ENGINEERING LABORATORY TEST REPORT 

TITLE OF REPORT: 

Analysis of THC as a Rich Burn 

Formaldehyde Surrogate 

PROJECT NO.: 22208 

MATRIX ONE 

DOCUMENT NO(S): TR-4854 

PRODUCT 

LINE: VHP GSI 

OWNER: Dennis Spaulding 

APPLICABLE 

DOCUMENTS: X-3281, EPA-454/R-00-037 (EPA – CSU testing); CAE Report #10845 

TEST PURPOSE: 

Develop pre-cat and post-cat CH2O – THC correlations for rich burn, 

natural gas engines, using a test structure that mimics the EPA-454/R00-037 testing done by the Environmental Protection Agency (EPA) at 

Colorado State University (CSU). Also, extend the test matrix to 

provide sufficient statistical power to likely identify and quantity factors 

that could affect this correlation and to ensure a robust solution. 

ABSTRACT: 

The test was run using Clean Air Engineering’s (CAE) FTIR 

instrumentation as well as Waukesha’s in lab emissions bench. The 

test block that mimics the EPA-CSU test produced a pre-cat THC 

correlation that was superior to the EPA-CSU CO lean burn correlation. 

When the extended matrix was considered the pre-cat correlation 

developed was not as good. A more complicated pre-cat correlation 

was developed from the extended matrix that was superior to both the 

simple “block 1” correlation and the EPA-CSU CO lean burn correlation. 

Post-cat data were also taken. Post-cat formaldehyde does not appear 

to require a surrogate correlation as virtually complete CH2O 

destruction occurred regardless of pre-cat CH2O over a broad range of 

operating conditions. 

KEY WORDS: Rich burn, THC, CH2O, formaldehyde, surrogate, correlation 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 2 of 17 

INTRODUCTION 

Regulatory changes are being considered relative to formaldehyde emissions from IC 

engines (RICE NESHAP rule, reference 74FR9698, Docket ID No. EPA-HQ-OAR-2008-

0708). CO measurement is expected to continue to be allowed as a surrogate for 

actual formaldehyde (CH2O) measurement on lean burn engines. For rich burn, spark 

ignited engines it is expected that actual formaldehyde measurement will continue to be 

required unless a suitable surrogate correlation can be demonstrated. 

A recent post-review of test X-3281 indicated a strong likelihood that a pre-catalyst 

THC-CH2O correlation exists, but those data were not taken with the intent of 

developing a correlation. Also, those data did not include any post-catalyst 

measurements. However, the data and analysis were good enough to be submitted to 

the EPA to show the potential surrogate relationship and allow time for a proper data 

collection and review to be conducted. 

OBJECTIVES 

Develop pre-cat and post-cat CH2O – THC correlations for rich burn engines, using a 

test structure that mimics the EPA-454/R-00-037 testing done by the Environmental 

Protection Agency (EPA) at Colorado State University (CSU) in 2000. Also, extend the 

test matrix to provide sufficient statistical power to likely identify and quantity factors that 

could affect this correlation and to ensure a robust solution. 

CONCLUSIONS 

The simple correlation developed using the 16 point matrix that mimics the EPA-CSU 

test (block 1) between pre-cat THC and pre-cat CH2O for rich burn engines is better 

than the lean burn CO - CH2O correlation from the EPA-CSU test. The EPA-CSU test 

in 2000 is believed to have been used by the EPA to determine the surrogate 

correlation between CO and CH2O for lean burn engines. 

When both data blocks are included in the analysis, the simple correlation fit is not as 

good as the block 1 only fit and slightly worse than the fit believed to have been used for 

the lean burn correlation. However, the slope is about the same so, while adding more 

data makes the correlation more “noisy”, the “strength” of the correlation remains. 

While this simple correlation applied to a broad data set or application base may be a 

slightly “noisier” correlation than is expected from block 1 alone, block 1 was based on a 

test design that mimicked what is thought to have been used for the lean burn CO 

correlation so it will likely be no different than what is seen in practice with the lean burn 

correlation. Also, an equation was developed to “clean up” this correlation considerably 

using engine parameter measurements that are readily available through Waukesha’s 

ESM control ESP interface. 

There does not appear to be a good correlation between post-cat CH2O and either precat CH2O or post-cat THC. However, that does not appear to be necessary as virtually 

complete CH2O reduction occurs regardless of the fairly broad conditions varied in this 

test. 

RECOMMENDATIONS 

It is recommended that the simple THC correlations created and shown in Figure 14 be 

submitted to the EPA as the rich burn engine out formaldehyde surrogate that is 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 3 of 17 

equivalent to the already accepted lean burn CO surrogate. The better - but more 

complicated - correlation also developed in this report can be used if necessary. 

It is also recommended that, since a properly functioning NSCR catalyst can be 

expected to provide virtually complete formaldehyde destruction, no post-cat correlation 

is needed with THC or any other surrogate. 

TEST EQUIPMENT 

L7044GSI installed in cell 17, ESM Cal.: C21H000_NEW_XFR_CURVE.dat 

Maxim Catalytic Converter, model 3WC 674-20, installed in the test cell. 

WED Horiba emissions bench Model#: PN-255951-1 Serial#: 0001 

MKS FTIR owned and operated by Clean Air Engineering (See CAE report for details) 

RESULTS 

Test Overview

The base test was designed to mimic a test contracted by the EPA that was run at CSU 

in 2000 and believed used to establish the current lean burn CH2O – CO correlation. 

That base test is as shown in Table 1. 

Table 1 - Base EPA Test 

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

Run A:Speed B:Torque C:A/F D:Timing E:ICW F:JWT

rpm % lambda Offset °F °F

1 1200 100 0.9985 0 130 180

2 1200 70 0.9985 0 130 180

3 1000 70 0.9985 0 130 180

4 1000 100 0.9985 0 130 180

5 1200 100 0.993 0 130 180

6 1200 100 1.004 0 130 180

7 1200 70 1.004 0 130 180

8 1000 100 0.993 0 130 180

9 1200 100 0.9985 0 120 180

10 1200 100 0.9985 0 140 180

11 1200 100 0.9985 0 130 170

12 1200 100 0.9985 0 130 190

13 1200 100 0.9985 -5 130 180

14 1200 100 0.9985 -2.5 130 180

15 1200 100 0.9985 0 130 180

16 1200 100 0.9985 0 130 180

This block 1 test should be sufficient to demonstrate the expected CH2O – THC 

correlation, however, there are issues with the base design particularly relative to the 

factor power (see highlighted section of Attachment A). Therefore, the test was 

augmented with another block to provide acceptable factor power for a full quadratic 

model. The additional block 2 included the points shown in Table 2. 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 4 of 17 

Table 2 - Test Augmentation for better statistical power 

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

Run A:Speed B:Torque C:A/F D:Timing E:ICW F:JWT

rpm % lambda Offset °F °F

17 1000 85 0.9985 -2.5 130 180

18 1200 70 1.004 -5 120 190

19 1200 100 0.993 -5 120 190

20 1000 70 0.993 -2.5 120 170

21 1100 100 0.993 -5 140 170

22 1000 100 0.993 -5 140 190

23 1200 70 1.004 -5 140 170

24 1200 100 1.004 -5 120 170

25 1000 100 1.004 -5 140 170

26 1200 70 0.993 -5 120 170

27 1000 85 1.004 0 120 190

28 1000 70 1.004 -5 140 190

29 1000 70 1.004 0 120 170

30 1000 100 1.004 -5 120 190

31 1000 100 0.993 -5 120 170

32 1000 70 0.993 -5 140 170

33 1200 85 1.004 -5 140 190

34 1000 85 1.004 0 140 170

35 1000 70 0.993 0 120 190

36 1100 70 0.993 -5 140 190

37 1000 85 1.004 -5 120 170

38 1100 70 1.004 0 140 190

39 1000 100 0.9985 0 120 170

40 1000 70 0.993 -5 120 190

41 1200 85 0.993 0 120 170

42 1100 100 1.004 0 140 190

43 1200 100 0.993 0 140 180

44 1000 70 1.004 0 140 190

45 1200 70 0.993 -2.5 140 190

46 1100 70 0.993 0 140 170

As shown in Attachment B this provides a much better test that has adequate power to 

identify factor effects of moderate magnitude. 

When Clean Air Engineering (CAE) arrived they did not bring any sample probes; they 

intended to just tap into the side of the exhaust stack. This has been a poor practice in 

Waukesha experience and is not compliant with EPA sampling requirements. So WED 

gathered probes that could be used from lab stock and these were installed. 

The CAE FTIR instrumentation was set up following their usual protocol of collecting 10 

spectrum samples, then adding these samples to provide one “valid” sample. The 

spectrum samples are taken once per second, so “valid” samples can be posted once 

every ten seconds. 

The first task was to determine how many samples were required to get a consistent 

average. However, while attempting this, several issues were encountered. The first 

issue was very high catalyst outlet temperatures particularly at low engine loads. This 

was determined to be caused by having the wrong spark plugs installed in the engine. 

The cylinder heads that were used on the engine for this test were just transferred from 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 5 of 17 

another engine that was configured as an LT. The spark plugs had not been checked 

as part of this transfer since it was rushed from a time stand point. The 69919D spark 

plugs were removed and correct 60999Z plugs gapped to 0.011” were installed. There 

was no trouble for the remainder of the testing. The second issue encountered was a 

high %O2 reading from the CAE instrumentation compared to the Waukesha Horiba 

instrumentation. There was a rigorous investigation to determine the source of a 

perceived leak. Finally, the lab’s Testo was plugged into the exhaust of CAE’s FTIR 

and it registered little O2 proving that CAE’s instrument was not reading correctly. 

Since there was good agreement on NOx, CO, CO2 and THC between WED and CAE 

instruments it was determined that the FTIR results were OK and only the O2 values 

from CAE’s instruments had to be discarded. The WED O2 readings were used for 

testing. Since O2 is a good indicator of a line leak the Testo was left in the FTIR 

exhaust and checked with each data collect to ensure the reading was less than 0.5% 

O2. After these issues were cleared up the testing went well until about noon on Friday 

(point 43 in run order). Then, apparently, a valve was bumped in the CAE trailer 

causing a reduced sample flow resulting in very long stabilization times, longer than the 

expected total sampling time. So, points 43-46 were re-run to get good data after a flow 

valve adjustment. 

Sample Time Determination

To determine the sampling time required, run #1 was monitored for 1⁄2 hour pre-cat and 

1⁄2 hour post cat. The stripchart results of these runs are shown in Figure 1 and Figure 

2. 

Pre Cat Stripchart

-20

-15

-10

-5

0

5

10

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197

Sample Number

Acetaldehyde, Acrolein, Formaldehyde (ppm)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

CO, NO (ppm)

Acetaldehyde 191C Acrolein 191c Formaldehyde 191C CO ppm 191C (1of2) NO 191C

Figure 1 - Run 1 Pre-Cat Stripchart 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 6 of 17 

Post Cat Stripchart

-20

-15

-10

-5

0

5

10

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204 211

Sample Number

Acetaldehyde, Acrolein, Formaldehyde (ppm)

0

50

100

150

200

250

300

350

400

450

CO, NO (ppm)

Acetaldehyde 191C Acrolein 191c Formaldehyde 191C CO ppm 191C (1of2) NO 191C

Figure 2 - Run 1 Post-Cat Stripchart 

The data from these stripcharts were then averaged in a building average manner, 

where initially the first two samples were averaged, and then the first three, and then the 

first four, and so on until the last value became the grand average of the whole data set. 

The results of this are shown in Figure 3 and Figure 4. This analysis follows the Law of 

Large Numbers where, after a certain number of samples form an average, adding 

more samples does not significantly affect the average. As can be seen from these 

figures about 60 samples were required to get a stable average. So, given the CAE 

sampling routine described above, this would require sampling points for 10 minutes to 

obtain a stable, representative value. After each 10 minute sample charts similar to 

those shown in Figure 1 and Figure 2 were created and reviewed to ensure the sample 

was stable. Charts similar to those shown in Figure 3 and Figure 4 were also created 

and reviewed to ensure enough data had been taken to obtain a stable average. These 

results are not included in this report but are available in the “Processed CAE Data 

Files.zip” in Matrix under this TR. 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 7 of 17 

Pre Cat Building Average

-6

-4

-2

0

2

4

6

8

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204

Samples Averaged

Acetaldehyde, Acrolein, Formaldehyde (ppm)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

CO, NO (ppm)

Acetaldehyde 191C Acrolein 191c Formaldehyde 191C CO ppm 191C (1of2) NO 191C

Figure 3 - Run 1 Pre-Cat Building Average 

Post Cat Building Average

-7

-6

-5

-4

-3

-2

-1

0

1

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204 211

Samples Averaged

Acetaldehyde, Acrolein, Formaldehyde (ppm)

0

50

100

150

200

250

CO, NO (ppm)

Acetaldehyde 191C Acrolein 191c Formaldehyde 191C CO ppm 191C (1of2) NO 191C

Figure 4 - Run 1 Post-Cat Building Average 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 8 of 17 

Data Collection Monitoring

Since this test was essentially a “one shot” deal where, if next week after further 

analysis a point needed to be re-run it would be impossible, extra steps were taken to 

ensure the data were good. For each data collect the CAE FTIR value was subtracted 

from the WED emissions bench value for pre-cat and post-cat for CO, NOx, CO2, and 

THC. The summary results of these are shown in Figure 5 through Figure 12. One 

thing to note is that, since there were two different technologies used to measure these 

results, the values were not necessarily expected to match exactly. The values were 

just used for trend review, making sure that the last value was not substantially different 

than the “mass” of values accumulated before. The minimal outliers (shown as “*” in the 

boxplot portion) are evidence that the data are consistent and the discrepancies are 

either random or a constant “block” offset. 

-200 -0 200 400

Median

Mean

150 160 170 180 190 200 210

1st Q uartile 130.03

Median 177.49

3rd Q uartile 235.95

Maximum 425.13

164.80 213.13

154.33 201.66

67.49 102.49

A -Squared 0.41

P-V alue 0.332

Mean 188.97

StDev 81.37

V ariance 6621.77

Skewness 0.654292

Kurtosis 0.364089

N 46

Minimum 44.57

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE CO (ppm dry)

Sample Label = Pre Cat

Figure 5 - WED-CAE Pre-Cat CO Summary 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 9 of 17 

-300 -240 -180 -120 -60 0

Median

Mean

-190 -180 -170 -160 -150

1st Q uartile -204.16

Median -163.27

3rd Q uartile -134.29

Maximum -72.22

-186.24 -156.49

-181.75 -151.70

40.99 62.54

A -Squared 0.38

P-V alue 0.383

Mean -171.36

StDev 49.51

V ariance 2451.05

Skewness -0.411791

Kurtosis 0.022860

N 45

Minimum -288.41

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE NOx (ppm dry)

Sample Label = Pre Cat

Figure 6 - WED-CAE Pre-Cat NOx Summary 

1.1 1.2 1.3 1.4 1.5

Median

Mean

1.30 1.32 1.34 1.36 1.38 1.40

1st Q uartile 1.2822

Median 1.3296

3rd Q uartile 1.3991

Maximum 1.5241

1.3126 1.3674

1.3028 1.3891

0.0765 0.1162

A -Squared 0.33

P-V alue 0.506

Mean 1.3400

StDev 0.0922

V ariance 0.0085

Skewness 0.034271

Kurtosis -0.808170

N 46

Minimum 1.1620

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE CO2 (% dry)

Sample Label = Pre Cat

Figure 7 - WED-CAE Pre-Cat CO2 Summary 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 10 of 17 

-30 0 30 60 90

Median

Mean

60 62 64 66 68 70 72

1st Q uartile 57.581

Median 66.041

3rd Q uartile 78.851

Maximum 91.463

64.852 71.589

60.493 71.714

9.409 14.287

A -Squared 1.37

P-V alue < 0.005

Mean 68.221

StDev 11.343

V ariance 128.671

Skewness 0.39071

Kurtosis -1.23408

N 46

Minimum 54.264

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE THC (ppm wet)

Sample Label = Pre Cat

Figure 8 - WED-CAE Pre-Cat THC Summary 

-200 -0 200 400

Median

Mean

-60 -50 -40 -30 -20 -10

1st Q uartile -50.301

Median -18.930

3rd Q uartile -8.412

Maximum 52.756

-58.379 -21.131

-26.319 -13.853

52.018 78.990

A -Squared 4.03

P-V alue < 0.005

Mean -39.755

StDev 62.715

V ariance 3933.122

Skewness -2.26909

Kurtosis 6.87708

N 46

Minimum -306.634

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE CO (ppm dry)

Sample Label = Post Cat

Figure 9 - WED-CAE Post-Cat CO Summary 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 11 of 17 

-300 -240 -180 -120 -60 0

Median

Mean

-80 -70 -60 -50 -40

1st Q uartile -78.249

Median -60.686

3rd Q uartile -32.043

Maximum 3.239

-75.728 -48.669

-70.480 -40.262

37.788 57.383

A -Squared 1.40

P-V alue < 0.005

Mean -62.198

StDev 45.559

V ariance 2075.636

Skewness -1.40078

Kurtosis 2.62145

N 46

Minimum -209.804

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE NOx (ppm dry)

Sample Label = Post Cat

Figure 10 - WED-CAE Post-Cat NOx Summary 

1.1 1.2 1.3 1.4 1.5

Median

Mean

1.09 1.10 1.11 1.12 1.13 1.14 1.15

1st Q uartile 1.0805

Median 1.1217

3rd Q uartile 1.1710

Maximum 1.3027

1.1104 1.1511

1.0972 1.1436

0.0568 0.0862

A -Squared 0.72

P-V alue 0.056

Mean 1.1308

StDev 0.0685

V ariance 0.0047

Skewness 0.721362

Kurtosis -0.063509

N 46

Minimum 1.0256

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE CO2 (% dry)

Sample Label = Post Cat

Figure 11 - WED-CAE Post-Cat CO2 Summary 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 12 of 17 

-30 0 30 60 90

Median

Mean

0 2 4 6 8 10 12

1st Q uartile -4.4963

Median 6.8673

3rd Q uartile 15.4516

Maximum 29.0124

2.6066 9.8286

1.1817 12.0171

10.0857 15.3154

A -Squared 0.22

P-V alue 0.811

Mean 6.2176

StDev 12.1597

V ariance 147.8582

Skewness -0.296224

Kurtosis 0.025357

N 46

Minimum -28.0177

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% Confidence Intervals 95% C onfidence Interv al for StDev

Summary for WED-CAE THC (ppm wet)

Sample Label = Post Cat

Figure 12 - WED-CAE Post-Cat CO Summary 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 13 of 17 

Brake Specific Fuel Consumption (BSFC) was also monitored relative to previous 

development data with the summary shown in Figure 13. The expectation was that the 

measured BSFC value should be within ±3% of the expected value from previous 

development data. There were a few points that exceeded that, but those were typically 

at lower loads. Algorithms based on previous data historically have not predicted 

performance values at lower loads as well as at higher loads so no corrective action 

was taken. This review provides evidence that the engine was in generally good 

“health” as most engine irregularities have a fuel consumption impact. 

-0.01 0.00 0.01 0.02 0.03 0.04

Median

Mean

0.006 0.008 0.010 0.012 0.014

1st Q uartile -0.001605

Median 0.009819

3rd Q uartile 0.021971

Maximum 0.039645

0.008219 0.013782

0.006708 0.014625

0.011730 0.015710

A -Squared 0.80

P-V alue 0.037

Mean 0.011001

StDev 0.013430

V ariance 0.000180

Skewness 0.097719

Kurtosis -0.928529

N 92

Minimum -0.015398

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% C onfidence Interv al for StDev

95% Confidence Intervals

Summary for BSFC Error (% / 100)

Figure 13 – Test BSFC Error Relative to Previous Development Data 

What can be concluded from this analysis is that the WED emissions bench and CAE 

FTIR were in good agreement and that the engine was running properly throughout the 

test. 

Pre-Catalyst Formaldehyde Correlation Development

As stated before, the test was run in 2 blocks. The first block mimicking a test that the 

EPA contracted with CSU for a lean burn engine during HAP testing at CSU in 2000. 

The second block providing higher statistical power for identifying factors that may affect 

this correlation. 

Using only the data from the first block the simple correlation shown in Figure 14 was 

developed. There are two correlations; one using the WED measured THC and the 

other using the CAE measured THC. Both are very similar in slope and fit indicating 

that either could be used with equal effectiveness. Also, at this stage, both are a better 

R2

 fit than was observed in X-3281 for the lean burn CO-CH2O fit from either the WEDCAE data (R2

=0.6047) or the CSU-EPA data (R2=0.633). 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 14 of 17 

Based on this, it can be concluded that the simple correlation developed here between 

pre-cat THC and pre-cat CH2O for rich burn engines is better, in an “apples to apples” 

data set comparison, than what is believed to have been used by the EPA to determine 

a correlation between CO and CH2O for lean burn engines. 

EPA (Block 1) Pre-Cat Data

y = 0.016280x + 1.334714

R2 = 0.715848

y = 0.02081x + 1.43140

R2 = 0.68342

0

1

2

3

4

5

6

7

8

9

0 50 100 150 200 250 300 350 400 450

PreCat THC (ppmvw)

PreCat CH2O (ppmvw)

CAE THC WED THC Linear (WED THC) Linear (CAE THC)

Figure 14 - Simple Pre-Cat Correlation (Block 1 only) 

When both blocks are included in the analysis, see Figure 15, the simple correlation fit 

(R2

) is not as good as the block 1 only fit and slightly worse than the fit believed to have 

been used for the lean burn CO correlation. However, the slopes are still about the 

same as shown in Figure 14, indicating that, while adding more data makes the 

correlation more “noisy”, the “strength” of the correlation remains. The lower R2

 implies 

more scatter in the data which is not entirely unexpected as the complete test (both 

blocks) was designed to maximize the ability to identify significant effects. While, as 

discussed above, block 1 only data still have these effects but do not provide enough 

statistical power to likely be able to identify and quantify these effects. 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 15 of 17 

All (Block 1 & 2) Pre-Cat Data

y = 0.013025x + 2.063414

R2 = 0.516614

y = 0.01545x + 2.38918

R2 = 0.47788

0

1

2

3

4

5

6

7

8

9

0 50 100 150 200 250 300 350 400 450

PreCat THC (ppmvw)

Pre Cat CH2O (ppmvw)

CAE THC WED THC Linear (WED THC) Linear (CAE THC)

Figure 15 - Simple Pre-Cat Correlation (Both Blocks) 

To make use of the additional statistical power provided by both data blocks to identify 

the cause of this scatter, the residuals (i.e. measured - predicted) of each point for both 

WED and CAE THC were calculated. Two models were then fit to these residuals with 

the potential terms being the factors that made up the test matrix (i.e. speed, torque, a/f 

ratio, ign. timing, intercooler and jacket water temps.) and their interactions. 

Both the WED and CAE THC models agreed on the terms to include and both fits were 

approximately the same as shown in Table 3 and Table 4. The only issue with both 

models is that they fail a “lack of fit” test. This is not fatal to a model since all that 

means is that error in the model is more than the replicated design points. A test that 

has very reproducible responses, as the sample time determination procedure at the 

beginning of this test was intended to produce, could easily encounter this. The R2

s 

shown in Table 5 indicate that both models account for about 90% of the variation seen 

in Figure 15. 

Table 3 - Models in Terms of Coded Factors 

CAE resid = WED resid =

0.075292603 0.065746552

0.097424296 * A 0.059891564 * A

-0.18219422 * B -0.118481554 * B

0.656414148 * C 0.652349586 * C

0.177116838 * D 0.166338081 * D

-0.098851252 * F -0.10540293 * F

-0.242956505 * A * B -0.228602795 * A * B
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 16 of 17 

Table 4 - Models in Terms of Actual Factors 

CAE resid = WED resid =

-132.3207951 -130.5387507

0.014741778 * Speed 0.013553074 * Speed

0.166021822 * Torque 0.159743279 * Torque

119.348027 * A/F 118.6090157 * A/F

0.070846735 * Timing 0.066535232 * Timing

-0.009885125 * JWT -0.010540293 * JWT

-0.000161971 * Speed * Torque -0.000152402 * Speed * Torque

Table 5 - Residual Model R2s 

CAE THC WED THC

R-Squared 0.910 0.915

Adj R-Squared 0.896 0.901

Pred R-Squared 0.865 0.872

The conclusion drawn from this analysis is that the initial simple correlation, when 

applied to a broad data set or application base, may be a slightly “noisier” correlation 

than is expected from Figure 14 alone. However, since Figure 14 was based on a test 

design that mimicked what is thought to have been used to develop the lean burn CO 

correlation, it will likely be no different than what is seen in practice with the lean burn 

CO correlation. Also, as demonstrated with the equation developed above, the 

correlation can be “cleaned up” considerably (to be superior to the accepted lean burn 

CO correlation), by using conventional engine parameter measurements that are readily 

available through Waukesha’s ESM control ESP interface. 

Post-Catalyst Formaldehyde Correlation Development

Attempting the same correlation techniques used for the pre-cat correlation was not 

possible for the post-cat samples. Block 1 of the test only had one data point where 

post cat CH2O was above the CAE formaldehyde detection limit. Adding block 2 to the 

data set included a few more points that were above the CAE formaldehyde detection 

limit, but the vast majority of the data were still below this limit making any attempted 

correlation bogus. This is caused by the virtually complete destruction of CH2O 

regardless of its initial level or the THC level. The CAE report (Appendix C) shows that 

the mean, observed, post-cat CH2O level is under the 0.23 ppmvw detection limit with 

the maximum measured value, under any operating condition, less than 0.8 ppmvw 

(800 ppbvw). This is particularly significant considering the wide range of conditions 

that this test covered, making a strong case that virtually complete CH2O reduction can 

be considered a given for most applications with a properly functioning NSCR catalyst. 

The term “most applications” is used because there is a potentially significant variable 

that was missing from this study, which is fuel quality (i.e. WKI or LHV). It was not 

included in the study, because the factors were set to mimic the test done by the EPA at 

CSU which did not include fuel quality as a variable. In addition, Waukesha’s 

Engineering Laboratory has only limited capability to vary fuel gas composition in a 

realistic manner. 

The conclusion drawn from this analysis is that, while a correlation between post-cat 

CH2O and either pre-cat CH2O or post-cat THC can not be made, the correlation does 
TR-4854 Analysis of THC as a Rich Burn Formaldehyde Surrogate Page 17 of 17 

not appear to be necessary as virtually complete CH2O reduction occurs regardless of 

the fairly broad conditions evaluated in this test. 

WED versus CAE THC Measurement

Throughout this test all of the analyses were essentially doubled by using both the WED 

measured THC and CAE measured THC. While there were slight value differences 

between these two data sets, there was at no time a substantive difference in the 

conclusions that would be drawn from either method. So either could have been used 

and the same conclusions reached, lending further credibility to the broad applicability 

of the conclusions drawn here. 

Summary

• In process checks were made to ensure data integrity. These validated engine 

performance and criteria emissions agreement between the two measurement 

methods. 

• The simple pre-catalyst correlation CH2O(ppmvw) = 0.013025 * THC(ppmvw) + 

2.063414, using the Waukesha measured THC is better, in an “apples to apples” 

data set comparison, than what is believed to have been used by the EPA to 

determine a correlation between CO and CH2O for lean burn engines. 

• The simple pre-catalyst correlation can be enhanced, for broader application by 

adding: 

-130.53875 + 0.013553 * Speed + 0.15974 * Torque + 118.60902 * A/F + 

0.066535 * Timing - 0.010540 * JWT - 1.52402E-004 * Speed * Torque 

to reduce about 90% of the noise. 

• No post catalyst CH2O correlation appears to be required, as virtually complete 

reduction occurs regardless of the fairly broad conditions evaluated in this test. 

INDEX OF ATTACHMENTS 

Attachment A - ORIGINAL BASE TEST EVALUATION 

Attachment B - AUGMENTED TEST EVALUATION 

Attachment C – FORMAL REPORT OF HAP TESTING AT WAUKESHA BY CAE (See 

Matrix for copy of Attachment C) 
Attachment A - ORIGINAL BASE TEST EVALUATION 

 

 6 Factors: A, B, C, D, E, F

 Design Matrix Evaluation for Response Surface Linear Model

 No aliases found for Linear Model

 Degrees of Freedom for Evaluation

 Model 6 

 Residuals 9 

 Lack 0f Fit 7

 Pure Error 2

 Corr Total 15 

 Power at 5 % alpha level to detect 

signal/noise ratios of

Term StdErr** VIF Ri-Squared 1 Std. Dev. 1.5 Std. Dev. 2 Std. Dev.

 A 0.36 1.26 0.2054 23.8 % 46.2 % 69.8 % 

 B 0.36 1.26 0.2054 23.8 % 46.2 % 69.8 % 

 C 0.58 1.33 0.2500 12.1 % 21.4 % 34.1 % 

 D 0.49 1.05 0.0496 15.1 % 28.1 % 45.0 % 

 E 0.71 1.00 0.0000 9.7 % 15.8 % 24.5 % 

 F 0.71 1.00 0.0000 9.7 % 15.8 % 24.5 % 

**Basis Std. Dev. = 1.0

 Measures Derived From the (X'X)-1 Matrix

Std Leverage Point Type

 1 0.1031 ?? 

 2 0.4648 ?? 

 3 0.5258 ?? 

 4 0.4648 ?? 

 5 0.4364 ?? 

 6 0.4364 ?? 

 7 0.4648 ?? 

 8 0.4648 ?? 

 9 0.6031 ?? 

 10 0.6031 ?? 

 11 0.6031 ?? 

 12 0.6031 ?? 

 13 0.8041 ?? 

 14 0.2165 ?? 
 15 0.1031 ?? 

 16 0.1031 ?? 

Average = 0.4375

 Maximum Prediction Variance (at a design point) = 0.804

 Average Prediction Variance = 0.438

 Condition Number of Coefficient Matrix = 3.059

 Scaled D-optimality Criterion = 3.222

 Determinant of (X'X)-1 = 1.342E-5

 Trace of (X'X)-1 = 2.166
Attachment B - AUGMENTED TEST EVALUATION 

 6 Factors: A, B, C, D, E, F

 Design Matrix Evaluation for Response Surface Quadratic Model

 No aliases found for Quadratic Model

 Degrees of Freedom for Evaluation

 Blocks 1 

 Model 27 

 Residuals 17 

 Lack 0f Fit 15

 Pure Error 2

 Corr Total 45 

 Power at 5 % alpha level to detect 

signal/noise ratios of

Term StdErr** VIF Ri-Squared 1 Std. Dev. 1.5 Std. Dev. 2 Std. Dev.

 Block 1 0.49 

 Block 2 

 A 0.19 1.51 0.3376 68.8 % 95.6 % 99.8 % 

 B 0.19 1.42 0.2952 69.8 % 96.0 % 99.9 % 

 C 0.20 1.31 0.2352 64.5 % 93.7 % 99.6 % 

 D 0.21 1.79 0.4426 61.1 % 91.9 % 99.4 % 

 E 0.22 1.55 0.3559 55.8 % 88.4 % 98.8 % 

 F 0.20 1.20 0.1694 65.3 % 94.1 % 99.7 % 

 AB 0.19 1.19 0.1567 70.4 % 96.2 % 99.9 % 

 AC 0.22 1.31 0.2351 57.2 % 89.4 % 99.0 % 

 AD 0.19 1.29 0.2260 70.7 % 96.3 % 99.9 % 

 AE 0.22 1.28 0.2175 56.5 % 88.9 % 98.9 % 

 AF 0.22 1.20 0.1661 57.6 % 89.7 % 99.0 % 

 BC 0.22 1.36 0.2664 55.5 % 88.2 % 98.7 % 

 BD 0.19 1.27 0.2150 71.3 % 96.5 % 99.9 % 

 BE 0.21 1.11 0.1019 62.3 % 92.6 % 99.5 % 

 BF 0.21 1.14 0.1215 59.5 % 90.9 % 99.2 % 

 CD 0.21 1.28 0.2157 62.7 % 92.8 % 99.5 % 

 CE 0.21 1.18 0.1543 63.0 % 92.9 % 99.5 % 

 CF 0.22 1.27 0.2110 58.3 % 90.1 % 99.1 % 

 DE 0.20 1.20 0.1693 63.8 % 93.4 % 99.6 % 

 DF 0.21 1.18 0.1522 63.2 % 93.1 % 99.6 % 

 EF 0.20 1.15 0.1289 63.8 % 93.4 % 99.6 % 

 A2 0.66 1.96 0.4888 29.7 % 57.0 % 81.2 % 

 B2 0.54 1.50 0.3336 42.1 % 75.1 % 94.0 % 
 C2

 0.51 2.51 0.6012 46.0 % 79.6 % 96.0 % 

 D2 0.68 1.67 0.4002 28.7 % 55.3 % 79.7 % 

 E2 0.70 4.92 0.7968 27.2 % 52.7 % 77.1 % 

 F2 0.60 3.76 0.7337 35.0 % 65.4 % 88.1 % 

**Basis Std. Dev. = 1.0

 Measures Derived From the (X'X)-1 Matrix

Std Leverage Point Type

 1 0.1302 ?? 

 2 0.4130 ?? 

 3 0.3706 ?? 

 4 0.3264 ?? 

 5 0.4064 ?? 

 6 0.5284 ?? 

 7 0.5130 ?? 

 8 0.6201 ?? 

 9 0.6944 ?? 

 10 0.6075 ?? 

 11 0.6234 ?? 

 12 0.6527 ?? 

 13 0.4282 ?? 

 14 0.4331 ?? 

 15 0.1302 ?? 

 16 0.1302 ?? 

 17 0.7545 PlaneCent 

 18 0.9093 Vertex 

 19 0.7681 Vertex 

 20 0.6503 CentEdge 

 21 0.7185 CentEdge 

 22 0.8775 Vertex 

 23 0.9256 Vertex 

 24 0.8040 Vertex 

 25 0.8210 Vertex 

 26 0.8110 Vertex 

 27 0.7154 CentEdge 

 28 0.6683 Vertex 

 29 0.7630 Vertex 

 30 0.7846 Vertex 

 31 0.6905 Vertex 

 32 0.7903 Vertex 

 33 0.8063 CentEdge 

 34 0.7000 CentEdge 

 35 0.7060 Vertex 

 36 0.6547 CentEdge 

 37 0.7760 CentEdge 

 38 0.4769 CentEdge 

 39 0.6743 CentEdge 
 40 0.6812 Vertex 

 41 0.6603 CentEdge 

 42 0.6388 CentEdge 

 43 0.7041 CentEdge 

 44 0.5691 Vertex 

 45 0.7987 CentEdge 

 46 0.6943 CentEdge 

Average = 0.6304

 Maximum Prediction Variance (at a design point) = 0.926

 Average Prediction Variance = 0.630

 Condition Number of Coefficient Matrix = 60.060

 Scaled D-optimality Criterion = 2.624

 Determinant of (X'X)-1 = 2.747E-35

 Trace of (X'X)-1 = 4.339