# Air Resource Specialists, Inc. VISTAS Conceptual Descri ption 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 CO NDITIONS 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 Revise d 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 (Base line, 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 Internati onal Attribution Plots L-1

ii

# LIST OF FIGURES

Figure Page

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

3-1 Comparison of Measured Light Scatte ring (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 extinct ion calculated usi ng the new IMPROVE algorithm (left), the old IMPROVE al gorithm (right), and measured light scattering (grey line) in 2004 3-4

3-3 Stacked bar chart comparing light extinc tion 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 a nd neighboring Class I areas 3-5

3-4 Stacked bar chart comparing light extinc tion calculated using both the new (left) and old (right) IMPROVE algorithm for th e average of the 20% best visibility days in 2000-2004 at VISTAS a nd neighboring Class I areas 3-5

3-5 Stacked bar chart comparing 20% wo rst 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 Organi c 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 Ma ss Between SHRO1, NC (y-axis) and GRSM1, TN (x-axis) 3-12

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

3-10 10-year annual average extinction tr ends 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 Vi sual 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 VIST AS 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 VIST AS and neighboring Class I areas 3-22

3-16 Contributions to mass (μg/m 3 

# ) for the average of the 20% worst visibility days in 2000-2004 at VISTAS a nd neighboring Class I areas 3-23

3-17 Contributions to mass (μg/m 3 

# ) for the average of the 20% best visibility days in 2000-2004 at VISTAS a nd 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 vi sibility 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 vi sibility 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 defau lt natural conditi ons (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 defau lt natural conditi ons (Default NB) and the new IMPROVE algorithm using the revised estimate of natural background conditions (NB2) 3-29

3-26 Glidepath depicting total b ext 

# (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 fo r 20% worst days at the GRSM1 site 3-31

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

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

GRSM1 site 3-32

3-30 Glidepath depicting total b ext 

# (Mm -1 

# ) for 20% worst days at the ROMA1 site 3-32

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

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

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

ROMA1 site 3-34

3-34 Back trajectories for the 20% Wors t 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 th e GRSM1 site depicting domestic and

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

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

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

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

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

3-39 Stacked bar charts for mass at th e 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 Avai lable 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 IM PROVE 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 Bac kground Visibility Conditions 20% Worst Visibility Days 3-20

3-4 Baseline (2000-2004) and Natural Bac kground 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 Resour ce Specialists, Inc. (A RS) 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 gove rnments, and various federal agencies established to initiate and coor dinate activities associated with the management of regional haze, visibility and ot her air quality issues in the S outheastern United States. VISTAS is working to develop the technical basis fo r 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 pr esented 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 a nd 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 establis h “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 impa ir visibility. The nati onal 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 th e regional haze regulatio n are due in December

2007.

1.2 DATA SUMMARY PRO DUCT FTP SITE

Methods descriptions and analys is 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 curre ntly available on the ftp site.

1-2Table 1-1Summary of Data Products Available on ARS VISTAS FTP SiteSamplePathDescription[data files]...Aerosol_dataset_VISTAS_2000-2004/SAMA1_daily_budgets_sub_nia.xlsData sets including substituted data for VISTAS andneighboring Class I Areas,old and new IMPROVEalgorithm.Average Extinction for 20% Worst DaysNew IMPROVE Algorithm (nia)2000-2004050100150200250300 SWAN1 ROMA1 OKEF1 EVER1 CHAS1 SAMA1 DOSO1 SHEN1 JARI1 LIGO1 SHRO1 GRSM1 COHU1 SIPS1 MACA1 BRIG1 BRET1 MING1 HEGL1 UPBU1 CACR1VISTAS coastalVISTAS inlandnon-VISTAS

Extinction (Mm
-1 )Sea SaltCMSoilECPOMAmm NO3Amm SO4Rayleigh...Aerosol_stacked_bar_charts/Average_BestWorstDays_2000-04/VISTAS_nia_00-04_20070129.xlsRegional stacked bar charts depicting 20% best and worstdays, extinction and mass, old and new algorithm.GRSM1Baseline Extinction, nia20% W > 1420100200300400 J-0 2 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 > 1400100200300400 J-0 1 F-01 M-01 A-01 M -01 J-0 1 J-01 A-01 S-01 O-01 N-0 1 D -0 1

Extinction (Mm
-1 )20% W > 1390100200300400 J -00 F-00 M-00 A-00 M -00 J-0 0 J -00 A-00 S -0 0 O-00 N -0 0 D-00

Extinction (Mm
-1 )20% W > 1390100200300400 J -0 3 F - 0 3 M -0 3 A -0 3 M -0 3 J -03 J -03 A -0 3 S -0 3 O -0 3 N-03 D -03

Extinction (Mm
-1 )20% W > 1300100200300400 J-04 F-0 4 M-0 4 A-04 M-04 J-04 J-0 4 A-0 4 S-0 4 O-04 N -04 D-04

Extinction (Mm
-1 )...Aerosol_stacked_bar_charts/Timelines_AllDays_2000-04/GRSM.pdfStacked bar charts depictingextinction for all monitoreddays during the baseline years, 2000-2004. For VISTASsites requiring data substitution, two charts are provided,where the first page distinguishes substituted days fromoriginal days.GRSM12000-2004 Reconstructed ExtinctionNew IMPROVE Algorithm20% Worst Days050100150200250300350400450 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 10/3020002001200220032004

Extinction (Mm
-1 )Sea SaltCMSoilLACPOMAmm NO3Amm SO4Rayleigh...Aerosol_stacked_bar_charts/Timelines_BestWorstDays_2000-04/GRSM1_20bw_nia.xlsStacked bar charts that selectively show just the 20% bestand worst days for 2000-2004 baseline period.1-3GRSM1Old and New IMPROVE Algorithm (oia/nia) Extinction by Species20% Best Days (2002)0102030405060 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 oia1/8 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 )RayleighAmm SO4Amm NO3POMLACSoilCMSea Salt...Aerosol_stacked_bar_charts/Timelines_nia_oia_comparison_2002/GRSM1_nia_oia.xlsRegional and site specific stacked bar charts whereextinction calculations using the new and old IMPROVEalgorithm are presented side by side.All Daysy = 0.93x + 9.16R2= 0.870501001502002503000 50 100 150 200 250 30024-hr Nephelometer bsp(Mm-1)

24-hr Aerosol b sp (Mm
-1 )Q4y = 1.10x + 1.49R2= 0.960501001502002503000 50 100 150 200 250 300Q1y = 0.77x + 13.88R2= 0.480501001502002503000 50 100 150 200 250 300Q2y = 0.93x + 12.17R2= 0.810501001502002503000 50 100 150 200 250 300Q3y = 0.86x + 14.28R2= 0.820501001502002503000 50 100 150 200 250 300-100-75-50-250255075100 2000 2001 2002 2003 2004

Difference (Mm
-1 ) (Aer. b sp - Neph. b sp )Aerosol Scattering vs. Nephelometer ScatteringUsing New IMPROVE Algorithm (nia) and Daily f(RH)GRSM, 2000 - 2004...Nephelometer_Aeosol_Comparisons/GRSM_neph.xlsCharts comparing collocated IMRPROVE nephelometersand IMPROVE aerosol samplers, old and newIMPROVE algorithm.Glide Path to Natural Conditions (2004-2064)(5-yr Rolling Average for 20% Haziest Days - New IMPROVE equation and NB II )05101520253035 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 GRSMNew Glide Path GRSMDefault 5-yr Rolling Avg GRSMNew 5-yr Rolling Avg GRSMAnnual g90 - OldAnnual g90 - NewBase old Base new Default NB NB2Great Smokey Mtns 28.8 30.3 11.4 dv 11.2 dv...Glidepaths/Revised Glide Path new IMPROVEequation_Reynolds.pptDeviview Glidepaths (developed by Scott Reynolds) byspecies depicting baselineconditions and estimatednatural conditions for boththe new and old algorithm.GRSM1Total ExtinctionGlide Slope for 20% Worst Days050100150200250 2000 2002 2004 2018 2064

Extinction (Mm
-1 )Total BextBaselineGlide Slope2018 Base GNatural Conditions...Glidepaths/Speciated_Glidepaths/Glideslopes_GRSM1.xlsGlidepaths by species depicting baseline condition, 2018modeled predictions and estimated natural conditions.1-410 Year Temporal TrendsAll Days151719212325 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

DVOKEF1m = -0.13, p = 0.05ROMA1m = -0.24, p = 0.06SWAN1N/A (< 5 years)10 Year Temporal Trends20% Best Days101214161820 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

DVOKEF1m = -0.05, p = 0.43ROMA1m = -0.23, p = 0.02SWAN1N/A (< 5 years)10 Year Temporal Trends20% Worst Days202224262830 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

DVOKEF1m = -0.17, p = 0.01ROMA1m = -0.28, p = 0.24SWAN1N/A (< 5 years)...IMPROVE_Trend_Charts/Trends_DV.xls10 Year temporal trends for sites grouped regionally,includes Standard Visual Range (SVR), Deciview (DV)and Mm-1.GRSM1Domestic and International Aerosol Mass by Species20% Worst Days (2002)05101520253035 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 International2/25 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 SO4Amm NO3POMLACSoilCMSea Salt...International_Attribution/International_Attribution_mass_worst.xlsComparison of domestic and international attribution ofmass on 20% best and worst days, 2002....Back_Trajectory_Analyis/IMPROVE_ResidenceTimeMaps_2000-04_nia/GRSM_2002_20high.bmpBack trajectory maps for 20% worst extinction days.GRSM12000-0420% Worst Monitored Days100m Residence Times (%)< 0.010.01 - 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.bmpResidence time maps for 20% worst days, 2000-2004.1-5

# 2.0 ANALYTICAL METHODS

2.1 THE IMPROVE MONITORING NETWORK

The Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring program collects speciated PM 2.5 

# , and PM 2.5 

# and PM 10 

# total mass. IMPROVE is a nation-wide network which began in 1988 and expanded signi ficantly 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 inte grated 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 PM 2.5 

# and PM 10 

# mass, and PM 2.5 

# mass constituents, including numerous trace elemen ts, 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 lis ting of IMPROVE sites, locations, and operational start dates is presented in Table 2-1. The list also includes star t (and end) dates for collocated nephelometers, which are continuous monitoring in struments 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 IMPR OVE 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) 7/94 35.39 -82.77 4/94 – 9/99 NC

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. Th e three most common metrics used to describe visibility impairment are:

• 

# Extinction (b ext 

# ) – Extinction is a measure of the fr action of light lost per unit length along a sight path due to s cattering and absorption by gase s and particles, expressed in inverse Megameters (Mm -1 

# ). This metric is useful for representing the contribution of each aerosol species to visibility impai rment 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 di stance a large black object can be seen on the horizon, expressed in k ilometers (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 approxi mately 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 ex tinction based upon the measured mass of various contributing aerosol species. EPA’s 2003 guidance (http://vista.cira.colostate.edu/improve/Publi cations/GuidanceDocs/guidancedocs.htm) for calculating light extincti on is based on the original protoc ol defined by the IMPROVE program in 1988. In December 2005, the IMPROVE Steer ing Committee voted to adopt a revised algorithm for use by IMPROVE as an alte rnative to the original approach.

The elements and species meas ured 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 [(NH 4 

# ) 2 

# SO 4 

# ] 4.125× [S]

-or1.375× [SO 4 

# ] [S] is derived from the Teflon filter (A module). [SO 4 

# ] is derived from the nylon filter (B module).

Ammonium Nitrate [(NH 4 

# )NO 3 

# ] 1.29× [NO 3 

# ] [NO 3 

# ] 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] [PM 10 

# ] - [PM 2.5 

# ] [PM 10 

# ] is derived from the Teflon filter (D module). [PM 2.5 

# ] 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 (b ext 

# ) is:

2-3

# [ ] [ ] [ ]

[ ] [ ] [ ]

(10) Scattering Rayleigh CM6.0 Soil Fine1 EC10 POM4 Nitrate Amm. f(RH)3 Sulfate Amm. f(RH)3b

+ ×+ ×+ ×+ ×+ ××+ ××≈ ext



# Reconstructed b ext 

# is expressed in Mm -1 

# , dry extinction efficienci es (leading numbers) are expressed as m 2 

# /g and species mass concentrations are expressed in μ g/m 3 

# . 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 IM PROVE 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 reas onable estimates of light scattering over a broad range of conditions, but it tends to u nderestimate the highest extinction values and

overestimate the lowest extinction values. The re vised algorithm for esti mating light extinction recommended for use by the IMPROVE steering committee is:



# [ ] [ ] [ ][ [ ][ ] [ ] [ ] [ ] [ ]

[ ]

Specific) (Site Scattering Rayleigh (ppb)NO33.0 CM6.0 Salt Sea(RH)f7.1 Soil1 EC10 POM Large1.6POM Small8.2 Nitrate Amm. Large (RH)f1.5Nitrate Amm. Small (RH)f4.2 Sulfate Amm. Large (RH)f8.4Sulfate Amm. Small (RH)f2.2b

2 ss L s L s



# + ×+ ×+ ××+ ×+ ×+ ×+ ×+ ××+ ××+ 

# ] × × + ××≈ ext



# The revised algorithm splits ammonium sulfate, ammonium nitrate, and POM concentrations into small and large size fractions as follows:



# [ ] [ ] [ ] [ ]

[ ] [ ][

[ ] [ ][ ] Total Large, μ g/m20TotalFor Large Total Small Total 20 Total Large

μ g/m20TotalFor

3 3



# = ≥ ⎪ ⎪ ⎩ ⎪ ⎪ ⎨ ⎧

−= ×=

< 

# ]

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

2-4

# mass concentration in the revised algorithm, wher e it was calculated as 1.4 times carbon mass in the original algorithm. The new algorithm contai ns three distinct water growth factors, designated f S 

# (RH), f L 

# (RH), and f SS 

# (RH) for water absorption due small and large sulfate and nitrate fractions, and for sea salt, respectively. New terms have al so been added for sea salt and for absorption by gaseous NO 2 

# . NO 2 

# is not available at most IMPROVE sites, and is not included in analysis presented here.

IMPROVE data are availabl e on the IMPROVE Web site ( http://vista.cira.colostate.edu/improve/ ) and the Visibility Inform ation 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 designati on indicating that extinction was calculated using the original/old IMPROVE algor ithm, and RHR2 indicates that extinction was calculated using the revised/ new IMPROVE algorithm.

VISTAS chose to use the new IMPROVE al gorithm 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 geographi c source areas most likely to contribute to visibility impairment on th e 20% worst visibility days at the Class I areas. Back trajectory analyses use interpolated measur ed or modeled meteorological fields to estimate the most likely central path over geographical areas that provided air to a re ceptor 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 fo r 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 Hybr id-Single Particle La grangian Integrated Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Labora tory (ARL). HYSPLIT uses archived 3- dimensional meteorological fields generated fr om observations and short-term forecasts. HYSPLIT can be run to generate forward or b ackward 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 A ssimilation 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 horizo ntal 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 trajectori es 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 measuremen ts (represented by model data), surfaces of constant entropy, or surfaces of constant pressure, depending on th e meteorological conditions at a given location and time. The impact of receptor height (or e nd height) on an individual trajectory is also important. Low-ending trajectories represent air parcels nearer to ground level and high-ending trajectories may better represen t boundary layer flow above th e local terrain. Specific back trajectory analyses performed by ARS fo r 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 timelin e 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. Anal yses include comparisons of the old and new IMPROVE algorithms, determinatio n of baseline (2000-2004) condi tions, determination of the glide slope between baseline and natural conditions, and determ ination of geographic source areas using back trajectory analysis.

3.1 COMPARISON OF OLD AND NEW IMPROVE ALGORITHM

One of the most compelling reasons for de veloping 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 GRSM 1 site comparing measured light scattering (nephelometer) and reconstructed light scattering calculated using the revi sed (New) and original (old) IMPROVE algorithms. A stacked bar chart fo r the most recent year of comparable record,

in this case 2004 at the GRSM1 s ite, 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 ae rosol light scattering is calculated using daily f(RH) based upon measured RH, as opposed to th e IMPROVE method of us ing 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 reconstruc ted extinction, coarse ma ss 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 VI STAS nephelometer site in Appendix A for both the total available data set and each quarter separately.

The GRSM1 site has one of the longest peri ods of nephelometer data in the VISTAS region, and has been in operation since 1993. In ge neral, 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 th e data and generally sli ghtly lower correlation.

Figures 3-3 and 3-4 present comparisons of th e average 20% worst an d best days in the 2000-2004 baseline period at VISTAS and neighboring sites calculated using both the revised and original IMPROVE algorithm. For the wors t 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 compar ison 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 revi sed algorithms. In the case of GRSM1, 9/23 was a worst day in 2002 using the old algo rithm, but this one day is trad ed for 7/22 when extinction is calculated using the new algorithm. Other days cha nge in magnitude, but the same days are still counted among the 20% worst days. Additional plots comparing extincti on calculated using the old and new IMPROVE algorithms for 20% best a nd worst days in 2002 at all VISTAS sites are available in Appendix B.

3-2Old Algorithmy = 0.71x + 14.70R2= 0.890501001502002503000 50 100 150 200 250 30024-hr Nephelometer bsp(Mm-1)

24-hr Aerosol b sp (Mm

-1 )New Algorithmy = 0.98x + 5.97R2= 0.870501001502002503000 50 100 150 200 250 30024-hr Nephelometer bsp(Mm-1)

24-hr Aerosol b sp (Mm -1 )Figure 3-1. Comparison of measured lightscattering (nephelometer) andlight scattering calculated using the original (old) and revised (new)IMPROVE algorithms for the GRSM1 site, 1993-2004.3-3050100150200250 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 10/30 11/2 11/5 11/8 11/11 11/14 11/17 11/26 11/29 12/2 12/5 12/8 12/17 12/26 12/29

Extinction (Mm
-1 )Amm SO4Amm NO3POMSoilCMSea SaltnephFigure 3-2. Stacked bar chart comparing extinction calculated using thenew IMPROVE algorithm(left), the old IMPROVE algorithm(right), and measured light scattering (grey line) in 2004.3-40 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) 

### CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh



# Figure 3-3. Stacked bar chart comp aring 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 60SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) 

### CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh



# Figure 3-4. Stacked bar chart comp aring 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.

3-5GRSM1Old and New IMPROVE Algorithm (oia/nia) Extinction by Species20% Worst Days (2002)050100150200250300350400 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 nia oia nia oia2/25 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 9/23 Avg.

Extinction (Mm

-1 )RayleighAmm SO4Amm NO3POMLACSoilCMSea SaltFigure 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

# 3.2 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 base line period average (2000- 2004) contain at least 3 complete years of data. RHR guidance requi rements for IMPROVE aerosol data completeness include the following conditions:

• Individual samples must contain all speci es required for the calculation of light extinction (sulfate, nitrate, organic carbon, elemental car bon, 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 le ast 75% of all possible daily samples

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

• The baseline period (2000-2004) must contai n 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 f ilter 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 th e data, the resulting complete years are eligible for use in calculation of baseline conditions and tracking pr ogress under the RHR.

Further details can be found in the RH R 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 fo r 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, SH RO1 and SWAN1), and two regional site (BRET1 and MING1) did not ach ieve 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 ha d 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

EVER1 0 1 1 1 1 4 FL

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

SHRO1* 0 0 0 1 1 2 NC

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 1NonVISTAS



# 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 ch art of the VISTAS data substitution methods, and details for

these methods are described below. The starti ng data set was the RHR2 IMPROVE data using the new IMPROVE algorithm. This data set in cludes the routine surroga te 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 mi ssing individual sample s 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. H ydrogen (H) is measured on the A module filter, and is assumed to be primarily associated with orga nic carbon and inorganic compounds such as ammonium sulfate. Organic ca rbon (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 i norganic 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 Caro lina during the second quarter between 2000-2004 for OC vs. organic H, and EC vs. OC. Statistic s were calculated and appl ied 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 Or ganic 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 identi fication 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 character istics to be used as a donor site.

Figure 3-8 presents a sample inter-site ma ss 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 (GRS M1) 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, ch loride/chlorine was not available from the GFP SEARCH site. In this case, sea salt could not be calcula ted from the GFP data, so seasonal averages of sea

salt from the BRET1 site were used as substitute s. 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 require d some degree of substitution, where a 2 indicates a substituted year, a 1 indicates the ye ar was already complete under RHR guidelines, and dashes indicate the year di d not meet RHR guidelines and no additional substitutions were

made. The table also lists sites that were select ed 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 th e 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 th e SAMA1 site depicti ng 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 ba r 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 a nd not substituted. In the case of SAMA1, substitutions were made for the years 2001 a nd 2004. In 2001, data from the CHAS1 site was

scaled and substituted for about 33% of monitore d 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 requi red 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 include d in Appendix C. Additional char ts and tables for all VISTAS

substituted sites are in cluded in Appendix D.

3- 11

### Q2

r2 = 0.68

0 10 20 30 40 50

0 10 20 30 40 50

AmmSO 4 

### (μg/m3)AmmSO4(μg/m3) 

### Q2

r2 = 0.62

0 1 2 3 4 5

012345

AmmNO 3 

### (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 Ma ss 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-0 2 A -0

2 M-0 2 J- 02 J- 02 A-02 S- 0 2 O - 0 2 N-0 2 D-0 2Extinction (Mm-1) ■ ■ ■ ■■■■■■■■■■■■■■■■■■■ ■ ■ ■■ ■■■■■■■■■■ ■■■ ■ 0 50 100 150 200

J-01 F- 0 1 M -0

1 A -0

1 M -0

1 J-01 J-01 A-01 S- 0 1 O - 0 1 N-01 D-01Extinction (Mm-1)



### 20% W > 101 0 50 100 150 200

J-00 F- 0 0 M- 0 0 A-00 M-0 0 J- 0 0 J- 0 0 A-00 S-00 O-0 0 N-00 D-0 0Extinction (Mm-1)



### 20% W > 109

0 50 100 150 200

J-03 F - 0 3 M -0

3 A -0

3 M-03 J-0 3 J-03 A -0

3 S- 0 3 O- 0 3 N- 0 3 D-03Extinction (Mm-1)

■■■■■■■ ■ ■■■■■■■■■■■■■■■■■■■■ ■■■■■■■■■■■■■ 0 50 100 150 200

J-0

4 F-04 M-0 4 A - 04 M- 04 J-0 4 J-0 4 A- 0 4 S - 04 O - 04 N- 0 4 D- 0 4Extinction (Mm-1) 

### 20% W > 117



# Figure 3-9. 2000-2004 annual bar char ts 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 indicate s 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 1995-20 04 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 provisi ons of the 1990 Clean Air Act Amendments and under the NOx SIP call for ozone. Theil slopes we re calculated to determine the trend, and pvalues were calculated using Ma nn-Kendall trend analysis to dete rmine the significance of each slope. Lower p-values indicate higher conf idence levels in the computed slopes.

Figure 3-10 is a map indicating 10-year annual av erage 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 show ed decreasing trends (using pvalue<0.20 as indicator ). No s ites 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 site s are included on the plot for reference. Additional trend plots for other regional groupi ngs 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 tr ends and blank diamonds indica te insignificant trends (pvalue<0.20). No sites sh owed increasing trends.

3- 15

# 10 Year Temporal Trends All Days

0 20 40 60 80 100 120 1401995199619971998199920002001200220032004TBext (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 601995199619971998199920002001200220032004TBext (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 3001995199619971998199920002001200220032004TBext (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 tr end 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 we re determined using the new revised IMPROVE algorithm to select the 20% worst a nd 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 visibil ity for the 20% worst days is estimated by assuming that fine particle concentrations fo r natural background are normally distributed and

the 90 th 

# percentile of the annual distribution repres ents 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 92 nd 

# percentile of a normal

distribution would be a better re presentation of the mean of th e 20% worst days than the 90 th


# percentile 16 

# . EPA’s guidance did not estimate the co ntributions of indivi dual fine particle components to natural background visibility on the 20% worst days. Following development of the new IMPROVE algorithm, a workgr oup 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 ea ch 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’ Wi nHaze Visual Air Quality Modeler (Ver. 2.9.6). Figure 3-12 presents a spit im age depicting simulated baselin e conditions and 2018 projected

conditions at the GRSM1 site. There is a discerna ble difference in visibility between these time periods. Figure 3-13 depicts the estimated natu ral 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 co ntribution to aerosol ex tinction (Rayleigh not in cluded), and 2064 natural condition estimates generated using the revised ca lculations 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 a nd 3-17 indicate species contribution to mass (μg/m 3 

# ) on the 20% worst and best extinction days.

Ammonium sulfate is the largest contributor to visibility impairme nt on the 20% haziest days in the baseline 2000-2004 pe riod (69-74%) at all the IMPROV E sites in the VISTAS region except Everglades National Park in Florida, wh ere Ammonium sulfate is a close second to Particulate Organic Mate rial, POM (40 and 45%, respectively). Particul ate Organic Material (also referred to as organic car bon) is the second larg est contributor to aeros ol extinction at all other sites, contributing to between 13 and 18% of aerosol extinction on the worst days.

Baseline conditions for 20% worst da ys at the inland sites (182.2 - 241.4 Mm -1 

# ) average higher

3- 17

# than conditions measured at the coastal site s (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 th e 20% worst days, but for the 20% best days it contribu tes to between 2

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

Ammonium sulfate, CM and PO M are the largest contributo rs 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. Ammoni um 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 ar e most likely to occur in the summer, and the 20% best days occur most frequently durin g the winter. For coastal ROMA1 site, the 20% haziest days can occur year round, with the summe r days being dominated by ammonium sulfate, while the worst days that occur between Octobe r and February have large contributions from ammonium sulfate, POM and some times 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 GRSM 1 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.

SO 4 Amm.

NO 3 POM LAC Soil CM Sea

Salt b ext (Mm -1 ) dV VR (km) b ext (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 11.0VISTAS 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 10.9VISTAS 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 11.5non-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.

SO 4 Amm.

NO 3 POM LAC Soil CM Sea

Salt b ext (Mm -1 ) dV VR (km) b ext (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 5.9VISTAS 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 5.0VISTAS 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 4.1non-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 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (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 60SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (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-

220 5 10 15 20 25 30 35SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASMass (μg/m3) Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4



# Figure 3-16. Contributions to mass (μg/m 3 

# ) 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 12SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASMass (μg/m3) Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4



# Figure 3-17. Contributions to mass (μg/m 3 

# ) 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-0 2 A -0

2 M-0 2 J- 02 J- 02 A-02 S- 0 2 O - 0 2 N-0 2 D-0 2Extinction (Mm-1) 

### 20% W > 140

0 100 200 300 400

J-01 F- 0 1 M -0

1 A -0

1 M -0

1 J-01 J-01 A-01 S- 0 1 O - 0 1 N-01 D-01Extinction (Mm-1) 

### 20% W > 139

0 100 200 300 400

J-00 F- 0 0 M- 0 0 A-00 M-0 0 J- 0 0 J- 0 0 A-00 S-00 O-0 0 N-00 D-0 0Extinction (Mm-1)



### 20% W > 139

0 100 200 300 400

J-03 F - 0 3 M -0

3 A -0

3 M-03 J-0 3 J-03 A -0

3 S- 0 3 O- 0 3 N- 0 3 D-03Extinction (Mm-1)



### 20% W > 130

0 100 200 300 400

J-0

4 F-04 M-0 4 A - 04 M- 04 J-0 4 J-0 4 A- 0 4 S - 04 O - 04 N- 0 4 D- 0 4Extinction (Mm-1)



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

The red line indicates the thre shold 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-0 2 M -0

2 A - 0 2 M-02 J- 0 2 J- 0 2 A-02 S -02 O-0 2 N -0

2 D-0 2Extinction (Mm-1) 

### 20% W > 102

0 50 100 150 200 250 300

J-

0 1 F -01 M -0

1 A - 01 M-01 J- 0 1 J -0

1 A-0 1 S -0

1 O-0 1 N-01 D-01Extinction (Mm-1) 

### 20% W > 133

0 50 100 150 200 250 300

J-0

0 F - 0 0 M-0 0 A-00 M -00 J-00 J-00 A- 0 0 S - 00 O-00 N - 00 D- 0 0Extinction (Mm-1)



### 20% W > 96

0 50 100 150 200 250 300

J-

0 3 F-03 M-03 A - 03 M-03 J-03 J- 0 3 A - 03 S -0

3 O-03 N-0 3 D-03Extinction (Mm-1)



### 20% W > 116

0 50 100 150 200 250 300

J-04 F- 04 M -0

4 A-0 4 M-04 J-04 J - 04 A-04 S-0 4 O-04 N-04 D-04Extinction (Mm-1)



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

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

3-

25

### y

0 50 100 150 200 250 300 350 400 4503/85/65/176/36/106/287/17/87/228/58/168/198/238/2610/1510/1810/2110/2410/2711/25/15/76/96/126/216/277/37/127/187/217/247/308/28/58/88/118/148/178/238/269/79/139/1911/182/255/25/85/176/16/136/196/227/17/77/107/167/227/318/38/68/98/128/158/219/59/89/119/173/164/275/245/276/56/116/266/297/57/177/207/268/78/108/168/198/228/258/289/39/69/99/129/211/102/216/86/116/206/266/297/87/177/207/298/48/108/168/198/258/288/319/39/129/159/3010/310/30

2000 2001 2002 2003 2004Extinction (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 70 801/81/121/151/221/261/292/123/113/294/54/84/124/154/224/2610/911/1411/2012/1412/231/71/101/191/221/312/62/152/242/273/143/204/135/256/309/19/49/2510/710/1010/1610/2511/3012/1512/211/81/111/141/232/12/72/192/283/33/93/304/267/139/149/2610/2610/2911/411/1611/2212/712/1312/221/302/22/52/172/263/193/314/94/185/125/217/210/610/1510/2711/511/2011/2612/212/512/812/1412/171/11/71/161/251/312/62/122/152/273/73/314/66/239/1810/1511/1111/1411/2311/2611/2912/212/812/1112/23

2000 2001 2002 2003 2004Extinction (Mm-1) Sea Salt

CM

Soil

LAC

POM

Amm NO3

Amm SO4 Rayleigh



# Figure 3-21. Contributi ons to light extinction (Mm -1 

# ) for the 20% best vi sibility days in 2000-

2004 at the GRSM1 site.

3- 26

### y

0 50 100 150 200 250 300 350 4001/12/122/235/37/17/87/127/157/198/128/168/198/269/1510/1510/1811/511/812/812/111/11/42/213/24/105/135/165/195/285/316/157/97/127/158/88/238/268/299/199/229/2810/3111/911/1812/31/171/292/132/162/224/205/26/46/77/17/47/77/167/197/257/318/249/119/149/1710/2010/2310/2612/71/92/202/263/255/275/306/56/116/206/236/267/117/298/198/259/69/99/129/2110/310/610/1210/211/101/131/222/243/134/95/65/125/276/207/117/147/207/237/268/48/199/39/249/3010/310/2710/3012/5

2000 2001 2002 2003 2004Extinction (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 70 801/51/151/292/264/224/266/146/176/287/298/28/239/99/129/1810/910/2412/2312/261/101/312/123/144/255/16/276/307/38/28/59/109/1610/710/1010/1310/2211/311/1511/2411/2712/612/1812/241/141/233/33/63/94/24/144/175/56/106/196/226/257/108/158/309/29/59/209/239/2610/1112/191/242/52/233/314/95/215/246/146/177/147/237/268/169/39/159/2711/511/1411/1711/2012/1112/2012/231/72/122/152/273/13/43/73/314/156/146/177/298/18/139/2111/211/511/1111/2612/212/1112/1412/20

2000 2001 2002 2003 2004Extinction (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 prog ress to be tracked using the Haze Index (deciviews), which is determined as a logar ithmic 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 natu ral 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 al gorithm for the GRSM1 and ROMA1 sites are presented in Figures 3-24 and 3-25 and for other Class I area s in Appendix H. Natural conditions for the glidepath usi ng the original IMPROVE equati on are EPA default calculations, and natural conditions for the path using the re vised 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 coasta l sites and thus a higher rate of improvement is required in each decade to ach ieve a uniform rate of progr ess 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 351986-19901988-19921990-19941992-19961994-19981996-20001998-20022000-2004200620082010201220142016201820202022202420262028203020322034203620382040204220442046204820502052205420562058206020622064Deciviews (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 na tural 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 351986-19901988-19921990-19941992-19961994-19981996-20001998-20022000-2004200620082010201220142016201820202022202420262028203020322034203620382040204220442046204820502052205420562058206020622064Deciviews (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 usi ng both the original IMPROVE algorithm using EPA default natural conditions (Default NB) and the new IMPROVE algorithm using the revised estimate of na tural background conditions (NB2).

The glidepath defined using deciview does not provide information regarding the relative contributions of individual specie s to overall visibility. This in formation is useful because some species (sulfate and nitrate) originate from larg ely anthropogenic sources, while others (organic carbon, elemental carbon) originate from a mixtur e 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 ch arts for total extinction and for ammonium sulfate, ammonium nitrate and POM extinction at the GRSM1 site, a nd 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, transl ates to a curved line

when converted to total extinction in Mm -1 

# . The dV contribution can not be constructed for individual species, so li near approximations in Mm -1 

# are used for the species specific glidepaths to approximate progress goals. 2018 projecte d extinction values were provided by ENVIRON based on CMAQ modeling of the 2018 Base G1 inve ntory. Natural conditions presented here do

not use the revised NC2 numbers that became available in Augus t, 2007 but differences between the original set provided by IMPROVE , and the revised set were minima l. Plots for each site in and around the VISTAS region are included in Appendix I.

3-

29

# For total extinction, the proj ected 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 projecte d value of 54 Mm -1 

# in 2018. POM again needs little improvement to reach natural c onditions, and projecte d 2018 values are on the glidepath. For ammonium nitrate, projected 2018 values are lower than the ba seline emissions, slightly above the glidepath, but still low, w ith projected 2018 values of 5 Mm -1



# .

0 50 100 150 200 25020002002200420182064Extinction (Mm-1) 

### Total Bext

Baseline

Glide Slope

2018 Base G

Natural Conditions



# Figure 3-26. Glidepat h depicting total b ext 

# (Mm -1 

# ) for 20% worst days at the GRSM1 site.

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300 20 40 60 80 100 120 140 160 180 20020002002200420182064Extinction (Mm-1) 

### Ammonium Sulfate

Baseline

Glide Slope

2018 Base G

Natural Conditions



# Figure 3-27. Glidepath depicti ng Ammonium Sulfate for 20% wo rst days at the GRSM1 site.

0 1 2 3 4 5 6 7 8 9 1020002002200420182064Extinction (Mm-1) 

### Ammonium Nitrate

Baseline

Glide Slope

2018 Base G

Natural Conditions



# Figure 3-28. Glidepath depicti ng Ammonium Nitrate for 20% wo rst days at the GRSM1 site.

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310 5 10 15 20 25 30 35 4020002002200420182064Extinction (Mm-1) 

### Particulate Organic Matter

Baseline

Glide Slope

2018 Base G

Natural Conditions



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

GRSM1 site.

0 20 40 60 80 100 120 140 160 180 20020002002200420182064Extinction (Mm-1) 

### Total Bext

Baseline

Glide Slope

2018 Base G

Natural Conditions



# Figure 3-30. Glidepat h depicting total b ext 

# (Mm -1 

# ) for 20% worst days at the ROMA1 site.

3-

320 20 40 60 80 100 120 14020002002200420182064Extinction (Mm-1) 

### Ammonium Sulfate

Baseline

Glide Slope

2018 Base G

Natural Conditions



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

0 1 2 3 4 5 6 7 820002002200420182064Extinction (Mm-1) 

### Ammonium Nitrate

Baseline

Glide Slope

2018 Base G

Natural Conditions



# Figure 3-32. Glidepath depicti ng Ammonium Nitrate for 20% wo rst days at the ROMA1 site.

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330 5 10 15 20 25 30 3520002002200420182064Extinction (Mm-1) 

### Particulate Organic Matter

Baseline

Glide Slope

2018 Base G

Natural Conditions



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

ROMA1 site.

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# 3.6 ATTRIBUTION ANALYSIS

An attribution analysis was performed to allo w 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 compar isons 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 be fore 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 ho urly point for back trajectori es 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 pr esented in Figure 3-34. Back trajectory maps

for all VISTAS sites are included in Appendix J.

Figure 3-34. Back trajectories for the 20% Wo rst extinction days at the Great Smoky Mountains National Park (GRSM1) IM PROVE monitoring site.

3.6.2 Residence Time Maps

Residence time maps were constructed us ing 2000-2004 back trajectories. 20% worst extinction days were determined using th e substituted IMPROVE RHR2 (new IMPROVE algorithm, updated 3/06) data set. Each hourly point for back trajecto ries with end dates

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35

# corresponding to the 20% worst visibility da ys was counted and summed into 1⁄4 degree horizontal grid cells of latitude and longitude. The percent of hourly point s 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 reachin g the IMPROVE monitors. A residence time map for the 20% worst measured extinction days at th e GRSM1 site for trajectories with end heights of 100m is presented in Figure 3-31. 100m an d 500m residence time Maps for all VISTAS and regional sites are incl uded 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 h aze 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 fo r 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 genera ted extinction-weighted resi dence time data for each IMPROVE sites in and around the VISTAS region. These analyses used the VISTAS substituted data set, with extinction calculated using th e original IMPROVE algorithm. The original algorithm was used because these da ta 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 traject ories 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 ex tinction components including

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36

# ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), particulate organic material (POM), Light Absorbing Carbon (LAC), Soil, a nd 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 remova l processes. These char ts 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 in ternational emissions wa s used to represent species mass attributable to international sources.

Figure 3-36 and 3-37 present st acked 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 RO MA1 site. For this comparison all sulfate and

nitrate were assumed to be fu lly neutralized by particulate NH 4 + 

# (similar to IMPROVE monitoring network assumptions). Negative number s 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 comput ed as the difference between total measured

mass and international modeled mass.

International attribution at the GRSM1 site ra nges 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, attr ibution was between 0 a nd 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.

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### GRSM1

Domestic and Internationa l Aerosol Mass by Species 20% Worst Days (2002)

0 5 10 15 20 25 30 35DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 9/17Mass (μg/m3)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt



# Figure 3-36. Stacked bar charts of mass at the GRSM1 site depict ing domestic and international contributions to the 20% worst days in 2002.

GRSM1

Domestic and Internationa l Aerosol Mass by Species 20% Best Days (2002)

0 2 4 6 8 10 12DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 12/22Mass (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 dome stic and international contributions to the 20% best days in 2002.

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### ROMA1

Domestic and Internationa l Aerosol Mass by Species 20% Worst Days (2002)

0 5 10 15 20 25 30 35 40DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 12/7Mass (μg/m3)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt


# Figure 3-38. Stacked bar charts of mass at the ROMA1 site depict ing domestic and international contributions to the 20% worst days in 2002.

ROMA1

Domestic and Internationa l Aerosol Mass by Species 20% Best Days (2002)

0 2 4 6 8 10 12 14 16 18 20DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 12/19Mass (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.

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