1730 RHODE ISLAND AVENUE, NW 

SUITE 700 

WASHINGTON, DC 20036 

WWW.ENERGYRECOVERYCOUNCIL.ORG

 

November 29, 2010 

United States Environmental Protection Agency 

Mailcode 6102T 

1200 Pennsylvania Ave., NW. 

Washington, DC 20460, 

Attn: Docket ID No. EPA–HQ–OAR–2009–0559 

Re: Standards of Performance for New Stationary Sources and Emission Guidelines 

for Existing Sources: Sewage Sludge Incineration Units; Proposed Rule (75 Fed. Reg. 

63,260 (October 14, 2010))

The Energy Recovery Council (“ERC”) appreciates the opportunity to submit to the 

United States Environmental Protection Agency (“EPA”) the following comments on 

Standards of Performance for New Stationary Sources and Emission Guidelines for 

Existing Sources: Sewage Sludge Incineration Units; Proposed Rule. 

ERC is the national trade association representing companies and communities engaged 

in the waste-to-energy sector. Waste-to-energy facilities produce clean, renewable 

energy through the combustion of municipal solid waste in specially designed power 

plants equipped with the most modern pollution control equipment to clean emissions. 

ERC members include: Covanta Energy Corporation, Wheelabrator Technologies Inc., 

and Babcock & Wilcox, several dozen business organizations in the municipal waste 

management and energy fields, and 28 municipalities that are served by waste-to-energy 

plants. ERC members own or operate 67 of the 86 waste-to-energy facilities in the 

United States. Members of ERC have a vital stake in the outcome of this rulemaking as 

owners and operators of facilities regulated under Section 129 of the Clean Air Act and 

which may combust sewage sludge in conjunction with municipal solid waste. 

Comment 1. EPA should exempt all solid waste incinerator units which are subject 

to other Section 129 standards. 

The proposed rules define a Sewage Sludge Incineration (SSI) unit as “an 

incineration unit combusting sewage sludge for the purpose of reducing the volume of the 

sewage sludge by removing combustible matter.” (75 FR 63313; 75 FR 63338.) The 

definition explicitly includes fluidized bed and multiple hearth SSI unit designs, but does 

not limit the definition to only these designs and does not require that a minimum amount 

of sewage sludge be combusted to be considered a SSI unit. As such, other solid waste 

incineration unit designs could be considered SSI units and subject to the rules if they 

combust any amount of sewage sludge. This would include Municipal Waste Combustors 

(MWCs) currently subject to other Clean Air Act (CAA) Section 111/129 New Source 

Performance Standards (NSPS) and Emission Guidelines (EG). 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 2 of 14 

EPA proposes to exclude from SSI regulation those commercial and industrial 

incinerators subject to the Commercial and Industrial Solid Waste Incinerator (CISWI) 

standards1, and seeks comment on whether other combustion units combust sludge and 

such units should be subject to SSI standards or to other Section 129 standards. (75 FR 

63268.) ERC believes that MWCs have the potential to fire sewage sludge and that the 

exemption afforded to CISWI-regulated units should be extended to both Large and 

Small MWCs subject to new or existing Section 129 MWC standards. 

It is appropriate to consider MWCs as potential combustors of sewage sludge. 

MWC units are or may in the future be permitted to accept it as a supplemental waste. 

There is no intrinsic technical limitation to accepting sewage sludge at MWCs. Material 

handling, combustion and emission control systems at many MWCs are appropriately 

configured or could be modified to successfully burn sewage sludge, and sludge content 

does not present unique challenges meeting MWC standards when fired with municipal 

solid waste. Co-fired amounts would be operationally limited by the relatively high water 

content of the sewage sludge, even if dewatered. From a policy perspective MWCs offer 

an environmentally sound alternative management option for municipal officials seeking 

to acceptably dispose POTW sewage sludge and recover its renewable energy potential. 

MWCs are typically located in urban areas proximate to sewage sludge generators and 

thereby represent a convenient, low transportation option. 

EPA should extend the Section 60.4780 and Section 60.5065 exclusions to all 

solid waste incineration units that meet the applicability requirements of other Section 

129 NSPS and EG rules, including MWCs regulated under Subparts Ea, Eb, Cb, AAAA, 

and BBBB. This exemption is consistent with EPA’s proposed CISWI NSPS and EG 

rules which explicitly exempt MWC units subject to these other Section 129 rules. (75 

FR 31974, Section 60.2020(c); 75 FR 31990, Section 60.2555(c).) 

Comment 2. EPA should exempt co-fired combustors which fire less than 30% 

sewage sludge by weight.

“Co-fired combustor” is defined in Sections 60.4930 and 60.5250 as follows: 

“Co-fired combustor means a unit combusting sewage sludge or dewatered sludge 

pellets with other fuels or wastes (e.g., coal, clean biomass, municipal solid waste, 

commercial or institutional waste hospital infectious medical waste, unused 

pharmaceuticals, other solid waste) and subject to an enforceable requirement 

limiting the unit to combusting a fuel stream, 10 percent or less of the weight of 

 

1

 In proposed Section 60.5065 EPA excludes existing CISWI units from Subpart CCCC, but this exclusion 

should be from Subpart DDDD which applies to existing CISWI units. 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 3 of 14 

which is comprised, in aggregate, of sewage sludge.”(75 FR 63312; 75 FR 

63337.) 

The inclusion of this definition in the proposal suggests EPA’s intent to limit 

applicability of the SSI rule to combustors firing more than 10% sewage sludge by 

weight. However, applicability criteria in proposed Subpart LLLL Section 60.4770 and 

Subpart MMMM Section 60.5005 do not explicitly exclude co-fired combustors. Indeed, 

once defined the term “co-fired combustor” is never used again anywhere in the proposed 

Subpart LLLL or Subpart MMMM regulations. We wonder why EPA defined the term if 

it did not intend to use it to exclude co-fired combustors from the SSI rules. 

EPA should exempt all co-fired combustors from Subpart LLLL and Subpart 

MMMM regulations. The co-fired combustor definition should place an upper limit on 

the amount of sewage sludge that could be co-fired and still meet the exemption. 

However, EPA should apply the exemption to units firing 30% or less by weight instead 

of 10% or less by weight. Because sewage sludge has high moisture content its heating 

value (kilojoules per kilogram as fired) is low, and a 10% limit by weight would 

effectively limit firing to a much lower fraction of total heat input, providing little 

incentive for operators to make any physical and permitting modifications necessary to 

accept sewage sludge. The 30% limit is also consistent with the co-fired combustor 

definition contained in MWC Section 129 rules, e.g. Subpart Eb rules at 40 CFR 60.51b. 

Comment 3. EPA should modify the definition of “co-fired combustor” to include all 

biomass, not just clean biomass.

EPA’s co-fired combustor definition applies to fuels and wastes and includes 

“clean biomass” and “other solid wastes” (75 FR 75 FR 63312; 75 FR 63337.) In the 

final rule EPA should assure consistency with the Identification of Non-Hazardous 

Secondary Materials That Are Solid Waste Rule (NHSM Rule) which was proposed June 

4, 2010 and is expected to be promulgated by December 16, 2010. Depending on the 

outcome of the NHSM Rule it is possible that some biomass materials (say, for example, 

urban demolition wood) would be neither “clean” nor classified as “solid waste”, thereby 

excluding these materials from the co-fired combustor definition. EPA can solve this 

potential problem by striking the adjective “clean” from biomass in the definition. Since 

EPA’s intent appears to be to include all biomass, either as clean material or solid waste, 

deleting “clean” from the definition would assure its intent is fulfilled regardless of the 

outcome of the NHSM Rule. 

Comment 4. EPA should change its MACT floor-setting methodology to conform to 

the law’s “average emissions limitation achieved” requirement. 

EPA’s proposed methodology sets a Maximum Achievable Control Technology 

(MACT) floor for each pollutant from an average of best performing 12% of units and 

then employs a statistical methodology which accounts for emissions variability to set 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 4 of 14 

MACT floor emissions limits. As explained in an April 2010 memorandum from Roy 

Oommen, ERG, to Amy Hambrick, U.S. EPA, entitled “MACT Floor Analysis for the 

Sewage Sludge Incinerator Source Category”, (hereafter called the “ERG Floor 

Memorandum”), EPA distinguishes between a “MACT floor” (an average of emissions 

from the best performing units), and a “MACT floor emission limit” (the value 

determined from its variability analysis). According to the ERG Floor Memorandum, for 

existing units “The MACT floor was calculated as the average of the test runs from the 

best performing (i.e. lowest emitting) 12% percent of sources” and for new units “The 

MACT floor was calculated as the average of the test runs from the best performing 

single unit (i.e. lowest emitting).” (ERG Floor Memorandum, page 10, emphasis added). 

EPA then conducted a variability analysis using the UPL statistic to determine the 

“MACT floor emission limit”. (ERG Memorandum, page 12, emphasis added). 

CAA Section 129(a)(2) states “Emission standards for existing units in a 

category...shall not be less stringent than the average emissions limitation achieved by 

the best performing 12 percent of units in the category.” A plain reading of this 

requirement with the key phrase “average emissions limitation achieved” directs that the 

limitation achieved be determined first, and then an average taken to determine the 

applicable least stringent standard. EPA’s method is inconsistent with this Section 129 

language. In EPA’s method there is no averaging of the achieved emissions limitations, 

an average is only used to select the best performing units and set a “MACT floor” value 

before considering variability. 

EPA should employ an alternate methodology which determines the emissions 

limitation achieved for each best performing unit first, and then averages these limitations 

to determine the least stringent standard, or MACT floor. This method conforms to the 

plain meaning of the phrase “average emissions limitation achieved”. Table 1 shows the 

difference between the EPA and alternate methods: 

Table 1. MACT Floor-Setting Methodology Comparison 

Step EPA Method Alternate Method 

Select best performing 

12% units based on...

average emissions. average emissions. 

Set emissions 

limitation achieved 

based on...

the upper limit of all data 

from selected units, i.e., pool 

all the emission data from 

selected units and calculate 

the upper limit value. 

the average of upper limit 

values for the selected units, 

i.e., determine the upper limit 

value for each of the selected 

units and then calculate the 

average of those values. 

The alternate method also conforms with EPA’s own explanation of the Mossville 

case findings: “The Court has recognized that EPA may consider emission variability in 

estimating the degree of emission reduction achieved by the best-performing sources and 

in setting MACT floors that the best-performing sources can expect to meet ‘every day 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 5 of 14 

and under all operating conditions’.” (75 FR 63269, emphasis added.) In “setting the 

MACT floors” the floor value should include the effect of variability. In EPA’s method 

the “floor” is the average of the best performing units before variability is considered. 

EPA then adjusts for the variability effects. In the alternate method the floor value 

already considers variability, consistent with the Mossville findings. 

From a statistics perspective, the alternate method is also superior. EPA’s method 

pools data from all best performing units for the statistical calculations which leads to 

biased results from 1) over-weighting the effect of units that have more data (see 

Comment 5), and 2) running statistical calculations on a pool of data from units 

representing distinct populations due to differences in design, feed, operating 

characteristics, and emission controls (see Comment 6). The alternate method avoids both 

these problems; data from each unit is given equal weight (one emissions limitation 

achieved calculated per unit) and statistical calculations are run using data from only one 

unit (distinct population) at a time. 

Comment 5. EPA’s floor-setting methodology biases results in favor of units that 

have more data. EPA should use the alternate methodology presented in Comment 4 

which avoids this problem.

In setting MACT standards for existing units, EPA pools and utilizes data from all 

available test runs for the best performing units without regard to the number of data 

points available for each unit. For all pollutants the number of test runs varies from unit 

to unit. Using data this way biases the statistical results and ultimately the standards by 

over-weighting the performance of the units that have more data. As an example, in the 

ERG Floor Memorandum, Attachment A-2, page 2, “Variability Analysis for CO from 

Existing FB Units” the five best performing units include a total of 112 data points, 

distributed as shown in Table 2. EPA’s analysis biases the MACT floor results toward 

Units 3, 4, and 5 which constitute 92% of the data points even though they make up only 

60% of the units, and under-weights Units 1 and 2 which are 40% of the units but only 

contribute 1/12th of the data. This example clearly shows EPA’s floor-setting 

methodology is scientifically and statistically flawed. 

Table 2. EPA's CO Variability Analysis for 

Existing FB SSIs 

Unit 

Number of 

Data Points % of units % of Data

1 6 20% 5% 

2 3 20% 3% 

3 35 20% 31% 

4 30 20% 27% 

5 38 20% 34% 

All 112 100% 100% 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 6 of 14 

EPA should avoid this serious flaw simply by using the alternate methodology 

presented in Comment 4. In this alternate method each best performing unit’s emissions 

limitation achieved is determined first and then that single value is averaged along with 

the single values from the other best performing units to determine the floor. All best 

performing units are thereby weighted equally. 

Comment 6. The UPL approach does not work because best performing MACT 

units represent distinct populations due to variability in design, sludge 

characteristics, operating characteristics, operating/maintenance procedures and 

emission controls. 

 

Best performing MACT units represent separate and distinct populations due to 

variability in design, sludge characteristics, operating characteristics, 

operating/maintenance procedures and emission controls. All these variables are 

independent from one best performing source to the next. Therefore the only way a UPL 

based approach could statistically work is if variability from individual best performing 

sources are treated independently and data from each source is given equal weight. EPA 

has used the square root of sample variance instead of the square root of total variance. 

By substituting sample variance for total variance EPA has not properly accounted for 

total variability. Given these two assumptions then between source variance and within 

source variance must be additive not pooled and total variance between the best 

performing sources would be used in UPL approach as was proposed in the Hazardous 

Waste Combustor (HWC) MACT Rule.2 

The equation for the UPL that addresses total variation from the HWC MACT 

Rule is: 

 UPL = Mean + t √ VT

Where, Mean is the average of the best performing MACT unit averages and VT is the 

total variance determined as the sum of the within (intra) source variance and the between 

(inter) source variance. 

Total Variance of VT = VB + VW , 

Where, VB is the variance of the average of the best performing unit averages. As 

described above VB is additive because the variance of each MACT source unit is 

independent of one another and dependent on individual units sludge characteristics, 

sludge combustor type, air pollution control type and sample matrix affects. VW is the 

within or intra source variance and is calculated as the sum of the variances of individual 

 

2

 Technical Support Document for HWC MACT Standards, Volume III: Selection of MACT Standards. 

U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response. September 2005, 

Pages 7-5 to 7-7. EPA-HQ-OAR-2004-0022-0453.pdf
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 7 of 14 

runs within each of the best performing sources since individual unit test results will vary 

with sludge characteristics, and process and air pollution control operation conditions 

during each test run and test event. 

Using the UPL outlined in the HWC MACT Rule that accounts for total variance 

between best performing source provides another alternative to calculating MACT limits 

that is in line with the 99% UL calculated from the 3 run averages. 99% UPL MACT 

limit for CO and Cd calculated using total variance approach is 73.3 ppm and 0.0020 

mg/dscm respectively. Similar results would be expected for the other limits as well. 

Comment 7. In its variability analysis EPA should not use the upper prediction limit 

(UPL) to set MACT floors because the random data distribution premise of the UPL 

calculation is incorrect. EPA should instead use actual 3-run averages and calculate 

the floor using the upper limit (UL) statistic. If EPA cannot use 3-run averages due 

to a paucity of data then EPA should use individual test runs and the UL.

EPA determines the MACT floor limit for each pollutant using individual test run 

values and an upper predictive limit (UPL) calculation. (75 FR 63269.) The UPL is a 

statistical tool that is misapplied in this case and should not be used. The UPL recognizes 

that the variability of 3-run averages is different from that of individual test runs, i.e. they 

have different frequency distributions. Mathematically the UPL accounts for this 

difference by adjusting the upper limit determined from individual runs to that using 

multiple runs using the factor SQRT ((1/n) + (1/m)), where m=3, the number of runs per 

complete performance test. However, this adjustment presumes that each test run result 

within a given 3-run test occurs randomly over the entire population distribution. EPA 

provides no evidence supporting this presumption. In fact, as will be seen in the examples 

below, run-to-run results within performance tests are not distributed randomly across the 

entire distribution. Rather, each of the three runs reflects conditions affecting a unit’s 

emissions at the time of the test. Many of these conditions (e.g., sludge characteristics, 

condition of combustor and air pollution control equipment, season of the year) are likely 

to remain the same or at least similar over the short duration (up to a few days) of a 

performance testing program. Individual run results in a short term performance test will 

therefore not vary randomly across the entire distribution of emissions that would be 

observed over longer (monthly or annual) time periods. For example, suppose testing is 

performed with sludge that has seasonally higher-than-average sulfur content leading to 

elevated SO2 emissions. EPA’s UPL calculation presumes that SO2 emissions during any 

test run is just as likely to be below the average SO2 emissions as above when in fact all 

three runs are likely to be above the average because the sulfur content is higher than 

normal over the entire course of the short term performance test. In short, the frequency 

distribution of 3-run averages will exhibit a greater standard deviation and hence greater 

variability than that predicted by EPA’s UPL. EPA’s UPL approach under-estimates 3-

run average performance test variability thereby setting MACT floor limits which have 

not been achieved in practice and failing to comply with CAA Section 129. 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 8 of 14 

Examples Demonstrate the Validity of Our Comment

EPA’s inappropriate use of the UPL is demonstrated in examples for three pollutants 

taken from EPA’s MACT Floor calculations for existing FB units (ERG Floor 

Memorandum, “Attachment A., Detailed MACT Floor Analysis for Existing FB Sources 

Cd, Pb, Hg, HCl, SO2, NOx, and CO”, Docket # EPA-HQ-OAR-2009-0059-0006.1). 

Attachment 1 to these comments is an Excel file which repeats EPA’s floor calculations 

and also contains seven additional columns of calculations we have added for CO, Cd, 

and Hg, highlighted in yellow. First, let’s assess the accuracy of EPA’s 99% UPL 

calculation for CO, which is shown in pink-highlighted cell G132 as 51.1 ppm. Given the 

relatively large CO database (112 test runs) we can test the CO UPL accuracy with 

confidence by calculating 3-run performance test averages3 and the resulting 99% UL, 

and then comparing this 3-run average 99% UL with EPA’s 99% UPL. Column H shows 

this calculation which yields a 99% UL of 74.1 ppm (green-shaded cell H130), 34% 

higher than EPA’s value. Again, this 74.1 ppm value represents the true 99% upper limit 

of variability because it uses the actual 3-run average performance test data. So what 

accounts for this 34% difference? It’s the fact that EPA’s UPL statistic presumes run-torun variability is random across the entire distribution of data, whereas the actual data 

show the variability is not random. We can duplicate EPA’s UPL value if we randomly 

sort the raw data using the Excel RANDBETWEEN function in Column I and recalculate 

the 99% UL. The resulting 55.0 ppm 99% UL value as (orange-shaded cell K130) closely 

matches EPA’s value, verifying that the only way to support EPA’s UPL approach is to 

incorrectly presume that run-to-run data occur randomly across the entire data 

distribution. (The calculations in Column K will not match EPA’s UPL exactly because 

the limited data introduce some error, but the calculated values will always be similar.) 

Similar conclusions result from an assessment of Cd and Hg data and also Lntransformed data for CO, Cd, and Hg shown in Columns L, M & O. The results, 

summarized in Table 3, demonstrate that EPA’s UPL understates the variability of 3-run 

performance test averages and should not be used. 

 

3

For two of the tests only 2 valid runs were available so in those instances we used 2-run averages. 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 9 of 14 

Table 3. Summary of UPL and UL calculations 

CO (ppm) Cd (mg/dscm) Hg (mg/dscm) 

MACT Floor Using... N LN N LN N LN 

99% UPL (EPA’s approach) 55.1 105.4 0.0014 0.0019 0.0109 0.0032

99% UL with Actual 3-run 

Test Averages (Statistically 

valid approach) 76.1 435.1 0.0020 0.0092 0.0177 0.0153

99% UL with Randomly 

Distributed Data and 3-run 

Test Averages (Random data 

approach) 55.0 110.2 0.0013 0.0017 0.0109 0.0036

N = Normal statistics, LN = Log-normal statistics 

EPA should avoid the entire issue of adjustments for the number of runs per 

performance test by using 3-run test averages in its database and calculating the 3-run 

average upper limits (UL) for each pollutant. The calculated UL values will appropriately 

reflect the true 3-run performance test variability. If EPA cannot use 3-run averages due 

to a lack of data then it should use individual test run results and the UL value that is 

unadjusted for the number of runs per performance test, i.e. m=1. EPA should not 

penalize the regulated community with more restrictive emission standards because it has 

not obtained enough test data to provide for valid statistical analysis. 

Comment 8. For the purposes of characterizing emission data distributions EPA 

should default to non-normal unless sufficient data are available to conduct robust 

analyses which unambiguously shows the distribution can only be described by 

normal statistics. 

The first step in statistical analysis on a dataset is to determine the type of distribution the 

data follow, typically characterized as normal or non-normal (log-normal). In its 

proposed SSI rule methodology EPA employs simplistic criteria using two Excel 

functions (skewness and kurtosis) to decide whether emission data are normally or nonnormally distributed. 

Using its criteria EPA finds that the data used for SSI floors follow normal 

distributions for 45% of the pollutants for EG and 90% for NSPS. (ERG Floor 

Memorandum, Attachments A-E.) This finding is inconsistent with both conventional 

wisdom and EPA’s own Guidance for Data Quality Assessment Manual,4 (hereafter 

referred to as “EPA Guidance for Data Assessment”) which hold that it is more likely 

that environmental data are distributed log-normally. EPA’s Guidance for Data 

Assessment provides that the log-normal distribution is “a commonly met distribution in 

 

4 U.S. Environmental Protection Agency, Office of Environmental Information, “Guidance for Data Quality 

Assessment: Practical Methods for Data Analysis”, EPA/600/R-96/084, July 2000
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 10 of 14 

environmental work” (page 2-40), also stating “Environmental data commonly exhibit 

frequency distributions that are non-negative and skewed with heavy or long right tails” 

(page 4-7), and “The lognormal distribution is a commonly used distribution for 

modeling environmental contaminant data” (page 4-7). It is reasonable to believe that 

environmental emissions distributions are non-normal, since frequency plots typically 

show many readings approaching zero and fewer large readings forming an elongated tail 

to the right. Normal distributions may exist for certain pollutants where the entire dataset 

is many standard deviations away from zero, and values are controlled by an air pollution 

control process with set points, and feedback and control loops. 

EPA’s characterization approach using Excel functions is not robust. The 

Guidance for Data Assessment states that skewness and kurtosis tests are “rarely used as 

they are less powerful than many alternatives.” It is therefore reasonable to conclude that 

EPA’s data distribution designations are flawed and that they bias the resulting MACT 

floor determinations. 

Distribution determination is not an exact science, even with datasets that are 

representative of the entire data population. Graphical methods and mathematical 

methods such as Shapiro Wilk are frequently employed but can still lead to ambiguous 

results. Add the additional confounding factor of EPA’s small database for many of the 

units and the determination becomes highly uncertain. For new units where normal 

distributions were assigned to 90% of the pollutants, EPA is applying its Excel criteria to 

as few as three data points! Any conclusion reached from such a cursory analysis is 

extremely uncertain and speculative. In addition datasets do not lend themselves to 

simple black and white normal/non-normal designations, there are shades of grey. EPA’s 

forced, binary analysis belies this fact. 

The normal/non-normal designation is too important to be left to chance. In the 

SSI proposal 99% UPL values differ significantly between normal and non-normal; for 

new units the normal distribution 99% UPLs are on average only 60% of the non-normal 

distribution 99% UPLs. EPA’s criteria for assigning data distributions risks setting 

MACT floors which have not been achieved in practice. 

EPA must, by default, assume that emissions data it analyzes are non-normally 

distributed unless rigorous statistical analysis conducted in accordance with EPA 

guidance unambiguously show otherwise. This approach is reasonable and consistent 

with the need to err on the side of achievability in order to assure compliance with the 

Section 129 requirement that emissions limitations be achieved in practice. In setting 

MACT floors the stakes are too high for EPA to rely on cursory Excel tests and criteria 

applied to small and likely non-representative datasets to determine distributions. 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 11 of 14 

Comment 9. In its statistical calculations EPA should select the 99.9% upper limit 

(and not the 99% upper limit) as representative of emissions limitation achieved. 

EPA should reject its proposed 95% UPL alternative.

In its proposal EPA determined MACT floor emission limits for existing and new 

units based on a 99th percentile UPL. In Comments 6 and 7 we explained our concerns 

about EPA’s use of the UPL versus the UL. In this comment we address the 

appropriateness of the selected numerical percentile value and will refer to it simply as 

the “% limit”. From the statistical point of view a 99% limit is the emission value that the 

unit will meet with 99% probability. While this would seem to suggest a high likelihood 

of compliance, probability must be viewed from a violation perspective, i.e. that there is a 

1% likelihood that a given pollutant test on a given unit will exceed the selected 

limitation. In this regard the 99% limit is inadequate. EPA’s rules propose annual 

performance tests to demonstrate compliance with each of 11 emission limits. For each 

unit the probability of passing all 11 pollutant emission tests in an annual performance 

testing program is (0.99)11 = 90%, i.e. the probability of at least one emission violation is 

10%, excluding the additional compliance risk associated with continuous emission 

monitoring (CEM). These are unacceptable risks to any responsible operator, and should 

likewise be unacceptable to EPA. 

The consequences of emission limit exceedances are severe. Operators face stiff 

fines, retesting costs, additional regulatory scrutiny, bad press, citizen suits, and negative 

public opinion. All diligent operators try to keep emissions well below limits in order to 

account for emissions variability and thereby avoid violations and their consequences. 

If EPA employs the statistical limit to set MACT floor emission limits it should 

use the 99.9% limit. This represents a 0.1% probability of a failure for individual tests, or 

a 1% per unit non-compliance probability per annual performance test program. This 

value better encompasses unit emissions variability and represents a manageable risk to 

the responsible facility operator.5

 

EPA originally proposed using the 99.9% UL in its Hospital/Medical/Infectious 

Waste Incinerator (HMIWI) MACT rule (73 FR 72962), stating “The 99.9 percent UCL6

is appropriate for use in this analysis because sources must meet the standards at all 

times, and as mentioned above, the limited amount of test data introduces a degree of 

uncertainty.” (73 FR 72977). EPA changed its protocol to 99% in the final HMIWI rule 

 

5

 We are concerned that EPA’s emissions database does not account for emissions variability occurring 

during startup, shutdown, and malfunction periods. This comment does not address that concern and the 

resulting additional compliance risk. 

6

 The HMIWI rule used the term upper confidence limit (UCL); however, EPA acknowledged in its 

proposed CISWI rule that the term as used in the HMIWI rule is the same as the upper limit (UL). See 75 

FR 31943, footnote 3. 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 12 of 14 

in response to public comments, “The 99 percent UCL values are more in line with the 

highest test runs for the MACT floor units than the other percentiles, indicating that the 

99 percent UCL provides a more reasonable compensation for variability.” (74 FR 

51387). EPA’s conclusion is invalid because, like the SSI unit database, the HMIWI 

database consisted of scant emission test results, few enough to require EPA to use 

individual test runs in order to have more data to use in its statistical analyses. With so 

few data points it is highly unlikely that the highest emissions and full variability would 

have been observed. Indeed, the inability to capture and describe the full range of 

emissions and emission distribution is the very reason for relying on statistics to predict 

upper limits! EPA’s conclusion to use 99% in the HMIWI rule therefore has no valid 

statistical basis and only serves to increase the probability of emissions violations. In the 

SSI MACT rule EPA should use 99.9% limit as originally proposed in the HMIWI rule. 

EPA requests comment on an alternative to use 95% limits (95% UPL) to 

calculate MACT floors. (75 FR 63274.) EPA observed that certain calculated floors were 

higher than SSI test data so it is considering the use a 95% upper limit to get lower floors 

and tighter limits. In short, it appears EPA didn’t like the results so it’s thinking about 

changing the % limit to get results that are more stringent. This is purely arbitrary and 

capricious. 

In addition, EPA’s lack-of-data rationale to reduce the UPL % is inconsistent with 

its conclusion that it has enough data (sample size) to characterize emissions. (75 FR 

63270-63271). If EPA argues that there are enough data to determine the floors EPA 

cannot also argue that insufficient data is causing the need to make a calculation change. 

Rather than making arbitrary changes to fit a desired outcome, EPA should 

instead be comparing the data scatter in the SSI database with that in other MACT rules 

(which also suffer from limited data) to determine whether scatter (standard deviation) is 

indeed higher and if so examine its methodology to explain it. What EPA might find is 

that the combination of the way units were selected (using data from all units thought to 

be best performers based on air pollution control devices rather than selecting best 

performing units from the universe of SSIs) and EPA’s pooled data approach (running 

statistics on pooled data from units representing distinct data populations due to 

differences in design, feed, operating characteristics, and emission controls) is what 

results in higher standard deviations. 

EPA should not attempt to solve one problem with its methodology (the data 

scatter largely caused by its use of pooled data from different units) by creating another 

problem (promoting acceptability of a 5% failure rate per pollutant per test). In fact, 

based on the above discussion even a 1% failure rate is unacceptable. EPA should instead 

revise its overall methodology in accordance with Comment 4 and calculate the 99.9% 

UL as the MACT floors. EPA should not arbitrarily change the % limit. Where there is 

uncertainty, EPA must err on the side of achievability; otherwise it risks setting the 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 13 of 14 

technology-based MACT standards at levels which technology cannot achieve, in 

contradiction to the CAA. 

EPA can use its authority under the law to go beyond-the-floor in instances where 

derived floors do not reflect “maximum degree in reduction of emissions”. In fact, with 

its limited emissions database and statistical tools EPA should anticipate that some 

calculated floor values may be higher than is ultimately achievable. This is result of these 

limitations. In such cases EPA should rely on its beyond-the-floor evaluation to set the 

standards. EPA can also set more stringent standards in the residual risk and five-year 

review processes wherein a more robust data population would be available. 

 

Comment 10. EPA correctly omitted a PM2.5 standard. 

EPA requests comment on whether it should set PM2.5 standards for SSIs and 

whether OTM 27 and 28 are appropriate measurement techniques. (75 FR 63275.) ERC 

believes that EPA acted properly by excluding a PM2.5 emission standard from its 

proposal and that it should not recognize the OTM 27/28 methods for PM performance 

testing. 

Section 129 standards are based on emissions reductions achieved using MACT. 

MACT air pollution control (APC) equipment for particulate matter (PM) emissions is 

limited by its ability to capture particulate that exists at the APC device operating 

temperature. This temperature is much higher than the ambient temperatures at which 

much of the condensable particulate forms. The MACT standard and associated 

performance test method should reflect the PM control device’s capability at operating 

flue gas temperatures. The OTM 27/28 methods measure not only PM actually present in 

the flue gas but also any particulate matter formed from the interaction and condensation 

of gaseous organic/inorganic flue gas constituents in the sampling train, and thereby 

measure and report PM which is beyond the capability of the PM control device selected 

as MACT. In addition, to our knowledge OTM 27/28 methods have not been validated 

on SSIs as mandated by Section 129. As such the SSI MACT standards should regulate 

PM as measured by EPA Reference Method 5, and not OTM 27/28. 

PM2.5 emission standards are appropriate in the context of Ambient Air Quality 

Standards or other ambient health-based standards, and are set as part of source PSD/Title 

V permitting processes which evaluate both solid and condensable PM emissions and 

their impacts. Regulation under MACT is inappropriate and unnecessary. 

Comment 11. EPA’s two dioxin/furan emission standards are duplicative and 

unnecessary. EPA should set a single standard for dioxin/furan total mass basis.

EPA’s proposal contains two emission standards for dioxin/furan, one as total 

mass basis (TMB) and the other as toxic equivalents (TEQ). These standards are 

redundant, only a TMB standard is appropriate. The same test, EPA Reference Method 
Docket ID No. EPA–HQ–OAR–2009–0559 

Comments of Energy Recovery Council 

November 29, 2010 

Page 14 of 14 

23, is used to measure both TMB and TEQ, the only difference being a mathematical 

calculation using TEQ factors to convert the measured TMB values to TEQ values. TEQ 

factors have changed over the years from the original 1989 I-TEQ to the presently used 

2005 World Health Organization Toxic Equivalence Factors, so setting a TEQ standard 

represents a potentially moving target. Two standards are not required by Section 129 

which lists “dioxins and dibenzofurans” only once and without distinction between TMB 

and TEQ. (Section 129(a)(4).) Finally, MACT standards are based on emissions 

reductions at best performing units, i.e. are technology based as opposed to health based. 

Considering these facts, EPA should promulgate a single dioxin/furan standard, as TMB, 

or if compelled to regulate both TMB and TEQ should base compliance on achieving 

either one of the two limits. 

Conclusion

The Energy Recovery Council shares EPA’s commitment to improving emissions. 

As an industry, our members have demonstrated this commitment with a constant drive to 

enhance technology and reduce emissions. ERC appreciates the opportunity to submit 

these detailed comments. Of course, we would be pleased to answer any questions you 

may have. 

Sincerely, 

 Ted Michaels 

 President 
Attachment 1 

(This was filed as an Excel spreadsheet in 

conjunction with these comments)