1 

## IMPROVE Data Substitution Methods for Regional Haze Planning

Extended Abstract # 58

Cassie M. Archuleta 1 , Joseph P. Adlhoch 1 , Scott A. Copeland 2 , Warren H. White 3 , Charles E. McDade 3 , Patricia Brewer 4 , Tom Moore 5 ;

1 Air Resource Specialists, Inc. (ARS), 1901 Shar p Point Dr., Suite E, Fort Collins, CO 80525 2 Cooperative Institute for Research in the At mosphere (CIRA), Washakie Ranger Station, 333 East Main Street, Lander, WY 82520 3 University of California, Crocker Nuclear La boratory, One Shields Avenue, Davis, CA 95616 4 Visibility Improvement State and Tribal Associ ation of the Southeast (VISTAS), Division of Air Quality, NC-DNR Ashville Regional Offi ce, 2090 U.S. 70 Highway, Swannanoa, NC 28778 5 Western Governors Association, Western Regional Air Partne rship (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 Vi sual Environments (IMPROVE) program. RHR guidance outlines data completeness requirements designed to balance the need for data from individual days, seasons, and years to be r easonably representative of ambient aerosol concentrations at each monitoring site. For site s 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 near by donor sites which had favorable long-term comparisons. 

### RHR REQUIREMENTS

Regional Haze Rule (RHR) guidance 1 outlines IMPROVE aerosol data completeness requirements that include the following conditions:

• Individual samples must contai n all species required for the ca lculation 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 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 data2 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 su lfur 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 missi ng 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 surroga te as described above can be patched, or replaced, by a seasonal average if the patc hing 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 a nd 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 re quirements for the 2000-2004 baseline period. Additionally, some sites that met the RHR require ments were missing years that were desirable for planning and modeling purposes.

The WRAP, CENRAP, Midwest RPO and VISTAS, wo rking with states and various technical support contractors, developed additional data subs titution methods to the desired years of data at various sites.

• Carbon substitution:

° Organic carbon (OC) is estimated using th e historic comparison between organic H (Org_H) and OC at the site. Org_H is estimated by subtra cting 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) is determined using comparisons between OC and EC at the site.

• Donor site substitution:

° A nearby IMPROVE site with favorable l ong-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 pr edecessor 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 exte nd donor site substitu tion 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 substituti on for the BRET1 CENRAP site for VISTAS planning purposes.

• In 2005, Scientists from the State of Missouri an d from UC Davis collab orated to devise the carbon substitution methodology to fill in mi ssing OC and EC data for 2000-2004 baseline period at the MING1 site 2

.

• In 2006, Scott Copeland, with the Cooperative Institute for Research in the Atmosphere (CIRA), substituted the years 2002-2004 substitute d data for the BOWA1 Midwest RPO site using linear regression m odels with the VOYA2 site as a donor site.

• In 2007, the WRAP requested that ARS to perf orm data substitution methods similar to VISTAS methods to complete RHR baseli ne years at ten WRAP IMPROVE sites.



### RESULTS

Table 1 lists the substituted sites, the specific don or sites, and the baseline years where additional substitution was applied, and Table 2 presents eac h 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 VIST AS planning purposes. ** Southeastern Aerosol Research and Characterization (SEARCH) site4 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. SO 4 Amm. NO 3 OC/ EC Soil CM Sea Salt 2001 25 4% 92% 92% 92% 92% 96% 92% BALD1 2002 21 57% 95% 95% 38% 100% 100% 100% AZ TONT1 2002 14 93% -- -- -- 7% 57% 7% KAIS1 2002 33 -- 91% 91% 94% 97% 97% 97% 2000 28 -- 86% 86% 86% 100% 100% 100% 2001 33 -- 88% 94% 88% 85% 91% 85% RAFA1 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% 2001 60 -- 80% 80% 80% 82% 97% 82% UT CAPI1 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%MWRPO 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 deem ed incomplete under RHR guidance were candidates for additional data substitutions. Th e carbon substitution method was not sufficient to complete years at any of these sites, so the donor site method wa s 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 cl ogging of some modules (especia lly 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 substitu tion 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 malfunc tion resulted in three out of four IMPROVE module samplers invalid for three out of ever y 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) database 3 . These data are referred to as “substitu ted” 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 Qual ity 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, 3 rd 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, Region al Planning Organizations, Substituted Data, Visibility