adem.alabama.gov

AERMOD Experiences 

during the Birmingham 

Area Particle Study (BAP

EPA 9th Modeling Conference

October 9, 2008
adem.alabama.gov

Background

• EPA designated Jefferson, Shelby, an

small portion of Walker counties as nonattainment for the annual standard effective April 5, 2005.

• Current PM2.5 Design Values – 2005-

– North Bham – 18.9 ug/m3 (18.7)

– Wylam - 17.7 ug/m3 (17.5)

• NAAQS = 15 ug/m3
adem.alabama.gov

State Implement

Plan

• Contracted with ENVAIR to help identify ca

high PM2.5.

• Based on the conclusions of the ENVAIR s

SIP focuses on reduction of emissions of fiparticles in the area surrounding the North Birmingham and Wylam monitors.

• The plan also relies on reductions from nat

programs such as CAIR, and cleaner cars, and fuels.

• Base Case 2002/2009/2012 modeling to he

develop attainment plan is being completed CMAQ/AERMOD integrated approach in acwith EPA implementation guidance.
adem.alabama.gov

Measurement S

840 860 880 900 920 940 960 980 1000 1020 1040

-760-740-720-700-680-660-640-620-600-580

Ashland

Gadsden

Birmingham North

route 8 Mcadory

1801 Bruce Shaw Rd

Wylam

Hoover

Pinson

Warrior

Tuscaloosa

Jasper

Childersburg

Birmingham North

1801 Bruce Shaw Rd

CTR

Birmingham PM2.5 Observation Sites

FRMSTNSEARCH
adem.alabama.gov

Birmingham A

Design Valu

Leeds 15.60 

Providence 14.08 12.63 12.30 13.07 13.46 

Corner 14.95 13.87 13.53 14.22 14.52 

Pinson 14.72 13.72 13.57 14.18 14.45 

McAdory 15.65 14.73 14.59 15.01 15.49 Hoover 16.18 14.73 14.33 14.76 15.14 Wylam 18.43 16.74 16.05 16.49 17.28 North Bham 19.63 18 17.53 18.24 18.56 

2004-

2006

2003-

2005

2002-

2004

2001-

2003

2000-

Site 2002

3 Year Avg.
adem.alabama.gov

Annual PM2.5 Design Values 2005-2007

14.6 15.1 15.9 15.6 14.6 13.7

0.02.04.06.08.0

10.012.014.016.018.020.0

Corner Hoover Leeds McAdory Pinson Providence N

Site

Concentration (ug/m3)
adem.alabama.gov

Modeling predicts that EPA’s adopted regulafor mobile sources and electric utilities will rregional and general urban PM by about 1 μ

Additional modeling suggests this may be h

i.e. 1 – 1.5 μg m–3

This reduction will help, but is not likely to bWylam and North Birmingham into attainme2010

Are reductions of local PM possible? Need 

understand what local PM is and where it cofrom.

VISTAS/CAIR M
adem.alabama.gov

Major Finding

ENVAIR Stud

• Nonattainment due to N. Birmingham & • Local and urban PM contributions are 

superimposed on regional component

– Regional - ~12-14 μg/m3– General urban - ~2 μg/m3– Local - ~3-4 μg/m3

• Multiple lines of evidence link local exce

at Wylam and North Birmingham to sevgeographical source complexes

• Evidence includes wind directions, carb

compounds, elements (metals), day-of-variations, fence-line samples, & PM sp
adem.alabama.gov

• With moderate decreases projected in regio

local emission reductions will likely be needethe standard

• Since Wylam and N. BHM drive nonattainme

attention to source complexes surrounding t

• Many sources are intermittent or semi-contin

processes in open buildings

• Very high infrequent PM concentrations• Transportation – rail and trucking – contribut• What to do now? Model and see....

Major Finding

ENVAIR Stu
adem.alabama.gov

PM2.5 (μg m-3)

0

1020

30
adem.alabama.gov

PM2.5 (μg m-3)

0

1020

30
adem.alabama.gov

ENVAIR to ENVIR

• Taking the findings from the monitor

study, JCDH and ADEM contracted ENVIRON/Alpine Geophysics to conmodel attainment demonstration

– Contract awarded in Fall 2006– Using the CMAQ platform with MM5/S

to model the regional and urban signal

– Using the AERMOD model to evaluate 

source impacts

– Integration of modeling platform results
adem.alabama.gov

What doesn’t kill 

• This has been a learning process• Many different stakeholders• New territory for modeling• Uncertainty in emissions inventories• Uncertainty in modeling integration• Highly variable emissions from many 

of sources, many of whom have nevbeen involved in a modeling study omagnitude

• Sheer number of sources
adem.alabama.gov

Emissions Inven

Developmen

• Multiple 2002, 2009, and 2012 CMAQ an

AERMOD inventories have been develop

identify direct, inert PMfine emissions

– Much bigger challenge than expected– Many sources never modeled with this much 

and scrutiny

– Emissions factors for PM2.5 poorly defined, 

available

– Needed to weigh a perfect inventory against 

resource constraints

– Known errors in emissions are being correcte

final runs

– Small sources may have significant impacts
adem.alabama.gov

Emissions Inventory 

• Mistakes were made by both the regulatory agencie

as the facilities. This is due in large part, to the lack understanding of what is needed to model at this le

– For transparency, we insisted on active involvement of fac– If we had known how difficult it would be, we might have c

the inventory development.

• This led to multiple revisions of the 2002, 2009 and 

SMOKE runs

• SMOKE outputs were run through CAMx to produce 

consistent hourly emissions profiles to be input into 
adem.alabama.gov

AERMOD Mode

• Our studies showed a clear “local sou

signature, especially for primary PM2.

• CMAQ, even with 4 km grid spacing, w

considered adequate to resolve impaclocal emission controls.

• AERMOD selected as the best way to 

the significant industrial contributors.

• Which local sources should be modele
adem.alabama.gov

AERMOD Mode

Local Source Cr

• No established criteria- all new territory.• Based on the results of the ENVAIR study, it was a

that every source identified by the study would be 

• Any source within 5 km of either monitor with PM2.

emissions greater than 1 tpy (~1/4 lb/hr) was inclu

• Between 5 – 10 km of either monitor, any source w

emissions greater than 4 tpy (~1 lb/hr) was include

• A Q/d and Q/d2 analyses supported the above crite

well.

• Total of 46 facilities identified; roughly 1200 individ

emitting sources. Included point, area, volume anlines.
adem.alabama.gov

AERMOD Mod

Grid

• Initial discussions with EPA and among 

participants led to a 1 km X 1 km AERMreceptor grid with 100 meter spacing

• Plant property issues

• Additional discussion led to agreement o

m X 300 m Cartesian grid with 100 mete

• For the attainment demonstration, concen

be averaged across all receptors

• For culpability and RACT, concentrations 

monitor were used
adem.alabama.gov

AERMOD Met 

• Used 2002 met data – same as base case e

data year.

• Options

– Conventional NWS ASOS data at Birmingham 

(BHM) – 7 – 18 km from key monitors.

– SEARCH site wind data at North Bham monito– Hourly-averaged ASOS data at BHM.

• Choice – hybrid of hourly ASOS data augme

conventional ASOS data as necessary. SEAdata had too many holes and quality questioOAQPS invaluable in developing the hybrid 
adem.alabama.gov

AERMOD Met 

NBHM PM2.5 - AERMOD PREDICTIONS VS. OBSERVED - LIG

WINDS IMPACT STUDY (Q1 2002)

0

20406080

100

BHM_1-min BHM_ISHD NBHM PM2.5 SEARCH(1.0) S
adem.alabama.gov

AERMOD Over

AERMOD run for local significant 

facilities

– ADEM assessed “significance” and 

determined facility list for AERMOD

– Only primary PM2.5 was simulated– Wind inputs generated using draft E

1-minute ASOS data methodology

– For 2002 MPE, 24-hr concentrations 

saved at WYLM and NBHM monitor coordinates
adem.alabama.gov

AERMOD Over

Thus, we expect AERMOD to predict loconcentrations than daily FRM observa

– Observation-based analyses (ENVAIR S

suggest annual local industrial contribut

• ~3 ug/m3 at NBHM• ~2 ug/m3 at WYLM

But we recognize AERMOD is conside“conservative” (high) model
adem.alabama.gov

AERMOD Res

Annual 6.47 5.3

4th 6.09 4.93

3rd 6.48 5.17

2nd 7.02 5.73

1st 6.27 5.4

WYLM

Annual 33.49 19.6

4th 35.87 21.3

3 37.66 22.1

rd

2 34.69 20.1

nd

1 25.74 15.0

st

NBHM

2009 Quarte

Conce

2002 Quarterly PM2.5

Monitor Quarter Concentration
adem.alabama.gov

2002 by Quarter at 

Sequenced 24 hour PM2.5

1st Quarter, WYLM Monitor

0

1020304050

2010124

2010424

2010724

2011024

2011324

2011624

2011924

2012224

2012524

2012824

2013124

2020324

2020624

2020924

2021224

2021524

2021824

2022124

2022424

2022724

2030224

2030524

2030824

2031124

2031424

Date

ug/m3

Sequenced Observations
adem.alabama.gov

Sequenced 24 hour PM2.5

2nd Quarter, WYLM Monitor

0

1020304050

2010124

2010424

2010724

2011024

2011324

2011624

2011924

2012224

2012524

2012824

2013124

2020324

2020624

2020924

2021224

2021524

2021824

2022124

2022424

2022724

2030224

2030524

2030824

2031124

2031424

2031724

Date

ug/m3

Sequenced Observations

2002 by Quarter at 
adem.alabama.gov

2002 by Quarter at 

Ranked 24 hour PM2.5

1st Quarter, WYLM Monitor

0

1020304050

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 7

Rank

ug/m3

Ranked Observations
adem.alabama.gov

Ranked 24 hour PM2.5

3rd Quarter, WYLM Monitor

0

1020304050

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 

Rank

ug/m3

Ranked Observations

2002 by Quarter at 
adem.alabama.gov

2002 Wylam Frequ

Distribution

Annual Frequency Distribution

W YLM

0

20406080

100120140160

0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 4

ug/m3

Frequency

Obs AERMOD
adem.alabama.gov

WYLM Resu

Agrees with expected patterns (goo

– Always lower than daily FRM total o

• Expected local industry contributions a

ug/m3

• AERMOD annual mean is ~ 6.5 ug/m3

– AERMOD is rarely >10x the assume

local component (4 days)

• >5x local component 20% of the year

– Annual frequency distribution is hea

the 0-10 ug/m3 range
adem.alabama.gov

2002 by Quarter at 

Sequenced 24 hour PM2.5

2nd Quarter, NBHM Monitor

0

20406080

100120140160

2040124 2040424 2040724 2041024 2041324 2041624 2041924 2042224 2042524 2042824 2050124 2050424 2050724 2051024 2051324 2051624 2051924 2052224 2052524 2052824 2053124 2060324 2060624 2060924 2061224 206152

2

Date

ug/m3

Sequenced Observations
adem.alabama.gov

Sequenced 24 hour PM2.5

3rd Quarter, NBHM Monitor

0

20406080

100120140160

2070124 2070424 2070724 2071024 2071324 2071624 2071924 2072224 2072524 2072824 2073124 2080324 2080624 2080924 2081224 2081524 2081824 2082124 2082424 2082724 2083024 2090224 2090524 2090824 2091124 209142

2

Date

ug/m3

Sequenced Observations

2002 by Quarter at 
adem.alabama.gov

2002 by Quarter at 

Ranked 24 hour PM2.5

3rd Quarter, NBHM Monitor

0

20406080

100120140160

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 

Rank

ug/m3

Ranked Observations
adem.alabama.gov

2002 by Quarter at 

Ranked 24 hour PM2.5

4th Quarter, NBHM Monitor

0

20406080

100120140160

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 

Rank

ug/m3

Ranked Observations
adem.alabama.gov

2002 NBHM Frequ

Distribution

Annual Frequency Distribution

NBHM

0

102030405060708090

100

0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 

ug/m3

Frequency

Obs AERMOD
adem.alabama.gov

NBHM Resu

Dramatic over predictions (bad)

– Usually higher than daily FRM total 

• Expected local industry contributions a

ug/m3

• AERMOD annual mean is ~ 5x higher

– AERMOD is >10x the assumed loca

component ~1/2 of year

• >5x local component 2/3 of the year

– Annual frequency distribution is hea

the >30 ug/m3 range
adem.alabama.gov

Quantile-Quan

Compariso

Q-Q Plot

Ranked Modeled vs. Observed

y = 0.5

R2 = 

y = 3.08x - 

R2 = 0.

0

20406080

100120140160

0 20 40 

Observations (ug/m3)

AERMOD (ug/m3)

WYLMNBHMLinear (WYLM)Linear (NBHM)
adem.alabama.gov

Conclusion

• Q-Q plot shows a marked differenc

the character of AERMOD predictiobetween NBHM and WYLM

– NBHM shown to be dominated by fac

in very close proximity

– Are sources characterized adequatel– Should we expect AERMOD to perfo

poorly for certain source configuratio

– What are our expectations from AER
adem.alabama.gov

Conclusions, c

• Additional revisions to source characteriza

have been made, and emission rates have revised

• Will these changes affect AERMOD perfor

• Unknown

• Hope to show compliance with CMAQ alon• Think that future modeling exercises like t

focus on refining photochemical models to at very small grid scales

– Don’t feel this is the best use of these models
adem.alabama.gov

• AERMOD was run for selected local sources for t

and 2009 bases to simulate the dispersion of primPM2.5. 

• CMAQ was run to simulate the dispersion of urba

regional scale primary as well as secondary emisPM.

– Secondary and gaseous PM from all facilities

• CMAQ was run twice for the 2002 and 2009 base

– Each base year was run once with all sources and once 

AERMOD sources

– Additional runs, including alternate future years, are bei

considered

• The results of the combination of CMAQ and AER

were used to obtain the future year projections of 

CMAQ - AERM

Integration
adem.alabama.gov

• Followed EPA’s modeling guidance • EPA’s involvement has been invalua

– Met data– Modeling assistance– Discussion on issues such as source 

characterization, policy implications anmodel performance 

• Even with this involvement, it is still 

to determine whether this is an apprapplication of the model for this situa

CMAQ - AERM

Integration
adem.alabama.gov

2009 DV Projec

Circa Spring 200

• CMAQ “all-source” runs

– 1x1 and 3x3 grid cell averaging arou

NBHM and WYLM

• CMAQ + AERMOD runs
adem.alabama.gov

CMAQ "All Source" 2009 DV Projection (3x3 cell average)

0.005.00

10.0015.0020.00

2002 NBHM 2009 NBHM 2002 WYLM 2009 WYLM

Annual Concentration (ug/m3) 

18.4

15.5

17.1 16.7
adem.alabama.gov

CMAQ + AERMOD 2009 DV Projection (3x3 cell average)

0.005.00

10.0015.0020.00

2002 NBHM 2009 NBHM 2002 WYLM 2009 WYLM

Annual Concentration (ug/m3) 

18.4

15.0

17.1

15.7
adem.alabama.gov

2009 CMAQ

“All-Source” Pro

3x3 averagin

2002 2009 Red

N. Bham. 18.4 16.7 

McAdory 15.0 13.8 

Providence 13.0 11.7 

Wylam 17.1 15.5 

Hoover 15.1 13.7 

Pinson 14.0 12.6 

Corner 14.1 12.6 
adem.alabama.gov

ASIP Modeling R

• Updated modeling for 2012 (12km) accom

by ASIP in July/August for GA and AL SI

• All states provided updated emissions in

• Alabama rolled in the “to-date” 2002 BA

inventory

• CAIR controls assumed
adem.alabama.gov

ASIP Modeling R

• The 2012 results are promising –It’s important not to look to closely 

number per se, but rather the reduc

–2002/2009 results used different em

inventories than the 2012 (VISTAS v

–Still, we think the results show that 

in GA and AL will help bring the areattainment

• The following chart illustrates the 2002 

2009 Best and Final, 2012 Initial, 2018 Final results for Alabama assuming CAimplementation.
adem.alabama.gov

ASIP RESULT

Alabama, 2002 Design Value, 2009 base G4a 12km and 36km,

2012 base G4a 12km and 36km, and 2018 base G4a 12km and 36km Projected 

02468

101214161820

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

DVF 12g4 12km

DVF 18g4 12km

DVC

DVF 09g4 12km

Baldwin 0010 Clay 0001 Colbert 1002 DeKalb 1003 Escambia 0002 Etowah 0010 Jefferson 0023 Jefferson 1005 Jeffers

μg/m

3

State Alabama set 1

Name dataset
adem.alabama.gov

Determination 

Attainment Ye

• ADEM will propose an attainment date th

represents attainment as expeditiously as practicable based on implementation of eFederal and State measures and all new reasonable local measures.

•We believe that 2012 will represent the best future yBirmingham NAA•However, we will model both future years and develo(2009 and 2012) 

• In our 2009 basecase, we will account fo

controls already on the books such as CAmobile source controls, as well as local incontrols implemented between 2002 and 

• Same for 2012
adem.alabama.gov

Final Attainmen

• The process of identifying significan

contributors and candidate control strategies will continue until an emisreduction plan is developed that demonstrates attainment.

• JCDH will modify permits to reflect f

emission controls.