1 Summary of Discussion and Action Items from 10/21/2010 HPBA

- EPA Wood Stove NSPS Meeting

Date of Meeting : October 21, 2010 Time: 8 : 3 0 am

– 1 1 : 3 0 a m

Purpose: The purpose of the meeting was for HPBA to present information to EPA on test methods and othe r topics for consideration in its deliberation of possible revisions to propose to the wood heater NSPS (40CFR Part 60, Subpart AAA) . HPBA provided presentation s to help guide the discussion. The agenda of topics was 1) Test Method Variability; 2) Method Comparison; 3) Pellet Ash; 4) Economics; and 5) PFI (Pellet Fuels Institute). Powerpoint presentations and handouts provided by HPBA are attached to the summary.

Participants: Allan Cagnoli, HPBA John Crouch, HPBA Rick Curkeet, Intertek Daniel Henry, Hearth and Home Technologies Bob Ferguson, HPBA David Menotti, Crowell & Moring for HPBA Amanda Aldridge (on phone), EPA Larry Brockman, EPA David Cole, EPA Chebryll Edwards, EPA Greg Green, EPA Larry Sorrels , EPA Mike Toney, EPA Gil Wood, EPA Graham Fitzs imons, EC/R Bill Huang, EC/R

Introduction

• Allan Cagnoli opened by saying that HPBA has spen t a lot of time, money and effort to collect and provide information to EPA

.
• Greg Green e mphasized that just because EPA proposes something, it does not mean it wil l be finalized and that EPA has not made up its mind yet on final rule revisions.

• David Menotti added that HBPA’s efforts were designed to generate robust facts.2 Test Method Variability

- Rick Curkeet presented a Powerpoint and HPBA provided a paper on Tes t Method Variability. The P owerpoint slides are shown in Attachment 1 , and the paper is provided in Attachment 6

. Questions and comments regarding this presentation are summarized below.

• HPBA described the e leme nts of precision: r epeatability , which an swers whether a lab can repeat with similar results; and r eproducibility , which answers whether different labs can get similar results

. o The primary data set available to evaluate test result variability is that generated through the EPA required Accredited Laboratory Proficiency Test Program.

o It is apparent that the repeatability and reproducibility of the test procedures are not very good.

o Even without applying any statistical tools, one can simply look at the results of testing the same stove in the sam e laboratory over two or more years to see the range of intra

- laboratory results.

o Using the results from all the laboratories for all the stoves over all the years of the program, it is possible to assess the inter

- laboratory precision.

o Using 2.8 times th e standard deviation to estimate the potential range of results that could be expected with a 95% confidence level [Ref.: ASTM E177, 28.1], it is clear that the for any given test series the reproducibility is on the order of ± 4.9

– 9.8 grams per hour. T his means that for any emissions rate measured using the EPA test methods, the result could be 4.9 to 9.8 grams per hour higher or lower if the appliance were tested again at a different laboratory.

 Gil Wood asked if this was relative to the mean or a per cent basis.

 Rick Curkeet also stated that the translatability to real world conditions is also an issue here.

o Gil Wood also asked that as devices improve over time, won’t variability decrease?

• A key question HBPA sought to answer in their study is : Where is the variability coming from?

o Is it method related or does it arise from a different source

- that is, a variable performance of the appliance itself.

 To answer this, they s tarted with emissions measurement m ethods ( 5G

1, 5G

- 2, etc. ) and then addressed th e operation side, Method 28 . The y concluded that the emission measurement methods only explained a small part of the overall variability shown by the precision analyses.

o Using the EPA proficiency test data, it is possible to examine several of the various Method 28 parameters for the ir impact on precision, including:3  Impacts of burn rate variations

. The high burn rate variability is substantial, and it is certain that this variability is a contributing factor in the emissions variability. However, Rick C urkeet said that fact that you don’t get the same burn rate at the same oper ating conditions is significant; therefore, burn rate variability does not explain much of the overall variability of emissions rates.

 Impa cts of fuel moisture variation and fuel d ensity variation

. Rick Curkeet stated that by looking at the chart, it is clear that there is no relationship. Gil Wood stated that John Kinsey believes moisture content is important. He also pointed out that this wasn’t done with non

- catalytic stoves. There is a difference between talking about moisture content variability allowed by the method (as opposed to the real world).

o Bob Ferguson said that although intuitively tigh tening method (e.g. moisture content) should improve results, the data is not th ere to support this. Tightening these parameters to improve test precision would simply increase costs and the data show that such tightening would not significantly improve precision.

o Mike T oney asked if lab temperatures were looked at.

 Rick Curkeet resp onded yes, and as well as baro metr ic pressure too, but the impacts can’t be quantif i ed

. Bob Ferguson noted that it was an “eye opener” how these can impact results from the same product.

o The ir conclusion (as stated in their paper), is that v ariability in wood heater emission testing results for any given appliance is most likely a function of the random nature of burning wood, no matter how tightly you try to control the process. Many relatively small, uncontrollable variables that are inherent in the

wo od combustion process can combine to significantly affect the outcome of any given test.

 Larry B rockman emphasized the importance of educating on how to burn properly, and the group agreed.

• Gil Wood said that 85% of stoves sold meet the WA state sta ndard

. o Rick Curkeet stated that the target is now 4.5 gr/hr for non

- cat unit s

.

 Maybe they improve the unit to get it or just get lucky

.
• Gil Wood was interested to know how many test runs were there before certification

run

.
• David Menotti said that the WA standar d took the NSPS compliance margin away.

o What the study show ed is that there is no real difference between a 2 and a 4 gr/hr.

• Rick Curkeet said he would rather test Cat 2 burn rate 5 times and report the average

ra ther than look for the lowest number.4 • Dan H enry said that nobody has worked harder to product clean stoves than Quadrafire.

o The economy has caused them to look for a different market channel. They found it and none of it is certified (because of loopholes and exemptions). Gil Wood stated that E PA is looking at closing certification loopholes.

o Quadrafire has developed two new “eco choice” pellet stoves th at are EPA certified at 3 gr/hr, and predicts sales of 20,000

– 30,000 units/year.

Update on Test Method Comparison

- Bob Ferguson provided a p resentation for the group. His Powerpoint slides are shown in Attachment 2. Questions and comments regarding this presentation are summarized below.

• The issue involving the long suspected flaw in the equation used to “adjust” the emission values determin ed using EPA Methods 5G

- 1 and 5G

- 3 to EPA Method 5H equivalents was outlined in a report dated March 30, 2010

. o Bob Ferguson said that all points in the report were sent to Gil back in April.

• Bob Ferguson is still doing QA on data and will provide more when he has it , but, so far it looks like the cleaner you get, the more you are penalized under the current correction equation. (e.g. 7 corrects to 9, 0.7 corrects to 1.5)

o Dan Henry said this is why Quadra fire used 5H to certify, even at an extra cost.

o Allan Cagnoli pointed out that the cost to HPBA is an issue, and that this would double the cost of each run.

o HPBA said that paying for correction is too much, and getting data is problematic because of time and money.

o David Menotti asked if EPA want ed HPBA to k eep submitting data (and is there time to submit data?)

o Gil Wood said he would have to think about it.

o Bob Ferguson said that one lab had asked not to do anymore. Bob said 5H requires additional technology. It’s taken months to get the data.

Impact on P ellet Ash

- Bob Ferguson provided a presentation on Pellet Fuel Ash

. His Powerpoint slides are shown in Attachment 3. Questions and comments regarding this presentation are summarized below.

• Dan Henry explained that e very pellet stove tested ha s probably used low

- ash douglas

fir from the P a cific NW, however, pellets that are most commonly available in other areas of the country where pellet heaters are popular are made from hardwood have a higher ash content.5 • Though there is limited data (more is coming), there appears to be a trend between higher ash fuels and higher particulate emissions.

o HPBA state that there was almost no data directly comparing low and high ash wood pellet fuels in the same heater using the same test method.

o Bob Ferguson stated that t here is one softwood versus hardwood pellet test series that has been completed, still needs to be QA’d.

• There was concern over the impacts of BDT since different pellets might produce different results, even when the burn settings are optimized.

o HPBA stat ed that i f this is a BDT list, it could mean hardwood pellet manufacturing may not be able to stay in business.

• Dan Henry made a point that all pellets on the Test Results page were lean b u rners.

Economics Impacts of NSPS “ Straw man ” Proposals on Hearth P roduct Companies

- David Menotti provided the presentation. His Powerpoint slides are shown in Attachment 4. Questions and comments regarding this presentation are summarized below.

• David Menotti recounted that t he current NSPS had a massive and largely unanticipated impact on woodstove manufacturers. It has led to a decre as e in the number of manufacturers (about 400 to 60)

o HPBA emphasized that it is in everyone’s interest to avoid repeating that experience this time around.

• HPBA has therefore taken step s to develop high quality economic impact data for consideration by EPA.

o They hired NERA, a top

- flight economic consulting firm to assist, because NERA is allowed a broader reach. John Crouch noted that some foreign owned companies (e.g., Napoleon and Y odel) are players and the Canadians are critical.

• NERA developed guidance for manufacturers in preparing economic impact assessments.

o The NERA guidance was given to SERs in the SBREFA process for their use in preparing their presentations to the SBREFA pan el.

o HPBA identified a group of manufacturers that are broadly representative of our membership.

 These companies have agreed to perform analyses of the impacts on their businesses of the "straw man" proposals provided to the SBREFA panel, using the NERA gu idance.

o The SBREFA submittal will com e as CBI (pushing for October 31)

. o By earl y next week , Larry Sorrels will get with John Crouch and maybe NERA to discuss the process/question s

.6 Status Report on PFI

- John Crouch led the presentation and provided hando uts (included as Attachment 5)

. Questions and comments regarding this presentation are summarized below

.

• John Crouch said the letter containing the PFI fuel grade requirements was drafted in response to Gil’s comment.

• John Crouch said that t here are many mills that will have difficulty holding to 1% ash.

• Gil Wood said he appreciated what PFI has done here.

Action Items /Next Steps

• Gil Wood and Mike Toney to get back to Bob Ferguson on 5G

- 5H. Bob Ferguson would like to get on a call with Gil Wood and Mike Toney in the future to discuss a plan if they could get more data points.

• By early next week, Larry Sorrels will get with John Crouch and maybe NERA to discuss the process/questions.

• Overall Schedule from Gil Wood

o Proposal in June

o SBREFA panel report is ne xt (EPA is a little late on this)

 SBA/OMB/EPA will have differences that proposal will address

o “Early Guidance” Meeting with AAS this coming Tuesday (Oct. 26, 2010)

o Options selection in December

o Draft preamble in January or February

o Trade Show in 1 st week in March, will be attended by Gil Wood or David Cole , who will give an update.

o Mike Toney is going to spring ASTM Meeting.1 Attachment 1

EPA Wood Heater Test Method Variability Study Analysis of Uncertainty, Repeatability and Reproducibility based on the EPA Accredited Laboratory Proficiency Test Database2 Slide 1

1 

## EPA Wood Heater Test Method Variability Study Analysis of Uncertainty, Repeatability and Reproducibility based on the EPA Accredited Laboratory Proficiency Test Database

Rick Curkeet, PE Chief Engineer

– Hearth Products Intertek Testing Services Robert Ferguson Ferguson, Andors & Company3 Slide 2

2 

# Introduction

• The precision of any test method is an extremely important tool in understanding the limitations of the data generated from the method.

• No rigorous assessment of the precision of the test methods contained in the woodstove NSPS has ever been performed.

• A large data base of proficiency test data from accredited laboratories has been assembled.

• The objective of this paper is to perform that assessment, using the EPA proficiency test data base and broadly accepted tools for assessing repeatability and reproducibility.4 Slide 3

3 

# EPA Test Methods

• EPA Method 28

– Certification and Auditing of Wood Heaters

• EPA Method 5H

– Determination of Particulate Matter Emissions from Wood Heaters from a Stack Location

• EPA Method 5G
- 1

- Determination of Particulate Matter Emissions from Wood Heaters (Dilution Tunnel Sampling Location), Single Filter Train with Dual 100mm Filters (filters at near ambient temperature)

• EPA Method 5G
- 2

- Determination of Particulate Matter Emissions from Wood Heaters (Dilution Tunnel Sampling Location), Method 5H Filter Train (heated front filter with chilled impinger train)

• EPA Method 5G
- 3

- Determination of Particulate Matter Emissions from Wood Heaters (Dilution Tunnel Sampling Location), Dual Filter Trains with Dual 47 mm Filters (filters at near ambient temperature)5 Slide 4

4 

## • All measurement processes have an inherent element of variability in the measurement result.

• Each measurement that is made as part of the test procedure, and ultimately combined mathematically to produce a result, contributes to the overall uncertainty of that result. The more measurements made, the greater the overall uncertainty.

• This variability can be evaluated empirically by performing multiple measurements of a single artifact and evaluating the mean and standard deviation of the test results. 

# Test Method Variability6 Slide 5

5 

## • The relative magnitude of the standard deviation to the mean is a measure of the dispersion (variability) of the measurement process.

• This measure of dispersion includes variability that originates both from the measurement processes and from the inherent variability of the phenomenon being measured.

• When the measurement involves performance of a process which might be affected by uncontrolled variables or by the ranges allowed for operational parameters within the process, the variability associated with the process is usually much greater than that that arises from the uncertainty of the actual measurements made.7 Slide 6

6 

# The NORMAL Distribution

NORMAL DISTRIBUTION

-4 -3 -2 -1 0 1 2 3 4 STANDARD DEVIATIONS 95% MEAN

68%8 Slide 7

7 

# Terminology

• The closeness of agreement between independent test results obtained under stipulated conditions is the

“ precision ” of the measurement.

• Precision is usually broken down further into:

– Repeatability

– The closeness of multiple measurements of the same artifact under the same conditions with the same equipment and operator. The symbol “ r ” is often used to refer to repeatability. Repeatability can be evaluated by replicate tests of the same product at the same laboratory following the defined procedure.

– Reproducibility

– The closeness of measurements made on the same or presumed to be identical artifacts by different laboratories, equipment and operators. The symbol “ R ” is often used for reproducibility. Reproducibility can be evaluated for any quantitative measurement system through an Interlaboratory Study or round robin test program.9 Slide 8

8 

# Quantifying Test Method Precision

• The primary data set available to evaluate test result variability is that generated through the EPA required Accredited Laboratory Proficiency Test Program.

– A total of 14 laboratories have participated over the years (to varying degrees).

– 5 individual test heaters have been used in the proficiency test program.10 Slide 9

911 Slid e 10

10 

# • This database can be analyzed using standard statistical tools.

• This database can be further analyzed using advanced statistical procedures specifically intended to assess test method variability (ASTM E691).12 Slide 11

11 

## “Macro” Analysis Using Standard Statistical Tools13 Slide 12

12 

## • Since there is a wide range in the weighted average emissions performance for each stove in the database, both the standard deviation and the coefficient of variation (CV) were computed for each stove to avoid any potentially misleading assessments of variability that might result from the wide range in the calculated means for the individual test stoves.

– Note: The coefficient of variation represents the ratio of the standard deviation to the mean, and it is a useful statistic for comparing the degree of variation from one data series to another, even if the means are drastically different from each other.14 Slide 13

13 

# • It is apparent that the repeatability and reproducibility of the test procedures are not very good.

• Even without applying any statistical tools, one can simply look at the results of testing the same stove in the same laboratory over two or more years to see the range of intra

- laboratory results.15 Slide 14

14 

# • Using the results from all the laboratories for all the stoves over all the years of the program, it is possible to assess the inter

laboratory precision.

– Using 2.8 times the standard deviation to estimate the potential range of results that could be expected with a 95% confidence level [Ref.: ASTM E177, 28.1], it is clear that the for any given test series the reproducibility is on the order of ± 4.9

– 9.8 grams per hour.16 Slide 15

15 

# • This means that for any emissions rate measured using the EPA test methods, the result could be 4.9 to 9.8 grams per hour higher or lower if the appliance were tested again at a different laboratory.

• Even at one standard deviation (68% confidence level), the reproducibility interval is about 1.7 to 3.5 grams per hour, i.e., there is a 32% chance that a new test result would deviate by more than this amount.17 Slide 16

16 

## • The CV calculations further confirm that variability is high (>40 % CV) for the three test stoves with significant data sets but it is not consistent for all units.

• Since CV is calculated from one standard deviation, the implied variability in the actual data is really about 2.8 times the CV at a 95% confidence level. For example, a CV of 40% implies that the results of any one test could vary by +/

- 112% from a population mean with a probability of 5% or less of being farther away.18 Slide 17

17 

# ASTM E177

3.1.12 repeatability limit (r) , n
— the value below which the absolute difference between two individual test results obtained under repeatability conditions may be expected to occur with a probability of approximately 0.95 (95 %).

3.1.12.1 Discussion

— The repeatability limit is 2.8 (1.96 x √ 2 ) times the repeatability standard deviation. This multiplier is independent of the size of the interlaboratory study.

3.1.12.2 Discussion

— The approximation to 0.95 is reasonably good (say 0.90 to 0.98) when many laboratories (30 or more) are involved, but is likely to be poor when fewer than eight laboratories are studied.19 Slide 18

18 

# Precision Analysis Using ASTM E691

• Under the presumption of using consensus standards, we determined that ASTM E691

– Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method was appropriate for use here.20 Slide 19

19 

## • ASTM E691 provides procedures for planning and conducting studies of the precision of test methods, and also provides statistical techniques for performing precision analyses.

• Since the EPA proficiency test program has been on

- going for more than 20 years, the test program design components of ASTM E691 are not germane here.

• However, the analytical procedures can be applied to the EPA proficiency test data for the purposes of determining precision (both r & R).21 Slide 20

20 

# • Separate tables were created for each of the different stoves that were tested over the years the proficiency test program was conducted where there is sufficient data to apply the procedures specified in ASTM E691.22 Slide 21

2123 Slide 22

2224 Slide 23

2325 Slide 24

24 

# Conclusions from ASTM E691 Analyses

• The ASTM E691 analyses shows that the repeatability (within lab), **r** , of the weighted average emissions rate determined by the EPA test methods at the 95% confidence level is at best ± 2.9 grams per hour and typically about ± 3.5 to ± 5.4 grams per hour. The reproducibility (between labs), **R** , at the 95% confidence level is ± 4.5 to
± 6.4 grams per hour.26 Slide 25

25 

# Sources of Variability in EPA Wood Heater Testing

• Given that 12 labs (five are still accredited) and all four particulate measurement methods are represented, it is important to try to understand if the repeatability and reproducibility issues are laboratory and method related or arise from a different source
– that is, variable performance of the appliance itself.27 Slide 26

26 

# • To evaluate that question, we next investigated the potential sources of variability in the test methods.

– We started with the emissions measurement methods (5G

- 1, 5G

- 2, 5G

- 3 and 5H), and then addressed Method 28, which specifies how the appliance is to be operated during emission testing.28 Slide 27

27 

# Emission Measurement Methods

Method 5G

- 1

• Potential sources of variability in Method 5G

- 1 include the following:

– Accuracy of dilution tunnel gas flow and sample flow measurement and the resulting consistency of proportionality.

– Recovery of particulates from the probe and front half of filter holder using a solvent cleaner.

– Weighing errors for tare and final weights of filters and evaporation containers used to collect and weigh the catch.



### • These sources combine to produce an estimated measurement uncertainty of about ± 2.7 to 3% of the emission value measured for a typical passing wood stove test.29 Slide 28

28 

### Method 5G

- 2

• Potential sources of variability in Method 5G

- 2 include the following:

– Accuracy of dilution tunnel gas flow and sample flow measurement and the resulting consistency of proportionality.

– Recovery of particulates from the probe and sampling line using a solvent cleaner.

– Recovery of particulate collected in the impingers and connecting glassware.

– Weighing errors for tare and final weights of filters and evaporation containers used to collect and weigh the catch.



### • These sources combine to produce an estimated measurement uncertainty of about ± 3

– 3.5% of the emission value measured for a typical passing wood stove test.30 Slide 29

29 

## Method 5G

- 3

• Potential sources of variability in Method 5G

- 3 include the following:

– Accuracy of dilution tunnel gas flow and sample flow measurement and the resulting consistency of proportionality.

– Weighing errors for weights of filters, probes including front filter housings and filter seals.



## • The measurement uncertainty of method 5G

- 3 has been determined to be approximately ± 2.5% of the emission value measured for a typical passing wood stove test.31 Slide 30

30 

### Method 5H

• Potential sources of variability in Method 5H include the following:

– Accuracy of flue gas flow and sample flow measurement and the resulting consistency of proportionality.

– Recovery of particulates from the probe and sampling line using a solvent cleaner.

– Recovery of particulate collected in the impingers and connecting glassware.

– Weighing errors for tare and final weights of filters and evaporation containers used to collect and weigh the catch.



### • These sources combine to produce an estimated measurement uncertainty of about ± 20 to 30% of the total particulate mass determination.

• The major contributor to MU is the difficulty in measurement of low and variable stack flow rates.32 Slide 31

31 

## Conclusions Regarding the Contribution of Emissions Measurement Method Uncertainty to Overall Method Variability



# • It is apparent that the emission measurement methods explain only a small part of the overall variability shown by the precision analyses.

– It should be noted that Method 5G

- 3 showed lower variability in the analyses than the other emission measurement methods.33 Slide 32

32 

### Operating Protocol for the Appliance (EPA Method 28)

• Potential Sources of Variability in Method 28 include the following:

– Fuel density variation from approximately 30 to 40 lb/ft3 (dry weight basis).

– Fuel moisture content variation from 19 to 25% dry basis (varies in uniformity as well as average).

– Fuel load configuration details.

– Coal bed size (20

- 25% of fuel load weight) and pre

- burn temperature conditions.

– Loading time and start

- up procedure.

– Ambient temperature, barometric pressure and humidity.

– Variations in control settings and resulting burn rates.

– Random uncontrollable variables such as when and how the fuel load settles, falls and collapses.34 Slide 33

33 

# • Using the EPA proficiency test data, it is possible to examine several of the various Method 28 parameters for their impact on precision.

– Impacts of burn rate variations.

• Emissions performance is related to burn rate to some degree.

– Higher burn rates generally produce more complete combustion.35 Slide 34

34 

# • The proficiency test data does not lend itself well to determining the impact of burn rate variability over the full burn rate range of the heater in that each lab must adjust the air control(s) to a setting that will produce a burn rate in each of the required burn rate categories.

• The exception is the high burn rate (Category 4) which is always run with the air control(s) fully open.36 Slide 35

3537 Slide 36

36 

# Burn Rates

• The high burn rate variability is substantial, and it is certain that this variability is a contributing factor in the emissions variability.

• There are many instances in the proficiency test data where two runs in one lab at very similar burn rates produced substantially different emissions rates. So burn rate variability does not explain much of the overall variability of emissions rates.38 Slide 37

37 

## – Impacts of fuel moisture variations

– Impacts of fuel density variations

• The following charts show the relationship between emissions and fuel moisture content and emissions and load weight (assumed to relate to fuel density) for the 121 runs conducted on the catalytic proficiency test stove in 1987 and 1988. Using the “Corner Score” statistical test where a score of >11 indicates potential dependency between variables [Ref.: Mark’s Standard Handbook for Mechanical Engineers, 17

- 22], it is clear that there is no relationship.39 Slide 38

38 1987 &1988 Cat Stove 1 - % M.C. v Emissions

y = -0.1496x + 7.4864 R 2 = 0.0048

0 2 4 6 8 10 12 14 16 18 20

15 17 19 21 23 25 %M.C. Dry BasisEmssions (g/h) Emissions Rate Median MC Median Emissions rate Linear (Emissions Rate)

Corner Score +440 Slide 39

39 1987 &1988 Cat Stove 1 - Load Wt. v Emissions

y = -0.2276x + 7.368 R 2 = 0.0048

0 2 4 6 8 10 12 14 16 18 20

9 10 11 12 13 14 15 16 Load Weight (lbs)Emissions (g/h) Emissions Rate

Med. E

Med. Laod Wt. Linear (Emissions Rate)

Corner Score +241 Slide 40

40 

### • By practical necessity, EPA Method 28 contains tolerances on operational and fueling parameters. These include fuel density, moisture content, laboratory ambient temperature, coal bed size, fuel load weight and several others. While it might be supposed that the method variability could be lessened by even tighter specifications within the test method relating to fuel and operating conditions, the data does not support this proposition.

• Without these tolerances or specified ranges wood heater emission testing would become prohibitively expensive with significant additional costs incurred while attempting to control these variables within a significantly narrower range than specified. As demonstrated, these additional costs would not significantly reduce variability.42 Slide 41

41 

# Final Conclusions

• The repeatability and reproducibility of wood heater emission testing as demonstrated by the EPA accredited laboratory proficiency test data is quite poor.

– At the 95% confidence level, repeatability for the EPA weighted average emission rate is at best ± 2.9 g/hour and ranged as high as ± 5.4 g/hour.

– The reproducibility was no better than ± 4.5 g/hour and ranged as high as ± 6.4 g/hour.43 Slide 42

42 

# Final Conclusions

Emissions r & R - Best Case

0 2 4 6 8 10 12 14 16 18 20

0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5 12.5 13.5
Mean Emissions Rate (g/h)95% Confidence Limits
Intralab

r Mean Emission g/hr Interlab R44 Slide 43

43 

# Typical Distribution45 Slide 44

44 

# • Further analyses of the potential sources of variability have shown that the emission measurement test methods (EPA Methods 5G

- 1, 5G

- 2, 5G

- 3 and 5H) are not major contributors to the high overall variability being demonstrated by the data.

– However, Method 5G

- 3 does demonstrate the lowest uncertainty of the four methods currently specified in the NSPS.46 Slide 45

45 

# • Analyses of the variability inherent in EPA Method 28 also indicate that the operational and fuel parameter tolerance ranges specified in that method are not major contributors to the high variability.

– Tightening these parameters to improve test precision would simply increase costs and the data show that such tightening would not significantly improve precision.47 Slide 46

46 

# • This leaves the only logical conclusion.

– Variability in wood heater emission testing results for any given appliance is most likely a function of the random nature of burning wood, no matter how tightly you try to control the process.

• Many relatively small, uncontrollable variables that are inherent in the wood combustion process can combine to significantly affect the outcome of any given test.48 Slide 47

47 

## • These conclusions should not be taken to mean that the current test methodology is inadequate to characterize an appliance’s emissions performance.

– There is no question that the currently certified low emissions wood stoves produce far less particulate emissions than their pre

- regulation predecessors which produced emissions rates of over 50 to 100 grams per hour.

– Our primary conclusion is that the current testing process simply cannot reliably distinguish emissions performance differences of less than 4 to 6 grams per hour. The process is certainly capable of reliably distinguishing between good and bad performance, but it cannot reliably distinguish between “good, better and best” performance.1 Attachment 2

Wood Heater Emission Test Method Comparison2 Slide 1



# Wood Heater Emission Test Method Comparison

EPA Methods 5G

- 1/5G

- 3 versus 5G

- 2/5H3 Slide 2



# Background

• The issue involving the long suspected flaw in the equation used to “adjust” the emission values determined using EPA Methods 5G

- 1 and 5G

- 3 to EPA Method 5H equivalents was outlined in a report dated March 30, 2010. This report was forwarded to EPA in April 2010.4 Slide 3



## • It has been widely suspected by users of the EPA wood heater test methods that the test method adjustment equation used to “correct” EPA Methods 5G

- 1 and 5G

- 3 to EPA Method 5H equivalency was flawed, especially in the critical lower emission range (<7.5 g/hour).

• This issue has taken on new importance with the evaluation of BDT using the EPA certified heater database.5 Slide 4



## • The subset of that database identified by HPBA as representing the majority of currently produced heaters includes nearly 50% heater models tested using either M5H or 5G

- 2.

• The importance of understanding the true relationship between the test methods is amplified if the database is to be evaluated using M5G

- 3 (ASTM E2515) as the “currency” for evaluating BDT.6 Slide 5



# • Adjusting the 5H/5G

- 2 data to 5G

- 3 equivalents using the inverse of the present adjustment equation could skew the database.

• This, in turn, impacts the BDT analysis.7 Slide 6



# Action

• HBPA worked with OAQPS and OECA to create a procedure that allowed a second emission measurement method to be run simultaneously with the method designated for use for certification testing. The second method would not be reported for certification purposes.

• For example, if M5G

- 1 was being used for certification, M5G

- 2 was piggy

- backed on to allow a direct comparison of the results.8 Slide 7



# • HPBA absorbed the cost of adding the second emission measurement method and has accumulated the comparison data.

• The data we have gathered so far is presented here. It should be noted that the M5G

- 1 and 5G

- 3 values are as measured (not adjusted to 5H equivalents).9 Slide 8

Emission Test Method Comparison Data (through October 19, 201010 Slide 9



# Analyses

• The data show varying relationships when comparing subsets of the data.

• The datasets breakdown as follow:

– M5G

- 3 versus M5G

- 2

– M5G

- 3 versus M5H

– M5G

- 1 versus M5G

- 211 Slide 1012 Slide 11



# Preliminary Conclusions

• The impacts of testing at three laboratories with three different combinations of test method comparisons has resulted in a relatively noisy database.

• The data does indicate that the current adjustment equation does not reflect the relationship between the methods.1 Attachment 3

The Impact of Pellet Fuel Ash Content on Particulate Emission Performance o f Pellet Heaters2 Slide 1



# The Impact of Pellet Fuel Ash Content on Particulate Emission

Performance of Pellet Heaters3 Slide 2



# Background

• Many of the certified pellet heaters were tested using pellets with very low ash content (< 0.5%).

• These pellets are made from softwood feed stock and are produced in the Pacific Northwest.

• These pellets are commonly available for the lab that conducted much of the pellet heater certification testing.

• Pellets that are most commonly available in other areas of the country where pellet heaters are popular are generally hardwood or mixed wood and have higher ash content (>1%).4 Slide 3



# • There was supposition that higher ash fuels would result in higher particulate emissions.

– This was based on observations made by pellet heater manufacturers when they tested other fuel types (corn, grains, hulls, etc.) that were known to have higher ash content than wood pellets.5 Slide 4



# • There was almost no data directly comparing low and high ash wood pellet fuels in the same heater using the same test method.

• There was concern over the impacts on BDT since different pellets might produce different results, even when the burn settings are optimized.6 Slide 5



# • This concern expands further when other fuel types are considered (corn, grain, hulls, pits, switch grass, etc.)7 Slide 6



# Action

• HPBA has been working to obtain data that will shed some light on this potential problem.

• Some comparison testing has been conducted, both in manufacturer labs and one EPA accredited lab.

• The results obtained to date are shown in the following table.8 Slide 7



# Test Results (To

- date)9 Slide 8



# • There is one softwood versus hardwood pellet test series that has been completed but the data has not been QA’d. This data will be added will be available within a few days.10 Slide 10



## • An assessment of the impact on BDT determination must be made before pellet heater emission levels (passing grade(s)) can be set within the revised NSPS.

• The performance of pellet heaters on higher ash fuels can still provide a clean

- burning option.

• Without considering this issue, alternative bio

fuel development and heater development for those fuels could be stifled.11 Slide 9



# Conclusions

• Based on the limited data obtained so far, it appears that higher ash pellets will produce higher levels of particulate emissions.

• Due to the fact that pellet heaters include combustion air blowers, it is likely that the additional PM collected with the higher ash fuels is primarily ash (inorganic) that has been entrained in the exhaust flow.

• The higher ash pellet fuels dominate the available pellet fuel supply in areas other than the west coast (primarily due to available feedstock for the pellet mills).1 Attachment 4

Assessment of the Economic Impacts of NSPS “Strawman” Proposals on Hearth Product Companies2 Slide 1

1 

# ASSESSMENT OF THE ECONOMIC IMPACTS OF NSPS “STRAWMAN” PROPOSALS ON HEARTH PRODUCT COMPANIES

October 21, 20103 Slide 2

2 

# • Costs and other economic impacts are an important input into the NSPS process.

• All stakeholders therefore have an interest in seeing that the record contains high quality data that accurately reflects the potential impacts of new standards on the hearth industry. 

# Background4 Slide 3

3 

# • The current NSPS had a massive and largely unanticipated impact on woodstove manufacturers. It is in everyone's interest to avoid repeating that experience this time around.5 Slide 4

4 

# HPBA Activities

• For these reasons, HPBA has taken steps to develop high quality economic impact data for consideration by EPA in the NSPS process.

– We hired NERA, a top

- flight economic consulting firm to assist in this effort.6 Slide 5

5 

# • NERA's first assignment was to prepare guidance for use by our manufacturers in preparing economic impact assessments.

– That guidance reflects and implements the latest EPA and OMB guidance on how to perform these assessments.

– A copy of that guidance has been provided to EPA.7 Slide 6

6 

# SBREFA

• The NERA guidance was provided to the SERs in the SBREFA process for their use in preparing their presentations to the SBREFA panel.8 Slide 7

7 

## • HPBA identified a group of manufacturers that are broadly representative of our membership.

– These companies have agreed to perform analyses of the impacts on their businesses of the "straw man" proposals provided to the SBREFA panel, using the NERA guidance.

• In addition, HBPA has made arrangements for these companies to seek assistance from NERA in developing these analyses.



## • The final products of this effort will be submitted by the companies to EPA, hopefully in the near future. 

# Beyond SBREFA9 Slide 8

8 

# CBI

• Much of the data in these reports will be CBI. The companies will submit these data to EPA in compliance with EPA's procedures for CBI submissions.1 Attachment 5

Pellet Standards Update for EPA/OAQPS, October 21, 2010231 Attachment 6

EPA Wood Heater Test Method Variability Study234567891011121314151617181920212223242526272829303132333435363738394041424344