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 

9th Floor L&C Annex 

401 Church Street 

Nashville, TN 37243

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Appendix B.3 - 1

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1 

1 Trends in Speciated PM2.5 and Visibility across Monitoring 

2 Networks in the Southeastern US 

3 

4 Patricia F. Brewer 

5 VISTAS, 2090 US Highway 70, Swannanoa, NC 28778 

6 Joseph P. Adlhoch 

7 Air Resource Specialists, Inc., 1901 Sharp Point Dr. Suite E, Fort Collins, CO 80525-4429 

8 

9 ABSTRACT 

10 

11 Trends in fine particulate matter less than 2.5 microns in diameter (PM2.5) and visibility in the 

12 Southeastern U.S. were evaluated for sites in the Interagency Monitoring of Protected Visual 

13 Environments (IMPROVE), Speciated Trends Network (STN), and Southeastern Aerosol 

14 Research and Characterization Study (SEARCH) networks. These analyses are part of the 

15 technical assessment by VISTAS, the regional planning organization for the Southeastern states, 

16 in support of State Implementation Plans for the regional haze rule. 

17 

18 At all VISTAS IMPROVE sites, ammonium sulfate and organic carbon are the largest and 

19 second largest contributors, respectively, to light extinction on both the 20% haziest and 20% 

20 clearest days. Ammonium nitrate, elemental carbon, soils, and coarse particles make 

21 comparatively small contributions to PM2.5 mass and light extinction on most days at the Class I 

22 areas. At Southern Appalachian sites, the 20% haziest days occur primarily in the late spring to 

23 fall, while at coastal sites, the 20% haziest days can occur through out the year. Levels of 

24 ammonium sulfate in Class I areas are similar to those in nearby urban areas, and generally 

25 higher at the interior sites than the coastal sites. Concentrations of organic carbon, ammonium 

26 nitrate and, sometimes, elemental carbon, tend to be higher in the urban areas than in nearby 

27 Class I areas, although differences in measurement methods complicated comparisons between 

28 networks. Results support regional controls of sulfur dioxide for both regional haze and PM2.5

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

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30 nitrogen oxides might also be considered for urban areas that are not attaining the annual 

31 National Ambient Air Quality Standard for PM2.5. 

32 

33 IMPLICATIONS 

34 

35 State Implementation Plans for the first phase of implementation of the Regional Haze Rule are 

36 due in December 2007. This paper describes the pollutant contributions on the haziest and 

37 clearest days in Class I areas in the southeastern U.S. and compares fine particle composition in 

38 Class I areas to those in nearby urban areas. Several of the urban areas are also nonattainment 

39 areas for the national ambient air quality standard for fine particulate matter. States are using the 

40 results of the analyses described in this paper to design more effective emissions control 

41 strategies for regional haze and related air quality issues. 

42 

43 INTRODUCTION 

44 

45 Visibility is a term that refers to the color, contrast, and outline of objects viewed in a landscape. 

46 Particulate matter and gases in the atmosphere scatter or absorb light and reduce visibility by 

47 reducing the clarity and distance that can be discerned by the human eye. Regional haze 

48 describes the cumulative visibility impact from numerous air emission sources across a broad 

49 geographic region. 

50 

51 The 1977 Amendments to the Clean Air Act set a national visibility goal to prevent “any future, 

52 and remedy any existing, impairment of visibility in mandatory Class I Federal areas” which 

53 results from manmade air pollution. In 1999 the U.S. Environmental Protection Agency (EPA) 

54 promulgated regional haze regulations to address visibility at 156 designated Class I areas 

(national parks greater than 6000 acres and wilderness areas greater than 5000 acres)155 . The 

56 regional haze rule calls for States to establish “reasonable progress goals” for each Class I area to 

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

58 clearest days. States are to evaluate their contributions to visibility impairment at Class I areas 

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

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

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

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

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

64 2007. The southeastern states illustrated in Figure 1 are working together through a regional 

65 planning organization, Visibility Improvement – State and Tribal Association of the Southeast 

66 (VISTAS) to conduct the technical analyses to support the states’ regulatory planning for 

67 regional haze and related air quality issues. 

68 

69 The National Ambient Air Quality Standard for particulate matter was revised in 1997 to set 

annual and 24-hr limits (15.0 and 65 μg/m370 , respectively) for particles with diameters less than 

71 2.5 microns (PM2.5). In December 2004, several counties in the southeastern states were 

72 designated as not attaining the annual PM2.5 standard. These counties include several urban 

73 areas near Class I areas, for example: Atlanta, GA; Birmingham, AL; Charleston, WV; 

74 Louisville, KY; and Chattanooga and Knoxville, TN (PM2.5 design value for years 2002-2004 in 

these cities ranged between 17.5 and 15.7 μg/m3)

 2 75 . By April 2008, affected states are required 

76 to submit a State Implementation Plan demonstrating control strategies to attain the annual PM2.5

77 standard by April 2010. 

78 

79 This paper summarizes current fine particle and visibility conditions at Class I areas in the 

80 southeastern U.S, and compares fine particle loadings at Class I areas with nearby urban areas in 

81 the region. These analyses are being used by VISTAS states to better understand source 

82 contributions to PM2.5 and regional haze in the southeastern United States and to design effective 

83 emissions control strategies for State Implementation Plans. 

84 

85 METHODS 

86 

87 Fine Particle Measurements 

88 Fine particle mass and components are being measured at several sites in the southeastern U.S. 

89 The locations of the 18 Class I areas in the VISTAS region (plus Breton Wildlife Refuge located 

90 on the Louisiana coast of the Gulf of Mexico), and the locations of monitoring sites included in 

91 analyses described in this paper are illustrated in Figure 1. 

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92

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

fine particle concentrations at Class I areas throughout the U.S.394 including 15 of the 18 Class I 

95 areas in the VISTAS region. IMPROVE collects fine particle samples on filters for 24 hours 

96 every third day. EPA and the State and Local Agencies monitor fine particle components at 

97 Speciated Trends Network (STN) sites in both urban and rural areas using filter samples 

collected every third or every sixth day.498 The Southeastern Aerosol and Research 

99 Characterization Study (SEARCH) monitors fine particle concentrations at 4 paired urban and 

rural sites (8 sites total) in Alabama, Georgia, and the Gulf Coast of Florida and Mississippi.5100 

101 SEARCH filter samples are collected once every third day (daily in Atlanta, GA). IMPROVE 

102 monitoring began between 1988 and 1993 for several Class I areas in the VISTAS states; 

103 monitors were installed at additional sites during 2000. SEARCH operations began in 1999, 

104 while STN sites reported in this paper began monitoring in 2001 or 2002. 

105 

106 The three networks use similar methods for sample collection and analysis, but differences 

107 between programs complicate inter-comparison of monitoring results. All three networks collect 

108 PM2.5 on Teflon, nylon, and quartz filters. For all networks, the Teflon filters are weighted 

109 gravimetrically to define PM2.5. IMPROVE uses X-Ray Fluorescence (XRF), and Proton Elastic 

110 Scattering Analysis (PESA) to analyze elements. SEARCH uses XRF and STN uses Energy 

111 Dispersive X-Ray Fluorescence (EDXRF) to analyze elements. IMPROVE and STN define 

112 “fine soils” as a weighted sum of aluminum (Al), calcium (Ca), iron (Fe), silicon (Si), and 

113 titanium (Ti). SEARCH defines “major metal oxides” (similar to fine soils) as a somewhat 

114 different weighted sum of these elements and potassium (K). 

115 

116 IMPROVE uses a sodium carbonate denuder in the nylon filter sample inlet to remove acidic 

117 gases. SEARCH uses both sodium carbonate and citric acid denuders upstream of its 

118 Teflon/nylon/glass fiber filter packs to remove acidic gases and ammonia (NH3), respectively. 

119 Some STN samplers use a magnesium oxide denuder to remove acidic gases prior to the nylon 

120 filter. All three networks analyze the nylon filters using ion chromatography and report sulfate 

121 (SO4), chloride (Cl), and nitrate (NO3). (Valences are omitted for brevity.) SEARCH includes 

122 non-volatilized NO3 from the Teflon filter in reported NO3. STN and SEARCH both report 

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123 ammonium (NH4). SEARCH uses a citric acid coated cellulose filter behind the Teflon filter to 

124 capture volatilized NH4; STN does not. 

125 

126 IMPROVE infers NH4 concentrations from the combined concentrations of SO4 and NO3, by 

127 assuming both are fully neutralized by NH4 as ammonium sulfate, (NH4)2SO4 and ammonium 

128 nitrate, NH4NO3. To test this assumption, for 13 of 15 IMPROVE sites in the VISTAS region, 

129 the nylon filters have been analyzed for NH4 (beginning 1997 for Dolly Sods, Shenandoah, and 

130 Great Smoky Mountains and since October 2002 for 10 additional Southern Appalachian and 

131 Coastal sites). 

132 

133 The quartz filters are used to analyze carbon. SEARCH uses a carbon denuder upstream of its 

134 quartz filter to remove organic gases from the sample. IMPROVE uses a backup quartz filter on 

135 a small fraction of samples to estimate the extent of adsorbed organic gases. The STN data 

reported on the EPA Air Quality System website6136 do not include a correction factor for carbon 

137 artifacts. However, EPA has evaluated carbon on backup filters and now recommends a 

correction factor for each of the STN monitor brands7138 . The separation of particulate organic 

139 carbon (OC) from elemental carbon (EC) is operationally defined. IMPROVE and SEARCH use 

140 Thermal Optical Reflectance (TOR) while STN uses Thermal Optical Transmittance (TOT) for 

141 carbon analysis. The temperature of separation of EC is higher for TOT than for TOR. Using 

142 the TOT method, STN reports higher OC values and lower EC values than IMPROVE and 

143 SEARCH. All three networks use a mass multiplier of 1.4 to account for species associated 

144 with carbon. 

145 

146 IMPROVE uses a second Teflon filter to collect particles with diameters less than 10 microns 

147 (PM10). SEARCH uses a separate sampler to collect PM10. STN does not measure PM10. 

148 Coarse mass is calculated as the difference between PM10 and PM2.5 and can be calculated for 

149 IMPROVE and SEARCH but not for STN sites. The difference between mass measured 

150 gravimetrically on the PM2.5 filter and the reconstructed mass is reported as an unidentified 

151 component. The unidentified component may be positive or negative and is the net result of 

152 positive and negative artifacts on the filters, unmeasured species, and measurement errors. 

153 

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Data for the years 2000 – 20038, 9 154 for IMPROVE sites in the VISTAS region are reported here. 

Data were compared to SEARCH10 for the years 2000 – 2003 and to STN6155 for the years 2002 – 

156 2003. Data completeness requirements outlined by the EPA for tracking progress under the 

Regional Haze Rule11 157 (valid data for at least 75% of days in a year and for at least 50% of the 

158 days in each quarter) were adopted and applied to IMPROVE, SEARCH, and STN data sets. 

159 Table 1 lists the years determined to have complete data sets for IMPROVE sites under these 

160 requirements. All SEARCH and STN sites used in this analysis met these same requirements for 

161 the time periods analyzed. 

162 

163 Calculating Light Extinction 

164 Light extinction is a measure of visibility that can be estimated from the measured (or modeled) 

165 concentrations of the components of fine particle mass. Total light extinction consists of both 

166 scattering of light by particles and absorption of light by gases (e.g., nitrogen dioxide) and 

167 particles (e.g., light-absorbing carbon). A particle’s chemical composition, size, shape, and 

168 mixture with other chemical components affect the efficiency of light extinction. Particles in the 

169 size range of 0.1 to 1.0 microns are most efficient at scattering light. Ammonium sulfate, 

170 (NH4)2SO4, and ammonium nitrate, NH4NO3, particles are hygroscopic and absorb increasingly 

171 more water at higher relative humidity. The acidity of SO4 particles also affects water 

172 absorption; fully neutralized ammonium sulfate, (NH4)2SO4, absorbs less water than the more 

173 acidic ammonium bisulfate (NH4HSO4) or sulfuric acid (H2SO4). Some organic carbon species 

174 absorb water but the amounts are variable and are less well defined. 

175 

EPA guidance for calculating light extinction11 176 , which is based on the protocol defined by the 

IMPROVE program12-15 177 was followed for this analysis. The extinction (scattering or absorption) 

178 efficiency of each species is multiplied by the measured species mass. Particle components are 

179 assumed to act as if in an external mixture (single chemical species per particle) even though 

180 particles actually occur in internal mixtures of different chemical species (chemical interactions 

181 could alter extinction efficiency). Sulfate is assumed to be fully neutralized. The extinction 

efficiencies for ammonium sulfate and ammonium nitrate are assumed to be equal (3 m2182 /g) and 

less than that of organic carbon mass (4 m2183 /g). Scattering enhancement factors are included for 

184 ammonium sulfate and ammonium nitrate to account for increased scattering at higher relative 

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185 humidity. Monthly average “climatologically-representative” enhancement factors appropriate 

186 for each Class I area are used in the calculation. The measured organic carbon is multiplied by a 

187 factor of 1.4 to account for other chemical species associated with carbon in the total organic 

carbon mass. A value of 10 inverse megameters (Mm-1 188 ) is added to account for extinction due to 

189 scattering from molecules in a clean atmosphere (Rayleigh conditions). The full extinction 

190 equation is: 

191 

bext 192 = 3 fs(RH) [(NH4)2SO4] + 3 fn(RH) [NH4NO3] + (1) 

193 4 [OCM] + 1 [SOIL] +0.6 [Coarse] + 10 [LAC] + 10 

194 

Where bext = calculated extinction, in units of inverse megameters (Mm-1 195 ) 

196 f(RH) = scattering enhancement factor based on relative humidity 

197 OCM = Organic Carbon Mass defined as 1.4 times measured Organic Carbon 

198 LAC = Light Absorbing Carbon (typically represented by measured Elemental Carbon) 

199 

200 Uncertainties in the calculation of light extinction include: 

201 • measurement methods for fine particle mass and composition 

202 • the factor used to calculate total organic carbon mass 

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

204 components of coarse mass 

205 • the lack of contribution by unidentified fine mass 

206 • the assumed scattering enhancement factors for relative humidity 

207 

208 The IMPROVE Steering Committee is currently reviewing the assumptions used to calculate 

209 light extinction and will make recommendations for modifications of the above assumptions 

based on the most recent data16, 17 210 . This paper does not attempt to address the accuracy of the 

211 current assumptions or potential modifications to these assumptions. 

212 

213 RESULTS 

214 

215 Visibility and Fine Particle Trends in VISTAS Class I areas 

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216 Eight of the 15 IMPROVE sites in the VISTAS region have complete data sets for the four year 

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

Regional Haze Rule11 218 . Three sites had valid data for 2001-2003, but not for 2000. There are 

219 only two years of valid data for St. Marks, FL, and Swanquarter, NC and only one year of valid 

220 data for Cohutta, GA and Shining Rock, NC. For the latter four sites, contributions to light 

221 extinction (Figures 2-3) may be skewed by smaller sample sizes and seasonal bias in available 

222 data. All IMPROVE, STN, and SEARCH sites used in quarterly analyses (Figures 4-8) meet 

223 EPA’s data completeness criteria for the illustrated quarters of 2002 (at least 50% of days in the 

224 quarter have valid data.) Breton, LA had no years meeting the minimum annual criteria, but data 

225 do meet the quarterly criteria for first and third quarters of 2002. 

226 

227 Ammonium sulfate, (NH4)2SO4, is the largest contributor to light extinction at the IMPROVE 

228 sites in the VISTAS region on both the 20% haziest and 20% clearest days in the period 2000 – 

229 2003 (Figures 2 and 3). Ammonium sulfate is also the largest contributor to fine particle mass 

230 at the IMPROVE sites on the 20% haziest days and the 20% clearest days (not shown). 

231 Extinction from (NH4)2SO4 on the 20% haziest days is higher in the interior and northern tier of 

sites (116-161 Mm-1) than at the coastal and southern IMPROVE sites (44-85 Mm-1 232 ). On the 

20% clearest days, extinction from (NH4)2SO4 (11-24 Mm-1 233 ) shows smaller spatial variation. 

234 The exception is Shining Rock, NC, which on the 20% clearest days shows the lowest extinction 

from (NH4)2SO4 (6 Mm-1 235 ) of all the VISTAS IMPROVE sites. Shining Rock, at 1621 m 

236 elevation, may be influenced on the clearest days by regional transport of air masses above the 

237 boundary layer. Because only one year (2003) at Shining Rock met the data completeness 

238 criteria established for these analyses, these results may be skewed compared to the other sites, 

239 but are not inconsistent with the site’s topography. Other sites with missing data show similar 

240 (NH4)2SO4 contributions to nearby sites with complete records. 

241 

242 Organic carbon mass (OCM) is the second largest contributor to fine particle mass and light 

243 extinction at VISTAS Class I areas on the 20% haziest days (Figure 2). On the 20% clearest 

244 days, OCM is the second largest contributor to light extinction at all the coastal sites and most 

245 interior sites (Figure 3). On the 20% clearest days, OCM can exceed (NH4)2SO4 mass at some 

coastal IMPROVE sites and NH4NO3 246 ,mass at all sites. Due to the hygroscopic nature of 

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247 (NH4)2SO4 and NH4NO3, these components still contribute more to extinction on the 20% 

248 clearest days than OCM. 

249 

250 Ammonium nitrate, EC, and fine soil have small contributions to fine particle mass and light 

251 extinction on most days. At coastal sites, fine soil has a larger relative contribution to extinction 

252 and mass than at Southern Appalachian sites. Coarse mass is higher at coastal sites than at 

253 Southern Appalachian sites, possibly due to the presence of sea salt. Due to the low extinction 

254 efficiency assigned to coarse mass, the contribution of this component to light extinction is low 

255 at all sites. 

256 

257 The fractional contribution of NH4NO3 to extinction is higher on the clearest days than on the 

haziest days, even though the absolute contribution is similar between the clearest (1-9 Mm-1 258 ) 

and haziest (2-12 Mm-1 259 ) days. In the southeastern U.S., NH4NO3 formation is generally limited 

by availability of NH3 in the atmosphere18 260 . Ammonia preferentially reacts with SO4 to neutralize 

261 the ion’s two negative charges. Until SO4 particles are fully neutralized, little NH3 is available to 

262 react with nitric acid (HNO3) and form NH4NO3. Ammonium nitrate formation is dependent on 

263 temperature and relative humidity. Because NH4NO3 volatilizes at higher temperatures, 

264 NH4NO3 concentrations in VISTAS Class I areas are lowest during the summer months and 

265 highest during the winter months. 

266 

267 For the Southern Appalachian and interior IMPROVE sites, the 20% haziest days are most likely 

268 to occur May through October. The 20% clearest days occur most frequently in the cooler 

269 winter months. For the southern and coastal IMPROVE sites, the 20% haziest days occur year 

270 round. Light scattering measured by nephelometer at Great Smoky Mountains, Mammoth Cave, 

271 and Shenandoah National Parks is under estimated by the IMPROVE default assumptions on the 

haziest days and over estimated on the clearest days19 272 . Alternative assumptions that increase the 

273 OCM multiplier and reflect greater extinction efficiency for SO4, NO3, and OCM at greater mass 

concentrations16, 17 274 result in slightly greater extinction on the 20% haziest days and slightly lower 

275 extinction on the 20% clearest days. They do not change the conclusion that the haziest days at 

276 Class I areas in the VISTAS region are dominated by SO4 with significant contributions from 

277 OCM. 

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278

279 The relative importance of components of fine particle mass varies seasonally and spatially, as 

280 illustrated in Figure 4 for Mammoth Cave, Great Smoky Mountains, and Everglades National 

281 Parks, and Okefenokee and Cape Romain National Wildlife Refuges for the year 2002. 

282 Ammonium sulfate is highest in the summer months at the Southern Appalachian and interior 

283 sites but less variable seasonally at the southern and coastal sites. Note that NH4NO3 is elevated 

284 in the winter months (quarters 1 and 4) at Mammoth Cave compared to other sites. Note also 

285 that fine soil is the largest component of PM2.5 mass at Everglades in the summer quarter of 2002 

286 while SO4 mass is least in the summer quarter at Everglades. Fine soil is episodically elevated 

287 at the Florida IMPROVE sites (and to a lesser extent at other IMPROVE sites) during the 

summer months due to fine dust transported from Africa (Saharan Desert20 288 ). When air masses 

289 are influenced by transport from the Atlantic Ocean and African continent, SO4 mass is low. The 

290 impact of a single large fire in May 2002 near Okefenokee, GA, is illustrated in the elevated 

291 average OCM for the second quarter at Okefenokee. 

292 

293 Network Measurement Intercomparison and Source Implications 

294 VISTAS is using the year 2002 as the base year for emissions inventories and air quality 

modeling for both the regional haze and PM2.5 State Implementation Plans21 295 . To evaluate the 

296 relative contributions to PM2.5 mass at Class I and nearby urban areas, quarterly average 

297 components of PM2.5 mass in 2002 were compared at the IMPROVE, nearby STN, and 

298 SEARCH sites. Average components of PM2.5 mass for the third quarter of 2002 (July, August, 

299 September) are illustrated for selected sites in the Southern Appalachian area in Figure 5 and in 

300 the Gulf and Atlantic coastal areas in Figure 6. Average particulate concentrations for the same 

301 sites during the first quarter of 2002 (January, February, March) are illustrated in Figures 7 and 

302 8. Birmingham, AL; Louisville, KY; Chattanooga and Knoxville, TN; and Atlanta, GA 

303 (illustrated in Figures 5 and 6) are PM2.5 nonattainment areas. 

304 Sulfate. Sulfate measurement methods are comparable across the three networks and 

305 measurement uncertainty is lower for SO4 than for other components of PM2.5. Sulfate values in 

quarter 3 (July, August, September) are very similar (6-9 μg/m3306 ) across IMPROVE, STN, and 

307 SEARCH sites in the southern Appalachians (Figure 5) and are generally higher than SO4 values 

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(2-6 μg/m3

308 ) across the coastal sites (Figure 6). Sulfate levels in urban areas are generally within 

1 μg/m3309 of those in nearby rural and Class I areas. Larger differences between Shining Rock and 

310 Charlotte, NC, and between Shenandoah and Roanoke, VA on the winter days are at least 

311 partially attributable to difference in elevation that lead to differences in air masses trajectories 

312 and influences from regional transport between these sites. Large differences in SO4 between 

Cape Romain and Charleston, SC, and Okefenokee and Savannah, GA (2 μg/m3 313 during the 

314 summer quarter) indicate local as well as regional source contributions in these southern coastal 

315 areas. Sulfate is attributable primarily to utility and industrial sources and these are broadly 

316 distributed across a large geographic region. Sulfate levels in the southern Appalachian and 

interior urban sites are lower in winter (2-4 μg/m3317 , Figure 7) than summer, reflecting lower rates 

318 of chemical production of SO4 from sulfur dioxide, SO2, in the winter (due to low winter 

319 temperatures and low availability of ozone, hydrogen peroxide, and the hydroxyl radical.) 

Sulfate levels at the coastal areas are fairly similar in winter (2-4 μg/m3320 , Figure 8) and summer 

321 and do not show as strong seasonal patterns as the interior sites. Rao, et al. compared annual 

322 average constituents of PM2.5 mass for the period March 2001 to February 2002 at 13 paired 

IMPROVE-STN sites nationwide7323 . Quarterly average SO4 values reported here show greater 

324 variability between urban-rural pairs than reported by Rao, et al. for annual average SO4 (0.0-0.5 

μg/m3325 ) for eight paired IMPROVE-STN sites in the eastern U.S. Greater rural-urban variability 

326 in this analysis is attributable to a combination of seasonal variability, smaller geographic scope, 

327 and local as well as regional contributions to SO4 at these sites. 

328 

329 Nitrate. Nitrate measurement uncertainty is higher than that for SO4 and is attributable to 

330 differences in measurement methods between the networks. SEARCH measurements are likely 

331 to have the highest accuracy because the citric acid denuder reduces the positive NO3 artifact due 

332 to reaction of NH3 gas onto the Teflon filter. Nitrate values are low at all sites during quarter 3 

333 but are higher at urban sites than at IMPROVE sites. In contrast to SO4, NO3 values are higher 

during winter months (less than 1 to greater than 2 μg/m3334 across IMPROVE sites, Figure 7) than 

summer months (less than 1 μg/m3335 ). Because NH4NO3 formation is generally limited by NH3 in 

336 the southeastern U.S., lower SO4 values during the winter months mean more NH3 is available to 

337 react with nitric acid gas, HNO3. Also NH4NO3 volatilizes at higher temperature so less is 

338 present in particulate phase during the warmer summer months. As a result, NH4NO3 has a 

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339 larger contribution to mass and light extinction on the 20% clearest days, which tend to occur 

340 during the winter months, than on the haziest days. 

341 

342 Ammonium. In Figures 5 through 8, NH4 is illustrated separately from SO4 and NO3, using 

343 inferred NH4 for IMPROVE and measured NH4 for STN and SEARCH. Inferred NH4 values at 

344 IMPROVE sites are similar to measured NH4 at nearby SEARCH sites. STN sites generally 

345 have lower measured NH4 values than IMPROVE and SEARCH. 

346 

347 NH4 measurements in all three networks are subject to positive and negative artifacts. The 

348 SEARCH NH4 measurements likely have greater accuracy and fewer artifacts than the 

349 IMPROVE and STN measurements due to the use of a citric acid coated backup filter behind the 

350 nylon filter, specifically designed to capture volatilized NH4. In special studies at Great Smoky 

351 Mountains National Park, the potential loss of NH4 off the nylon filter was evaluated using a 

352 denuder/filter pack system with a phosphorous acid-coated denuder after the nylon filter to 

capture NH3

22 353 . Results indicated that for summertime samples at Great Smoky Mountains, an 

354 average of 18% (with a range of 10-35%) of the NH4 volatilized off the nylon filter. Losses of 

355 NH4 off the routine IMPROVE nylon filter may be of similar magnitude. 

356 

357 The validity of the assumption used in the IMPROVE equation, Eq. 1, that SO4 is fully 

358 neutralized as (NH4)2SO4 was tested by measuring NH4 on the nylon filters for routine 

359 IMPROVE samples from 13 sites in the VISTAS region. Molar ratios of NH4 to SO4 were used 

360 to describe the degree of neutralization of SO4 by NH4. A molar ratio of 2.0 indicates fully 

361 neutralized (NH4)2SO4 , while a molar ratio of 1.0 implies NH4HSO4 (or mix of forms with 

362 average molar ratio of 1.0), and a molar ratio of 0.0 indicates H2SO4. Because the more acidic 

363 forms of SO4 aerosol absorb more water and scatter more light than (NH4)2SO4, three separate 

364 curves have been developed to describe the light extinction enhancement factor for water 

365 absorption, f(RH), for (NH4)2SO4, NH4HSO4, and H2SO4. The f(RH) curve for H2SO4 is much 

366 steeper than the f(RH) curve for (NH4)2SO4 and NH4SO4, so if the molar ratio of NH4 to SO4 is 

367 less than 1.0 (indicating a greater fraction of H2SO4), light extinction would be greater than that 

368 calculated by the IMPROVE equation, Eq. 1. Monthly average molar ratios for interior and 

369 coastal IMPROVE sites are always less than 2.0, frequently less than 1.5, and sometimes below 

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370 1.0. Some but not all sites show seasonal variation in molar ratios with the lowest ratios in the 

371 fall and summer and higher ratios in the spring. Molar ratios are generally lower at the coastal 

372 sites than at the interior sites. Given the likely underestimate in NH4 values reported for 

373 IMPROVE nylon filters, these monthly average molar ratios of NH4 to SO4 should be interpreted 

374 as lower limits. 

375 

376 For comparison, monthly average molar ratios for NH4 to SO4 were calculated for SEARCH 

377 sites using NH4 collected on both the nylon filter and the backup filter. For the SEARCH sites, 

378 the monthly average molar ratio is higher than at nearby IMPROVE sites and frequently close to 

379 2.0 (example IMPROVE and SEARCH sites are illustrated in Figure 9.) Values are lower at 

380 coastal SEARCH sites than at urban interior SEARCH sites but rarely fall below 1.4. There is 

381 much less seasonal variation in the SEARCH values than seen in the IMPROVE data. It is 

382 difficult to separate differences due to loss of NH4 from IMPROVE filters from those attributable 

383 to spatial differences in NH3 emissions. We can conclude, based on SEARCH NH4

384 measurements, that SO4 may not be fully neutralized in the coastal areas and possibly interior 

385 sites in the summer, and that light extinction by SO4 may be slightly underestimated using the 

386 IMPROVE equation, Eq. 1. Improved methods for measuring NH4 at the IMPROVE sites are 

387 required to verify this conclusion. 

388 

389 Organic Carbon mass. The greatest uncertainties and the largest differences in measured mass 

390 are related to organic carbon mass, OCM. STN reported values for OCM do not include a 

391 correction for background carbon on the quartz filter, however OC correction factors have been 

estimated for each of the STN monitors7392 . Quarterly average OCM values for STN sites 

393 illustrated in Figures 5-8 include the appropriate carbon correction factors. Corrected quarterly 

394 average OCM values are 20-45% lower than reported OCM values in quarters 1 and 3 of 2002. 

Quarterly average STN OCM values after correction are 1-5 μg/m3395 greater than OCM values at 

396 nearby IMPROVE sites. These differences are partially attributable to differences in TOR vs 

397 TOT analytical methods and partially attributable to differences in source strengths between 

398 urban and rural sites. STN OCM values are greater than SEARCH OCM values in Birmingham, 

399 AL for both quarters 1 and 3 and in Atlanta for quarter 3, while SEARCH OCM is higher than 

400 STN OCM in Atlanta, GA for quarter 1 (Figure 5). While local-scale variations in emissions 

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Appendix B.3 - 14

January 18, 2008
401 sources may contribute to differences in measured OCM in Birmingham and Atlanta (the 

402 SEARCH and STN monitors are not collocated), differences between analytical methods are 

403 likely the major contributors to OCM differences. 

404 

405 Measurement of total carbon on quartz filters is comparable across the three networks, but the 

406 TOT method used by STN applies a higher temperature of separation than the TOR method 

407 (used by IMPROVE and SEARCH). More of the total measured carbon is reported by STN as 

408 OC and less as EC than that reported by IMPROVE and SEARCH. Because analytical 

409 laboratories differ subtly in application of the TOR or TOT methods, there is not currently a 

410 single consistent correlation factor that can be used to compare OC reported by STN with that 

reported by IMPROVE and SEARCH23 411 . 

412 

413 Another source of uncertainty in the reported OCM is the accuracy of the assumption that a 

414 common OC multiplier of 1.4 can be used at all sites to account for the mass of other 

415 components of organic carbon compounds (e.g. hydrogen, oxygen, nitrogen, etc.). Currently 

416 IMPROVE, SEARCH, and STN consistently use an OC multiplier of 1.4. Several studies and 

417 reviews have recommended that a higher multiplier would be appropriate for organic carbon in 

urban areas influenced by fossil fuels (~1.6 +/- 0.2) 24 418 . Multipliers of 2.1 (+/- 0.2) and 2.1-2.4 

419 (+/- 0.2) are recommended for carbon from vegetative emissions and biomass burning, 

respectively24, 25 420 . If a carbon mass multiplier of 1.6 were applied to OC for measurements in 

421 urban areas and a multiplier of 1.8 were applied for rural sites, the differences in OCM between 

422 IMPROVE sites and urban STN and SEARCH sites would be less than illustrated in Figures 5-8. 

423 

424 Sources contributing to OCM vary spatially for both biogenic sources (e.g. vegetative emissions, 

425 wildfire) and anthropogenic sources (e.g. automotive, truck, or construction equipment, 

426 residential wood smoke, prescribed fire or land-clearing emissions). Chemical Mass Balance 

427 analyses use chemical profiles as indicators for gasoline, diesel, wood smoke, meat cooking, and 

vegetation to evaluate the relative contributions of different sources of primary organic carbon26 428 . 

Analysis of the 14 429 C isotope is used to identify the percentage of a carbon sample attributed to 

430 fossil fuel combustion compared to recent carbon sources (e.g. wood burning or vegetative 

emissions). Analyses of PM2.5 samples from SEARCH sites by Zheng, et al.26 431 and Edgerton, et 

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Appendix B.3 - 15

January 18, 2008
al.

27

432 indicate higher proportions of recent carbon in rural areas than in urban areas and higher 

433 contributions from fossil carbon in urban areas than in rural areas. At both urban and rural areas, 

434 primary carbon sources dominate in the winter, while secondary carbon sources are more 

435 important in the summer. Wood burning contributes to the majority of the recent carbon in the 

436 winter, but it is difficult to separate the contributions of wood smoke due to anthropogenic 

437 activities (land clearing, prescribed fire, and residential wood burning) from those due to 

438 wildfire. 

439 

At Great Smoky Mountains, analysis of 14 440 C isotope in PM10 samples indicates that 55-85% of 

441 the total organic carbon mass measured in spring, summer, and fall is modern carbon (from 

442 biomass burning or secondary conversion from biogenic emissions) and 15-40% is attributable to 

fossil carbon28 443 . Using PM2.5 samples, fossil carbon was found to have a larger contribution in a 

444 nearby urban area, Chattanooga, TN, than in the Great Smoky Mountains, but still less than 

modern carbon for most samples29 445 . To develop a better understanding of the sources of carbon, 

446 VISTAS supported high-volume PM2.5 filter samplers at Mammoth Cave, Great Smoky 

447 Mountains, and Shenandoah National Parks, Cape Romain Wilderness Area, and Millbrook, NC 

448 (suburban location outside Raleigh, NC) for the period April 2004-May 2005. Twenty-four 

449 hour samples were collected on quartz filters every third day. Chemical Mass Balance analyses 

and analyses of 14 450 C isotope are underway and will provide better characterization of fossil fuel 

451 versus biogenic influences at these sites. 

452 

453 Elemental Carbon. Elemental carbon values are higher at urban STN sites than at nearby 

454 IMPROVE sites, despite the fact that the TOT method yields lower EC than the TOR method. 

455 EC values are also higher at urban SEARCH sites than at rural SEARCH and IMPROVE sites. 

456 Emissions inventories indicate that industrial point sources and fires are generally localized 

457 sources of EC while vehicles and equipment engines are more regionally dispersed sources. 

458 

459 Total Carbon Mass. Total carbon mass, TCM, (calculated as 1.4 times OC, plus EC) can be 

460 compared between networks to eliminate the effect of difference between the TOR and TOT 

461 analytical methods. Because EC is such a small fraction of TCM, the range for TCM between 

462 urban STN sites and IMPROVE sites illustrated in Figures 5-8 is the same as the range for OCM, 

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Appendix B.3 - 16

January 18, 2008
1-5 μg/m

3

463 . These differences in quarterly average TCM between rural and urban sites are 

similar to those reported by Rao, et al.7 464 for annual average TCM for IMPROVE-STN pairs in the 

465 eastern U.S. 

466 

467 Fine Soil. Measurement methods for fine soils are comparable across the three networks, 

468 although SEARCH uses a slightly different calculation of component elements. Fine soil is 

469 higher at the southern and coastal sites than at the southern Appalachian sites, especially during 

470 the summer months. Construction, road dust, and agriculture are major anthropogenic sources 

471 of fine soil. Saharan dust is a major contributor to fine soil mass at the southern and coastal 

472 sites, especially Everglades, while Asian dust is seen in fine soil at northern tier sites such as 

Shenandoah in spring and early summer months20 473 . Because fine soil has low extinction 

474 efficiency, its average contribution to light extinction is generally low. 

475 

476 Coarse Mass. Coarse mass is higher at coastal IMPROVE sites than Southern Appalachian 

477 IMPROVE sites or SEARCH sites. Sea salt is an unspeciated component of coarse mass and 

478 likely contributes to higher values of coarse mass at coastal areas. 

479 

480 DISCUSSION 

481 

482 Implications for Future Monitoring 

483 The IMPROVE, STN, and SEARCH monitoring networks have similar, but differing objectives 

484 and differing analytical methods that complicate inter-comparison across networks. Additions of 

485 an acid denuder before the nylon filter to collect NH3, a backup nylon filter to collect volatilized 

486 NH4, and an acid denuder after the nylon filter to collect volatilized NH3 would improve NO3

487 and NH4 measurements at IMPROVE sites. Given that these methods are labor intensive and 

488 expensive to implement in the routine network, we recommend additional intensive studies in 

489 different seasons and IMPROVE locations to better understand NO3 and NH4 chemistry in the 

490 southeastern U.S. 

491 

492 Collated IMPROVE and STN monitors are providing information on comparability of the 

493 measurements in the two networks, and EPA is already evaluating changes to the STN protocol, 

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Appendix B.3 - 17

January 18, 2008
494 particularly for carbon, to be more similar to that used by IMPROVE. Studies currently 

495 underway in VISTAS will assist in definition of contributions of primary vs secondary 

496 carbonaceous species and fossil fuel vs recent carbon sources in the southeastern U.S. This 

497 information, combined with other studies, can be used to improve estimates of the OCM 

498 multiplier appropriate to the urban and rural areas in the southeastern U.S. 

499 

500 Implications for Atmospheric Modeling 

VISTAS is modeling air quality in 200221 501 as the base year for regional haze and PM2.5 State 

502 Implementation Plans. A critical component of this analysis is to demonstrate that the 

503 performance of the atmospheric model meets established performance goals. Model 

504 performance is constrained by measurement uncertainty as well as uncertainties in emissions 

505 inventories and representation of chemical and transport processes in the model. Differences in 

506 network measurement methods contribute to measurement uncertainty, especially for organic 

507 carbon mass, and these differences need to be considered when evaluating model performance 

508 across the networks. Sulfate measurements are comparable across the networks. SEARCH NO3 

509 measurements are likely more accurate than IMPROVE and STN measurements, but all three 

510 networks report fairly low NO3 concentrations. Because NO3 concentrations are low, model 

performance can tolerate larger bias and error than for SO4 and OCM components21 511 . Given the 

512 likely underestimate in NH4 from the IMPROVE nylon filters, we cannot recommend using the 

513 measured NH4 mass from IMPROVE nylon filters as a better estimate of NH4 for IMPROVE 

514 sites than inferred NH4 based on measured SO4 and NO3. For STN sites, OCM values should be 

515 corrected for background carbon before comparison to modeled OCM values. Model 

516 performance evaluation should also consider that OC reported by STN is defined by TOT 

517 analysis and is likely at least 20% higher than OCM reported by SEARCH and IMPROVE based 

518 on TOR analysis. Consideration should be given to using a higher carbon mass multiplier than 

519 1.4 for all three networks (in the range between 1.6-2.0, possibly selecting a lower multiplier for 

520 urban areas than rural areas) to account for chemical species associated with carbon. 

521 

522 CONCLUSIONS 

523 Fine particle mass and light extinction are dominated by ammonium sulfate in the southeastern 

524 U.S. Ammonium sulfate levels are generally higher in the northern tier of the VISTAS states 

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Appendix B.3 - 18

January 18, 2008
525 and lower at the coastal and southern sites. Regional SO2 controls should be effective in 

526 reducing fine particulate sulfate and its contribution to light extinction and PM2.5 mass in the 

527 VISTAS states. Levels of organic carbon, elemental carbon, and ammonium nitrate are 

528 generally higher in urban areas than rural and Class I areas. A combination of local and regional 

529 sources is likely contributing to these fine particle components. Improved understanding of the 

530 relative contributions of forest fire, land clearing, or residential wood burning will be necessary 

531 to determine what reductions in carbon from wood burning are feasible at urban and Class I 

532 areas. Fossil carbon sources are important contributors to OCM in urban areas, suggesting 

533 greater opportunity for reduction in OCM in response to anthropogenic emissions controls than 

534 at Class I areas. Because secondary carbonaceous species from biogenic emissions are major 

535 contributors to OCM in the southeastern U.S., particularly in the summer months, even after 

536 anthropogenic controls, OCM will likely remain a major component of PM2.5 and visibility in 

537 the VISTAS region. 

538 

539 ACKNOWLEDGEMENTS

540 

541 The work reported in this paper was supported by the VISTAS regional planning organization 

542 through its funding agency the Southeastern Air Resource Managers, Inc. and grants from the 

543 Environmental Protection Agency. The authors thank the VISTAS Data Workgroup for 

544 technical direction and are especially grateful to Dr. Ivar Tombach for technical review and 

545 editorial recommendations. 

546 

547 REFERENCES 

548 

549 1. Regional Haze Regulations; Final Rule. Federal Register, 1999, 64, 35713-35774. 

550 2. U.S. Environmental Protection Agency. PM2.5 Air Quality Trends Update 2002-2004.

551 www.epa.gov/airtrends/pdfs/pm25dv20050824.pdf. Data retrieved September 2005. 

552 3. Malm, W.C.; Pitchford, M.L; Scruggs, M.; Sisler, J.F.; Ames, R.; Copeland, S.; Gebhart, K.; 

553 Day, D.E. Spatial and Seasonal Patterns and Temporal Variability of Haze and Its 

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554 Constituents in the United States. Report III. Cooperative Institute for Research in the 

555 Atmosphere, May 2000. 

556 4. U.S. Environmental Protection Agency. Particulate Matter (PM2.5) Speciation Guidance, 

557 Final Draft. 1999. http://www.epa.gov/ttn/amtic/files/ambient/pm25/spec/specfinl.pdf 

558 5. Hansen, D.A.; Edgerton, E.S.; Hartsell, B. E.; Jansen, J.J.; Kandasamy, K.; Hidy, G. M.; 

559 Blanchard, C. L. The Southeastern Aerosol Research and Characterization Study: Part 1 - 

560 Overview; J. Air & Waste Manage. Assoc. 53, 1260-1471, 2003. 

561 6. Aerometric Information Retrieval System Database. U. S. Environmental Protection Agency 

562 http://www.epa.gov/ttn/airs/airsaqs/aqsweb/aqswebhome.htm. Data retrieved June 2005. 

563 7. Rao, V., Frank, N., Rush, A., Dimmick, F. Chemical Speciation of PM2.5 in Urban and 

564 Rural Areas in National Air Quality and Emissions Trends Report, 2003. 

565 http://www.epa.gov/air/airtrends/aqtrnd03 

566 8. IMPROVE website, http://vistas.cira.colostate.edu/improve/ Data retrieved June 2005. 

567 9. VIEWS website, http://vista.cira.colostate.edu/views/ Data retrieved June 2005. 

568 10. SEARCH website, http://www.atmospheric-research.com/studies/SEARCH/ Data retrieved 

569 June 2005. 

570 11. U.S. Environmental Protection Agency. Guidance for Tracking Progress under the Regional 

571 Haze Program; EPA-54/B-03-004, 2003. 

572 12. Malm, W.C.; Sisler, J.F.; Huffman, D.; Eldred, R.A.; Cahill, T.A. Spatial and seasonal trends 

573 is particle concentration and optical extinction in the United States. J. Geophys. Res. 99, 

574 1347-1370, 1994. 

575 13. Malm, W.C.; Molenar, J.V.; Eldred, R.A.; Sisler, J.F. Examining the relationship among 

576 atmospheric aerosols and light scattering and extinction in the Grand Canyon area, J. 

577 Geophys. Res. 101, 19,251-19,265, 1996. 

578 14. Malm, W.C.; Day, D.E. Optical properties of aerosols at Grand Canyon National Park. 

579 Atmos. Environ. 34, 3373-3391, 2000. 

580 15. Malm, W.C.; Day, D.E.; Kreidenweis, S.M. Light Scattering Characteristics of Aerosols as a 

581 Function of Relative Humidity: Part I -- A Comparison of Measured Scattering and Aerosol 

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582 Concentrations Using the Theroretical Models. J. Air & Waste Manage. Assoc 50, 686-700, 

583 2000. 

584 16. Hand, J. L., and Malm, W. C. Review of the IMPROVE Equation for Estimating Ambient 

585 Light Extinction Coefficients. 

586 http://www.vista.cira.colostate.edu/improve/Publications/Graylit/016_IMPROVEeqReview/I

587 MPROVEeqReview.htm. 

588 17. Ryan, P. A., Lowenthal, D., Kumar, N. Light Scattering in Light Extinction Reconstruction. 

589 J. Air & Waste Manage. Assoc., this issue, 2005. 

590 18. Blanchard, C.L. and Hidy, G.M. Effects of Changes in Sulfate, Ammonia, and Nitric Acid 

591 on Particulate Nitrate Concentrations in the Southeastern United States. J. Air & Waste 

592 Manage. Assoc. 53,283-290, 2003. 

593 19. Air Resource Specialists, Inc. Analysis of Visibility and Particulate Data Within the 

594 VISTAS Region. May 2003. ftp://ftp.air-resource.com/VISTAS. 

595 20. Tombach, I. and Brewer, P. Natural Background Visibility and Regional Haze Goals in the 

596 Southeastern United States. J. Air & Waste Manag. Assoc., this issue, 2005. 

597 21. Morris, R. E., Kou, B. Guenther, A., McNally, D. E., Tesche, T.W., Tonnessen, G., Boylan, 

598 J. W., and Brewer, P. Model Sensitivity Evaluation for Organic Carbon Using Two Multi599 pollutant Air Quality Models that Simulate Regional Haze in the Southeastern United States 

600 Atmos. Environ., In press, 2005. 

601 22. Yu, X.-Y., Lee, T., Ayres, B., Kreidenweis, S. M., Malm, W., and Collett, J.L. Loss of fine 

602 particle ammonium from denuded nylon filters. Submitted to Atmos. Environ., 2005. 

603 23. Watson, J. Visibility: Science and Regulation. J. Air & Waste Manage. Assoc. 52, 626-713. 

604 2002. 

605 24. Turpin, B. J.; Lim, H-J. Species Contributions to PM2.5 Mass Concentrations: Revisiting 

606 Common Assumptions for Estimating Organic Mass. Aerosol Sci. Tech., 35, 602-610, 2001. 

607 25. McMeeking G. R.; Kreidenweis, S. M.; Carrico, C. M.; Lee, T.; Collett, J. L., Jr.; Malm, W. 

608 C. Observations of smoke-influenced aerosol during the Yosemite Aerosol Characterization 

609 Study: Size distributions and chemical composition, J. Geophys. Res., 110, D09206, 

610 doi:10.1029/2004JD005389, 2005. 

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611 26. Zheng,, M.; Cass, G.R.; Schauer, J.J.; Edgerton, E.S. Environ. Sci. Tech. 36, 2361-2371, 

612 2002. 

613 27. Edgerton, E. S., Hartsell, B. E., and Jansen, J. J. Natural Sources of PM2.5 and PMcoarse

614 Observed in the SEARCH network. Regional and Global Perspectives on Haze: Causes, 

615 Consequences and Controversies - Visibility Specialty Conference, Air and Waste 

616 Management Association, Asheville, NC, October 25-29, 2004. 

617 28. Tanner, R.L., Parkhurst, W. J., and McNichol, A.P. Fossil Sources of Ambient Aerosol 

Carbon based on 14 618 C measurements. Aerosol Sci. Tech., 38(S1), 133-139, 2004. 

619 29. Tanner, R. L., Zheng, M., Lin, K., Schauer, J. J., and McNichol, A.P. Source Contributions 

620 to the Organic Aerosol Fraction in the Tennessee Valley: Seasonal and Urban-Rural 

621 Differences. Presentation to AAAR International Specialty conference, Particulate Matter: 

622 Supersites Program and Related Studies”, Atlanta, GA, Feb 7-11, 2005. 

 623 

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Appendix B.3 - 22

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Brewer, P. F. and Adlhoch, J. P. 

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

Southeastern U.S. 

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 

Shenandoah, VA X X X X 

James River Face, VA X X X 

Mammoth Cave, KY X X X X 

Sipsey, AL X X X X 

Great Smoky Mtns, TN X X X X 

Cohutta, GA X 

Shining Rock, NC X 

Linville Gorge, NC X X X 

Swanquarter, NC X X 

Cape Romain, SC X X X X 

Okefenokee, GA X X X X 

Saint Marks, FL X X 

Chassahowitzka, FL X X X X 

Everglades, FL X X X 

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Appendix B.3 - 23

January 18, 2008
Brewer, P. F. and Adlhoch, J. P. 

Trends 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. 

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Appendix B.3 - 24

January 18, 2008
ABOUT THE AUTHORS 

Patricia 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. 

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January 18, 2008
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Appendix B.3 - 26

January 18, 2008
0

50

250

200

150

100

Extinction (Mm-1)

Dolly Sods, WV

Shenandoah, VA

James Rvier Face, VA

Mammoth Cave, KY

Sipsey, AL

Great Smoky Mtns, TN

Linville Gorge, NC

Shining Rock, NC

Cohutta, GA

Saint Marks, FL 

Swan Quarter, NC

Cape Romain, SC

Okefenokee, GA

Chassahowitzka, FL

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Appendix B.3 - 27

January 18, 2008
Extinction (Mm-1)

0

60

50

40

30

20

10

Dolly Sods, WV

Shenandoah, VA

James Rvier Face, VA

Mammoth Cave, KY

Sipsey, AL

Great Smoky Mtns, TN

Linville Gorge, NC

Shining Rock, NC

Cohutta, GA

Saint Marks, FL 

Swan Quarter, NC

Cape Romain, SC

Okefenokee, GA

Chassahowitzka, FL

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Appendix B.3 - 28

January 18, 2008
5.0

0.0

20.0

15.0

10.0

Q1

Q2

Q3Q4

Q1Q2Q3Q4

Q1

Q2

Q3

Q4

Q1Q2

Q3

Q4

Q1Q2

Q3

g/m3

μ

Mammoth

Cave, KY

Okefenokee,

GA

Evergla

FL

Cape 

Romain, SC

Great Smoky 

Mtn., TN

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Appendix B.3 - 29

January 18, 2008
5.0

0.0

25.0

20.0

15.0

10.0

g/m3 μ Fine Particle Mass -

Shenandoah, VA

Mammoth Cave, KY

Sipsey, AL

Great Smoky Mtns, TN

Shining Rock, NC

Atlanta, GA

Birmingham, AL

Louisville, KY

Knoxville, TN

Atlanta, GA

Charlotte, NC

Roanoke, VA

Cohutta, GA

Birmingham, AL

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Appendix B.3 - 30

January 18, 2008
Cape Romain, SC

Tampa, FL

St. Marks, FL

Charleston, SC

Okefenokee, GA

Savannah, GA

Chassahowitzka, FL

Everglades, FL

Pensacola, FL

Breton Island, LA

Gulfport, MS

5.0

0.0

25.0

20.0

15.0

10.0

g/m3 μ Fine Particle Mass -

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Appendix B.3 - 31

January 18, 2008
8.0

4.0

0.0

16.0

12.0

g/m3 μ Fine Particle Mass -

Shenandoah, VA

Mammoth Cave, KY

Sipsey, AL

Great Smoky Mtns, TN

Shining Rock, NC

Atlanta, GA

Birmingham, AL

Louisville, KY

Chattanooga, TN

Atlanta, GA

Charlotte, NC

Roanoke, VA

Cohutta, GA

Birmingham, AL

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Appendix B.3 - 32

January 18, 2008
8.0

4.0

0.0

16.0

12.0

Cape Romain, SC

Tampa, FL

St. Marks, FL

Charleston, SC

Okefenokee, GA

Chassahowitzka, FL

Everglades, FL

Pensacola, FL

Breton Island, LA

Gulfport, MS

g/m3 μ Fine Particle Mass -

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Appendix B.3 - 33

January 18, 2008
2.5

2.0

1.5

1.0

0.5

0.0

Jan-02

Mar-02

May-02

Jul-02

Sep-02

Nov-02

Jan-03

Mar-03

May-03

Ju

Molar Ratio

Great Smoky Mtn, TN

Birmingham, AL Gulfport, MS

Mammoth Cave, KY

SEARCH

IMPROVE 

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