Air Resource Specialists, Inc. 

VISTAS Conceptual Description Support Document 

Prepared for the: 

Visibility Improvement State and Tribal Association of the Southeast 

The Interchange Building 

59 Woodfin Place 

Asheville, North Carolina 28801 

Prepared by: 

Air Resource Specialists, Inc. 

1901 Sharp Point Drive, Suite E 

Fort Collins, Colorado 80525 

(970) 484-7941 

www.air-resource.com

September 20, 2007
TABLE OF CONTENTS 

Section Page

1.0 INTRODUCTION 1-1 

 1.1 Overview 1-1 

 1.2 Data Summary Product FTP Site 1-2 

2.0 ANALYTICAL METHODS 2-1 

 2.1 The IMPROVE Monitoring Network 2-1 

 2.2 Back Trajectory Modeling 2-5 

3.0 VISIBILITY CONDITIONS 3-1 

 3.1 Comparison of Old and New IMPROVE Algorithm 3-1 

 3.2 RHR Data Completeness 3-7 

 3.2.1 Additional Data Substitutions 3-7 

 3.2.1.1 Carbon Substitutions 3-10 

 3.2.1.2 Donor Site Substitutions 3-10 

 3.2.1.3 Data Completeness Following Substitutions 3-11 

 3.3 Extinction Trends 3-15 

 3.4 Baseline (2000-2004) and Natural (2064) Visibility Conditions 3-17 

 3.5 Glidepaths 3-28 

 3.6 Attribution Analysis 3-35 

 3.6.1 Back Trajectory Maps 3-35 

 3.6.2 Residence Time Maps 3-35 

 3.6.3 Extinction-Weighted Residence Time 3-36 

 3.6.4 International Contributions 3-37 

 

APPENDIX A Nephelometer Comparisons A-1 

APPENDIX B Original and Revised Algorithm Comparisons by Site B-1 

APPENDIX C File Key for Substituted Data C-1 

APPENDIX D Data Substitution Results for Individual Sites D-1 

APPENDIX E Extinction Trend Charts (Mm-1, DV and SVR) E-1 

APPENDIX F WinHaze Images (Baseline, 2018 and Natural Conditions) F-1 

i
APPENDIX G 2000-2004 Timelines G-1 

APPENDIX H DV Glidepaths H-1 

APPENDIX I Speciated Glidepaths I-1 

APPENDIX J Back Trajectory Maps J-1 

APPENDIX K Residence Time Maps K-1 

APPENDIX L International Attribution Plots L-1 

ii
LIST OF FIGURES 

Figure Page

2-1 Map of Class I Areas and IMPROVE Monitoring sites in and around VISTAS 2-1 

3-1 Comparison of Measured Light Scattering (Nephelometer) and Light Scattering 

 Calculated Using the Original (Old) and Revised (New) IMPROVE Algorithms 

 for the GRSM1 Site, 1993-2004 3-3 

3-2 Stacked bar chart comparing extinction calculated using the new IMPROVE 

 algorithm (left), the old IMPROVE algorithm (right), and measured light 

 scattering (grey line) in 2004 3-4 

3-3 Stacked bar chart comparing light extinction calculated using both the new (left) 

 and old (right) IMPROVE algorithm for the average of the 20% worst visibility 

 days in 2000-2004 at VISTAS and neighboring Class I areas 3-5 

3-4 Stacked bar chart comparing light extinction calculated using both the new (left) 

 and old (right) IMPROVE algorithm for the average of the 20% best visibility 

 days in 2000-2004 at VISTAS and neighboring Class I areas 3-5 

3-5 Stacked bar chart comparing 20% worst days in 2002 at the GRSM1 site 

 calculated using both the new (left) and old (right) IMPROVE algorithm 3-6 

3-6 Flow chart of data substitution methods used 3-9 

3-7 Comparison of OC and Estimated Organic H, and EC and OC at SHRO1, NC 

 Using Second Quarter Raw OC and Organic H Data, 2000-2004 3-10 

3-8 Comparison of Aerosol Species Mass Between SHRO1, NC (y-axis) and 

 GRSM1, TN (x-axis) 3-12 

3-9 2000-2004 annual bar charts indicating substituted data at the SAMA1 site 3-14 

3-10 10-year annual average extinction trends for sites in and around VISTAS 

 Blue triangles indicate decreasing trends and blank diamonds indicate 

 insignificant trends (p-value<0.20) 3-15 

3-11 10-year trend plots for a regional grouping of sites. Slopes and p-values are 

 indicated in the legend 3-16 

3-12 2000-2004 baseline conditions and 2018 projected conditions at the 

 GRSM1 site simulated using WinHaze Visual Air Quality Modeling program 3-19 

iii
LIST OF FIGURES (CONTINUED) 

Figure Page

3-13 2064 natural conditions at the GRSM1 site simulated using WinHaze Visual 

 Air Quality Modeling program 3-19 

3-14 Contributions to light extinction (Mm-1) for the average of the 20% worst 

 visibility days in 2000-2004 at VISTAS and neighboring Class I areas 3-22 

3-15 Contributions to light extinction (Mm-1) for the average of the 20% best 

 visibility days in 2000-2004 at VISTAS and neighboring Class I areas 3-22 

3-16 Contributions to mass (μg/m3

) for the average of the 20% worst visibility 

 days in 2000-2004 at VISTAS and neighboring Class I areas 3-23 

3-17 Contributions to mass (μg/m3

) for the average of the 20% best visibility 

 days in 2000-2004 at VISTAS and neighboring Class I areas 3-23 

3-18 Bar charts by year indicating speciation of all data collected at the GRSM1 site 3-24 

3-19 Bar charts by year indicating speciation of all data collected at the ROMA1 site 3-25 

3-20 Contributions to light extinction (Mm-1) for the 20% worst visibility days in 

 2000-2004 at the GRSM1 site 3-26 

3-21 Contributions to light extinction (Mm-1) for the 20% best visibility days in 

 2000-2004 at the GRSM1 site 3-26 

3-22 Contributions to light extinction (Mm-1) for the 20% worst visibility days in 

 2000-2004 at the ROMA1 site 3-27 

3-23 Contributions to light extinction (Mm-1) for the 20% best visibility days in 

 2000-2004 at the ROMA1 site 3-27 

3-24 DV Glidepaths for the GRSM1 site, calculated using both the original 

 IMPROVE algorithm using EPA default natural conditions (Default NB) 

 and the new IMPROVE algorithm using the revised estimate of natural 

 background conditions (NB2) 3-28 

3-25 DV Glidepaths for the ROMA1 site, calculated using both the original 

 IMPROVE algorithm using EPA default natural conditions (Default NB) 

 and the new IMPROVE algorithm using the revised estimate of natural 

 background conditions (NB2) 3-29 

3-26 Glidepath depicting total bext (Mm-1) for 20% worst days at the GRSM1 site 3-30 

iv
LIST OF FIGURES (CONTINUED) 

Figure Page

3-27 Glidepath depicting Ammonium Sulfate for 20% worst days at the GRSM1 site 3-31 

3-28 Glidepath depicting Ammonium Nitrate for 20% worst days at the GRSM1 site 3-31 

3-29 Glidepath depicting Particulate Organic Material for 20% worst days at the 

 GRSM1 site 3-32 

3-30 Glidepath depicting total bext (Mm-1) for 20% worst days at the ROMA1 site 3-32 

3-31 Glidepath depicting Ammonium Sulfate for 20% worst days at the ROMA1 site 3-33 

3-32 Glidepath depicting Ammonium Nitrate for 20% worst days at the ROMA1 site 3-33 

3-33 Glidepath depicting Particulate Organic Material for 20% worst days at the 

 ROMA1 site 3-34 

3-34 Back trajectories for the 20% Worst extinction days at the Great Smoky 

 Mountains National Park (GRSM1) IMPROVE monitoring site 3-35 

3-35 Residence times for 72-hour back trajectories with 100m end heights for 

 20% worst extinction days at the GRSM1 IMPROVE monitoring site 3-36 

3-36 Stacked bar charts of mass at the GRSM1 site depicting domestic and 

 international contributions to the 20% worst days in 2002 3-38 

3-37 Stacked bar charts for mass at the GRSM1 site depicting domestic and 

 international contributions to the 20% best days in 2002 3-38 

3-38 Stacked bar charts of mass at the ROMA1 site depicting domestic and 

 international contributions to the 20% worst days in 2002 3-39 

3-39 Stacked bar charts for mass at the ROMA1 site depicting domestic and 

 international contributions to the 20% best days in 2002 3-39 

v
LIST OF TABLES 

Table Page

1-1 Summary of Data Products Available on ARS VISTAS FTP Site 1-3 

2-1 IMPROVE Aerosol Monitor Sites in and around the VISTAS Region 2-2 

2-2 IMPROVE Aerosol Elements and Species Used to Reconstruct Light Extinction 2-3 

2-3 Back Trajectory Model Parameters 2-6 

3-1 RHR Data Completeness From IMPROVE Data Sets for 2000-2004 Baseline 

Years for Sites in and Around the VISTAS Region 3-8 

3-2 Data Completeness Following Data Substitution 3-13 

3-3 Baseline (2000-2004) and Natural Background Visibility Conditions 20% Worst 

Visibility Days 3-20 

 

3-4 Baseline (2000-2004) and Natural Background Visibility Conditions 20% Best 

Visibility Days 3-21 

vi
1.0 INTRODUCTION 

The primary purpose of this document is to provide data, results and methods 

documentation for analysis performed by Air Resource Specialists, Inc. (ARS) in support of the 

Visibility Improvement State and Tribal Association of the Southeast (VISTAS). 

Any questions or comments regarding contents of this report should be addressed to: 

Cassie Archuleta 

or 

Joe Adlhoch 

Air Resource Specialists, Inc.

1901 Sharp Point Drive, Suite E 

Fort Collins, Colorado 80525 

Telephone: 970-484-7941 

Fax: 970-484-3423 

carchuleta@air-resource.com

jadlhoch@air-resource.com

1.1 OVERVIEW 

VISTAS is a collaborative effort of state governments, tribal governments, and various 

federal agencies established to initiate and coordinate activities associated with the management 

of regional haze, visibility and other air quality issues in the Southeastern United States. VISTAS 

is working to develop the technical basis for the Regional Haze Rule (RHR) promulgated in 

1999 by the Environmental Protection Agency (EPA) to address visibility at 156 designated 

Class I areas. Specific objectives of analyses presented in this report to support the VISTAS 

states are: 

• To describe current visibility conditions and particulate matter concentrations at Class 

I areas in the VISTAS region. 

• To investigate the relative contributions of regional and local sources of emissions to 

fine particle concentrations and visibility in Class I areas. 

• To understand the rate of improvement in visibility that would demonstrate a uniform 

rate of progress toward visibility improvement goals between current visibility 

conditions and natural background visibility conditions in 2064. 

States and tribes are required to establish “reasonable progress goals” for each Class I 

area to improve visibility on the 20% haziest days and to prevent visibility degradation on the 

20% clearest days. States are to evaluate their contributions to visibility impairment at Class I 

areas both within and outside the State and to develop long-term control strategies to reduce 

emissions of air pollutants that impair visibility. The national goal is to return visibility to natural 

background levels by 2064. Using the period 2000 to 2004 as the baseline period, States are to 

evaluate progress in improving visibility by 2018 and every 10 years thereafter. State 

1-1 
Implementation Plans for the first phase of the regional haze regulation are due in December 

2007. 

1.2 DATA SUMMARY PRODUCT FTP SITE 

 Methods descriptions and analysis results are provided in this document. Analysis results 

for VISTAS are also available on the ARS VISTAS project public ftp site (ftp://ftp.airresource.com/VISTAS). Table 1-1 lists products currently available on the ftp site. 

1-2 
Table 1-1 

Summary of Data Products Available on ARS VISTAS FTP Site 

Sample Path Description 

[data files] ...Aerosol_dataset_VISTAS_2000-2004/ SAMA1_daily_budgets_sub_nia.xls Data sets including substituted data 

neighboring Class I Areas, old and algorithm. 

Average Extinction for 20% Worst Days

New IMPROVE Algorithm (nia)

2000-2004

0

50

100150200250300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm-1)

Sea SaltCMSoilECPOMAmm NO3Amm SO4Rayleigh

...Aerosol_stacked_bar_charts/ 

Average_BestWorstDays_2000-04/ 

VISTAS_nia_00-04_20070129.xls 

Regional stacked bar charts depictindays, extinction and mass, old and n

GRSM1

Baseline Extinction, nia

20% W > 142

0

100200300400

J-02 F-02 M-02 A-02 M-02 J-02 J-02 A-02 S-02 O-02 N-02 D-02

Extinction (Mm-1)

20% W > 140

0

100200300400

J-01 F-01 M-01 A-01 M-01 J-01 J-01 A-01 S-01 O-01 N-01 D-01

Extinction (Mm-1)

20% W > 139

0

100200300400

J-00 F-00 M-00 A-00 M-00 J-00 J-00 A-00 S-00 O-00 N-00 D-00

Extinction (Mm-1)

20% W > 139

0

100200300400

J-03 F-03 M-03 A-03 M-03 J-03 J-03 A-03 S-03 O-03 N-03 D-03

Extinction (Mm-1)

20% W > 130

0

100200300400

J-04 F-04 M-04 A-04 M-04 J-04 J-04 A-04 S-04 O-04 N-04 D-04

Extinction (Mm-1)

...Aerosol_stacked_bar_charts/ 

Timelines_AllDays_2000-04/ 

GRSM.pdf 

Stacked bar charts depicting extinctdays during the baseline years, 200sites requiring data substitution, twwhere the first page distinguishes suoriginal days. 

GRSM1

2000-2004 Reconstructed Extinction

New IMPROVE Algorithm

20% Worst Days

0

50

100150200250300350400450

3/8

5/6

5/17

6/3

6/10

6/28

7/1

7/8

7/22

8/5

8/16

8/19

8/23

8/26

10/15

10/18

10/21

10/24

10/27

11/2

5/1

5/7

6/9

6/12

6/21

6/27

7/3

7/12

7/18

7/21

7/24

7/30

8/2

8/5

8/8

8/11

8/14

8/17

8/23

8/26

9/7

9/13

9/19

11/18

2/25

5/2

5/8

5/17

6/1

6/13

6/19

6/22

7/1

7/7

7/10

7/16

7/22

7/31

8/3

8/6

8/9

8/12

8/15

8/21

9/5

9/8

9/11

9/17

3/16

4/27

5/24

5/27

6/5

6/11

6/26

6/29

7/5

7/17

7/20

7/26

8/7

8/10

8/16

8/19

8/22

8/25

8/28

9/3

9/6

9/9

9/12

9/21

1/10

2/21

6/8

6/11

6/20

6/26

6/29

7/8

7/17

7/20

7/29

8/4

8/10

8/16

8/19

8/25

8/28

8/31

9/3

9/12

9/15

9/30

10/3

10/30

2000 2001 2002 2003 2004

Extinction (Mm-1)

Sea SaltCMSoilLACPOMAmm NO3Amm SO4Rayleigh ...Aerosol_stacked_bar_charts/ 

Timelines_BestWorstDays_2000-04/ 

GRSM1_20bw_nia.xls 

Stacked bar charts that selectively sand worst days for 2000-2004 base

1-3 
GRSM1

Old and New IMPROVE Algorithm (oia/nia) Extinction by Species

20% Best Days (2002)

0

102030405060

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

1/8 1/11 1/14 1/23 2/1 2/7 2/19 2/28 3/3 3/9 3/30 4/26 7/13 9/14 9/26 10/26 10/29 11/4 11/16 11/22 12/7 12/13 12/22 Avg.

Extinction (Mm-1)

Rayleigh Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

...Aerosol_stacked_bar_charts/ 

Timelines_nia_oia_comparison_2002/ 

GRSM1_nia_oia.xls 

Regional and site specific stacked bextinction calculations using the nealgorithm are presented side by side

All Days

y = 0.93x + 9.16

R2 = 0.87

0

50

100150200250300

0 50 100 150 200 250 300

24-hr Nephelometer bsp (Mm-1)

24-hr Aerosol bsp (Mm-1)

Q4

y = 1.10x + 1.49

R2 = 0.96

0

50

100150200250300

0 50 100 150 200 250 300

Q1

y = 0.77x + 13.88

R2 = 0.48

0

50

100150200250300

0 50 100 150 200 250 300

Q2

y = 0.93x + 12.17

R2 = 0.81

0

50

100150200250300

0 50 100 150 200 250 300

Q3

y = 0.86x + 14.28

R2 = 0.82

0

50

100150200250300

0 50 100 150 200 250 300

-100

-75-50-25

0

255075

100

2000

2001

2002

2003

2004

Difference (Mm-1) 

(Aer. bsp - Neph. bsp

)

Aerosol Scattering vs. Nephelometer Scattering

Using New IMPROVE Algorithm (nia) and Daily f(RH)

GRSM, 2000 - 2004

...Nephelometer_Aeosol_Comparisons/ 

GRSM_neph.xls 

Charts comparing collocated IMRPand IMPROVE aerosol samplers, oIMPROVE algorithm. 

Glide Path to Natural Conditions (2004-2064)

(5-yr Rolling Average for 20% Haziest Days - New IMPROVE equation and NB II )

05

101520253035

1986-1990

1988-1992

1990-1994

1992-1996

1994-1998

1996-2000

1998-2002

2000-2004

2006

2008

2010

2012

2014

2016

2018

2020

2022

2024

2026

2028

2030

2032

2034

2036

2038

2040

2042

2044

2046

2048

2050

2052

2054

2056

2058

2060

2062

2064

Deciviews (dv)

Default Glide Path GRSM New Glide Path GRSMDefault 5-yr Rolling Avg GRSM New 5-yr Rolling Avg GRSMAnnual g90 - Old Annual g90 - New

 Base old Base new Default NB NB2 Great Smokey Mtns 28.8 30.3 11.4 dv 11.2 dv

...Glidepaths/ 

Revised Glide Path new IMPROVE 

equation_Reynolds.ppt 

Deviview Glidepaths (developed by species depicting baseline conditionnatural conditions for both the new 

GRSM1

Total Extinction

Glide Slope for 20% Worst Days

0

50

100150200250

2000

2002

2004

2018

2064

Extinction (Mm-1

)

Total BextBaselineGlide Slope2018 Base GNatural Conditions ...Glidepaths/ 

Speciated_Glidepaths/ 

Glideslopes_GRSM1.xls 

Glidepaths by species depicting basmodeled predictions and estimated 

1-4 
10 Year Temporal Trends

All Days

151719212325

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

DV

OKEF1 m = -0.13, p = 0.05ROMA1 m = -0.24, p = 0.06SWAN1 N/A (< 5 years)

10 Year Temporal Trends

20% Best Days

101214161820

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

DV

OKEF1 m = -0.05, p = 0.43ROMA1 m = -0.23, p = 0.02SWAN1 N/A (< 5 years)

10 Year Temporal Trends

20% Worst Days

202224262830

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

DV

OKEF1 m = -0.17, p = 0.01ROMA1 m = -0.28, p = 0.24SWAN1 N/A (< 5 years)

...IMPROVE_Trend_Charts/ 

Trends_DV.xls 

10 Year temporal trends for sites grincludes Standard Visual Range (SVand Mm-1. 

GRSM1

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

05

101520253035

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

2/25 5/2 5/8 5/17 6/1 6/13 6/19 6/22 7/1 7/7 7/10 7/16 7/22 7/31 8/3 8/6 8/9 8/12 8/15 8/21 9/5 9/8 9/11 9/17

Mass (μg/m

3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

...International_Attribution/ 

International_Attribution_mass_worst.xls 

Comparison of domestic and internmass on 20% best and worst days, 2

...Back_Trajectory_Analyis/ 

IMPROVE_ResidenceTimeMaps_2000-04_nia/ 

GRSM_2002_20high.bmp 

Back trajectory maps for 20% wors

GRSM1

2000-04

20% Worst Monitored Days

100m Residence Times (%)

< 0.01

0.01 - 0.020.02 - 0.040.04 - 0.080.08 - 0.160.16 - 0.32> 0.32 ...Back_Trajectory_Analyis/ 

IMPROVE_ResidenceTimeMaps_2000-04_nia/ 

GRSM_2002_20high.bmp 

Residence time maps for 20% wors

1-5 
2.0 ANALYTICAL METHODS 

2.1 THE IMPROVE MONITORING NETWORK 

The Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring 

program collects speciated PM2.5, and PM2.5 and PM10 total mass. IMPROVE is a nation-wide 

network which began in 1988 and expanded significantly in 2000 in response to the EPA’s 

Regional Haze Rule (RHR). It is data from this program that states and tribes must use to track 

progress under the RHR. 

The IMPROVE network collects 24-hour integrated filter samples every third day 

(Wednesdays and Saturdays prior to 2001). Each monitoring location operates four samplers 

(designated Module A through D) designed to quantify PM2.5 and PM10 mass, and PM2.5 mass 

constituents, including numerous trace elements, ions, Elemental Carbon (EC), and Organic 

Carbon (OC). 

 A map of the IMPROVE sites in and around the VISTAS region and their proximity to 

Class I areas is presented in Figure 2-1. A listing of IMPROVE sites, locations, and operational 

start dates is presented in Table 2-1. The list also includes start (and end) dates for collocated 

nephelometers, which are continuous monitoring instruments that make direct measurements of 

light scattering due to particles. 

IMPROVE Site

Federal Tribal

Class I Areas

BRET1

BRIG1

CACR1

CADI1

CHAS1

COHU1

DOSO1

EVER1

GRSM1

HEGL1

JARI1

LIGO1

MACA1

MING1

OKEF1

ROMA1

SAMA1

SHEN1

SHRO1

SIPS1

SWAN1

UPBU1

Figure 2-1. Map of Class I Areas and IMPROVE Monitoring sites in and around VISTAS. 

2-1 
Table 2-1 

IMPROVE Aerosol Monitor Sites in and around the VISTAS Region 

Region State Class I Area (Site) Start 

Date Latitude Longitude 

Nephelometer

Start Date 

( - End Date) 

AL Sipsy Wilderness (SIPS1) 3/92 34.34 -87.34 -- 

Chassahowitzka NWR 

(CHAS1) 4/93 28.75 -82.55 -- 

Everglades NP (EVER1) 9/88 25.39 -80.68 -- FL 

St. Marks (SAMA1) 6/00 30.09 -84.16 -- 

Cohutta (COHU1) 5/00 34.79 -84.63 1/04 – 3/07 GA 

Okefenokee NWR (OKEF1) 9/91 30.74 -82.13 1/93 – 6/97 

KY Mammoth Cave NP 

(MACA1) 9/91 37.13 -86.15 1/93 - current 

Linville Gorge (LIGO1) 3/00 35.97 -81.93 -- 

Shining Rock Wilderness 

(SHRO1) NC 7/94 35.39 -82.77 4/94 – 9/99 

Swanquarter (SWAN1) 6/00 35.45 -76.21 -- 

SC Cape Romain NWR 

(ROMA1) 9/94 32.94 -79.66 1/04 - current 

TN Great Smoky Mountains NP 

(GRSM1) 3/88 35.63 -83.94 4/93 - current 

James River Face Wilderness 

(JARI1) 6/00 37.63 -79.51 10/00 – 12/03 VA 

Shenandoah NP (SHEN1) 3/88 38.52 -78.43 1/00 - current 

VISTAS 

WV Dolly Sods Wilderness 

(DOSO1) 9/91 39.11 -79.43 10/93 – 12/97 

Caney Creek (CACR1) 6/00 34.45 -94.14 1/93 – 12/97 

9/04 - current AR 

Upper Buffalo Wilderness 

(UPBU1) 12/91 35.83 -93.20 -- 

LA Breton (BRET1) 6/00 29.12 -89.21 -- 

Hercules-Glades (HEGL1) 3/01 36.61 -92.92 -- MO 

Mingo (MING1) 5/00 36.97 -90.14 -- 

NonVISTAS 

NJ Brigantine NWR (BRIG1) 9/91 39.47 -74.45 -- 

The IMPROVE program has developed methods for estimating light extinction from 

speciated aerosol and relative humidity data. The three most common metrics used to describe 

visibility impairment are: 

• Extinction (bext) – Extinction is a measure of the fraction of light lost per unit length 

along a sight path due to scattering and absorption by gases and particles, expressed 

in inverse Megameters (Mm-1). This metric is useful for representing the contribution 

of each aerosol species to visibility impairment and can be practically thought of as 

the units of light lost in a million meter distance. 

• Visual Range (VR) – Visual range is the greatest distance a large black object can be 

seen on the horizon, expressed in kilometers (km) or miles (mi). 

2-2 
• Deciview (dV) – The deciview index was designed to be linear with respect to human 

perception of visibility. A one deciview change is approximately equivalent to a 10% 

change in extinction, whether visibility is good or poor. A one deciview change in 

visibility is generally considered to be the minimum change the average person can 

detect. This is the metric used for tracking regional haze in the RHR. 

The IMPROVE network estimates light extinction based upon the measured mass of 

various contributing aerosol species. EPA’s 2003 guidance 

(http://vista.cira.colostate.edu/improve/Publications/GuidanceDocs/guidancedocs.htm) for 

calculating light extinction is based on the original protocol defined by the IMPROVE program

in 1988. In December 2005, the IMPROVE Steering Committee voted to adopt a revised 

algorithm for use by IMPROVE as an alternative to the original approach. 

The elements and species measured by the IMPROVE network relevant for reconstructed 

light extinction are listed in Table 2-2. 

Table 2-2 

IMPROVE 

Aerosol Elements and Species 

Used to Reconstruct Light Extinction 

Species Composite Mass Algorithm * Comment 

Ammonium Sulfate 

[(NH4)2SO4] 

4.125× [S] 

-or1.375× [SO4] 

[S] is derived from the Teflon 

filter (A module). 

[SO4] is derived from the nylon 

filter (B module). 

Ammonium Nitrate 

[(NH4)NO3] 1.29× [NO3] [NO3] is derived from the nylon 

filter (B module). 

Particulate Organic Matter 

[POM] 

1.4× [OC] (original algorithm) 

1.8× [OC] (revised algorithm) 

[OC] is derived from the quartz 

filter (C module). 

Elemental Carbon [EC] 1.0[EC] [EC] is derived from the quartz 

filter (C module). 

Soil 

2.20× [Al] + 2.49× [Si] + 

1.63× [Ca] 

+ 2.42× [Fe] + 1.94× [Ti] 

Soil elements are derived from 

the Teflon filter (A module). 

Coarse Mass [CM] [PM10] - [PM2.5] 

[PM10] is derived from the 

Teflon filter (D module). 

[PM2.5] is derived from the 

Teflon filter (A module). 

Sea Salt (revised algorithm 

only) 

1.8× [Chl](Chloride) 

-or1.8×[Cl](Chlorine) 

[Chl] and [Cl] are derived from 

the Teflon filter (A module). 

[Cl] only used if {Chl] is below 

the detection limit. 

The original algorithm used by IMPROVE/regional haze guidance to reconstruct 

extinction (bext) is: 

2-3 
[ ]

[ ]

[ ]

[ ]

[ ]

[ ]

Rayleigh (10) Scattering

CM6.0

Soil Fine1

EC10

POM4

f(RH)3 Nitrate Amm.

f(RH)3b Sulfate Amm.

+

×+

×+

×+

×+

××+

ext ××≈

Reconstructed bext is expressed in Mm-1, dry extinction efficiencies (leading numbers) are 

expressed as m2/g and species mass concentrations are expressed in μg/m3. The f(RH) factor is a 

water growth term that is a function of climatologically representative monthly average relative 

humidity (RH). The f(RH) factors are designed to account for the absorption of water by sulfate 

and nitrate species. In the original IMPROVE algorithm, a constant value of 10 Mm-1 is also 

added to account for extinction due to scattering from molecules in a clean atmosphere (Rayleigh 

conditions). 

The original IMPROVE algorithm produces reasonable estimates of light scattering over 

a broad range of conditions, but it tends to underestimate the highest extinction values and 

overestimate the lowest extinction values. The revised algorithm for estimating light extinction 

recommended for use by the IMPROVE steering committee is: 

[ ] [ ]

[ ][

[ ][ ]

[ ]

[ ]

[ ]

[ ]

[ ]

Rayleigh Specific) (Site Scattering

(ppb)NO33.0

CM6.0

Salt Sea(RH)f7.1

Soil1

EC10

POM Large1.6POM Small8.2

(RH)f4.2 (RH)f1.5Nitrate Amm. Small Nitrate Amm. Large

(RH)f2.2b (RH)f8.4Sulfate Amm. Small Sulfate Amm. Large

2

ss

s L

s L

+

×+

×+

××+

×+

×+

×+ ×+

××+ ××+ ] ext ××≈ + × ×

The revised algorithm splits ammonium sulfate, ammonium nitrate, and POM 

concentrations into small and large size fractions as follows: 

[ ]

[ ] [ ] [ ]

[ ] [ ][

[ ] [ ][ ] μg/m20TotalFor Large, Total

Small Total Large

Total

20

Total Large

μg/m20TotalFor 

3

3

≥ =

⎪

⎪

⎩

⎪

⎪

⎨

⎧

−=

×=

<

]

As noted in table 2-2, the organic mass concentration is 1.8 times the organic carbon 

2-4 
mass concentration in the revised algorithm, where it was calculated as 1.4 times carbon mass in 

the original algorithm. The new algorithm contains three distinct water growth factors, 

designated fS(RH), fL(RH), and fSS(RH) for water absorption due small and large sulfate and 

nitrate fractions, and for sea salt, respectively. New terms have also been added for sea salt and 

for absorption by gaseous NO2. NO2 is not available at most IMPROVE sites, and is not 

included in analysis presented here. 

IMPROVE data are available on the IMPROVE Web site 

(http://vista.cira.colostate.edu/improve/) and the Visibility Information Exchange Web System 

(VIEWS) Web site (http://vista.cira.colostate.edu/views/). The starting data sets for analysis 

presented here are the IMPROVE RHR1 data set (updated 11/05), and the IMPROVE RHR2 

data set (updated 3/06), where RHR1 is the IMPROVE designation indicating that extinction was 

calculated using the original/old IMPROVE algorithm, and RHR2 indicates that extinction was 

calculated using the revised/new IMPROVE algorithm. 

VISTAS chose to use the new IMPROVE algorithm because it takes into account the 

most recent review of the science and because it is recommended by the IMPROVE Steering 

Committee. Comparisons between the old and new algorithm are presented in Section 3.1, but 

most analysis presented here uses the revised algorithm. 

2.2 BACK TRAJECTORY MODELING 

Back trajectory analyses were undertaken to identify the geographic source areas most 

likely to contribute to visibility impairment on the 20% worst visibility days at the Class I areas. 

Back trajectory analyses use interpolated measured or modeled meteorological fields to estimate 

the most likely central path over geographical areas that provided air to a receptor at a given 

time. The method essentially follows a parcel of air backward in hourly steps for a specified 

length of time. Back trajectories account for the impact of wind direction and wind speed on 

delivery of emissions to the receptor, but do not account for chemical transformation, dispersion 

and deposition of emissions. 

 Trajectories were generated using the Hybrid-Single Particle Lagrangian Integrated 

Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric 

Administration’s (NOAA) Air Resources Laboratory (ARL). HYSPLIT uses archived 3-

dimensional meteorological fields generated from observations and short-term forecasts. 

HYSPLIT can be run to generate forward or backward trajectories using several available 

meteorological data archives. 

 The data archives used in this analysis were the National Weather Service's National 

Centers for Environmental Prediction Eta Data Assimilation System (EDAS). The EDAS fields 

are archived by the ARL across the continental U.S., including a buffer zone, at a horizontal 

resolution of 80 km before 2004, and at a horizontal resolution of 40 km starting in 2004. 

Detailed information regarding the trajectory model and these data sets can be found on NOAA’s 

Web site (http://www.arl.noaa.gov/ready/hysplit4.html). 

 The major model parameters selected for these analyses are presented in Table 2-3. The 

choice of these parameters affects the trajectories generated and the final attribution analyses 

based on them. In particular, trajectories tend to become increasingly uncertain the further back 

in time they are used. Vertical motion in the model is sometimes best represented by following 

2-5 
actual vertical motion measurements (represented by model data), surfaces of constant entropy, 

or surfaces of constant pressure, depending on the meteorological conditions at a given location 

and time. The impact of receptor height (or end height) on an individual trajectory is also 

important. Low-ending trajectories represent air parcels nearer to ground level and high-ending 

trajectories may better represent boundary layer flow above the local terrain. Specific back 

trajectory analyses performed by ARS for VISTAS are described in Section 3.6.1. 

Table 2-3 

Back Trajectory Model Parameters 

Model Parameter: Value 

Trajectory duration 72 hours backwards in time 

Top of model domain 14,000 meters 

Vertical motion option used model data 

Meteorological Field EDAS 

End Times 0600, 1200, 1800 and 2400 EST 

End Heights 100 and 500 m 

2-6 
3.0 VISIBILITY CONDITIONS 

 The Regional Haze Rule sets a 60 year timeline for states to improve visibility within 

Federal Class I Areas (CIAs) from “baseline” (2000-2004) levels to “natural conditions” by 

2064. The following sections describe some of the major components for tracking reasonable 

progress at each CIA in the VISTAS region. Analyses include comparisons of the old and new 

IMPROVE algorithms, determination of baseline (2000-2004) conditions, determination of the 

glide slope between baseline and natural conditions, and determination of geographic source 

areas using back trajectory analysis. 

3.1 COMPARISON OF OLD AND NEW IMPROVE ALGORITHM 

One of the most compelling reasons for developing the revised IMPROVE algorithm was 

to reduce the biases in light scattering estimates at the high and low extremes, when compared to 

nephelometer measurements. Nephelometers make a direct measurement of light scattering due 

to particles and are collocated with the IMPROVE aerosol samplers at some IMPROVE sites. 

These measurements can be compared to light scattering derived from the particulate data. 

Figure 3-1 presents scatter plots for the GRSM1 site comparing measured light scattering 

(nephelometer) and reconstructed light scattering calculated using the revised (New) and original 

(old) IMPROVE algorithms. A stacked bar chart for the most recent year of comparable record, 

in this case 2004 at the GRSM1 site, is included in Figure 3-2. Nephelometers make continuous 

hourly measurements of light scattering and RH. For these comparisons hourly nephelometer 

scattering is averaged into daily values, and aerosol light scattering is calculated using daily 

f(RH) based upon measured RH, as opposed to the IMPROVE method of using climatologically 

representative monthly average RH. Also light absorbing carbon (LAC) is not included in the 

reconstructed extinction because nephelometers measure atmospheric scattering but do not 

measure atmospheric absorption. For reconstructed extinction, coarse mass scattering was also 

scaled by a factor of 0.5 to account for the tendency of a nephelometer to underestimate coarse 

mass scattering. Charts are included for each VISTAS nephelometer site in Appendix A for both 

the total available data set and each quarter separately. 

The GRSM1 site has one of the longest periods of nephelometer data in the VISTAS 

region, and has been in operation since 1993. In general, the original algorithm tends to under 

estimate light scattering on those days with high scattering and over estimate scattering on days 

with low values. The new algorithm is more accurate as it does not have the same biases, but the 

data is less precise, with more spread in the data and generally slightly lower correlation.

Figures 3-3 and 3-4 present comparisons of the average 20% worst and best days in the 

2000-2004 baseline period at VISTAS and neighboring sites calculated using both the revised 

and original IMPROVE algorithm. For the worst days, extinction calculations using the new 

algorithm are higher than extinction calculations using the old algorithm Difference in total 

extinction range between 8 Mm-1 (BRET1) and 35 Mm-1 (MACA1). For the best days, the 

calculated extinction values were within 3 Mm-1 of each other. 

Figure 3-5 presents a comparison of the 20% worst days in 2002 at the GRSM1 site 

3-1 
calculated using both the new and old IMPROVE algorithm. The 20% best and worst days are 

very similar using either the original and revised algorithms. In the case of GRSM1, 9/23 was a 

worst day in 2002 using the old algorithm, but this one day is traded for 7/22 when extinction is 

calculated using the new algorithm. Other days change in magnitude, but the same days are still 

counted among the 20% worst days. Additional plots comparing extinction calculated using the 

old and new IMPROVE algorithms for 20% best and worst days in 2002 at all VISTAS sites are 

available in Appendix B. 

3-2 
Old Algorithm

y = 0.71x + 14.70

R2 = 0.89

0

50

100150200250300

0 50 100 150 200 250 300

24-hr Nephelometer bsp (Mm-1)

24-hr Aerosol b sp (Mm-1)

New Algorithm

y = 0.98x + 5.97

R2 = 0.87

0

50

100150200250300

0 50 100 150 200 

24-hr Nephelometer bsp (

24-hr Aerosol bsp (Mm-1)

Figure 3-1. Comparison of measured light scattering (nephelometer) and light scattering calculated using the originaIMPROVE algorithms for the GRSM1 site, 1993-2004. 

3-3 
0

50

100150200250

1/1

1/4

1/7

1/13

1/16

1/19

1/22

1/28

1/31

2/9

2/21

2/24

3/1

3/4

3/7

3/10

3/13

3/19

3/22

3/25

3/28

4/3

4/6

4/9

4/15

4/18

4/21

4/24

4/27

4/30

5/9

5/12

5/15

5/21

5/24

5/27

5/30

6/2

6/5

6/11

6/14

6/17

6/20

6/29

7/5

7/8

7/11

7/23

7/29

8/1

8/4

8/7

8/10

8/16

8/19

8/25

8/28

9/3

9/6

9/12

9/15

9/18

9/21

9/24

9/27

10/6

10/9

10/15

10/18

10/27

Extinction (Mm-1)

Amm SO4 Amm NO3 POM Soil CM Sea Salt 

Figure 3-2. Stacked bar chart comparing extinction calculated using the new IMPROVE algorithm(left), the old IMP(right), and measured light scattering (grey line) in 2004. 

3-4 
0

50

100

150

200

250

300

SWAN1ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm-1)

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-3. Stacked bar chart comparing light extinction calculated using both the new (left) and 

old (right) IMPROVE algorithm for the average of the 20% worst visibility days in 2000-2004 at 

VISTAS and neighboring Class I areas. 

 

0

10

20

30

40

50

60

SWAN1ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm-1)

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-4. Stacked bar chart comparing light extinction calculated using both the new (left) and 

old (right) IMPROVE algorithm for the average of the 20% best visibility days in 2000-2004 at 

VISTAS and neighboring Class I areas.

3-5
GRSM1

Old and New IMPROVE Algorithm (oia/nia) Extinction by Species

20% Worst Days (2002)

0

50

100150200250300350400

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

oia

nia

2/25 5/2 5/8 5/17 6/1 6/13 6/19 6/22 7/1 7/7 7/10 7/16 7/22 7/31 8/3 8/6 8/9 8/12 8/15 8/21 9/5 

Extinction (Mm-1)

Rayleigh Amm SO4 Amm NO3 POM LAC Soil CM Sea S

Figure 3-5. Stacked bar chart comparing 20% worst days in 2002 at the GRSM1 site calculated using both the new (

IMPROVE algorithm. 

3-6 
3.2 RHR DATA COMPLETENESS 

Once extinction has been calculated for each species at a monitoring site, the Regional 

Haze Rule provides some provisions for handling missing data. Treatment of missing data is 

necessary because the RHR requires that the baseline period average (2000-2004) contain at least 

3 complete years of data. RHR guidance requirements for IMPROVE aerosol data completeness 

include the following conditions: 

• Individual samples must contain all species required for the calculation of light 

extinction (sulfate, nitrate, organic carbon, elemental carbon, soil, coarse mass, and, 

for the new IMPROVE algorithm, chloride or chlorine) 

• Individual seasons must contain at least 50% of all possible daily samples 

• Individual years must contain at least 75% of all possible daily samples 

• Individual years must not contain more than 10 consecutive missing daily samples 

• The baseline period (2000-2004) must contain at least 3 complete years of data 

 RHR guidelines provide provisions to fill in missing data under specific circumstances. 

There are currently two methods routinely used in preparing the RHR data set to substitute data 

for missing samples: 

• The use of a surrogate in the data set: 

− Total sulfate is generally determined as 3 times the sulfur measured on the A 

module filter. If sulfur is missing, the sulfur measurement from the B module 

filter is used to calculate sulfate. 

− For the new IMPROVE algorithm, sea salt is calculated from chloride measured 

on the B module filter. If chloride is missing or below detection limit, the 

chlorine measurement from the A module filter is used to calculate sea salt. 

• The application of “patching” missing data described by the RHR guidance: 

− Missing samples not substituted using a surrogate as described above can be 

patched, or replaced, by a seasonal average if the patching exercise passes a series 

of tests outlined in the guidance document. 

Once these methods have been applied to the data, the resulting complete years are 

eligible for use in calculation of baseline conditions and tracking progress under the RHR. 

Further details can be found in the RHR guidance document for tracking progress 

(http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_tpurhr_gd.pdf). 

3.2.1 Additional Data Substitutions

Table 3-1 summarizes data completeness for the 2000-2004 baseline years for IMPROVE 

3- 7 
sites in and around the VISTAS region. After routine RHR data substitutions, five IMPROVE 

monitoring sites in the VISTAS states (CHAS1, SAMA1, COHU1, SHRO1 and SWAN1), and 

two regional site (BRET1 and MING1) did not achieve RHR data completeness requirements. 

VISTAS performed additional data substitutions for these sites. Additional substitutions 

included estimating missing species from other on-site measurements and appropriately scaling 

data collected at selected donor sites which had favorable long-term comparisons. Additional 

substitutions were also made for the CHAS1 site, because it is the only VISTAS site that met 

RHR baseline period requirements, but still had 2003 and 2004 as incomplete years. Additional 

substitutions for the MING1 site were performed separately by UCDavis. Details of data 

substitutions performed by ARS for VISTAS are outlined below. 

Table 3-1 

RHR Data Completeness From IMPROVE Data Sets for 2000-2004 Baseline Years 

for Sites in and Around the VISTAS Region 

Region State Site 2000 2001 2002 2003 2004 2000-04 

Count 

AL SIPS1 0 1 1 1 1 4 

CHAS1 1 1 1 0 0 3 

FL EVER1 0 1 1 1 1 4 

SAMA1* 0 0 1 1 0 2 

COHU1* 0 0 1 0 1 2 GA OKEF1 1 1 1 1 1 5 

KY MACA1 1 1 1 1 1 5 

LIGO1 0 1 1 1 1 4 

NC SHRO1* 0 0 0 1 1 2 

SWAN1* 0 1 1 0 0 2 

SC ROMA1 1 1 1 1 1 5 

TN GRSM1 1 1 1 1 1 5 

JARI1 0 1 1 1 1 4 VA SHEN1 1 1 1 1 1 5 

VISTAS 

WV DOSO1 1 1 1 1 1 5 

CACR1 0 0 1 1 1 3 AR 

UPBU1 1 1 1 1 1 5 

LA BRET1* 0 0 0 0 0 0 

HEGL1 0 0 1 1 1 3 MO MING1* 0 1 0 0 0 1 

NonVISTAS 

NJ BRIG1 1 1 1 1 1 5 

* Indicates site has <3 complete years for RHR baseline calculations 

0 indicates an incomplete year with no substitutions made 

1 indicates a complete RHR year 

 Figure 3-6 presents a flow chart of the VISTAS data substitution methods, and details for 

these methods are described below. The starting data set was the RHR2 IMPROVE data using 

the new IMPROVE algorithm. This data set includes the routine surrogate and patched data 

3- 8 
substitutions allowed by RHR guidance. Note that only years deemed incomplete under RHR 

guidance were candidates for additional data substitutions. Years deemed complete were not 

changed, even thought there may have been missing individual samples during those years. 

Start with IMPROVE RHR dataset

(daily_budgets_nia_20060306.csv)

3 complete years

(including 2003/2004)?

Check year

for completeness

Substitute OC based on Organic H,

and EC based on OC

(use raw data linear regression statistics)

For each missing year,

check each incomplete day

Final Data

Set

Substitute missing species from

a nearby donor site

(use raw data linear regression statistics)

yes

Check year

for completeness

no

yes

yes

no

no

Year remains incomplete

Figure 3-6. Flow chart of data substitution methods used. 

3- 9 
3.2.1.1 Carbon Substitutions 

 The first substitution method relied on using a surrogate for carbon mass measurements 

when the C module data was not available. Hydrogen (H) is measured on the A module filter, 

and is assumed to be primarily associated with organic carbon and inorganic compounds such as 

ammonium sulfate. Organic carbon (OC) can be estimated using the historical comparison 

between estimated organic H and OC. Organic H is estimated by subtracting the portion of H 

that is assumed to be associated with the inorganic compounds from the total H (Org_H = H – 

0.24*S). Once OC has been estimated using this method, elemental carbon (EC) mass is 

determined using long-term comparisons between OC and EC at the site. 

Figure 3-7 presents sample comparisons for data collected at the Shining Rock 

Wilderness Area (SHRO1) site in North Carolina during the second quarter between 2000-2004 

for OC vs. organic H, and EC vs. OC. Statistics were calculated and applied quarterly to account 

for seasonal variations. 

Q2

r2 = 0.55

0

2

4

6

8

10

0.0 0.2 0.4 0.6 0.8 1.0

org_H (μg/m3)

OC (μg/m3)

Q2

r2 = 0.65

0.0

0.2

0.4

0.6

0.8

1.0

0 2 4 6 8 10

OC (μg/m3)

EC (μg/m3)

Figure 3-7. Comparison of OC and Estimated Organic H, and EC and OC at SHRO1, NC 

Using Second Quarter Raw OC and Organic H Data, 2000-2004 

3.2.1.2 Donor Site Substitutions 

In VISTAS, the carbon data substitution methods were not sufficient to complete the 

required years. A second method involved identification of another nearby IMPROVE site (or, 

in the case of BRET1, a nearby SEARCH site) which had the most favorable long-term 

comparisons and similar regional characteristics to be used as a donor site. 

Figure 3-8 presents a sample inter-site mass comparison by species for data collected 

during the second quarter, 2000-2004, between the Shining Rock Wilderness Area (SHRO1) site 

and the Great Smoky Mountains National Park (GRSM1) site in Tennessee. Component specific 

correlations were calculated and applied quarterly. Note that only species missing in a given 

sample were substituted based on donor site data. Species collected at the site were not replaced 

with data from a donor site. 

3- 10
For BRET1 substitutions, chloride/chlorine was not available from the GFP SEARCH 

site. In this case, sea salt could not be calculated from the GFP data, so seasonal averages of sea 

salt from the BRET1 site were used as substitutes. Missing coarse mass at the SEARCH site was 

also substituted using SEARCH methodologies prior to use as a donor for the BRET1 site. 

3.2.1.3 Data Completeness Following Substitutions 

Table 3-2 indicates the years that required some degree of substitution, where a 2 

indicates a substituted year, a 1 indicates the year was already complete under RHR guidelines, 

and dashes indicate the year did not meet RHR guidelines and no additional substitutions were 

made. The table also lists sites that were selected as donor sites. The minimum data requirement 

of 3 complete years was met for each site, and additional substitutions beyond these 

requirements were made with the exception of the year 2000, which was not substituted at any 

site either because monitoring started in late 2000, or the additional substitutions did not fill in 

enough data to make a complete RHR year. 

Figure 3-9 presents bar charts by year for the SAMA1 site depicting substituted data. 

The original RHR data is indicated in blue, and substituted data by species in specific colors. 

Substituted days are also indicated by a black bar underneath the day. The red line indicates the 

threshold above which days are counted in the 20% worst days for that year. A red line is not 

included for any year that was incomplete and not substituted. In the case of SAMA1, 

substitutions were made for the years 2001 and 2004. In 2001, data from the CHAS1 site was 

scaled and substituted for about 33% of monitored days, mostly for mid-April through May, and 

August through mid-September. In 2004, about 34% of the days have some degree of 

substitution, but most of these days only required the OC/EC substitutions from the organic H 

collected at the SAMA1 site. The substituted days are mostly between June and November, but 

only a very small portion of extinction for these days was substituted with most data being 

salvaged from the samples actually collected at the site. 

The substituted data are available on the VIEWS website, 

http://vista.cira.colostate.edu/views/web/documents/substitutedata.aspx, and a key for the 

substituted data files is included in Appendix C. Additional charts and tables for all VISTAS 

substituted sites are included in Appendix D. 

3- 11
Q2

r2 = 0.68

0

10

20

30

40

50

0 10 20 30 40 50

AmmSO4 (μg/m3)

AmmSO4 (μg/m3)

Q2

r2 = 0.62

0

1

2

3

4

5

012345

AmmNO3 (μg/m3)

AmmNO3 (μg/m3)

Q2

r2 = 0.6

0

2

4

6

8

10

0 2 4 6 8 10

OC (μg/m3)

OC (μg/m3)

Q2

r2 = 0.49

0.0

0.5

1.0

1.5

2.0

2.5

0.0 0.5 1.0 1.5 2.0 2.5

LAC (μg/m3)

LAC (μg/m3)

Q2

r2 = 0.8

0

1

2

3

4

5

012345

Soil (μg/m3)

Soil (μg/m3)

Q2

r2 = 0.73

0

5

10

15

20

0 5 10 15 20

CM (μg/m3)

CM (μg/m3)

 Figure 3-8. Comparison of Aerosol Species Mass Between SHRO1, NC (y-axis) and GRSM1, 

TN (x-axis).

3- 12
 

Table 3-2 

Data Completeness Following Data Substitution 

State Site Donor 

Site 2000 2001 2002 2003 2004 2000-04 Count 

CHAS1 SAMA1 1 1 1 2 2 5 FL SAMA1* CHAS1 -- 2 1 1 2 4 

GA COHU1* GRSM1 -- 2 1 2 1 4 

SHRO1* GRSM1 -- 2 2 1 1 4 NC SWAN1* ROMA1 -- 1 1 2 2 4 

LA BRET1* GFP -- 2 2 2 2 4 

-- indicates an incomplete year with no substitutions made 

 1 indicates a complete RHR year 

 2 indicates a year is considered complete with some substituted values 

3- 13
SAMA1 (CHAS1 donor)

Baseline Extinction, New IMPROVE Algorithm

20% W > 105

0

50

100

150

200

J-02

F-02

M-02

A-02

M-02

J-02

J-02

A-02

S-02

O-02

N-02

D-02

Extinction (Mm-1)

0 ■ ■ ■ ■■■■■■■■■■■■■■■■■■■ ■ ■ ■■ ■■■■■■■■■■ ■■■ ■

50

100

150

200

J-01

F-01

M-01

A-01

M-01

J-01

J-01

A-01

S-01

O-01

N-01

D-01

Extinction (Mm-1)

20% W > 101

0

50

100

150

200

J-00

F-00

M-00

A-00

M-00

J-00

J-00

A-00

S-00

O-00

N-00

D-00

Extinction (Mm-1)

20% W > 109

0

50

100

150

200

J-03

F-03

M-03

A-03

M-03

J-03

J-03

A-03

S-03

O-03

N-03

D-03

Extinction (Mm-1)

0 ■■■■■■■ ■ ■■■■■■■■■■■■■■■■■■■■ ■■■■■■■■■■■■■

50

100

150

200

J-04

F-04

M-04

A-04

M-04

J-04

J-04

A-04

S-04

O-04

N-04

D-04

Extinction (Mm-1)

20% W > 117

Figure 3-9. 2000-2004 annual bar charts indicating substituted data at the SAMA1 site. RHR 

data are indicated in blue, and substituted data by species in specific colors. Substituted days are 

also indicated by a black bar underneath the day. The red line indicates the threshold above 

which days are counted in the 20% worst days for that year. 

3- 14
3.3 EXTINCTION TRENDS 

10-year extinction trends for the period 1995-2004 were computed for each site that had 

at least 5 years of complete data. Emissions reductions were implemented in the eastern US 

during this period under the Acid Rain provisions of the 1990 Clean Air Act Amendments and 

under the NOx SIP call for ozone. Theil slopes were calculated to determine the trend, and pvalues were calculated using Mann-Kendall trend analysis to determine the significance of each 

slope. Lower p-values indicate higher confidence levels in the computed slopes. 

Figure 3-10 is a map indicating 10-year annual average extinction trends for sites with at 

least 5 years of complete data. For sites in and around VISTAS, the BRIG1 and SHEN1 sites 

indicated insignificant trends (p-value < 0.20) and 8 sites showed decreasing trends (using pvalue<0.20 as indicator ). No sites indicated increasing trends. 

Figure 3-11 presents 10-year trend plots for a regional group of sites. The legend 

indicates the slope and p-value for the 20% worst days, 20% best days, and all monitored days. 

For these plots the GRSM1 and SHRO1 sites were the only sites with sufficient data for trend 

calculation, but annual observations for other sites are included on the plot for reference. 

Additional trend plots for other regional groupings of sites are included in Appendix E, 

represented in terms of SVR, dV and Mm-1. 

+4 Mm-1

+2 Mm-1

Insig. Trend

-2 Mm-1

-4 Mm-1

<5 years

Total

Extinction Trends

IMPROVE

1995-2004

Light Extinction

Change Per Year

BRIG1

SHEN1

CHAS1

DOSO1

GRSM1

MACA1

OKEF1

ROMA1

SHRO1

UPBU1

Figure 3-10. 10-year annual average extinction trends for sites in and around VISTAS Blue 

triangles indicate decreasing trends and blank diamonds indicate insignificant trends (pvalue<0.20). No sites showed increasing trends. 

3- 15
10 Year Temporal Trends

All Days

0

20

40

60

80

100

120

140

1995199619971998199920002001200220032004

TBext (Mm-1)

LIGO1

 N/A (< 5 years)

GRSM1

 m = -1.52, p = 0.01

SHRO1

 m = -1.62, p = 0.20

COHU1

 N/A (< 5 years)

SIPS1

 N/A (< 5 years)

10 Year Temporal Trends

20% Best Days

0

10

20

30

40

50

60

1995199619971998199920002001200220032004

TBext (Mm-1)

LIGO1

 N/A (< 5 years)

GRSM1

 m = -0.65, p = 0.19

SHRO1

 m = -0.54, p = 0.09

COHU1

 N/A (< 5 years)

SIPS1

 N/A (< 5 years)

10 Year Temporal Trends

20% Worst Days

0

50

100

150

200

250

300

1995199619971998199920002001200220032004

TBext (Mm-1)

LIGO1

 N/A (< 5 years)

GRSM1

 m = -6.77, p = 0.00

SHRO1

 m = -4.61, p = 0.20

COHU1

 N/A (< 5 years)

SIPS1

 N/A (< 5 years)

Figure 3-11. 10-year trend plots for a regional grouping of sites. Slopes and p-values are 

indicated in the legend. 

3- 16
3.4 BASELINE (2000-2004) AND NATURAL (2064) VISIBILITY CONDITIONS 

Baseline (2000-2004) visibility conditions were determined using the new revised 

IMPROVE algorithm to select the 20% worst and best visibility days, and using VISTAS 

substituted data when appropriate. 

Natural background visibility as defined in EPA guidance 

(http://vista.cira.colostate.edu/views/Web/RHR/RHR_Planning.aspx) is based on annual average 

concentrations of fine particle components. The same annual average natural background mass 

concentrations are assumed for all Class I areas in the eastern US (separate values are estimated 

for the western US). Natural background visibility for the 20% worst days is estimated by 

assuming that fine particle concentrations for natural background are normally distributed and 

the 90th percentile of the annual distribution represents natural background visibility on the 20% 

worst days. These assumptions are somewhat over simplified because the distribution of 

visibility conditions is likely not a normal distribution and the 92nd percentile of a normal 

distribution would be a better representation of the mean of the 20% worst days than the 90th

percentile16. EPA’s guidance did not estimate the contributions of individual fine particle 

components to natural background visibility on the 20% worst days. Following development of 

the new IMPROVE algorithm, a workgroup under the IMPROVE Steering Committee 

recommended revised assumptions to estimate natural background visibility on the 20% worst 

days (http://vista.cira.colostate.edu/TSS/Tools/WOEChecklist.aspx). For each Class I area, the 

natural background distribution of each fine particle component is assumed to be the same as the 

current (2000-2004) distribution of that component. Original errors in NC2 calculations were 

corrected by Scott Copeland, USFS, in August, 2007. 

For visualization purposes, haze conditions using images available for several of the 

VISTAS sites were simulated using ARS’ WinHaze Visual Air Quality Modeler (Ver. 2.9.6). 

Figure 3-12 presents a spit image depicting simulated baseline conditions and 2018 projected 

conditions at the GRSM1 site. There is a discernable difference in visibility between these time 

periods. Figure 3-13 depicts the estimated natural conditions goal for the GRSM1 site. These 

images were not generated using Scott Copeland’s revised numbers. Images for all VISTAS 

sites available through the WinHaze program (12 sites) are included in Appendix F. 

Tables 3-3 and 3-4 present the average baseline conditions for individual species, 

including the percent contribution to aerosol extinction (Rayleigh not included), and 2064 natural 

condition estimates generated using the revised calculations discussed in Section 2.5, updated in 

August, 2007. Figures 3-14 and 3-15 present stacked bar charts indicating species contributions 

to light extinction (Mm-1) for the average of the 20% worst and best visibility days for 2000-

2004 at VISTAS regional sites. Figures 3-16 and 3-17 indicate species contribution to mass 

(μg/m3

) on the 20% worst and best extinction days. 

Ammonium sulfate is the largest contributor to visibility impairment on the 20% haziest 

days in the baseline 2000-2004 period (69-74%) at all the IMPROVE sites in the VISTAS region 

except Everglades National Park in Florida, where Ammonium sulfate is a close second to 

Particulate Organic Material, POM (40 and 45%, respectively). Particulate Organic Material 

(also referred to as organic carbon) is the second largest contributor to aerosol extinction at all 

other sites, contributing to between 13 and 18% of aerosol extinction on the worst days. 

Baseline conditions for 20% worst days at the inland sites (182.2 - 241.4 Mm-1) average higher 

3- 17
than conditions measured at the coastal sites (116.4 - 147.3 Mm-1). 

Ammonium sulfate is also the largest contributor to visibility impairment on the 20% best 

days (45-59%), with large contributions from ammonium nitrate (9-21%) POM (11-19%). Sea 

salt is not a factor on the 20% worst days, but for the 20% best days it contributes to between 2 

and 7% of the aerosol extinction at the VISTAS coastal sites. 

Ammonium sulfate, CM and POM are the largest contributors to total mass on the 20% 

best and worst days. CM, although it is a factor for total mass, has a low extinction efficiency 

and does not contribute significantly to aerosol extinction. Ammonium sulfate contributes more 

significantly to aerosol extinction because it readily absorbs water vapor in the air. 

Figures 3-18 and 3-19 present stacked bar charts including all samples days at the 

GRSM1 and ROMA1 sites in the 2000 through 2004 baseline period. The red line is a threshold 

line, above which days are counted in the 20% worst days. Figures 3-20 and 3-21 select just the 

20% worst and best days at the GRSM1 site, and Figures 3-22 and 3-23 select the 20% worst and 

best visibility days at the ROMA1 site. The same charts are presented for additional Class I 

areas in Appendix G.

For the GRSM1 site, the 20% haziest days are most likely to occur in the summer, and 

the 20% best days occur most frequently during the winter. For coastal ROMA1 site, the 20% 

haziest days can occur year round, with the summer days being dominated by ammonium sulfate, 

while the worst days that occur between October and February have large contributions from 

ammonium sulfate, POM and sometimes ammonium nitrate. 

3- 18
2000-04 Baseline

216.3 Mm-1

2018 Projected

113.6 Mm-1

Figure 3-12. 2000-2004 baseline conditions and 2018 projected conditions at the GRSM1 site 

simulated using WinHaze Visual Air Quality Modeling program. 

2064 Natural Conditions

31.3 Mm-1

Figure 3-13. 2064 natural conditions at the GRSM1 site simulated using WinHaze Visual Air 

Quality Modeling program. 

3- 19
Table 3-3 

Baseline (2000-2004) and Natural Background Visibility Conditions 

20% Worst Visibility Days 

2000-04 Component Extinction (Mm-1) 

(% of aerosol extinction) 2000-04 Baseline 2064 Natural Conditions 

Site 

Amm. 

SO4

Amm. 

NO3

POM LAC Soil CM Sea 

Salt 

bext

(Mm-1) dV VR (km) 

bext

(Mm-1) dV 

SWAN1 83.5 

(74%) 

5.8 

(5%) 

14.8 

(13%) 

3.7 

(3%) 

0.6 

(1%) 

3.5 

(3%) 

0.2 

(0%) 124.2 24.7 31.5 32.6 11.5 

ROMA1 96.5 

(71%) 

5.3 

(4%) 

23.8 

(18%) 

5.7 

(4%) 

0.6 

(0%) 

3.2 

(2%) 

0.2 

(0%) 147.3 26.5 26.6 34.2 12.1 

OKEF1 102.9 

(69%) 

4.9 

(3%) 

30.3 

(20%) 

6.2 

(4%) 

0.8 

(1%) 

3.1 

(2%) 

0.2 

(0%) 159.4 27.1 24.5 31.7 11.2 

EVER1 42.5 

(40%) 

4.8 

(5%) 

47.1 

(45%) 

5.9 

(6%) 

0.9 

(1%) 

3.0 

(3%) 

1.2 

(1%) 116.4 22.3 33.6 42.7 12.1 

CHAS1 87.6 

(71%) 

5.2 

(4%) 

20.7 

(17%) 

6.7 

(5%) 

0.9 

(1%) 

3.0 

(2%) 

0.2 

(0%) 135.2 25.8 28.9 30.5 11.0 

VISTAS coastal 

SAMA1 93.1 

(71%) 

4.5 

(3%) 

24.2 

(18%) 

5.6 

(4%) 

0.8 

(1%) 

2.6 

(2%) 

0.2 

(0%) 142.1 26.3 27.5 33.1 11.7 

DOSO1 160.5 

(87%) 

3.4 

(2%) 

13.4 

(7%) 

4.7 

(3%) 

0.8 

(0%) 

1.7 

(1%) 

0.1 

(0%) 194.6 29.0 20.1 28.4 10.4 

SHEN1 155.5 

(83%) 

5.8 

(3%) 

16.1 

(9%) 

5.7 

(3%) 

0.7 

(0%) 

2.5 

(1%) 

0.1 

(0%) 196.5 29.3 19.9 32.3 11.4 

JARI1 136.4 

(76%) 

7.8 

(4%) 

22.8 

(13%) 

7.4 

(4%) 

0.8 

(0%) 

3.0 

(2%) 

0.2 

(0%) 189.5 29.1 20.6 30.8 11.1 

LIGO1 146.0 

(85%) 

2.3 

(1%) 

16.1 

(9%) 

5.2 

(3%) 

0.8 

(0%) 

2.2 

(1%) 

0.1 

(0%) 183.6 28.8 21.3 30.9 11.2 

SHRO1 149.0 

(87%) 

2.7 

(2%) 

14.6 

(8%) 

3.6 

(2%) 

0.9 

(0%) 

1.3 

(1%) 

0.1 

(0%) 182.2 28.5 21.5 31.8 11.5 

GRSM1 172.7 

(84%) 

3.4 

(2%) 

20.6 

(10%) 

5.7 

(3%) 

0.8 

(0%) 

1.9 

(1%) 

0.2 

(0%) 216.3 30.3 18.1 30.8 11.1 

COHU1 171.6 

(84%) 

3.5 

(2%) 

22.1 

(11%) 

5.1 

(2%) 

1.0 

(0%) 

1.8 

(1%) 

0.1 

(0%) 216.0 30.3 18.1 29.8 10.8 

SIPS1 133.0 

(75%) 

8.5 

(5%) 

24.0 

(14%) 

6.5 

(4%) 

0.8 

(0%) 

3.2 

(2%) 

0.3 

(0%) 187.3 29.0 20.9 30.1 10.9 

VISTAS inland 

MACA1 188.9 

(82%) 

9.7 

(4%) 

22.3 

(10%) 

6.2 

(3%) 

0.9 

(0%) 

2.2 

(1%) 

0.1 

(0%) 241.4 31.4 16.2 30.7 11.1 

BRIG1 127.1 

(70%) 

15.7 

(9%) 

24.2 

(13%) 

7.0 

(4%) 

1.0 

(1%) 

5.4 

(3%) 

0.4 

(0%) 192.7 29.0 20.3 35.7 12.1 

BRET1 97.0 

(76%) 

8.5 

(7%) 

11.7 

(9%) 

5.2 

(4%) 

1.0 

(1%) 

3.8 

(3%) 

0.7 

(1%) 139.0 26.0 28.2 33.7 11.9 

MING1 100.2 

(61%) 

27.8 

(17%) 

21.8 

(13%) 

5.9 

(4%) 

1.4 

(1%) 

6.6 

(4%) 

0.2 

(0%) 175.9 28.3 22.2 32.4 11.6 

HEGL1 87.9 

(63%) 

17.9 

(13%) 

25.3 

(18%) 

5.2 

(4%) 

0.9 

(1%) 

2.8 

(2%) 

0.2 

(0%) 151.2 26.7 25.9 31.9 11.2 

UPBU1 83.2 

(63%) 

13.3 

(10%) 

22.5 

(17%) 

4.7 

(4%) 

1.2 

(1%) 

6.8 

(5%) 

0.2 

(0%) 142.9 26.3 27.4 32.3 11.5 

non-VISTAS 

CACR1 87.1 

(65%) 

13.8 

(10%) 

23.4 

(17%) 

4.8 

(4%) 

1.1 

(1%) 

3.7 

(3%) 

0.2 

(0%) 145.1 26.4 27.0 32.1 11.6 

3- 20
Table 3-4 

Baseline (2000-2004) and Natural Background Visibility Conditions 

20% Best Visibility Days 

2000-04 Component Extinction (Mm-1) 

(% of aerosol extinction) 2000-04 Baseline 2064 Natural Conditions 

Site Amm. 

SO4

Amm. 

NO3

POM LAC Soil CM Sea 

Salt 

bext

(Mm-1) dV VR (km) 

bext

(Mm-1) dV 

SWAN1 11.3 

(52%) 

2.3 

(10%) 

2.3 

(11%) 

0.8 

(4%) 

0.2 

(1%) 

3.2 

(15%) 

1.5 

(7%) 33.6 12.0 116.3 17.3 5.5 

ROMA1 15.7 

(51%) 

3.1 

(10%) 

4.7 

(15%) 

1.7 

(5%) 

0.3 

(1%) 

2.9 

(10%) 

2.2 

(7%) 42.4 14.3 92.2 18.1 5.9 

OKEF1 19.7 

(55%) 

3.7 

(10%) 

6.8 

(19%) 

2.2 

(6%) 

0.4 

(1%) 

2.2 

(6%) 

0.7 

(2%) 46.7 15.2 83.8 17.1 5.3 

EVER1 9.6 

(45%) 

2.2 

(10%) 

3.5 

(16%) 

1.1 

(5%) 

0.4 

(2%) 

2.7 

(13%) 

1.9 

(9%) 32.3 11.7 121.0 16.9 5.2 

CHAS1 18.3 

(50%) 

4.2 

(11%) 

6.3 

(17%) 

2.9 

(8%) 

0.6 

(2%) 

3.3 

(9%) 

1.0 

(3%) 47.6 15.5 82.1 18.1 5.9 

VISTAS coastal 

SAMA1 18.6 

(59%) 

2.8 

(9%) 

4.9 

(16%) 

1.7 

(6%) 

0.5 

(2%) 

2.3 

(7%) 

0.6 

(2%) 42.4 14.3 92.2 17.2 5.4 

DOSO1 14.3 

(56%) 

3.1 

(12%) 

4.9 

(19%) 

2.1 

(8%) 

0.2 

(1%) 

0.7 

(3%) 

0.1 

(0%) 35.4 12.3 110.5 14.5 3.6 

SHEN1 11.2 

(53%) 

4.2 

(20%) 

2.9 

(14%) 

1.6 

(8%) 

0.2 

(1%) 

1.1 

(5%) 

0.1 

(1%) 31.2 10.9 125.4 13.8 3.1 

JARI1 17.5 

(56%) 

3.7 

(12%) 

5.6 

(18%) 

3.0 

(9%) 

0.2 

(1%) 

1.2 

(4%) 

0.1 

(0%) 42.3 14.2 92.5 15.5 4.4 

LIGO1 11.3 

(56%) 

2.2 

(11%) 

3.8 

(19%) 

1.8 

(9%) 

0.2 

(1%) 

0.8 

(4%) 

0.1 

(1%) 31.2 11.1 125.4 15.1 4.1 

SHRO1 7.0 

(58%) 

1.5 

(12%) 

2.1 

(17%) 

0.9 

(7%) 

0.2 

(1%) 

0.4 

(3%) 

0.1 

(1%) 22.2 7.7 176.6 12.9 2.5 

GRSM1 16.4 

(56%) 

3.9 

(14%) 

4.9 

(17%) 

2.2 

(8%) 

0.2 

(1%) 

1.3 

(5%) 

0.2 

(1%) 40.2 13.6 97.3 15.8 4.5 

COHU1 16.1 

(55%) 

5.2 

(18%) 

4.8 

(16%) 

2.0 

(7%) 

0.2 

(1%) 

1.0 

(3%) 

0.1 

(0%) 40.5 13.7 96.6 15.4 4.3 

SIPS1 18.5 

(50%) 

7.1 

(19%) 

6.5 

(17%) 

2.6 

(7%) 

0.4 

(1%) 

2.1 

(6%) 

0.1 

(0%) 48.3 15.6 81.0 16.6 5.0 

VISTAS inland 

MACA1 22.1 

(53%) 

8.8 

(21%) 

6.3 

(15%) 

3.0 

(7%) 

0.3 

(1%) 

1.4 

(3%) 

0.1 

(0%) 53.0 16.5 73.8 16.5 5.0 

BRIG1 14.8 

(49%) 

3.9 

(13%) 

4.5 

(15%) 

2.4 

(8%) 

0.2 

(1%) 

3.2 

(11%) 

1.4 

(4%) 42.4 14.3 92.2 17.3 5.4 

BRET1 17.0 

(57%) 

3.1 

(10%) 

3.2 

(11%) 

1.8 

(6%) 

0.4 

(1%) 

3.4 

(11%) 

1.1 

(4%) 41.1 14.0 95.2 17.1 5.3 

MING1 14.3 

(46%) 

4.6 

(15%) 

6.2 

(20%) 

2.3 

(7%) 

0.4 

(1%) 

3.1 

(10%) 

0.1 

(0%) 42.9 14.4 91.1 17.1 5.4 

HEGL1 10.8 

(42%) 

4.9 

(19%) 

5.1 

(20%) 

2.0 

(8%) 

0.3 

(1%) 

2.3 

(9%) 

0.2 

(1%) 36.6 12.8 106.9 16.0 4.7 

UPBU1 8.7 

(39%) 

4.6 

(21%) 

4.2 

(19%) 

1.5 

(7%) 

0.3 

(2%) 

2.8 

(13%) 

0.1 

(0%) 33.2 11.7 117.9 15.2 4.1 

non-VISTAS 

CACR1 8.5 

(41%) 

4.0 

(20%) 

4.3 

(21%) 

1.5 

(7%) 

0.2 

(1%) 

1.8 

(9%) 

0.2 

(1%) 31.6 11.2 123.7 15.3 4.2 

3- 21
Average Extinction for 20% Worst Days

New IMPROVE Algorithm (nia)

2000-2004

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-14. Contributions to light extinction (Mm-1) for the average of the 20% worst visibility 

days in 2000-2004 at VISTAS and neighboring Class I areas. 

Average Extinction for 20% Best Days

New IMPROVE Algorithm (nia)

2000-2004

0

10

20

30

40

50

60

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm-1

)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-15. Contributions to light extinction (Mm-1) for the average of the 20% best visibility 

days in 2000-2004 at VISTAS and neighboring Class I areas.

3- 22
0

5

10

15

20

25

30

35

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Mass (μg/m3

)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Figure 3-16. Contributions to mass (μg/m3) for the average of the 20% worst visibility days in 

2000-2004 at VISTAS and neighboring Class I areas. 

0

2

4

6

8

10

12

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1

DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Mass (μg/m3

)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Figure 3-17. Contributions to mass (μg/m3) for the average of the 20% best visibility days in 

2000-2004 at VISTAS and neighboring Class I areas. 

3- 23
GRSM1

Baseline Extinction, New IMPROVE Algorithm

20% W > 142

0

100

200

300

400

J-02

F-02

M-02

A-02

M-02

J-02

J-02

A-02

S-02

O-02

N-02

D-02

Extinction (Mm-1)

20% W > 140

0

100

200

300

400

J-01

F-01

M-01

A-01

M-01

J-01

J-01

A-01

S-01

O-01

N-01

D-01

Extinction (Mm-1)

20% W > 139

0

100

200

300

400

J-00

F-00

M-00

A-00

M-00

J-00

J-00

A-00

S-00

O-00

N-00

D-00

Extinction (Mm-1)

20% W > 139

0

100

200

300

400

J-03

F-03

M-03

A-03

M-03

J-03

J-03

A-03

S-03

O-03

N-03

D-03

Extinction (Mm-1)

20% W > 130

0

100

200

300

400

J-04

F-04

M-04

A-04

M-04

J-04

J-04

A-04

S-04

O-04

N-04

D-04

Extinction (Mm-1)

 Figure 3-18. Bar charts by year indicating speciation of all data collected at the GRSM1 site. 

The red line indicates the threshold above which days are counted in the 20% worst days. 

3- 24
ROMA1

Baseline Extinction, New IMPROVE Algorithm

20% W > 92

0

50

100

150

200

250

300

J-02

F-02

M-02

A-02

M-02

J-02

J-02

A-02

S-02

O-02

N-02

D-02

Extinction (Mm-1)

20% W > 102

0

50

100

150

200

250

300

J-01

F-01

M-01

A-01

M-01

J-01

J-01

A-01

S-01

O-01

N-01

D-01

Extinction (Mm-1)

20% W > 133

0

50

100

150

200

250

300

J-00

F-00

M-00

A-00

M-00

J-00

J-00

A-00

S-00

O-00

N-00

D-00

Extinction (Mm-1)

20% W > 96

0

50

100

150

200

250

300

J-03

F-03

M-03

A-03

M-03

J-03

J-03

A-03

S-03

O-03

N-03

D-03

Extinction (Mm-1)

20% W > 116

0

50

100

150

200

250

300

J-04

F-04

M-04

A-04

M-04

J-04

J-04

A-04

S-04

O-04

N-04

D-04

Extinction (Mm-1)

 Figure 3-19. Bar charts by year indicating speciation of all data collected at the ROMA1 site. 

The red line indicates the threshold above which days are counted in the 20% worst days. 

3- 25
y

0

50

100

150

200

250

300

350

400

450

3/8 5/6 5/17 6/3 6/10 6/28 7/1 7/8 7/22 8/5 8/16 8/19 8/23 8/26 10/15 10/18 10/21 10/24 10/27 11/2 5/1 5/7 6/9 6/12 6/21 6/27 7/3 7/12 7/18 7/21 7/24 7/30 8/2 8/5 8/8 8/11 8/14 8/17 8/23 8/26 9/7 9/13 9/19 11/18 2/25 5/2 5/8 5/17 6/1 6/13 6/19 6/22 7/1 7/7 7/10 7/16 7/22 7/31 8/3 8/6 8/9 8/12 8/15 8/21 9/5 9/8 9/11 9/17 3/16 4/27 5/24 5/27 6/5 6/11 6/26 6/29 7/5 7/17 7/20 7/26 8/7 8/10 8/16 8/19 8/22 8/25 8/28 9/3 9/6 9/9 9/12 9/21 1/10 2/21 6/8 6/11 6/20 6/26 6/29 7/8 7/17 7/20 7/29 8/4 8/10 8/16 8/19 8/25 8/28 8/31 9/3 9/12 9/15 9/30 10/3 10/30

2000 2001 2002 2003 2004

Extinction (Mm-1)

Sea Salt

CM

Soil

LAC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-20. Contributions to light extinction (Mm-1) for the 20% worst visibility days in 2000-

2004 at the GRSM1 site. 

0

10

20

30

40

50

60

70

80

1/8 1/12 1/15 1/22 1/26 1/29 2/12 3/11 3/29 4/5 4/8 4/12 4/15 4/22 4/26 10/9 11/14 11/20 12/14 12/23 1/7 1/10 1/19 1/22 1/31 2/6 2/15 2/24 2/27 3/14 3/20 4/13 5/25 6/30 9/1 9/4 9/25 10/7 10/10 10/16 10/25 11/30 12/15 12/21 1/8 1/11 1/14 1/23 2/1 2/7 2/19 2/28 3/3 3/9 3/30 4/26 7/13 9/14 9/26 10/26 10/29 11/4 11/16 11/22 12/7 12/13 12/22 1/30 2/2 2/5 2/17 2/26 3/19 3/31 4/9 4/18 5/12 5/21 7/2 10/6 10/15 10/27 11/5 11/20 11/26 12/2 12/5 12/8 12/14 12/17 1/1 1/7 1/16 1/25 1/31 2/6 2/12 2/15 2/27 3/7 3/31 4/6 6/23 9/18 10/15 11/11 11/14 11/23 11/26 11/29 12/2 12/8 12/11 12/23

2000 2001 2002 2003 2004

Extinction (Mm-1)

Sea Salt

CM

Soil

LAC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-21. Contributions to light extinction (Mm-1) for the 20% best visibility days in 2000-

2004 at the GRSM1 site. 

3- 26
y

0

50

100

150

200

250

300

350

400

1/1 2/12 2/23 5/3 7/1 7/8 7/12 7/15 7/19 8/12 8/16 8/19 8/26 9/15 10/15 10/18 11/5 11/8 12/8 12/11 1/1 1/4 2/21 3/2 4/10 5/13 5/16 5/19 5/28 5/31 6/15 7/9 7/12 7/15 8/8 8/23 8/26 8/29 9/19 9/22 9/28 10/31 11/9 11/18 12/3 1/17 1/29 2/13 2/16 2/22 4/20 5/2 6/4 6/7 7/1 7/4 7/7 7/16 7/19 7/25 7/31 8/24 9/11 9/14 9/17 10/20 10/23 10/26 12/7 1/9 2/20 2/26 3/25 5/27 5/30 6/5 6/11 6/20 6/23 6/26 7/11 7/29 8/19 8/25 9/6 9/9 9/12 9/21 10/3 10/6 10/12 10/21 1/10 1/13 1/22 2/24 3/13 4/9 5/6 5/12 5/27 6/20 7/11 7/14 7/20 7/23 7/26 8/4 8/19 9/3 9/24 9/30 10/3 10/27 10/30 12/5

2000 2001 2002 2003 2004

Extinction (Mm-1)

Sea Salt

CM

Soil

LAC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-22. Contributions to light extinction (Mm-1) for the 20% worst visibility days in 2000-

2004 at the ROMA1 site. 

0

10

20

30

40

50

60

70

80

1/5 1/15 1/29 2/26 4/22 4/26 6/14 6/17 6/28 7/29 8/2 8/23 9/9 9/12 9/18 10/9 10/24 12/23 12/26 1/10 1/31 2/12 3/14 4/25 5/1 6/27 6/30 7/3 8/2 8/5 9/10 9/16 10/7 10/10 10/13 10/22 11/3 11/15 11/24 11/27 12/6 12/18 12/24 1/14 1/23 3/3 3/6 3/9 4/2 4/14 4/17 5/5 6/10 6/19 6/22 6/25 7/10 8/15 8/30 9/2 9/5 9/20 9/23 9/26 10/11 12/19 1/24 2/5 2/23 3/31 4/9 5/21 5/24 6/14 6/17 7/14 7/23 7/26 8/16 9/3 9/15 9/27 11/5 11/14 11/17 11/20 12/11 12/20 12/23 1/7 2/12 2/15 2/27 3/1 3/4 3/7 3/31 4/15 6/14 6/17 7/29 8/1 8/13 9/21 11/2 11/5 11/11 11/26 12/2 12/11 12/14 12/20

2000 2001 2002 2003 2004

Extinction (Mm-1)

Sea Salt

CM

Soil

LAC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 3-23. Contributions to light extinction (Mm-1) for the 20% best visibility days in 2000-

2004 at the ROMA1 site. 

3- 27
3.5 GLIDEPATHS 

The RHR guidance requires reasonable progress to be tracked using the Haze Index 

(deciviews), which is determined as a logarithmic transformation of the sum of all light 

extinction terms in the IMPROVE light extinction algorithm. The rate of visibility improvement 

between baseline conditions in 2000-2004 and natural background conditions in 2064 is defined 

as the glidepath for the uniform rate of progress toward visibility goals. Glidepaths calculated 

using the original and revised IMPROVE algorithm for the GRSM1 and ROMA1 sites are 

presented in Figures 3-24 and 3-25 and for other Class I areas in Appendix H. Natural 

conditions for the glidepath using the original IMPROVE equation are EPA default calculations, 

and natural conditions for the path using the revised IMPROVE equations are the revised natural 

condition calculations discussed in Section 2.5, updated in August, 2007. Current conditions at 

the interior sites are poorer than at the coastal sites and thus a higher rate of improvement is 

required in each decade to achieve a uniform rate of progress toward natural background 

conditions in 2064. 

Glide Path to Natural Conditions (2004-2064)

(5-yr Rolling Average for 20% Haziest Days - New IMPROVE equation and NB II )

0

5

10

15

20

25

30

35

1986-19901988-19921990-19941992-19961994-19981996-20001998-20022000-2004

200620082010201220142016201820202022202420262028203020322034203620382040204220442046204820502052205420562058206020622064

Deciviews (dv)

Default Glide Path GRSM New Glide Path GRSM

Default 5-yr Rolling Avg GRSM New 5-yr Rolling Avg GRSM

Annual g90 - Old Annual g90 - New

 Base old Base new Default NB NB2

 Great Smokey Mtns 28.8 30.3 11.4 dv 11.1 dv

Figure 3-24. DV Glidepaths for the GRSM1 site, calculated using both the original IMPROVE 

algorithm using EPA default natural conditions (Default NB) and the new IMPROVE algorithm 

using the revised estimate of natural background conditions (NB2). 

3- 28
Glide Path to Natural Conditions (2004-2064)

(5-yr Rolling Average for 20% Haziest Days - New IMPROVE equation and NB II )

0

5

10

15

20

25

30

35

1986-19901988-19921990-19941992-19961994-19981996-20001998-20022000-2004

200620082010201220142016201820202022202420262028203020322034203620382040204220442046204820502052205420562058206020622064

Deciviews (dv)

New Glide Path ROMA Default Glide Path ROMA

New 5-yr Rolling Avg ROMA Default 5-yr Rolling Avg ROMA

Annual g90 - New Annual g90 - Old

 Base old Base new Default NB NB2

 Cape Romain 25.3 26.5 11.4 dv 12.1 dv

Figure 3-25. DV Glidepaths for the ROMA1 site, calculated using both the original IMPROVE 

algorithm using EPA default natural conditions (Default NB) and the new IMPROVE algorithm 

using the revised estimate of natural background conditions (NB2). 

The glidepath defined using deciview does not provide information regarding the relative 

contributions of individual species to overall visibility. This information is useful because some 

species (sulfate and nitrate) originate from largely anthropogenic sources, while others (organic 

carbon, elemental carbon) originate from a mixture of both anthropogenic and natural sources. 

To look at individual species contribution, species specific glidepaths were constructed 

using extinction in a manner similar to that outlined in RHR guidance for total deciviews. 

Figures 3-26 through 3-29 present glidepath charts for total extinction and for ammonium 

sulfate, ammonium nitrate and POM extinction at the GRSM1 site, and figures 3-30 through 3-

33 present the glidepaths for the ROMA1 site. The dV glidepath is linear as defined in the RHR, 

which, because it is a logarithmic transformation of extinction data, translates to a curved line 

when converted to total extinction in Mm-1. The dV contribution can not be constructed for 

individual species, so linear approximations in Mm-1 are used for the species specific glidepaths 

to approximate progress goals. 2018 projected extinction values were provided by ENVIRON 

based on CMAQ modeling of the 2018 Base G1 inventory. Natural conditions presented here do 

not use the revised NC2 numbers that became available in August, 2007 but differences between 

the original set provided by IMPROVE, and the revised set were minimal. Plots for each site in 

and around the VISTAS region are included in Appendix I. 

3- 29
For total extinction, the projected 2018 value at the GRSM1 site is well below the 

glidepath to natural conditions. This is in large part due to the substantial improvement in 

projected ammonium sulfate values, from 173 Mm-1 to 70 Mm-1 in 2018. POM needs little 

improvement to reach natural conditions, and projected 2018 values fall slightly below the 

glidepath. For Ammonium nitrate, baseline conditions are low, and are similar to estimated 

natural conditions. Projected 2018 nitrate values are actually higher than the baseline emissions, 

but still low at 9 Mm-1 when compared to the baseline ammonium sulfate emissions of 173 

Mm-1. 

At the ROMA1 site, the baseline is lower than for the GRSM1 site, and the projected 

2018 value for total extinction at the ROMA1 site is on the glidepath. Projected ammonium 

sulfate is below the glidepath, with a projected value of 54 Mm-1 in 2018. POM again needs little 

improvement to reach natural conditions, and projected 2018 values are on the glidepath. For 

ammonium nitrate, projected 2018 values are lower than the baseline emissions, slightly above 

the glidepath, but still low, with projected 2018 values of 5 Mm-1. 

0

50

100

150

200

250

20002002200420182064

Extinction (Mm-1)

Total Bext

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-26. Glidepath depicting total bext (Mm-1) for 20% worst days at the GRSM1 site. 

3- 30
0

20

40

60

80

100

120

140

160

180

200

20002002200420182064

Extinction (Mm-1)

Ammonium Sulfate

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-27. Glidepath depicting Ammonium Sulfate for 20% worst days at the GRSM1 site. 

0

1

2

3

4

5

6

7

8

9

10

20002002200420182064

Extinction (Mm-1)

Ammonium Nitrate

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-28. Glidepath depicting Ammonium Nitrate for 20% worst days at the GRSM1 site. 

3- 31
0

5

10

15

20

25

30

35

40

20002002200420182064

Extinction (Mm-1)

Particulate Organic Matter

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-29. Glidepath depicting Particulate Organic Material for 20% worst days at the 

GRSM1 site. 

0

20

40

60

80

100

120

140

160

180

200

20002002200420182064

Extinction (Mm-1)

Total Bext

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-30. Glidepath depicting total bext (Mm-1) for 20% worst days at the ROMA1 site. 

3- 32
0

20

40

60

80

100

120

140

20002002200420182064

Extinction (Mm-1)

Ammonium Sulfate

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-31. Glidepath depicting Ammonium Sulfate for 20% worst days at the ROMA1 site. 

0

1

2

3

4

5

6

7

8

20002002200420182064

Extinction (Mm-1)

Ammonium Nitrate

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-32. Glidepath depicting Ammonium Nitrate for 20% worst days at the ROMA1 site. 

3- 33
0

5

10

15

20

25

30

35

20002002200420182064

Extinction (Mm-1)

Particulate Organic Matter

Baseline

Glide Slope

2018 Base G

Natural Conditions

Figure 3-33. Glidepath depicting Particulate Organic Material for 20% worst days at the 

ROMA1 site. 

3- 34
3.6 ATTRIBUTION ANALYSIS 

An attribution analysis was performed to allow states to understand what source regions 

impact Class I areas in the VISTAS region. The analysis included construction of back 

trajectory and residence time maps, and comparisons of international and domestic mass 

attribution. 

3.6.1 Back Trajectory Maps

For the year 2002, back trajectories were computed for IMPROVE monitoring sites in 

and around the VISTAS region. These analyses used the VISTAS substituted data set, with 

extinction calculated using the original IMPROVE algorithm. The original algorithm was used 

because the maps were generated and mapped before VISTAS made the decision to use the 

revised algorithm, but the days identified as the 20% worst days are similar, if not exactly the 

same, between algorithms. Each hourly point for back trajectories with end dates corresponding 

to the 20% worst visibility days was plotted on a map. A back trajectory map for the 20% worst 

measured extinction days at the GRSM1 sites is presented in Figure 3-34. Back trajectory maps 

for all VISTAS sites are included in Appendix J. 

Figure 3-34. Back trajectories for the 20% Worst extinction days at the Great Smoky Mountains 

National Park (GRSM1) IMPROVE monitoring site. 

3.6.2 Residence Time Maps

Residence time maps were constructed using 2000-2004 back trajectories. 20% worst 

extinction days were determined using the substituted IMPROVE RHR2 (new IMPROVE 

algorithm, updated 3/06) data set. Each hourly point for back trajectories with end dates 

3- 35
corresponding to the 20% worst visibility days was counted and summed into 1⁄4 degree 

horizontal grid cells of latitude and longitude. The percent of hourly points in each grid cell was 

calculated and mapped using color gradients, where darker colors indicate regional areas where 

air parcels spent the most time before reaching the IMPROVE monitors. A residence time map 

for the 20% worst measured extinction days at the GRSM1 site for trajectories with end heights 

of 100m is presented in Figure 3-31. 100m and 500m residence time Maps for all VISTAS and 

regional sites are included in Appendix K. 

Residence time over an area is indicative of general flow patterns, but since it does not 

account for emissions and removal processes, it does not necessarily imply specific areas 

contributed significantly to haze compounds at a receptor site. 

GRSM1

2000-04

20% Worst Monitored Days

100m Residence Times (%)

< 0.01

0.01 - 0.02

0.02 - 0.04

0.04 - 0.08

0.08 - 0.16

0.16 - 0.32

> 0.32

Figure 3-35. Residence times for 72-hour back trajectories with 100m end heights for 20% worst 

extinction days at the GRSM1 IMPROVE monitoring site. 

3.6.3 Extinction-Weighted Residence Time

For the years 2000-2004 ARS generated extinction-weighted residence time data for each 

IMPROVE sites in and around the VISTAS region. These analyses used the VISTAS substituted 

data set, with extinction calculated using the original IMPROVE algorithm. The original 

algorithm was used because these data files were generated prior to VISTAS decision to use the 

new algorithm, and it was determined that updating these data with the revised algorithm would 

not affect interpretation. Each hourly point for back trajectories with end dates corresponding to 

one the 20% worst visibility days were weighted with calculated extinction values for that day. 

Trajectory data were weighted by total extinction, and by extinction components including 

3- 36
ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), particulate organic material 

(POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). The extinction values 

associated with hourly points were summed into 1 degree horizontal grid cells of latitude and 

longitude. 

These extinction-weighted residence time data files were provided to ENVIRON to use in 

conjunction with emissions information to relate emissions and transport to components of haze, 

and to apply distance weighting to estimate removal processes. These charts are available from 

ENVIRON. 

3.6.4 International Contributions

To account for contribution to mass measured at VISTAS sites from international 

emissions, VISTAS generated model results with zeroed out Mexican and Canadian emissions, 

and boundary conditions (as defined by the GEOS-CHEM global model). The difference 

between the model run with and without the international emissions was used to represent 

species mass attributable to international sources. 

Figure 3-36 and 3-37 present stacked bar charts separating domestic and international 

attribution of mass on the 20% worst and best extinction days in 2002 at the GRSM1 site, and 

Figures 3-38 and 3-39 present charts for the ROMA1 site. For this comparison all sulfate and 

nitrate were assumed to be fully neutralized by particulate NH4

+

 (similar to IMPROVE 

monitoring network assumptions). Negative numbers in the international results indicated that 

species concentration went up when the non-US anthropogenic emissions were removed. The 

negative impacts were usually small, and these values were set to zero for purposes of this 

comparison. Domestic contributions were computed as the difference between total measured 

mass and international modeled mass. 

International attribution at the GRSM1 site ranges between 2 and 7% of total mass on the 

20% worst days. Magnitudes on the 20% best days were similar, but accounted for up to 41% of 

total measured mass. At the ROMA1 site, attribution was between 0 and 18% on the worst days, 

and up to 21% on the best days. Similar charts for the other Class I areas are included in 

Appendix L. 

3- 37
GRSM1

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

0

5

10

15

20

25

30

35

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

2/25 5/2 5/8 5/17 6/1 6/13 6/19 6/22 7/1 7/7 7/10 7/16 7/22 7/31 8/3 8/6 8/9 8/12 8/15 8/21 9/5 9/8 9/11 9/17

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 3-36. Stacked bar charts of mass at the GRSM1 site depicting domestic and international 

contributions to the 20% worst days in 2002. 

GRSM1

Domestic and International Aerosol Mass by Species

20% Best Days (2002)

0

2

4

6

8

10

12

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

1/8 1/11 1/14 1/23 2/1 2/7 2/19 2/28 3/3 3/9 3/30 4/26 7/13 9/14 9/26 10/26 10/29 11/4 11/16 11/22 12/7 12/13 12/22

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 3-37. Stacked bar charts for mass at the GRSM1 site depicting domestic and international 

contributions to the 20% best days in 2002. 

3- 38
ROMA1

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

0

5

10

15

20

25

30

35

40

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

1/17 1/29 2/13 2/16 2/22 4/20 5/2 6/4 6/7 7/1 7/4 7/7 7/16 7/19 7/25 7/31 8/24 9/11 9/14 9/17 10/20 10/23 10/26 12/7

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 3-38. Stacked bar charts of mass at the ROMA1 site depicting domestic and international 

contributions to the 20% worst days in 2002. 

ROMA1

Domestic and International Aerosol Mass by Species

20% Best Days (2002)

0

2

4

6

8

10

12

14

16

18

20

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

1/14 1/23 3/3 3/6 3/9 4/2 4/14 4/17 5/5 6/10 6/19 6/22 6/25 7/10 8/15 8/30 9/2 9/5 9/20 9/23 9/26 10/11 12/19

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 3-39. Stacked bar charts for mass at the ROMA1 site depicting domestic and 

international contributions to the 20% best days in 2002. 

3- 39