## 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

Mo deling 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 mode ling received by EPA and to provide the Agency’s view of those submittals.

Plume opacity is the d egree 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 up on many factors, including fuels combusted, industry type, boiler type, PM particl e composition and size, controls used to reduce pollutants, etc. Given these variables, development of a specific correlation between p lume 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
modeli ng 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 S ubmitted Regarding this SIP Revision

In the 2008 rule revision approval notice, EPA not ed several uncertainties or weaknesses in the modeling submitted during the comment period on the April 12, 2007, proposal, and we conti nue 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 tu rned 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 in clude impacts of nearby emission sources in the modeling;
6. The inability of the models used to address secondary formation of PM 2.5 

## ; 7. The failure to consider condensable PM emissions; and
8. The lack of information on the range of sources affected by the opacit y 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 1 00 percent

. Moreover, no data w ere supplied by commenters to demonstrate either that 100 percent opacity means control devices
have been de

- energiz ed (i.e., turn ed off) or that de

- energiz ing PM control device s 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 th at 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 efficie ntly than larg er sizes, meaning that equal mass rates of PM 1.0 

## emissions produce greater opacities than PM 10 

## 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

r egarding 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
increm ents 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 the se other sources of emissions in the modeling analysis renders the analysis incomplete. T o 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 oth er 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 PM 2.5 

## , and none of the analyses consider ed formation of secondary PM 2.5 

## . The models used to estimate the impacts cannot address secondary particle formation, so this mechanism was not included in the modeling. Because n o commenter has provided such cumulative PM impact assessment from all emission sources in an area, the mo deling 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 believe d 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 wor ds, 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 anal yses 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 b ased 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.

I I

. 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) stac k 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 C olbert

1. The assessment is very similar to AEC analysis except that PM mass emission rates
modeled are 3 to 8 times smaller

.

2. C ondensable PM emissions not included in the assessment. Condensable particle formation could be an important contributor to amb ient 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

assess ment of compliance with the national ambient air quality standards.

## 5

A PC (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 PM 10 

## increment modeling procedure in appropriately uses the difference
between the controlled and the uncontrolled emission rate s to estimate PSD emissions

.

ADEM Modeling (2003 SIP submittal)

1. The submittal does not address PM 2.5 

## , the most important PM indicator of concern

. The
submittal only addresses the impact of PM10 emission s on ambient concentrations and compliance with ambient standards

.

2. PM m ass 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 m ul tiple. 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.

II I

. Observations on the Modeling Submitted for the 2009 Reconsideration Proposal

AEC and o thers (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 I I

. above apply here as well

.

2. Perf ormed additional PM 2.5 

## 24

- hour analysis in the form of the NAAQS (average of the
98 th 

## per centile for the annual periods modeled).

3. Compared the modeling results to PM 2.5 

## 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 pri marily 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 u nrealistic 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 firs t 2.4 hours of each day. T he 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. T he 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 an d period should be used.

A PC ’s Recap of 2003 ADEM Modeling (Paine)

1. The 2003 ADEM modeling analysis was performed using ISCST3. Th i s same analysis

w as 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 I I

. above remain applicable for this re

- modeling.

A PC ’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 I I

. above remain applicable.

A PC ’s New Analysis (Paine)

– Plant Barry

1. APC provided a n ew NAAQS compliance assessment for another plant

– Plant Barry.

2. C ondensable PM emissions are not included in the assessme nt. 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. T his is a conservative assumption that was used for 10 percent of the daily hours for each day modeled.

4. The total s of the maximum PM 10 

## and PM 2.5 

## modeled concentrations, in the form of the standards, plus background concentrations were less than the applicable PM 10 

## and PM 2.5 

## NAAQS.

Summary of Observations

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

comme nters 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 PM 10 

## and PM 2.5 

## concentrations to exceed their relevant NAAQS when background
concentrations were included. A ll the modeling demonstrations were produced without certain knowledge of the range of PM mass emission rates that would produce 100 percent opacity.
M ore definitive modeling assessment s 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 neit her known nor considered by the

commenters , none of the modeling result s provide conclusive and comprehensive estimate s 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

BLANK PAGE

## 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

- OAR

2005

- 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 C o

. is attainment for PM 2.5 , no PM monitors nearby

Area a ttainment 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 ha d ESP replaced
in 1992 Unit 5 ESP upgrade
scheduled Fall 2007 Unknown Source

- specific modeling would have to be developed for each appl icable 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 o f general

assessment.
How n earby 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 totall y uncontrolled = 100% opacity; ESP turned off;
HOWEVER

- shutting down
ESPs would violate operating permit and would be captured by COM S 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 u sed by NC. No basis pro vided.

- 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 prohibit ed 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 affect s 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
PM 2.5 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 o f modeling condensables for primary
PM 2.5 is important.

- No analysis addressed secondary PM 2.5

.

- Nuck e ls has incorrect multiplier in Table 6 for
controlled PM 2.5 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), Centrev ille (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 C o. 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 ra tes 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 a sh content; no
ESP = 6.82 lb/MM Btu

- 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
Unc ontrolled 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. 1 6 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 h ave modeled largest emissions.

- All emissions m odeled 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 = 43 4

. 8 2 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 2 nd highest
mode led 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 =
1 47.99
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 98 th percentile (i.e., 8 th 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 8 th 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 rec ommended 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

reasona ble

. 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
ab out 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 source s 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. Need s 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 relations h ip 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

o pacity. It is also expected that 100% opacity would be represented by mass emission rates that range over orders of magnitud e. The range in emission rates used to represent 100% opacity in the 4 modeling exercises further support this basic problem wit h 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

p lus 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 fa ctor 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 co ncentration
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 sourc es affected by the rule change or indicate s 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 20 08 ) 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

t he 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 PM 10 and
PM2.5 concentrations would be less than 10% of the daily NAAQS values
in both cases.

Unco n trolled 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
98 th 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 a ttainment 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 pre dictions. 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;
H owever

- 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

perm it 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; 2 nd 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/7.92 m 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 discharge d 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 betwe en

## 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 C o. 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

o ver two consecutive days is flawed
because the 24

- hour
PM 2.5 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) C ontrolled 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

- I nformation on coal heat
content and coal ash content
from 2004 DOE EIA Form
767

- I nformation on % fly from Normal operation: For 21.6 hours, assumed emitting at the permitted limit of
0.12 l b/ 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

- I nformation 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 PM 2.5 and PM 10
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. 1 6 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
1/60 th of a day and
Alabama allows for opacity excursions
1/10 th of a day,
ADEM used
incremental PM 10
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 PM 10 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 &

u ncontrolled: 9.94 AERMOD maximum
PM10 modeled results (84.23) plus previous background of 42 =
126.23
Less than 1 50 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 98 th percentile over 5 yrs)

1

. Background ( 30.7 )+ 98 th

% modeled ( 0.653 ) ; less
than NAAQS w /o CPM.
2. Background ( 30.7 )+ 98 th

% modeled ( 0.976 ); less
than NAAQS w /o CPM.

1

. Background ( 30.7 )+ 98 th

% modeled ( 3.265 ); les s than NAAQS with CPM.
2. Background ( 30.7 )+ 98 th

% modeled ( 4.966 ); e xceeds NAAQS with CPM. Does not follow EPA’s protocol in calculating and rounding the 3

- year average 24

- hour
PM 2.5 monitoring
data. The 3

- Year Average 98 th
Percentile 24

- Hour Average in Table 7 of his report should be
30 rather than 30.7.
The three

- year average of the yearly
8 th

- highest 24

- hour
PM 2.5 predictions at each receptor should
be added to the background and compared to the NAAQS. PM2.5 use 98 th percentile (i.e., 8 th highest)

W/O cond
1. Controlled: 0.12
2. Controlled &
uncontrolled: 0.41

W cond
1. Controlled: 0.39
2

. Controlled &
Uncontrolled: 0.47

Wi th 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 t he PM2.5 PSD
Class II increment was proposed in September 2007 by EPA to be
9 μg/m 3 and 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

t he PM2.5 PSD Class II
increment to be 9 μg/m 3

wi th 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
98 th percentile over 5 modeled years). NA. This is Mueller’s discussion of Tran’s analysis. 1. Modele d 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
A PC ’s assessment except used
AERMOD rather
than ISCST3. See
Attachment A.
3. AERMOD modeling results
are less than
ISCST3

. NA. This is APC’s r ecap

of their o wn previous

m odeling on Plant Greene

. 1. New NAAQS compliance assessment for another plant

– Plant Berry.
2. C ondensable 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 da ily 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 rece nt guidance was not available for the provided modeling assessments, so the modeling information provided by commenters is suspe ct, even if previous versions of / instructions for using AERMOD were followed. Were we to conduct modeling, we would use the

c urrent 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 expec ted results given assumed emission scenarios associated with the proposed allowed 10 percent unlimited opacity. The range of
emiss ions 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 relatio nship between opacity me asurements 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. A ppears 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 da ily 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 analys es 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 PM 10 

### and PM 2.5 

### 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 PM 10 

### concentrations greater than PSD in crement, not NAAQS, when background concentrations are included. They also show concentrations exceeding the PM 2.5 

### NAAQS when background concentration is included. Although these results may be unlikely or rare, they have not been refuted.
6. As with the 2 007 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 oper ation
under th e 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.