Implementation Workgroup MeetingDecember 6, 2006

Attribution of Haze Workgroup’sMonitoring Metrics Document Status:

1) 2018 Visibility Projections – Alternative Procedures using Relative Response Factors

2) Ambient Haze Monitoring Data Substitution

Monitoring Metrics Document Status• Issue identified at late July AoH Workgroup meeting• Document to provide consensus technical recommendations to

support haze planning• 4 major topics

Adopt revised IMPROVE equation – done Adopt alternate natural conditions values (by species) – done Adopt 2000-04 IMPROVE dataset for sites with complete data – done

Sites with insufficient data identified and data substitution underway Analysis of default and alternate visibility projections methods

2 calls completed, next call 12/13, maybe 1 additional call Potential methods explained later

• Final draft of Monitoring Metrics document out for review early January

Introduction to Visibility Projections• Difficult to meet 2018 Uniform Rate of Progress

(URP) goal for western Class I areas using EPA default or alternative modeled 2018 visibility projections methods due to large contributions of:– Fires (High EC and OC)– Dust (High Soil and CM)– International Transport

• Most of these emissions are natural, unpredictable and uncontrollable

• Unable to realistically forecast these sources in 2018– many source categories held constant from 2002 to 2018 – Two examples follow: Crater Lake (CRLA) OR and Salt

Creek (SACR) NM

13.7813.29

12.08

10.87

9.65

8.44

7.23

6.50

13.31

5

7

9

11

13

15

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haz

ines

s In

dex

(Dec

ivie

ws)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Uniform Rate of Reasonable Progress Glide PathSawtooth Wilderness - 20% Worst Days

5

7

9

11

13

15

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

18.0317.29

15.43

13.57

11.71

9.85

8.00

6.88

17.14

5

8

11

14

17

20

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haz

ines

s In

dex

(Dec

ivie

ws)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Uniform Rate of Reasonable Progress Glide PathSalt Creek - 20% Worst Days

5

8

11

14

17

20

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

2018 Emission Projections• Sources Held Constant 2000-04 to 2018 base case

– Biogenics– Wind Blown Dust (WRAP model)– Ammonia from WRAP model– Mexico and Canada– Off-Shore Marine– Boundary Conditions from GEOS-Chem Global Model

• Sources with emission reductions 2000-04 to 2018 base case– Mobile source NOx, SOx, EC & OC– Point and Area Source NOx and SOx (amount varies by state)– Nonattainment areas (mainly VOC & NOx in CA)– Many other anthropogenic sources relatively unchanged or

increase• Road dust, oil & gas, some uncontrolled area sources

2018 Visibility Projection Issues• EPA guidance (September 2006) recommends using

average modeling results for the 2002 Worst 20% (W20%) days to project 2018 visibility for W20% days from the 2000-2004 Baseline (Relative Response Factors, RRFs)

• W20% days in 2002 may not be representative of W20% days from other years in Baseline– 2002 W20% days may occur in different times of the year

and therefore emphasize different PM components– Episodic events may dominate W20% days in some years

• Fires dominate 2002 W20% days at some western Class I areas that makes the 2002 year derived RRFs very stiff

• Fire impacts in other years at Class I areas with little fires in 2002

Agua Tibia, CA (AGTI1) Distribution of 20% Worst Days by Year (IMPROVE data)

0

0.1

0.2

0.3

0.4

1 2 3 4 5 6 7 8 9 10 11 12Month

2001

2002

2003

2004

Salt Creek, NM (SACR1) Distribution of 20% Worst Days by Year (IMPROVE data)

0

0.1

0.2

0.3

1 2 3 4 5 6 7 8 9 10 11 12Month

2001

2002

2003

2004

Badlands (BADL1) Distribution of 20% Worst Days by Year (IMPROVE data)

00.1

0.20.3

0.40.5

1 2 3 4 5 6 7 8 9 10 11 12Month

2000

2001

2002

2003

2004

Concern 2002 May Not Capture Seasonal Variations

2018 Visibility Projection Issues• Missing IMPROVE data at some Class I areas hinders

visibility projection calculations at 18 sites in western U.S.– 5 IMPROVE sites did not meet RHR criteria of at least 3

complete years in 2000-2004 Baseline– 13 IMPROVE sites did not satisfy data completeness criteria

for 2002 so RRFs could not be calculated– Data substitution underway to address this issue

• Model performance for Coarse Mass (CM) sufficient bad we do not believe the RRFs are reliable– Suspect a lot of measured CM are subgrid-scale to the model

so the model 36 km CM estimates are not representative– Set RRFs for CM = 1.0

2018 Visibility Projection Issues• 2018 URP goal is not a NAAQS, just one element of

the Reasonable Progress (RP) determination • Four Factor Analysis another important element of RP• EPA default 2018 visibility projections one approach

for using modeling results in RP determination– Can we use alternative projection techniques that take into

account seasonal differences in W20% days during Baseline– Are there other ways we can use the modeling results to

assist in the Reasonable Progress determination?

Approaches for RRFs (1)• Method 1: Average RRF Approach from

September 2006 EPA Guidance– For each Class I area and Observed Worst/Best 20%

days from 2002 take the ratio of the average modeled 2018 to 2002 PM species concentrations

– Applied to observed daily PM components for each Worst/Best 20% day from each year from the Baseline, calculate daily Bext/dv, annual dv and 2018 projected dv same as before

N

iij

N

iij

N

iij

N

iij

j

SO

SO

SON

SONSORRF

1

1

1

1

)2002(4

)2018(4

)2002(41

)2018(41

)4(

Approaches for RRFs (2)• Method 2A: Average Quarterly RRF

Approach– Similar to Average RRF Approach only calculate

separate RRFs for each Quarter of the year using the observed Worst/Best 20% days for each Quarter in 2002

– Allows for seasonal variations in RRFs, has similarities to 24-Hour PM2.5 projection approach specified by EPA guidance

Approaches for RRFs (3)• Method 2B: Average Monthly RRF

Approach– Calculate separate RRFs for each Month of the

year using the observed Worst/Best 20% days for each Month in 2002

– Allows for seasonal variations in RRFs • Results follow for:

– 2002 Plan02c & 2018 Base18b– CMAQ 2002 36 km annual simulations– New IMPROVE equation

Visibility Projection Comparisons• Use DotPlots that present 2018 visibility at

Class I areas as a percentage of meeting 2018 URP benchmark– Compare Method 1 (Annual W20%) with

Method 2A (Quarterly W20%) and Method 2B (Monthly W20%) New IMPROVE Algorithm

– New IMPROVE equation– RRF for CM = 1.0– No Western US Class I area achieves 2018

URP benchmark• In contrast to eastern US where many Class I areas

achieve 2018 URP goal due to sulfate domination

Visibility Predictions for Colorado Plateau and Desert Southwest sites

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%B

RC

A1

CA

NY

1

GR

CA

2

ME

VE

1

SA

PE

1

WE

MI1

ZIO

N1

BA

ND

1

BO

AP

1

CH

IR1

GIC

L1

GR

SA

1

IKB

A1

SA

CR

1

SA

GU

1

SIA

N1

WH

IT1

WH

PE

1

Perc

ent o

f tar

get r

educ

tion

achi

eved

from monthly RRF

from quarterly RRF

from annual RRF

Colorado Plateau Desert Southwest

Visibility Predictions for North, Great Basin and Rockies sites

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%BAD

L1

CABI1

GAM

O1

LOST1

MELA

1

MO

NT1

SU

LA1

THR

O1

ULB

E1

WIC

A1

CR

MO

1

JAR

B1

SAW

T1

BR

ID1

NO

AB1

RO

MO

1

WH

RI1

YELL

2

Perc

ent o

f tar

get r

educ

tion

achi

eved

from monthly RRF

from quarterly RRFfrom annual RRF

North Great Basin Rockies

Visibility Predictions for Pacific Northwest and California sites

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%HECA1

KALM

1

MO

HO

1

MO

RA1

NO

CA1

OLY

M1

PASA1

SNPA1

STA

R1

THSI1

WHPA1

AG

TI1

BLI

S1

DO

ME1

HO

OV1

JOSH1

LAVO

1

PIN

N1

REDW

1

SAG

A1

SAG

O1

YO

SE1

Perc

ent o

f tar

get r

educ

tion

achi

eved

from monthly RRF

from quarterly RRF

from annual RRF

Pacific Northwest California

Worst 20% Obs (left) vs plan02c (right) at AGTI1

0

20

40

60

80

100

120

140

160

59 80 89 92 134 137 212 224 227 230 239 248 284 287 293 296 299 302 305 329 _ _ _ _ _ Avg

Julian Day in Worst 20% group

bEXT

(1/M

m) bCM

bSOILbECbOCbNO3bSO4

Bext Response (base18b - plan02c) at AGTI1 on Worst 20% Days

-25

-20

-15

-10

-5

0

5

59 80 89 92 134 137 212 224 227 230 239 248 284 287 293 296 299 302 305 329 Avg

Julian Day

Del

ta B

ext (

1/M

m) bCM

bSOILbECbOCbNO3bSO4

Uniform Rate of Reasonable Progress Glide PathAgua Tibia Wilderness - 20% Worst Days

23.5022.45

19.81

17.18

14.54

11.91

9.287.70

21.72

0

5

10

15

20

25

30

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haz

ines

s In

dex

(Dec

ivie

ws)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Worst 20% Obs (left) vs plan02c (right) at SAWT1

0

10

20

30

40

50

60

70

116 137 170 191 194 197 200 203 206 209 212 215 218 224 230 233 254 257 269 296 299 317 _ _ _ Avg

Julian Day in Worst 20% group

bEXT

(1/M

m) bCM

bSOILbECbOCbNO3bSO4

Bext Response (base18b - plan02c) at SAWT1 on Worst 20% Days

-4

-3

-3

-2

-2

-1

-1

0

1

116 137 170 191 194 197 200 203 206 209 212 215 218 224 230 233 254 257 269 296 299 317 Avg

Julian Day

Del

ta B

ext (

1/M

m) bCM

bSOILbECbOCbNO3bSO4

Uniform Rate of Reasonable Progress Glide PathSawtooth Wilderness - 20% Worst Days

13.7813.29

12.08

10.87

9.65

8.44

7.23

6.50

13.27

5

7

9

11

13

15

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haz

ines

s In

dex

(Dec

ivie

ws)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Worst 20% Obs (left) vs plan02c (right) at SACR1

0

10

20

30

40

50

60

70

80

90

100

2 8 56 83 92 95 110 116 125 131 143 146 155 161 164 218 221 227 248 251 272 344 359 _ _ Avg

Julian Day in Worst 20% group

bEXT

(1/M

m) bCM

bSOILbECbOCbNO3bSO4

Bext Response (base18b - plan02c) at SACR1 on Worst 20% Days

-20

-15

-10

-5

0

5

10

2 8 56 83 92 95 110 116 125 131 143 146 155 161 164 218 221 227 248 251 272 344 359 Avg

Julian Day

Del

ta B

ext (

1/M

m) bCM

bSOILbECbOCbNO3bSO4

Uniform Rate of Reasonable Progress Glide PathSalt Creek - 20% Worst Days

18.0317.29

15.43

13.57

11.71

9.85

8.00

6.88

17.10

5

8

11

14

17

20

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haz

ines

s In

dex

(Dec

ivie

ws)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Additional Visibility Projection Metrics

• Need to assess Glide Paths for each component of visibility impairment except CM– SO4, NO3, EC, OC and Fine Soil– Adding PM species Natural Conditions as end point– Presenting Species glide paths analysis on AoH call 12/13

• More likely [be closer] to meet 2018 URP benchmark when looking at controllable (SO4 and NO3) extinction

• Need to analyze results of alternative methods more closely

Conclusions• The EPA Default (Annual Average ) and

alternative (Quarterly/Monthly Average) 2018 projection can be used to estimate visibility levels in 2018 for comparisons with the URP benchmark

• Additional PM species-specific Glide Paths and 2018 projections will be made to assess progress in reducing the “controllable” portion of haze

• Data will be used in Reasonable Progress determinations