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 for thesesources considering the4 RPG and other factors

identified in the RHR.

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 no LTS beyond BART is developed, then the 4 RPG factorsare inherently taken into account via BART.

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%?

Eagle Cap Example(Starkey, OR)

NO3

• Is the Base+BART projection better than URP?– Yes: The CMAQ base case projections for 2018 show

a 25% reduction in NO3.• Results do not yet include BART• WRAP anthro reduction is 39%

• Are there any important uncontrolled upwind sources– Usee TSS to examine inventory upwind– Might want to see ID’s CALPUFF results

NO3 PSAT Results

SO4

• Is the Base+BART projection better than URP?– No: The CMAQ base case projections for 2018 show only a

1% reduction in SO4.• Results do not yet include BART• Sources outside the WRAP have a large influence

• Is WRAP anthro reduction > 20%?– No: The PSAT source apportionment shows only a 10%

reduction from WRAP anthro SO2 sources– Also, the WEP analysis of upwind emissions shows relatively

no change as mobile source reductions are offset by point source growth

• Again, BART not yet included

SO4 PSAT Results

Sources and Areas of Potential Sulfur Oxide Emissions Influence2000-2004 Baseline for Starkey, OR

20% Worst Visibility Days

0.0 2.0 0.0 1.7 0.2 0.5 0.0 0.0

70.6

0.0 0.0

15.9

0.04.1

0.0 0.0 0.05.0

0

10

20

30

40

50

60

70

80

90

100

Arizon

a

Califor

nia

Colora

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Montan

a

Nevad

a

New M

exico

North

Dakota

Oregon

South

Dakota Utah

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Perc

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Biogenic Natural Fire Point Area WRAP Area O&G Off-Shore On-Road Mobile Off-Road Mobile Road Dust Fugitive Dust WB Dust Anthro Fire

SO4 WEP Results

Sources and Areas of Potential Sulfur Oxide Emissions Influence2018 Projections for Starkey, OR

20% Worst Visibility Days

0.0 2.1 0.0 1.1 0.2 0.5 0.0 0.0

73.5

0.0 0.0

13.8

0.03.8

0.0 0.0 0.04.9

0

10

20

30

40

50

60

70

80

90

100

Arizon

a

Califor

nia

Colora

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Montan

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Nevad

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North

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Oregon

South

Dakota Utah

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Biogenic Natural Fire Point Area WRAP Area O&G Off-Shore On-Road Mobile Off-Road Mobile Road Dust Fugitive Dust WB Dust Anthro Fire

SO4 WEP Results

Source Category PSAT WEP Notes

Offshore shipping Outside state authority.

WA point sources See Centralia trends to follow. BART not yet included at other sources.

OR point sources BART not yet included. See Boardman emissions data to follow.

OR and WA mobile Note large reductions (83% in PSAT).

OR area See following table.

Canadian point Outside state authority.

Most Likely SO2 Sources Significantly Contributing to SO4 at Eagle Cap

Oregon Area Source SO2 Emissions (2002 tpy) for 2002 and 2018 Base Cases

SCC1_DESC SCC3_DESC SCC6_DESC SCC8_DESC 2002 2018Stationary Source Fuel Combustion Residential Natural Gas 12 14

Wood 616 642Liquified Petroleum Gas (LPG) 1 1Distillate Oil 992 753Kerosene 160 160Bituminous/Subbituminous Coal 27 27

Industrial Natural Gas 15 17Liquified Petroleum Gas (LPG) 0 0Residual Oil 2,693 1,800Distillate Oil 1,453 449Kerosene 49 60Bituminous/Subbituminous Coal

Commercial/Institutional Liquified Petroleum Gas (LPG) 0 0Natural Gas 8 10Distillate Oil 989 1,376Residual Oil 398 398Kerosene 63 63

Waste Disposal, Treatment, and Recovery 292 410Industrial ProcessesSolvent UtilizationMiscellaneous Area Sources Agriculture Production - Crops Agriculture - Crops

Orchard Heaters Diesel 2,164 2,243Propane 0 0Total, all fuels 0 0

Agricultural Propaning - tractor-pulled burners to burn stubble only0 1Agricultural Stack Burning - straw stacks moved from field for burning

Other CombustionStorage and TransportGrand Total 9,932 8,422

Crater Lake Example

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

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.

Centralia SO2 Emission Trends

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

2000 2001 2002 2003 2004 2005

SO2

Tons

Per

Yea

r

Base Case Modeling Year

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)– Positive Matrix Factorization (PMF) also available,

especially for carbon

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

Califor

nia

Colora

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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

Califor

nia

Colora

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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

Califor

nia

Colora

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Montan

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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

Califor

nia

Colora

doIda

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Montan

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Nevad

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Oregon

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WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic

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

Califor

nia

Colora

doIda

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Montan

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Nevad

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New_M

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North_

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Oregon

South_

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CRLA1 Weighted Emissions Potential Primary PMC Emissions (2018)

PMC x Res Time

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Arizon

a

Califor

nia

Colora

doIda

ho

Montan

a

Nevad

a

New_M

exico

North_

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Oregon

South_

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