1

MEMORANDUM

Date: November 2011

To: Brian Shrager, US EPA

From: Eastern Research Group, Inc.

Subject: CO CEMS MACT Floor Analysis (November 2011) for the Industrial, Commercial, 

and Institutional Boilers and Process Heaters National Emission Standards for Hazardous Air 

Pollutants – Major Source

This memorandum describes the rationale, available data, and methodology for the 

proposed alternative compliance option of a CO continuous emissions monitor (CEMS) MACT 

floor emission limit. This alternative is provided to increase compliance flexibility for boilers 

which already employ CEMS or may need to install CEMS for other regulations and it also 

provides flexibility for load-swinging units.

The memorandum is organized as follows:

1.0 Background

2.0 CEMS MACT Floor Calculation Methodology – Existing Source

2.1 Determining Best Performers

2.2 Upper Prediction Limit Calculation

3.0 CEMS MACT Floor Calculation Methodology - New Source

4.0 Available CEMS Data

5.0 CO CEMS MACT Floor Results

5.1 Existing Source MACT Floors

5.2 New Source MACT Floors

6.0 Comparison of CEMS Data to Stack Test Data

7.0 Alternative MACT Floor Calculation Methodology

8.0 References

Appendix A: CO CEMS Subcategory Rankings and Raw Data
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Appendix B: CO CEMS Existing Source UPL Calculations

Appendix C: CO CEMS New Source UPL Calculations

1.0 BACKGROUND

For the Boiler MACT rule reconsideration proposal, a MACT floor analysis using the 

available CO CEMS data was performed in response to requests from petitioners. While an 

inordinate amount of data is not available, there is enough data available to consider and analyze 

the options for most of the subcategories outlined in the proposal. It is noted, however, that 

additional data would provide a more reliable and accurate picture of long-term CO emissions 

from best performing units. Given the limited dataset available in this proposal, the MACT floor 

was computed using two methods, as discussed in Sections 2 and 7 of this memorandum.

2.0 CEMS MACT FLOOR CALCULATION METHODOLOGY – EXISTING SOURCE

2.1 DETERMINING BEST PERFORMERS

For existing sources, MACT cannot be less stringent than the average emission limitation 

achieved by the best performing 12 percent of existing sources (for which emission information 

is available) for categories and subcategories with 30 or more sources or the best performing five 

sources for subcategories with less than 30 sources. The size of the subcategory was determined 

according to the number of units in the boiler and process heater inventory, not the number of 

units within each subcategory that had emission data available.

To identify the universe of best performing units in each subcategory, we first looked at 

all boilers which were best performers based on their CO stack test results. These were 

compared to the available units which had corresponding CO CEMS data; however, there was 

very little overlap in the number of best performing units that had both CO stack test and CO 

CEMS data available. After comparing the data, only five subcategories had units with both 

types of data. Given such limited overlap, we opted to select CO CEMS best performers by 

ranking each unit according to its minimum 10-day rolling average CO CEMS value. For the 

five subcategories where we have CEMS data for units that are part of the stack test-based 
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MACT floors, we also included the CEMS data from those units in the CEMS-based floors 

because those units are demonstrated best performers for CO. There are two exceptions to 

ranking by the 10-day minimum rolling average, which are discussed below. Within each 

subcategory, the minimum 10-day rolling averages were ranked from lowest to highest to 

determine the best performing 12 percent. If the number of units in the subcategory was greater 

than 30, the best performing 12 percent was determined by multiplying the number of units in 

each subcategory with CEMS data by 12 percent and rounding up to the nearest whole integer. 

Given the limited dataset, the top 12 percent represented a single combustion unit for all of the 

subcategories with greater than 30 units, except for wet biomass stoker, where the top 12 percent 

represented two units. If the number of units in the subcategory was less than 30, the units with 

the five lowest minimum 10-day rolling averages were identified as best performers; however, in 

these instances most subcategories only had a single unit with CO CEMS data, with the 

exception of the biomass fluidized bed subcategory which had two units with CO CEMS data. 

For the non-continental liquid and light liquid subcategories there was insufficient data to 

calculate 10-day rolling averages. Based on the available non-continental liquid data the 

averaging basis selected was 3-hours; only one non-continental liquid boiler submitted CO 

CEMS data, with a total of 24 hourly averages. For light liquid boilers, a one-day average was 

selected based on the available data. Six light liquid boilers had CEMS data but they each have 

only four or eight daily average values. Further, two of these units had CEMS data based on cofiring natural gas and liquid fuel, and those data were not used in the analysis since the 

contribution of the gaseous fuel is unknown and the MACT floor data eligibility criteria for cases 

where a single unit serves as the basis of the floor calculation require that the data must be based 

on firing 100 percent of a given fuel category. The ranking of the dataset can be seen in 

Appendix A.

2.2 UPL CALCULATION

With the best performing 12 percent for each subcategory determined, a 99 percent upper 

predictive limit (UPL) was calculated for each subcategory. This is the same level of confidence 

selected for the stack test-based emission limits. First, it was determined if each CO CEMS 

dataset was best characterized by a normal or lognormal distribution. To evaluate the distribution 
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of the best performing dataset, we computed the skewness and kurtosis statistics and then 

conducted the appropriate small-sample hypothesis tests. 

The skewness statistic (S) characterizes the degree of asymmetry of a given data 

distribution. Normally distributed data have a skewness of 0. A skewness statistic that is greater 

(less) than 0 indicates that the data are asymmetrically distributed with a right (left) tail 

extending toward positive (negative) values. Further, the standard error of the skewness statistic 

(SES) is given by SES = SQRT(6/N) where N is the sample size. According to the small sample 

skewness hypothesis test, if the skewness statistic (S) is greater than two times the SES, the data 

distribution can be considered non-normal. 

The kurtosis statistic (K) characterizes the degree of peakedness or flatness of a given 

data distribution in comparison to a normal distribution. Normally distributed data have a 

kurtosis of 0. A kurtosis statistic that is greater (less) than 0 indicates a relatively peaked (flat) 

distribution. Further, the standard error of the kurtosis statistic (SEK) is given by SEK = 

SQRT(24/N) where N is the sample size. According to the small sample kurtosis hypothesis test, 

if K is greater than two times the SEK, the data distribution is typically considered to be nonnormal.

We applied the skewness and kurtosis hypothesis tests to both the reported daily average 

CO CEMS values and the natural log of the reported daily average CO CEMS values. If the S 

and K statistics of the reported dataset were both less than twice the SES and SEK, respectively, 

the dataset was classified as normally distributed. If neither of the S and K statistics or only one 

of these statistics was less than twice the SES or SEK, respectively, then the skewness and 

kurtosis hypothesis tests were conducted for the natural log-transformed data. Then the 

distribution most similar to a normal distribution was selected as the basis for calculating the 

UPL. If both the reported values and the natural log-transformed reported values had S and K 

statistics that were greater than twice the SES or SEK, respectively, the lognormally distributed 

dataset was selected as the basis of the floor, consistent with guidelines from EPA Guidance 

document, Data Quality Assessment: Statistical Methods for Practitioners EPA QA/G-9S which 

notes that a lognormal distribution is a commonly used distribution for most environmental 

contaminant data.1

 This guidance document also notes that the lognormal is an important 

probability distribution when analyzing environmental data where normality cannot be assumed. 
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If the results of the skewness and kurtosis hypothesis tests were mixed for the reported values 

and the natural log-transformed reported values, or if the dataset was too small to apply skewness 

or kurtosis tests, we also chose the lognormal distribution, consistent with the guidance noted 

above. We believe this approach is more accurate and obtained more representative results than a 

more simplistic normal distribution assumption. 

For datasets that were determined to be normally distributed, the UPL is computed using 

a student’s t-test statistic. The t-statistic is calculated using the following Excel equation:

t-statistic = TINV(2*(1-0.99),n-1)

Where:

n = the number of daily averages in the best performing 12 percent (or hourly averages 

for non-continental liquid units)

Next, the mean and standard deviation of the CO CEMS data were calculated and the 

UPL calculated via the following equation:

Where:

the mean of the daily averages for the best performing 12 percent (or hourly 

averages for non-continental liquid units)

s

2

= the standard deviation of the daily averages in the best performing 12 percent (or 

hourly averages for non-continental liquid units)

n = the number of daily averages in the best performing 12 percent (or hourly averages 

for non-continental liquid units)

m = the number of daily averages (or hourly averages for non-continental units) in the 

compliance average; m = 10 for all subcategories based on 10-day rolling averages; 

m = 3 for non-continental units which are based on a 3-hour rolling average; and m 

= 1 for light liquid units which are based on a one-day block average.

For datasets that were determined to be lognormally distributed, the same t-statistic was 

applied, but a slightly different UPL equation was used.
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Where:

n = the number of daily averages in the best performing 12 percent (or hourly averages 

for non-continental liquid units)

m = the number of daily averages (or hourly averages for non-continental units) in the 

compliance average; m = 10 for all subcategories based on 10-day rolling averages; 

m = 3 for non-continental units which are based on a 3-hour rolling average; and m 

= 1 for light liquid units which are based on a one-day average..

For each subcategory the analysis showed that the datasets were lognormally distributed. 

Given the rolling-average compliance metric, many of the datasets also exhibit varying degrees 

of autocorrelation. Autocorrelation describes the correlation between values of the process at 

different points in time.7,8,9 Although the UPL calculation is affected by autocorrelation, no 

adjustments were made to incorporate autocorrelation in this dataset since EPA is aware of 

ongoing CEMS testing for many of the affected boilers and the dataset at this time is 

preliminary. Depending on the final compliance metric selected, EPA may adjust the dataset for 

the promulgated rule to better address autocorrelation.

3.0 CEMS MACT FLOOR CALCULATION METHODOLOGY - NEW SOURCE

A similar methodology used to calculate the existing source UPL was used to calculate 

the new source UPL. For the new source calculations, however, only data from the top 

performing unit in each subcategory were used in the analyses. Since most of the subcategories 

only have one unit in the top 12 percent this makes little difference in the computed MACT 

floors. However, the top performing unit must be firing a fuel which is representative of and 

reasonable to obtain for the entire subcategory and not process specific nor based on co-fired 

configurations. If a boiler were not firing a similar fuel available to others in the same 

subcategory, then the new source floor could be biased. This same exception is also used in the 

new source floors for the CO stack test MACT floors. In the case of fluidized bed units firing 

biomass, the third ranked unit, GATempleInlandRome (WF), is the unit with the lowest rolling 

average that is not firing process-specific fuels. For the light liquid subcategory, the top two 
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ranked facilities are co-firing natural gas and are thus not representative of light liquid fuel 

boilers; the third ranked facility is used for the UPL.

There was also one additional step for new sources to ensure that the emission limit for 

new sources is not less stringent than the emission limit for existing sources in the same 

subcategory. If the UPL selected to represent the MACT floor value for new sources is less 

stringent than the emission limit selected to represent the MACT floor for existing sources, then 

the floor corresponding to the same subcategory for existing sources was used as the basis for the 

floor for new sources. Although the minimum average test run for the best performing source 

resulted in the lowest 10-day CEMS average, the 99 percent UPL limit incorporates variability. 

As the sample size - in this case the number of hourly CEMS values - gets smaller, the t-statistic 

increases. When the sample size is small, and there is large variability in the CEMS values, the 

calculated limit using the UPL approach can be larger than the variability among a larger set of 

data in the best performing 12 percent. 

4.0 AVAILABLE CEMS DATA

The CEMS data was obtained from two Information Collection Requests (ICRs) 

approved under OMB Control No. 2060-0616: ICR numbers 2286.01 and 2286.03, as well as 

additional voluntary data submittals.2,3,4,5 

The ICR Phase I survey requested that owners submit CO CEMS data for the most recent 

30 days of operation (i.e., thirty 24-hour averages). Owners were asked to exclude data if they 

were from periods of start-up, shutdown, or malfunctions (SSM) and submittal was not required 

if the CEMs monitor was not installed for regulatory purposes. Owners were also requested to 

submit a “typical” operating rate, which often represented the average rate for the 30-day period, 

but it did not request daily load averages to correspond to the daily average CO CEMS emission 

concentrations. Phase II of the ICR requested 30 days of CEMS data, including hourly data and 

the corresponding hourly heat input and steam output of the boiler. The additional voluntary 

data submittals were provided as minute, hourly or daily averages.

Consistent with the data eligibility criteria in the stack-test MACT floor analysis, when 

determining the applicable data for the CEMS analysis, the fuel fired during the CEMS analysis 
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must meet a 90% heat input threshold to be considered for a subcategory.6 While the fuel was 

indicated for the majority of the data, assumptions for three boilers were necessary as described 

here:

1. GATempleInlandRome, WF: Used oil along with wood bark are listed for certain 

data, but the percentage of used oil contributing to the heat input is not provided 

in all instances. For those instances when the percentage of used oil was provided 

it was always substantially less than 10 percent of total heat input, which would 

still allow the data to be considered in the biomass fluidized bed CEMS analysis. 

It is assumed all CEMS data points for this unit meet the 90% threshold for 

biomass since used oil is typically burned in such small quantities.

2. USVIHovensa, H-4101A: #6 oil and refinery gas are listed as the fuels burned in 

the unit. However, there is no fuel data associated with the dates corresponding to

the CO CEMS data. As this unit has a limited amount of data and is the only noncontinental unit with data, it was assumed the boiler met the 90% fuel input 

threshold criteria for #6 oil.

3. MITBSimonPowerPlant, Unit 4: Bituminous coal and natural gas are fired and the 

percentage each contributed to the heat input are not provided for the dates 

associated with the CO CEMS monitoring data. However, other fuel data for this 

boiler in other portions of the Phase I ICR survey shows that natural gas is burned 

in miniscule amounts. Therefore, it is assumed all CEMS data meets the 90% 

threshold for bituminous coal.

Generally most sources that reported CEMS data had 30 days of data either reported as 

hourly or daily averages. Given this limited length of time, we selected a 10-day rolling 

averaging period in order to allow us to compute multiple rolling averages from each source’s 

dataset. Although a longer averaging time would have been preferable in order to account for 

dramatic load swings, there was simply not enough data available to analyze a longer averaging 

period. Where sources reported CEMS data on both an hourly and daily average basis we first 

reduced the hourly data into daily averages. The hourly data points for each boiler were sorted 

sequentially, grouped together by day, and then averaged to compute daily averages. Only the 

hours meeting the 90 percent fuel criteria were included in the daily averages. Next, we 

combined the two datasets, sorted the data in sequential calendar date order and computed a 
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series of 10-day rolling averages from each unit. The 10-day rolling averages represent 

sequential, but not necessarily continuous, calendar dates. In some cases the data reported by the 

facility skipped certain days due to unit downtime or data associated with SSM conditions. Table 

1 shows the subcategories which have daily CO CEMS data available to calculate 10-day rolling 

averages. 

A very limited amount of CEMS data was available from non-continental liquid units, see 

Table 2, and a 10-day rolling average could not be computed. This data was provided at minute 

intervals and was converted to hourly averages. The minute average data points for each boiler 

were sorted sequentially, grouped together by hour, and then averaged to compute hourly 

averages. Next, the data was sorted in sequential calendar date order and a series of 3-hour 

rolling averages from each unit were calculated. The data reported to EPA was not provided in 

continuous hours so the 3-hour rolling averages represent consecutive, but not continuous, 

rolling averages. Based on the data available it was determined that 3-hour averages were an 

appropriate option for this subcategory. As mentioned above, all data from this unit were used, 

since the exact fuel percentages were unknown. 

The data available for the light liquid subcategory is presented in Table 3. All data was 

provided as daily averages. Based on the limited data a daily average was selected as the 

compliance metric and used to calculate a UPL and identify the maximum average; a multiple 

day rolling average would have too few data points to evaluate variability in the performance of 

the unit. In all instances, the averaging times were selected as the best alternatives in light of the 

available dataset; longer averaging times would not be practical to calculate an appropriate 

MACT floor unless additional data is provided. 

Table 1. Available daily average CO CEMS data for each subcategory, to determine a 10-day rolling 

average.

Fuel Category Combustor Design

Number of 

Units in 

Subcategory

Number of 

Units with Daily 

Avg CO CEMS

Data

Number of 

Units In 

Top 12%

Coal

FB 35 6 1

PC 190 3 1

Stoker/SlopedGrate/Other 391 6 1

Biomass

Dutch Oven/Pile Burner 24 1 1

FB 24 3 3

Fuel Cell 14 a a
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Fuel Category Combustor Design

Number of 

Units in 

Subcategory

Number of 

Units with Daily 

Avg CO CEMS

Data

Number of 

Units In 

Top 12%

Suspension Burner 47 1 1

Suspension/Grate 18 1 1

Wet Biomass Stoker/SlopedGrate/Other 305 14 4 (b)

Dry Biomass Stoker/SlopedGrate/Other 74 a a

Heavy Liquid N/A 320 2 1

Light Liquid N/A 581 a a

Non-Continental Liquid N/A 44 a a

Process Gas N/A 129 a a

Note:

a. Data was not available to calculate a rolling average either on a daily or hourly basis.

b. Includes 2 units which were stack test best performers.

Table 2. Available hourly average CO CEMS data, to determine a 3-hr rolling average.

Fuel Category Combustor Design

Number of 

Units in 

Subcategory

Number of Units 

with Hourly Avg 

CO CEMS Data

Number of 

Units In 

Top 12%

Non-Continental Liquid N/A 44 1 1

Table 3. Available hourly average CO CEMS data, to determine UPL on a one-hour average basis.

Fuel Category Combustor Design

Number of 

Units in 

Subcategory

Number of Units 

with Hourly Avg 

CO CEMS Data

Number of 

Units In 

Top 12%

Light Liquid N/A 581 6 1

5.0 CO CEMS MACT FLOOR RESULTS

5.1 EXISTING SOURCE MACT FLOORS

After the CO CEMS MACT floor calculations were performed for each subcategory the 

same rounding technique used in the stack-test based MACT floors emission limits was applied. 

Each final MACT floor was determined by rounding the limit up to two significant figures. 

Rounding up is appropriate for establishing emission standards that must be complied with at all 
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times. The CO CEMS MACT floors for existing sources are summarized in Tables 4 through 6. 

The rankings for each subcategory are shown in Appendix A and the UPL floor calculations for 

each subcategory are shown in Appendix B.

In reviewing Tables 1 through 3 above, note there are three subcategories which do not 

have CO CEMS data available. While substituting a MACT floor from a different subcategory 

for the subcategories with no data was considered, ultimately it was determined that an 

alternative CO CEMS floor would not be provided for subcategories with no data. If other 

subcategories’ data were used to fill in incomplete subcategories, this data would not be 

representative of the applicable boilers operations and it would not be appropriate to subject 

boilers to a limit which is not based off representative data. 

Table 4. Summary of CO CEMS MACT floor limits for existing boilers and process heaters, 10-day 

rolling average.

Fuel Category Combustor Design 

Category

99% UPL for 

10-Day 

Rolling Avg

Rounded CO CEMS 

MACT Floor, 10-Day 

Rolling Avg (ppm @ 

3% O2)

Coal FB 58.2 59

PC 27.6 28

Stoker/SlopedGrate/Other 33.2 34

Biomass Dutch Oven/Pile Burner 434 440

FB 176 180

Fuel Cell a a

Suspension Burner 1333 1400

Suspension/Grate 723 730

Wet Biomass Stoker/SlopedGrate/Other 405 410

Dry Biomass Stoker/SlopedGrate/Other a a

Heavy Liquid N/A 18.0 18

Light Liquid N/A a a

Non-Continental Liquid N/A a a

Process Gas N/A a a

Note:

a. No applicable CO CEMS data available for this subcategory
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Table 5. Summary of CO CEMS MACT floor limits for non-continental existing boilers and process 

heaters, 3-hr rolling average.

Fuel Category

Combustor 

Design 

Category

99% UPL for 

3-Hour 

Rolling Avg

Rounded CO CEMS 

MACT Floor, 3-Hour 

Rolling Avg (ppm @ 

3% O2)

Non-Continental Liquid N/A 90.5 91

Table 6. Summary of CO CEMS MACT floor limits for light liquid existing boilers and process heater, 1-

hr average.

Fuel Category

Combustor 

Design 

Category

99% UPL 

for 1-Day

Avg

Rounded CO 

CEMS MACT Floor, 

1-Hour Avg (ppm 

@ 3% O2)

Light Liquid N/A 59.9 60

5.2 NEW SOURCE MACT FLOORS

The new source CO CEMS MACT floors are summarized in Tables 7 through 9 and the 

UPL calculations are provided in Appendix C. 

Table 7. Summary of CO CEMS MACT floor limits for new boilers and process heaters, 10-day rolling 

average.

Fuel Category

Combustor Design 

Category

99% UPL for 

10-day 

Rolling Avg

Rounded CO CEMS 

MACT Floor, 10-

Day Rolling Avg 

(ppm @ 3% O2)

Coal

FB 58.2 59

PC 27.6 28

Stoker/SlopedGrate/Other 33.2 34

Biomass

Dutch Oven/Pile Burner 434 440

FB 174 180

Fuel Cell a a

Suspension Burner 1333 1400

Suspension/Grate 723 730

Wet Biomass Stoker/SlopedGrate/Other 451 410 (b)

Dry Biomass Stoker/SlopedGrate/Other a a

Heavy Liquid N/A 18.0 18

Light Liquid N/A a a
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Non-Continental 

Liquid N/A a a

Process Gas N/A a a

Notes:

a. No applicable CO CEMS data available for this subcategory

b New source UPL is less stringent than existing source UPL so this value has defaulted to the 

corresponding existing source value.

Table 8. Summary of CO CEMS MACT floor limits for new non-continental boilers and process heaters, 

3-hr rolling average.

Fuel Category Combustor 

Design Category

99% UPL for 

3-Hour 

Rolling Avg

Rounded CO 

CEMS MACT 

Floor, 3-Hour 

Rolling Avg (ppm 

@ 3% O2)

Non-Continental Liquid N/A 90.5 91

Table 9. Summary of CO CEMS MACT floor limits for new light liquid boilers and process heaters, 1-hr 

average.

Fuel Category Combustor 

Design Category

99% UPL for 

1-Day Avg

Rounded CO 

CEMS MACT 

Floor, 3-Hour 

Rolling Avg (ppm 

@ 3% O2)

Light Liquid N/A 59.9 60

6.0 COMPARISON OF CEMS DATA TO STACK TEST DATA

With separate sets of boilers in the CO stack test and CO CEMS datasets there is the 

chance of incongruent results between the two compliance options. This is due to the fact that 

ranking the CO CEMS dataset according to the minimum 10-day rolling average does not 

correlate, due to the limited data, with the rankings used to identify the best performers from 

stack test data. To evaluate whether the CO CEMS MACT floor could relate with the CO stack 

test MACT floor, a comparison was made between the CEMS data and the computed stack test 

CO MACT floor for each subcategory. For each best performing unit in the CEMS analysis, a 

minimum 3-hour rolling average was calculated from the hourly CEMS data. A 3-hour period 
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was selected because stack tests are based on three 1-hour averages. If hourly data were not 

available for a best performer, the minimum daily average was determined instead. See Table 10 

for the results of this analysis, along with both the CO CEMS and CO stack test new and existing 

source floors for comparison. Each unit identified as a best performing unit in the CO CEMS 

analysis had at least one 3-hour or daily CEMS average at or below the corresponding stack test 

CO MACT floor for the subcategory suggesting that the CEMS floors are reasonable. The fact 

that CO CEMS floors are lower or higher than stack test data shows the variability that does exist 

for CO over the range of a boiler’s operation. 
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Table 10. Comparison of CO CEMS floors versus CO stack test floors.

Fuel Category Combustor Design

Boiler 

Subcategory 

Rank

Minimum

CEMS

3-Hr Avg

Minimum

CEMS Daily 

Avg, If No 

Hourly Data 

is Available

CO CEMS 

Existing 

Source 

Floor

CO CEMS 

New 

Source 

Floor

CO Stack 

Test 

Existing 

Source 

Floor

CO Stack 

Test 

New 

Source 

Floor

Coal

FB 1 No Data 1.2 59 59 56 17

PC 1 No Data 15.4 28 28 41 9

Stoker/SlopedGrate/Other 1 12.0 - 34 34 220 19

Biomass

Dutch Oven/Pile Burner 1 No Data 112 440 440 810 810

FB 1 No Data 7.7 180 180 370 230

FB 2 0.02 - 180 180 370 230

FB 3 35.3 - 180 180 370 230

Fuel Cell N/A No Data No Data - - 1500 210

Suspension Burner 1 9.5 - 1400 1400 58 58

Suspension/Grate 1 4.3 - 730 730 3900 1500

Wet Biomass Stoker/SlopedGrate/Other 1 0.1 - 410 410 790 590

Stoker/SlopedGrate/Other 2 No Data 131.3 410 410 790 590

Dry Biomass Stoker/SlopedGrate/Other N/A No Data No Data - - 250 250

Heavy Liquid N/A 1 No Data 0.1 18 18 10 10

Light Liquid N/A N/A No Data No Data 60 60 7 3

Non-Continental Liquid N/A 1 0.2 - 91 91 18 18

Process Gas N/A N/A No Data No Data - - 4 4

Notes:

• Blue text indicates the CEMS data is lower than the corresponding CO stack test floor.

• Red text indicates the CEMS data is higher than the corresponding CO stack test floor.
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7.0 ALTERNATIVE MACT FLOOR CACLCULATION METHODOLOGY

Given the limited datasets, a second method of calculating a MACT floor value was 

evaluated. After the rankings were determined, the emissions of the top half (6%, or often the 

top single unit) of the best performing units was further analyzed. For each of these units, the 

rolling averages were calculated, as shown in section 2.1, and reviewed to identify the maximum 

rolling average. After the maximum rolling average was determined for each unit, the highest 

maximum rolling average from the top half of the best performers for each subcategory was 

selected as a MACT floor option. In the CEMS-based compliance alternative, it is necessary for 

MACT floors to be achieved by the best performers at all times, even during large CO swings; 

the maximum rolling average value from the top half of the best performers is chosen to 

represent the performance of the average emission limitation achieved by the best performing 12 

percent of existing sources (for which emission information is available). 

Also, since only one unit’s maximum rolling average is used for this option, the unit’s 

operation must be representative of the entire subcategory. Therefore, the unit selected must be 

firing a fuel which is reasonable to obtain for the entire subcategory and not process specific nor 

based on co-fired configurations; this exception is the same as for new sources. In the case of 

fluidized bed units firing biomass, the third ranked unit, GATempleInlandRome (WF), is the unit 

with the lowest rolling average that is not firing process-specific fuels. For the light liquid 

subcategory, the top two ranked facilities are co-firing natural gas and are thus not representative 

of light liquid fuel boilers; the third ranked facility is used for the maximum rolling average.

Appendix A-3 shows the maximum rolling average for the top 6 percent of units in each 

subcategory.

Tables 11 to 13 of this Section compare the highest rolling average from the top 6 percent 

of units with the calculated UPL. Tables 14 to 16 of this Section compare the highest rolling 

average from the top performing unit with the calculated UPL for new sources. Since the value 

must be achieved at all times, the calculated UPL emission limits were evaluated to determine 

whether or not the units in the top 6 percent of each subcategory were consistently meeting the 

limits. If not, the highest rolling average from the top 6 percent of units in each subcategory was 

selected as an alternative MACT floor. These tables also show how often the top 6 percent of 

each subcategory are meeting the calculated UPL.
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Table 11. Summary of Alternative CO CEMS MACT floor limits for existing boilers and process heaters, 

10-day rolling average.

Fuel Category Combustor Design 

Category

99% UPL 

for 10-

Day 

Rolling 

Avg

Percent of 

Rolling Avgs 

from Top 6% 

of Units 

Meeting UPL

Maximum 

10-Day 

Rolling 

Avg

Rounded CO 

CEMS MACT 

Floor, 10-Day 

Rolling Avg 

(ppm @ 3% O2)

Coal

FB 58.2 79.1% 77.5 78

PC 27.6 82.4% 34.3 35

Stoker/SlopedGrate/Other 33.2 100% 31.03 34

Biomass

Dutch Oven/Pile Burner 434 100% 406.2 440

FB 176 89.8% 478 480

Fuel Cell a a a

Suspension Burner 1333 71.4% 2249 2300

Suspension/Grate 723 76.7% 1356 1400

Wet Biomass Stoker/SlopedGrate/Other 405 75.2% 919 920

Dry Biomass Stoker/SlopedGrate/Other a a a a

Heavy Liquid N/A 18.0 100% 10.1 18

Light Liquid N/A a a a a

Non-Continental Liquid N/A a a a a

Process Gas N/A a a a a

Notes:

a. No applicable CO CEMS data available for this subcategory

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.

Table 12. Summary of Alternative CO CEMS MACT floor limits for non-continental existing boilers and 

process heaters, 3-hr rolling average.

Fuel Category

Combustor 

Design 

Category

99% UPL for 

3-Hour 

Rolling Avg

Percent of 

Rolling Avgs 

from Top 6% 

of Units 

Meeting UPL

Maximum

3-Hour

Rolling 

Avg

Rounded CO 

CEMS MACT 

Floor, 3-Hour 

Rolling Avg (ppm 

@ 3% O2)

Non-Continental Liquid N/A 90.5 90.9% 117 120

Note:

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.
18

Table 13. Summary of CO CEMS MACT floor limits for light liquid existing boilers and process heater, 

1-hr average.

Fuel Category

Combustor 

Design 

Category

99% UPL 

for 1-Day

Avg

Percent of 

Rolling Avgs 

from Top 6% 

of Units 

Meeting UPL

Maximum

1-Day Avg

Rounded CO 

CEMS MACT Floor, 

1-Hour Avg (ppm 

@ 3% O2)

Light Liquid N/A 59.9 100% 50.5 60

Note:

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.

Table 14. Summary of Alternative CO CEMS MACT floor limits for new boilers and process heaters, 10-

day rolling average.

Fuel Category

Combustor Design 

Category

99% UPL for 

10-day 

Rolling Avg

Maximum

10-Day 

Rolling 

Avg

Rounded CO CEMS 

MACT Floor, 10-

Day Rolling Avg 

(ppm @ 3% O2)

Coal

FB 58.2 77.5 78

PC 27.6 34.3 35

Stoker/SlopedGrate/Other 33.2 31.0 34

Biomass

Dutch Oven/Pile Burner 434 406 440

FB 174 478 480

Fuel Cell a a a

Suspension Burner 1333 2249 2300

Suspension/Grate 723 1356 1400

Wet Biomass Stoker/SlopedGrate/Other 451 919 920

Dry Biomass Stoker/SlopedGrate/Other a a a

Heavy Liquid N/A 18.0 10.1 18

Light Liquid N/A a a a

Non-Continental 

Liquid N/A a a a

Process Gas N/A a a a

Notes:

a. No applicable CO CEMS data available for this subcategory

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.
19

Table 15. Summary of CO CEMS MACT floor limits for new non-continental boilers and process 

heaters, 3-hr rolling average.

Fuel Category Combustor 

Design Category

99% UPL for 

3-Hour 

Rolling Avg

Maximum 3-

Hour Rolling 

Avg

Rounded CO 

CEMS MACT 

Floor, 3-Hour 

Rolling Avg 

(ppm @ 3% O2)

Non-Continental Liquid N/A 90.5 117 120

Note:

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.

Table 16 Summary of Alternative CO CEMS MACT floor limits for new light liquid boilers and process 

heaters, 1-hr average.

Fuel Category Combustor 

Design Category

99% UPL for 

1-Day Avg

Maximum 1-Day

Avg

Rounded CO 

CEMS MACT 

Floor, 3-Hour 

Rolling Avg (ppm 

@ 3% O2)

Light Liquid N/A 59.9 50.5 60

Note:

- Cells highlighted blue designate the value chosen for the alternative MACT Floor.
20

8.0 REFERENCES

1. EPA. Data Quality Assessment: Statistical Methods for Practitioners. EPA QA/G-9S. 

February 2006. Available on-line at: http://www.epa.gov/quality/qs-docs/g9s-final.pdf

2. Phase I ICR 2008 Combustion Survey. [ICR No. 2286.01]. OMB Control No. 2060-0616 -

Information Collection Effort for Facilities with Combustion Units. Approved by OMB on 

August 1, 2008.

3. Phase II ICR Test Plan Requesting Emission Testing from Boilers, Process Heaters, and 

CISWI. [ICR No. 2286.03]. OMB Control No. 2060-0616 - Information Collection Effort for 

Facilities with Combustion Units. Approved by OMB on May 21, 2009.

4. Eastern Research Group, Inc. Handling and Processing of Corrections and New Data in the 

EPA ICR Databases. January 2011.

5. Eastern Research Group, Inc. Handling and Processing of Corrections and New Data in the 

EPA ICR Databases – Revised November 2011.

6. Eastern Research Group, Inc. Revised MACT Floor Analysis (November 2011) for the 

Industrial, Commercial, and Institutional Boilers and Process Heaters National Emission 

Standards for Hazardous Air Pollutants – Major Source. November 2011. 

7. Young, T.M., and Winistorfer, P.M. The Effects of Autocorrelation on Real-Time Statistical 

Process Control with Solutions for Forest Products Manufacturers. Forest Products Journal, Vol 

51 (11/12). pp 70-77. November/December 2001.

8. SAS Institute Inc. SAS/QC User’s Guide, Version 8, Chapter 39. 1999.

9. Thaga, K. Control Chart for Autocorrelated Processes with Heavy Tailed Distributions. 

Economic Quality Control, Vol 23, No. 2. pp 197-206. 2008.