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# Final Report

EPA Wood Heater Emission Test Method Comparison Study

Prepared by Robert Ferguson Ferguson, Andors & Company

For the Hearth, Patio and Barbecue Association

December 1, 2010Page 2 of 9 Background During the Regulatory Negotiation (RegNeg) that resulted in the Wood Heater New Source Performance Standard (NSPS) in 1988, th e data that was available to determine Best Demonstrated Technology (BDT) and th e resultant passing grades was from the Oregon DEQ wood heater certification program . That data had been collected using Oregon Method 7, a method that was based on the traditional EPA Method 5 with its origins in industrial stack sampling. Since the NSPS passing grades were set using these data, this method became the “reference method” for the NSPS. The method, re-titled as Method 5H in the NSPS, sampled in the heater stack and includes a heated filter and a series of cooled glass impingers as the way to collect the particulate matter exiting the wood heater. Work had been underway l eading up to and during the RegNeg on a different method for measuring particulates. This method involved collecting the smoke from the wood heater chimney in a hood and mixing it with a fairly large amount of ambient dilution air before drawing the part iculate sample. The RegNeg committee felt that this method had advantages over Method 5H and it was included as an alternative to

Method 5H. This “dilution tunnel” method was designated Method 5G, and was further refined to include Methods 5G-1, 5G-2 and 5G-3 . Method 5G-1 uses one filter train with two large (100 mm) filters (primary and back -up) to collect the particulate sample.

Method 5G-3 uses two filter trains each with of two smaller (47mm) filters and requires a certain precision level between tr ains to have a valid test. Method 5G-2 uses the Method 5H train (heated filter and cooled glass im pingers) but with the sample taken from the

dilution tunnel rather than the heater stack.

However, since the versions of Method 5G (5G- 1 and 5G-3) that prescribed collecting the particulate sample on unheated filters (wit hout impingers) were typically collecting less total particulate than the methods (5H and 5G-2) that in cluded both a filter and cooled impingers, an equation was developed to “adju st” Method 5G-1 and 5G-3 data to Method 5H equivalents so that the data could be used to determine NSPS compliance.

To develop the equivalency equation, data sets were considered that included test runs using both test methods simultaneously. The data that was availa ble did not define a clear relationship between the methods. Using “engineering judgment”, EPA proposed

that the “best fit” to this da ta set was a non-linear curve, wh ich resulted in an exponential conversion equation. In retr ospect, it has become appa rent that the test method correlation issue and the potential impacts for the future were not given adequate consideration by the RegNeg Committee.

The current equation per EPA Method 28 is: 

### E 5Hequiv 

### = 1.82 x E 5GMeas 0.83

One problem is that the data that was us ed to determine the correlation between the methods was gathered from either conventi onal wood heaters or w ood heaters certified by the Oregon program. The emission rates we re generally quite high, especially when compared with today’s wood heaters. Also, examination of the data shows significant differences in the test method relationship s between the different laboratories that generated the data. Finally, ther e is a logic gap in the formul ation of the current equation. The equation imposes the highest conversion pe nalty, as a percentage of the measuredPage 3 of 9 emissions, at the lowest emission range. We have to assume that as wood heaters achieve lower and lower PM 2.5 emission rates, the volatile material s (those that would be caught in the method 5H impinger train) are being combusted rather than being emitted to the atmosphere. So, in theory, as total particulate emissions are reduced, the two methods should get closer and closer to the same result, ultimately converging at zero. However, the Method 28 conversion equa tion, perversely, operates in the opposite direction; as wood heaters get cleaner a nd cleaner, the current 5G – 5H conversion equation yields 5H equivalent values that increase in magnitude, with the highest percentage-based penalty at the lowest emission rates.

Implications for BDT determinations in revising the NSPS

A. Wood heater Database Some manufacturers recognized the impact of the present adjustment equation on their product emission ratings and have opted to te st for certification us ing Method 5H or 5G2, thus avoiding the adjustment issue all togeth er. Models that have been tested using Methods 5G-1 and 5G-3 were certified using c onverted values, which because of the flaw in the equation, has probably oversta ted their actual emission rates.

With the upcoming NSPS revisions, EPA has te ntatively agreed to have only one test method, rather than the two plus variations curr ently allowed. That method is expected to be ASTM E2515, a reformulation of EPA Me thod 5G-3. Moreover, the adjustment equation will be eliminated; there will be no need for it since the reference method will

be the dilution tunnel with dual filter tr ains (ASTM E2515). This is universally considered to be a good idea.

The enhanced EPA certified heater database currently has usable data for 147 heater models (including certified pellet heaters). Looking only at cataly tic and non-catalytic wood heaters, for those models that reported what test method was used, 49 heaters used

5H or 5G-2 and 52 used 5G-1 or 5G-3. This is shown graphically in Chart 1.

B. Impact on BDT Determinations

EPA must do a comprehensive analysis of da ta from the currently certified wood heater models to determine BDT and ultimately any new passing grade or grades. Since currently certified wood heater s have been tested using ei ther Method 5G or Method 5H, the data must be all evaluated for purposes of the BDT analysis as 5G data or 5G equivalents.

For heaters tested with dilution tunnel/filters only methods (Method 5G-1 or 5G-3), either

the raw emission values can be used or th e adjusted data can be converted back by reversing the adjustment equation.

The real issue is what to do with the 5H/5G-2 data sets. In these cases, “dilution tunnel/ filter only” data do not exist so using raw data is not an option. To preserve these data sets (representing almost half of the availabl e data for wood heaters) the test results will have to be adjusted downward to 5G-3 e quivalents using another methodology. Since thePage 4 of 9 current adjustment equation is now widely regarded as being grossly unrepresentative of the relationship between the tw o test methods, especially in the lower emission ranges typical of current heater technology, its us e for conversion of the 5H data is not appropriate or defendable. The upcoming BDT determination, and therefore future passing grades, could be unfairl y biased low if we are not able to establish a method conversion equation that is more representative at low emission rates. This impact could be very significant based on th e large percentage of 5H (or 5G-2) tested heaters in the

database.

Recent Data Gathering

In cooperation with EPA (both OAQPS and OECA) HPBA funded an emission test method comparison program. The test me thod comparison testing was piggy-backed onto EPA certification testing with OECA a llowing the comparison data (data from the second test method) to be excluded from the h eater certification app lication. The testing was conducted between May and November, 2010 with three laboratorie s participating.

Seven total heater models were tested a nd the models included both non-catalytic and pellet models. No catalytic heaters were available for testing. The participating laboratories provided HPBA with masked da ta sets showing the direct comparison

between methods for each of the test r uns conducted (including other relevant

information about the heater a nd test conditions). A total of 31 individu al test run comprise the resultant database.

Because the test program relied on testing that was being scheduled by manufacturers at random rather than as part of a specifically designed test program, the resultant test data included three permutations of data compar ison. These were 5G-3 versus 5G-2, 5G-3

versus 5H and 5G-1 versus 5G-2. This three-way dispersion of datasets has made analysis of the data more complicated than was anticipated when test program was initially conceived.

Table 1 presents the final method comparison data.

Data Analysis

The purpose of this data gathering effort was to try to define a more justifiable relationship between the 5H/5G-2 and 5G-1 /5G-3 emission measurement methods as a way to preserve the usefulness of the 5H/5G-2 datasets in the certifi ed heater database.

Although the data that was gathered may be vi ewed as less than ideal for its intended purpose, at least from a statistical perspective, it does give at least a qualitative look at the test method relationships with all their inhere nt variability imbedded in the dispersion of

the results.

After considering the options for treatment of the data, the conclusion that was reached was that the best way to consider the data was in aggregate. Th is approach groups the 5G-1 and 5G-3 data together and compares it to the corresponding 5H or 5G-2 data.Page 5 of 9 Table 2 shows the aggregated datasets.

The datasets are plotted in Ch art 2. The data are further id entified on this chart by the test method comparison groupings. A linear re gression line with a y-intercept = 0 is shown on the chart using all the aggregated data points. The slope of this line is 1.116. Itmight be tempting to eliminate some of the data from the analysis. For example, the 5G3 versus 5H data show a possible systematic difference between the methods in the two

test series that included 5H testing (see Heaters B and C in Table 1). However, as pointed out in the test method variability pa per presented to EPA in October, Method 5H has significant inherent va riability due primarily to stack flow measurement and calculation procedure disconnects and this recently collected method comparison data may simply reflect the predictable variab ility including both random and systematic elements. Since there is no technical justifi cation for disregarding any of the datasets, all data points were used in the regression.

The correlation coefficient (R) is 0.9 for this regression line. This value infers a relatively strong relations hip between the data. Although the resultant R 2 (coefficient of determination) value at 0.82 ( 82%) could be viewed as bein g lower than might otherwise be desired, it does indicate that the regre ssion formula is a fairly good predictor of the overall method relationship. For the purposes of conversion of the 5H/5G-2 datasets to their 5G-3 equivalents, and recognizing that the overall variability in the test methods

themselves affects both the data in this databa se and to an even highe r degree the data in the heater certification database, the follo wing formula can be used with reasonable confidence when converting from 5H or 5G-2 emissions to 5G-3 equivalents.



### E 5G3equiv 

### = E 5H 

### /1.116Page 6 of 9 Chart 1 – Certification Test Method Distribution

Cat, Non-Cat & Pellet Heaters, All QC'd Data - Methods 5G1/5G3 vs. Method 5H/5G2 Data

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65

RankingM28 Weighted Ave. Emission Rate - g/hr 5G1/5G3

5H/5G2 Method 5G1/5G3
Cats. = 9, NC = 43, Pellet = 14

Method 5H/5G2
Cats. = 6, NC = 43, Pellet = 3 Data 1/25/10

3/23/10 Cat Non-Cat Non-Cat PelletPage 7 of 9 Table 1 – Final Emission Test Method Comparison DataPage 8 of 9 Table 2 – Aggregated DataPage 9 of 9 Chart 2 – Emission Test Method ComparisonEmission Test Method Comparison Datay = 1.1163xR2= 0.8180.01.02.03.04.05.06.07.08.09.010.011.012.013.014.00.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0EPA Method 5G1 or 5G3 Emission Rate (Unadjusted) - g/hr

EPA Method 5G2 or 5H Emission Rate - g/hrAll 5G1/3 v. All 5G2/5H5G3 v. 5G25G3 v. 5H5G1 v. 5G2Linear (All 5G1/3 v. All 5G2/5H)11/29/10