Methods to Assess Carbonaceous Aerosol Sampling Artifacts for ...

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ISSN:1047-3289 J. Air & Waste Manage. Assoc. 59:898 –911 DOI:10.3155/1047-3289.59.8.898 Copyright 2009 Air & Waste Management Association

Methods to Assess Carbonaceous Aerosol Sampling Artifacts for IMPROVE and Other Long-Term Networks John G. Watson and Judith C. Chow Division of Atmospheric Sciences, Desert Research Institute, Reno, NV; and Aerosol and Environmental Division, Institute of Earth Environment, Chinese Academy of Science, Xi’an, People’s Republic of China L.-W. Antony Chen Division of Atmospheric Sciences, Desert Research Institute, Reno, NV Neil H. Frank Air Quality Assessment Division, U.S. Environmental Protection Agency, Research Triangle Park, NC

ABSTRACT Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) adsorb to quartz fiber filters during fine and coarse particulate matter (PM2.5 and PM10, respectively) sampling for thermal/optical carbon analysis that measures organic carbon (OC) and elemental carbon (EC). Particulate SVOCs can evaporate after collection, with a small portion adsorbed within the filter. Adsorbed organic gases are measured as particulate OC, so passive field blanks, backup filters, prefilter organic denuders, and regression methods have been applied to compensate for positive OC artifacts in several long-term chemical speciation networks. Average backup filter OC levels from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network were approximately 19% higher than field blank values. This difference is within the standard deviation of the average and likely results from low SVOC concentrations in the rural to remote environments of most IMPROVE sites. Backup filters from an urban (Fort Meade, MD) site showed twice the OC levels of field blanks. Sectioning backup filters from top to bottom showed nonuniform OC densities within the filter, contrary to the assumption that VOCs and SVOCs on a backup filter equal those on the front filter. This nonuniformity may be partially explained by evaporation and readsorption of vapors in different parts of the front and backup quartz fiber filter owing to temperature, relative humidity, and ambient concentration changes throughout a 24-hr sample duration. OC-PM2.5 regression analysis and organic denuder approaches demonstrate negative sampling artifact from both Teflon membrane and quartz fiber filters.

IMPLICATIONS Particulate OC measured on quartz fiber filters is often overestimated because organic vapors adsorb within the filter media. Field blanks and backup filters do not fully represent the degree of this adsorption and are a major cause of uncertainties in OC and EC measurements.

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INTRODUCTION “Organic sampling artifact” refers to interference in the collection and quantification of carbonaceous aerosol because of adsorption and desorption of organic components on the filter substrate. Organic vapor adsorption can occur during active sampling and passive exposure (zero face velocity). These vapors leave the sample during thermal analyses1 and are interpreted as part of the measured organic carbon (OC). This positive OC artifact yields higher values for OC in particulate samples than exist in ambient air.2 Adsorbed organic vapors also cause differences in elemental carbon (EC) levels determined by reflectance and transmittance corrections during thermal/ optical analysis as they char within the filter.3,4 Semivolatile organic compounds (SVOCs) can be collected as particles, but portions can evaporate because of increases in temperature or decreases of their gas-phase concentrations in the sampled air, leaving the particle in the gas stream.5 Evaporated SVOCs yield negative OC artifacts that should be reported as part of the particulate mass to represent ambient concentrations.6 Organic sampling artifacts should be quantified to understand noncompliance with fine and coarse particulate matter (PM2.5 and PM10, respectively) air quality standards, which are based on aerosol mass, and to determine long-term trends and chemical mass closure. Several U.S. networks, including the Interagency Monitoring of Protected Visual Environments (IMPROVE) network,7 the urban Chemical Speciation Network (CSN, including the Speciation Trends Network [STN]),8 the Southeastern Aerosol Research and Characterization (SEARCH) network,9,10 and the Maryland Aerosol Research and Characterization (MARCH-Atlantic) study,11–13 have been collecting field blanks and/or backup filters to correct the OC artifact. How field blanks and backup filters represent the positive and negative artifacts is still under debate.14,15 Because of limited resources, field blanks and backup filters are usually acquired at a lower frequency and spatial coverage than sample filters. Volume 59 August 2009

Watson, Chow, Chen, and Frank Table 1. Sampling protocols for the IMPROVE, SEARCH, and MARCH-Atlantic networks. Network Variable Carbon sampler type Total number of sites Number of channels Flow rate Face velocity Sample volume Sampling frequency Passive deposition time (time field blank is in sampler) Filter pack configuration Sites with backup filters (QBQ) Quartz filter deposit area Backup filter analysis frequency Quartz filter type (QF and QBQ) Laboratory blank frequency Field blank frequency Field blank analysis frequency Total number of field blanks

IMPROVEa

SEARCHb

MARCH-Atlanticc

IMPROVE Module C 181 3 22.7 L/min 107.2 cm/sec 32.7 m3 Third day ⬃7 days

PCM3 8 3 16.7 L/min 39.1 cm/sec 24 m3 Third dayd 1–15 min

DRI SFS 1 2 20.0 L/min 24.2 cm/sec 28.8 m3 Every day, 1 month/season 3 days

QF or QF and QBQ 6 3.53 cm2 100% 25 mm Palle 2% 2% 100% 959f

Carbon denuder followed by QF and QBQ 8 7.12 cm2 10% 37 mm Palle 2% 10% 10% on QF 144f

QF and QBQ/Teflon membrane and QBT 1 13.8 cm2 100% 47 mm Palle 2% 33% 100% 112f

Notes: aIMPROVE uses monthly median QBQ concentrations from six sites for network-wide blank subtraction. bSEARCH calculates the site-specific quarterly mean QBQ and field blank concentrations and corrects the sampling artifact by adding the QBQ and subtracting twice the front filter field blank carbon concentrations. c MARCH-Atlantic corrects the sampling artifact by subtracting monthly mean field blank carbon concentrations. dEvery third day sampling at all sites except for daily sampling at the urban BHM and JST sites. ePall Tissuquartz 2500 QAT-UP, Pall Scientific Corporation. fJanuary 1, 2005 to December 31, 2006 for IMPROVE and SEARCH networks, and July 1, 1999 to July 31, 2002 for the MARCH-Atlantic study.

This work16,17 uses field blank and backup filter data from the IMPROVE, SEARCH, and MARCH-Atlantic networks (see Table 1) to evaluate the magnitude and variability of adsorbed organic gases and to determine variation by location, season, and aerosol concentration. Laboratory analyses were conducted on archived samples to determine the homogeneity of adsorbed organic gases within a filter and relationships between artifacts on front and backup filters. Near-, middle-, and long-term strategies for artifact correction in long-term networks are recommended. Table 2 shows a list of acronyms applied for the observables, filter pack configuration, as well as sampling networks and sites. METHODS TO CORRECT ORGANIC SAMPLING ARTIFACT Methods used to compensate for organic sampling artifacts include (1) blank subtraction, (2) backup filter adjustment, (3) the “slicing method” (top and bottom filter half comparison), (4) prefilter organic vapor denuders, and (5) regression intercept. Different combinations of these methods are applied to long-term networks as detailed in Table 1. Field Blank Subtraction Field blank filters accompany the sampled filters through all processes except having ambient air drawn through them. They are subject to passive deposition and adsorption of materials that differ from those in the sampled air.18 –22 Average field blank levels can be subtracted from levels measured on the sampled filters. The uncertainty of this average is represented by its standard deviation, which should be incorporated into the reported measurement precision and Volume 59 August 2009

lower quantifiable limit (LQL).23 Properly handled field blanks usually show low particle deposition (as indicated by low EC and trace elements) and high OC adsorption.24 –27 Field blanks are easy to deploy but do not account for sampling artifacts due to active sampling. They must remain exposed under conditions and durations similar to the exposure of the active samples. Backup Filter Adjustment A quartz fiber filter is placed behind the front sample filter, which may be either a Teflon membrane (QBT) or quartz fiber (QBQ) filter. If OC measured on the backup filter is uniformly adsorbed within the front and backup filters, the backup filter amount should be subtracted from the front filter OC to represent ambient concentrations. Turpin et al.28 suggested that QBT provides a more accurate estimate of the positive OC artifact; however, QBT often yields higher OC than QBQ.14,28,29 This might reflect a larger quantity of particulate SVOC that evaporates from particles on the front Teflon membrane filter. Being inert, the Teflon membrane adsorbs less of these vaporized gases than the quartz fiber filter. Slicing Method An alternative to deploying QBT or QBQ is slicing the sampled quartz fiber filter horizontally and quantifying carbon on the bottom half of the filter. Fung et al.30 developed a jig and sharp blade to slice the filter through its cross section into nearly equal top and bottom halves. Both halves can be weighed to scale OC on the bottom half to the whole filter. Assuming that particulate OC is collected only on the top half and that the adsorbed vapor is distributed uniformly throughout the filter depth, OC on the bottom half should Journal of the Air & Waste Management Association 899

Watson, Chow, Chen, and Frank Table 2. Summary of acronyms used in this study. Acronym Observables EC LQL OC OCM OP PM2.5 PM10 SVOC(s) TC TOR VOC(s) Filter pack configurations bQBQ bQF dQBQ dQF QBQ QBQbottom QBQtop QBT

to avoid contamination during slicing, but no more than that required for normal laboratory analyses.

Meaning

Elemental carbon Lower quantifiable limit Organic carbon Organic carbon mass Pyrolyzed or charred carbon Particles with aerodynamic diameters ⬍2.5 ␮m Particles with aerodynamic diameters ⬍10 ␮m Semi-volatile organic compound(s) Total carbon Thermal/optical reflectance Volatile organic compound(s) Field blank of quartz fiber backup filter behind quartz fiber front filter Field blank of quartz fiber front filter Denuded quartz fiber backup filter (QBQ downstream of organic denuder) Denuded quartz fiber front filter (QF downstream of organic denuder) Quartz fiber backup filter behind quartz fiber front filter Bottom half of quartz fiber backup filter behind quartz fiber front filter Top half of quartz fiber backup filter behind quartz fiber front filter Quartz fiber backup filter behind Teflon membrane front filter Quartz fiber front filter Bottom half of quartz fiber front filter Top half of quartz fiber front filter

QF QFbottom QFtop Sampling networks and sites CSN/STN Chemical Speciation Network, including the Speciation Trends Network IMPROVE Interagency Monitoring of Protected Visual Environments MORA Mount Rainier National Park, WA YOSE Yosemite National Park, CA HANC Hance Camp at Grand Canyon National Park, AZ CHIR Chiricahua National Monument, AZ SHEN Shenandoah National Park, VA OKEF Okefenokee National Wildlife Refuge, FL HAVO1 Hawaii Volcanoes National Park, HI SEARCH Southeastern Aerosol Research and Characterization GLF Gulfport, MI OAK Oak Grove, MI BHM Birmingham, AL CTR Centreville, AL JST Jefferson Street, Atlanta, GA YRK Yorkville, GA PNS Pensacola, FL OLF Outlying Field outside Pensacola, FL MARCH-Atlantic Maryland Aerosol Research and Characterization FME Fort Meade, MD

provide an estimate of the adsorbed organic vapor throughout the filter (i.e., positive artifact). Microscopic examination of filter cross sections shows that few particles penetrate into the bottom half of a filter.4 This method avoids two quartz fiber filters in series and allows the QBQ backup filter approach to be applied to archived samples. Care is needed 900 Journal of the Air & Waste Management Association

Denuder Approach OC denuders31– 42 allow organic vapors to diffuse to an absorbing surface while permitting small particles to pass through the filter. Baked quartz fiber filter strips,33 XAD resin,35 and activated carbon impregnated filter strips14,43 have been used as absorbents. By removing organic gases, these denuders reduce the equilibrium vapor pressure over the SVOC and enhance its volatilization within the denuder and on the filter. Assuming a 100% efficiency of a denuder, OC on backup filters downstream of the denuder would quantify the negative artifact. Regularly deploying and replacing denuders at every sampling site substantially increases operational costs. Regression Intercept Approach If positive OC artifact at a monitoring site is relatively constant for all seasons and concentration levels, it should provide a constant increment over the mass measured on a Teflon membrane filter. Calculating a linear regression line of OC versus PM2.5 or PM10 mass results in an intercept at zero mass that might indicate the magnitude of the artifact OC.44,45 This method assumes (1) the sum of positive and negative artifacts is constant for all samples (within measurement uncertainties), (2) the OC artifact is the dominant reason for lack of mass closure, and (3) OC and PM2.5 concentrations are highly correlated (i.e., OC constitutes a reasonably consistent fraction of PM2.5). The regression intercept approach requires no additional material and laboratory analysis, but in many cases the assumptions above are not met. Frank46 further assumes that all of the unaccounted PM2.5 mass measured on a Teflon membrane filter when elements, ions, and water are summed can be associated with the carbonaceous component; that is, OC ⫹ EC. The OC or OC mass (OCM) estimated from the material balance can be compared with those measured from quartz fiber filters using different multipliers to evaluate other artifact correction methods. This assumes that other semi-volatile species (e.g., ammonium nitrate47–50) are accounted for in the material balance. This approach provides a basis to evaluate artifact correction methods and to estimate the OC artifact in PM2.5 mass. IMPROVE BLANK AND BACKUP FILTER ANALYSIS Between January 1, 2005 and December 31, 2006, 44,016 samples from the IMPROVE network were analyzed for OC and EC following the IMPROVE_A thermal/optical reflectance (TOR) protocol51 with 959 (2.2% of the total) field blanks (bQFs) collected at 181 sites. Between 1 and 17 bQFs were taken at individual sites with the number varying by location and season. During the same period, 1406 backup filters (i.e., QBQ) were acquired at 6 anchor sites (i.e., Mount Rainier National Park [MORA], Yosemite National Park [YOSE], Hance Camp at Grand Canyon National Park [HANC], Chiricahua National Monument [CHIR], Shenandoah National Park [SHEN], and Okefenokee National Wildlife Refuge [OKEF]; see Figure 1). Volume 59 August 2009

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Figure 1. Sampling sites in the IMPROVE network.16 The circled sites are locations where QBQ are acquired: 78 ⫽ MORA, 96 ⫽ YOSE, 48 ⫽ HANC, 39 ⫽ CHIR, 6 ⫽ SHEN, and 16 ⫽ OKEF. See Table 2 for definitions of acronyms in figure legends.

For most sites, average bQF total carbon (TC) levels ranged from 7 to 11 ␮g per 25-mm filter, which translates to 2– 4.3 ␮g/cm2. In terms of thermal carbon fractions, each of the OC1 (140 °C in 100% helium [He]), OC2 (280 °C in 100% He), and OC3 (480 °C in 100% He) fractions contributed 2–3 ␮g/filter of TC with very low concentrations found in other carbon fractions.16 Most of the OC4 (580 °C in 100% He) was less than 0.5 ␮g/filter, compared with less than 0.1 ␮g/filter for EC1 (580 °C in 98% He/2% oxygen [O2]), EC2 (740 °C in 98% He/2% O2), and charring/pyrolysis (OP). EC3 (840 °C in 98% He/2% O2) concentrations were not detected. As expected for filters without a particle deposit, EC levels (EC1 ⫹ EC2 ⫹ EC3 ⫺ OP) were negligible. Among 181 IMPROVE sites, bQF TC and OC can be considered equivalent within analytical uncertainties. Figure 2 shows that the average bQF TC concentration was higher during summer than during the other seasons, ranging from 7 ⫾ 2.5 ␮g/filter in winter to 12.3 ⫾ 14.6 ␮g/filter in summer. For OC2 and OC3, the winter/summer ratios were 0.71 and 0.73, respectively. Turpin et al.28 and Subramanian et al.52 suggest that quartz fiber (front and backup) filters might reach equilibrium/saturation within 24 hr of sampling. They did not examine the extent to which this conjecture might apply to field blanks that experience no active sample flow. The winter-summer contrast suggests that equilibrium/saturation depends on ambient conditions. Higher temperatures in summer would be expected to shift SVOC equilibrium toward the vapor phase, leading to higher TC levels on field Volume 59 August 2009

blanks. However, summertime photochemical activity might also create less volatile SVOCs.53 Wildfires54 –58 may contain substantial SVOCs and are more prevalent during dry summer and early fall periods near IMPROVE sites. Figure 3 shows that average bQF TC levels were more uniform across the network than front quartz fiber filter (QF) TC and carbon fractions. The ratio of the 90th-percentile to the 10th-percentile TC was only approximately 1.5 for bQF, compared with 3.5 on QF. This is a small variability considering the variety of environments in which these sites are located. At clean, remote sites, such as Hawaii Volcanoes National Park (HAVO1, no. 107 in Figure 1), bQF TC (⬃10 ␮g/filter) accounted for most of the QF TC. In the mediumloading range (20 – 40 ␮g/filter), bQF TC was comparable to the sum of the two lowest-temperature carbon fractions, OC1 and OC2, on QF. However, for higher loadings (⬎40 ␮g/filter), bQF TC was much less than OC1 ⫹ OC2 on QF (Figure 3). Not all of the OC1 and OC2 on a sample filter is positive artifact. At the six anchor sites, site-averaged QBQ TC does not show a clear dependence on QF TC, and QBQ TC is distributed among the carbon fractions,16 confirming OC equivalence to TC after TOR charring corrections. The most visible differences between QBQ and bQF are the higher OC4 abundances in QBQ. Site-averaged OC measured on QF, QBQ, and bQF are compared in Table 3. For 1406 QBQ at 6 nonurban locations, the average positive OC artifact was 10 ⫾ 5 ␮g/filter. QBQ OC ranged from 8.1 ⫾ 2.8 ␮g/filter at the CHIR site to 13.1 ⫾ 4.7 ␮g/filter at the OKEF site. Journal of the Air & Waste Management Association 901

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Figure 2. Seasonal averages of bQF carbon fractions for 77 IMPROVE network sites with more than five field blanks for the period from January 1, 2005 to December 31, 2006 (spring ⫽ March, April, May; summer ⫽ June, July, August; fall ⫽ September, October, November; winter ⫽ December, January, February). Carbon fractions are determined by the IMPROVE_A51 TOR protocol (OC1, OC2, OC3, and OC4 at 140, 280, 480, and 580 °C, respectively, in a 100% He atmosphere; EC1, EC2, and EC3 at 580, 740, and 840 °C, respectively in a 98% He/2% O2 atmosphere; OP ⫽ pyrolyzed carbon measured by reflectance; OC ⫽ OC1 ⫹ OC2 ⫹ OC3 ⫹ OC4 ⫹ OP; EC ⫽ EC1 ⫹ EC2 ⫹ EC3 ⫺ OP; TC ⫽ OC ⫹ EC).

Between January 1, 2005 and December 31, 2006, only 22 samples from 6 sites acquired concurrent field blanks and backup filters. Figure 4 shows that OC on blank filters agrees within ⫾15% with OC on backup filters at all but the YOSE site. QBQ are expected to show higher carbon loadings than bQF because of air being drawn through the backups. However, in rural and remote atmospheres, such as the environment of most IMPROVE sites, aerosols are relatively aged and their SVOC content might be minor. With sufficient exposure time, field blanks (bQF and bQBQ) would adsorb volatile organic compounds (VOCs) in quantities similar to that of the QBQ filters. Average OC levels at YOSE bQF were

approximately 35% (⬃3.4 ␮g/filter) lower than OC on QBQ. Average OC concentrations on QF were also highest (59.3 ⫾ 14.5 ␮g/filter) at the YOSE site because of the wildfires throughout the 2005- to 2006-measurement period. This is consistent with a higher SVOC level due to fresh emissions at this site. CARBON DISTRIBUTION WITHIN FRONT BACKUP FILTER STACKS When using QBQ, it is assumed that the filter is saturated and that organic vapors are uniformly adsorbed throughout the filter. Thus, the top half (QBQtop) of a backup filter

Figure 3. Average bQF TC concentration compared with average QF carbon loading at 77 IMPROVE network sites with more than five field blanks for the period between January 1, 2005 and December 31, 2006, sorted by average QF TC concentration. 902 Journal of the Air & Waste Management Association

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Watson, Chow, Chen, and Frank Table 3. OC comparison between the QF (no blank subtraction), bQF, and QBQ filter concentrations collected at the six anchor sites (all available data) in the IMPROVE network for the period from January 1, 2005, to December 31, 2006. OC Concentration (␮g/filter, average ⴞ standard deviation) Site MORA YOSE HANC CHIR SHEN OKEF All sites

QF

QBQ

Number of QBQ

bQF

Number of bQF

41.89 ⫾ 32.76 45.04 ⫾ 33.54 29.02 ⫾ 35.25 24.15 ⫾ 11.85 45.07 ⫾ 27.1 76.28 ⫾ 43.54 42.69 ⫾ 35.39

8.22 ⫾ 3.48 10.34 ⫾ 4.26 8.74 ⫾ 4 8.06 ⫾ 2.8 11.74 ⫾ 6.01 13.07 ⫾ 4.71 10.03 ⫾ 5.04

237 228 243 228 230 240 1406

6.26 ⫾ 2.18 6.37 ⫾ 2.39 7.51 ⫾ 2.35 7.87 ⫾ 3.33 8.21 ⫾ 2.94 10.57 7.52 ⫾ 2.69

5 4 3 5 9 1 27

should yield the same OC as the bottom half (QBQbottom), and analysis of a punch from the left side should yield the same results as a punch from the right side. If the filter adsorption capacity is not reached, adsorbed organic vapors can be described by a gradient (i.e., decreasing with increasing penetration depth). OC artifact from high to low would follow QFbottom ⬎ QBQtop ⬎ QBQbottom ⬎ bQF. Twelve IMPROVE samples from five anchor sites with front and backup quartz fiber filters were examined for these gradients. Circular 0.5-cm2 portions of the QF or QBQ filters were weighed and analyzed for OC and EC. Another circular section was removed from each filter and sliced into front and back sections. Each section was weighed and analyzed for OC and EC. Chow et al.16 showed that the slicing experiment conserved filter mass (with average percent difference of ⫺3.3 to ⫹5.3%). Figure 5 shows examples of carbon densities across the filter stack. On average, QFbottom contained higher OC and TC densities than the top and bottom halves of the QBQ filters in terms of micrograms of carbon (␮g C) per milligrams filter. The difference was more pronounced for higher-temperature OC fractions

(e.g., OC3, OC4), especially when QF OC loadings were high (e.g., the YOSE and SHEN sites). The number of cases studied in this experiment is too small to generalize, but the results in Table 4 indicate that the assumptions that backup filter adsorption equals that of the front filter, and that adsorption is uniform throughout the filter, are not universally valid.16 URBAN-RURAL CONTRAST MARCH-Atlantic samples from Fort Meade (FME), MD, used QBT and QBQ configurations12 (see Table 1) from July 1999 to July 2002, including 10 sampling months during 4 seasons. The FME site was located on a military base approximately halfway between Baltimore, MD, and Washington, DC, representing an urban-scale mixture of PM2.5 carbon contributions from vehicle exhaust, residential wood combustion, and secondary organic aerosol. This site provides a good contrast to the rural IMPROVE environment. Three filter sets were obtained for three days of consecutive 24-hr sampling. The first two sample sets (i.e., Day 1, Day 2) remained at the site for 72 hr (irrespective of sampling period),

Figure 4. Comparisons of average OC concentrations on QF, QBQ, bQF, and bQBQ for 22 collocated sample sets from January 1, 2005 to December 31, 2006 for 6 IMPROVE anchor sites. See Figure 1 for site locations. Error bars represent the standard deviation of the average for all sites except OKEF. Only one sample set was available for the OKEF site, so the analytical uncertainty is used. Volume 59 August 2009

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Figure 5. Comparison of original and sliced filter mass (mg) with carbon loading (␮g). Diamonds and circles indicate QF and QBQ filters, respectively. Upward- and downward-pointing triangles indicate top (QFtop or QBQtop) and bottom (QFbottom or QBQbottom) halves of slices, respectively, whereas rectangles represent the original filter punch (0.5 cm2). (a) and (b) The bottom halves of QF contain similar carbon concentrations as those on backup filters. (c) and (d) The bottom half of QF contains higher carbon concentrations than QBQ slices.

which is consistent with the passive period of the field blanks. Seasonal average OC levels from QF, QBT, QBQ, and bQF are compared in Figure 6. OC concentrations at the FME site were much higher in summer than during other seasons. The volatility of organic aerosol is also expected to be higher in summer, resulting in higher positive and negative artifacts. The bQF shows seasonal differences, ranging from 10.5 ␮g/47-mm filter in fall to 15.7 ␮g/ 47-mm filter in summer, equivalent to 2.7– 4 ␮g/25-mm IMPROVE filter. This seasonal variation is consistent with that found in the IMPROVE network (Figure 2) although the magnitude appears to be lower. QBT and QBQ show 2– 4 times the OC of bQF and bQBQ, in contrast to the case for IMPROVE, where the differences were within the standard deviation of the average. This may be caused by the urban-rural difference, because SVOCs are probably more abundant in urban atmospheres. It may also be due to the shorter exposure time for the field blanks, which are typically in the field for 7 days at IMPROVE sites. In Figure 6, there is no difference between Day 1 (24-hr sampling 904 Journal of the Air & Waste Management Association

on the first day, followed by 48-hr passive adsorption) and Day 2 (the filter remained in the sampler for 24 hr before the 24-hr sampling on the second day, followed by a 24-hr passive period). In summer and fall, average QBT OC was more than 60% of QF OC. This difference was less than 50% in winter and spring. QBQ OC was between QBT and bQF OC. Turpin et al.28 attributed this to a slow saturation of the tandem quartz fiber/ quartz fiber filter configuration. On the other hand, Chow et al.29 conjectured that this is mostly due to the volatilization of particulate SVOCs from the front Teflon membrane filter, which was also reported by Subramanian et al.52 using the denuder method. Average OC thermal fractions for QF, QBT, and QBQ filters for summer 1999 are compared in Figure 7, representing the warmest period during MARCH-Atlantic. OC1, OC2, and OC3 levels for QBT are similar to those on QF, whereas corresponding levels on QBQ are half of these amounts. There is more OP for QBT than for QBQ, which might be associated with semi-volatile polar compounds.59 Volume 59 August 2009

Watson, Chow, Chen, and Frank Table 4. Average carbon fractions for top and bottom sliced quartz fiber front (QFtop and QFbottom) and concurrent backup (QBQtop and QBQbottom) filters.

Site Codea (Number of Samples) MORA (2)

YOSE (1)

HANC (2)

CHIR (3)

SHEN (4)

Loading of Carbon Fractionsb (␮g C/mg filter) Sliced Filter

OC

EC

TC

OC1

OC2

OC3

OC4

OP

EC1

EC2

EC3

QFtop QFbottom QBQtop QBQbottom QFtop QFbottom QBQtop QBQbottom QFtop QFbottom QBQtop QBQbottom QFtop QFbottom QBQtop QBQbottom QFtop QFbottom QBQtop QBQbottom

4.30 3.32 2.52 2.09 10.71 4.10 2.02 1.76 7.90 8.54 5.90 6.36 5.95 3.96 2.36 2.56 13.98 5.57 3.14 1.96

0.43 0.36 0.00 0.00 1.95 0.49 0.00 0.00 1.71 0.77 0.43 0.62 1.28 0.18 0.00 0.01 5.12 1.57 0.13 0.00

4.73 3.69 2.52 2.10 12.67 4.59 2.02 1.76 9.61 9.31 6.33 6.98 7.24 4.13 2.36 2.57 19.10 7.14 3.27 1.96

0.04 0.02 0.38 0.06 0.00 0.45 0.24 0.33 0.47 0.00 0.31 0.03 0.28 0.59 0.09 0.33 0.33 0.21 0.45 0.17

0.79 0.78 0.91 0.70 1.75 1.15 0.69 0.57 1.90 1.42 1.10 1.22 1.41 1.25 0.74 0.78 3.08 1.62 0.85 0.63

2.10 2.14 1.09 1.27 3.88 1.91 1.09 0.77 3.91 6.24 3.87 4.40 2.57 1.80 1.52 1.34 3.66 1.64 1.60 1.13

0.77 0.39 0.15 0.06 2.19 0.59 0.00 0.09 1.41 0.87 0.63 0.71 0.95 0.32 0.02 0.11 3.52 0.77 0.25 0.04

0.59 0.00 0.00 0.00 2.90 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.74 0.00 0.00 0.00 3.38 1.34 0.00 0.00

0.87 0.36 0.00 0.00 4.40 0.34 0.00 0.00 1.60 0.77 0.43 0.60 1.60 0.14 0.00 0.01 7.64 1.75 0.13 0.00

0.15 0.00 0.00 0.00 0.45 0.15 0.00 0.00 0.33 0.00 0.00 0.02 0.42 0.03 0.00 0.00 0.86 0.61 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.55 0.00 0.00

Notes: aSite codes are defined in Table 2. bOC ⫽ OC1 ⫹ OC2 ⫹ OC3 ⫹ OC4 ⫹ OP; EC ⫽ EC1 ⫹ EC2 ⫹ EC3 ⫺ OP; TC ⫽ OC ⫹ EC; OC1–OC4 are carbon fractions evolved at 140, 280, 480, and 580 °C, respectively, in a 100% He atmosphere; EC1–EC3-carbon fractions evolved at 580, 740, and 840 °C in a 98% He/2% O2 atmosphere; OP ⫽ pyrolyzed carbon measured by reflectance.51

DENUDER/BACKUP FILTER APPROACH The SEARCH network9 contains four urban versus rural (or suburban) pairs of sampling sites (i.e., Mississippi pair: urban Gulfport [GLF] in Gulfport and rural Oak Grove [OAK] near Hattiesburg; Alabama pair: urban Birmingham [BHM] in North Birmingham and rural Centreville [CTR] south of Tuscaloosa; Georgia pair: urban Jefferson Street [JST] in Atlanta and rural Yorkville [YRK] northwest of Atlanta; and Florida pair: urban Pensacola [PNS] in Pensacola and suburban outlying field [OLF] northwest of Pensacola). SEARCH particle composition monitors (PCM3)60 contain a carbon denuder upstream of the QBQ filters (see Table 1). Because the denuder is believed to remove most of the VOCs and gaseous SVOCs created during particle transit, the positive OC artifact should be minimal, and the negative OC artifact should dominate the QBQ OC. In contrast to the IMPROVE network’s 1-week exposure, SEARCH field blanks are placed in the sampler for 1–15 min before removal, so passive adsorption periods are much shorter. SEARCH denuded QBQ (dQBQ) TC in micrograms per square centimeter (the SEARCH filter deposit area [7.12 cm2] is about twice the IMPROVE filter deposit area [3.53 cm2]) was 10 –70% lower than the IMPROVE blank TC (bQF) of 1.54 –3.77 ␮g/cm2 (with median blank value of 2.4 ␮g/cm2), consistent with expectations. There is evidence of negative artifact (up to ⬃16% of denuded QF [dQF] OC) at the JST and YRK sites. The bQF TC was lower than dQBQ TC, partly because of insufficient exposure time. Only three SEARCH samples contained concurrent dQF, dQBQ, Volume 59 August 2009

and bQF measurements: one from the OAK site and two from the JST site. Their OC levels were similar. Except for the urban-rural pair in Georgia (JST and YRK sites), SEARCH dQBQ were enriched in OC2 and OC3 relative to OC1 (Figure 8). At the GLF, OAK, PNS, and OLF sites, OC1 was less than 0.2 ␮g/filter on dQF, consistent with VOCs being removed from the sampling stream. Adsorbed SVOCs (negative OC artifact) should have more OC2–OC4 than OC1 (positive OC artifact). However, at the JST and YRK sites, high OC1 may indicate VOC denuder breakthrough. OC-PM2.5 MASS REGRESSION The regression method calculates the slope, intercept, and correlation of OC versus PM2.5. A significant (⬎2–3 standard errors) positive intercept quantifies the average excess carbon for samples included in the regression. IMPROVE PM2.5 mass from Teflon membrane filters were linked to the OC concentrations from QF. OC, on average, accounts for a larger fraction of PM2.5 in summer (⬃20%) than in winter (15%). Because positive and negative OC artifacts differ both spatially and temporally, OC-PM2.5 pairs were segregated by site and season. To minimize outlier influence, a robust ordinary least-squares regression (ROR)61 algorithm was applied that uses an iteratively reweighted least-squares algorithm. This ROR algorithm is also used in factor-analysis models such as positive matrix factorization (PMF).62 Figure 9 shows a wide range of positive and negative intercepts. By the regression method, the OC artifact is higher in summer than in winter. Fourteen (9%) Journal of the Air & Waste Management Association 905

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Figure 6. Comparison of seasonally averaged OC on QF, QBT, QBQ, and blank filters (bQF and bQBQ) for: (a) Day 1 (24-hr sampling on first day followed by a 48-hr passive period) and (b) Day 2 (24-hr sampling on second day with 24 hr passive period before and after sampling) samples acquired from FME (spring ⫽ April, summer ⫽ July, fall ⫽ October, winter ⫽ January).

and 6 (4%) IMPROVE sites experience negative OC intercepts in summer and winter, respectively. Because summer sulfate is so high that the OC versus PM2.5 relationship is biased, the OC artifact is a minor component of PM2.5 mass. Intermittent contributions from summertime fires may also affect the intercept. The network average and standard deviation of OC versus PM2.5 regression intercepts are shown in Table 5. The intercepts (11.2–18.2 ␮g/filter) are approximately 40% higher than either bQF or QBQ OC concentrations. This is consistent with a negative OC artifact for Teflon membrane filters.52 The intercept method, if 906 Journal of the Air & Waste Management Association

applied, will likely overestimate the positive OC artifact and overcorrect the OC concentration. CONCLUSIONS AND RECOMMENDATIONS Positive OC artifacts occur when VOCs adsorb onto quartz fiber filters. Negative OC artifacts occur when particulate organic compounds evaporate during active sampling. Some of these evaporated compounds may also be adsorbed within quartz fiber filters. Sectioning of QBQ filters from top to bottom demonstrates that areal densities of OC fractions could decrease with depth through the filter. The assumption that VOC and SVOC adsorption on the backup filter equals that on the front filter is Volume 59 August 2009

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Figure 7. Average and standard deviation (vertical lines) for OC fractions on QF, QBT, and QBQ for summer 1999 at FME (total ⫽ 36 24-hr samples).

not always correct. This unequal distribution could be caused by inhomogeneities in the filter material. This inhomogeneity occurs during active sampling and was not observed in field blanks. Active sampling is responsible for all negative and part of the positive sampling artifact. Positive OC artifact on backup filters is expected to be equal to or greater than OC measured on field blanks.

Positive and negative artifacts compete with each other, but this analysis shows that the positive artifact is typically larger than the negative artifact in the IMPROVE network, where 959 field blanks were acquired at 181 sites during 2005 and 2006. QBQ OC levels of 8 –13 ␮g/filter were 2– 4 ␮g/filter above bQF from the same sites, although the number of field blanks at each site was low. The difference is within the standard deviation of the average, and they could

Figure 8. Average carbon fractions on dQBQ in the SEARCH network from January 1, 2005, to December 31, 2006. Volume 59 August 2009

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Figure 9. Robust regression intercepts (bar) and slopes (lines) for QF OC (dependent variable) vs. PM2.5 mass (independent variable) for all IMPROVE sites for the period from January 1, 2005 to December 31, 2006, during (a) spring, (b) summer, (c) fall, and (d) winter (spring ⫽ March, April, May; summer ⫽ June, July, August; fall ⫽ September, October, November; winter ⫽ December, January, February).

be used interchangeably to adjust for the positive OC artifact in the non-urban IMPROVE sites. QBT showed twice the OC adsorption as QBQ at the urban MARCH-Atlantic location. QBQ showed twice the OC levels of bQF, in contrast to the similarity between these estimators from the IMPROVE samples. This difference could be caused by (1) larger concentrations of adsorbable VOCs in urban areas, which might have deposited or reacted before arriving at remote IMPROVE sites; (2) greater abundances of SVOCs at the urban site, which might have largely 908 Journal of the Air & Waste Management Association

evaporated from particles during transport to IMPROVE sites; and/or (3) a longer passive period for the IMPROVE field blanks (⬃7 days) than for the MARCH-Atlantic field blanks (⬃3 days). The SEARCH network uses an OC denuder upstream of the front and backup filters, and backup filter levels were only slightly higher than field blank levels. Because the denuder removes most of the organic vapors from the airstream, the backup should consist mostly of material evaporated from the aerosol deposit and be an indication of the Volume 59 August 2009

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Figure 9. Cont. Table 5. Robust ordinary least squares regression intercept of QF OC (y-axis) vs. PM2.5 mass (x-axis) averaged over all IMPROVE sites for each season during the period from January 1, 2005, to December 31, 2006.

Observables Average intercept OC (␮g/filter) Average blank (bQF) OC (␮g/filter) Average backup (QBQ) OC from six sites (␮g/filter) Number of pairs

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Spring (March, April, May)

Summer (June, July, August)

12.44 ⫾ 6.43 8.44 8.88

18.18 ⫾ 15.13 10.17 12.68

8898

7184

Fall (September, October, November) 15.23 ⫾ 10.45 8.14 10.23 4372

Winter (December, January, February) 11.20 ⫾ 7.63 7.08 7.78 7311

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Watson, Chow, Chen, and Frank negative OC artifact. This negative OC artifact may be more prevalent in urban than in non-urban areas because of higher SVOCs in the urban areas. Urban samples appear to be more complex because of the dynamic nature of aerosol in the atmosphere and on a filter. Because the IMPROVE network also includes a few urban sites (e.g., Washington, DC), more geographical coverage for the backup filters is needed. A systematic protocol to acquire field blanks (e.g., once/month at the beginning or end of each month with ⬃7 days in the passive period) would obtain a better record of the seasonal variability than is currently provided by the random field blank placement in the IMPROVE network. The IMPROVE method of adjusting for OC adsorption appears to be the best that can be done within the constraints of current understanding. Given the non-urban nature of most IMPROVE measurement locations, OC denuders appear to be unnecessary. The negative OC artifact appears to be partially compensated for by recapture of material within the bottom half of the front filter. The field blanks and backup filter appear to retain a representative amount of positive OC artifact. The small exposure area (3.53 cm2) of the 25-mm filter relative to the deposit also makes artifact correction less important for samples with OC levels more than 20 ␮g/filter. Parallel QBT and QBQ offer the opportunity to separate the adsorbed VOCs from the evaporated and re-adsorbed SVOCs; however, each of these approaches requires more resources in terms of filter handling and analysis. Positive and negative sampling artifacts are an important issue for chemical speciation, and current correction methods contain large uncertainties. Maximizing sample volume and minimizing filter size increases particle loading and mitigates the influence of sampling artifacts in terms of micrograms per square centimeter. Field blanks should be exposed for at least the full duration of active samples to provide sufficient time in which they can passively acquire organic vapors. Field blanks and backup filters should be deployed to represent several different seasons and source environments. Although the results reported here are indicative, they need to be expanded upon. Further laboratory and field experiments are needed to determine adsorption capacities and retention for filter media and SVOCs. In the longer term, it is necessary to develop, evaluate, and deploy new carbon analysis methods that achieve more information (e.g., finer thermal fractions, specific organic compounds, reflectance and transmittance at different wavelengths, inorganic as well as organic compounds) for the same or lesser cost. The long-term goal may involve state-of-the-art mass and optical spectrometric detectors. This development will also need to maintain the continuity of long-term trends established by the currently applied methods. ACKNOWLEDGMENTS This work was partially supported by U.S. Environmental Protection Agency (EPA) STAR grant no. RD-83108601-0, EPA/ National Park Service under contract no. C2350064010, the California Air Resources Board under contract no. 04-307, and the Nazir and Mary Ansari Foundation. The authors appreciate the thoughtful comments provided by Joann Rice of EPA. Although this work has been reviewed by EPA 910 Journal of the Air & Waste Management Association

and approved for publication, it does not necessarily reflect agency policies or views. REFERENCES 1. Watson, J.G.; Chow, J.C.; Chen, L.-W.A. Summary of Organic and Elemental Carbon/Black Carbon Analysis Methods and Intercomparisons; AAQR 2005, 5, 65-102; available at http://aaqr.org/ (accessed 2009). 2. Kukreja, V.P.; Bove, J.L. Determination of Free Carbon Collected on High-Volume Glass Fiber Filter; Environ. Sci. Technol. 1976, 10, 187-189. 3. Chen, L.-W.A.; Chow, J.C.; Watson, J.G.; Moosmu ¨ ller, H.; Arnott, W.P. Modeling Reflectance and Transmittance of Quartz Fiber Filter Samples Containing Elemental Carbon Particles: Implications for Thermal/Optical Analysis; J. Aerosol Sci. 2004, 35, 765-780; doi: 10.1016/ j.jaerosci.2003.12.005. 4. Chow, J.C.; Watson, J.G.; Chen, L.-W.A.; Arnott, W.P.; Moosmu ¨ ller, H.; Fung, K.K. Equivalence of Elemental Carbon by Thermal/Optical Reflectance and Transmittance with Different Temperature Protocols; Environ. Sci. 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Assessment of Carbon Sampling Artifacts in the IMPROVE, STN/CSN, and SEARCH Networks; Desert Research Institute: Reno, NV, 2008; available at http:// www.epa.gov/air/airtrends/specialstudies/20080822_sampling_artifact_rev.pdf (accessed 2009). 18. Bruckman, L.; Rubino, R.A. High Volume Sampling: Errors Incurred during Passive Deposition Exposure Periods; J. Air Pollut. Control Assoc. 1976, 26, 881-883. 19. Sweitzer, T.A. Characterization of Passively Loaded Particles on HIVOL Samples; J. Air Pollut. Control Assoc. 1980, 30, 1324-1325. 20. Swinford, R.L. The Assessment of Passive Loading Effects on TSP Measurements in Attainment Areas; J. Air Pollut. Control Assoc. 1980, 30, 1322-1324. 21. Chow, J.C.; Watson, J.G.; Lowenthal, D.H.; Solomon, P.A.; Magliano, K.L.; Ziman, S.D.; Richards, L.W. In Planning and Managing Regional Air Quality, Modeling and Measurement Studies, Solomon, P.A., Ed.; CRC: Boca Raton, FL, 1994; pp 687-698. 22. Chow, J.C.; Watson, J.G.; Lu, Z.; Lowenthal, D.H.; Frazier, C.A.; Solomon, P.A.; Thuillier, R.H.; Magliano, K.L. Descriptive Analysis of PM2.5 and PM10 at Regionally Representative Locations during SJVAQS/AUSPEX; Atmos. Environ. 1996, 30, 2079-2112. Volume 59 August 2009

Watson, Chow, Chen, and Frank 23. Watson, J.G.; Turpin, B.J.; Chow, J.C. In Air Sampling Instruments for Evaluation of Atmospheric Contaminants, 9th ed.; Cohen, B.S., McCammon, C.S.J., Eds.; American Conference of Governmental Industrial Hygienists: Cincinnati, OH, 2001; pp 201-216. 24. Kirchstetter, T.W.; Novakov, T.; Hobbs, P.V.; Magi, B.I. Airborne Measurements of Carbonaceous Aerosols in Southern Africa during the Dry Biomass Burning Season; J. Geophys. Res. Atmos. 2003, 108, SAF 12-1-SAF 12-8; doi: 10.1029/2002JD002171. 25. Eatough, D.J.; Eatough, N.L.; Pang, Y.; Sizemore, S.; Kirchstetter, T.W.; Novakov, T.; Hobbs, P.V. Semivolatile Particulate Organic Material in Southern Africa during SAFARI 2000; J. Geophys. Res. 2003, 108, SAF15-1-SAF15-6; doi: 10.1029/2002JD002296. 26. Kim, E.; Hopke, P.K.; Qin, Y. Estimation of Organic Carbon Blank Values and Error Structures of the Speciation Trends Network Data for Source Apportionment; J. Air & Waste Manage. Assoc. 2005, 55, 1190-1199. 27. Offenberg, J.H.; Lewandowski, M.; Edney, E.O.; Kleindienst, T.E. Investigation of a Systematic Offset in the Measurement of Organic Carbon with a Semicontinuous Analyzer; J. Air & Waste Manage. Assoc. 2007, 57, 596-599; doi: 10.3155/1047-3289.57.5.596. 28. Turpin, B.J.; Huntzicker, J.J.; Hering, S.V. Investigation of Organic Aerosol Sampling Artifacts in the Los Angeles Basin; Atmos. Environ. 1994, 28, 3061-3071. 29. Chow, J.C.; Watson, J.G.; Lowenthal, D.H.; Chen, L.-W.A.; Magliano, K.L. Particulate Carbon Measurements in California’s San Joaquin Valley; Chemosphere 2006, 62, 337-348. 30. Fung, K.K.; Chow, J.C.; Watson, J.G. Determining Organic Carbon Adsorption on Quartz Fiber Filters by Sample Splitting and Thermal/ Optical Analysis. In Proceedings, 13th World Clean Air and Environmental Protection Congress and Exhibition, International Union of Air Pollution Prevention Associations: London, U.K., 2004; pp 313-1–313-6. 31. Bertoni, G.; Febo, A.; Perrino, C.; Possanzini, M. Annular Active Diffusive Sampler: a New Device for the Collection of Organic Vapours; Ann. di Chim. 1984, 74, 97-104. 32. Eatough, D.J.; Brutsch, M.; Lewis, L.; Hansen, L.D.; Lewis, E.A.; Eatough, N.L.; Farber, R.J. Diffusion Denuder Sampling Systems for the Collection of Gas and Particle Phase Organic Compounds. In Transactions, Visibility Protection: Research and Policy Aspects, Bhardwaja, P.S., Ed.; Air Pollution Control Association: Pittsburgh, PA, 1987; pp 397-406. 33. Fitz, D.R. Reduction of the Positive Organic Artifact on Quartz Filters; Aerosol Sci. Technol. 1990, 12, 142-148. 34. Krieger, M.S.; Hites, R.A. Diffusion Denuder for the Collection of Semivolatile Organic Compounds; Environ. Sci. Technol. 1992, 26, 1551-1555. 35. Gundel, L.A.; Stevens, R.K.; Daisey, J.M.; Lee, V.C.; Mahanama, K.R.R.; Cancel-Velez, H.G. Direct Determination of the Phase Distributions of Semi-Volatile Polycyclic Aromatic Hydrocarbons Using Annular Denuders; Atmos. Environ. 1995, 29, 1719-1733. 36. Cui, W.; Machir, J.; Lewis, L.; Eatough, D.J.; Eatough, N.L. Fine Particulate Organic Material at Meadview during the Project MOHAVE Summer Intensive Study; J. Air & Waste Manage. Assoc. 1997, 47, 357-369. 37. Mader, B.T.; Flagan, R.C.; Seinfeld, J.H. Sampling Atmospheric Carbonaceous Aerosols Using a Particle Trap Impactor/Denuder Sampler; Environ. Sci. Technol. 2001, 35, 4857-4867. 38. Ding, Y.; Pang, Y.; Eatough, D.J. High-Volume Diffusion Denuder Sampler for the Routine Monitoring of Fine Particulate Matter I. Design and Optimization of the PC-BOSS; Aerosol Sci. Technol. 2002, 36, 369-382. 39. Ding, Y.; Pang, Y.; Eatough, D.J.; Eatough, N.L.; Tanner, R.L. HighVolume Diffusion Denuder Sampler for the Routine Monitoring of Fine Particulate Matter II. Field Evaluation of the PC-BOSS; Aerosol Sci. Technol. 2002, 36, 383-396. 40. Ding, J.; Zhu, T. Heterogeneous Reactions on the Surface of Fine Particles in the Atmosphere; Chin. Sci. Bull. 2003, 48, 2267-2276. 41. Fan, X.; Brook, J.R.; Mabury, S.A. Sampling Atmospheric Carbonaceous Aerosols Using an Integrated Organic Gas and Particle Sampler; Environ. Sci. Technol. 2003, 37, 3145-3151. 42. Viana, M.; Chi, X.; Maenhaut, W.; Cafmeyer, J.; Querol, X.; Alastuey, A.; Mikuska, P.; Vecera, Z. Influence of Sampling Artifacts on Measured PM, OC, and EC Levels in Carbonaceous Aerosols in an Urban Area; Aerosol Sci. Technol. 2006, 40, 107-117. 43. Eatough, D.J.; Wadsworth, A.; Eatough, D.A.; Crawford, J.W.; Hansen, L.D.; Lewis, E.A. A Multiple-System, Multi-Channel Diffusion Denuder Sampler for the Determination of Fine-Particulate Organic Material in the Atmosphere; Atmos. Environ. 1993, 27, 1213-1219. 44. White, W.H.; Macias, E.S. Carbonaceous Particles and Regional Haze in the Western United States; Aerosol Sci. Technol. 1989, 10, 111-117. 45. Solomon, P.A.; Klamser, T.; Egeghy, P.; Crumpler, D.; Rice, J. STN/IMPROVE Comparison Study—Preliminary Results. 2004. Presented at the PM Model Performance Workshop, Research Triangle Park, NC, February 10, 2004; available at http://www.cleanairinfo.com/PMModelPerformanceWorkshop2004/ presentation/RiceSTNImprove.ppt (accessed 2009). 46. Frank, N.H. Retained Nitrate, Hydrated Sulfates, and Carbonaceous Mass in Federal Reference Method Fine Particulate Matter for Six Eastern Cities; J. Air & Waste Manage. Assoc. 2006, 56, 500-511.

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47. Chow, J.C.; Fujita, E.M.; Watson, J.G.; Lu, Z.; Lawson, D.R.; Ashbaugh, L. L. Evaluation of Filter-Based Aerosol Measurements during the 1987 Southern California Air Quality Study; Environ. Mon. Assess. 1994, 30, 49-80. 48. Chow, J.C.; Watson, J.G.; Edgerton, S.A.; Vega, E. Chemical Composition of PM10 and PM2.5 in Mexico City during Winter 1997; Sci. Total Environ. 2002, 287, 177-201. 49. Chow, J.C.; Watson, J.G.; Lowenthal, D.H.; Magliano, K.L. Loss of PM2.5 Nitrate from Filter Samples in Central California; J. Air & Waste Manage. Assoc. 2005, 55, 1158-1168. 50. Chow, J.C.; Watson, J.G.; Lowenthal, D.H.; Park, K.; Doraiswamy, P.; Bowers, K.; Bode, R. Continuous and Filter-Based Measurements of PM2.5 Nitrate and Sulfate at the Fresno Supersite; Environ. Mon. Assess. 2008, 144, 179-189. 51. Chow, J.C.; Watson, J.G.; Chen, L.-W.A.; Chang, M.C.O.; Robinson, N.F.; Trimble, D.; Kohl, S. The IMPROVE_A Temperature Protocol for Thermal/ Optical Carbon Analysis: Maintaining Consistency with a Long-Term Database; J. Air & Waste Manage. Assoc. 2007, 57, 1014-1023. 52. Subramanian, R.; Khlystov, A.Y.; Cabada, J.C.; Robinson, A.L. Positive and Negative Artifacts in Particulate Organic Carbon Measurements with Denuded and Undenuded Sampler Configurations; Aerosol Sci. Technol. 2004, 38(Suppl. 1), 27-48. 53. Pandis, S.N.; Harley, R.A.; Cass, G.R.; Seinfeld, J.H. Secondary Organic Aerosol Formation and Transport; Atmos. Environ. 1992, 26, 2269-2282. 54. Chen, L.-W.A.; Moosmu ¨ ller, H.; Arnott, W.P.; Chow, J.C.; Watson, J.G.; Susott, R.A.; Babbitt, R.E.; Wold, C.; Lincoln, E.; Hao, W.M. Particle Emissions from Laboratory Combustion of Wildland Fuels: In Situ Optical and Mass Measurements; Geophys. Res. Lett. 2006, 33, 1-4; doi: 10.1029/2005GL024838. 55. Chen, L.-W.A.; Moosmu ¨ ller, H.; Arnott, W.P.; Chow, J.C.; Watson, J.G.; Susott, R.A.; Babbitt, R.E.; Wold, C.E.; Lincoln, E.N.; Hao, W.M. Emissions from Laboratory Combustion of Wildland Fuels: Emission Factors and Source Profiles; Environ. Sci. Technol. 2007, 41, 4317-4325. 56. Chow, J.C.; Watson, J.G.; Kuhns, H.D.; Etyemezian, V.; Lowenthal, D.H.; Crow, D.J.; Kohl, S.D.; Engelbrecht, J.P.; Green, M.C. Source Profiles for Industrial, Mobile, and Area Sources in the Big Bend Regional Aerosol Visibility and Observational (BRAVO) Study; Chemosphere 2004, 54, 185-208. 57. Chow, J.C.; Watson, J.G.; Lowenthal, D.H.; Chen, L.-W.A.; Zielinska, B.; Mazzoleni, L.R.; Magliano, K.L. Evaluation of Organic Markers for Chemical Mass Balance Source Apportionment at the Fresno Supersite; Atmos. Chem. Phys. 2007, 7, 1741-1754. http://www.atmos-chem-phys. net/7/1741/2007/acp-7-1741-2007.pdf (accessed 2009). 58. Park, K.; Chow, J.C.; Watson, J.G.; Trimble, D.L.; Doraiswamy, P.; Arnott, W.P.; Stroud, K.R.; Bowers, K.; Bode, R.; Petzold, A.; Hansen, A.D.A. Comparison of Continuous and Filter-Based Carbon Measurements at the Fresno Supersite; J. Air & Waste Manage. Assoc. 2006, 56, 474-491. 59. Yu, J.Z.; Xu, J.H.; Yang, H. Charring Characteristics of Atmospheric Organic Particulate Matter in Thermal Analysis; Environ. Sci. Technol. 2002, 36, 754-761. 60. Edgerton, E.S.; Hartsell, B.E.; Saylor, R.D.; Jansen, J.J.; Hansen, D.A.; Hidy, G.M. The Southeastern Aerosol Research and Characterization Study Part II: Filter-Based Measurements of Fine and Coarse Particulate Matter Mass and Composition; J. Air & Waste Manage. Assoc. 2005, 55, 1527-1542. 61. Dutter, R.; Huber, P.J. Numerical Methods for the Nonlinear Robust Regression Problem; J. Stat. Comput. Sim. 1981, 13, 79-113. 62. Paatero, P. Least-Squares Formulation of Robust Non-Negative Factor Analysis; Chemom. Intell. Lab. Sys. 1997, 37, 23-35.

About the Authors John G. Watson is a research professor, Judith C. Chow is the Nazir and Mary Ansari Chair in Entrepreneurialism and Science and a research professor, and L.-W. Antony Chen is an associate research professor with the Division of Atmospheric Sciences at the Desert Research Institute. Drs. Watson and Chow are also adjunct professors at the Institute of Earth Environment at the Chinese Academy of Sciences in Xi’an, People’s Republic of China. Neil H. Frank is Senior Air Quality Data Advisor with EPA. Please address correspondence to: John G. Watson, Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512; phone: ⫹1-1-775-674-7046; fax: ⫹1-775-6747009; e-mail: [email protected].

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