# Appendix B

. 3

Trends in Speciated PM2.5 and Visibility across Monitoring Networks in the Southeastern US

Tennessee Department of Environment and Conservation Division of Air Pollution Control 9 th 

### Floor L&C Annex 401 Church Street Nashville, TN 37243

### 1



# Tr ends in Speciated PM2.5 and Visibility across Monitoring 1 

# Networks in the Southeastern US 2
3
Patricia F. Brewer 4 VISTAS, 2090 US Highway 70, Swannanoa, NC 28778 5 Joseph P. Adlhoch 6 Air Resource Specialists, Inc., 1901 Sharp Point Dr. Suite E, Fort Collins, CO 80525-4429 7 8
ABSTRACT 9 10 Trends in fine particulate matter less than 2.5 microns in diameter (PM 2.5 

### ) and visibility in the 11 Southeastern U.S. were evaluated for sites in the Interagency Monitoring of Protected Visual 12 Environments (IMPROVE), Speciated Trends Network (STN), and Southeastern Aerosol 13 Research and Characterization Study (SEARCH) networks. These analyses are part of the 14 technical assessment by VISTAS, the regional planning organization for the Southeastern states, 15 in support of State Implementation Plans for the regional haze rule. 16 17 At all VISTAS IMPROVE sites, ammonium sulfate and organic carbon are the largest and 18 second largest contributors, respectively, to light extinction on both the 20% haziest and 20% 19 clearest days. Ammonium nitrate, elemental carbon, soils, and coarse particles make 20 comparatively small contributions to PM 2.5 

### mass and light extinction on most days at the Class I 21 areas. At Southern Appalachian sites, the 20% haziest days occur primarily in the late spring to 22 fall, while at coastal sites, the 20% haziest days can occur through out the year. Levels of 23 ammonium sulfate in Class I areas are similar to those in nearby urban areas, and generally 24 higher at the interior sites than the coastal sites. Concentrations of organic carbon, ammonium 25 nitrate and, sometimes, elemental carbon, tend to be higher in the urban areas than in nearby 26 Class I areas, although differences in measurement methods complicated comparisons between 27 networks. Results support regional controls of sulfur dioxide for both regional haze and PM 2.5 

### 28 implementation and suggest that controls of local sources of organic carbon, elemental carbon, or 29

### nit rogen oxides might also be considered for urban areas that are not attaining the annual

30 National Ambient Air Quality Standard for PM 2.5 

### . 31 32
IMPLICATIONS 33 34 State Implementation Plans for the first phase of implementation of the Regional Haze Rule are 35 due in December 2007. This paper describes the pollutant contributions on the haziest and 36 clearest days in Class I areas in the southeastern U.S. and compares fine particle composition in 37 Class I areas to those in nearby urban areas. Several of the urban areas are also nonattainment 38 areas for the national ambient air quality standard for fine particulate matter. States are using the 39 results of the analyses described in this paper to design more effective emissions control 40 strategies for regional haze and related air quality issues. 41
42
INTRODUCTION 43
44 Visibility is a term that refers to the color, contrast, and outline of objects viewed in a landscape. 45 Particulate matter and gases in the atmosphere scatter or absorb light and reduce visibility by 46 reducing the clarity and distance that can be discerned by the human eye. Regional haze 47 describes the cumulative visibility impact from numerous air emission sources across a broad 48 geographic region. 49 50 The 1977 Amendments to the Clean Air Act set a national visibility goal to prevent “any future, 51 and remedy any existing, impairment of visibility in mandatory Class I Federal areas” which 52 results from manmade air pollution. In 1999 the U.S. Environmental Protection Agency (EPA) 53 promulgated regional haze regulations to address visibility at 156 designated Class I areas 54 (national parks greater than 6000 acres and wilderness areas greater than 5000 acres) 1 

### . The 55 regional haze rule calls for States to establish “reasonable progress goals” for each Class I area to 56 improve visibility on the 20% haziest days and to prevent visibility degradation on the 20% 57 clearest days. States are to evaluate their contributions to visibility impairment at Class I areas 58 both within and outside the State and to develop long-term control strategies to reduce emissions 59 of air pollutants that impair visibility. The national goal is to return visibility to natural 60

### bac kground levels by 2064. Using the period 2000 to 2004 as the baseline period, States are to

61 evaluate progress in improving visibility by 2018 and every 10 years thereafter. State 62 Implementation Plans for the first phase of the regional haze regulation are due in December 63 2007. The southeastern states illustrated in Figure 1 are working together through a regional 64 planning organization, Visibility Improvement – State and Tribal Association of the Southeast 65 (VISTAS) to conduct the technical analyses to support the states’ regulatory planning for 66 regional haze and related air quality issues. 67 68 The National Ambient Air Quality Standard for particulate matter was revised in 1997 to set 69 annual and 24-hr limits (15.0 and 65 μ g/m 3 

### , respectively) for particles with diameters less than 70 2.5 microns (PM 2.5 

### ). In December 2004, several counties in the southeastern states were 71 designated as not attaining the annual PM 2.5 

### standard. These counties include several urban 72 areas near Class I areas, for example: Atlanta, GA; Birmingham, AL; Charleston, WV; 73 Louisville, KY; and Chattanooga and Knoxville, TN (PM 2.5 

### design value for years 2002-2004 in 74 these cities ranged between 17.5 and 15.7 μ g/m 3 

### ) 2 

### . By April 2008, affected states are required 75 to submit a State Implementation Plan demonstrating control strategies to attain the annual PM 2.5 

### 76 standard by April 2010. 77 78 This paper summarizes current fine particle and visibility conditions at Class I areas in the 79 southeastern U.S, and compares fine particle loadings at Class I areas with nearby urban areas in 80 the region. These analyses are being used by VISTAS states to better understand source 81
contributions to PM 2.5 

### and regional haze in the southeastern United States and to design effective 82 emissions control strategies for State Implementation Plans. 83 84
METHODS 85 86
Fine Particle Measurements 87 Fine particle mass and components are being measured at several sites in the southeastern U.S. 88 The locations of the 18 Class I areas in the VISTAS region (plus Breton Wildlife Refuge located 89 on the Louisiana coast of the Gulf of Mexico), and the locations of monitoring sites included in 90 analyses described in this paper are illustrated in Figure 1. 91

### 92 The Interagency Monitoring of Protected Visual Environments (IMPROVE) network monitors

93 fine particle concentrations at Class I areas throughout the U.S. 3 

### including 15 of the 18 Class I 94 areas in the VISTAS region. IMPROVE collects fine particle samples on filters for 24 hours 95 every third day. EPA and the State and Local Agencies monitor fine particle components at 96 Speciated Trends Network (STN) sites in both urban and rural areas using filter samples 97 collected every third or every sixth day. 4 

### The Southeastern Aerosol and Research 98 Characterization Study (SEARCH) monitors fine particle concentrations at 4 paired urban and 99 rural sites (8 sites total) in Alabama, Georgia, and the Gulf Coast of Florida and Mississippi. 5 

### 100 SEARCH filter samples are collected once every third day (daily in Atlanta, GA). IMPROVE 101 monitoring began between 1988 and 1993 for several Class I areas in the VISTAS states; 102 monitors were installed at additional sites during 2000. SEARCH operations began in 1999, 103 while STN sites reported in this paper began monitoring in 2001 or 2002. 104 105 The three networks use similar methods for sample collection and analysis, but differences 106 between programs complicate inter-comparison of monitoring results. All three networks collect 107
PM 2.5 

### on Teflon, nylon, and quartz filters. For all networks, the Teflon filters are weighted 108 gravimetrically to define PM 2.5 

### . IMPROVE uses X-Ray Fluorescence (XRF), and Proton Elastic 109 Scattering Analysis (PESA) to analyze elements. SEARCH uses XRF and STN uses Energy 110 Dispersive X-Ray Fluorescence (EDXRF) to analyze elements. IMPROVE and STN define 111 “fine soils” as a weighted sum of aluminum (Al), calcium (Ca), iron (Fe), silicon (Si), and 112 titanium (Ti). SEARCH defines “major metal oxides” (similar to fine soils) as a somewhat 113 different weighted sum of these elements and potassium (K). 114 115 IMPROVE uses a sodium carbonate denuder in the nylon filter sample inlet to remove acidic 116 gases. SEARCH uses both sodium carbonate and citric acid denuders upstream of its 117 Teflon/nylon/glass fiber filter packs to remove acidic gases and ammonia (NH 3 

### ), respectively. 118 Some STN samplers use a magnesium oxide denuder to remove acidic gases prior to the nylon 119 filter. All three networks analyze the nylon filters using ion chromatography and report sulfate 120 (SO 4 

### ), chloride (Cl), and nitrate (NO 3 

### ). (Valences are omitted for brevity.) SEARCH includes 121
non-volatilized NO 3 

### from the Teflon filter in reported NO 3 

### . STN and SEARCH both report 122

### am monium (NH 4 

### ). SEARCH uses a citric acid coated cellulose filter behind the Teflon filter to

123 capture volatilized NH 4 

### ; STN does not. 124 125
IMPROVE infers NH 4 

### concentrations from the combined concentrations of SO 4 

### and NO 3 

### , by 126 assuming both are fully neutralized by NH 4 

### as ammonium sulfate, (NH 4 

### ) 2 

### SO 4 

### and ammonium 127 nitrate, NH 4 

### NO 3 

### . To test this assumption, for 13 of 15 IMPROVE sites in the VISTAS region, 128 the nylon filters have been analyzed for NH 4 

### (beginning 1997 for Dolly Sods, Shenandoah, and 129 Great Smoky Mountains and since October 2002 for 10 additional Southern Appalachian and 130 Coastal sites). 131 132 The quartz filters are used to analyze carbon. SEARCH uses a carbon denuder upstream of its 133 quartz filter to remove organic gases from the sample. IMPROVE uses a backup quartz filter on 134 a small fraction of samples to estimate the extent of adsorbed organic gases. The STN data 135 reported on the EPA Air Quality System website 6 

### do not include a correction factor for carbon 136 artifacts. However, EPA has evaluated carbon on backup filters and now recommends a 137
correction factor for each of the STN monitor brands 7 

### . The separation of particulate organic 138 carbon (OC) from elemental carbon (EC) is operationally defined. IMPROVE and SEARCH use 139 Thermal Optical Reflectance (TOR) while STN uses Thermal Optical Transmittance (TOT) for 140 carbon analysis. The temperature of separation of EC is higher for TOT than for TOR. Using 141 the TOT method, STN reports higher OC values and lower EC values than IMPROVE and 142 SEARCH. All three networks use a mass multiplier of 1.4 to account for species associated 143
with carbon. 144 145 IMPROVE uses a second Teflon filter to collect particles with diameters less than 10 microns 146 (PM 10 

### ). SEARCH uses a separate sampler to collect PM 10 

### . STN does not measure PM 10 

### . 147
Coarse mass is calculated as the difference between PM 10 

### and PM 2.5 

### and can be calculated for 148
IMPROVE and SEARCH but not for STN sites. The difference between mass measured 149 gravimetrically on the PM 2.5 

### filter and the reconstructed mass is reported as an unidentified 150 component. The unidentified component may be positive or negative and is the net result of 151 positive and negative artifacts on the filters, unmeasured species, and measurement errors. 152 153

### Da ta for the years 2000 – 2003 8, 9 

### for IMPROVE sites in the VISTAS region are reported here.

154 Data were compared to SEARCH 10 

### for the years 2000 – 2003 and to STN 6 

### for the years 2002 – 155 2003. Data completeness requirements outlined by the EPA for tracking progress under the 156 Regional Haze Rule 11 

### (valid data for at least 75% of days in a year and for at least 50% of the 157 days in each quarter) were adopted and applied to IMPROVE, SEARCH, and STN data sets. 158 Table 1 lists the years determined to have complete data sets for IMPROVE sites under these 159 requirements. All SEARCH and STN sites used in this analysis met these same requirements for 160 the time periods analyzed. 161 162 Calculating Light Extinction 163 Light extinction is a measure of visibility that can be estimated from the measured (or modeled) 164 concentrations of the components of fine particle mass. Total light extinction consists of both 165 scattering of light by particles and absorption of light by gases (e.g., nitrogen dioxide) and 166 particles (e.g., light-absorbing carbon). A particle’s chemical composition, size, shape, and 167 mixture with other chemical components affect the efficiency of light extinction. Particles in the 168 size range of 0.1 to 1.0 microns are most efficient at scattering light. Ammonium sulfate, 169 (NH 4 

### ) 2 

### SO 4 

### , and ammonium nitrate, NH 4 

### NO 3 

### , particles are hygroscopic and absorb increasingly 170 more water at higher relative humidity. The acidity of SO 4 

### particles also affects water 171 absorption; fully neutralized ammonium sulfate, (NH 4 

### ) 2 

### SO 4 

### , absorbs less water than the more 172 acidic ammonium bisulfate (NH 4 

### HSO 4 

### ) or sulfuric acid (H 2 

### SO 4 

### ). Some organic carbon species 173
absorb water but the amounts are variable and are less well defined. 174 175
EPA guidance for calculating light extinction 11 

### , which is based on the protocol defined by the 176 IMPROVE program 12-15 

### was followed for this analysis. The extinction (scattering or absorption) 177 efficiency of each species is multiplied by the measured species mass. Particle components are 178 assumed to act as if in an external mixture (single chemical species per particle) even though 179 particles actually occur in internal mixtures of different chemical species (chemical interactions 180 could alter extinction efficiency). Sulfate is assumed to be fully neutralized. The extinction 181 efficiencies for ammonium sulfate and ammonium nitrate are assumed to be equal (3 m 2 

### /g) and 182 less than that of organic carbon mass (4 m 2 

### /g). Scattering enhancement factors are included for 183 ammonium sulfate and ammonium nitrate to account for increased scattering at higher relative 184

### humi dity. Monthly average “climatologically-representative” enhancement factors appropriate 185 for each Class I area are used in the calculation. The measured organic carbon is multiplied by a 186 factor of 1.4 to account for other chemical species associated with carbon in the total organic 187 carbon mass. A value of 10 inverse megameters (Mm -1 

### ) is added to account for extinction due to 188 scattering from molecules in a clean atmosphere (Rayleigh conditions). The full extinction 189 equation is: 190 191
b ext 

### = 3 f s 

### (RH) [(NH 4 

### ) 2 

### SO 4 

### ] + 3 f n 

### (RH) [NH 4 

### NO 3 

### ] + (1) 192 4 [OCM] + 1 [SOIL] +0.6 [Coarse] + 10 [LAC] + 10 193 194
Where b ext 

### = calculated extinction, in units of inverse megameters (Mm -1 

### ) 195 f(RH) = scattering enhancement factor based on relative humidity 196 OCM = Organic Carbon Mass defined as 1.4 times measured Organic Carbon 197 LAC = Light Absorbing Carbon (typically represented by measured Elemental Carbon) 198 199 Uncertainties in the calculation of light extinction include: 200

• measurement methods for fine particle mass and composition 201

• the factor used to calculate total organic carbon mass 202

• the assumed extinction efficiencies for the fine mass components and for the unidentified 203 components of coarse mass 204

• the lack of contribution by unidentified fine mass 205

• the assumed scattering enhancement factors for relative humidity 206 207 The IMPROVE Steering Committee is currently reviewing the assumptions used to calculate 208 light extinction and will make recommendations for modifications of the above assumptions 209
based on the most recent data 16, 17 

### . This paper does not attempt to address the accuracy of the 210 current assumptions or potential modifications to these assumptions. 211 212
RESULTS 213 214 Visibility and Fine Particle Trends in VISTAS Class I areas 215

### Ei ght of the 15 IMPROVE sites in the VISTAS region have complete data sets for the four year

216 period 2000-2003 (see Table 1), as defined by EPA’s Guidance for Tracking Progress Under the 217 Regional Haze Rule 11 

### . Three sites had valid data for 2001-2003, but not for 2000. There are 218 only two years of valid data for St. Marks, FL, and Swanquarter, NC and only one year of valid 219 data for Cohutta, GA and Shining Rock, NC. For the latter four sites, contributions to light 220 extinction (Figures 2-3) may be skewed by smaller sample sizes and seasonal bias in available 221 data. All IMPROVE, STN, and SEARCH sites used in quarterly analyses (Figures 4-8) meet 222 EPA’s data completeness criteria for the illustrated quarters of 2002 (at least 50% of days in the 223 quarter have valid data.) Breton, LA had no years meeting the minimum annual criteria, but data 224 do meet the quarterly criteria for first and third quarters of 2002. 225 226 Ammonium sulfate, (NH 4 

### ) 2 

### SO 4 

### , is the largest contributor to light extinction at the IMPROVE 227 sites in the VISTAS region on both the 20% haziest and 20% clearest days in the period 2000 – 228 2003 (Figures 2 and 3). Ammonium sulfate is also the largest contributor to fine particle mass 229 at the IMPROVE sites on the 20% haziest days and the 20% clearest days (not shown). 230 Extinction from (NH 4 

### ) 2 

### SO 4 

### on the 20% haziest days is higher in the interior and northern tier of 231 sites (116-161 Mm -1 

### ) than at the coastal and southern IMPROVE sites (44-85 Mm -1 

### ). On the 232 20% clearest days, extinction from (NH 4 

### ) 2 

### SO 4 

### (11-24 Mm -1 

### ) shows smaller spatial variation. 233 The exception is Shining Rock, NC, which on the 20% clearest days shows the lowest extinction 234 from (NH 4 

### ) 2 

### SO 4 

### (6 Mm -1 

### ) of all the VISTAS IMPROVE sites. Shining Rock, at 1621 m 235 elevation, may be influenced on the clearest days by regional transport of air masses above the 236 boundary layer. Because only one year (2003) at Shining Rock met the data completeness 237 criteria established for these analyses, these results may be skewed compared to the other sites, 238 but are not inconsistent with the site’s topography. Other sites with missing data show similar 239 (NH 4 

### ) 2 

### SO 4 

### contributions to nearby sites with complete records. 240 241 Organic carbon mass (OCM) is the second largest contributor to fine particle mass and light 242 extinction at VISTAS Class I areas on the 20% haziest days (Figure 2). On the 20% clearest 243 days, OCM is the second largest contributor to light extinction at all the coastal sites and most 244 interior sites (Figure 3). On the 20% clearest days, OCM can exceed (NH 4 

### ) 2 

### SO 4 

### mass at some 245
coastal IMPROVE sites and NH 4 

### NO 3 

### ,mass at all sites. Due to the hygroscopic nature of 246

### (N H 4 

### ) 2 

### SO 4 

### and NH 4 

### NO 3 

### , these components still contribute more to extinction on the 20% 247 clearest days than OCM. 248 249 Ammonium nitrate, EC, and fine soil have small contributions to fine particle mass and light 250 extinction on most days. At coastal sites, fine soil has a larger relative contribution to extinction 251 and mass than at Southern Appalachian sites. Coarse mass is higher at coastal sites than at 252 Southern Appalachian sites, possibly due to the presence of sea salt. Due to the low extinction 253 efficiency assigned to coarse mass, the contribution of this component to light extinction is low 254
at all sites. 255 256
The fractional contribution of NH 4 

### NO 3 

### to extinction is higher on the clearest days than on the 257 haziest days, even though the absolute contribution is similar between the clearest (1-9 Mm -1 

### ) 258 and haziest (2-12 Mm -1 

### ) days. In the southeastern U.S., NH 4 

### NO 3 

### formation is generally limited 259 by availability of NH 3 

### in the atmosphere 18 

### . Ammonia preferentially reacts with SO 4 

### to neutralize 260 the ion’s two negative charges. Until SO 4 

### particles are fully neutralized, little NH 3 

### is available to 261 react with nitric acid (HNO 3 

### ) and form NH 4 

### NO 3 

### . Ammonium nitrate formation is dependent on 262 temperature and relative humidity. Because NH 4 

### NO 3 

### volatilizes at higher temperatures, 263
NH 4 

### NO 3 

### concentrations in VISTAS Class I areas are lowest during the summer months and 264 highest during the winter months. 265 266 For the Southern Appalachian and interior IMPROVE sites, the 20% haziest days are most likely 267 to occur May through October. The 20% clearest days occur most frequently in the cooler 268 winter months. For the southern and coastal IMPROVE sites, the 20% haziest days occur year 269 round. Light scattering measured by nephelometer at Great Smoky Mountains, Mammoth Cave, 270 and Shenandoah National Parks is under estimated by the IMPROVE default assumptions on the 271 haziest days and over estimated on the clearest days 19 

### . Alternative assumptions that increase the 272 OCM multiplier and reflect greater extinction efficiency for SO 4 

### , NO 3 

### , and OCM at greater mass 273
concentrations 16, 17 

### result in slightly greater extinction on the 20% haziest days and slightly lower 274 extinction on the 20% clearest days. They do not change the conclusion that the haziest days at 275 Class I areas in the VISTAS region are dominated by SO 4 

### with significant contributions from 276
OCM. 2772 7 8 The relative importance of components of fine particle mass varies seasonally and spatially, as

279 illustrated in Figure 4 for Mammoth Cave, Great Smoky Mountains, and Everglades National 280 Parks, and Okefenokee and Cape Romain National Wildlife Refuges for the year 2002. 281 Ammonium sulfate is highest in the summer months at the Southern Appalachian and interior 282 sites but less variable seasonally at the southern and coastal sites. Note that NH 4 NO 3 is elevated 283 in the winter months (quarters 1 and 4) at Mammoth Cave compared to other sites. Note also 284 that fine soil is the largest component of PM 2.5 mass at Everglades in the summer quarter of 2002 285
while SO 4 mass is least in the summer quarter at Everglades. Fine soil is episodically elevated 286 at the Florida IMPROVE sites (and to a lesser extent at other IMPROVE sites) during the 287 summer months due to fine dust transported from Africa (Saharan Desert 20 ). When air masses 288 are influenced by transport from the Atlantic Ocean and African continent, SO 4 mass is low. The 289 impact of a single large fire in May 2002 near Okefenokee, GA, is illustrated in the elevated 290 average OCM for the second quarter at Okefenokee. 291 292 Network Measurement Intercomparison and Source Implications 293 VISTAS is using the year 2002 as the base year for emissions inventories and air quality 294 modeling for both the regional haze and PM 2.5 State Implementation Plans 21 . To evaluate the 295
relative contributions to PM 2.5 mass at Class I and nearby urban areas, quarterly average 296 components of PM 2.5 mass in 2002 were compared at the IMPROVE, nearby STN, and 297 SEARCH sites. Average components of PM 2.5 mass for the third quarter of 2002 (July, August, 298 September) are illustrated for selected sites in the Southern Appalachian area in Figure 5 and in 299 the Gulf and Atlantic coastal areas in Figure 6. Average particulate concentrations for the same 300 sites during the first quarter of 2002 (January, February, March) are illustrated in Figures 7 and 301 8. Birmingham, AL; Louisville, KY; Chattanooga and Knoxville, TN; and Atlanta, GA 302 (illustrated in Figures 5 and 6) are PM 2.5 nonattainment areas. 303

Sulfate. Sulfate measurement methods are comparable across the three networks and 304 measurement uncertainty is lower for SO 4 than for other components of PM 2.5 . Sulfate values in 305 quarter 3 (July, August, September) are very similar (6-9 μ g/m 3 ) across IMPROVE, STN, and 306 SEARCH sites in the southern Appalachians (Figure 5) and are generally higher than SO 4 values 307(2-6 μ g /m 3 ) across the coastal sites (Figure 6). Sulfate levels in urban areas are generally within

308
1 μ g/m 3 of those in nearby rural and Class I areas. Larger differences between Shining Rock and 309 Charlotte, NC, and between Shenandoah and Roanoke, VA on the winter days are at least 310 partially attributable to difference in elevation that lead to differences in air masses trajectories 311 and influences from regional transport between these sites. Large differences in SO 4 between 312 Cape Romain and Charleston, SC, and Okefenokee and Savannah, GA (2 μ g/m 3 during the 313 summer quarter) indicate local as well as regional source contributions in these southern coastal 314 areas. Sulfate is attributable primarily to utility and industrial sources and these are broadly 315 distributed across a large geographic region. Sulfate levels in the southern Appalachian and 316 interior urban sites are lower in winter (2-4 μ g/m 3 , Figure 7) than summer, reflecting lower rates 317 of chemical production of SO 4 from sulfur dioxide, SO 2 , in the winter (due to low winter 318 temperatures and low availability of ozone, hydrogen peroxide, and the hydroxyl radical.) 319 Sulfate levels at the coastal areas are fairly similar in winter (2-4 μ g/m 3 , Figure 8) and summer 320 and do not show as strong seasonal patterns as the interior sites. Rao, et al. compared annual 321 average constituents of PM 2.5 mass for the period March 2001 to February 2002 at 13 paired 322
IMPROVE-STN sites nationwide 7 . Quarterly average SO 4 values reported here show greater 323 variability between urban-rural pairs than reported by Rao, et al. for annual average SO 4 (0.0-0.5 324

μ g/m 3 ) for eight paired IMPROVE-STN sites in the eastern U.S. Greater rural-urban variability 325 in this analysis is attributable to a combination of seasonal variability, smaller geographic scope, 326 and local as well as regional contributions to SO 4 at these sites. 327 328
Nitrate. Nitrate measurement uncertainty is higher than that for SO 4 and is attributable to 329 differences in measurement methods between the networks. SEARCH measurements are likely 330 to have the highest accuracy because the citric acid denuder reduces the positive NO 3 artifact due 331
to reaction of NH 3 gas onto the Teflon filter. Nitrate values are low at all sites during quarter 3 332 but are higher at urban sites than at IMPROVE sites. In contrast to SO 4 , NO 3 values are higher 333 during winter months (less than 1 to greater than 2 μ g/m 3 across IMPROVE sites, Figure 7) than 334 summer months (less than 1 μ g/m 3 ). Because NH 4 NO 3 formation is generally limited by NH 3 in 335 the southeastern U.S., lower SO 4 values during the winter months mean more NH 3 is available to 336 react with nitric acid gas, HNO 3 . Also NH 4 NO 3 volatilizes at higher temperature so less is 337 present in particulate phase during the warmer summer months. As a result, NH 4 NO 3 has a 338l a r ger contribution to mass and light extinction on the 20% clearest days, which tend to occur

339 during the winter months, than on the haziest days. 340 341
Ammonium. In Figures 5 through 8, NH 4 is illustrated separately from SO 4 and NO 3 , using 342
inferred NH 4 for IMPROVE and measured NH 4 for STN and SEARCH. Inferred NH 4 values at 343
IMPROVE sites are similar to measured NH 4 at nearby SEARCH sites. STN sites generally 344
have lower measured NH 4 values than IMPROVE and SEARCH. 345 346
NH 4 measurements in all three networks are subject to positive and negative artifacts. The 347
SEARCH NH 4 measurements likely have greater accuracy and fewer artifacts than the 348 IMPROVE and STN measurements due to the use of a citric acid coated backup filter behind the 349 nylon filter, specifically designed to capture volatilized NH 4 . In special studies at Great Smoky 350 Mountains National Park, the potential loss of NH 4 off the nylon filter was evaluated using a 351 denuder/filter pack system with a phosphorous acid-coated denuder after the nylon filter to 352 capture NH 3 22 . Results indicated that for summertime samples at Great Smoky Mountains, an 353 average of 18% (with a range of 10-35%) of the NH 4 volatilized off the nylon filter. Losses of 354
NH 4 off the routine IMPROVE nylon filter may be of similar magnitude. 355 356 The validity of the assumption used in the IMPROVE equation, Eq. 1, that SO 4 is fully 357 neutralized as (NH 4 ) 2 SO 4 was tested by measuring NH4 on the nylon filters for routine 358 IMPROVE samples from 13 sites in the VISTAS region. Molar ratios of NH 4 to SO 4 were used 359 to describe the degree of neutralization of SO 4 by NH 4 . A molar ratio of 2.0 indicates fully 360 neutralized (NH 4 ) 2 SO 4 , while a molar ratio of 1.0 implies NH 4 HSO 4 (or mix of forms with 361 average molar ratio of 1.0), and a molar ratio of 0.0 indicates H 2 SO 4 . Because the more acidic 362
forms of SO 4 aerosol absorb more water and scatter more light than (NH 4 ) 2 SO 4 , three separate 363 curves have been developed to describe the light extinction enhancement factor for water 364 absorption, f(RH), for (NH 4 ) 2 SO 4 , NH 4 HSO 4 , and H 2 SO 4 . The f(RH) curve for H 2 SO 4 is much 365 steeper than the f(RH) curve for (NH 4 ) 2 SO 4 and NH 4 SO 4 , so if the molar ratio of NH 4 to SO 4 is 366 less than 1.0 (indicating a greater fraction of H 2 SO 4 ), light extinction would be greater than that 367 calculated by the IMPROVE equation, Eq. 1. Monthly average molar ratios for interior and 368 coastal IMPROVE sites are always less than 2.0, frequently less than 1.5, and sometimes below 3691.0. S om e but not all sites show seasonal variation in molar ratios with the lowest ratios in the

370 fall and summer and higher ratios in the spring. Molar ratios are generally lower at the coastal 371 sites than at the interior sites. Given the likely underestimate in NH 4 values reported for 372 IMPROVE nylon filters, these monthly average molar ratios of NH 4 to SO 4 should be interpreted 373
as lower limits. 374 375 For comparison, monthly average molar ratios for NH 4 to SO 4 were calculated for SEARCH 376 sites using NH 4 collected on both the nylon filter and the backup filter. For the SEARCH sites, 377 the monthly average molar ratio is higher than at nearby IMPROVE sites and frequently close to 378 2.0 (example IMPROVE and SEARCH sites are illustrated in Figure 9.) Values are lower at 379 coastal SEARCH sites than at urban interior SEARCH sites but rarely fall below 1.4. There is 380
much less seasonal variation in the SEARCH values than seen in the IMPROVE data. It is 381 difficult to separate differences due to loss of NH 4 from IMPROVE filters from those attributable 382 to spatial differences in NH 3 emissions. We can conclude, based on SEARCH NH 4 383 measurements, that SO 4 may not be fully neutralized in the coastal areas and possibly interior 384 sites in the summer, and that light extinction by SO 4 may be slightly underestimated using the 385 IMPROVE equation, Eq. 1. Improved methods for measuring NH 4 at the IMPROVE sites are 386 required to verify this conclusion. 387 388 Organic Carbon mass. The greatest uncertainties and the largest differences in measured mass 389 are related to organic carbon mass, OCM. STN reported values for OCM do not include a 390 correction for background carbon on the quartz filter, however OC correction factors have been 391
estimated for each of the STN monitors 7 . Quarterly average OCM values for STN sites 392 illustrated in Figures 5-8 include the appropriate carbon correction factors. Corrected quarterly 393 average OCM values are 20-45% lower than reported OCM values in quarters 1 and 3 of 2002. 394 Quarterly average STN OCM values after correction are 1-5 μ g/m 3 greater than OCM values at 395 nearby IMPROVE sites. These differences are partially attributable to differences in TOR vs 396 TOT analytical methods and partially attributable to differences in source strengths between 397 urban and rural sites. STN OCM values are greater than SEARCH OCM values in Birmingham, 398 AL for both quarters 1 and 3 and in Atlanta for quarter 3, while SEARCH OCM is higher than 399 STN OCM in Atlanta, GA for quarter 1 (Figure 5). While local-scale variations in emissions 400s our c es may contribute to differences in measured OCM in Birmingham and Atlanta (the

401 SEARCH and STN monitors are not collocated), differences between analytical methods are 402 likely the major contributors to OCM differences. 403 404 Measurement of total carbon on quartz filters is comparable across the three networks, but the 405 TOT method used by STN applies a higher temperature of separation than the TOR method 406 (used by IMPROVE and SEARCH). More of the total measured carbon is reported by STN as 407 OC and less as EC than that reported by IMPROVE and SEARCH. Because analytical 408 laboratories differ subtly in application of the TOR or TOT methods, there is not currently a 409 single consistent correlation factor that can be used to compare OC reported by STN with that 410 reported by IMPROVE and SEARCH 23

. 411 412 Another source of uncertainty in the reported OCM is the accuracy of the assumption that a 413 common OC multiplier of 1.4 can be used at all sites to account for the mass of other 414 components of organic carbon compounds (e.g. hydrogen, oxygen, nitrogen, etc.). Currently 415 IMPROVE, SEARCH, and STN consistently use an OC multiplier of 1.4. Several studies and 416 reviews have recommended that a higher multiplier would be appropriate for organic carbon in 417 urban areas influenced by fossil fuels (~1.6 +/- 0.2) 24 . Multipliers of 2.1 (+/- 0.2) and 2.1-2.4 418 (+/- 0.2) are recommended for carbon from vegetative emissions and biomass burning, 419 respectively 24, 25 . If a carbon mass multiplier of 1.6 were applied to OC for measurements in 420 urban areas and a multiplier of 1.8 were applied for rural sites, the differences in OCM between 421 IMPROVE sites and urban STN and SEARCH sites would be less than illustrated in Figures 5-8. 422 423 Sources contributing to OCM vary spatially for both biogenic sources (e.g. vegetative emissions, 424 wildfire) and anthropogenic sources (e.g. automotive, truck, or construction equipment, 425 residential wood smoke, prescribed fire or land-clearing emissions). Chemical Mass Balance 426 analyses use chemical profiles as indicators for gasoline, diesel, wood smoke, meat cooking, and 427 vegetation to evaluate the relative contributions of different sources of primary organic carbon 26

. 428 Analysis of the 14 C isotope is used to identify the percentage of a carbon sample attributed to 429 fossil fuel combustion compared to recent carbon sources (e.g. wood burning or vegetative 430 emissions). Analyses of PM 2.5 samples from SEARCH sites by Zheng, et al. 26 and Edgerton, et 431al

. 2 7 i ndicate higher proportions of recent carbon in rural areas than in urban areas and higher

432 contributions from fossil carbon in urban areas than in rural areas. At both urban and rural areas, 433 primary carbon sources dominate in the winter, while secondary carbon sources are more 434 important in the summer. Wood burning contributes to the majority of the recent carbon in the 435 winter, but it is difficult to separate the contributions of wood smoke due to anthropogenic 436 activities (land clearing, prescribed fire, and residential wood burning) from those due to 437
wildfire. 438 439 At Great Smoky Mountains, analysis of 14 C isotope in PM10 samples indicates that 55-85% of 440 the total organic carbon mass measured in spring, summer, and fall is modern carbon (from 441 biomass burning or secondary conversion from biogenic emissions) and 15-40% is attributable to 442
fossil carbon 28 . Using PM 2.5 samples, fossil carbon was found to have a larger contribution in a 443 nearby urban area, Chattanooga, TN, than in the Great Smoky Mountains, but still less than 444 modern carbon for most samples 29 . To develop a better understanding of the sources of carbon, 445 VISTAS supported high-volume PM 2.5 filter samplers at Mammoth Cave, Great Smoky 446 Mountains, and Shenandoah National Parks, Cape Romain Wilderness Area, and Millbrook, NC 447 (suburban location outside Raleigh, NC) for the period April 2004-May 2005. Twenty-four 448 hour samples were collected on quartz filters every third day. Chemical Mass Balance analyses 449 and analyses of 14 C isotope are underway and will provide better characterization of fossil fuel 450 versus biogenic influences at these sites. 451 452
Elemental Carbon. Elemental carbon values are higher at urban STN sites than at nearby 453 IMPROVE sites, despite the fact that the TOT method yields lower EC than the TOR method. 454 EC values are also higher at urban SEARCH sites than at rural SEARCH and IMPROVE sites. 455 Emissions inventories indicate that industrial point sources and fires are generally localized 456 sources of EC while vehicles and equipment engines are more regionally dispersed sources. 457 458
Total Carbon Mass. Total carbon mass, TCM, (calculated as 1.4 times OC, plus EC) can be 459 compared between networks to eliminate the effect of difference between the TOR and TOT 460 analytical methods. Because EC is such a small fraction of TCM, the range for TCM between 461 urban STN sites and IMPROVE sites illustrated in Figures 5-8 is the same as the range for OCM, 4621-5 μ g/ m 3 . These differences in quarterly average TCM between rural and urban sites are

463 similar to those reported by Rao, et al. 7 for annual average TCM for IMPROVE-STN pairs in the 464
eastern U.S. 465 466
Fine Soil. Measurement methods for fine soils are comparable across the three networks, 467 although SEARCH uses a slightly different calculation of component elements. Fine soil is 468 higher at the southern and coastal sites than at the southern Appalachian sites, especially during 469 the summer months. Construction, road dust, and agriculture are major anthropogenic sources 470 of fine soil. Saharan dust is a major contributor to fine soil mass at the southern and coastal 471 sites, especially Everglades, while Asian dust is seen in fine soil at northern tier sites such as 472 Shenandoah in spring and early summer months 20 . Because fine soil has low extinction 473 efficiency, its average contribution to light extinction is generally low. 474 475
Coarse Mass. Coarse mass is higher at coastal IMPROVE sites than Southern Appalachian 476 IMPROVE sites or SEARCH sites. Sea salt is an unspeciated component of coarse mass and 477 likely contributes to higher values of coarse mass at coastal areas. 478 479
DISCUSSION 480 481 Implications for Future Monitoring 482 The IMPROVE, STN, and SEARCH monitoring networks have similar, but differing objectives 483 and differing analytical methods that complicate inter-comparison across networks. Additions of 484 an acid denuder before the nylon filter to collect NH 3 , a backup nylon filter to collect volatilized 485
NH 4 , and an acid denuder after the nylon filter to collect volatilized NH 3 would improve NO 3 486
and NH 4 measurements at IMPROVE sites. Given that these methods are labor intensive and 487 expensive to implement in the routine network, we recommend additional intensive studies in 488
different seasons and IMPROVE locations to better understand NO 3 and NH 4 chemistry in the 489
southeastern U.S. 490 491 Collated IMPROVE and STN monitors are providing information on comparability of the 492 measurements in the two networks, and EPA is already evaluating changes to the STN protocol, 493pa r t icularly for carbon, to be more similar to that used by IMPROVE. Studies currently

494 underway in VISTAS will assist in definition of contributions of primary vs secondary 495 carbonaceous species and fossil fuel vs recent carbon sources in the southeastern U.S. This 496 information, combined with other studies, can be used to improve estimates of the OCM 497 multiplier appropriate to the urban and rural areas in the southeastern U.S. 498 499 Implications for Atmospheric Modeling 500 VISTAS is modeling air quality in 2002 21 as the base year for regional haze and PM 2.5 State 501 Implementation Plans. A critical component of this analysis is to demonstrate that the 502 performance of the atmospheric model meets established performance goals. Model 503 performance is constrained by measurement uncertainty as well as uncertainties in emissions 504 inventories and representation of chemical and transport processes in the model. Differences in 505 network measurement methods contribute to measurement uncertainty, especially for organic 506 carbon mass, and these differences need to be considered when evaluating model performance 507 across the networks. Sulfate measurements are comparable across the networks. SEARCH NO 3 508 measurements are likely more accurate than IMPROVE and STN measurements, but all three 509 networks report fairly low NO 3 concentrations. Because NO 3 concentrations are low, model 510 performance can tolerate larger bias and error than for SO 4 and OCM components 21

. Given the 511 likely underestimate in NH 4 from the IMPROVE nylon filters, we cannot recommend using the 512
measured NH 4 mass from IMPROVE nylon filters as a better estimate of NH 4 for IMPROVE 513
sites than inferred NH 4 based on measured SO 4 and NO 3 . For STN sites, OCM values should be 514 corrected for background carbon before comparison to modeled OCM values. Model 515 performance evaluation should also consider that OC reported by STN is defined by TOT 516 analysis and is likely at least 20% higher than OCM reported by SEARCH and IMPROVE based 517 on TOR analysis. Consideration should be given to using a higher carbon mass multiplier than 518 1.4 for all three networks (in the range between 1.6-2.0, possibly selecting a lower multiplier for 519 urban areas than rural areas) to account for chemical species associated with carbon. 520 521
CONCLUSIONS 522 Fine particle mass and light extinction are dominated by ammonium sulfate in the southeastern 523 U.S. Ammonium sulfate levels are generally higher in the northern tier of the VISTAS states 524a nd l ow er at the coastal and southern sites. Regional SO2 controls should be effective in

525 reducing fine particulate sulfate and its contribution to light extinction and PM2.5 mass in the 526 VISTAS states. Levels of organic carbon, elemental carbon, and ammonium nitrate are 527 generally higher in urban areas than rural and Class I areas. A combination of local and regional 528 sources is likely contributing to these fine particle components. Improved understanding of the 529 relative contributions of forest fire, land clearing, or residential wood burning will be necessary 530 to determine what reductions in carbon from wood burning are feasible at urban and Class I 531 areas. Fossil carbon sources are important contributors to OCM in urban areas, suggesting 532 greater opportunity for reduction in OCM in response to anthropogenic emissions controls than 533 at Class I areas. Because secondary carbonaceous species from biogenic emissions are major 534 contributors to OCM in the southeastern U.S., particularly in the summer months, even after 535 anthropogenic controls, OCM will likely remain a major component of PM2.5 and visibility in 536 the VISTAS region. 537 538
ACKNOWLEDGEMENTS 539 540 The work reported in this paper was supported by the VISTAS regional planning organization 541 through its funding agency the Southeastern Air Resource Managers, Inc. and grants from the 542 Environmental Protection Agency. The authors thank the VISTAS Data Workgroup for 543 technical direction and are especially grateful to Dr. Ivar Tombach for technical review and 544
editorial recommendations. 545 546

REFERENCES 547

548

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Table 1 – Years determined to have complete data sets at IMPROVE sites, indicated by an ‘X’. Data completeness requirements adopted from EPA’s Guidance for Tracking Progress Under the Regional Haze Rule . The IMPROVE data set used was the February, 2005, RHR summary data set available on the VIEWS web site.

IMPROVE Site 2000 2001 2002 2003 Dolly Sods, WV X X X X S he nandoah, VA X X X X Ja m es River Face, VA X X X Mammoth Cave, KY X X X X Sipsey, AL X X X X G r eat Smoky Mtns, TN X X X X Cohut t a, GA X Shining Rock, NC X L i nville Gorge, NC X X X Sw a nquarter, NC X X Cape Romain, SC X X X X Okefenokee, GA X X X X S a int Marks, FL X X Chassahowitzka, FL X X X X Everglades, FL X X XB r ewer, P. F. and Adlhoch, J. P. Tr e nds in Speciated PM2.5 and Visibility across Monitoring Networks in the Southeastern U.S.
Figure Captions

Figure 1. Locations of Class I areas in the VISTAS region and locations of IMPROVE, SEARCH and selected STN monitors.
Figure 2. Calculated light extinction on the 20% Haziest Days in 2000 to 2003 at IMPROVE sites in the VISTAS region.
Figure 3. Calculated light extinction on the 20% Clearest Days in 2000 to 2003 at IMPROVE sites in the VISTAS region.
Figure 4. Seasonal (quarterly) variation in fine particle mass and composition at example IMPROVE sites in Southern Appalachian (Mammoth Cave and Great Smoky Mountains) and coastal (Okefenokee, Cape Romain and Everglades) areas of the VISTAS region.
Figure 5. Comparison of measured fine particle mass and composition in quarter 3 (July, August, and September) 2002 at IMPROVE and nearby STN and SEARCH sites in VISTAS’ Southern Applachian and interior area.
Figure 6. Comparison of measured fine particle mass and composition in quarter 3 (July, August, and September) 2002 at IMPROVE and nearby STN and SEARCH sites in VISTAS’ Gulf and Atlantic coastal areas.
Figure 7. Comparison of measured fine particle mass and composition in quarter 1 (January, February, and March) 2002 at IMPROVE and nearby STN and SEARCH sites in VISTAS’ Southern Applachian and interior area.
Figure 8. Comparison of measured fine particle mass and composition in quarter 1 (January, February, and March) 2002 at IMPROVE and nearby STN and SEARCH sites in VISTAS’ Gulf and Atlantic coastal areas.
Figure 9. Molar ratio of ammonium (NH4) to sulfate (SO4) at example IMPROVE and SEARCH sites in VISTAS Southern Appalachian and coastal areas.A B OUT THE AUTHORS

Pa t ricia Brewer is the Technical Coordinator for the VISTAS Regional Planning Organization for the southeastern US and is located at 2090 U.S. Highway 70, Swannanoa, NC 28778.
Joseph Adlhoch is a consultant with Air Resource Specialists, Inc., and is located at 1901 Sharp Point Dr. Suite E, Fort Collins, CO 80525-4429.

## 0 50 100 150 200 250Extinction (Mm-1) 

### C o arse So i l OC M EC N H 4 

### NO 3 

### (N H 4 

### ) 2 

### SO 4 

### R a yleighDolly Sods, WVShenandoah, VAJames Rvier Face, VAMammoth Cave, KYSipsey, ALGreat Smoky Mtns, TNLinville Gorge, NCShining Rock, NCCohutta, GASaint Marks, FLSwan Quarter, NCCape Romain, SCOkefenokee, GAChassahowitzka, FLEverglades, FLExtinction (Mm-1)



## 0 10 20 30 40 50 60Dolly Sods, WVShenandoah, VAJames Rvier Face, VAMammoth Cave, KYSipsey, ALGreat Smoky Mtns, TNLinville Gorge, NCShining Rock, NCCohutta, GASaint Marks, FLSwan Quarter, NCCape Romain, SCOkefenokee, GAChassahowitzka, FLEverglades, FL 

### C o arse So i l OC M EC N H 4 

### NO 3 

### (N H 4 

### ) 2 

### SO 4 

### R a yleigh

## 0.0 5.0 10.0 15.0 20.0Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4μg/m3 

## Un id entified

M am moth Cave, K Y O kefenokee, GA Everglades,

FL Cape Romain, SC Great Smoky Mtn., TN S o il

O CM E C

NH 4 

## NO 3 

## ( NH 4 

## ) 2 

## SO 4

## 0.0

5.0 10.0 15.0 20.0 25.0Fine Particle Mass -μg/m3 

### U n identified F i ne Soil EC OC M N O 3 

### N H 4 

### SO 4Shenandoah, VAMammoth Cave, KYSipsey, ALGreat Smoky Mtns, TNShining Rock, NCAtlanta, GABirmingham, ALLouisville, KYKnoxville, TNAtlanta, GACharlotte, NCRoanoke, VACohutta, GADolly Sods, WV 

## IM P ROVE SE A RCH S T NBirmingham, AL

## IM P ROVE SE A RCH S T NSwan Quarter, NCCape Romain, SCTampa, FLSt. Marks, FLCharleston, SCOkefenokee, GASavannah, GAChassahowitzka, FLEverglades, FLPensacola, FLBreton Island, LAGulfport, MS 

## 0.0 5.0 10.0 15.0 20.0 25.0Fine Particle Mass -μg/m3 

### U n identified F i ne Soil EC OC M N O 3 

### N H 4 

### SO 4

## 0.0 4.0 8.0 12.0 16.0Fine Particle Mass -μg/m3



### U n identified F i ne Soil EC OC M N O 3 

### N H 4 

### SO 4Shenandoah, VAMammoth Cave, KYSipsey, ALGreat Smoky Mtns, TNShining Rock, NCAtlanta, GABirmingham, ALLouisville, KYChattanooga, TNAtlanta, GACharlotte, NCRoanoke, VACohutta, GADolly Sods, WV 

## IM P ROVE SE A RCH S T NBirmingham, AL

## 0.0 4.0 8.0 12.0 16.0

IM P ROVE SE A RCH S T NSwan Quarter, NCCape Romain, SCTampa, FLSt. Marks, FLCharleston, SCOkefenokee, GAChassahowitzka, FLEverglades, FLPensacola, FLBreton Island, LAGulfport, MSFine Particle Mass -μg/m3 

### U n identified F i ne Soil EC OC M N O 3 

### N H 4 

### SO 4

## 0.0 0.5 1.0 1.5 2.0 2.5

Jan-02 M a r- 02 M ay-02 Jul-02 Sep-02 Nov-02 Jan-03 M a r- 03 M ay-03 Jul-03 Sep-03Molar Ratio



### Gr ea t Smoky Mtn, TN B i rmingham, AL Gu l fport, MS
M ammo th Cave, KY 

## S E ARCH IMP RO VE Cape Romain, SC