Regional Haze Rule• Promulgated in 1999• Requires states to set RPGs based on 4 statutory factors

and consideration of a URP• URP = 20% reduction in manmade haze (dv) per planning

period (10 years)• URP heavily dependent on:

– Assumptions regarding future natural conditions– Contribution of non-WRAP sources to baseline– Representativeness of 2000-04 baseline

• 24 of the 77 Class I sites have no more than 3 years of data in baseline period

– These issues more accute in the West

Why A Species-Based Approach?

• Species differ significantly from one another in their:– Contribution to visibility impairment– Spatial and seasonal distributions– Source types– Contribution from natrual and international sources– Emissions data quality– Atmospheric science quality– Tools available for assessment and projection

SO2 NOx OC CM

Emission Sources

Almost entirely anthro.

Mostly point sources.

Mostly anthro.

Mix of combustion sources.

Diverse.

Mix of anthro, fire, and biogenic VOCs.

Diverse.

Very difficult to partition wb dust into nat/anthro.

Emissions Data Quality

Very good overall.

Activity data less good for area sources.

Good.Activity data less good, some coding concerns w/ smaller point, area, and O&G sources.

Fair.Good activity data & conf. in PM2.5 emissions, but uncertain spec. of PM2.5 & bio. VOCs.

Poor, except for some locales.Categorically complete but accuracy very uncertain.

Emission Projections

Very good.

Uncertain about area sources.

Good.

Uncertain about offshore and O&G.

Fair.

What to expect from fire?

Fair.

What to expect from wb dust?

Atmospheric Science Quality

Very good.

Meteorology probably largest uncertainty.

Fair.

Chemistry more complex, but meteorology too.

Fair.

Most complex, least understood, but model perf. OK.

Fair.

No major chemistry, but model resolution, met. insufficient.

WRAP Tools Emission Inv.

CMAQ Proj.

PSAT Apport.

Emission Inv.

CMAQ Proj.

PSAT Apport.

Emission Inv.

CMAQ Proj.

PMF, WEP.

Emission Inv.

Causes of Dust.

WEP.

What Is A Potential Process?

• For each site and species:• Estimate progress expected from Base Case + BART

in 2018• Determine any other LTSs which may be reasonable

for that pollutant and recalculate 2018 species concentration

• Add up improvements from all species into dv• This becomes the RPG for the 20% worst days• Explain why this is less than URP

– Large international and natural contributions, large uncertainties in dust inventory preclude action, etc.

Determining Non-BART LTSs

• Determine species glidepath and 2018 URP value• Estimate progress expected from Base Case +

BART in 2018• If progress is better than or equal to 2018 URP:

– Check inventory for “important sources” which may be uncontrolled

• If progress is worse than 2018 URP, but WRAP antho contribution declines by at least 20%:– Check inventory for important sources which may be

uncontrolled

Determining Non-BART LTSs

• If progress is worse than 2018 URP, and WRAP antho contribution declines by less than 20%:– Evaluate air quality & emission trends in more detail– Check inventory for important sources which may be

uncontrolled or undercontrolled– Identify LTSs for these sources considering the 4

RPG factors and 7 LTS factors, where applicable– Either adopt these strategies, commit to adopting

them post 2007, or commit to evaluating them further

“Important Sources”

• Identified and qualitatively ranked based on some or all of the following:– Size, proximity, current/potential degree of control,

feasibility of control, cost effectiveness, etc.• If point sources important, identify ~10 facilities• If area sources important, identify 3-5 categories

• Identification of important sources should not be limitted by state boundaries

Determine URP for a species

IsBase+BART

projection better than

URP?

IsWRAPAnthro

reduction> 20%?

Are thereany importantuncontrolled

sources?

Are thereany important

uncontrolled orundercontrolled

sources?

Repeat for other species.

Evaluate emission & airquality trends more closely

Identify LTSs forthese sources.

Adopt, commit to adopt, orcommit to further evaluation.

Determine reductions at C1A.

Add up all species reductionsto get a RPG. Explain whyit’s less than default URP

but still reasonable.

Y

Y Y

N

N N

N

Y

Note, if projection is better than URP and/or WRAP anthro reduction is >20%, the 4 RPG factors are inherently taken into account via BART.

Crater Lake Example

Do SO4, NO3, OC, and EC meet their glidepaths? No, Yes, No, Yes.Then do the WRAP anthro contributions for SO4 and OCdecline by 20%?

SO4 and NO3 Data

• The following 6 slides describe and show the results of the CAMx-PSAT source apportionment model results for SO4 and NO3.

• Results are used to determine the rank and significance of sources and to evaluate the percent change in their contribution to haze in the baseline and future years. They are not used to predict a specific amount / concentration of pollution.

SO4 and NO3 Apportionment

• CAMx air quality model with PM Source Apportionment Technology (PSAT)

• PSAT completed for 2 cases:– Plan 2002c– Base 2018b

• Tracks sources of sulfate and nitrate• Tracking organic carbon too computationally

intensive. However, data is available that delineates primary OC, from biogenic SOA, and anthropogenic SOA.

18 Source Regions on a 36 km Grid

- 2 7 3 6 - 2 4 1 2 - 2 0 8 8 - 1 7 6 4 - 1 4 4 0 - 1 1 1 6 - 7 9 2 - 4 6 8 - 1 4 4 1 8 0 5 0 4 8 2 8 1 1 5 2 1 4 7 6 1 8 0 0 2 1 2 4 2 4 4 8- 2 0 8 8

- 1 8 7 2

- 1 6 5 6

- 1 4 4 0

- 1 2 2 4

- 1 0 0 8

- 7 9 2

- 5 7 6

- 3 6 0

- 1 4 4

7 2

2 8 8

5 0 4

7 2 0

9 3 6

1 1 5 2

1 3 6 8

1 5 8 4

1 8 0 0

26

9

1 2

4

58

1 3

1 13

1 7

1 5

1 5

1 6

1 6

1 6

1 8 1 8

1 4

1 7

1 4

1 0

Eight Source Categories

• Examples of PSAT “sources”:– MV_CO = mobile sources in Colorado

– PT_CE = point sorces in CENRAP

– BCON = transport from modeling domain boundaries (derived from GEOS-CHEM)

ICON Initial conditions

BCON Boundary conditions

PT Point sources

MV Mobile sources

ANF WRAP anthropogenic fires

Natural WRAP natural fires and biogenics

NWF Elevated fires in other RPOs

AR All other sources (non-elevated fires in other RPOs, area sources, offshore, oil & gas area sources, etc.)

Status of Modeling

• Plan 2002c just completed• Base 2018b completed end of August• Results currently available for daily and monthly

averages• Results will be provided for 20% best and worst

visibility days at each Class I area• See “Apportionment” link on TSS for results

Do WRAP anthropogenic SO4 contributions decline by 20%? Not quite (18%). Note: WRAP reductions would be significantly larger if 2001 were used as a base year because the first Centralia cut occurred in 2002. Also, OR_PT contribution will likely decline with BART, especially at the Boardman power plant.

Do WRAP anthropogenic NO3 contributions decline by 20%? Yes (39%). Again, note potential reductions from Boardman.

Carbon and Dust Apportionment

• PSAT results for OC and EC not available due to computational resources.

• No air quality modeling results available whatsoever for CM, and FS due to poor model peformance.

• For these pollutants, an alternative technique developed by the WRAP could be used to evaluate sources and progress.– Weighted Emissions Potential (WEP)

Weighted Emissions Potential Method

• Combine gridded emissions data with gridded backtrajectory residence times to determine sources with the most potential to affect a site.

• Sources with the greatest potential will tend to be both upwind on the worst visibility days and have relatively large emissions.– 2002 and 2018 annual average emissions– 3-5 years of 20% worst days back trajectories– Discount sources based on distance from site– Ignore grid cells with very low residence times– Does not account for chemistry, dispersion, deposition– Method being finalized

Weighted Emissions Potential MethodPrototype example for Salt Creek, New Mexico

Emissions ResidenceTimes

Weighted EmissionsPotential

X =

CRLA1 Weighted Emissions Potential Primary OC Emissions (2002)

POA x Res Time

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

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ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Rel

ativ

e C

on

trib

uti

on

WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic

Do WRAP upwind weighted anthro OC emissions decline by 20%?

No. They hardly change.

CRLA1 Weighted Emissions Potential Primary OC Emissions (2018)

POA x Res Time

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Re

lati

ve

Co

ntr

ibu

tio

n

WB_Dust

Fugitive_DustRoad_Dust

Natural_Fire

Anthro_FireOff-Road_Mobile

On-Road_Mobile

Off-ShoreOil&Gas

Area

PointBiogenic

Do WRAP upwind weighted anthro VOC emissions decline by 20%?

No. They hardly change because growth in point and area sources offsets mobile source reductions.

CRLA1 Weighted Emissions Potential Primary VOC Emissions (2002)

VOC x Res Time

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Rel

ativ

e C

on

trib

uti

on

WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic

CRLA1 Weighted Emissions Potential Primary VOC Emissions (2018)

VOC x Res Time

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Rel

ativ

e C

on

trib

uti

on

WB_Dust

Fugitive_DustRoad_Dust

Natural_Fire

Anthro_FireOff-Road_Mobile

On-Road_Mobile

Off-ShoreOil&Gas

Area

PointBiogenic

Do WRAP upwind weighted anthro EC emissions decline by 20%?

Yes, 28% due to mobile source controls.

CRLA1 Weighted Emissions Potential Primary EC Emissions (2002)

PEC x Res Time

0

5,000

10,000

15,000

20,000

25,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Rel

ativ

e C

on

trib

uti

on

WB_Dust

Fugitive_Dust

Road_Dust

Natural_Fire

Anthro_Fire

Off-Road_Mobile

On-Road_Mobile

Off-Shore

Oil&Gas

Area

Point

Biogenic

CRLA1 Weighted Emissions Potential Primary EC Emissions (2018)

PEC x Res Time

0

5,000

10,000

15,000

20,000

25,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Re

lati

ve

Co

ntr

ibu

tio

n

WB_Dust

Fugitive_Dust

Road_Dust

Natural_Fire

Anthro_Fire

Off-Road_Mobile

On-Road_Mobile

Off-Shore

Oil&Gas

Area

Point

Biogenic

Do WRAP upwind weighted anthro CM emissions decline by 20%?

No, they increase 32%.

CRLA1 Weighted Emissions Potential Primary PMC Emissions (2002)

PMC x Res Time

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Re

lati

ve

Co

ntr

ibu

tio

n

WB_Dust

Fugitive_Dust

Road_Dust

Natural_Fire

Anthro_Fire

Off-Road_Mobile

On-Road_Mobile

Off-Shore

Oil&Gas

Area

Point

Biogenic

CRLA1 Weighted Emissions Potential Primary EC Emissions (2018)

PMC x Res Time

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Arizon

a

Califo

rnia

Colora

doId

aho

Mon

tana

Nevad

a

New_M

exico

North

_Dak

ota

Orego

n

South

_Dak

ota

Utah

Was

hingt

on

Wyo

ming

Pacific

_Offs

hore

CENRAP

Easte

rn_U

S

Mex

ico

Canad

a

Region

Re

lati

ve

Co

ntr

ibu

tio

n

WB_Dust

Fugitive_Dust

Road_Dust

Natural_Fire

Anthro_Fire

Off-Road_Mobile

On-Road_Mobile

Off-Shore

Oil&Gas

Area

Point

Biogenic