMARY 5** 

**1.0 INTRODUCTION**  **6**

**2.0 REVIEW	OF	RECENT	BAM** 

**- BASED	TEST	RESULTS**  **8**

2.1 Background for CEMS, Testing, and Power Plant 8

2.2 Testing Results at the Bruce Mansfield Po wer Station 9

2.3 Comparison of QAG and PS

- 11 Results 12



### 3.0 **PROPOSED	MODELS 15** 

3.1 Overview 15

3.2. Physical Model 15

3.3 Mathematical Model 17

3.4 Model Evaluation 19



### 4.0 **PROPOSED	ALTERNATIVE S	TO	PS** 

**- 11	AND	P** 

**- 2**  **22**

4.1 PS

- 11 and P

- 2 22

4.2 Proposed Alternative: Performance Specification 11b 22

4.3 Proposed Alternative: Procedure 2B 24

4.4 Evaluation of P roposed Alternative Methods 24

4.5 Summary of Benefits of Proposed Alternatives 26



### 5.0 **CONCLUSIONS	AND	RECO MMENDATIONS**  **27**

**6.0 REFERENCES**  **27**



## Appendix **A :**  Preliminary Application of Alternative Performance Specificati on 11B to Examples of Existing BAM

- Based PM CEMS Database**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **4** of **28** 

## Tables

Table 1. Summary of initial PS

- 11 Certification correlation test results f or the three PM CEMS challenged by the QAG (1A, 2B, 3A)

Table 2. Summary of CEMS correlation parameters resulting from QAG measurements

Table 3. Comparison of Linear Model Fit Parameters for Fifteen BAM

- Based PM CEMS Developed with
PS

- 11 In

- Stack or QAG Off

- line Measurements (MSI BetaGuard data)

Table 4. Examples of po tential variables influencing measured PM CEMS concentration and their potential range

Table 5. Compar ison of Linear Model Fit Parame ters (In Order from Smallest to Largest Slope) for Fifteen

BAM

- Based PM CEMS Correlated with M5 and PS

- 11 In

- Stack Measurem ents

Table 6. Comparison of PS

- 11/P S

- 11B Calibration Correlations f or 14 BAM

- Based PM CEMS Databases



## Figures

Figure 1. Plots of original PS

- 11 correlation data and ongoing Calibration Results for MSI BetaGuard PM CEMS 1A (a), 2B (b), and 3A (c) at the B MPS

Figure 2. Plot of predicted QAG reference aerosol concentration versus measured concentration by
three different BAM

- based PM CEMS exhibiting a highly linear relationship and a slope close to one

Figure 3. Comparison of PS

- 11/PM CEMS and QAG/PM CEMS re sponse functions for 1A (a), 2B (b) and 3A (c) PM CEMS at the BMPS

Figure 4. Schematic illustration of proposed physical model of the PM deposit measurements for both
EPA Reference Method 5 and extractive BAM

- based PM CEMS



## Appendix A: Preliminary Application of Alternative Performance Specification 11B to Examples of Existing BAM

- Based PM CEMS Databases**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **5** of **28** 

## S **UMMARY**

Recent quantitative aerosol generator (QAG) testing with three independent beta attenuation monitor (BAM)

- based particulate matter (PM) continuous emissions monitoring systems (CEMS) has demonstrated strong agreement between predicted QAG reference aerosol concentrations and measured PM CEMS aerosol concentrations based on PM CEMS factory thin film standard calibrations

. The a verage concentration relationship between the QAG (C QAG ) reference aerosol concentration and all three of the BAM

- based PM CEMS (C CEMS ) measurements is given by the following linear equation:

C QAG = (1.06 ± 0.02)C CEMS – 1.43 ± 0.61

The linearity of this r elationship over a concentration range from zero to 75 mg/m 3 was strong, as evidenced by a coefficient of determination (R 2 ) of 0.99. In addition, the uncertainty in the individual slopes was about 2%, while the standard deviation in the mean slope for all three CEMS (1.05 (1A), 1.06 (2B), and 1.07 (3A))
was less than 1%.

Results from Environmental Protection Agency (EPA) Performance Specification 11 (PS

- 11) fo r multiple BAM

based PM CEMS show ed not only high variability between PM CEMS’ calibration slopes, but also a significant departure from the ideal 1:1 linear relationship, with some slopes as high as 3.7. The results from both the QAG and PS

- 11 testing indicate that off

- line QAG calibration s of PM CEMS cannot be used alone to predict in

stack response functions for BAM

- based PM CEMS. However, based on this data and theoretical considerations, a model has been developed that suggests that independent off

- line BAM

- based PM CEMS
calibrations u sing the QAG, in conjunction with measurements of PM CEMS probe deposits at typical stack
conditions

, can reliably and accurately estimat e in

- stack PM concentrations

. A k ey concept of this proposed
linear model assum e s that a PS

- 11 slope ’s deviation from 1 .0 is due primarily to losses from probe deposits.

Based on this model, alternatives to PS

- 11 and Procedure 2 (P

- 2) are outlined that would not require altering plant processes. These alternative specifications and procedures are expected to meet EPA crite ria for approval of alternative methods. Results from applying the alternative PS

- 11 method to existing PS

- 11 data
from 14 coal fired power plants (CFPP) are encouraging. The results demonstrate that the proposed model of incorporating off

- line QAG and probe deposit measurements is capable of producing results comparable to
PS

- 11, except the QAG method would not require extrapolation at higher conc entrations nor modification of CFPP processes.

Cooper Environmental Services, LLC recommend s that these alternative s ( performance specification (PS

- 11B)
and an alternative on

- going quality assurance procedure (P

- 2B )) be developed and formalized. Once

comp leted, the alternatives should be submitted to the EPA to solicit their comments and contributions

to wards the development of a field demonstration plan. It is further recommended that these field demonstration tests be conducted to develop a database to support a request for EPA approval of these proposed alternative methods.

This document presents a conceptual physical and mathematical model approach for determining in

- stack response functions. In addition, outlines of alternative s to EPA’s PS

- 11 for in itial certification and calibration
and EPA’s P

- 2 for on

- going quality assurance of BAM

- based PM CEMS are presented. Also presented here are discussions of the data and theoretical considerations to support model conclusions and proposed alternative

proce dures.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **6** of **28** 

## 1.0 **Introduction**

Recent EPA regulations for electric generating units (EGUs) require plant operators to limit emissions of hazardous air pollutant ( HAP ) metals. Operators have several paths for demonstrat ing compliance
under this new regulation. One of the preferred compliance demonstration paths is to monitor total PM
emissions with a PM CEMS as an EPA

- accepted surrogate for HAP metals emissions. I nitial PM CEMS certification with performance specification 11 ( PS

- 11 ) an d o n

- going QA with procedure 2 ( P

- 2 ) are difficult, costly, and are typically unable to establish an adequate linear operating range. Cooper Environmental Services LLC (CES) has developed a quantitative aerosol generator (QAG) similar to reference gas genera tors and certified reference calibration gas cylinders. CES’ QAG has been proposed as a reference aerosol source that could be used in alternative performance specification s and on

- going QA procedures , which would be easier to implement, less costly

, and p rovide a larger dynamic range of validated linearity. U s ing a QAG in an alternative certification and/or on

- going QA procedure would

mo st likely require off

- line calibration of a candidate CEMS with a QAG

- generated aerosol and then infer
an in

- stack CEMS response function from these off

- line QAG

- based calibration s

.
Results from recent QAG field tests with BAM

- based PM CEMS provided encouraging results that support the potential of this off

- line calibration approach (Pittenger et al., 2012) . For example, i n these
recent field tests

, a QAG

- generated reference aerosol challenged three previously PS

- 11 certified BAM

based PM CEMS off

- line by comparing predicted QAG reference concentrations to reported PM CEMS
concentrations , and by comparing the QAG

- /CEMS

- based regression parameters to PS

- 11

- /CEMS

- based regression parameters. The average concentration relationship between all three of the PM CEMS (C CEMS ) and the QAG (C QAG ) concentration measurements is given by the following linear equation:

C QAG = (1.06 ± 0.02) C CEMS – 1.43 ± 0.61

.

The l inearity of the QAG / PM CEMS relationship over the concentration range from zero to 75 mg/m 3
was strong, as evidenced by a coefficient of determination (R 2 ) of 0.99 . In addition, the uncertainty in
the individual slo pes was about 2%

, while the standard deviation in the mean slope for all three CEMS (1.05 (1A) , 1.06 (2B)

, and 1.07 (3A) ) was less than 1%. This high level of agreement is even more impressive when one considers that the PM CEMS factory calibration is bas ed on thin film s tandards, while the QAG

- predicted c oncentrations are based on NIST

- traceable components and in

- field
determination of tra nsport efficiency. The independent nature of the QAG ’s predicted concentration
and the PM CEMS ’ measured concentration supports the high accuracy, precision, stability

, and reproducibility of **both** the QAG and the PM CEMS

. As evidenced by the data , these three PM CEMS ’ sensors, which have been in operation for about three years

, provide an accurate measure of PM mass captured on the CEMS filter tape.

The linearity of the relationship between these three PM CEMS and EPA Method 5B (M5B) was also quite good with a coefficient of determination of 0.99

. However, although the off

- line response
functions for the three BAM

- based PM CEMS were nearly identical, the in

- stack slopes measured with**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **7** of **28** M5B for these same three PM CEMS were 1.17 ( CEMS 1A) , 1.19 ( CEMS 2B), and 1.63 ( CEMS 3A) with an average slope uncertainty of about 4%. Although the slope uncertainty as determined with M5B is higher than that obtained with the QAG (4% versus 1%) , the more important issue is why these three nearly identical PM CEMS and off

- line QAG response functions are reporting such significantly different slopes with M5B compared t o the QAG

.

Th e difference between in

- stack and off

- line response functions is particularly important for the development of alternative s to PS

- 11 and P

- 2 based on off

- line QAG meas urements. For example, any
off

- line measurements with the QAG would have s uggested similar in

- stack response functions, whereas
the PS

- 11 /M5B data show the in

- stack response functions are clearly different, and quite significantly for the CEMS exhibiting a slope of 1.63. It is important to note that this high slope (1.63) is not an outlier ;

o n the contrary, numerous other high slopes have been reported ( M echanical Systems, Incorporated (M SI ) , BetaGuard PM CEMS data

, presented in Subsection 2.3 of this report ) for this same type of PM CEMS, with one slope as high as 3.7

. It can be assumed from the results of the three BAM

- based PM CEMS tested that off

- line QAG calibration for these other BAM

- based PM CEMS would be similar to the QAG

- determined slope values. Additionally, these measurements (QAG, CEMS, and M5B) can be
considered to be precise, independent (NIST, thin film, reference method)

, and accurate measurement s and prediction s of PM concentration. Furthermore, these recorded differences between slopes are rea l and statistically signific ant with, in some cases
, differences exceeding well over five standard deviations in the slope measurements. As such, these differences need to be well understood before an
alternative method to PS

- 11 and P

- 2 can be developed based on off

- line QAG measure ments and proposed to the EPA.

The objective of this work is to develop alternative procedures to PS

- 11 and P

- 2 based on off

- line PM
CEMS reference aerosol measurements

, such as those generated by a QAG. The objective of this specific document is to provide a foundation for further discussions of how the QAG might be used in this capacity. Our approach to this problem has been to first develop conceptual physical and
mathematical model s to explain the results from these three independent measurements and understand why the data fit a linear model so well. Then, b ased on this new understanding, we propose an alternative performance specification and procedure that use s off

- line mea surements in conjunction with probe

- and transport

- loss measurements . Section 2.0 reviews the details of these recent QAG/PM CEMS/M5 test results and their implications. In Section 3.0

, physical and mathematical m odel s are proposed that form the foundatio n f o r understanding the current field data and the d evelopment of
alternative s to PS

- 11 and P

- 2. Based on this new understanding, preliminary outlines of alternatives to
PS

- 11 and P

- 2 are proposed and discussed in Section 4 followed by considerations of i mplications,
recommendations

, and conclusions.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **8** of **28** 

## 2.0 **Review	of Recent**  **BAM**

**- Based	Test	Results** 

**2.1 Background	for	CEMS,	Testing,	and	Power	Plant** 

**2.1.1 Bruce**  **Mansfield	Power	Plant**

The BAM

- based PM CEMS testing occurred near Shippingport, Pennsylvania at the Bruce Mans field
Power Station (BMP S ) , which is a coal

- fired power plant owned and operated by First Energy. BM P S has
three pulverized coal

- fired boilers producing 835 megawatt s ( MW ) each, for a combined site total of
2505 MW

. It is the largest coal plant owned and operated by First Energy. At full capacity, the plant’s generating units can produce 56

- million kilowatt

- hours of electricity daily.

Units 1 and 2 exhaust through a 950

- foot stack and are equipped with several emission controls, including a wet venturi s crubber for sulfur dioxide (SO 2 ) and PM controls, low

- nitrogen oxide ( NO x ) burner/separated over

- fired air integration system (LNB/SOFA) , selective catalytic control, and a sodium bisulfite injection system. Unit 3 exhausts through a 600

- foot stack and is controlled with an electrostatic precipitator (ESP) , followed by a horizontal weir wet scrubber for PM and SO 2 control. It is also equipped with an LNB/SOFA , selective catalytic control, and a sodium bisulfite injection system (Hatch, 2012). Each unit ha s two exhaust flues with a PM CEMS located on each flue. The QAG was interfaced with one CEMS from each unit (1A, 2B

, and 3A). Units 1 and 2 both have a typical PM level between 15 and 25 milligrams per wet standard cubic meter (mg/wscm) ; the stack gas is not saturated
with water . Unit 3 has a typical PM level between 5 and 15 mg/wscm and is saturated with free water droplets

.

**2.1.2 BAM** 

**- based	PM**  **CEMS**

The PM monitors tested at BMP S were MSI BetaGuard PM CEMS

. The primary components of a
BetaGuard PM CEMS include a probe and transport system to deliver a representative PM sample to a
reel

- to

- reel filter tape sampler. The measured flow through the fi lter tape and the PM mass deposited are measured and used to calculate the stack gas PM concentration. The pr inciple behind BAM

- based

PM CEMS is that the intensity of a beam of beta particles is reduced as it pass es through PM collected
on a filter media. A baseline beta intensity of blank filter media is collected and compared to the beta intensity after sample collection. T he attenuation of beta ray intensity between t he baseline and post

sample filter provides a measure of the PM deposit mass.

MSI BetaGuard CEMS are capable of measuring on a wet or dry basis and have dual carbon

- 14 ( 14 C ) beta sensor designs, a seven

- point thin film factory beta calibration, a four

- point flow calibration

, and automatic daily beta and flow calibration checks. The three PM CEMS tested were all installed and PS

- 11 certified about three years prior to QAG test ing and each CEMS met all on

- going QA requirements defined in P

- 2 . The PM CEMS’ sampler ( reel

- to

- reel tape drive ) and mass sensor ( be ta source and detector) are located between 45 (1A) and 80 (2B, 3A) feet away from the probe outlet, which were
identical f or all three CEMS. A P

- 2 response correlation audit (RCA) for CEMS 1A and 2B was performed before the QAG testing of those PM CEMS , and a P

- 2 relative response audit (RRA) for CEMS 3A was performed after QAG testing

. All P

- 2 criteria were met for all three of the P M CEMS tested

.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **9** of **28** 

### 2.2 **Testing	Results	at	the	Bruce	Mansfield	Power	Station**

**2.2.1 PS** 

**- 11	Results** 

**Results from initial PS**

**- 11 certification tests**  **for the three PM CEMS of interest (1A, 2B, and 3A) are**  summarized below in Table 1. These results show a very linear relationship (R 2 =0.992, 0.983 and 0.981)
between the PM CEMS factory calibration concentration and the M5

- measured PM concentration ; all
three CEMS met PS

- 11 initial certification test criteria. The slo pes for 1A and 2B CEMS correlations are similar (1.17 ± 0 .02 and 1.19 ±0.02 ) and within one standard deviation of each other . However, the PS

11 correlation slope for CEMS 3A is significantly different (1.63 ± 0.053) from the first two PM CEMS, and
all three are st atistically different from 1.00 by well over five standard deviations. It is generally thought
that this d ivergence from one is due to differences between the thin films used to calibrate the PM CEMS sensor in the factory and such fac tors as in

- stack aerosol characteristics, probe location, particle losses in sampling system, etc . (Jahnke, 2000) . The EPA considers these differences are compensated for by using the in

- stack calibration based on simultaneous M5 and PM CEMS concentration

measurements , as defined in PS

- 11

. As discussed in this report, we hypothesize that d eviations in slope
from 1.00 are due primarily to PM losses (deposits) in the probe and transport before the PM aerosol reaches the filter tape and beta ga u ge sensor , while most of the other possible influenc ing variables contribute primarily to the systematic constant bias term or random variability, i.e. data scatter

.

Table 1. Summary of initial PS

- 11 Certification correlation test results for the three PM CEMS cha llenged by the QAG (1A, 2B, 3A)

**C EMS ID**  **1A 2B**  **3A**
**Parameter**

R 2 (CoD) 0.992 0.983 0.982 m (slope) 1.17 ± 0.025 1.19 ± 0.043 1.63 ± 0.054 b (intercept) 0.32 ± 0.500

- 2.04 ± 0.962

- 1.17 ± 0.532 COL (mg/wscm) 45.6 62.5 38.0

CoD = Coefficient of Determination; COL = Continuous Operating Limit

**2.2.2 P** 

**- 2	On** 

**- Going	Results** 

As noted above, the initial PS

- 11 certificat ion test results were strongly linear . In addition, the on

- going
P

- 2 QA test results were within linear confidence intervals, as illustrated in F igure 1 a through 1 c , where original PS

- 11 correlation data (black diamonds) are compared to subsequent P

- 2 data for RRA (red squares and blue triangles)

, and RCA (black circles) tests conducted since initial installation and

c ertification. A ll of the P

- 2 data fit well within EPA

- accept e d correlation regression line limits ( dashed red lines; ± 25% of the numerical emission limit value from the correlation regression line ) and were within EPA

- defined tolerance and confidence int ervals

. These graphs show that these CEMS remained stable and precise over a period of several year s. T hey w ere also operating well

, and in compliance

, at the time of and immediately following the QAG tests as evidenced with the successful RRA and RCA

tests

.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **10** of **28 2.2.3**  **QAG	Testing Results** 

The three BMP S operating PM CEMS were taken off

- line and challenged with QAG

- generated, NIST

traceable aerosols of known concentrations. The results of this comparison (QAG

- predicted concentration versus PM CEMS measured concentration) are summarized in Table 2 and Figure 2 . These results show very similar correlation parameters for all three of the CEMS with a strong linear relationship (R 2 >0.985) up to about 75 mg/m 3

. Th e average concentration relationship between the
three PM CEMS (C CEMS ) and the predicted QAG (C QAG ) concentration is given by the following linear equation:

C QAG = ( 1.06 ± 0.02) C CEMS – 1.43 ± 0.61 Equation 1

This linear equation is an average of QAG testing of three BAM

- based PM CEMS; s ummarized in Table 2
below: Figure 1. Plots of original PS

- 11 correlation data and ongoing Calibration Results for MSI BetaGuard PM CEMS 1A (a), 2B (b), and 3A (c) at the BMPS**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **11** of **28** Table 2. Summary of CEMS correlation parameters resulting from QAG measurements

Figure 2. Plot of predicted QAG reference aerosol concentration versus measured concentration by three different BAM

- based PM CEMS exhibiting a highly linear relati onship and a slope close to one

The l inearity of the relationship over the concentration range from zero to 75 mg/m 3 was very strong, as represented by a coefficient of determination (R 2 ) of 0.99

. T he uncertainty in the individual slopes was
about 2%

, while the uncertainty in the mean slope was less than 1%. As previously mentioned, t his level of agreement is very impressive
, consider ing that the CEMS factory calibration is based on thin film

s tandards

, while the QAG

- predicted c oncentrations are based on NIST

- traceable components and in

field determination of transport efficiency. The linearity of the relationship between the PM CEMS and
EPA M5B was also quite good

, with a coefficient of determination of 0.99, but the slopes for these same
three PM CE MS were 1.17, 1.19 and 1.63 with an average slope uncertainty of 2 to 4 %. Although the slope uncertainty

, as determined with M5B

, is higher than that obtained with the QAG, the more important issue is why these three, nearly identical ly performing PM CEMS and response functions are reporting significantly different slopes with M5B compared to the QAG and thin film

- based PM CEMS **PM CEMS ID**  **1A 2B**  **3A**

**Parameter**

R 2 (CoD) 0.9 85 0.9 94 0.9 93 m (slope) 1.077 ± 0.04 1.054 ± 0.025 1. 063 ± 0.024 b (intercept)

- 3.103 ± 1.483

- 1.391 ± 1.01

- 0.281 ± 0. 955

**y = 1.06x**

**- 1.43**  **R2 = 0.9899**

0 10 20 30 40 50 60 70 80

0 10 20 30 40 50 60 70 80**Q A** **G C** **o n** **c (** **m g** **/ w** **s c** **m )** 

**PM CEMS (mg/wscm) Draft**  EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **12** of **28** calibrations. A s noted previously, the primary contribution to correlation slopes that deviate from one in this BAM

- based PM CEMS application is hypothesized to be due to probe and transport loss of PM prior to being sampled and measured with the filter tape and beta ga u ge.



### 2.3 **Comparison	of	QAG	and	PS**

**- 11	Results** 

A difference in slopes between the QAG

- and PS

- 11

- calibration results is seen in the data presented in sections 2.2.1 through 2.2.3. This difference is particularly im portant for the development of alternative s to PS

- 11 and P

- 2 based on off

- line QAG measurements. For example, any off

- line measurements with the QAG would have suggested similar in

- stack response functions ( similar slopes within a few percent )

, whereas the PS

- 11 data clearly show the in

- stack response functions are significantly different for CEMS 3A, which exhibit ed a slope of 1.63 ± 0.05 . It is impo rtant to note that this high slope (1.63) is not an outlier. On the contrary, numerous other high slopes have been reported for this same type of BAM

based PM CEMS (MSI BetaGuard)

, one of which exceeded three , as shown in Table 3

. Based on the stability and reproducibility of the three BMPS PM CEMS tested with the QAG, it can he assumed that
off

- line QAG calibrations for these latter CEMS would have been similar to the 1.06 measured with the QAG

. It can also be drawn from these measurements (QAG, CEMS, M5B) that each instrument/method is a precise, independent (NIST

- QAG , thin film

- CEMS factory calibration

, M 5B )

, and accurate measurement/prediction of PM concentration . In addition, it can be concluded that these recorded slope differences , which in some cases exceed the ideal linear slope of one by well over five standard
deviations

, are real and statistically significant. As such, these differences need to be well understood
before an alternative method to PS

- 11 and P

- 2
, based on off

- line QAG measuremen ts , can be proposed
to the EPA

.
Table 3 lists correlation parameters from a comparison of concentrations measured by factory

calibrated MSI BetaGuard PM CEMS and Reference Methods 5 or 5B simultaneously. Examples 13 through 15 show the resulting slopes fro m PS

- 11

- calibrated CEMS at BMPS, while 16 through 18 show the resulting slopes from the same BMPS PM CEMS when c alibrated with the QAG. Overall, the QAG

calibrated CEMS results depict more strongly correlated data based on the R 2 values, as well as slopes that are closer to a 1:1 ratio in CEMS response.

The graphs shown in Figures 3a through 3 c provide side

- by

- side comparison of the correlation plots and
best

- fit linear regression parameters for the three BMPS PM CEMS tested with both PS

- 11 and the QAG.

Our approach to th e problem arising from such statistically different results for the same PM CEMS, despite the apparent stability and precision of each respective method’s measurements, has been to first develop a conceptual physical model (described in Section 3.0 ) to explain the results from these three independent measurements and understand why they fit a linear model so well

, while being so statistically different. Then, based on this new understanding, outlines of alternative performance specificat ions and procedures that use off

- line measurements are suggested and discussed.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **13** of **28** Table 3 . Comparison of Linear Model Fit Parameters for Fifteen BAM

- Ba sed PM CEMS Developed with PS

- 11 In

- Stack or QAG Off

- line Measurements (MSI BetaGuard data)

**Example Slope ± Uncertainty**  **Intercept ± Uncertainty R**  **2 % Slope**  **Uncertainty Notes** *

1 2.053 ± 0.095 + 0.437 ± 0.203 0.971 4.6 IS
2 2.297 ± 0.083 + 0.848 ± 0.240 0.982 3.6 IS
3 1.100 ± 0.082 + 0.376 ± 0.159 0.864 7.5 IS
4 1.805 ± 0.042 + 1.024 ± 0.555 0.991 2.3 IS
5 1.263 ± 0.107

- 0.809 ± 0.280 0.914 8.5 IS
6 1.462 ± 0.045

- 2.689 ± 0.871 0.988 3.1 IS
7 1.529 ± 0.058

- 0.222 ± 0.291 0.977 3.8 IS
8 2.665 ± 0.134

- 0.923 ± 0.852 0.957 5.0 IS
9 1.355 ± 0.088

- 0.493 ± 0.901 0.919 6.5 IS
10 1.488 ± 0.054

- 0.298 ± 0.545 0.977 3.6 IS
11 3.702 ± 0.125

- 0.820 ± 2.582 0.983 3.4 IS

12 1.844 ± 0.114 + 0.058 ± 1.175 0.945 6.2 IS 13 (1A

- PS

- 11) 1.166 ± 0.025 + 0.322 ± 0.501 0.992 2.1 IS 14 (2B

- PS

- 11) 1.190± 0.043

- 2.043 ± 0.962 0.983 3.6 IS 15 (3A

- PS

- 11) 1.625 ± 0.054

- 1.170 ± 0.532 0.982 3.3 IS 16 (1A

- QAG) 1.077 ± 0.036

- 3.103 ± 1.483 0.985 3.3 OL 17 (2B

- QAG) 1.054 ± 0.025

- 1.3591± 1.01 0.994 2.4 OL 18 (3A

- QAG) 1.063 ± 0.024

- 0.81 ± 0.955 0.993 2.3 OL
* IS = In

- Stack; OL = Offline**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **14** of **28** Figure 3

. Comparison of PS

- 11/PM CEMS and QAG /PM CEMS resp onse functions for 1A (a) , 2B (b) and 3A (c) PM CEMS at the BMPS

. **y = 1.169x + 0.3442 R2 = 0.9925** 

0 10 20 30 40 50 60 70

0 10 20 30 40 50 60**M e** **t h** **o d** **5 (** **m g** **/ w** **s c** **m )** 

**PM CEMS (mg/wscm)** 

### PM CEMS 1A PS

**- 11 Calibration** 

**y = 1.0736x**

**- 2.9605**  **R2 = 0.9847**

0 10 20 30 40 50 60 70

0 10 20 30 40 50 60**Q A** **G C** **o n** **c (** **m g** **/ w** **s c** **m )** 

**PM CEMS Conc (mg/wscm)** 

### PM CEMS 1A QAG Calibration 

## (a)

**y = 1.05x**

**- 1.35** 

**R2 = 0.994**

0 10 20 30 40 50 60 70 80

0 20 40 60 80**Q A** **G C** **o n** **c (** **m g** **/ w** **s c** **m )** 

**PM CEMS Conc (mg/wscm)** 

### PM CEMS 2B QAG Calibration

**y = 1.1937x**

**- 1.9916**  **R2 = 0.9826**

0 10 20 30 40 50 60 70 80

0 10 20 30 40 50 60 70 80**M e** **t h** **o d** **5 (** **m g** **/ w** **s c** **m )** 

**PM CEMS Conc. (mg/wscm)** 

### PM CEMS 2B PS

**- 11 Calibration**  

## (b)

**y = 1.0628x**

**- 0.3636** 

**R2 = 0.9931**

0 10 20 30 40 50 60 70 80

0 10 20 30 40 50 60 70 80**Q A** **G C** **o n** **c (** **m g** **/ w** **s c** **m )** 

**PM CEMS Conc (mg/wscm)** 

### PM CEMS 3A QAG Calibration

**y = 1.6258x**

**- 1.2604**  **R2 = 0.981**

0 10 20 30 40 50 60 70 80

0 10 20 30 40 50 60 70 80**M e** **t h** **o d** **5 (** **m g** **/ w** **s c** **m )** 

**PM CEMS Conc. (mg/wscm)** 

### PM CEMS 3A PS

**- 11 Calibration**  

## (c)**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **15** of **28** 

## 3.0 **Proposed	Model s** 

**3.1 Overview** 

As discussed in this report, a lternatives to EPA ’s PS

- 11 and P

- 2 are needed . Although off

- line calibration of PM CEMS with an independent reference aerosol generator like the QAG holds great promise, off

- line QAG calibrations have not demonstrated distinct applicability to in

- stack response functions for BAM

based PM CEMS (CES 2 012) . Although the data presented in Section 2.0 for BAM

- based PM CEMS like the BetaGuard are encouraging, the differences between off

- line and in

- stack calibrations are large relative to the statistical uncertainties. The factors responsible for these st atistically significant
differences need to be understood before reliable alternatives to PS

- 11 and P

- 2 can be developed, and before they are likely to be accepted by the EPA. One possible starting point for understanding the
causes of these observed diff erences is to posit a physical model describing the physical parameters that might influence the system being measured (stack gas PM aerosol), the measurement systems (M5, M5B, CEMS)

, and statements of assumptions implicit in a theoretical mathematical mod el , as described
in Section 3.2

. Following the physical model description, we present a linea r mathematical model that
defines BAM

- based PM CEMS data variability and a discussion of how this physical model influences the correlation parameters, the consis tency of field measurements with the model

, and model implications.



### 3.2. **Physical	Model**

A simplified physical model of our system is schematically illustrated in Figure 4 . This system includes not only the measurement systems, but also the system being measured since variability in both can contribute to observed variability in aerosol PM concentration.

Figure 4. Schematic illustration of proposed physical model of the PM deposit measurements for both EPA Reference Method 5 and extractive BAM

- based PM CEMS

S tack gas PM aerosol s consists of a suspension of liquid and solid particles of varying size and composition traveling at high velocities (typically 30 to 50 mph), at relatively high temperatures (about**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **16** of **28** 150° to 350°F) and moisture conditions that range up to super

- saturation. These conditions can be relatively dynamic

, with mass being exchanged between phases

, and can be strongly influenced by a range of process operations including fuel type, combustion characteristics, emission controls, additives, etc. However, in the case of coal

- fired power plants, these conditions are generally maintained relatively constant so as to assure optimum operational efficiency while consistently meeting required emission limits. These aerosol characteristics are important because they can aff ect PM CEMS sampling and transport efficiency as well as contribute to potential measurement artifacts.

The objective of both EPA M5 and PM CEMS is to measure the “true” stack PM concentration. In the case of M5, a traverse of the stack is conducted while an isokinetic sample of known flow (volume) is drawn through a nozzle, probe, filter and flow monitor. Although a substantial portion of the PM may be deposited in the probe, this deposit is recovered as part of the M5 procedure and added to the PM depos ited on the filter. This total PM mass is divided by the volume sampled to calculate the stack gas PM concentration, which

, by definition

, is assumed to be the “true” stack concentration. Although the
referenc e method is good, it is not a perfect measure of the “ true ” stack concentration. The M5 reported results are only an estimate of the true stack gas concentration. The reference method (M5) will have to varying degrees both systematic and random uncertainties associated with each estimate of
the tru e concentration due to such variables as local turbulence, deviations from isokinetic sampling conditions, errors in pitch and yaw, flow uncertainties, less than 100% PM recovery from the probe, acid filter artifacts, sample handling, contamination, etc.

The PM CEMS also attempts to collect a representative sample of the stack gas by collecting an isokinetic sample, but from a single point in the stack that has been generally selected to represent the mean traverse concentration. The PM aerosol is transp orted through a probe and transport component before it is drawn through a filter tape where the PM is deposited and its mass measured with a beta
attenuation sensor. Although some PM mass is deposited in the CEMS probe and transport components, it is not recovered, but is periodically purged from the sampling line with a “blow back” step. These PM CEMS limitations are well recognized by the EPA, which is one reason why the EPA insists on calibrating PM CEMS with in

- stack M5 measurements as part of PS

- 1 1. I mplicit with this calibration requirement is the assumption that aerosol features that might affect PM deposition in the CEMS probe are constant with time. There are, of course, other systematic bias and random errors that
can contribute to the uncerta inties and variability of both M5 and PM CEMS measurements

, as well as process changes

, that can vary the characteristics of the aerosol and subsequently the quantity of PM CEMS probe deposition.

What is clear from this simplified physical model and the QA G/PM CEMS results summarized in Section
2.0 is that the PM CEMS beta attenuation sensor provides an accurate, precise

, and reproducible measure of mass deposited on the CEMS ’ filter tape. And, although the in

- stack aerosol conditions might be significantl y different from the off

- line QAG aerosol, the BAM

- based PM CEMS’ mass sensor does not detect this difference

, because it does not come in direct contact with the aerosol, but only quantifies the mass deposited on the filter tape. Consequentially , it is reasonable to assume 1) the operation of the beta attenuation sensor functions the same under QAG aerosol conditions as under stack gas sampling conditions and 2) differences in BAM

- based PM CEMS comparisons between the QAG**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **17** of **28** off

- line measurements an d M5 in

- stack measurements are due primarily to differences up

- stream of the
BAM

- based PM mass sensor , assuming a representative sampling location in the stack is chosen

. For the PM CEMS, t hese might include differences in probe and transport conditio ns s uch as nozzle diameter,

yaw, pitch, and temperature ; transport tubing diameter, length, polish, and bends ; sampling flow rate ; filter tape sampling efficiency and chemistry

. S tack conditions might include stack gas characteristics
such as moisture content , PM size distribution, free acid content, presence or absence of droplets, and
gas temperature

. P lant conditions might include plant process es and controls, operating conditions, additives, scrubber solution chemistry, coal type, de

- mister efficiency, et c.

Thus, the conceptualized physical model that forms the foundation of our attempts to understand the
contributors to differences in off

- line QAG calibrations of PM CEMS and in

- stack M5 calibrations of these same PM CEMS is a simplified model composed of five major components:

 PM CEMS beta attenuation sensor

 PM CEMS sampling and transport

 Stack gas aerosol properties

 QAG aerosol

 Reference Method
These will be discussed in the following subsection as the y impact the mathematical form and components of th e linear calibration equation.



### 3.3 **Mathematical	Model**

It is clear from the data presented in Section 2.0 that the relationship between the QAG

- predicted concentration, the BAM

- based PM CEMS measured concentration

, and th e M5 measured concentration
is linear as illustrated by the plots presented in Figure 3 and data in Table 3

. T he mathematical form of the classical slope/interce pt form i s noted below in Equation 2:



## = + Equation 2

w here Y is the QAG

- predicted aerosol concentrati on or M5 measured concentration , m is the slope (representing influence of variables proportional to X) , X is the BAM

- based PM CEMS measured
concentration
, and b is the intercept (representing the influence of constants independent of X)

.

As noted in Section 2. 0, most of the variability in the data is driven by the variability in the concentration and there is minimal variability associated with general data scatter as evidenced by the high observed coefficient of determination ( R 2 = 0.99 )

. In addition, the var iability between the slope s is large (1 to 3.7 ) relative to the statistical uncertainty (about 0.05) in the slope measurement

, while the variability in the intercept (1 to 3) is large relative to its statistical uncertainty (about 1). As such, the primary focus is on the slope and the variables that are likely responsible for differences between slope measurements (calibration factors) made with a QAG

- generated aerosol

, as compared to slope
measurements made with in

- stack M5 measurements of stack gas aeros ols. The primary objective of**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **18** of **28** this section is to review those parameters that are likely to have significant impacts on the slope and intercept, and relate them to this linear model.

As noted above, the true PM concentration (C true ) can be expressed as a function of the reported M5 concentration (C 5 ), plus or minus a systemic bias (C 5 B ) and random (C 5 R ) uncertainty or error terms, as noted below in Equation 3:

Equation 3

Similarly, the true PM concentration can b e expressed as a function of the reported PM CEMS

concentration 

### (C C ) , its known and unknown bias and random uncertainties or err ors , as noted below in Equation 4:

Equation 4

Where : is the concentration bias due to PM deposited in the probe and transport line

is an acid artifact bias due to vapor phase acids reacting with a basic filter
is a single po int bias (Assumption: SPB minimized by selecting a CEMS sampling point close
to traverse average concentration)

is other unknown bias
is concentration error associated with random measurement variability

Combining Equations 3 and 4 , and solving for the M5 reported concentration (C 5 ) , w e obtain the following equation:

Equation 5

The terms on the right side of Equation 5 can be grouped into three categories as indicated in Equation 6
below :

If we assume that probe and transport losses are proportional to PM CEMS reported concentration ( = )

, where k equals a constant value, the bias terms ( ± ± ± ) are assumed to be nearly constant, and the third category ± contains random variables for both the CEMS and M5; Eq uation 6 can be simplified to the following classic linear relationship : 

# = ± ±

= +

− ± ± ±

= +

− ± ± ± ± ±

= [ + ] + [

− ± ± ± ] ± [ ± ]

**B R** **Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **19** of **28** Equation 7

The random component of variability (“R”) in E quation 7 is actually a function of both the concentration (C c ) and constant bias (B) terms. It is important to note that the probe and transport losses are proportional to concentration only to a degree, but, in fact, may also be a function of such variables as particle size distributions, dissolved and suspended solids in droplets downstream of wet scrubbers, and
othe r factors affecting the n ature of the stack gas aerosol. In a perfect world 

### C C 

### = C true 

### = C 5 where m = 1, k = 0 and B = 0. More realistically, k and B are not equal to zero and m = 1+k. One can thus conclude that the slope of the in

- stack PM

- CEMS respons e function can be estimated from a measurement of the probe and transport PM deposit r elative to the CEMS

- measured PM concentration ( /C C ); that is

m=1+ /C C .


### 3.4			Model	Evaluation

As noted above, a number of variables can influence the measured PM aerosol concentration

. I t is important to estimate the magnitude of the more significant potential variables. Examples of these variables and the magnitude of their potential range of impact are listed in Table 4. The CEMS and M5
measured co ncentrations in EGU emissions are expected to range from about 1 to 100 mg/m 3 . BAM

based PM CEMS probe deposits are expect ed to have the largest influence on deviations from true
concentration measurements and are expected to range from 10 to about 75% of the “true” concentration based on the measured slopes (Table 3) and the above discussed model. Acid artifacts (vapor phase acid reactions with glass fiber filters) represent an example of a variable that is likely to be relatively constant, independent o f the PM concentration and have a magnitude less than about 5% of
the PM concentration. Although this potential acid artifact could be a higher percentage for sources with lower PM concentrations, these lower PM concentrations are typically achieved with wet scrubbers which also remove most of the acids that are likely to react with BAM

- based PM CEMS filter tapes. The single point bias is expected to be small

, in part because large differences in PM are not expect ed in the stack at the point where measure ments are made, but also because the point selected for the probe nozzle is selected to minimize this difference. As such, its magnitude is expected to be substantially less
than about 5%. Other BAM

- based PM CEMS biases are expe cted to be small because t he QAG test bias
was small for all three of the BAM

- based PM CEMS. Method 5 bias is also expected to be small in part because it is a reference method. Random errors associated with the CEMS, M5 and QAG are expected
to be small based on the small amount of data scattered and high coefficient of determination observed in the regression plots. Based on these estimates, it seems reasonable to assume/conclude that measured M5/BAM

- based PM CEMS regression slopes greater than 1 are an indicator of the primary influence of probe deposits. Thus, in

- stack BAM

- based PM CEMS response functions might be estimated either by 1) measuring probe deposits directly or 2) by comparing simultaneous M5 and PM
CEMS in

- stack concentration measurements at typical or normal operating conditions, or 3) by eliminating or minimizing these losses.



## = ( 1 + ) + ±

m**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **20** of **28** Table 4

. Examples of potential variables influencing measured PM CEMS concentration an d their potential range

**Variable CEMS** 

**Correction Percent of PM** 

**Concentration Expected** 

**Range (mg/m**  **3 )**  **Notes**

1 Method 5 C 5 -

--- 1

- 100 Expected for Coal

- Fired Utility Boilers CEMS C c -

2 CEMS, Probe Deposit C c PD (+) 1 0

- 7 5% 0.01 → 7 5 Fraction of C c lost in the probe during sampling transport

3 CEMS, Acid Artifact Bias C c AAB (

- ) <5% 0.1 →5 Function of filter and acid concentration

4 CEMS, Single Point Bias C c SPB (±) <5% <0.01 →5 Correction in PM concentration expected to be proportional, but small

5 CEMS, Other Unknown Bias C c O U B (±) <5% <0.01 →5 Other unknown bias, should be small because QAG difference is small

6 Method 5, Bias C 5 B (±) <5% <0.01 →5 Bias is expected to be small because M5 is a federal reference method

7 CEMS, Random

error C c R (±) < 5% <0.01 →5 Random CEMS error, such as tape position and counting statistics, are expected to be small and independent of concentration

8 Method 5, Random

error C 5 R (±) <10% <0.01 →10 Random uncertainties in flow, isokinetic sampling, PM recovery, mass determination, etc.

The influence of probe loss on the in

- stack response function can be seen in the data from the 15 BAM

based PM CEMS listed in Table 3. The PM CEMS/ M5 regression data has been re

- ordered according to increasing slope in Table 5. Additional details regarding the CEMS transport characteristics, PS

- 11 correlation technique, Plant/EGU emission controls have been added, as they might impact either the
in

- s tack aerosol characteristics or CEMS probe and transport loss. The deposition and aerosol characteristics are ranked based on their potential to and/or likelihood of deposition in the probe and transport components prior to reaching the filter tape and BA M sensor. Generally speaking, an increase in deposition and aerosol characteristic ranking is assumed with an increase in slope. Although this is not a perfect correlation, it is supportive of the model discussed earlier in this section where the slope i s dominated by the fraction of PM deposited in the probe and transport. (Note: this paragraph will be edited pending the addition of data in Table 5)**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **21** of **28 P** **r o** **b e** **( d** **/ L** **) T** **r a** **n s** **p o** **r t** **( d** **/ L** **) C** **o a** **l T** **y p** **e b** **S a** **t u** **r a** **t e** **d ?** **S y** **s t** **e m** **( s** **) c** **A d** **d i** **t i** **v e** **s D** **e m** **i s** **t e** **r ?** 31.100VaryingunitloadBituESP,SCR,WFGD,WESPNH3orCO(NH2)2,lime131.166___/45'PulvNoSCR,LNB,SOFA,SBS,WVSNH3,NaHSO3,lime141.190___/80'PulvNoSCR,LNB,SOFA,SBS,WVSlime,NH3,NaHSO351.263SlightESPdetuningPRBESP,SCR,WFGDNH3,lime91.355ESPdetuning,PairedtrainsBituESP,SCR,WFGDNH3,lime61.462ESPdetuningBituESP,SCR,WFGDNH3,lime101.488ESPdetuningBituESP,SCR,WFGDNH3,lime71.529BaghousedetuningBituBH,SCR,WFGD,WESPNH3,lime151.625___/80'PulvYesESP,SCR,LNB,SOFA,SBS,HWSNH3,lime,NaHSO341.805ESPdetuningBitu&PRBESP,SCR,WFGDNH3,lime121.844ESPdetuningLSSBESP-12.053B3InjectionofplantashupstreamofIDfanWasteSCR,BHNH3,PlantAsh22.297B3InjectionofplantashupstreamofIDfanWasteSCR,BHNH3,PlantAsh82.665ESPdetuning,PairedtrainsBituESP,SCR,WFGDNH3,lime113.702ESPdetuningLSSBESPw/SO3injection-b.Bitu=bituminous,Pulv=pulverized,PRB=PowderRiverBasinCoal,LSSB=LowSulfur,Sub-Bitominous.c.SCR=SelectiveCatalyticReduction,ESP=ElectrostaticPrecipitator,WFGD=WetFlueGasDesulfurization,WESP=WetElectrostaticPrecipitator,WVS=WetVenturiScrubber,LNB=LowNitrogenOxideBurner,SOFA=SeparateOver-FiredAir,SBS=SodiumBisulfateInjectionSystem,HWS=HorizontalWeirScrubber.Unitsarelistedinestimatedorderofemissioncontrolprocess.d.Aerosolrankingwouldbeafurthersubjectiveratingtooltoillustratethelikelihoodofdepositionontoprobeduetothetypeofaerosol,arankingof‘10’beinghighlylikelyandarankingof‘1’beingveryunlikely.Saturatedaerosolsresultingfromtheuseofwetscrubbers,forexample,wouldbemorelikelytodepositduetothehighpresenceofdissolvedsoliddropletsandwaterandthereforewouldreceiveahighrating.Ex.=Examplenumber,sameasshowninTable3.m=slopeforPS-11calibrationresults,showninTable3ofthisreportCEMS=ContinousEmissionsMonitoringSystemd/L=diameter/Lengtha.DepositionrankingisasubjectiveratingtooltoillustratethelikelihoodofdepositionontoprobeandtransportlinesduetothecharacteristicsoftheCEMS,arankingof‘10’beinghighlylikelyandarankingof‘1’beingunlikely.Examplesofparameterswhichmightdeterminetherankingareasfollows:probe/transportdiameter,probe/transportlength,numberofbendsinthesystem,andtheaerosol’svelocity.Table5.ComparisonofLinearModelFitParamenters(InOrderfromSmallesttoLargestSlope)forFifteenBAM-BasedPMCEMSCorrelatedwithM5andPS-11In-StackMeasurements**E x** **. m** **C E** **M S** **T r** **a n** **s p** **o r** **t C** **h a** **r a** **c t** **e r** **i s** **t i** **c s** **D e** **p .** **R a** **n k** **a P** **S -** **1 1** **C o** **r r** **e l** **a t** **i o** **n ,** **M i** **d /** **H i** **g h** **P M** **C o** **n c** **. T** **e c** **h n** **i q** **u e** **P l** **a n** **t C** **h a** **r a** **c t** **e r** **t i** **s t** **i c** **s P** **l a** **n t** **E m** **i s** **s i** **o n** **C o** **n t** **r o** **l A** **e r** **o s** **o l** **R a** **n k** **d Draft**  EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **22** of **28** 

## 4.0 **Proposed	Alternatives	to	PS**

**- 11	and	P** 

**- 2** 

**4 .1**  **PS**

**- 11**  **and	P**

**- 2** 

PS

- 11 establishes procedures and performance requirements that must be met to establish initial
certification of PM CEMS ’ ability to demonstrate a facility is in compliance with emission limits. It is different from performance specifications for gaseous pollutants for several reasons. First
, the type and characteristics of PM aerosols in stack gas can vary from source to source

. S ome PM CEMS , such as light scattering

- ba s ed CEMS, are sensitive to such characteristics as particle size changes, water droplets,
dis solved and suspended solids within droplets, sta ck gas velocity changes, etc. Secondly , PS

- 11 is
different because EPA

- approved PM standard calibration aerosols are not available to independently certify a PM CEMS ’ in

- stack response function

. Thirdly, PM aerosols are different from other gaseous pollutants because a significant fraction of PM can be lost in the sampling and transport components of
a PM CEMS.

A key component of PS

- 11 is a calibration procedure based on simultaneous M5 and P M CEMS measurements over a range of concentrations. This initial correlation test (calibration) is performed to develop a relationship between PM CEMS ’ response and the manual reference method (M5) results over a range of PM concentrations. A minimum of 1 5 valid runs must be conducted, each consisting of
simultaneous PM CEMS and M5 measurements covering the full range of PM concentrations. It is important to note that this initial correlation test is not an independent check of accuracy, but an on

- site
calibration of the PM CEMS that is dependent on the aerosol characteristics at the time of the tests at the specific facility. It is this initial correlation test that is so onerous

, due to the need to att ain a range of in

- stack PM concentrations that are only obtained by modifying normal plant operations . It is this
characteristic of PS

- 11 that is proposed for modifi cation in the proposed alternative method (PS

- 11B)
outlined in Subsection 4.2.

Procedure 2 establishes minimum requirements for ev aluating the effectiveness of PM CEMS quality control (QC) and quality assurance (QA) proced ures, and assess es PM CEMS data quality by estimating data accuracy. One relevant tool in P

- 2 used to perform this function is a relative correlation audit (RCA). The RCA is similar to the initial correlation test in PS

- 11 except only 12 simultaneous M5 test runs are required in P

- 2
, instead of the 15 test runs required in PS

- 11. Initial correlation tests are required at
the time the PM CEMS is installed whereas RCAs are required to be performed periodically as defined by regulations over the lifetime of the CEMS.

The following outlines of proposed alternative specification (PS

- 11B) and procedure (P

- 2B) focus on
modificati ons to the initial correlation tests and on

- going RCA tests and assume most other aspects
remain as stated in the original specifications and procedures.



### 4 **.2 Proposed	Alternative:**  **Performance	Specification	11b**

As noted earlier, off

- line QAG calibrations o f BAM

- based PM CEMS cannot be used alone to accurately and reliably predict in

- stack response functions for PM CEMS. However, a s established in Subsection
3.3
, the in

- stack response function slope (m) could be determined if the ratio of CEMS probe deposit**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **23** of **28** ( ) to CEMS reported concentration (C c ) could be determined; i.e. m = 1+ /C C . It is this realization that forms the basis of the following outli ne for a proposed alternative performance specification to PS

11.



### Outline for Proposed Alternative PS

**- 11B** 

A lternativ e performance specification (PS

- 11B) might consist of the following five modified steps to the
initial correlation tests :

1. Perform an off

- line independent certification of the PM CEMS linear range using QAG

generated reference aerosols at the site (e.g. CFPP) of PM CEMS installation

.
Independently certify ing the linear range of the BAM

- based PM CEMS using a QAG

- generated
refer ence aerosol has the potential to establish the linear range well beyond the emission limit without requiring modification of plant processes and is independent of the original thin

- film
calibration of the BAM

- based PM CEMS. The QAG reference aerosol conc entrations will be collected from four (4) distinct ranges: <10%, 20

- 40%, 50

- 70%, and 80

- 120% of the PM CEMS ’

span or PM emissions limit. At least four ( 4 ) QAG data point s per concentration range, for a total of 16 data points, should be performed for initial certification.

2. Determine probe and transport losses

Determine the “k” constant ( /C C ) for stack gas at typical operating conditions for the EGU
and PM CEMS being tested. This ‘k” factor is relatively constant as a function of concentration, as evidenced by the high degree of linearity of the BAM

- based PM CEMS demonstrated both with the QAG and M5 correlations.

The “k” factor can be determined either directly by measuring the probe deposit or by multiple
simultaneous paired M5 and PM CEMS mea surements (M5 = total, = total

- C C ). The total number of simultaneous tests will depend on the specific acceptance criteria determined for
alternative PS

- 11B.

3. Calculate the in

- stack response function

.

Calculate the in

- stack response function b ased on data collected in steps 1 and 2, where the slope (m) equals 1 +k (m = 1+k )

4. Perform independent certification of the BAM

- based PM CEMS in

- stack response function using simultaneous M5 measurements

.
Complete 3 runs of M5 by collecting PM data from a full stack traverse at normal , “as found” operating conditions

. The number of traverse points for each stack is determined based on stack diameter and shape (circular versus rectangular), as described in EPA Method 1. Using the

response function determine d in Step 3, calculate the average PM CEMS concentration and
uncertainties during the time of M5 traverse measurements and compare the two results

.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **24** of **28** 5. Compare intercept of M5 results to the QAG PM CEMS results.

If the two results are within one standard dev iation of each other , make no adjustments to the calculated response function. If it is outside these limits, but within three standard deviations, adjust the intercept to match the M5 results. If these results differ by more than three standard
deviatio ns, repeat steps 1

- 4. Additional acceptance criteria will be defined as the alternatives are further developed.

The remainder of alternative PS

- 11b would be essentially the same as stated in the original PS

- 11.



### 4

**. 3**  **Proposed	Alternative: Procedure	2**  **B**

The key modification to P

- 2 in the proposed alternative Procedure 2B (P

- 2B) is t he replace ment of the
current RCA tests with the s ame five steps noted in the PS

- 11B outline above , except there will be 12 repetitions across the linear concentration range ( S tep 1 ) . This on

- going QA/QC certification test would be performed on the same schedule as the current P

- 2 test schedule.



### 4.4 **Evaluation	of	Proposed	Alternative	Methods**

Additional PS

- 11 datasets for MSI BetaGuard PM CEMS are available

, as noted in Subsecti on 2.3, Table 2.
Results from QAG testing of three MSI BetaGuard PM CEMS at the BMPS determined that there wa s very little difference in the off

- line

, QAG

- based response functions; i.e. coefficients of determination for all three PM CEMS were greater than 0.985 and the slopes were within ±2% of each other . Because of the similarity in the QAG measurements of these three PM CEMS , which were manufactured at different times, it i s reasonable to assume the factory calibrations for the other 13 PM CEMS

, for which we have
PS

- 11 data, would also be similar. As such, it is possible to apply PS

- 11B to these 13 sets of PS

- 11 data to demonstrate the application of the proposed model and alternative PS

- 11B.

Table 6 summarizes key aspects of th e PS

- 11 and PS

- 11B comparison. The entirety of the application of proposed alternative PS

- 11B to previously collected PS

- 11 data is provided in Appendix A of this report.
The PS

- 11 data was provided by MSI, the manufacturer of the BetaGuard PM CEMS. The PS

- 11B data

was c alculated using steps similar to t he five steps outlined for PS

- 11B in Section 4.2. The steps applied
to the MSI data are summarized below :

Step 1. Except for those PM CEMS where QAG data was collected (CEMS 1A, 2B, and 3A), the
off

- line CEMS response was assumed to equal the average slope of the three BMPS PM CEMS (1.06x

– 1.43) , as described in the first paragraph of this section.

Step 2. The probe/transport loss constant (k) was calculated by determining the probe deposit
as the difference between individual, paired PM CEMS and M5 or M5B concentration

measurements (normal operating range assumed). T he “k” value was then calculat ed by dividing the probe deposit amount by the PM CEMS concentration . (Note: the slope of the in

- stack PM

CEMS response f unction is estimated from a measurement of the probe and transport PM deposit relative to the CEMS

- measured PM concentration ( /C C ); that is m=1+ /C C . ). The**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **25** of **28** individual k

- values were then averaged to create the k

- constant for use in the next step of this

process.
Step 3. The in

- stack slope (m = 1 +k) was calculated using the formula defined in Section 3.3 of this report. The intercept (b) was evaluated using three approaches: 1)b set equal to zero, 2) b set equal to the offline QAG intercept, and 3) b defined by the M5 measured concentration at normal operating conditions. The in

- stack concentration using the calculated slope with b=0 and
b=M5 normalized were similar and best matched the PS

- 11 value. The percent errors in the predicted concentr ation at the emission limit in Table 6 were calculated using the zero intercept option.
Step 4. The independent certification of BAM

- based PM CEMS in

- stack response function was simulated using the true concentration calculated in Step 3. The standard devi ation for each
concentration was estimated , and the difference between the M5 (PS

- 11) concentration and PS

11 B concentration was determined.

Step 5. The results from Step 4 are compared to the PM emission limit for each CFPP to see if EPA criteria
are met. 

### Table 6. Comparison of PS

- 11 & PS

- 11B Calibration Correlations F or 14 BAM

- Based PM CEMS a

**Example Slopes**  **% Error of PS**

  ** 11b Slope from** **PS**

**- 11**  **PM Emission**

**Limit at CFPP % Error in the** 

**Predicted Conc. at the Emission**  **Limit PS** 

**- 11**  **PS**

**- 11b** 

1 2.053 ± 0.095 2.130 ± 0.352 3.7 9.9 0.8
2 2.297 ± 0.083 2.575 ± 0.190 12.1 9.9

- 2.3
4 1.805 ± 0.042 1.903 ± 0.203 5.4 53.2*

- 3.2
5 1.263 ± 0.107 1.019 ± 0.204 19.3 6.9* 12.4
6 1.462 ± 0.045 1.333 ± 0.104 8.8 55.5* 4.8
7 1.529 ± 0.058 1.433 ± 0.117 6.3 11.8 4.8
8 2.665 ± 0.134 2.392 ± 0.334 10.2 29.0 8.2
9 1.355 ± 0.088 1.163 ± 0.134 14.2 27.0 14.7
10 1.488 ± 0.054 1.430 ± 0.224 3.9 37.8* 3.3
11 3.702 ± 0.125 3.698 ± 0.455 0.1 182.6*

- 0.3
12 1.845 ± 0.114 1.896 ± 0.197 2.8 43.1*

- 2.6 13 (1A) b 1.169 ± 0.025 1.180 ± 0.060 0.9 97.9

- 0.6 14 (2B) b 1.194 ± 0.043 1.078 ± 0.079 9.7 94.4 8.6 15 (3A) b 1.626 ± 0.054 1.321 ± 0.149 18.7 93.2 21.7
Avg. 7.9 3.7

StDev. 5.7 6.0
% RSD 72 164

a Example 3, which was presented in Tables 3 and 5, was omitted from this table because of excessive uncertainty in the slope (40%) and results were more than 5 SD from the mean.
b These examples are BetaGuard PM CEMS from the BMPS with individual off

- line QAG measurements. * Emission limit was estimated as 125% or highest PS

- 11 reading.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **26** of **28** Table 6 compares the correlation slopes obtained with PS

- 11 to those obtained with PS

- 11B, as well as
the slopes’ uncertainties and percent uncertainties at each plant’s emission limits. The average percent
error or difference between PS

- 11B

- and PS

- 11

- determined slopes was 8.3%

, with a range of 0.1% to
19.3% , and f or all but one case

, CEMS 3A
, falls within the sum of one standard deviation of each
parameter. T he average percent error in the predicted concentration at the emiss ion limit is only +5% and ranged from a low of

- 3. 2 % to a high of +21.7%, which places all of the slopes within the EPA ’s P2 ± 25% limit. Although this data is far from definitive, it is encouraging and strongly supportive that PS

- 11B
is a viable candida te for an alternative to PS

- 11.

The QAG

- based PS

- 11B has the advantage that it would not require extrapolation to the emission limit and it would eliminate the need to modify normal plant operations and aerosol characteristics as is the case during perform ance of PS

- 11 and P

- 2. In addition, PS

- 11B is likely to have less pollution associated with its implementation and is expected to be easier and lower cost to implement.



### 4.5 **Summary	of	Benefits	of	Proposed	Alternatives**

In order to gain acceptance by the EP A, a newly proposed method should be:

 More stringent than the currently used method,

 Provide a stronger data set with higher statistical strength,

 Improve the “ease of use” for the plant to demonstrate compliance, and/or

 Provide data of equal strength, bu t with improved and lower costs.

We propose that the suggested alternative methods for PS

- 11 and P

- 2 using an off

- line QAG calibration have strong potential to meet several, if not all, of these criteria. Firstly, the off

- line QAG data is capable
of chall enging the PM CEMS over a much broader linear range than is possible under the current PS

- 11. In conjunction with the improved concentration range, the QAG method increases ease of use by not requiring plant modifications in order to meet linear range requ irements. Due to the precise, accurate, and quantifiable aerosols produced by the QAG, as demonstrated in the field, the QAG method is anticipated to provide linear results that meet much more stringent acceptance limits than the +/

- 25% that is currently accepted by the EPA in P

- 2. It is unclear at this time if the newly proposed method will provide cost savings; however, it would eliminate the need to modify or shut down normal operations during performance of PS

- 11 and P

- 2, which would translate to cost savings for the EGU.

Although our current knowledge of BAM

- based PM CEMS functioning in EGUs suggests that an off

- line certification with a QAG cannot be accomplished without knowledge of the probe and transport loss constant, the collection of appropriate data and calculation of the correction factor is not anticipated to be cumbersome. In addition, the calibration of the CEMS can be certified by minimal Method 5 runs, instead of the 12 or more runs required by the current procedures.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **27** of **28** 

## 5.0 **Conclusions and	Recommendations** 

A model has been developed that describes a linear relationship between BAM

- based PM CEMS measured concentrations and 1) QAG

- generated reference aerosol concentrations

, and 2) M5 measured stack gas aerosol concentrations. Key componen ts for this proposed linear model include 1) a slope
whose deviation from 1.0 is due primarily to probe deposits and 2) in

- stack BAM

- based PM CEMS response functions that can be determined using off

- line QAG

- generated reference aerosols and in

stack measur ement s at typical stack conditions.

This report outlines a lternatives to PS

- 11 and P

- 2 that do not require altering plant processes. These
alternatives meet most , if not all, of the criteria for approval of alternative methods by the EPA.

Based on the enco uraging results from QAG testing of the three BAM

- based PM CEMS installed at BMPS
and the successful application of the proposed model to fourteen BAM

- based M CEMS’ data sets, it is recommended that an alternative performance specification (PS

- 11B) and on

- going performance procedure (P

- 2B) be further developed and formalized. Once formalized, it is recommended that the se alternatives be submitted to the EPA to solicit their comments and contributions to the development of a field demonstration plan. It is further recommended that the field demonstration tests be conducted to confirm the theories presented in this report. Finally, a report supporting a request for the EPA to approve the alternative PS

- 11B and P

- 2B should be submitted after further field de monstration tests are
conducted.



## 6.0 **References**

Cooper Environmental Services, LLC, 2012. Draft Technical Update: QAG Modifications and Field Testing
with BAM

- based CEMS. Prepared for Electric Power Research Institute, Project EP

- P44336/C19235.
December 2012.

Environmental Protection Agency. Method 5

- Determination of Particulate Matter.

Environmental Protection Agency. Method 5B

- Determination of Nonsulfuric Acid Particulate.

Environmental Protection Agency. Performance Specification 11

— Specifications and Te st Procedures for
Particulate Matter Continuous Emission.

Environmental Protection Agency. Procedure 2

— Quality Assurance Requirements for Particulate Matter Continuous Emission Monitoring Systems. Web.

Environmental Protection Agency, 2006. Data Quality A ssessment: Statistical Methods for Practitioners. EPA/240/B06/003. February 2006.

Environmental Protection Agency, Office of Air Quality, 2000. Current Knowledge of Particulate Matter Emission Monitoring. EPA

- 454/R

- 00

- 039. September 2000.**Draft** EPRI Communication: PM

- QAG Model Report January 10, 2013

Cooper Environmental Services, LLC Page **28** of **28** Hatch , Barbara. "Commonwealth of Pennsylvania Department of Environmental Protection." Review of Operating Permit Renewal Application First Energy Generation, LLC Bruce Man s field Power Station Shippingport, Butler County. 24 May 2012. Print.

Jahnke, James A, 2000. Continu ous Emission Monitoring, Second Edition. John Wiley & Sons, Inc. New York, NY.

MSI BetaGuard Data: Provided through email correspondence with Craig Clapsaddle, including examples
of 13 BetaGuard PM CEMS PS

- 11 data and 2010 to 2012 P

- 2 data (RCA and RRA). E mail correspondence, 11/8/2012 and 11/29/2012