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
doIda
ho
Montan
a
Nevad
a
New M
exico
North
Dakota
Oregon
South
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
Offs
hore
CENRAP
Easter
n US
Mexico
Canad
a
Perc
ent o
f Tot
al D
ista
nce
Wei
ghte
d Em
is x
Res
Tim
e
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
doIda
ho
Montan
a
Nevad
a
New M
exico
North
Dakota
Oregon
South
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
Offs
hore
CENRAP
Easter
n US
Mexico
Canad
a
Perc
ent o
f Tot
al D
ista
nce
Wei
ghte
d Em
is x
Res
Tim
e
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
doIda
ho
Montan
a
Nevad
a
New_M
exico
North_
Dakota
Oregon
South_
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
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
doIda
ho
Montan
a
Nevad
a
New_M
exico
North_
Dakota
Oregon
South_
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic
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
doIda
ho
Montan
a
Nevad
a
New_M
exico
North_
Dakota
Oregon
South_D
akota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic
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
ho
Montan
a
Nevad
a
New_M
exico
North_
Dakota
Oregon
South_
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
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
ho
Montan
a
Nevad
a
New_M
exico
North_
Dakota
Oregon
South_
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic
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_
Dakota
Oregon
South_
Dakota Utah
Was
hingto
n
Wyo
ming
Pacific
_Offs
hore
CENRAP
Easter
n_US
Mexico
Canad
a
Region
Rel
ativ
e C
ontr
ibut
ion
WB_DustFugitive_DustRoad_DustNatural_FireAnthro_FireOff-Road_MobileOn-Road_MobileOff-ShoreOil&GasAreaPointBiogenic
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