1 

IMPROVE Data Substitution Methods for Regional Haze 

Planning 

Extended Abstract # 58 

Cassie M. Archuleta1

, Joseph P. Adlhoch1, Scott A. Copeland2, Warren H. White3, Charles E. 

McDade3, Patricia Brewer4, Tom Moore5; 

1

Air Resource Specialists, Inc. (ARS), 1901 Sharp Point Dr., Suite E, Fort Collins, CO 80525 

2

Cooperative Institute for Research in the Atmosphere (CIRA), Washakie Ranger Station, 333 

East Main Street, Lander, WY 82520 

3

University of California, Crocker Nuclear Laboratory, One Shields Avenue, Davis, CA 95616 

4

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

Air Quality, NC-DNR Ashville Regional Office, 2090 U.S. 70 Highway, Swannanoa, NC 28778 

5

Western Governors Association, Western Regional Air Partnership (WRAP), CIRA/CSU 1375 

Campus Delivery, Fort Collins, CO 80523 

INTRODUCTION 

The EPA’s Regional Haze Rule (RHR) sets a 60-year timeline for states to improve visibility 

within federal Class I Areas from “baseline” (2000-2004) levels to “natural conditions” by 2064. 

To track progress under the RHR, states and tribes use speciated aerosol measurements collected 

by the Interagency Monitoring of Protected Visual Environments (IMPROVE) program. RHR 

guidance outlines data completeness requirements designed to balance the need for data from 

individual days, seasons, and years to be reasonably representative of ambient aerosol 

concentrations at each monitoring site. For sites with incomplete data during the baseline years 

(fewer than 3 complete years), appropriate tracking metrics cannot be calculated. Regional 

Planning Organizations (RPOs), working with states and technical support contractors, 

developed additional data substitution methods for sites that did not have the required baseline 

data. These additional substitutions include estimating missing species from other on-site 

measurements and appropriately scaling data collected from nearby donor sites which had 

favorable long-term comparisons. 

RHR REQUIREMENTS 

Regional Haze Rule (RHR) guidance1

 outlines IMPROVE aerosol data completeness 

requirements that 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 
2 

RHR guideline provides two methods to fill in missing data under specific circumstances: 

• The use of a surrogate in the data set: 

° Total sulfate is determined as 3 times the sulfur measured on the A module filter. If 

sulfur is missing, the sulfate measurement from the B module filter is used. 

° 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: 

° 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 Regional Haze Rule. 

ADDITIONAL DATA SUBSTITUTION METHODS 

After RHR prescribed data substitutions were made, some IMPROVE monitoring sites still 

failed to meet the RHR data completeness requirements for the 2000-2004 baseline period. 

Additionally, some sites that met the RHR requirements were missing years that were desirable 

for planning and modeling purposes. 

The WRAP, CENRAP, Midwest RPO and VISTAS, working with states and various technical 

support contractors, developed additional data substitution methods to the desired years of data at 

various sites. 

• Carbon substitution: 

° Organic carbon (OC) is estimated using the historic comparison between organic H 

(Org_H) and OC at the site. Org_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) 

is determined using comparisons between OC and EC at the site. 

• Donor site substitution: 

° A nearby IMPROVE site with favorable long-term comparisons and similar regional 

characteristics is identified as a donor site. Species are substituted using component 

specific correlations between the sites. 

These methods were developed over time by separate technical support contractors: 

• In 2002, as part of a comprehensive regional environmental assessment for the Southern 

Appalachian Mountains Initiative (SAMI), a predecessor of VISTAS, used linear regression 

models to substitute donor site data for five southeastern IMPROVE sites for 1991-1995. 
3 

• In 2005, VISTAS contracted with ARS to extend donor site substitution methods developed 

during SAMI to the 2000-2004 baseline period at the five VISTAS IMPROVE sites. These 

methods were later combined with the UC Davis methodology for OC and EC substitution 

(see below). VISTAS also performed substitution for the BRET1 CENRAP site for VISTAS 

planning purposes. 

• In 2005, Scientists from the State of Missouri and from UC Davis collaborated to devise the 

carbon substitution methodology to fill in missing OC and EC data for 2000-2004 baseline 

period at the MING1 site2

. 

• In 2006, Scott Copeland, with the Cooperative Institute for Research in the Atmosphere 

(CIRA), substituted the years 2002-2004 substituted data for the BOWA1 Midwest RPO site 

using linear regression models with the VOYA2 site as a donor site. 

• In 2007, the WRAP requested that ARS to perform data substitution methods similar to 

VISTAS methods to complete RHR baseline years at ten WRAP IMPROVE sites. 

RESULTS 

Table 1 lists the substituted sites, the specific donor sites, and the baseline years where additional 

substitution was applied, and Table 2 presents each site with the number of days substituted per 

year, and percent of days by species and method that were required to complete the days. 

Table 1. Sites and years where additional data substitutions were applied. 

RPO State Site Donor Site 2000 2001 2002 2003 2004 

BALD1 TONT1 -- 2 2 1 1 AZ TONT1 SIAN1 -- 1 2 1 1 

KAIS1 YOSE1 -- -- 2 1 1 

RAFA1 PINN1 2 2 2 1 1 

SEQU1 DOME1 1 1 2 2 1 CA 

TRIN1 LAVO1 -- 1 2 1 1 

MT GLAC1 FLAT1 1 1 2 2 1 

ND THRO MELA1 2 1 1 1 1 

UT CAPI1 CANY1 2 2 2 1 1 

WRAP 

WA NOCA1 SNPA1 -- 1 1 2 2 

LA BRET1* GFP** -- 2 2 2 2 CENRAP MO MING1 N/A -- 1 2 2 2 

Midwest RPO MN BOWA1 VOYA2 1 1 2 2 2 

CHAS1 SAMA1 1 1 1 2 2 FL SAMA1 CHAS1 -- 2 1 1 2 

GA COHU1 GRSM1 -- 2 1 2 1 

SHRO1 GRSM1 -- 2 2 1 1 

VISTAS 

NC SWAN1 ROMA1 -- 1 1 2 2 

-- 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 

* Data substitution for this site was performed by the VISTAS RPO for VISTAS planning purposes. 

** Southeastern Aerosol Research and Characterization (SEARCH) site 
4 

Table 2. Number of days substituted, and percent of substituted days by method and by species. 

Carbon 

Subs. Donor Site Substitutions 

RPO State Site Year 

# 

Days

Sub. OC/ 

EC 

Amm. 

SO4

Amm. 

NO3

OC/ 

EC Soil CM Sea Salt 

2001 25 4% 92% 92% 92% 92% 96% 92% BALD1 

AZ 2002 21 57% 95% 95% 38% 100% 100% 100% 

TONT1 2002 14 93% -- -- -- 7% 57% 7% 

KAIS1 2002 33 -- 91% 91% 94% 97% 97% 97% 

2000 28 -- 86% 86% 86% 100% 100% 100% 

RAFA1 2001 33 -- 88% 94% 88% 85% 91% 85% 

2002 21 -- 76% 76% 76% 86% 100% 86% 

2002 17 -- 100% 100% 100% 71% 71% 71% SEQU1 2003 35 20% 69% 69% 69% 66% 94% 66% 

CA 

TRIN1 2002 30 3% 67% 83% 67% 80% 83% 80% 

2002 21 -- 38% 95% 29% 38% 43% 38% MT GLAC1 

2003 18 -- 61% 67% 44% 78% 94% 78% 

ND THRO 2000 12 17% 83% 83% 83% 83% 83% 83% 

2000 36 -- 100% 94% 97% 100% 100% 94% 

UT CAPI1 2001 60 -- 80% 80% 80% 82% 97% 82% 

2002 32 -- 100% 100% 100% 100% 84% 100% 

2003 30 -- 80% 80% 77% 100% 100% 100% 

WRAP 

WA NOCA1 

2004 33 -- 82% 82% 94% 100% 94% 100% 

2001 26 -- 85% 88% 96% 92% 69% 96% 

2002 31 3% 39% 39% 65% 94% 90% 97% 

2003 39 79% -- -- 5% 18% 26% 21% 

LA BRET1 

2004 31 19% 71% 71% 71% 77% 87% 81% 

2002 72 100% -- -- -- -- -- -- 

2003 121 100% -- -- -- -- -- -- 

CENRAP 

MO MING1 

2004 122 100% -- -- -- -- -- -- 

2002 27 -- -- -- 100% 100% 100% 100% 

2003 29 -- -- -- 100% 100% 100% 100% 

MW 

RPO 

MN BOWA1 

2004 31 -- -- -- 100% 100% 100% 100% 

2003 99 -- 3% 3% 1% 100% 91% 98% CHAS1 

2004 114 -- 3% 3% 1% 100% 94% 100% 

2001 43 7% 91% 91% 91% 93% 86% 93% 

FL 

SAMA1 

2004 50 86% 8% 8% 14% -- -- -- 

2001 69 -- 100% 100% 100% 97% 97% 97% GA COHU1 

2003 21 -- 62% 71% 62% 90% 90% 90% 

2001 33 -- 100% 100% 100% 97% 97% 97% SHRO1 

2002 36 36% 58% 64% 58% 58% 61% 58% 

2003 44 -- 39% 39% 39% 100% 100% 100% 

VISTAS 

NC 

SWAN1 

2004 118 -- 4% 4% 6% 100% 97% 100% 
5 

For VISTAS and the WRAP, only years deemed incomplete under RHR guidance were 

candidates for additional data substitutions. The carbon substitution method was not sufficient to 

complete years at any of these sites, so the donor site method was also applied. Complete years 

were not changed, even though there may have been missing samples during those years. 

Multiple factors contributed to missing data at these sites, including sampler installation late in 

the 2000-2004 baseline period, the clogging of some modules (especially during wildfire events), 

and various equipment failures. In many cases, the bulk of individual species were available at 

sites, and only minor components were required to complete individual days. 

For the CENRAP MING1 site, all data substitution was performed using the carbon substitution 

method. The carbon data was compromised for three years due to blockage of the sampler inlet 

by mud from insects. 

For the BOWA1 substitution, an instrument malfunction resulted in three out of four IMPROVE 

module samplers invalid for three out of every seven sample days affecting all components 

except ammonium nitrate and ammonium sulfate. No other missing days were substituted. 

Substituted data sets were submitted to the Visibility Information Interchange Web System 

(VIEWS) database3

. These data are referred to as “substituted” data to differentiate from the 

RHR “patched” data. These data have also been integrated into the WRAP web-based Technical 

Support System (TSS)4 for regional haze planning. 

REFERENCES 

1. Guidance for Tracking Progress Under the Regional Haze Rule; U.S. Environmental 

Protection Agency Office of Air Quality Planning and Standards; Emissions, Monitoring 

and Analysis Division; Air Quality Trends and Analysis Group: Research Triangle Park, NC, 

2003; EPA-454/B-03-004 

2. Substitution Techniques for Missing Data; C. McDade, University of California – Davis; The 

IMPROVE Newsletter, 3rd Qtr 2005, Air Resource Specialists, Inc.; Fort Collins, CO 

3. VIEWS Home Page. See http://vista.cira.colostate.edu/views/ (accessed February 2008)

4. WRAP TSS Home Page. See http://vista.cira.colostate.edu/tss/ (accessed February 2008) 

KEYWORDS 

Aerosol, IMPROVE, Regional Haze Rule, Regional Planning Organizations, Substituted Data, 

Visibility