March 25, 2011

MEMORANDUM TO DOCKET EPA-R04-OAR-2005-AL-0002

Subject: Review of Modeling Submitted for Alabama Opacity 2007 Proposal Notice and 2009 

Reconsideration Proposal Notice

From: Joel Huey, EPA Region 4

Stan Krivo, EPA Region 4

Background

Modeling analyses were submitted by commenters both in favor of and opposed to the Alabama 

visible emissions rule revisions, which EPA proposed for approval in 2007, finalized in 2008, 

and proposed for reconsideration in 2009. EPA has reviewed the modeling submitted by the 

State of Alabama with its original SIP submittal, the modeling analyses provided by commenters 

during the public comment period on the 2007 proposed rulemaking, and the modeling analyses 

submitted during the public comment period on the 2009 proposed rule reconsideration. The 

purpose of this document is to summarize the modeling received by EPA and to provide the 

Agency’s view of those submittals.

Plume opacity is the degree to which stack emissions reduce the transmission of light. A given 

opacity level is associated with a range of particulate matter (PM) mass emissions, which

depends upon many factors, including fuels combusted, industry type, boiler type, PM particle 

composition and size, controls used to reduce pollutants, etc. Given these variables, 

development of a specific correlation between plume opacity and the associated level of PM 

mass emissions at a source requires measurement data showing the opacity and associated PM 

mass at the source across a range of operating conditions. 

Because no demonstrated correlation between opacity and PM emissions for the sources affected 

by the rule revision was available, all commenters estimated PM mass emissions based on their 

respective views and assumptions concerning the relationship between opacity and PM mass 

emissions. The commenters then used the assumed PM emission rates to estimate ambient 

impacts through their modeling analyses.

While modeling can be a valid tool to estimate ambient impacts, its appropriateness for a 

particular application is dependent on the availability of representative input data. The emission 

rates used as inputs to a model dictate the modeling outputs. Of most importance to the 

modeling for this particular SIP revision is the representative PM mass emissions associated with 

specific levels of opacity. If the inputs are incorrect, the results are also incorrect, even if the 

procedures used to perform the modeling are done correctly.

Attachment A of this memo provides a detailed summary of the modeling submitted by the State 

of Alabama with its original SIP submittal and the modeling submittals provided by commenters 
2

during the public comment period on the 2007 proposed rulemaking. In addition to modeling 

done by the State, commenters who provided modeling in support of the proposed visible 

emissions rule revisions include Tennessee Valley Authority (TVA) and Alabama Power 

Company (APC). Commenters who provided modeling in opposition to the proposed rule 

revisions were Alabama Environmental Counsel and others.

Attachment B of this memo provides a detailed summary of the modeling analyses submitted 

during the public comment period on the 2009 proposed rule reconsideration. Commenters who 

provided modeling in support of affirming the final 2008 visible emissions rule revisions include 

TVA and APC. Commenters who provided modeling in support of reversing the rule revisions 

were Alabama Environmental Counsel and others.

Observations

I. Limitations of all Modeling Submitted Regarding this SIP Revision 

In the 2008 rule revision approval notice, EPA noted several uncertainties or weaknesses in the 

modeling submitted during the comment period on the April 12, 2007, proposal, and we continue 

to have those same concerns. Specifically, the following limitations were noted:

1. The assumption that maximum PM emissions occur at 100 percent opacity and that 100 

percent opacity occurs when the control device (e.g., electrostatic precipitator) is turned 

off;

2. The lack of a known relationship between opacity and PM emission rate;

3. The lack of a known range of PM emissions that produce 100 percent opacity;

4. The lack of information on source operating conditions that could affect opacity;

5. The failure to include impacts of nearby emission sources in the modeling;

6. The inability of the models used to address secondary formation of PM2.5;

7. The failure to consider condensable PM emissions; and

8. The lack of information on the range of sources affected by the opacity rule revision.

With respect to the first item, no data were supplied by commenters to demonstrate for any 

source either that opacity will be 100 percent when the maximum PM emissions occur or that 

maximum PM emissions are occurring whenever opacity is 100 percent. Moreover, no data were 

supplied by commenters to demonstrate either that 100 percent opacity means control devices 

have been de-energized (i.e., turned off) or that de-energizing PM control devices produces 100 

percent opacity. Without a known, established relationship between PM emissions and opacity, 

one must assume the maximum PM emissions from a source that is associated with 100 percent 

opacity. Using assumed rather than known PM emissions that represent 100 percent opacity in 

the modeling renders modeling results inconclusive.

The second item expands the issue of the unknown relationship between opacity and PM 

emissions from one condition – 100 percent opacity – to other opacity conditions. No data were 
3

supplied by the commenters to demonstrate the relationship between PM emissions and opacity

at any levels. As discussed above, without a known, established relationship between PM 

emissions and opacity for an emission source, one must assume a PM emission rate, or range of 

rates, associated with an opacity level. Again, using assumed PM emissions as an input to the 

model renders modeling results inconclusive.

The third and fourth items are related in that no data were supplied by the commenters to 

demonstrate the range of PM emissions or source conditions that produce 100 percent opacity. 

In general, particles sized around one micron scatter light more efficiently than larger sizes, 

meaning that equal mass rates of PM1.0 emissions produce greater opacities than PM10 emissions. 

Commenters provided neither PM sizing information nor corresponding opacity levels for those 

PM sizes or emission rates for any of the sources considered in their respective modeling 

analyses. Likewise, no information was provided on source operating conditions, such as level 

of PM control device efficiencies, and their relationships to PM sizes or emission rates and 

opacity levels. As discussed above, without a known, established relationship between the 

sources’ control device operation, PM emissions, and opacity, one must assume a PM emissions 

rate associated with control device operation and opacity level. Questionable model input 

regarding PM emissions produce modeling results that are inconclusive.

The fifth, sixth and seventh items are related, for they address the information needed to properly 

perform ambient air impact modeling to assess compliance with PM NAAQS and PSD 

increments as a result of changes in Alabama visible emissions rule. Other nearby sources of 

PM emissions not affected by this rule revision contribute to the total ambient PM concentrations 

needed for comparison with ambient standards. Failure to consider these other sources of 

emissions in the modeling analysis renders the analysis incomplete. To assess compliance with 

PM ambient standards, the impact of changes in PM emissions for the sources of concern must 

be combined with other PM emissions data from other sources in the area so that all the PM 

sources in the area are properly considered. Some of the analyses provided did not consider 

condensable PM2.5, and none of the analyses considered formation of secondary PM2.5. The 

models used to estimate the impacts cannot address secondary particle formation, so this 

mechanism was not included in the modeling. Because no commenter has provided such 

cumulative PM impact assessment from all emission sources in an area, the modeling results are 

based on a subset of sources that yield an incomplete assessment of the ambient concentration 

for comparison with PM NAAQS or PSD increments. 

With respect to the eighth item, while ADEM identified the sources it believed to be subject to 

the proposed SIP change, no commenter has identified each source or source type, provided PM 

emissions data from each source or source type, or ascertained the impact of changing the 

opacity limits of the SIP on each source or source type. In other words, none of the modeling 

analyses submitted by the commenters actually addressed the full range of sources or source 

types affected by the SIP revision. Of the commenters who provided assumptions about PM 

emissions, they limited their assumptions and analyses to one source, typically a coal-fired 

electric utility boiler with an electrostatic precipitator. No documentation was provided to 
4

demonstrate how or why the sole source modeled was representative of all sources subject to the 

SIP change. Modeling based on a subset of sources, but not all sources or source types affected 

by the rule, yields an incomplete assessment of the impact of the rule revision on the area’s PM 

NAAQS and PSD increment compliance. 

II. Observations on the Modeling Submitted for the 2007 Proposed Approval

AEC and others (John Nuckels) – Plant Colbert

1. Although the methodology for the development of the PM emission rate is reasonable, 

source operation entirely without emission controls is unlikely, thus rendering the 

modeling results suspect.

2. The analysis used actual stack heights as an input to the model, which would be a 

prohibited dispersion technique and would indicate greater dispersion than allowed under 

modeling protocol. The use good of engineering practice (GEP) stack heights in this 

assessment would likely increase PM impacts.

3. Scenario #2 (4.8 hours uncontrolled) is not applicable and should not be considered. 

Compliance with the PM NAAQS is assessed on a calendar day basis, and the Alabama 

rule allows at most 2.4 hours of opacity limit exemption per calendar day.

4. Although adding background concentration for PSD increment assessment is not 

appropriate, this assessment does so (and reports values greater than PSD increment). 

TVA (Jacobs, Cook and Wylie) – Plant Colbert

1. The assessment is very similar to AEC analysis except that PM mass emission rates 

modeled are 3 to 8 times smaller. 

2. Condensable PM emissions not included in the assessment. Condensable particle 

formation could be an important contributor to ambient PM concentration levels but has 

not been included in the analysis.

3. The analysis does not include the background pollutant concentration, which is a 

necessary component of a proper NAAQS compliance modeling analysis. Modeling 

source emissions without including nearby emission sources and an appropriate

background pollutant level does not provide an estimate of ambient levels to allow 

assessment of compliance with the national ambient air quality standards.
5

APC (Paine and Thomson) – Plant Greene

1. The analysis does not include the background pollutant concentration, which is a 

necessary component of a proper NAAQS compliance modeling analysis (see above 

observation 3 for TVA – Plant Colbert). 

2. The PSD PM10 increment modeling procedure inappropriately uses the difference 

between the controlled and the uncontrolled emission rates to estimate PSD emissions. 

ADEM Modeling (2003 SIP submittal)

1. The submittal does not address PM2.5, the most important PM indicator of concern. The 

submittal only addresses the impact of PM10 emissions on ambient concentrations and 

compliance with ambient standards. 

2. PM mass emissions modeled for 100 percent opacity are just a multiple of that used by 

another state. No basis or reasoning is provided for use of this multiple. ADEM also 

used differing emissions rates for 100 percent opacity when performing NAAQS and 

PSD increment compliance, but provided no explanation or bases for the differences.

3. The modeling procedure is very different from that of APC, TVA, and Nuckels, so a 

direct comparison with these results is not possible.

III. Observations on the Modeling Submitted for the 2009 Reconsideration Proposal

AEC and others (Khanh T. Tran) – Plant Colbert

1. This assessment and the results duplicate that provided by Nuckels. Therefore, the 

comments under AEC and others (John Nuckels) in Section II. above apply here as well.

2. Performed additional PM2.5 24-hour analysis in the form of the NAAQS (average of the 

98th percentile for the annual periods modeled). 

3. Compared the modeling results to PM2.5 PSD increment. Additional PSD affecting 

sources were not included.

TVA’s Comments on Tran Analysis (Mueller) – Plant Colbert 

1. TVA’s comments on the Tran analysis were primarily a critique of modeling analysis on 

Plant Colbert performed by Khanh T. Tran of AMI Environmental for the Sierra Club. 

The Tran analysis was incorporated by reference by AEC in their December 16, 2009, 

comments on the proposed reconsideration.
6

TVA’s Analysis (Mueller) – Plant Colbert

1. The modeling procedure is unrealistic in limiting 100 percent opacity emissions to the 

first 2.4 hours of each calendar day. The 100 percent opacity operation could occur at 

any time during the day – not just the first 2.4 hours of each day. The meteorological 

parameters used in the modeling have diurnal variations that would not be reflected in 

this modeling procedure. Therefore, for example, the periods of 100 percent opacity

would never be modeled under the typical unstable conditions of the afternoon hours.

2. The analysis does not include the background pollutant concentration, which is a 

necessary component of a proper NAAQS compliance modeling analysis (see above 

observation 3 for TVA – Plant Colbert). 

3. The modeling uses a different meteorological station and period than modeling 

assessments TVA completed for the same Colbert Plant for the 2007 proposed approval.

In order for a meaningful comparison to be made, data from the same meteorological 

station and period should be used. 

APC’s Recap of 2003 ADEM Modeling (Paine)

1. The 2003 ADEM modeling analysis was performed using ISCST3. This same analysis 

was run again (by AECOM for APC) using the current regulatory approved model, 

AERMOD. For the same input emissions and meteorological data, AERMOD produced 

lower ambient concentrations than ISCST3. 

2. The comments under ADEM Modeling (2003 SIP submittal) in Section II. above remain 

applicable for this re-modeling.

APC’s Recap of Own Modeling (Paine) – Plant Greene

1. Nothing new was added to this discussion of the modeling performed for APC Plant 

Greene provided for the 2007 proposed approval. 

2. The comments under APC (Paine and Thomson) - Plant Greene in Section II. above 

remain applicable.

APC’s New Analysis (Paine) – Plant Barry

1. APC provided a new NAAQS compliance assessment for another plant – Plant Barry.

2. Condensable PM emissions are not included in the assessment. Condensable particle 

formation could be an important contributor to ambient PM concentration levels but has 
7

not been included in the analysis.

3. Emissions at 100 percent opacity were assumed to be equal to the total ash content in the 

coal burned. This is a conservative assumption that was used for 10 percent of the daily 

hours for each day modeled.

4. The totals of the maximum PM10 and PM2.5 modeled concentrations, in the form of the 

standards, plus background concentrations were less than the applicable PM10 and PM2.5 

NAAQS.

Summary of Observations

All modeling impact analyses have limitations. The modeling analyses provided by the 

commenters regarding the Alabama visible emissions rule revisions are not exceptions. This 

technical support document summarizes the salient features, observations, and limitations of the 

modeling submitted.

In a possible worst-case scenario where 100 percent opacity was assumed to be associated with 

operation with no PM emission controls, some of the modeling analyses submitted suggest a 

potential for PM10 and PM2.5 concentrations to exceed their relevant NAAQS when background 

concentrations were included. All the modeling demonstrations were produced without certain 

knowledge of the range of PM mass emission rates that would produce 100 percent opacity. 

More definitive modeling assessments of the effect of the Alabama rule revision would include 

the specific range of PM mass emission rates and/or conditions capable of producing 100 percent 

opacity at each type of source affected by the rule. The range of mass emissions for a given level 

of opacity is unknown and appears to be facility dependent. 

Given that the rule revisions under review allow for an extended period of operation at 100

percent opacity at a number of facility types, and that the range of PM mass emissions producing 

100 percent opacity across the type of affected sources was neither known nor considered by the 

commenters, none of the modeling results provide conclusive and comprehensive estimates of 

the impacts of the rule revisions. EPA recognizes the operational difficulties in obtaining the 

pertinent input data to allow proper impact estimates. That being said, source-specific modeling 

of the possible emission scenarios under the opacity rule at issue would increase our 

understanding of the potential consequences of the rule revisions.
8

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A-1

Attachment A

Alabama Opacity 2007 ORIGINAL Proposal Notice Modeling Comparison Table from Submitted Comments

AEC and others

(John Nuckels)

(7/6/07)

TVA

(Jacobs, Cook &Wylie)

(6/0/07)

APC

(Paine and Thomson) 

(6/11/07)

ADEM Modeling

(2003 SIP submittal)

(9/11/03) Comments on the comparison

Docket ID

EPA-R04-OAR2005-AL-0002-

0010.4 0014 009.3 005.6

Source modeled TVA Plant Colbert TVA Plant Colbert APC Plant Greene Unknown All applicable but do not represent the range of 

facilities covered by the rule.

Modeled facility 

location 

Tuscumbia, AL, Colbert County Tuscumbia, AL, Colbert 

County

Demopolis, AL in Greene 

County on Black Warrior 

River

Unknown Colbert Co. is attainment for PM2.5, no PM monitors 

nearby

Area attainment 

status of plant 

modeled

Attainment for all NAAQS Attainment for all NAAQS Attainment for all NAAQS Unknown Attainment for all NAAQS

Emission control ESPs; 99.9% removal efficiency 

source from a Sierra Club /TVA 

deposition testimony (p.7); no date 

for data

Units 1-4 had ESP replaced 

in 1992

Unit 5 ESP upgrade 

scheduled Fall 2007

Unknown Source-specific modeling would have to be developed 

for each applicable source. It is not clear how a 

generically applicable scenario should be developed 

that is representative of the Alabama sources subject 

to the opacity regulation.

Mass emission limit 0.12 lb/MMBtu/hr 0.12 lb/MMBtu/hr Not indicated Not indicated

Model AERMOD AERMOD AERMOD ISCST3 Both models appropriate for this type of general 

assessment.

How nearby sources 

were accounted for 

None modeled, Nuckels assumed no 

nearby sources.

Addition of other nearby sources for 

both NAAQS and PSD would only 

make the resultant concentrations 

larger.

None modeled or addressed None modeled or addressed None Modeled Nearby sources need to be modeled for determining 

compliance with a NAAQS or PSD increment. It 

could make a difference. Use of background 

concentrations may not adequately capture these 

emissions. 

Assumptions for 

worst case opacity to 

determine emissions

Direct PM totally uncontrolled = 

100% opacity; ESP turned off 

Direct PM totally 

uncontrolled = 100% 

opacity; ESP turned off;

HOWEVER- shutting down 

ESPs would violate 

operating permit and would 

be captured by COMS data 

or Method 9.

Direct PM totally uncontrolled 

= 100% opacity; ESP turned 

off

Used 51 times NC 22 

lb/hr = 1122 lb/hr for 

NAAQS comparison

Used 10 times NC 22 

lb/hr = 220 lb/hr for PSD 

increment comparison

- TVA states shutting down controls is a major flaw in 

Nuckels’ modeling and illegal. TVA then uses the 

same assumption in their modeling.

- ADEM emissions modeled for 100% opacity are just 

a multiple of that used by NC. No basis provided.

- ADEM used a different emission rate for 100% 

opacity when comparing to NAAQS and PSD.

Receptor network Specific receptor grid not discussed;

Terrain included

Discrete Cartesian nested 

grids: 1 coarse (500-m 

resolution) & 2 fine (100-m 

4 nested discrete Cartesian 

grids

Most refined to 100-m 

Not provided Specifics of the Nuckels receptor grid are needed. 

TVA and Alabama Power receptors are acceptable.
A-2

AEC and others

(John Nuckels)

(7/6/07)

TVA

(Jacobs, Cook &Wylie)

(6/0/07)

APC

(Paine and Thomson) 

(6/11/07)

ADEM Modeling

(2003 SIP submittal)

(9/11/03) Comments on the comparison

& 250-m resolution) resolution

Stack heights/ 

diameter

Actual: Unit 5 - 500 ft/152.4 m; 21 

ft/6.4 m

Units 1-4 - 634 ft/193.2 m; 26 

ft/7.92 m

Actual: Unit 5 - 459 

ft/139.9 m; 23.6 ft/7.2 m; 

GEP = 363.8 ft/110.9 m

Units 1-4 - 457ft/139.3 m; 

26.3ft/8.0m;

GEP heights = 110.9 m

used in the modeling

GEP height modeled = 137.8 

m

Single stack for units 1 and 2

Assumed 3 stack facility 

Stack 1 = 76.2 m/ 3.96 m

Stack 2 and 3 = 121.6 m/ 

5.03 m 

Modeling actual heights would be a prohibited

dispersion technique and would provide more 

dispersion than would be allowed. Use of GEP 

heights in Nuckels would increase impacts.

Stack heights data 

source

DOE/Energy Information Admin. 

Database

Facility data used Facility data used NA

Exit velocity (m/s) 

and temperature (K)

Not provided Unit 1-4 - 27.7 m/s; 425 K

Unit 5 - 23.1 m/s; 417 K

22.55 m/s and 413.6 K Assumed

Stack 1 – 10.72 m/s; 

394.26 K

Stack 2 and 3 – 21.14 

m/s; 394.26 K

This information is important for review, and it affects

the final rise of the plume and hence impacts at the 

receptors. Nuckels did not address this data but 

should have.

Stack test data used 2002 stack test used to provide 

following data used in determining 

the worst-case emissions:

- heat required for full load

- lb/hr and lb/MMBtu

- flow rate ft3/min

Controlled: 2001-2006 

Uncontrolled: 2005 ADEM 

emission inventory 

Method 17 stack test from 

2006

NA Unclear if equipment performance, process 

equipment, or emissions remain unchanged over six 

years (2001 to 2006).

How was primary 

PM2.5 modeled

With and w/o condensable 

particulate matter (CPM).

Emission factors for CPM (taken 

from EPA AP42, Table 1.1-5) used 

percent ash of coal burned as a 

multiplier to determine the emission 

factor. Coal sulfur percentage taken 

from DOE/EIA Form 767 Database.

No condensables modeled Direct emissions only Direct emissions - The impact of modeling condensables for primary 

PM2.5 is important. 

- No analysis addressed secondary PM2.5. 

- Nuckels has incorrect multiplier in Table 6 for 

controlled PM2.5 fraction (0.67 instead of 0.29). 

Unknown how this impacts remaining assumptions, 

but could cause an answer to be 2.3 times too large. 

Meteorological data 1988-1992 from ADEM; Tupelo 

(sfc), Centreville (upper)

1988-1992 from ADEM; 

Tupelo (sfc), Centreville 

(upper)

1988-1992 from ADEM; 

Tupelo (sfc), Centreville 

(upper)

1988-92 

Montgomery(sfc); 

Centerville (upper)

Only ADEM used different met data.

Background PM 

monitoring data 

- 24-hr PM10 of 35 ug/m3 from 

Colbert Co. provided by ADEM = 

35 ug/m3

- 2004-2006 PM2.5 data obtained 

from EPA Air Data for Colbert Co. 

Muscle Shoals site (#010331002); 3 

year 98 percentile avgs =30.7 

None used for PM10 or 

PM2.5

None used NAAQS PM10 = 43

ug/m3

PSD PM10 = None

PM2.5 not modeled

- Nuckels use of background data is consistent with 

Appendix W modeling requirements.

- TVA and Alabama Power should have used 

background concentration.

- ADEM modeling did not address PM2.5. Used 

higher background for PM10.
A-3

AEC and others

(John Nuckels)

(7/6/07)

TVA

(Jacobs, Cook &Wylie)

(6/0/07)

APC

(Paine and Thomson) 

(6/11/07)

ADEM Modeling

(2003 SIP submittal)

(9/11/03) Comments on the comparison

ug/m3 [correct value is 30 ug/m3]

Scenarios modeled 1. 24 hr average period where 

emissions are uncontrolled for 2.4 

hrs.

2. 24 hr average period with 

uncontrolled emissions for 4.8 hr 

and emissions occur on a 

consecutive 2-day period

Modeled both w & w/o CPM

1. Controlled 24 hr /day

2. Controlled for 90% of 

day (21.6 hr/day) & 

uncontrolled 10% of day 

(2.4 hr/day)

- uncontrolled 24 hr avg PM10 

and PM2.5 

- 24 hr PM10 increment 

calculated by diff in emissions 

between controlled and 

uncontrolled cases by scaling 

NAAQS modeling results 

24-hr with emission rates 

equal to uncontrolled 

plus allowable.

[Did not do 10% 

uncontrolled plus 90% 

allowable.]

- Nuckels #2 scenario (4.8 hr) is not applicable and 

should not be used.

- ADEM appears to model total of uncontrolled plus 

allowable emissions for all periods.

Method to calculate 

PM10/PM2.5 

emission rates

Calculated from stack test and:

- coal characteristics

- max hourly heat per unit

- max coal burned per hour 

- Babcock and Wilcox information 

on % fly ash, CPM %, and 

PM10/PM2.5 distribution

- Uncontrolled:

Combustion coal with 

highest ash content; no 

ESP = 6.82 lb/MMBtu

- Controlled: Based on 

averages of all emission 

tests: Unit 1-4 ranges = 

0.007-0.025 lb/MMBtu & 

Unit 5 avg = 0.054 

lb/MMBtu

- AP-42 for distribution

 Controlled 67% PM10; 

29% PM2.5

 Uncontrolled 23% PM10; 

6% PM2.5

- Total ash content coal 

through stack

- Controlled emissions based 

on 2006 stack test (Unit 1 = 

0.014 lb/MMBtu; Unit 2 = 

0.020 lb/MMBtu)

- Max heating values 2,500 

MMBtu/hr/unit

- AP-42 for distribution

 Controlled 67% PM10; 29% 

PM2.5

 Uncontrolled 23% PM10; 

6% PM2.5

NA

PM10 emission rates 

modeled

- Uncontrolled emissions:

Unit 1 – 14,718.05 lb/hr

Unit 2 – 14,142.16 lb/hr

Unit 3 – 14,160.56 lb/hr

Unit 4 – 13,113.22 lb/hr

Unit 5 – 35,563.86 lb/hr

- Uncontrolled: 

Units 1-4 = 3,327 lb/hr

Unit 5 = 8,701 lb/hr

- Controlled: 

Units 1-4 = 88.11 lb/hr

Unit 5 = 200.69 lb/hr

PM10 Max short-term contr. 

=56.95 lb/hr

PM10 Max hourly uncontr. 

=15,783.0 lb/hr

Modeled 24-hr average hourly 

rate (10% uncontr + 90% 

contr)

PM10 uncontr. =1,629.59 

lb/hr

Stack 1 = 1205.9 lb/hr

Stacks 2 and 3 = 1362.8 

lb/hr

- NC modeling performed in support of changes in 

opacity rule used 11 lb/hr to represent 100% opacity 

conditions.

- AL followed NC procedure in their modeling. AL 

used 51 times NC emissions to represent 100% 

opacity for comparison with the NAAQS and 10 times 

for comparison with PSD increment. 

- Bases for these emission rates were not provided.

PM2.5 emission 

rates modeled

Not provided.

Used AP-42 percent (6%) of total 

PM mass emissions for each unit.

- Uncontrolled: 

Units 1-4 = 868 lb/hr

Unit 5 = 2,270 lb/hr 

- Controlled: 

PM2.5 Max short-term contr. 

=24.65 lb/hr

PM2.5 Max hourly uncontr. 

4,117.39 lb/hr

Modeled 24-hr average hourly 

PM2.5 not modeled - Nuckels appears to have modeled largest emissions.

- All emissions modeled are within factor of 10.

- All modeled emissions could represent 100% opacity 

conditions.
A-4

AEC and others

(John Nuckels)

(7/6/07)

TVA

(Jacobs, Cook &Wylie)

(6/0/07)

APC

(Paine and Thomson) 

(6/11/07)

ADEM Modeling

(2003 SIP submittal)

(9/11/03) Comments on the comparison

Units 1-4 = 38.14 lb/hr

Unit 5 = 86.87 lb/hr

rate (10% uncontr + 90% 

contr)

PM2.5 uncontr = 434.82 lb/hr

Modeling files See their Exhibit 2 for actual input 

and output files (Not available for 

review)

Not reviewed

24 hr PM10 

modeling results 

(ug/m3) by scenario 

modeled w/o CPM

1. Background (35)+ max modeled

(11.275)1990; less than NAAQS w/o 

other nearby sources 

2. Background (35)+ max modeled

(19.880)1990; less than NAAQS w/o 

other nearby sources

[1 = 2.4 hr/day scenario; 2 = 4.8 

hr/day scenario at 100% opacity].

Max 24-hr concentrations 

used and most conservative 

[Can use for HSH.] 

1. Controlled: 2.7 

2. Controlled & 

uncontrolled: 21.9 

TVA concludes EPA 

NAAQS & PSD increment 

and ADEM’ increment 

protected. However, 

background should be 

added for NAAQS analysis.

No nearby sources included.

Used 24-hr 2nd highest 

modeled concentrations

The highest over 5 year was 

12.06. This value and all other 

years were concluded to be 

<NAAQS and PSD increment

Note: No background values 

added. No other nearby 

sources included.

NAAQS:

Max (?) modeled 104.99 

plus background of 43 = 

147.99

Just less than 150 

NAAQS

PSD Increment:

Max (?) modeled 28.03 

with no background 

equals 28.03

Just less than PSD 

increment of 30

No nearby sources 

included.

- Although adding background concentration for PSD 

assessment is not appropriate, Nuckels has done this 

and reports values greater than PSD increment. 

[Use of NAAQS background for PSD increment is 

questionable. Need to model other PSD sources.]

24 hr PM2.5 

modeling results 

(ug/m3) by scenario 

modeled using 

(w/o CPM then with 

CPM; same 

scenarios as PM10)

1. Background (30.7)+ max 

modeled (2.973)1990; less than 

NAAQS w/o CPM.

2. Background (30.7)+ max 

modeled (5.203)1990; exceeds 

NAAQS w/o CPM.

1. Background (30.7)+ max 

modeled (15.1)1990; with CPM; 

exceeds NAAQS with CPM.

2. Background (30.7)+ max 

modeled (26.6)1990; CPM exceeds 

NAAQS with CPM.

[1 = 2.4 hr/day scenario; 2 = 4.8 

hr/day scenario at 100% opacity; 

No PM2.5 PSD increment]

Max 24-hr concentrations 

used and most conservative 

[PM2.5 could use 98th

percentile (i.e., 8th highest)]. 

1. Controlled: 1.2 

2. Controlled & 

uncontrolled: 5.8 

TVA concludes no NAAQS 

violations. However, if 

background used, then 

NAAQS violated for 

scenario 2.

Used 24-hr 8th highest 

modeled concentrations

The highest over 5 year was 

2.41. This value and all other 

years were concluded to be 

<NAAQS

Note: No background values 

added. No other nearby 

sources included.

Not Modeled - The use of the max modeled concentration is 

overly conservative.

- EPA has not determined or recommended how the 

PM2.5 NAAQS could be assessed with only a 

Gaussian model.

- Only Nuckels included condensable PM2.5 

emissions.

- Both the Nuckels and TVA modeled values plus 

background show values greater than NAAQS.
A-5

AEC and others

(John Nuckels)

(7/6/07)

TVA

(Jacobs, Cook &Wylie)

(6/0/07)

APC

(Paine and Thomson) 

(6/11/07)

ADEM Modeling

(2003 SIP submittal)

(9/11/03) Comments on the comparison

Annual NAAQS 

results

Not modeled 1. Controlled: PM10 

=0.29; PM2.5=0.12

2. Controlled & 

uncontrolled: PM10 =1.01; 

PM2.5=0.30

No background added

Not modeled Not modeled

Comments on 

modeling other 

sources subject to 

rule

Source specific modeling for each 

source recommended

Not addressed Not addressed Not addressed

Data/input/output 

files submitted

None None None None

Assessment of 

modeling

1. Methodology for development 

of worst-case PM emissions 

reasonable.

2. Operation without control 

equipment not likely a scenario.

3. Operation 100% opacity in 24 

hrs is applicable. Compliance 

based on calendar day where 2.4 

hrs is max.

4. Even using max possible 

emission rate for the 100% 

opacity condition, modeling 

results for applicable scenario 

show about 10 ug/m3 over 

NAAQS standard.

5. Given the range in emission 

rates that could produce 100% 

opacity, those associated with 

more likely scenario would 

appear to produce concentration 

less than standards. 

6. No nearby sources considered.

1. Very similar to Nuckels 

modeling. Used GEP 

stack heights (lower) by 

about 42 m; 

Uncontrolled PM10 

emission rates factor of 

4 lower; Uncontrolled 

PM2.5 emission rates 

factor of 3-8 lower

2. Modeled max 

concentrations are larger 

than Nuckels. Appears 

to be due to lower stack 

height.

3. No background 

concentration nor 

nearby sources 

considered.

1. ENSR performed 2 

modeling exercises; one 

duplicating ADEM’s ISC 

modeling. The AERMOD 

results showed lower air 

quality impacts than 

ADEM’s ISC modeling.

2. Other units at this plant 

fired natural gas or fuel oil. 

They were not modeled. 

3. Only 2 units modeled with 

unit emissions comparable 

to Nuckels. May not be 

representative of affected 

source that would produce 

controlling results.

4. PSD PM10 modeling 

procedure appears to be 

inappropriate. Needs

explanation.

1. Did not model the 

10% uncontrolled and 

90% controlled for 

24-hr period. 

Modeled the sum of 

uncontrolled plus 

allowable for each 

hour. Results cannot

be compared to other 

modeling.

2. Appears to have used 

different emission 

rates for 100% 

opacity for NAAQS 

and PSD in order to 

show compliance.

1. Nuckels attempted to follow EPA guidance in 

developing his modeling. Modeled actual stack 

heights rather than GEP. Condensables were not 

modeled. 

2. Both the Nuckels and TVA modeled values plus 

background show values greater than NAAQS.

Issues Raised/Identified in Modeling
A-6

Source-specific modeling for PM2.5 1. Commenting on the accuracy of source-specific modeling for NAAQS compliance for PM2.5 is precedent setting. Needs the input 

from Model Clearinghouse and other regions.

2. Compliance for these NAAQS is determined based on consideration of primary and secondary species. 

3. EPA has not determined or recommended how the PM2.5 NAAQS could be assessed with only a Gaussian model.

[Note: Modeling Procedures for Demonstrating Compliance with PM2.5 NAAQS PM2.5 (Stephen Page memorandum of March 23,

2010) provides modeling guidance that was not available for these modeling assessments.] 

General Comments 1. Modeling provided for the AL Opacity rule change is only to provide estimate of the range of expected results. It is not guidance 

for PM2.5 source-specific modeling.

2. The overall salient failing of any ambient impact modeling associated with opacity measurements is lack of specific relationship 

between opacity measurements and mass emission rates. For example, review of some source specific actual measurements of 

mass emission rates for opacities less than 15% reveals variations of about an order of magnitude in emission rate for a measured 

opacity. It is also expected that 100% opacity would be represented by mass emission rates that range over orders of magnitude. 

The range in emission rates used to represent 100% opacity in the 4 modeling exercises further support this basic problem with any 

modeling.

3. ADEM performed ISC modeling following the methodology used by NC. ADEM used mass emission rate 51 times that of NC for 

NAAQS assessment and 10 times NC for PSD increment assessment. Appears to have modeled the sum of the 100% opacity rate 

plus allowable rate for all hours; not 10% of daily hours. [Note: Neither NC nor ADEM demonstrated the emission rate used was

representative of 100% opacity.]

4. The Nuckels and TVA modeling are the most comparable. Although the emission rates used were a factor of 4-8 different and 

TVA’s stack heights were smaller, the results of both these modeling assessments show potential PM10 concentrations greater 

than PSD increment, not NAAQS. They also show concentrations exceeding the PM2.5 NAAQS when background concentration 

is included.

5. Nuckels and TVA modeled Colbert Plant, which is in an attainment area in northwestern Alabama. AL Power modeled Plant 

Greene, which is in an attainment area in western Alabama. ADEM modeled a “representative source.” None of the modeling 

studies either attempts to address the range of sources affected by the rule change or indicates the modeled source represents the 

worst-case affected source.
B-1

Attachment B

Alabama Opacity 2009 RECONSIDERATION Proposal Notice Modeling Comparison Table from Submitted Comments

AEC and others 

(Khanh T. Tran)

(July 2008)

TVA’s 

Comments on 

Tran Analysis

(Mueller)

(10/27/08)

TVA’s Analysis –

Plant Colbert 

(Mueller)

(10/27/08) 

APC’s Recap of 

2003 ADEM 

Modeling

(Paine)

(12/16/09)

APC’s Recap of Own 

Modeling

(Paine)

(12/16/09)

APC’s New Analysis –

Plant Barry

(Paine)

(12/16/09)

Docket ID

EPA-R04-OAR-2005-

AL-0002

0054.14 0088.1 0084.1

Source modeled TVA Plant Colbert TVA Plant Colbert Nothing new is added in 

this discussion, which 

simply summarizes 

previous modeling of 

APC Plant Greene. 

Restates conclusion that 

the results of the modeling 

scenarios indicated that 

even if the PM emissions 

from both units were 

uncontrolled for up to 

10% of a given day, the 

predicted PM10 and 

PM2.5 concentrations 

would be less than 10% of 

the daily NAAQS values 

in both cases.

Uncontrolled combined 

Unit 1 and Unit 2 24-hour 

average PM10 emission 

rate of 1,639.56 lb/hr and 

PM2.5 emission rate of 

433.92 lb/hr.

Maximum 24-hour PM10 

H2H of 12.04.

Maximum 24-hour PM2.5 

98th percentile of 2.4. All 

less than NAAQS without 

background values.

APC Plant Barry

Modeled facility 

location 

Tuscumbia, AL, Colbert 

County

Tuscumbia, AL, 

Colbert County

On Mobile River near Bucks, 

AL

Area attainment status 

of plant modeled

Attainment for all NAAQS Attainment for all 

NAAQS

Attainment for all NAAQS

Emission control Units 1-4 have ESP 

replaced in 1992

Unit 5 ESP refurbished in 

2007

Units 1-4 have ESP 

replaced in 1992

Unit 5 ESP 

refurbished in 2007

ESPs on all 5 units

Mass emission limit 0.12 lb/MMBtu/hr 0.12 lb/MMBtu/hr 0.12 lb/MMBtu/hr

Model AERMOD, apparently (lists 

AERMOD user guides)

AERMOD In 2005, EPA replaced 

ISCST3 with 

AERMOD as the 

preferred short-range 

dispersion model. The 

AERMOD results 

were almost always 

less than the ISCST3 

results and the overall 

peak AERMOD 

predictions over the 5 

years modeled were 

lower than the peak 

ISCST3 predictions. 

AERMOD

Nearby sources 

modeled

None modeled or addressed

Assumed no nearby sources

None modeled or 

addressed

None modeled or addressed

Assumptions for worst 

case opacity to 

determine emissions

Direct PM totally 

uncontrolled = 100% 

opacity; ESP turned off

Assumption that 

ESPs will be shut 

down when the units 

are exempt from the 

Primary PM totally 

uncontrolled = 100% 

opacity; 

However - shutting 

Primary PM totally uncontrolled 

= 100% opacity (all ESPs totally 

failed - an event that is nearly 

impossible).
B

-2

20% opacity 

requirement is 

unrealistic.

down ESPs would 

violate operating 

permit and would be 

captured by COMS

data or Method 9.

Receptor network Specific receptor grid not 

discussed;

Terrain included

Discrete Cartesian 

nested grids: 1 coarse 

(500-m resolution to 

20 km) & 2 fine (100-

m to 2.5 km & 250-m 

resolution to 5 km)

Discrete Cartesian receptor 

network

defined as four tiered rectangular 

grids for a total of 2,443 

receptors. 1

st grid: a rectangle of receptors 

spaced 100 m apart starting from 

the source and

extending out 2.0 km; 2nd grid: 

receptors spaced 500 m apart

extending 5 km from the source; 3

rd grid: receptors spaced 1,000 

m apart extending 10 km from 

the source; 4

th grid extends from the source 

out to 20 km with receptors 

spaced 2,000 m apart.

Stack heights/ 

diameter

Actual:

Unit 5 – 500 ft/152.4 m; 21 

ft/6.4 m

Units 1-4 – 634 ft/193.2 m; 

26 ft/7.92m

Actual:

Unit 5 –

500 ft/152.4 m; 23.6 

ft/7.2 m

Units 1-4 –602.0

ft/183.5 m; 26.3 ft/8.0 m

GEP heights were not 

used in the modeling

Actual:

Units 1, 2 and 3 ducted to a 

merged stack at 182.9 m high. 

Units 4 and 5 have individual 

stacks with fully creditable 

heights of 182.9 m.

Modeled:

GEP Stack Heights -

Units 1, 2, & 3: 153.9 m;

Units 4 & 5: 182.9 m

Stack heights data 

source

Department of Energy, 

Energy Information 

Administration

(DOE EIA) Form 767 

database

NA NA

Exit velocity (m/s) and 

temperature (K)

Not addressed Unit 1-4 - 27.7 m/s; 

425 K

Unit 5 - 23.1 m/s; 

418 K

Units 1, 2, & 3: 20.0 m/s; 422 K

Unit 4: 23.4 m/s; 400 K

Unit 5: 20.4 m/s; 422 K

Stack test data used 2002 stack test data Uses stack data from Controlled Stack test data not used. 
B-3

stack tests 2002, 

which is before a fuel 

switch at the plant 

and significant repair 

work on the 

precipitator on Unit 

5. More recent stack 

tests show 

significantly lower 

PM emission rates, 

which are more 

representative of 

current emissions.

Units 1-4: average all 

test 2006-2008

Unit 5: only 2008 

(after refur.)

Uncontrolled

Units 1-4 and Unit 5: 

coal combustion 2007 

w/o ESP

For 21.6 hours of normal 

operation, assumed emitting at 

the permitted limit of 0.12 

lb/MMBtu.

For 2.4 hours of 100% opacity, 

assumed total ash content in the 

coal fired was discharged to the 

atmosphere. Uncontrolled 

emission

estimates were based upon the 

ash content and heating value of 

the coal fired. (“It is important 

to note that these very 

conservative emissions

were assumed to occur for every 

day in the modeling analysis.”)

How was primary 

PM2.5 modeled

With and w/o condensable 

particulate matter (CPM).

Emission factors for CPM 

(taken from EPA AP42, 

Table 1.1-6) used percent 

ash in coal burned as a 

multiplier to determine the 

emission factor. Coal ash 

and heat content taken from 

DOE/EIA Form 767 

Database.

Modeling uses 

condensable

particulate matter 

(CPM), which is not

affected by ESP 

controls since it 

remains in vapor 

phase at ESP flue-gas

temperatures. 

Further, the 

methodology for 

measuring PM

emissions under the 

SIP expressly 

excludes CPM.

Meteorological data 1988-1992 from ADEM; 

Tupelo (sfc), Centreville 

(upper)

2001-2005 from 

Huntsville (sfc); 

Nashville (upper)

ADEM provided 

ENSR with its 

approved 

meteorological data.

Five years (2001-2005) of 

representative National Weather 

Service (NWS) meteorological 

data were used. The AERMET 

pre-processed, hourly 

meteorological data were 

obtained from ADEM. Surface 

data was from Mobile, AL, and 

upper air data was from Slidell, 

LA. Due to differences between 
B

-4

the surface characteristics at the

Mobile airport and the Plant 

Barry site, conservatively 

modeled a total of 10 years, 

using 5 years each with surface 

characteristics at the airport and 

the plant site, respectively.

Background PM 

monitoring data 

(Same as Nuckels 2007) - 24-hr PM10 of 35 ug/m3 

from Colbert Co. provided 

by ADEM = 35 ug/m3 - 2004-2006 PM2.5 data 

obtained from EPA Air 

Data for Colbert Co. 

Muscle Shoals site 

(#010331002); 3 year 98 

percentile avgs =30.7 

ug/m3[correct value is 30 

ug/m3]

PM10 = 35 ug/m3

PM2.5 = 30 ug/m3

PM10 = 51.0 ug/m3

PM2.5 = 23.9 ug/m3 

Taken from a nearby 

representative monitor at 

Chickasaw, AL.

Scenarios modeled 1. 24 hr average period 

where emissions are 

uncontrolled for 2.4 hrs.

2. 24 hr average period 

with uncontrolled emissions 

for 4.8 hr and emissions 

occur on a consecutive 2-

day period

Modeled both w & w/o 

CPM

Assumption that 4.8 

hours of uncontrolled 

emissions could 

occur in a 24-hour 

period if 2.4 hours 

were uncontrolled over two consecutive 

days is flawed 

because the 24-hour 

PM2.5 NAAQS is 

measured under

EPA’s rules on a 24-

hour calendar day 

basis.

1. Controlled 24 hr 

/day

2. Controlled for 

90% of day (21.6 

hr/day) & 

uncontrolled 10% of 

day (first 2.4 hr of 

each day)

Controlled for 90% of day (21.6 

hr/day) & uncontrolled 10% of 

day.

Method to calculate 

PM10/PM2.5 emission 

rates

Calculated from stack test 

and: - coal characteristics - max hourly heat per unit - max coal burned per hour - Information on coal heat 

content and coal ash content

from 2004 DOE EIA Form 

767 - Information on % fly from 

Normal operation:

For 21.6 hours, assumed 

emitting at the permitted limit of 

0.12 lb/MMBtu.

100% opacity operation:

For 2.4 hours, assumed total ash 

content in the coal fired was 

discharged to the atmosphere. 

Uncontrolled emission estimates 
B

-5

ash Babcock and Wilcox - Information on CPM % 

and PM10/PM2.5 

distribution from AP42

were based upon the ash content 

and heating value of the coal 

fired. (“It is important to note 

that these very conservative 

emissions were assumed to occur 

for every day in the modeling 

analysis.”)

The particle size distributions 

assumed for PM2.5 and PM10 

emission rates were based on the 

default values cited in the U.S. 

EPA’s AP-42 Document, 

Section 1.1, Table 1.1-6.

PM10 emission rates 

modeled

- Uncontrolled emissions:

Unit 1 – 14,718.05 lb/hr

Unit 2 – 14,142.16 lb/hr

Unit 3 – 14,160.56 lb/hr

Unit 4 – 13,113.22 lb/hr

Unit 5 – 35,563.86 lb/hr

(Same as Nuckels 2007)

Uncontrolled: 

Units 1-4 = 17,932 

lb/hr (w cond 17,976 

lb/hr)

Unit 5 = 11,527 lb/hr 

(w cond. 11,762)

Controlled: 

Units 1-4 = 71.21 

lb/hr (w cond. 109.1 

lb/hr)

Unit 5 = 40.88 lb/hr 

(w cond. 101.1 lb/hr)

ADEM started with the 

emissions used for the 

North Carolina 

demonstration, but 

made modeling 

assumptions that were 

more conservative than 

North Carolina’s. 

While North

Carolina allows for 

opacity excursions for 

1/60th of a day and 

Alabama allows for

opacity excursions 

1/10th of a day, 

ADEM used 

incremental PM10 

emissions in their

NAAQS modeling that 

were 51 times that 

used by North 

Carolina. Therefore, 

ADEM created an 

analysis that was more 

conservative than 

North Carolina’s and 

showed compliance 

with the PM10 

NAAQS.

24-Hour Average: 

Units 1, 2, & 3: 1,134 lb/hr

Unit 4: 764 lb/hr

Unit 5: 1,517 lb/hr
B

-6

PM2.5 emission rates 

modeled

Not provided.

Used AP-42 percent (6%) 

of total PM mass emissions 

for each unit.

Uncontrolled: 

Units 1-4 = 4,676 

lb/hr (w cond 4,724 

lb/hr)

Unit 5 = 3,007 lb/hr 

(w cond. 3,242)

Controlled: 

Units 1-4 = 30.82 

lb/hr (w cond. 68.6 

lb/hr)

Unit 5 = 17.69 lb/hr 

(w cond. 77.9 lb/hr)

24-Hour Average: 

Units 1, 2, & 3: 361 lb/hr

Unit 4: 243 lb/hr

Unit 5: 484 lb/hr

Modeling files Not available for review

. NA ADEM supplied 

ENSR with the 

ISCST3 modeling files 

that it used in its 

modeling of the excess 

PM emissions 

associated with the 

opacity excursions.

ENSR applied 

standard terrain and 

receptor processing

procedures along with 

meteorological 

processing procedures 

to prepare the

appropriate files for 

running AERMOD.

NA

24 hr PM10 modeling 

results (ug/m3) by 

scenario modeled w/o 

CPM

1. Background (35)+ max 

modeled(11.275)1990; less 

than NAAQS w/o other 

nearby sources 

2. Background (35)+ max 

modeled(19.880)1990; less 

than NAAQS w/o other 

nearby sources

[1 = 2.4 hr/day scenario; 2 = 

4.8 hr/day scenario at 100% 

opacity].

Modeled concentrations 

HSH 24-hr modeled 

concentrations used 

W/O cond

1. Controlled: 0.39

2. Controlled &

uncontrolled: 9.69 W cond

1. Controlled: 0.78

2 Controlled & uncontrolled: 9.94

AERMOD maximum 

PM10 modeled results 

(84.23) plus previous 

background of 42 = 

126.23

Less than 150 NAAQS

Modeled Concentration: 46.8

Ambient Background

Concentration: 51.0

Total Impact: 97.8

Less than 150 NAAQS

The modeled concentrations 

represent the highest of the sixth 

highest concentrations over a 5-

year meteorological period.
B

-7

(w/o other PSD emission 

sources) less than PSD 

increment

With background 

concentration of 35, 

all results are less 

than NAAQS of 150.

24 hr PM2.5 modeling 

results (ug/m3) by 

scenario modeled using 

w/o CPM then with 

CPM; same scenarios 

as PM10)

1. Background (30.7)+ max 

modeled(2.973)1990; less 

than NAAQS w/o CPM. 2. Background (30.7)+ max 

modeled (5.203)1990; 

exceeds NAAQS w/o CPM. 1. Background (30.7)+ max 

modeled(15.1)1990; with 

CPM; exceeds NAAQS 

with CPM.

2. Background (30.7)+ max 

modeled(26.6)1990; CPM 

exceeds NAAQS with 

CPM.

[1 = 2.4 hr/day scenario; 2 = 

4.8 hr/day scenario at 100% 

opacity; 

Also provided modeling in 

the form of the NAAQS 

(average annual 98th

percentile over 5 yrs) 1. Background (30.7)+ 98th

% modeled (0.653); less 

than NAAQS w/o CPM.

2. Background (30.7)+ 98th % modeled (0.976);less 

than NAAQS w/o CPM. 1. Background (30.7)+ 98th % modeled (3.265);less 

than NAAQS with CPM.

2. Background (30.7)+ 98th % modeled (4.966); exceeds 

NAAQS with CPM.

Does not follow 

EPA’s protocol in 

calculating and 

rounding the 3-year 

average 24-hour 

PM2.5 monitoring 

data. The 3-Year 

Average 98th 

Percentile 24-Hour 

Average in Table 7 of 

his report should be 

30 rather than 30.7. 

The three-year 

average of the yearly 8th-highest 24-hour 

PM2.5 predictions at 

each receptor should 

be added to the 

background and 

compared to the 

NAAQS.

PM2.5 use 98th

percentile (i.e., 8th

highest) 

W/O cond

1. Controlled: 0.12

2. Controlled & 

uncontrolled: 0.41 W cond

1. Controlled: 0.39 2. Controlled & 

Uncontrolled: 0.47

With background 

concentration of 30, 

all results are less 

than NAAQS of 35.

Modeled Concentration: 7.7

Ambient Background

Concentration: 23.9

Total Impact: 31.6

Less than 35 NAAQS

The modeled concentration 

represents the highest of the 

eighth highest concentration 

over rolling three-year 

meteorological periods.
B-8

Annual NAAQS 

results

Not modeled Modeled

- No PM10 NAAS

- PM2.5 less than 

NAAQS of 15

Comments on 

modeling other sources 

subject to rule

None

Data/input/output files 

submitted

None None

Assessment of 

modeling

1. One difference noted in 

the Tran analysis from 

the 2007 Nuckels 

analysis is that Tran 

noted the PM2.5 PSD 

Class II increment was 

proposed in September 

2007 by EPA to be 

9μg/m3and compared 

that increment with the 

24-hour average 

modeled PM2.5 

concentrations from the 

Colbert Plant. The 

Nuckels analysis noted 

that none had yet been 

established. On October 

20, 2010, EPA finalized 

the PM2.5 PSD Class II 

increment to be 9 μg/m3

with an effective date of 

December 20, 2010. 75 

FR 64864

2. Tran also calculated the 

modeled PM2.5 

concentrations in the 

form of the 24-hr 

NAAQS (average of the 

98th percentile over 5 

modeled years).

NA. This is 

Mueller’s discussion 

of Tran’s analysis.

1. Modeled the first 

2.4 hours of each 

day with 

uncontrolled 

emissions. 

Unrealistic; 

exceedances could 

occur any time in 

day.

2. Unexpected very 

small ambient 

impacts. 

Expected impact 

similar to 

Nuckels.

1. This is APC’s 

recap of the 2003 

ADEM modeling 

submittal.

2. Nothing new about 

APC’s assessment 

except used 

AERMOD rather 

than ISCST3. See 

Attachment A.

3. AERMOD 

modeling results 

are less than 

ISCST3.

NA. This is APC’s recap 

of their own previous 

modeling on Plant Greene.

1. New NAAQS compliance 

assessment for another plant 

– Plant Berry. 

2. Condensable PM emissions 

not included in assessment.

3. Emissions at 100% opacity 

assumed to be total ash 

content in the coal burned – a 

conservative assumption that 

was used for 10% of the daily 

hours for each day modeled.

4. Total of the maximum PM10 

and PM2.5 modeled 

concentrations, in the form of 

the standard plus background 

concentrations, were less than 

the applicable NAAQS.
B-9

Issues Raised/Identified in Modeling

Source-specific modeling for PM2.5 1. Modeling Procedures for Demonstrating Compliance with PM2.5 NAAQS (Stephen Page memorandum of 23 March 2010) provides 

modeling guidance that was not used in the 2007 Original Proposal modeling or in this 2009 Reconsideration modeling. This recent 

guidance was not available for the provided modeling assessments, so the modeling information provided by commenters is suspect, 

even if previous versions of / instructions for using AERMOD were followed. Were we to conduct modeling, we would use the 

current version of AERMOD coupled with the most recent guidance.

General Comments 1. The modeling provided for the reconsideration of the AL Opacity rule changes only to provides estimates of the range of expected 

results given assumed emission scenarios associated with the proposed allowed 10 percent unlimited opacity. The range of 

emissions rates developed for the various modeling analysis reflects possible scenarios and resultant impacts. 

2. The overall salient failing of the ambient impact modeling associated with opacity measurements is lack of a specific relationship 

between opacity measurements and mass emissions rates. For example, review of some source specific actual measurements of mass 

emissions rates for opacities less than 15% reveals variations of about an order of magnitude in emission rate for a measured opacity. 

It is also expected that 100% opacity would be represented by mass emissions rates that range over orders of magnitude. The range 

in emissions rates used to represent 100% opacity in the above modeling exercises further support this basic problem with any

modeling.

3. The initial ADEM performed ISC modeling and the above Paine recap of this modeling using AERMOD followed the methodology 

used by NC. ADEM used a mass emissions rate 51 times that of NC for NAAQS assessment and 10 times NC for PSD increment 

assessment. Appears to have developed a combined Unit 1 and Unit 2 emission rate for NAAQS compliance modeling that 24-hour 

average hourly emission rate that was based on 100% opacity emissions for 10 percent of the time and allowable emissions for 80 

percent of the daily hours. This 24-hour average hourly emissions rate was used for all five years of meteorological data. [Note: 

Neither NC nor ADEM demonstrated the emissions rate used was representative of 100% opacity.]

4. These additional reconsideration modeling analyses just add additional examples of possible operating scenarios that could occur 

under the proposed opacity rule. Although the reconsideration modeling analyses provided additional results demonstrating PM10

and PM2.5 NAAQS compliance when operating with the proposed rule allowed daily 10% unlimited opacity, the full range of 

possible emission rates and range of affected sources have not been assessed.

5. The 2007 Nuckels and TVA modeling provided to EPA represent another possible operating scenario under the proposed rule. 

Although the TVA’s emission rates were a factor of 4-8 less and TVA’s stack heights were smaller than those used in the Nickels 

analysis, the results of both these modeling assessments show potential PM10 concentrations greater than PSD increment, not 

NAAQS, when background concentrations are included. They also show concentrations exceeding the PM2.5 NAAQS when 

background concentration is included. Although these results may be unlikely or rare, they have not been refuted. 

6. As with the 2007 Original Proposal, the reconsideration analyses modeled other representative sources and representative emission 

rates that reflect the allowed 10 percent unlimited opacity. These modeling studies add addition examples of compliance operation 

under the proposed opacity rule. They do not address the total range of sources affected by the rule change and are not indicated to 

represent the combined worst-case affected source/emissions.