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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 & Company 

October 6, 2010 
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I. 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 and required to be used to 

certify model lines under that NSPS has ever been performed, despite the fact that the 

NSPS was promulgated over 20 years ago, more than 700 woodstoves have been tested 

and certified under it, and 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. 

The paper consists of four major sections. Section I is this introduction. Section II 

provides back ground information that will help frame the issues associated with test 

method precision. Section III is the assessment of test method precision and is comprised 

of several sub-sections that address the EPA proficiency test data, and analyze some of 

the sources of variability. The last section (IV) provides conclusions about variability 

that are supported by the preceding in-depth analyses. 

II. Regulatory Background. 

The NSPS was proposed on February 18, 1987 (52 Fed. Reg. 4994) and promulgated on 

February 26, 1988 (53 Fed. Reg. 5860). It is codified at 40 CFR Part 60, Subpart AAA –

Standards of Performance for New Residential Wood Heaters. The regulation includes 

the following EPA test methods: 

EPA Method 28 – This method prescribes the fueling and operation procedures for 

emission testing. Among other parameters, it specifies the test fuel properties, 

test fuel load configuration, pre-test operating conditions, charcoal bed weight at 

the start of the test run, loading and start-up time, allowable air supply 

adjustments, fuel adjustments, end of test run determination and allowable heater 

body temperature differential from start to end of test, and other parameters 

needed to conduct a wood heater emission test. 

EPA Method 5H - This particulate measurement procedure uses an EPA modified 

Method 5 sampling train which draws a flue gas sample from the wood heater 

stack and collects particulate in the sampling probe, on a heated 110 mm filter and 

in a series of ice water chilled impingers. The sampling rate for the sampling 

train is to be maintained at a constant proportion of the stack gas flow rate and 

includes a measurement protocol for determining the stack flow at equal time 

increments. The particulate mass collected in the probe, on the filters, and in the 

impingers is determined gravimetrically after the removal of uncombined water. 

EPA Method 5G-1 – This method and all of the “5G” methods use a dilution tunnel 

which collects all the effluent from the appliance chimney and draws it, with 

ambient dilution air, through a straight duct at a uniform velocity. The velocity is 

high enough to allow accurate flow rate measurement using a Standard or S-Type 

pitot tube. Method 5G-1 uses a sample train similar to the Method 5 train but 
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uses two 110 mm filters in series that are unheated and does not involve recovery 

of material past the second filter. The particulate mass collected in the probe and 

on the filters is determined gravimetrically after the removal of uncombined 

water. 

EPA Method 5G-2 – This method utilizes the Method 5H sampling train but the 

sample is taken from the dilution tunnel (as described in Method 5G-1 above) 

rather than the wood heater stack. Sample recovery is the same as Method 5H. 

EPA Method 5G-3 – This method used two 47 mm filters in series and is otherwise 

similar to Method 5G-1. However the method requires that two identical sample 

trains be used simultaneously and that the results from each agree within 7.5% of 

the mean for the result to be valid. 

At the time the NSPS was promulgated, there had been no rigorous assessment of the 

precision of the wood heater test methods. In the preamble accompanying the proposal, 

EPA had this to say about the inter-laboratory and intra-laboratory precision of Oregon 

Method 7, which became EPA Method 5H in the regulation: 

[T]he apparent heater-to-heater differences in the data base reflect not only true 

differences in performance, but also reflect test method precision. Although data 

are limited, data obtained by Oregon DEQ suggest that the interlab ... (sic) fourrun weighted average precision at the level of the standards is not greater than ± 

1 g/hr. 

In contrast, the database upon which the standards are based does not include 

individual wood heaters tested at more than one laboratory. Therefore, it was 

agreed that overall and inter-laboratory component of precision should be 

determined before enforcement tests are performed at laboratories other than the 

laboratory that initially certified the wood heater. Further, it was agreed that if 

the overall four-run weighted average precision exceeds ± 1 g/hr, then the 

interlab component of the precision would be added to the standard when . . . 

[enforcement] tests are conducted at other than the original certifying laboratory. 

 

The EPA will, by July 1, 1990, either publish in the Federal Register a 

determination that the inter-laboratory precision cannot be determined, or 

promulgate revisions reflecting what that precision has been found to be. 52 Fed. 

Reg. 5010-5011 (February 18, 1987). 

As noted above, however, no determination of either intra-lab or inter-lab precision has 

ever been made. 

Section 60.535 of the regulation provides for accreditation for wood heater emission test 

laboratories. The conditions of accreditation require that both initial (see §60.535(b)(5)) 

and annual (see §60.535(b)(7)) proficiency testing be conducted by each accredited 

laboratory. The proficiency test requirements include conducting at least eight test runs 

(two in each of the burn rate categories described in EPA Method 28) on a wood heater 

identified (or actually provided) by EPA. The tests are conducted using all EPA wood 

heater emission measurement methods for which the particular test laboratory is seeking 
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initial accreditation, or seeking to maintain accreditation. For example, a laboratory that 

was accredited for Methods 5H and 5G-1 would run both methods during their eight 

proficiency test runs. 

III. Test Method Variability

A. Basic Science 

All measurement processes have an inherent element of variability in the measurement 

result if the process has sufficiently fine resolution. 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. 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 process and from changes in the artifact being measured, i.e., 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. 

The “rifle” example is a common way of explaining these issues: If a rifle is repeatedly 

fired at a target, the impacts of variability can be visibly demonstrated. If the rifle is 

locked into a firing stand and carefully prepared cartridges (bullet plus powder load) are 

used and if the rounds are fired over a short period of time where the effects of 

variations in wind, temperature, humidity and barometric pressure conditions are 

minimized, the cluster of hits on the target should be very tight. The dispersion that is 

seen can be attributed to the minute differences in the rounds, variations in the rifle 

barrel as is heats and accumulates residue as well as the other unpreventable small 

shifts in ambient conditions. If the same experiment is repeated under a wider range of 

ambient conditions, say on two different days with different wind conditions, one might 

expect a wider dispersion of results. If the test is repeated with the rifle fired hand-held 

by the shooter, the dispersion will almost certainly be wider yet. If two different 

shooters fire the same rifle, the dispersion will widen further. If the shooters use two 

different rifles of the same model, again the results will almost certainly spread further. 

And so on and so on. In other words, as the opportunity for variation in the test 

conditions expands, so does the likelihood that the variation in the results will also 

increase. 

Understanding and quantifying the variability in measurement systems is a scientific 

discipline. That discipline uses standardized terminology to categorize and organize 

the various sources of variability. That terminology is as follows: 

Any test procedure that results in a numerical measurement of a product or material 

attribute is subject to a quantifiable value of “measurement uncertainty”

1

. Each 

 1 Two other concepts need brief mention: “accuracy,” and “bias”. “Accuracy” is the closeness of 

agreement between a test result and an accepted reference value. Ref.: ASTM E177. “Bias” is the total 
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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. 

The closeness of agreement between independent test results obtained under stipulated 

conditions is the “precision” of the measurement. Ref.: ASTM E177. 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. 

B. Quantifying Test Method Precision

1. The Available Data 

The primary data set available to evaluate test result variability is that generated 

through the EPA required Accredited Laboratory Proficiency Test Program. These data 

supplied by EPA provides a substantial data set which allows assessment of the intralab repeatability (r), and inter-lab reproducibility (R) for emissions testing using the 

NSPS specified test methods. 

The laboratories that participated in the proficiency testing are: 

Apex Environmental EEMC 

EESPC Engineering Sciences 

Intertek-Middleton Intertek-Montreal 

Lokee Testing Myren Consulting 

Northwest Testing OMNI-Oregon 

OMNI-RTP PFS 

Shelton Research Underwriters Laboratories 

Note: For the purposes of this paper, EEMC, EESPC and Lokee have been grouped 

together as one entity based on the understanding the test equipment remained the same 

throughout the changes of ownership. 

 systematic error in a measurement, as contrasted to random error. Ref.: ASTM E177. Quantification 

of both accuracy and bias requires a reference standard or material with known properties and known 

uncertainty of those properties. Since no wood stove exists that can consistently produce a specific 

emissions rate, there is no way to evaluate the accuracy or bias of the test procedures. Accordingly, 

“accuracy” and “bias” will not be discussed further in this paper. 
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In this program each of these accredited laboratories was supplied with a test appliance 

which EPA modified in a manner designed to assure that it would be robust enough to 

operate the same way after being shipped from lab to lab. 

Each laboratory was directed to conduct two full series of four test runs (two test runs 

in each of the four burn rate categories) in each round of proficiency testing. In 

addition, some laboratories that were accredited for more than one of the EPA methods 

were required to run both types of sampling equipment during their test runs and submit 

two sets of data. For example, a lab that was accredited for method 5H and 5G-1 would 

run both during their eight test runs. All Method 5G-1 and 5G-3 data were “adjusted to 

Method 5H equivalent2

” using the formula EHequiv. = 1.82 x E0.83. Ref.: 40 CFR Part 

60, Subpart AAA, Appendix A, Section 6.6, Eq. 5G-5.

In 1987 and 1988, EPA was able to send the first proficiency stove to each accredited 

laboratory in both years and obtain complete data sets. In 1989 a second proficiency 

stove was tested at each accredited laboratory, but several laboratories dropped their 

accreditation in the first two years of the program. From 1990 on, there was a further 

reduction in the number of laboratories participating and the schedule for proficiency 

testing was less rigorous. However, one test stove was used from 1993 - 2000. So 

there are three stoves with multiple test data sets from multiple laboratories. The data 

from these tests show no pattern of change over time that would indicate deterioration 

of the test appliance’s performance. 

Table 1 is a compilation of weighted average emission rates using all eight runs (or 

more if the lab ran more than 2 in a burn rate category). The weighted average 

emission rates were computed from individual test run data that were provided to the 

primary author by EPA upon request in 2006. These data are included in their entirety 

in Appendix A. The primary author of this paper performed a limited quality check on 

the data, by comparing a sample of the data to the original test reports submitted by his 

laboratory and others, and determined that the check sample and the original 

submissions were identical. Table 1 utilizes all proficiency test program data provided 

by EPA, and is grouped for each stove tested as well as being categorized by test 

laboratory and test year. 

 

2

 Although this conversion of data can be thought of as adding another layer of uncertainty to the results, 

especially since the adjustment equation is non-linear and it was itself based on a “best judgment” curve-fit 

to experimental data (with its own undetermined uncertainty), including the data adjustment is appropriate 

because it results in an analysis of the precision of the EPA methods as written and used.
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Table 1 

2. Data Analysis Options

Since there is no published EPA method for determining test method precision, two 

separate data analysis methodologies were employed. 

• “Macro” Analysis Using Standard Statistical Tools

In Table 2, we present the results of a “macro” analysis of the data using standard 

statistical tools. 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)3

 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. 

 

3 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. The coefficient of variation is useful because the standard deviation 

of data must always be understood in the context of the mean of the data. The coefficient of variation is 

a dimensionless number. So when comparing between data sets with different units or widely different 

means, one should also determine the coefficient of variation for comparison instead of the standard 

deviation alone. In this case there is a wide range in the average emission performance of the various test

stoves and assessing the variability of the results using just the standard deviation without also assessing 

the CV could be misleading.
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Table 2. 

From the Table 2 data it is apparent that the repeatability and reproducibility of the test 

procedures are not very good. 

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 intralaboratory results. 

And looking at 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. 

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. 

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. The 2005 data 

can be discounted since two data points are too few to draw any valid conclusions. 

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. 
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• Precision Analysis Using ASTM E691

Consistent with the National Technology Transfer and Advancement Act, which creates 

a presumption in favor 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. 

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 {Sections 6 – 14) 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). In the 

following subsections, these procedures are first described generally and then 

specifically as they were applied to the EPA proficiency test data. 

• ASTM E691 Analytical Procedure and Terminology

The analysis utilizes tabular, graphical, and statistical diagnostic tools for evaluating the 

consistency of the data so that unusual values may be detected and investigated, and 

also includes the calculation of the numerical measures of precision of the test method 

pertaining to both within-laboratory repeatability and between-laboratory 

reproducibility (r & R). 

Table of Test Results—The test results received from the laboratories are arranged in 

rows and columns. Each column contains the data obtained from all laboratories for 

one test sample, and each row contains the data from one laboratory for all test 

samples. The test results, x, from one laboratory on one test sample constitute a cell. 

The results of the following calculations for that test sample are also entered on the 

table. 

Cell Statistics: 

Cell Average4

, x —This statistic is the cell average for each laboratory. 

= ∑

n

1

x x / n where n = the number of test results per cell 

Average of the Cell Averages, x —This statistic is the average of all the cell 

averages for the one material and all laboratories. 

= ∑

p

1

x x / p where p = the number of laboratories 

Cell Standard Deviation, s —This statistic is the standard deviation of the test results 

in each cell and is calculated as the square root of the sum of the squares of the cell 

 

4 ASTM E691 refers to the term “average” when defining statistical terminology. “Average” is equivalent 

to the “arithmetic mean”. The term “mean”, when used in this paper should be considered interchangeable 

with “average” as defined in ASTM E691. 
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value minus the cell average divided by one less than the number of test results in the 

cell. 

= ∑ − −

n

1

2 s ( x x ) /( n 1 )

Cell Deviation, d — The cell deviation is calculated by subtracting the average of the 

cell averages for all laboratories from the cell average for each laboratory. 

d = x − x

Standard Deviation of the Cell Averages, x s —This statistic is calculated as the 

square root of the sum of the squares of the cell deviation divided by one less than the 

number of laboratories. 

= ∑ −

n

1

2

x s d /( p 1 )

Precision Statistics

While there are other precision statistics, the fundamental precision statistics of the 

Interlaboratory Study are the repeatability standard deviation and the reproducibility 

standard deviation. Other statistics are calculated from these standard deviations. 

Repeatability Standard Deviation, sr—This statistic is calculated as the square root of 

the sum of the squares of the cell standard deviation divided by the number of 

laboratories. 

= ∑

p

1

2 sr s / p

Reproducibility Standard Deviation, sR — This statistic is calculated as the square 

root of the square of the standard deviation of the cell average plus the square of the 

repeatability standard deviation (first adjusted for the number of test results) or is 

equal to sr, if sr is larger than sR. 

s ( s ) ( s ) ( n 1 ) / n 2

r

2

R = x + −

Consistency Statistics

The statistical analysis of the data for estimates of the precision statistics is simply a 

one-way analysis of variance (within- and between-laboratories) carried out 

separately for each material. Since such an analysis can be invalidated by the 

presence of severe outliers, it is necessary to first examine the consistency of the data. 

Between-laboratory Consistency Statistic, h— This statistic is calculated as the cell 

deviation divided by the standard deviation of the cell averages. 

x h = d / s
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Within-laboratory Consistency Statistic, k— This statistic is calculated as the cell 

standard deviation from one laboratory divided by the repeatability standard deviation 

of the material. 

r k = s / s

Critical Values of the Consistency Statistics—A table5 list critical values of the h and 

k consistency statistics at the 0.5 % significance level. The critical values for h

depend on the number of laboratories, p, and the critical values for k depend both on 

the number of laboratories, p, and on the number of replicate test results, n, per 

laboratory per material. When cell values approach or exceed the critical values for h

and k, those cells or laboratories should be investigated for data problems. 

• ASTM E691 Precision Analysis 

The proficiency test data was then analyzed to determine test method precision using 

the procedures outlined in ASTM E691 as described above.6 

Separate tables (Tables 3a-3c) 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 E6917. Each participating 

test lab has a row in each table. Since the proficiency test program required two 

emission tests in each Method 28 burn rate category, it was possible to calculate two 

EPA weighted average emission results for each proficiency test series. To do this, the 

first runs conducted in each of the four burn rate categories were grouped together for 

the purposes of determining the first weighted average emissions. Likewise, the second 

run in each burn rate category produces the second weighted average emissions result. 

This methodology was employed since the burn rate category tests were generally not 

conducted in any specific order and grouping the first runs in each category most 

closely simulates an actual emission certification test. The numbered columns in each 

table represent the weighted average emissions results for the grouped data for the 

different test series on the particular test stove. For example, in Table 3a, Lab A only 

participated in one year of testing on Catalytic Stove 1. By grouping the eight 

individual test runs as described above, two weighted average emissions values result 

for that lab for that stove and are shown in the columns labeled 1 and 2. Lab E 

participated in both test years and ran two test methods simultaneously in both years. 

The results from the second method are shown in the row labeled E1. The data 

grouping methodology results in four separate EPA weighted average emission rates for 

 

5 ASTM E691 Table 5

6 In some cases, inadequate data precluded using all data in the analyses. In 2005, only two test 

laboratories conducted proficiency testing and Non-Cat 4 was not tested in any other year. ASTM E691 

requires a minimum of three laboratories for a single sample so the 2005 data was not used. 

7 Ideally the data set used for this analysis should contain a minimum of 3 replicate tests from each of at 

least 6 laboratories. In Tables 3a-3c, only data from the proficiency test stoves that have sufficient data for 

a statistically meaningful evaluation are presented. 
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this lab for Catalytic Stove 1 for the 5G method as shown in the columns labeled 1 

through 4 and rows labeled E and four additional results for the 5H method in row E1. 

The next column shows x , the mean of all test series results on the tested stove for 

each lab. In this case, this includes the two test series for each proficiency test and 

multiple proficiency tests results on the same test stove whenever available. The 

columns to the right of x include the statistical information about the results from each 

lab for all test series for each sample tested per ASTM E691, as described above. This 

statistical information includes s , the standard deviation for individual lab results, d , 

the cell deviation (how much the cell mean deviates from the overall mean), h, a 

“between laboratory consistency statistic” and k , a “within laboratory consistency 

statistic”. These latter two are measures of whether data included in the analysis should 

be investigated for problems. Three weighted average emissions data points were 

excluded from the analysis based on this test. They are marked with * in the tables that 

follow. Also included in the table are x , the overall mean for all test series from all 

labs, x s , the standard deviation of the overall mean, sr, the repeatability standard 

deviation as well as sR, the reproducibility standard deviation. Finally, values for 

repeatability (r) and reproducibility (R) are shown to provide the true assessment of the 

precision demonstrated by the EPA proficiency test data. 

Table 3a 
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Table 3b 

Table 3c 

Abbreviations: 

s = standard deviation for individual lab results 

d = cell deviation = x − x

sx = standard deviation of x

sr = repeatability of standard deviation 

sR = reproducibility of standard deviation 

h = between laboratory consistency statistic 

k = within laboratory consistency statistic 
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• Conclusions from ASTM E691 Analyses

The Table 3a, 3b and 3c data 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. 

3. 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. 

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. 

• Emission Measurement Methods

Method 5G-1 

Potential sources of variability in Method 5G-1 include the following: 

o Accuracy of dilution tunnel gas flow and sample flow measurement and the 

resulting consistency of proportionality. 

o Recovery of particulates from the probe and front half of filter holder using a 

solvent cleaner. 

o 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. 

See Appendix C for the derivation of this estimated uncertainty range. 

Method 5G-2 

Potential sources of variability in Method 5G-2 include the following: 

o Accuracy of dilution tunnel gas flow and sample flow measurement and the 

resulting consistency of proportionality. 

o Recovery of particulates from the probe and sampling line using a solvent 

cleaner. 

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

o Weighing errors for tare and final weights of filters and evaporation 

containers used to collect and weigh the catch. 
Page 15 of 43 

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. 

See Appendix C for the derivation of this estimated uncertainty range.

Method 5G-3 

Potential sources of variability in Method 5G-3 include the following: 

o Accuracy of dilution tunnel gas flow and sample flow measurement and the 

resulting consistency of proportionality. 

o 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. See Appendix C for the derivation of this estimated uncertainty range. 

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. See Appendix C for the 

derivation of this estimated uncertainty range. 

• Conclusions Regarding the Contribution of Emissions Measurement Method 

Uncertainty to Overall Method Variability

It is apparent from the foregoing analysis that the emission measurement methods 

explain only a small part of the overall variability that has been discussed and 

quantified in Section III. It is clear, however, from this analysis that some emission 

measurement methods contribute less to variability than others with Method 5G-3 the 

best performer in this regard.8

 

8 With the objective of improving the wood heater test methods based on more than twenty years of 

experience with the current EPA methods, ASTM E06.54 sub-committee was charged with creating new 

methods. The first step was to specify only one particulate measurement procedure to help reduce the 

measurement uncertainty associated with multiple measurement methods. This resulted in the 

subcommittee’s development of ASTM E2515, which specifies a procedure that corresponds very closely 

to EPA Method 5G-3 but has provisions that allow appliance types other than just wood and pellet heaters 

to be tested. This procedure was selected because it has the smallest measurement uncertainty of the four 

current EPA methods and contains the dual train measurement which allows for ready detection of invalid 

results. 
Page 16 of 43 

• Operating Protocol for the Appliance (EPA Method 28)

Potential Sources of Variability in Method 28 include the following: 

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

o Fuel moisture content variation from 19 to 25% dry basis (varies in uniformity 

as well as average). 

o Fuel load configuration details. 

o Coal bed size (20-25% of fuel load weight) and pre-burn temperature 

conditions. 

o Loading time and start-up procedure. 

o Ambient temperature, barometric pressure and humidity. 

o Variations in control settings and resulting burn rates. 

o Random uncontrollable variables such as when and how the fuel load settles, 

falls and collapses. 

Using the EPA proficiency test data, it is possible to examine several of the various 

Method 28 parameters for their impact on precision. 

The first is an analysis of the impacts of burn rate variations. It is known that emissions 

performance is related to burn rate to some degree with higher burn rates generally 

producing more complete combustion. 

The proficiency test data does not lend itself well to determining burn rate variability in 

that each lab must adjust air controls to a setting that will produce a burn rate in one of 

the required categories. The exception is the high burn rate (Category 4) which is 

always run with the air controls fully open. Table 4 is a compilation of the Category 4 

burn rates from the proficiency test program. Note that the specific labs designated by 

the lab codes were different from year to year. 

 
Page 17 of 43 

Table 4 

.

The high burn rate variability is substantial, and it is certain that this variability is a 

contributing factor in the emissions variability, but it is not likely that it is the most 

important factor. 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. 

See Appendix B for burn rate versus emissions plots of all the individual run data. 

Charts 1 and 2 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. 
Page 18 of 43 

Chart 1 

Chart 2 

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. 

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

y = -0.1496x + 7.4864

R2

 = 0.0048

0

2

4

6

8

10

12

14

16

18

20

15 17 19 21 23 25

%M.C. Dry Basis

Emssions (g/h)

Emissions Rate

Median MC

Median Emissions rate

Linear (Emissions Rate)

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

y = -0.2276x + 7.368

R2

 = 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 +4 

Corner Score +2 
Page 19 of 43 

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. 

IV. 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. 

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. 

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. 

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. 

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 heaters produce far less particulate 

emissions than their pre-regulation predecessors which produced emissions rates of 50 to 

100 grams per hour or more. Our primary conclusion is that the current testing process 

simply cannot consistently distinguish emissions performance differences of less than 3 

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.9

 

 

9 To return to the “rifle” analogy, wood stoves are not modern high powered rifles in the hands of an expert 

marksman who can place a dozen shots in a 2 inch bull’s-eye at 100 yards. They are rather more like a 

smooth bore flintlock pistol where just “hitting the paper” at 50 feet is an accomplishment. 
Page 20 of 43 

Appendix A. – Raw Data

Note: The laboratory codes indicated in this appendix are not those used in the tables in 

the body of the paper since EPA assigned the lab codes to different labs from year to 

year. Labs have not been identified by name to maintain the anonymity of the 

participants. 

Year 1987 

Stove Catalytic ‐1 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5G 1 1.15 13.90 18.40 2.48

 2 2.16 13.30 18.00 4.25

 3 1.15 13.00 17.40 2.69

 4 1.35 13.30 18.20 3.67

 5 2.24 13.80 16.60 4.25

 6 0.79 13.30 17.40 1.18

 7 1.74 13.00 16.60 3.88

 8 0.73 10.00 18.00 1.09

 

Lab B Run DRY

5G 0 1.10 12.69 19.60 3.30

 1 2.90 12.76 18.90 28.11

 2 2.16 11.92 18.30 15.79

 3 0.56 12.19 16.50 2.83

 4 1.10 12.96 19.10 7.10

 5 0.99 12.76 20.30 4.07

 6 2.66 11.75 20.90 11.13

 7 2.03 11.97 20.90 6.18

 8 2.10 12.34 20.80 11.87

 9 1.69 11.15 21.30 6.60

 

Lab C Run DRY

5H 1 1.42 14.10 22.90 3.20

 2 1.89 13.20 24.29 3.63

 3 1.74 14.30 24.13 2.79

 4 1.71 14.00 23.07 2.08

 5 1.12 14.60 21.60 1.91

 6 1.21 13.80 22.20 1.35

 7 0.87 13.80 22.67 1.27

 8 0.97 14.30 21.63 0.89

 9 0.61 15.40 20.75 3.16
Page 21 of 43 

 

Lab D Run DRY

5G 1 2.13 15.03 19.90 5.50

 2 2.36 14.05 20.00 6.68

 3 1.36 13.97 20.30 6.07

 4 0.83 14.05 21.20 5.60

 5 0.57 14.03 21.00 3.40

 6 1.43 14.01 21.08 7.60

 7 1.10 14.05 20.10 5.14

 8 1.06 14.08 20.70 6.34

 

Lab E Run WET 

5G 1 2.06 14.90 18.70 6.30

 2 2.06 13.80 18.03 8.15

 3 1.56 14.60 17.86 7.30

 4 0.67 13.80 17.86 1.50

 5 1.34 13.80 18.20 6.15

 6 0.59 13.70 17.36 2.00

 7 0.91 13.80 17.86 8.25

 8 0.83 13.90 17.18 5.45

 

Lab E1 Run WET 

5H 1 2.06 14.90 18.70 5.50

 2 2.06 13.80 18.03 8.90

 3 1.56 14.60 17.86 9.50

 4 0.67 13.80 17.86 1.50

 5 1.34 13.80 18.20 4.90

 6 0.59 13.70 17.36 1.20

 7 0.91 13.80 17.86 8.80

 8 0.83 13.90 17.18 4.35

 

Lab F Run DRY

5G 1 1.69 13.52 21.30 10.30

 2 1.63 14.03 23.20 3.80

 3 0.99 13.36 23.00 2.70

 4 0.93 13.86 22.90 2.40

 5 0.93 13.88 22.70 2.00

 6 0.49 13.72 23.70 1.40

 7 1.74 14.25 23.80 3.20

 8 1.62 13.71 21.50 4.00
Page 22 of 43 

 

Lab G Run WET 

5G 1 4.27 14.50 18.80 8.29

 2 1.02 14.10 19.20 35.98

 3 0.72 14.30 19.00 19.49

 4 0.82 13.90 19.10 17.01

 5 0.77 14.10 19.30 1.36

 6 1.53 12.60 19.10 16.29

 7 1.46 13.90 19.20 13.16

 8 2.99 13.90 18.70 2.91

 

Lab H Run 

5H 1 1.68 n/a n/a 5.537 

 2 1.12 5.713 

 3 1.72 6.62 

 4 1.01 7.531 

 5 2.22 8.08 

 6 2.24 19.018 

 7 0.7 7.213 

 8 0.44 2.386 

 

Year 1988 

Stove Catalytic‐1 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5H 1 1.51 15.20 17.88 2.91

 2 1.96 15.50 18.67 3.66

 3 0.60 15.60 18.19 2.89

 4 0.65 15.90 19.09 9.32

 5 1.45 15.50 19.11 4.49

 6 1.20 15.60 19.94 8.94

 7 2.11 15.80 19.11 4.08

 8 1.22 15.80 17.94 2.85

 

Lab B Run WET 

5G 1 1.47 14.90 18.70 2.62

 2 1.03 13.60 20.00 2.72

 3 1.92 13.80 20.00 2.63

 4 2.08 12.60 20.00 5.25

 5 0.64 14.10 19.40 1.47
Page 23 of 43 

 6 0.61 13.10 17.00 1.54

 7 1.03 13.20 18.30 1.98

 8 2.13 13.40 18.40 5.38

 

Lab C Run DRY

5G 1 1.11 13.90 21.63 2.88

 2 0.87 13.60 20.73 2.56

 3 1.41 13.80 23.17 3.38

 4 0.75 13.80 21.13 1.34

 5 2.12 12.80 20.08 4.66

 6 0.59 13.00 22.71 1.40

 7 2.09 12.80 19.67 2.96

 8 1.32 13.10 21.92 2.80

 

Lab D Run DRY

5H 1 0.45 13.00 21.43 0.74

 2 2.13 14.30 21.64 2.39

 3 2.27 14.20 21.42 3.45

 4 1.82 13.90 22.50 1.89

 5 1.38 13.60 21.50 1.39

 6 0.76 14.40 22.73 1.23

 7 0.90 13.80 22.12 1.29

 8 1.18 14.20 21.46 1.61

 

Lab E Run DRY

5G 1 1.82 13.97 21.73 3.48

 2 2.92 12.96 22.32 1.71

 3 0.65 13.02 22.17 1.47

 4 1.83 12.95 21.97 4.64

 5 1.18 12.48 21.46 3.57

 6 1.14 14.09 22.28 2.55

 7 0.47 12.77 21.06 0.93

 8 2.27 12.62 22.10 5.06

 

Lab F Run DRY

5G 1 2.23 14.35 20.30 5.13

 2 1.85 14.95 20.80 6.47

 3 0.96 14.60 20.10 1.98

 4 1.47 14.55 21.10 3.77

 5 2.21 14.35 20.40 7.58
Page 24 of 43 

 6 0.49 14.70 20.80 0.99

 7 0.76 14.00 20.50 1.52

 8 1.03 14.05 20.30 1.96

 

Lab G Run DRY

5G 1 1.43 14.60 20.80 6.03

 2 2.04 13.60 21.10 6.47

 3 1.03 14.30 21.80 3.86

 4 0.75 13.90 22.70 2.73

 5 0.71 13.30 22.00 1.98

 6 0.93 13.60 19.80 2.75

 7 1.57 13.40 21.90 4.60

 8 1.17 13.40 20.10 3.61

 

Year 1989 

Stove Non‐Catalytic‐1 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

DRY

Emissions 

(g/h) 

5G 1 1.53 11.50 21.98 15.80

 2 0.89 9.80 22.38 10.95

 3 1.18 10.00 20.33 9.70

 4 0.58 10.40 20.56 20.10

 5 1.83 10.00 20.83 6.60

 6 0.91 9.80 20.56 11.35

 7 0.62 9.70 20.44 18.00

 8 1.77 10.40 20.46 9.85

 

Lab A1 Run DRY 

5H 1 1.53 11.50 21.98 16.10

 2 0.89 9.80 22.38 9.80

 3 1.18 10.00 20.33 9.35

 4 0.58 10.40 20.56 21.00

 5 1.83 10.00 20.83 9.85

 6 0.91 9.80 20.56 10.25

 7 0.62 9.70 20.44 17.25

 8 1.77 10.40 20.46 9.10

 

Lab B Run DRY 

5G 1 0.80 10.90 21.63 22.18

 2 1.04 11.20 20.85 13.82
Page 25 of 43 

 3 0.48 11.20 20.19 18.07

 4 0.98 11.40 21.98 14.19

 5 1.29 10.70 19.93 11.71

 6 1.58 11.40 23.48 13.69

 7 2.32 11.50 22.47 7.55

 8 2.06 11.60 23.05 7.46

 

Lab B1 Run DRY 

5G 1 0.80 10.90 21.63 22.05

 2 1.04 11.20 20.85 12.04

 3 0.48 11.20 20.19 18.39

 4 0.98 11.40 21.98 13.60

 5 1.29 10.70 19.93 10.93

 6 1.58 11.40 23.48 12.24

 7 2.32 11.50 22.47 6.83

 8 2.06 11.60 23.05 6.80

 

Lab C Run DRY 

5H 1 0.51 10.90 22.71 21.08

 2 0.79 10.90 22.15 14.41

 3 1.03 11.50 21.83 15.55

 4 0.92 11.50 21.66 16.28

 5 1.33 11.20 25.13 12.69

 6 1.47 11.20 21.88 15.05

 7 2.50 11.10 21.13 8.28

 8 2.60 11.60 21.73 8.54

 

Lab D Run DRY 

5G 1 1.53 10.90 21.88 17.75

 2 1.39 11.10 23.82 11.20

 3 1.95 11.40 23.34 14.02

 4 0.64 11.30 21.28 23.31

 5 1.03 11.30 21.74 19.69

 6 0.79 11.40 21.16 18.38

 7 2.02 10.50 21.75 4.93

 8 1.24 10.40 23.17 20.14

 

Lab E Run DRY 

5H 1 INVALID 

 2 1.7112 11.5 18.223 5.413
Page 26 of 43 

 3 0.8368 11.5 18.534 15.492

 4 1.3117 11.5 18.351 19.298

 5 1.8494 11.6 18.066 4.558

 6 1.1465 11.3 18.066 20.368

 7 1.1703 10.5 18.172 11.303

 8 0.8284 11.5 18.027 22.939

 9 1.9069 9.7 17.012 8.424

 

Year 1990 

Stove Non‐Catalytic‐2 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

DRY

Emissions 

(g/h) 

5H 1 1.70 17.69 21.49 3.07

 2 1.54 16.84 20.25 2.71

 3 1.02 17.36 21.00 5.68

 4 0.63 18.35 22.48 24.09

 5 4.39 19.03 23.51 8.92

 6 1.10 17.50 21.21 4.91

 7 4.84 18.58 22.82 11.23

 8 0.78 18.01 21.97 2.97

 

Lab B Run DRY 

5G 1 1.91 10.40 22.34 17.40

 2 0.64 9.50 22.33 8.80

 3 1.29 9.50 22.81 7.82

 4 1.09 10.00 22.33 5.04

 5 3.14 9.90 22.60 12.47

 6 0.99 9.60 23.48 7.82

 7 3.05 9.50 22.77 11.98

 8 0.74 10.70 21.60 38.04

 

Lab C Run DRY 

5G 1 2.18 10.40 22.63 13.36

 2 0.67 9.90 20.37 5.14

 3 3.49 10.80 21.95 14.89

 4 1.24 10.30 22.00 2.64

 5 1.24 10.40 21.23 2.63

 6 2.26 10.60 21.68 6.27

 7 1.28 9.80 22.23 5.66

 8 0.82 9.50 21.23 5.52

 
Page 27 of 43 

 

Lab D Run DRY 

5G3 1 4.375 9.36 21.33 10.26

 2 0.708 10.41 20.59 6.28

 3 0.639 10.93 19.89 7.24

 4 1.675 9.64 20.42 6.90

 5 1.665 10.45 20.42 9.58

 6 1.478 10.65 21.25 6.90

 7 1.387 10.34 21.65 7.50

 8 4.147 10.69 23.23 9.73

 

Year 1993 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5H 1 0.83 10.10 18.06 10.98

 2 3.23 10.10 18.06 13.02

 3 1.22 10.40 18.41 3.34

 4 1.41 10.50 18.39 1.62

 5 1.74 10.60 18.01 2.32

 6 3.20 10.00 17.69 8.20

 7 1.14 10.20 17.93 2.90

 8 0.88 10.20 17.56 6.30

 

 

Lab B Run DRY 

5G 1 3.75 14.40 23.65 9.31

 2 0.67 10.20 23.20 7.13

 3 2.91 10.30 22.57 5.12

 4 0.81 11.60 22.73 7.79

 5 1.20 10.90 22.48 3.72

 6 1.20 9.90 23.20 5.16

 7 1.36 12.30 21.87 1.54

 8 1.29 12.50 22.23 2.01

 

Lab C Run WET 

5G 1 0.94 9.56 18.82 7.02

 2 0.95 9.64 18.91 7.20

 3 1.07 10.17 19.10 5.79

 4 1.18 9.89 19.61 5.28

 5 1.39 10.04 18.81 5.35

 6 1.47 10.17 17.98 1.66
Page 28 of 43 

 7 5.18 9.99 18.17 28.47

 8 4.76 10.38 19.13 11.89

 

Year 1995 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5G 1 1.24 10.10 16.76 3.70

 2 1.07 10.20 18.82 12.00

 3 1.70 10.20 18.52 2.85

 4 4.08 11.10 19.03 11.26

 5 1.20 11.40 19.76 19.90

 6 4.73 11.60 17.57 14.44

 7 1.51 11.50 16.06 8.29

 8 0.95 10.50 18.69 11.00

 

Lab B Run DRY 

5G 1 0.70 10.29 21.90 14.46

 2 0.74 9.66 19.80 10.64

 3 0.87 10.83 19.90 7.49

 4 1.12 9.55 18.50 6.17

 5 1.38 9.80 19.10 4.26

 6 1.40 10.70 20.10 1.26

 7 

 8 

 

Year 1996 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5G 1 1.24 9.70 17.79 4.12

 2 0.94 9.30 18.04 9.45

 3 3.10 9.80 18.56 4.02

 4 1.59 10.30 17.96 2.84

 5 0.93 9.90 17.56 10.19

 6 3.70 9.80 16.81 11.27

 7 1.36 10.20 16.84 3.22

 8 1.13 10.60 17.79 8.07

 
Page 29 of 43 

 

Year 1997 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5G 1 0.94 10.00 17.48 3.59

 2 3.29 10.70 17.46 3.01

 3 1.42 10.10 17.65 4.96

 4 0.98 10.70 17.76 6.62

 5 1.13 10.60 17.84 4.70

 6 1.16 10.80 17.51 3.58

 7 3.17 10.30 14.51 6.66

 8 1.29 11.00 17.76 3.72

 

Lab B Run DRY 

5H 1 0.85 10.70 16.96 12.56

 2 0.79 10.20 17.62 3.78

 3 3.27 10.40 19.02 8.85

 4 1.22 10.60 17.75 0.82

 5 3.24 10.80 17.32 5.21

 6 1.32 10.50 16.96 1.18

 7 1.46 11.20 18.45 2.45

 8 1.06 11.10 17.75 3.54

 

Year 1999 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

WET

Emissions 

(g/h) 

5H 1 1.24 10.80 17.84 2.50

 2 4.18 11.30 19.39 5.53

 3 1.44 10.00 17.89 3.09

 4 4.49 10.20 19.10 4.78

 5 1.20 10.00 18.23 0.87

 6 1.61 10.20 19.02 0.96

 7 0.91 9.80 16.41 5.24

 8 0.98 10.00 17.27 1.28

 

Lab B Run DRY 

5G 1 1.16 10.60 23.87 6.06
Page 30 of 43 

 2 3.80 10.40 24.25 9.26

 3 1.62 10.30 23.71 4.11

 4 1.10 10.50 23.14 6.74

 5 0.99 10.20 21.31 9.16

 6 4.57 10.20 21.55 15.99

 7 1.32 10.60 21.68 3.34

 8 0.97 9.70 23.41 8.72

 

Lab C Run WET 

5G 1 0.966 10.50 17.18 2.42

 2 3.836 9.30 17.44 5.27

 3 1.150 9.50 17.69 3.76

 4 4.672 9.60 17.75 17.97

 5 0.617 9.70 17.70 4.35

 6 0.814 9.60 17.41 12.08

 7 1.262 9.40 17.63 2.45

 8 1.268 9.70 17.37 3.32

 

Year 2000 

Stove Non‐Catalytic‐3 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

DRY

Emissions 

(g/h) 

5G 1 1.26 10.08 22.51 6.10

 2 0.91 10.16 20.97 5.62

 3 0.79 10.04 21.65 7.42

 4 1.17 10.26 20.36 5.34

 5 1.11 10.19 23.05 4.72

 6 1.43 10.19 22.47 1.74

 7 4.71 10.16 22.37 11.40

 8 7.09 10.31 23.68 11.06

 

Lab B Run DRY 

5G 1 1.287 10.88 20.20 4.64

 2 0.699 10.33 19.70 59.60

 3 0.983 11.05 20.80 7.09

 4 3.967 10.76 21.20 19.82

 5 0.955 9.78 20.80 7.54

 6 1.428 9.62 21.30 4.74

 7 0.803 9.85 21.80 7.75

 8 2.901 10.67 22.00 14.42
Page 31 of 43 

 

Year 2005 

Stove Non‐Catalytic‐4 

Lab A Run 

Burn 

Rate 

(Kg/h) 

Test 

Load 

Wt. (lb) 

% M

DRY

Emissions 

(g/h) 

5G 1 2.54 9.10 22.00 6.30

 2 1.33 8.20 19.50 11.30

 3 0.54 9.00 19.20 24.30

 4 0.95 9.20 19.40 9.50

 5 0.91 8.40 20.10 10.80

 6 0.70 8.40 21.50 13.20

 7 1.36 8.00 23.20 5.60

 8 2.57 9.10 20.30 7.40

 

Lab B Run DRY 

5G 1 INVALID 8.89 21.79 

 2 0.91 8.34 20.85 23.82

 3 1.55 8.23 20.76 14.59

 4 3.20 8.13 21.51 6.10

 5 1.31 8.05 19.74 9.94

 6 0.55 8.05 20.44 19.55

 7 1.23 8.22 20.87 10.04

 8 2.83 8.23 20.14 7.93
Page 32 of 43 

Appendix B – Burn Rate versus Emissions Rate Charts 

Emissions v. Burn Rate 1987-1988

Cat Stove 1 y = 2.4542x + 2.9822

R2

 = 0.0794

y = 1.3643x + 1.4338

R2

 = 0.1816

0

5

10

15

20

25

30

35

40

0.0 1.0 2.0 3.0 4.0 5.0

Burn Rate (kg/hr)

Emissions (g/hr)

1987

1988

Linear (1987)

Linear (1988)

Burn Rate V. Emissions - 1989

Non-Cat Stove 1

y = -6.689x + 22.299

R2

 = 0.5151

0.00

5.00

10.00

15.00

20.00

25.00

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Burn Rate (kg/hr)

Emissions (g/hr)

1989

Linear (1989)
Page 33 of 43 

Burn Rate v. Emissions

Non-Cat Stove 2 y = 0.5034x + 8.2554

R2

 = 0.008

0

5

10

15

20

25

30

35

40

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Burn Rate (kg/h)

Emissions (g/hr)

1990

Linear (1990)

Burn Rate v. Emissions 

Non-Cat Stove 3

0

2

4

6

8

10

12

14

16

18

20

22

24

0.0 1.0 2.0 3.0 4.0 5.0

Burn Rate (kg/hr)

Emissions (g/hr)

1993

1995

1996

1997

1999

2000
Page 34 of 43 

Burn Rate v. Emissions

Non-Cat Stove 4 y = -4.6817x + 19.037

R2

 = 0.4428

0.00

5.00

10.00

15.00

20.00

25.00

30.00

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50

Burn rate (kg/h)

Emissions (g/hr)

2005

Linear (2005)
Page 35 of 43 

Appendix C - Measurement Uncertainty Analyses for EPA Wood Heater Test Methods

Every numerical physical measurement process is subject to a quantifiable level of 

uncertainty. This uncertainty is determined in the process of calibrating the measurement 

instrument. Therefore, the measurement uncertainty for each direct measurement required 

in a test method can be determined or estimated. When multiple measurements of specific 

quantities are combined into a final numerical measurement result, the combined 

uncertainty can be calculated by application of well defined and accepted procedures. 

These procedures are outlined fully in ISO “Guide to the Expression of Uncertainty in 

Measurement.” 

The ISO Guide defines two types of evaluation of measurement uncertainty. Type A is 

defined as “method of evaluation of uncertainty by statistical analysis of series of 

observations.” This is a quantitative evaluation. Type B is defined as a “method of 

evaluation of uncertainty by means other than the statistical analysis of series of 

observations.” This describes a more qualitative evaluation. The ISO Guide further 

elaborates that a “Type B evaluation of standard uncertainty is usually based on scientific 

judgment using all the relevant information available, which may include: 

• previous measurement data, 

• experience with, or general knowledge of, the behavior and property of relevant 

materials and instruments, 

• manufacturer’s specifications, 

• data provided in calibration and other reports, and 

• uncertainties assigned to reference data taken from handbooks.” 

Since there is no such thing as a wood heater test method calibration standard – that is, a 

wood heater with a “known” emissions rate – the uncertainty calculations and estimates 

that follow below are based on a hypothetical emissions value and evaluate only the 

particulate sampling method uncertainty relative to the hypothetical value. Variability in 

measured emissions due to the combination of the fueling and operation method and 

general wood burning variability are not components of measurement uncertainty. 

Measurement uncertainty quantifies only the potential difference between the actual 

measured result and the “true” value for one specific test run. Variation in results 

between different test runs includes both the effects of measurement uncertainty and 

many other variables that influence the actual performance of the product. 

An ISO Guide Type A measurement uncertainty analysis is included in this appendix for 

Method 5G-3 as an example of the way measurement uncertainty is determined using the 

ISO Guide procedures. Detailed measurement uncertainty calculations are not included 

for the other methods. However, estimates of the measurement uncertainties for the other 

5G methods along with the underlying assumptions used to achieve those estimates are 

provided. In the case of Method 5H, an estimate of overall method measurement 

uncertainty10 is provided. The estimate is based on both ISO Guide Type A and Type B 

evaluations. 

 

10 This estimate includes both measurement uncertainties that can be analyzed using ISO Guide Type A 

evaluations and other uncertainties that implicate Type B analyses. The use in this method of one approach 

for determining stack gas flow rate for setting the proportional sampling rate and another procedure for
Page 36 of 43 

EPA Methods 5G-3, 5G-1 and 5G-2

Analysis of the measurement uncertainty for the total particulate emissions in these 

dilution tunnel test methods requires combining the uncertainty of the following 

individual measurements. 

• Dilution tunnel volumetric flow rate. 

• Sampling system volumetric flow rate. 

• Filter and sample probe particulate gravimetric catch. 

Component Measurement Uncertainties:

• Dilution Tunnel Flow Rate—The dilution tunnel flow is measured by a standard 

Pitot tube and a differential pressure gauge. The direct measurement is of flow 

velocity at the operating temperature and pressure. Pitot tube measurements are 

considered a primary reference method and therefore the primary component of 

uncertainty in the velocity measurement is that of the differential pressure gauge. 

Conversion of the velocity measurement to flow rate at standard temperature and 

pressure conditions requires additional measurements of the tunnel cross sectional 

area, the temperature and the absolute pressure. An analysis of the overall 

uncertainty of the tunnel flow rate indicates that the measurements of tunnel 

cross-sectional area, temperature and pressure have a relatively minor affect. The 

procedure in this standard has been specified such that the overall uncertainty of 

this parameter is about ±2 % of the flow rate. 

• Sampling Volumetric Flow Rate—The equipment available to measure the 

sample flow rate has a high precision and can be calibrated such that the 

measurement uncertainty is ±1 % or better of the actual flow rate. For the 

purposes of this appendix, a ±1 % uncertainty will be assumed. 

• Filter and Probe Particulate Catch—The analytical balance specified in the 

method has a resolution of ±0.0001g (0.1 mg). For the purposes of measurement 

uncertainty analysis, we will conservatively assume that the balance resolution 

equals the measurement uncertainty. 

Detailed Measurement Uncertainty (MU) Analysis for Method 5G-3

Weighing Uncertainty

For Method 5G-3, a minimum total of four weighings is needed to determine the net 

particulate catch (filters and o-rings weighed together and probe weighed separately, 

before and after the test run). Since each weighing is subject to the same uncertainty, 

the overall uncertainty of the weighing is: 

MU ( MU ) X 2

weighing Balance = •

 

 determining stack gas flow rate for the calculation of total emissions is the principle source of measurement 

error that is assessed using the Type B Analysis. We note, however, that a rigorous analysis of the broader 

uncertainty implications of this and other Method 5H procedures is outside the scope of this paper. 
Page 37 of 43 

Where: 

MUBalance = Measurement uncertainty of the analytical balance (0.1 mg), and 

X = The total number of weight values (4) actually used to calculate 

emissions. Note: This does not include weight measurements made during pretest or 

post-test drying, only the final pretest and post-test weights. 

MU 0.1 4 2

weiighing = • = 0.20 

For a process that involves two pretest and two post-test weighings, this uncertainty is 

±0.20 mg. 

An additional component of the filter catch weight uncertainty is the potential for 

incomplete recovery of the filter material. There is no objective data to determine the 

magnitude of this factor, but laboratories familiar with the procedures report that they 

believe it to be less than 0.1 mg. Combining an additional ±0.1 mg with the weighing 

uncertainty results in an overall weighing uncertainty of ±0.22 mg (0.00022 g). 

Combined Measurement Uncertainty

Combined uncertainties are calculated by taking the square root of the sum of squares of 

the component uncertainties multiplied by a “sensitivity coefficient”. The sensitivity 

coefficient is the partial derivative of the function used to calculate the result with respect 

to the specific measurement parameter. The general formula (law of propagation of 

uncertainty) is: 

2

n n

2

1 1 uY = (( δY/ δx ) × u ) + ... + (( δY/ δx ) × u ) 

Where: 

δY/δxi = Partial derivative of the combining formula with respect to individual 

measurement xi, and 

ui = the uncertainty associated with that measurement.

The formula to calculate total particulate emissions is: 

ET = cs Qstd θ 

Where: 

cs = sample filter catch/(sample flow rate x test duration), g/dscf, 

Qstd = average dilution tunnel flow rate, dscf/min, and 

θ = sampling time, minutes. 
Page 38 of 43 

For the sake of example the following values will be used in an MU analysis of ET. 

Measurement Measured Value MU Units 

Sample Filter Catch 

(Fc) 

0.0210 ±0.00022 g 

Sample Flow Rate 

(Qsample) 

0.250 ±0.0025 dscfm 

Sampling Duration 

(θ) 

180 ±0.1 minutes 

Tunnel Flow Rate 

(Qstd) 

150 ±3 dscfm 

(1) Calculate the MU of cs: 

cs = Fc/(Qsample θ) = 0.0210/(0.25 x 180) = 0.000467 g/dscf 

0.0222

0.25 180

1

Q

1

F

c

c sample

s = • = • = δ θ

δ 

0.001867

0.25 180

0.021

Q

F

Q

c

2

sample

2

c

Sample

s = − •

− = •

− = δ θδ 

0.000003

0.25 180

0.0210

Q

c F

2 2

sample

s c = − •

− = •

− = δθ θ

δ 

2 2 2

s MUc = ( 0.00022 • 0.0222 ) + ( 0.0025 • −0.001867 ) + ( 0.1 • −0.000003 )

 MUcs = 0.000007 g/dscf

Thus, cs would be 0.467 mg/dscf ± 0.007 mg/dscf at a 95 % confidence level.

(2) Calculate ET and MUET

ET = csQstd θ = .000467 x 150 x 180 = 12.60 g 
Page 39 of 43 

Q 150 180 27 ,000

c

E

std

s

T = • θ = • = δ

δ

c 0.000467 180 0.084060

Q

E s

std

T = •θ = • = δ

δ

c Q 0.000467 150 0.070050 E s std

T = • = • = δθ

δ

2 2 2

ET MU = ( 27 ,000 • 0.000007 ) + ( 0.084060• 3 ) + (0.070050• 0.1 ) = 0.315 g

Thus the result in this example would be: 

ET = 12.60 g ± 0.32 g at a 95 % confidence level or stated as MU % = ±2.5%. 

Conclusion—This example, which is representative of the measurement method as it is 

currently applied to woodstoves under the EPA NSPS, indicates that the uncertainty 

related to the dilution tunnel flow rate measurement and filter catch weights are the 

primary components of the overall uncertainty of the result. Tunnel flow rates may be 

much higher than necessary to capture all emissions. This can influence the 

uncertainty of the test method. For example, increasing the tunnel flow rate from 150 to 

600 scfm in the above example increases the MU of the result to ±0.8 g or about ±6.5 % 

of the measured emissions. Therefore, keeping tunnel flow rates near the minimum 

necessary to reliably capture the exhaust stream, while keeping the tunnel velocity at a 

level that can be accurately measured during tests will minimize the uncertainty of the 

measurement. 

Measurement Uncertainty Estimate for EPA Method 5G-1

The major difference between EPA Method 5G-3 and 5G-1 is that 5G-1 uses solvent 

recovery to determine the particulate weight collected in the probe and front half of the 

front filter holder. The requirement to weigh a solvent blank results in at least one 

additional weighing before and after the test when compared to Method 5G-3. It is also 

common practice to weigh the 100mm filters separately which also results in another 

weighing before and after the test. These additional weighings add to uncertainty. There 

is also the likelihood of more substantial fiber loss while recovering adhered filter fibers 

from the filter gaskets with the 100 mm filters and the possibility of some loss of 

particulate from the probe during the solvent recovery process. 

If the same balance uncertainty of 0.1 mg for six total weighings is combined with a 

conservative estimate of 0.1% of total catch for the combination of fiber loss from the 

gaskets and particulate loss during solvent recovery is used, the resultant uncertainty for 

the filter and probe catch weight is significantly higher than with Method 5G-3. 
Page 40 of 43 

However, the sample flow rate, and therefore the probe and filter catch, with Method 5G1 is typically about twice as high as Method 5G-3 and this difference offsets much of the 

impact of the increase in weighing uncertainty on the overall method measurement 

uncertainty. Following the same analysis track as shown for Method 5G-3 above, the 

Method 5G-1 MU is about 10 - 15% higher than the MU for 5G-3. This MU% range of 

±2.7 to 3% is still quite good. 

Measurement Uncertainty Estimate for EPA Method 5G-2

Using the same logic applied to the Method 5G-1 measurement uncertainty estimate, the 

primary difference between 5G-1 and 5G-2 is in the number of filter train components 

subjected to solvent recovery and the total number of weighings before and after each test 

run. After consultation with a highly experienced 5G-2/5H test technician, it was 

determined that there are typically seven individual weight measurements before and 

after each test run. These include four beakers used for solvent recovery, a beaker for the 

solvent blank and the front and rear filters. These additional weighings contribute to 

additional uncertainty. 

It would not be unreasonable to assume that some additional fraction of particulate matter 

could be lost during solvent recovery due to all the additional components that are 

involved in the recovery. But, even if we continue to assume that a very conservative 

0.1% of the total particulate catch is lost from filter gaskets and solvent recovery, the 

weighing uncertainty increases by about 40% over Method 5G-1. However, since the 

total catch is expected to be somewhat higher with 5G-2, the larger catch mitigates some 

of the impact of the increased weighing uncertainty on the overall method measurement 

uncertainty. We would expect that the measurement uncertainty for Method 5G-2 is in 

the range of 15 -20% higher than Method 5G-1. The MU% is in the range of ±3 – 3.5% 

which is also quite good. 

Overall Measurement Uncertainty Estimate for EPA Method 5H

The same particulate sampling equipment is used for both Method 5H and Method 5G-2, 

but the methods are not close to the same in terms of overall measurement uncertainty. If 

we first examine the sampling protocols for the two methods, we find there are notable 

differences. These include: 

• The particulate concentrations in the 5H sampling stream are much higher than 

5G-2 (undiluted stack gas in 5H versus diluted gas in the tunnel with 5G-2). 

• Lower sampling rates are typically used for 5H to prevent filter plugging (0.1 – 

0.3 cfm for 5H and 0.5 cfm or higher for 5G-2). 

• Total particulate catches are higher (by an order of magnitude or more) for 5H 

compared to 5G-2. 

However, despite these differences, the particulate catch measurement uncertainty for 

Method 5H is not appreciably higher than that for 5G-2. This is because the impacts of 

the differences noted above cut to some extent in different directions, e.g., the added 

uncertainty contributed by the low sampling rate is somewhat mitigated by the much 

higher total particulate catch. Since the measurement uncertainty in the sample flow rate 
Page 41 of 43 

and the total particulate catch parameters are reasonably quantifiable, we would estimate 

their combined contribution to the overall measurement uncertainty of Method 5H using 

an ISO Guide Type A analysis to be no more than a few percentage points. At this level, 

the sampling-related measurement uncertainty is only a secondary contributor to the 

overall measurement uncertainty of Method 5H. 

The primary contributor to the large increase in overall measurement uncertainty 

associated with Method 5H when compared to Method 5G-2 (or the other dilution tunnel 

methods) is the determination of the stack gas flow rate over the course of the test. The 

associated complexities with this issue make quantitative assessments of the contribution 

to measurement uncertainty unworkable using ISO Guide Type A evaluations. The more 

qualitative Type B evaluation is appropriate in this case. 

Factors Contributing to Stack Flow Uncertainty

The stack flow must be determined for purposes of knowing where to set the sample flow 

rate in order to maintain sample flow proportionality over the test run. The procedure 

specified in Method 5H is a tracer gas method. This method has been generally replaced 

by adding a dilution tunnel to the system and determining stack flow using the ratio of 

tunnel CO2 to stack CO2 multiplied by the easily measured tunnel flow. At each 

sampling interval, the sample flow is adjusted based on this stack flow determination. 

There is additional uncertainty in this procedure if a single gas analyzer is used to 

determine both the stack and tunnel CO2 concentrations since the accuracy of these 

instruments is generally 1% of full scale and the tunnel CO2 readings are quite low. 

Some of this can be mitigated by using two analyzers or multi-scale analyzers where the 

accuracy can better match the concentrations. 

The 5H procedures then go on to calculate stack gas flow for the purpose of determining 

emissions using a mass balance algorithm where carbon from the fuel is balanced against 

the carbon measured in the stack (CO2 and CO) and an assumed hydrocarbon value to 

make the balance work. The stack flow calculated by this means often results in very 

different incremental stack flow values than the tracer gas methods. The impact of this 

difference is that the proportionality of the sample gas flow rate to the stack gas flow rate 

can be much different between the two procedures. Additionally, there is a wider range 

in variation from proportional sample flow rate allowed in this method than for the 

dilution tunnel methods. The allowable range is a necessity due to the fact that frequent 

stack gas flow calculations and sample flow rate adjustments are needed due to the 

instability in the actual stack gas flow. The impact of proportionality ranges is hard to 

asses but contribution to method uncertainty is definitely real. Finally, the total stack gas 

flow over the entire test run is also impacted by the mass balance procedure and this 

obviously directly impacts the particulate emission determination. The uncertainty of the 

carbon balance stack flow rate calculation is impacted by the unknown uncertainties of 

the fuel carbon content, the assumed hydrocarbon concentration and the measurement 

uncertainty of stack CO and CO2 measurements. 

Overall measurement uncertainty for 5H is commonly estimated in the ±20 – 30% range 

by those with considerable experience with the method. The increment of measurement 

uncertainty that can be analyzed using ISO Guide Type A procedures accounts for only a 
Page 42 of 43 

few percentage points of this range. The remainder (~17 – 27%) can be supported by a 

qualitative (Type B) analysis using reasonable estimates of the measurement uncertainties 

associated with the stack flow procedures in Method 5H. This estimate corresponds to 

the magnitude of the typical difference between stack flow rates determined by the tracer 

gas and carbon balance procedures for an individual test run. 
Page 43 of 43 

REFERENCES

1. 40 CFR, Part 60, Subpart AAA – Standards of Performance for New Residential 

Wood Heaters. 

2. EPA Woodstove NSPS Proficiency Test Results – Supplied by Michael Toney – 

EPA OAQPS, Emissions Measurement Branch. 

3. Guide to the Expression of Uncertainty in Measurements, First Edition 1995, 

International Organization for Standards. 

4. ASTM E177-2008 “Standard Practice for Use of the Terms Precision and Bias in 

ASTM Test Methods”, ASTM International, 100 Barr Harbor Drive, PO Box 

C700, West Conshohocken, PA 19428-2959. 

5. ASTM E691-2009 – “Standard Practice for Conducting an Interlaboratory Study 

to Determine the Precision of a Test Method”, ASTM International, 100 Barr 

Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. 

6. CSA B415.1-2010 - Performance Testing of Solid-Fuel-Burning Heating 

Appliances, CSA International, 5060 Spectrum Way, Suite 100, Mississauga, 

Ontario, Canada L4W 5N6, March, 2010. 

7. ASTM E2515 – 2007 – “Standard Test Method for Determination of Particulate 

Matter Emissions Collected by a Dilution Tunnel”, ASTM International, 100 Barr 

Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. 

8. ASTM E2618 – 2009 – “Standard Test Method for Measurement of Particulate 

Emissions and Heating Efficiency of Outdoor Solid Fuel-Fired Hydronic Heating 

Appliances”, ASTM International, 100 Barr Harbor Drive, PO Box C700, West 

Conshohocken, PA 19428-2959. 

9. Mark’s Standard Handbook for Mechanical Engineers, Ninth Edition, Eugene A 

Avallone, Theodore Baumeister III, McGraw Hill Book Co., 1987.