rXXXX American Chemical Society A dx.doi.org/10.1021/es202736a | Environ. Sci. Technol. XXXX, XXX, 000–000

ARTICLE

pubs.acs.org/est

Chemical Characterization and Source Apportionment of Fine andCoarse Particulate Matter Inside the Refectory of Santa Maria DelleGrazie Church, Home of Leonardo Da Vinci’s “Last Supper”Nancy Daher,† Ario Ruprecht,‡ Giovanni Invernizzi,‡ Cinzia De Marco,‡ Justin Miller-Schulze,§

Jong Bae Heo,§ Martin M. Shafer,§ James J. Schauer,§ and Constantinos Sioutas†,*†Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, California, United States‡LARS Laboratorio di Ricerca Ambientale SIMG/ISDE, Milan, Italy§Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, Wisconsin, United States

bS Supporting Information

1. INTRODUCTION

Damage to cultural assets has been of growing interest tomuseum conservators and curators. There is mounting evidencecorrelating indoor air pollution, biological contamination, masstourism, and variability in microclimate conditions with materialdeterioration.1,2 A major concern is damage by particulate mat-ter (PM) to masterworks of art displayed in museums. Poten-tial hazards include “soiling” (perceptible degradation of visualqualities) due to deposition of airborne particles, particularlyelemental carbon, and soil dust.3 Further damage can be inducedby chemically reactive species, such as ammonium sulfate andorganic acids.2,4

Typically, indoor PM consists of outdoor-infiltrating andindoor-emitted particles in addition to indoor-formed particlesthrough reactions of gas-phase precursors emitted both indoorsand outdoors.5,6 Moreover, the level and composition of indoorPM are governed by a myriad of factors. These mainly consist ofthe ventilation system, filtration effect of the building envelope,deposition rate of particles as well as the intensity of indoor and

outdoor sources.7,8 An accurate characterization of airbornePM in museums is therefore essential for conserving the ex-hibited artifacts.

An emerging concern is with PM-induced damage to the“Last Supper” painting, one of Leonardo da Vinci’s mostfamous artworks, located in the refectory of Santa Maria delleGrazie Church in Milan, Italy. Although this painting hassurvived many challenges, including bombing during WorldWar II, it is yet facing another challenge. The “Last Supper”painting, which was majorly restored in the 20th century, is atrisk with air pollution arising from its surrounding Milan area.Milan is one of the most polluted areas inWestern Europe9 withPM10 air quality standards frequently exceeded.

10 In an attemptto protect the painting, a sophisticated heating, ventilation, and

Received: August 5, 2011Accepted: November 9, 2011Revised: October 31, 2011

ABSTRACT: The association between exposure to indoorparticulate matter (PM) and damage to cultural assets has beenof primary relevance to museum conservators. PM-induceddamage to the “Last Supper” painting, one of Leonardo da Vinci’smost famous artworks, has been a major concern, given thelocation of this masterpiece inside a refectory in the city center ofMilan, one of Europe’s most polluted cities. To assess this risk, aone-year sampling campaign was conducted at indoor and out-door sites of the painting’s location, where time-integrated fineand coarse PM (PM2.5 and PM2.5�10) samples were simulta-neously collected. Findings showed that PM2.5 and PM2.5�10

concentrations were reduced indoors by 88 and 94% on a yearlyaverage basis, respectively. This large reduction is mainly attrib-uted to the efficacy of the deployed ventilation system in removing particles. Furthermore, PM2.5 dominated indoor particle levels,with organic matter as the most abundant species. Next, the chemical mass balance model was applied to apportion primary andsecondary sources tomonthly indoor fine organic carbon (OC) and PMmass. Results revealed that gasoline vehicles, urban soil, andwood-smoke only contributed to an annual average of 11.2 ( 3.7% of OC mass. Tracers for these major sources had minimalinfiltration factors. On the other hand, fatty acids and squalane had high indoor-to-outdoor concentration ratios with fatty acidsshowing a good correlation with indoor OC, implying a common indoor source.

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air conditioning (HVAC) system equipped with particle filtra-tion has been installed.

To assess the effectiveness of this control measure, we con-ducted a one-year sampling campaign at indoor and outdoorsites of the refectory. At both locations, fine and coarse PM(PM2.5 and PM2.5�10, respectively) samples were simultaneouslycollected then analyzed for their chemical properties. In thepresent article, the indoor-to-outdoor relationship of key tracersof PM sources is investigated in order to evaluate the impact ofindoor and outdoor sources on indoor particle levels. Further-more, the chemical mass balance model is applied to identify andestimate sources contributions to indoor PM2.5 concentration.Results of this study provide a quantitative understanding onthe composition, origin and level of PM inside the refectory.Ultimately, these findings can be used as guidelines for theimplementation of additional, and particularly source-specific,control strategies to mitigate the concentration of particlecomponents potentially detrimental to the “Last Supper” paint-ing. They can also be used as a benchmark in future studies aimedat protecting indoor artworks and antiquities.

2. MATERIALS AND METHODS

2.1. Sampling Description. To characterize PM inside therefectory, PM2.5 and PM2.5�10 were simultaneously sampled atindoor and outdoor sites of the refectory. The sampling cam-paign lasted from December 2009 to November 2010. Duringthis period, 24-hour size-segregated PM samples were collectedon a weekly basis by means of two sets of Sioutas personalcascade impactor samplers (Sioutas PCIS, SKC Inc., Eighty Four,PA11). Every set consisted of two collocated PCIS loaded with37 and 25 mm filters for fine and coarse PM analyses, respectively.Each of the PCIS was placed at the indoor or outdoor site andoperated at a flow rate of 9 lpm. For the purpose of chemicalanalysis, one set of the PCIS was loaded with Teflon filters (PallLife Sciences, Ann Arbor, MI), whereas the other one was loadedwith quartz microfiber filters (Whatman International Ltd.,Maidstone, England). PM mass concentration was determinedfrom themass loadings of the weekly Teflon filters as described inthe Supporting Information (SI).The indoor sampling location was inside the refectory of Santa

Maria delle Grazie Church, where da Vinci painted the “LastSupper” on one of its walls. Samples were collected at approxi-mately 1 m directly below the painting and a few centimetersfrom the wall surface. The site is equipped with a newly deployedHVAC system, supplying 4000 m3/h total air flow, of which2000 m3/h are external fresh air. This system is operated continu-ously. The air-flow rate inside the refectory, whose volume is 3130m3,is 3000 m3/h, resulting in an air exchange rate of roughly 1 h�1.This relatively low air change rate helps avoid convective airvelocities on the painting to the degree possible. The remainingair flow rate goes into two 130 m3 isolating zones, located at theentrance and exit of the refectory, through which visitors pass forisolation and decontamination from outdoor pollution. Further-more, the air is filtered with plane, pocket and absolute filters aswell as chemical filters (Purafil, Inc.); more details about thesefilters as well as the design and operation of the HVAC systemcan be found in the SI. The number of visitors and duration ofvisit are limited to 25 persons and 15 min at any time between8:15 a.m. and 6:45 p.m. Visits are allowed each day, except forMonday, with number of visitors averaging 1000 visitors/day.The temperature and relative humidity are automatically controlled

to maintain constant conditions. Large variations in the thermo-hygrometric factors in the refectory, enhanced by the presence ofvisitors, may lead to an increase in the deposition rate ofairborne pollutants on the painting, as previously demonstratedby Camuffo and Bernardi.12 The temperature of the backsideroom is also maintained at about 2 �C higher than the refectory’stemperature to avoid PM deposition on the painting due tothermophoresis effects.3,13 Finally, it should be noted that theHVAC system failed for few days during one week of April.PM concentration substantially increased during that week,compared to the remaining weeks with noninterrupted systemfunctioning. This effect was more noticeable for PM2.5�10, forwhich a nearly 9-fold increase was observed, as shown in SIFigure S3. This occurrence, however, has minor impacts on theresults where monthly averages are reported throughoutthis study.2.2. Chemical Analyses. To conduct the chemical analyses,

the Teflon and quartz filters were sectioned into portions. Thefractions used for elemental and organic carbon (EC and OC,respectively) quantification were grouped into weekly samplesand quantified using the NIOSH thermal optical transmissionmethod.14 All remaining fractions, with the exception of fewPM2.5�10 sections, were composited monthly. Given their lowmass loading, February/March, April/May, and October/No-vember coarse samples were composited bimonthly. Thesemonthly and bimonthly fractions were analyzed for water-solubleOC (WSOC) and ions using a Sievers 900 Total Organic CarbonAnalyzer15 and ion chromatography, respectively. Total elementalcontent of these composites was also measured using highresolution magnetic sector inductively coupled plasma massspectrometry (Thermo-Finnigan Element 2).16 Additionally,organic speciation was conducted on PM2.5 filter sections usinggas chromatography mass spectrometry (GC-6980, quadrupoleMS-5973, Agilent Technologies). PM2.5�10 lacked sufficientmass for this analysis. Details of these analyses are provided inthe SI.2.3. Source Apportionment. A molecular marker chemical

mass balancemodel (MM-CMB) that wasmathematically solvedwith the U.S. Environmental Protection Agency CMB (EPA-CMB8.2) software was used to estimate primary and secondarysource contributions to indoor fine OC on a monthly basis. Theeffective variance weighted least-squares algorithm was appliedto apportion the receptor data to the source profiles.17

MM-CMB was conducted using primary molecular sourcetracers that were quantified in the PM2.5 samples. Markers thatare chemically stable and secondary organic aerosol (SOA)tracers that are unique to their precursor gases were selected asfitting species.18 These included levoglucosan, αββ-20R&S�C27-cholestane, αββ-20R&S-C29-sitostane, 17α(H)-22,29,30-trisnorhopane, 17α(H)-21β(H)-hopane, 17β(H)-21α(H)-30-norhopane, benzo(b)fluoranthene, benzo(k)fluoranthene, indeno-[c,d]pyrene, benzo(ghi)perylene, EC, aluminum (Al), andtitanium (Ti).The input source profiles were based on the observed molec-

ular markers and assumed representative of sources in Milan.These profiles included wood-smoke,19,20 urban soil, gasolinevehicles,21 and diesel emissions.21 Biogenic-derived SOAwas notincluded in the model but its contribution was estimated usingfixed tracer-to-OC ratios.22 Moreover, the selected urban soilprofile is not specific toMilan. However, the choice of this profileis not critical for the overall apportionment of fine OC as itscontribution to total OC mass is small23. Its selection was

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nonetheless based on a comparison of the elemental ratios of themeasured data to those of available soil profiles, where the urbansoil profile of St. Louis (Missouri)23 provided a best fit. In contrast,natural gas, coal soot and toluene-derived (anthropogenic) SOAsources were not considered in the model, as their molecularmarkers were not detected in the samples. Furthermore, contribu-tions from vegetative detritus were not apportioned becausen-alkanes (C29�C33) did not exhibit an odd-carbon preferenceindicative of modern plant material. Lastly, the CMB modelresults were considered valid if they met specific acceptancecriteria as outlined in the SI.

3. RESULTS AND DISCUSSION

3.1. Indoor�Outdoor Relationship. 3.1.1. Particulate Massand Composition. Indoor and outdoor monthly average PM2.5

and PM2.5�10 mass concentrations are shown in Figure 1(a, b).Indoor concentrations were substantially lower than those out-doors for both particle modes. This significant reduction in PM2.5

and PM2.5�10 concentration (88( 7% and 94( 3% on a yearlyaverage ((standard deviation) basis, respectively) can be largelyattributed to the efficacy of the HVAC system in removinginfiltrating outdoor PM. Moreover, coarse PM exhibited

Figure 1. Monthly average indoor concentration (compared to outdoor concentration) and bulk composition for (a, c) PM2.5 and (b, d) PM2.5�10.Error bars represent one standard error.

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extremely low indoor levels ranging between 0.12 and 0.83 μg/m3

with no specific seasonal trend. PM2.5 was the dominant indoorPM component with a concentration range of 1.7�4.9 μg/m3. Italso followed a pattern dissimilar to that of its outdoor compo-nent, indicating that indoor sources may have major contribu-tions to fine PM indoors. Finally, it is noteworthy that currentlythere are no regulations for PM levels in museums, galleries, andarchives. However, the American Society of Heating, Refrigerat-ing and Air-Conditioning Engineers (ASHRAE)24 as well as theCanadian Conservation Institute,25 provide recommendationsfor PM2.5. They suggest concentration limits of <0.1 and 1�10 μg/m3

for sensitivematerials and general collections, respectively. PM2.5

levels in the refectory are within the limit values for generalcollections, but greater than those for sensitive materials. How-ever, it is important to recognize that attaining such limitsrequires controls that may not be feasible and realistic.To determine the monthly bulk composition of indoor PM2.5

and PM2.5�10, a chemical mass balance was conducted asillustrated in Figure 1(c, d). PM chemical species were classifiedinto water-insoluble organic matter (WIOM), water-solubleorganic matter (WSOM), EC, ions, crustal material (CM), andtrace elements (TE). WIOM and WSOM were determined bymultiplying bothWSOC and water-insoluble OC (WIOC =OC-WSOC) concentrations by a factor of 1.7.26�28 Further detailsabout the reconstruction are provided in the SI.WIOM was the dominant component of PM2.5 and PM2.5�10,

accounting for an average ((one standard deviation) of 70.9 (16.4% and 61.3 ( 29.7% of total PM mass, respectively. PM2.5-WIOM concentrations exhibited some variation, ranging between1.7 μg/m3 in December and 3.1 μg/m3 in July. Conversely, coarsemode WIOM displayed lower concentrations, varying between0.10 μg/m3 in December and 0.38 μg/m3 in April/May. WSOMwas the next most abundant component of PM2.5 but only a minorfraction ofOM, comprising 17.8( 4.4% and19.9( 2.9%of their totalmass, respectively. Moreover, WSOM only accounted for 8.8( 4.9%of coarse PMmass. EC, on the other hand, only contributed to PM2.5.Its concentration and relative proportion were however minimal(<0.05μg/m3 and 1.5%). CMaccounted for 8.2( 2.2% and 14.6(4.7% of PM2.5 and PM2.5�10, respectively. Lastly, ions accounted for3.1 ( 1.8% of PM2.5 and 5.4 ( 3.5% of PM2.5�10.The agreement between the reconstructed and gravimetric

mass is overall good, averaging 104 ( 20% for PM2.5 and 88 (29% for PM2.5�10. The observed discrepancy could be related touncertainties in the conversion factors from WSOC to WSOM,WIOC toWIOM, and metals to oxides as well as uncertainties inthe measured mass, particularly for coarse PM.3.1.2. Infiltration Ratios of Tracer Species. To investigate the

influence of outdoor and indoor sources on PM levels inside therefectory, seasonal average indoor-to-outdoor (I/O) mass ratiosand their standard deviations were determined for key tracers ofmajor PM sources as summarized in Table 1 for PM2.5. I/OSpearman correlation coefficients (R) were also evaluated todetermine whether an indoor species is attributable to infiltrationfrom outdoors. This analysis, coupled with CMB results, pro-vides a quantitative assessment of the infiltration of PM fromspecific outdoor sources. It should also be noted that concentra-tions that are below or comparable to the limit of detection(LOD), increase the uncertainty associated with the data, butshould not cause a large overprediction. Concentration valuesthat were below the LOD were assumed as half the detectionlimit. LODs of all measured species are listed in SI Table S1. Theseasons were segregated as winter (December�February), spring

(March�May), summer (June�August), and fall (September�November). Data for PM2.5�10, a minor component of indoorPM, is reported in SI Table S2. In consistence with its extremelylow indoor mass, coarse PM exhibited small I/O ratios (e8%).For a given species, the combination of the I/O ratio and

correlation provides an estimate of its I/O source relationship. Thelatter can be described by the following categories. First, a low I/Oratio accompanied by a good positive I/O correlation indicates alow but non-negligible infiltration factor and the lack of substantialindoor sources for a given species. Sulfate, which is a classic tracerof atmospheric outdoor aerosols with no known indoorsources29,30, presents a similar I/O source relationship, despiteits usual association with high I/O ratios. However, in the currentstudy, species that are usually considered to originate from out-doors (e.g., sulfate, EC in nonsmoking environments)29�31, havelow I/O ratios due to their effective removal by the HVAC system.Second, a species associated with a low I/O ratio and poor I/Ocorrelation has a very low infiltration factor and no significantsources impacting its indoor levels. Furthermore, a species with ahigh I/O ratio and a poor I/O correlation has a relatively lowinfiltration ratio but important indoor sources. For instance, OC,which is commonly associated with indoor sources29,31, exhibits asimilar behavior. Lastly, a species with a high I/O ratio and goodpositive I/O correlation displays high infiltration efficiency andlacks important indoor sources.As can be inferred from Table 1, the I/O ratios were generally

greater for PM2.5 than PM2.5�10 species, reflecting the lowerinfiltration efficiency and larger deposition velocity of coarseparticles.32,33 Moreover, I/O ratios for fine PM mass were belowunity and presented some seasonality reaching aminimum (0.04(0.03) in winter and a maximum (0.18 ( 0.06) in summer. Theseratios were also accompanied by a negative I/O correlation(R = �0.31), indicating that indoor sources have major contribu-tions to PM2.5. On the other hand, ionic species, sulfate, nitrate andammonium, originated from outdoors (R = 0.66�0.76) but withvery low infiltration factors (I/O ratioe2%). Similarly to fine PMmass, OC and WIOC exhibited peak I/O ratios in summer(0.61 and 1.07, respectively) and were negatively correlated to theiroutdoor components, implying the existence of significant indoorOM sources. Furthermore, WSOC, an indicator of SOA formationprocesses and biomass burning,34 showed a weak I/O associationand slightly higher I/O ratios in spring and summer (∼0.20).These results reflect a possible formation of SOA indoors. EC,a key tracer for diesel exhaust,35 displayed a weak I/O correlation(R = 0.20) although it is expected to originate from outdoors giventhe prohibition of smoking inside the refectory. This could berelated to its efficient removal by ventilation, where EC was presentat levels less than 0.05 μg/m3 with low I/O ratios (∼3%). Thesefindings suggest a nominal influence of outdoor diesel emissions onindoor PM levels. Typical crustal metals, for example, Al, calcium(Ca), Ti and iron (Fe), exhibited I/O ratios ranging from 0.03 to0.33 with similar peak occurrence in fall. Although these elementsare expected to originate from outdoors, they were weakly to mod-erately related to their outdoor components (R = 0.17�0.45), whichindicates their dependence on indoor sources, likely particleresuspension during visiting hours. Moreover, in spite of its weakI/O correspondence, potassium (K) was strongly associated withTi and Al (R = 0.98 and 0.62, respectively) at the indoor site,indicating their common outdoor crustal source. Its poor I/Ocorrelation may be attributed to its mixed outdoor origin.Marcazzan et al.36 reported that K is associated with motorvehicles in Milan. Conversely, Nickel (Ni), a marker of fuel oil

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Table 1. Indoor-to-Outdoor (I/O) Seasonal Average (One Standard Deviation) Mass Ratios and Spearman CorrelationCoefficients (R) for key species in PM2.5

average (standard deviation) I/O ratio

winter spring summer fall R(I/O)

mass 0.04(0.03) 0.14(0.10) 0.18(0.06) 0.11(0.07) �0.31

SO42‑ 0.01(0.003) 0.02(0.02) 0.01(0.001) <1% 0.76

NO3� <1% <1% 0.01(0.001) <1% 0.72

NH4+ <1% <1% <1% <1% 0.66

OC 0.11(0.03) 0.38(0.25) 0.61(0.17) 0.25(0.12) �0.13

WIOC 0.11(0.04) 0.51(0.29) 1.07(0.45) 0.30(0.18) �0.64

WSOC 0.11(0.01) 0.20(0.05) 0.22(0.04) 0.15(0.03) �0.10

EC 0.03(0.007) 0.03(0.01) 0.03(0.01) 0.02(0.01) 0.20

Al 0.09(0.02) 0.13(0.07) 0.06(0.03) 0.19(0.03) 0.17

Ca 0.17(0.04) 0.26(0.12) 0.15(0.06) 0.33(0.06) 0.43

Ti 0.18(0.06) 0.27(0.11) 0.21(0.1) 0.31(0.12) 0.45

Fe 0.03(0.01) 0.06(0.03) 0.05(0.02) 0.06(0.01) 0.39

K 0.03(0.02) 0.14(0.09) 0.14(0.05) 0.12(0.07) �0.45

Ni 0.04(0.01) 0.07(0.04) 0.04(0.01) 0.05(0.01) 0.66

Cu 0.04(0.02) 0.06(0.02) 0.05(0.01) 0.04(0.01) 0.31

Zn 0.02(0.02) 0.07(0.03) 0.10(0.05) 0.05(0.02) �0.23

benzo(e)pyrene 0.01(0.01) 0.03(0.03) n.d n.d n.q

benzo(a)pyrene <1% 0.01(0.02) n.d n.d n.q

indeno(l,2,3-cd)pyrene 0.02(0.005) 0.03(0.06) n.d n.d n.q

benzo(ghi)perylene 0.01(0.004) 0.03(0.03) n.d <1% n.q

coronene 0.01(0.003) 0.02(0.03) n.d <1% n.q

picene n.d n.d n.a n.a n.q

17β(H)-21α(H)-30-norhopane 0.14(0.06) 0.23(0.01) 0.69(0.36) 0.13(0.07) 0.61

17α(H)-21β(H)-hopane 0.22(0.14) 0.34(0.04) 0.85(0.7) 0.11(0.06) 0.73

22S-homohopane 0.11(0.05) 0.15(0.02) 0.36(0.22) 0.08(0.03) 0.53

22R-homohopane 0.10(0.05) 0.16(0.05) 0.32(0.11) 0.08(0.03) 0.62

nonacosane 0.13(0.05) 0.17(0.03) 0.24(0.06) 0.14(0.05) 0.38

triacontane 0.20(0.08) 0.38(0.15) 0.76(0.25) 0.28(0.14) 0.30

hentriacontane 0.09(0.04) 0.11(0.04) 0.17(0.05) 0.08(0.02) 0.59

dotriacontane 0.24(0.17) 0.32(0.15) 0.65(0.21) 0.32(0.1) 0.47

tritriacontane 0.20(0.17) 0.14(0.04) 0.23(0.05) 0.18(0.10) 0.69

squalane a 167(71) 62(55) 58(6.4) 76(30)

tetradecanoic acid 3.2(1.0) 5.8(0.62) 12(3.3) 11(5.0) �0.68

pentadecanoic acid 1.1(0.35) 2.3(0.22) 6.1(1.7) 4.4(1.9) �0.88

hexadecanoic acid 0.49(0.14) 1.0(0.11) 2.1(0.83) 0.94(0.52) �0.66

heptadecanoic acid 0.42(0.09) 0.82(0.17) 1.3(0.23) 0.89(0.41) 0.57

octadecanoic acid 0.40(0.10) 0.62(0.08) 1.2(0.42) 0.52(0.22) �0.20

nonadecanoic acid 0.15(0.05) 0.45(0.19) 0.73(0.17) 0.53(0.4) �0.20

palmitoleic acid a 182(58) 315(34) 413(98) 346(55)

oleic acid 2.2(0.8) 11(5.9) 37(17) 6.7(4.7) -0.78

tributyl phosphate 67(9.2) 32(8.5) 9.1(2.5) 37(36) 0.53

phthalic acid 0.04(0.02) 0.13(0.07) 0.07(0.02) 0.05(0.01) 0.71

methylphthalic acid 0.01(0.01) 0.03(0.03) n.d 0.03(0.01) 0.40

suberic acid 0.06(0.06) 0.06(0.11) 0.17(0.02) 0.18(0.02) �0.11

azelaic acid 0.06(0.02) 0.13(0.04) 0.21(0.04) 0.14(0.05) �0.30

2-methylthreitol n.a n.d n.d n.a n.q

2-methylerythritol n.a n.d n.d n.a n.q

2-hydroxy-4-ispropyladipic acid 0.26(0.21) 0.51(0.44) 1.07(0.48) 0.85(0.51) �0.43

pinonic acid n.a n.d n.d n.a n.q

2,3-dihydroxy-4-oxopentanoic acid n.a n.d n.d n.a n.q

levoglucosan 0.12(0.06) 0.09(0.10) 0.03(0.03) <1% 0.66

n.a, non detected indoor and outdoor compound. n.d, non detected indoor compound. n.q, Not quantified due to insufficient number of data points (<6).R in bold is statistically significant at a 0.05 level. a non detected outdoor concentration is replaced by 1/2 detection limit for I/O ratio computation.

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combustion,37,38 strongly correlated with its outdoor compo-nent (R = 0.66), signifying its mostly outdoor origin. Ni alsodisplayed comparable I/O ratios (4�7%), indicating a stablebut rather small outdoor influence on its indoor levels. Anthro-pogenic metals, copper (Cu) and zinc (Zn), displayed I/Oratios ranging from 0.02 to 0.10 and were weakly dependent ontheir outdoor components (R = 0.31 and �0.23, respectively),indicating a potential but small indoor influence such as theiraccumulation in indoor dust.39 This build up may in turn bedetermined by indoor and outdoor emissions.40

Among the listed polycyclic aromatic hydrocarbons (PAHs),picene, a molecular marker for coal soot,41 was not measured inthe indoor samples despite its detection outdoors, implying thatcoal soot is not a source contributor to indoor PM levels. Theremaining PAHs, common products of incomplete combustionincluding fossil fuel and biomass combustion,42 were mostlyundetected indoors, especially in summer, and exhibited extre-mely low infiltration factors (e3%), indicating that their sourcesdo not significantly impact indoor PM levels. Hopanes, which arepredominantly associated with engine lubricating oil of mobilesources,43 fairly correlated with their outdoor levels (R =0.53�0.73), confirming their outdoor origin. Excluding summer,during which high I/O ratios were observed for 17β(H)-21α(H)-30-norhopane and 17α(H)-21β(H)-hopane (0.69�0.85),seasonal infiltration factors ranged from 0.08 to 0.36. Theseratios highlight a year-long influence from vehicular sources onhopanes levels indoors. The peak summertime infiltration ratiomay be a result of measurement uncertainties associated with thelow outdoor hopanes levels (0.02�0.06 ng/m3). To investigatethe origin of indoor n-alkanes (C29�C33), the carbon preferenceindex (CPI), defined as the concentration ratio of their odd-to-even numbered homologues, was estimated. A CPI about 1indicates a dominance of anthropogenic sources, whereas a CPIgreater than 2 indicates a prevalence of biogenic sources.44 Theseindoor compounds did not exhibit a discernible odd-to-evencarbon number preference (CPI = 1.01 ( 0.14 on a yearlyaverage basis), indicating their anthropogenic outdoor source,such as fossil fuel utilization and wood-smoke.45 Nonetheless, thelow I/O correspondence for some of these n-alkanes can berelated to the primarily biogenic nature of their outdoor compo-nents, which exhibited a CPI of 2.53( 0.61. Moreover, n-alkanesdisplayed highest I/O ratios (0.17�0.76) in summer, possiblyrelated to condensation of infiltrating gas-phase n-alkanes ontoindoor particles as a result of I/O temperature differences. Incontrast, squalane existed in higher indoors than outdoor amounts.This undoubtedly suggests that indoor sources significantly con-tribute to its presence indoors. Squalane is a naturally occurringcompound in humans and plants as well as a compound used inskin care products,46,47 suggesting visitors as a possible sourcegiven the absence of plants in the refectory.n-alkanoic acids, C14�C19, were uncorrelated with their out-

door components and displayed relatively high I/O ratios withsome greater than unity, indicating their predominantly indoororigin. Their I/O ratios also demonstrated a seasonal patternwith greatest ratios occurring in summer (0.73�12.4), in accor-dance with those of OC and WIOC. Moreover, these fatty acidsdisplayed a yearly average CPI of 7.55 ( 0.92, indicative of theirbiogenic origin. For n-alkanoic acids, CPI is estimated as theconcentration ratio of their even-to-odd numbered homologues.Potential indoor sources include skin emissions from visitors48

and wax49 emissions from the painting itself. Waxes were usedduring the restoration process of the painting.50 Furthermore,

palmitoleic and oleic acids, normally associated with cooking,51

exhibited I/O ratios much greater than 1, also indicating theirprimarily indoor origin. However, given that cooking is prohib-ited inside the refectory, the most probable source is biogenicmaterial45 potentially emitted from waxes.52,53 Emissions fromskin surface lipids of visitors are also a likely source of oleic acid.48

These fatty acids are ubiquitous indoors and may be sorbed toindoor airborne particles or also settled dust54 that is subse-quently resuspended by human/cleaning activities. Tributylphosphate, a phosphate ester used in plasticizers and flameretardants,55 persistently displayed I/O ratios exceeding unity,thereby indicating its indoor source, most likely wall or ceilingpaint. In contrast, phtalic and methylphtalic acids, which exhib-ited low but non-negligible I/O ratios (e13 and 4%, re-spectively), infiltrated from outdoors (R = 0.71 and 0.40,respectively) with emissions frommobile sources and associationwith SOA formation45 as possible sources. The I/O ratios ofsuberic and azelaic acids, which are photo-oxidation products ofbiogenic unsaturated fatty acids,56 suggest the presence of SOAindoors. Nonetheless, the indoor levels of SOA are probably low,as WSOM only constitutes ∼20% of OM, as aforementioned.Tracers for biogenic-derived SOA include photo-oxidation

products of α-pinene and isoprene. These comprise pinonicacid, 2-hydroxy-4-isopropyladipic acid, 2-methylthreitol, and2-methylerythritol.22 Conversely, tracers for anthropogenic-derived SOA include 2,3-dihydroxy-4-oxopentanoic acid,photo-oxidation product of toluene.22 Among these SOAtracers, only 2-hydroxy-4-isopropyladipic acid, derivative ofα-pinene, was detected indoors with peak I/O ratio about unity(1.07 ( 0.48) in summer. This secondary compound alsopresented a poor I/O correlation (R = �0.43) suggesting itsindoor formation. A likely pathway is gas-phase reactionsinvolving α-pinene constituents and oxidants. The higher sum-mertime I/O ratio reflects an enhanced production of SOA,possibly promoted by an increase in infiltrating oxidants.Lastly, the low I/O ratio and high I/O correlation for

levoglucosan (R = 0.66), a tracer for biomass burning,57 indicatesits low but non-negligible indoor intrusion, mainly in winter(12%).In summary, these findings show that key tracers of major

outdoor sources generally have small infiltration factors. Addi-tionally, it is particularly interesting that fatty acids weremainly ofindoor origin with palmitoleic and oleic acids exhibiting I/Oratios >1.3.2. CMB Results. 3.2.1. Source Apportionment of Fine OC.

The monthly contributions of primary and secondary sources toindoor fine OC as estimated by the CMB model are shown inFigure 2a and summarized in SI Table S3a. Three sources,including wood-smoke, gasoline vehicles, and urban soil wereidentified. Contributions to OC from biogenic-derived SOA werenot statistically significant (<2 � standard error) with an utmostvalue of 0.015 μg/m3. Similarly, diesel emissions were notstatistically significantly different from zero. The three sourcescollectively contributed to 6.3�20.7% of measured fine OC,with the remainder representing unidentified sources, likelyincluding biogenic SOA. The largest contributor to OC massconsisted of gasoline vehicles, which accounted for 4.9�16.7%of OC. The largest percent contributions and source estimatesoccurred in cold months (December�March) with highestaverage ((standard error) levels of 0.23 ( 0.024 μg/m3

attained in February. The next most contributing source waswood-smoke during winter, while urban soil during the

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remaining seasons. Wood-smoke contribution was only statis-tically significant during December�April and peaked in Feb-ruary to reach 0.039 ( 0.015 μg/m3 (i.e., 2.8% of OC mass).This seasonal pattern suggests wood burning for domesticheating during cold months. On the other hand, urban soillacked any discernible seasonal trend and contributed to 1.14(0.46% (0.018 ( 0.007 μg/m3) of OC mass on a yearly basedaverage ((standard deviation).Lastly, unidentified source contributions, denoted as “other

OC”, were estimated as the difference between measured OCand the contributions from the modeled sources. The percent ofresidual mass was higher during July�October and could beattributed to uncharacterized primary and SOA sources.3.2.2. Source Apportionment of Total PM2.5. Source contribu-

tions to total PM2.5 were assessed by converting CMB results forfine OC to PM2.5 apportionment using reported fine OC-to-PMmass ratios for each source.19�23 In addition to the sourcesidentified in OC apportionment, “other OM” as well as sulfate,nitrate, and ammonium ion concentrations were considered inPM2.5 apportionment as displayed in Figure 2b and SI Table S3b.“OtherOM”was estimated bymultiplying “otherOC” by a factorof 1.7.26�28 These sources collectively accounted for 96.2 (18.7% of the measured PM2.5 mass, on a yearly based average((standard deviation). Some of the inconsistency in apportion-ment could be due to uncertainties associated with the conver-sion factor from OC to OM and geographical differences of thesources compositions. Finally, the most significant contributionswere from “other OM” (80.5 ( 17.4%), followed by urban soil(6.9 ( 1.7%), gasoline vehicles (6.5 ( 2.8%), wood-smoke(1.2 ( 0.51%), then sulfate, nitrate and ammonium ions withcontributions less than 1%.3.3. Comparison of OC to Organic Acid Species in PM2.5.

To elucidate the nature of uncharacterized OC, WSOC con-tribution to unapportioned OC was estimated as WSOC thatis not associated with wood-smoke emissions. This calculationestimates wood-smoke contribution to OC as 71%water-soluble.58

Accordingly, unapportioned WIOC was determined as thedifference between total WIOC and the sum of all primarysource estimates (excluding wood-smoke) and WIOC fromwood-smoke. These estimates are reported in SI Table S3a.As can be deduced, unattributed OC is largely water-insoluble(77.9( 3.2%), which indicates that uncharacterized OC sourcesare mostly primary. Given that major outdoor sources of OChave been included in the CMBmodel, and considering their lowinfiltration factors and contribution estimates, unknown primarysources are likely dominated by indoor sources such as dustof biogenic origin, or PM emissions from the visitors and thepainting itself.The relative importance of fine OM to indoor PM and the

likelihood of its predominantly indoor source warrant furtherinvestigation of this aerosol component. Accordingly, monthlyvariations of indoor fine WSOC, WIOC, fatty acids with I/Oratio >1 and CPI of n-alkanoic acids are examined as illustrated inFigure 3(a�d).WSOC, attributed to SOA formation processes and biomass

burning,34 mainly originated from indoors as previously noted. Infact, the contribution to WSOC from wood-smoke source wasonly significant in winter and early spring when it averaged((standard deviation) 0.02 ( 0.006 μg/m3. Total WSOC, onthe other hand, maintained a stable average concentration of0.31( 0.02 μg/m3 throughout the year, which further confirms acontinual and prevalent contribution to WSOC from indoorSOA formation processes. This contribution to overall OC washowever minor, as WSOC only comprised 20 ( 3% of indoorOC across the year.WIOC, on the other hand, was a major component of indoor

fine OC, accounting for 80 ( 3% of its mass on a yearly averagebasis. It also follows closely unapportioned OC, which could notbe assigned to outdoor sources, supporting the likelihood thatOC is mostly insoluble of indoor primary origin. Furthermore,WIOC was present at a yearly average concentration of 1.25 (0.25 μg/m3, with higher levels observed during May�October

Figure 2. Sources contribution to indoor (a) fine organic carbon (OC) and (b) PM2.5 estimated using the chemical mass balance (CMB) model.

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and peak occurrence of 1.82 μg/m3 in July. These variationsimply an increase in the source strength of indoor primaryemissions during these months.To characterize potential indoor sources of OC, the monthly

trend of palmitoleic and oleic acids, which were present ingreater indoors than outdoor amounts, was investigated. Thesecomponents exhibited a temporal distribution fairly similar tothat of WIOC and unapportioned OC, reaching a collectivepeak of 41.9 ng/m3 in July and low of 14.4 ng/m3 in January.Particularly, palmitoleic and oleic acids, biogenic componentssorbed to indoor airborne PM or dust as aforementioned, weresignificantly and well correlated to WIOC (R = 0.75 and 0.76,respectively). Thus, this temporal correlation suggests theircommon source with biogenic material associated with indoor

dust, waxes used in the painting and human skin emissions aspotential sources.Indoor n-alkanoic acids, C14�C29, exhibited a year-long

strong even carbon preference, with an annual average CPI of6.62 ( 0.55 and limited monthly variation. Carbon numbermaxima occurred at C16 and C14 (SI Table S4), which arecommonly found indoors59 and associated with human skinsurface lipids.48 These findings are indicative of the consistentbiogenic source of these n-fatty acids such as waxes used inpainting the “Last Supper” and skin emissions, as aforemen-tioned. Moreover, these components highly correlate withWIOC (R = 0.73), a dominant component of OC, suggestingtheir shared origin with indoor dust of biogenic nature, emis-sions from the painting or human skin as likely sources.

Figure 3. Monthly time series of (a) water-soluble organic carbon (WSOC), (b) water-insoluble organic carbon (WIOC) and un-apportioned organiccarbon (OC), (c) palmitoleic and oleic acids, (d) carbon preference index of n-alkanoic acids (C14�C29), in fine PM in the indoor environment.

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Overall, the results of this study showed that outdoor sourceshave small infiltration factors and contribution to PM2.5. OM,which could not be apportioned to any major outdoor sources,accounted for most of PM2.5 (80.5 ( 17.4%), and was largelywater-insoluble (77.9 ( 3.2%) with indoor dust of biogenicorigin as a potential source. Consequently, it can be concludedthat controls to prevent infiltration of outdoor PM into therefectory, where the “Last Supper” painting is housed, are veryeffective. However, additional measures targeting the reductionof fine OM should be implemented. Particularly, these controlsshould address indoor sources of biological material that is likelyassociated with indoor dust. Lastly, we should note that findingsof this study are characteristic of the specific site location, climaticconditions inside the refectory, visitors’ pattern and specifica-tions of the HVAC system. These results, therefore, cannot bedirectly extrapolated to other exhibits.

’ASSOCIATED CONTENT

bS Supporting Information. Figures S1�S3 and TablesS1�S4. This material is available free of charge via the Internetat http://pubs.acs.org.

’AUTHOR INFORMATION

Corresponding Author*E-mail: sioutas@usc.edu.

’ACKNOWLEDGMENT

This research was supported by Southern California ParticleCenter, funded by US EPA and the University of SouthernCalifornia (USC) Viterbi School of Engineering. We wouldlike to thank the superintendent of fine arts and culture inLombardy for his willingness to accept this study. We also wishto acknowledge the support of USC Provost’s Ph.D. fellowship.We thank Jeff DeMinter, Brandon Shelton and the staff at theWisconsin State Laboratory of Hygiene for their assistance withthe chemical measurements. We also wish to thank SIMG-ItalianCollege GPs and ISDE-International Doctors for the Environ-ment for managerial support, Eng. Franco Gasparini, designer ofthe HVAC system for technical help, and the whole managementand employees of the Sovrintendenza, particularly Arch. A.Artioli, Arch. G. Stolfi, Arch. Napoleone, Mr. G. Bonnet andDr. L. Dall’Aglio

’REFERENCES

(1) Camuffo, D.; VanGrieken, R.; Busse, H.-J.; Sturaro, G.; Valentino,A.; Bernardi, A.; Blades, N.; Shooter, D.; Gysels, K.; Deutsch, F.; Wieser,M.; Kim, O.; Ulrych, U. Environmental monitoring in four Europeanmuseums. Atmos. Environ. 2001, 35 (Supplement 1), S127–S140.(2) Brimblecombe, P. The composition of museum atmospheres.

Atmos. Environ., Part B 1990, 24 (1), 1–8.(3) Nazaroff, W. W.; Cass, G. R. Protecting museum collections

from soiling due to the deposition of airborne particles. Atmos. Environ.,Part A 1991, 25 (5�6), 841–852.(4) Alexandra, S.; Tunga, S.; Watts, S. F., Indoor pollutants in the

museum environment. In Organic Indoor Air Pollutants, 2nd ed.;Salthammer, T., Uhde, E., Eds.;Wiley-VCHVerlag GmbH&Co. KGaA:Weinheim, 2009; p 281.(5) Meng, Q. Y.; Turpin, B. J.; Korn, L.; Weisel, C. P.; Morandi, M.;

Colome, S.; Zhang, J. J.; Stock, T.; Spektor, D.;Winer, A.; Zhang, L.; Lee,J. H.; Giovanetti, R.; Cui, W.; Kwon, J.; Alimokhtari, S.; Shendell, D.;

Jones, J.; Farrar, C.; Maberti, S. Influence of ambient (outdoor) sourceson residential indoor and personal PM2.5 concentrations: Analyses ofRIOPA data. J. Exposure Anal. Environ. Epidemiol. 2005, 15 (1), 17–28.

(6) Wallace, L. Indoor particles: A review. J. Air Waste Manage. Assoc.1996, 46 (2), 98–126.

(7) Salmon, L. G.; Nazaroff, W. W.; Ligocki, M. P.; Jones, M. C.;Cass, G. R. Nitric acid concentrations in southern California museums.Environ. Sci. Technol. 1990, 24 (7), 1004–1013.

(8) Nazaroff, W. W. Indoor particle dynamics. Indoor Air 2004, 14(Suppl 7), 175–183.

(9) Putaud, J.-P.; Raes, F.; Van Dingenen, R.; Br€uggemann, E.;Facchini, M. C.; Decesari, S.; Fuzzi, S.; Gehrig, R.; H€uglin, C.; Laj, P.;Lorbeer, G.; Maenhaut, W.; Mihalopoulos, N.; M€uller, K.; Querol, X.;Rodriguez, S.; Schneider, J.; Spindler, G.; Brink, H. t.; Tørseth, K.;Wiedensohler, A. A European aerosol phenomenology—2: Chemicalcharacteristics of particulate matter at kerbside, urban, rural and back-ground sites in Europe. Atmos. Environ. 2004, 38 (16), 2579–2595.

(10) Lonati, G.; Giugliano, M.; Butelli, P.; Romele, L.; Tardivo, R.Major chemical components of PM2.5 in Milan (Italy). Atmos. Environ.2005, 39 (10), 1925–1934.

(11) Misra, C.; Singh, M.; Shen, S.; Sioutas, C.; Hall, P. M. Devel-opment and evaluation of a personal cascade impactor sampler (PCIS).J. Aerosol Sci. 2002, 33 (7), 1027–1047.

(12) Camuffo, D.; Bernardi, A. The Microclimate of Leonardo’s“Last Supper. Joint Edition European Cultural Heritage Newsletter onResearch and Bollettino Geofisico, Special Issue 1991, 14 (3), 1–123.

(13) Nazaroff, W. W.; Cass, G. R. Mass-transport aspects of pollu-tant removal at indoor surfaces. Environ. Int. 1989, 15 (1�6), 567–584.

(14) Birch, M. E.; Cary, R. A. Elemental carbon-based method foroccupational monitoring of particulate diesel exhaust: Methodology andexposure issues. The Analyst 1996, 121 (9), 1183–1190.

(15) Stone, E. A.; Hedman, C. J.; Sheesley, R. J.; Shafer, M. M.;Schauer, J. J. Investigating the chemical nature of humic-like substances(HULIS) in North American atmospheric aerosols by liquid chroma-tography tandem mass spectrometry. Atmos. Environ. 2009, 43 (27),4205–4213.

(16) Zhang, Y.; Schauer, J. J.; Shafer, M. M.; Hannigan, M. P.;Dutton, S. J. Source apportionment of in vitro reactive oxygen speciesbioassay activity from atmospheric particulate matter. Environ. Sci.Technol. 2008, 42 (19), 7502–7509.

(17) Watson, J. G. Overview of receptor model principles. Air Pollut.Control Assoc. 1984, 34 (6), 619.

(18) Schauer, J. J.; Rogge, W. F.; Hildemann, L. M.; Mazurek, M. A.;Cass, G. R.; Simoneit, B. R. T. Source apportionment of airborneparticulate matter using organic compounds as tracers. Atmos. Environ.1996, 30 (22), 3837–3855.

(19) Fine, P. M.; Cass, G. R.; Simoneit, B. R. T. Chemical char-acterization of fine particle emissions from the fireplace combustion ofwood types grown in the Midwestern and Western United States.Environ. Eng. Sci. 2004, 21 (3), 387–409.

(20) Sheesley, R. J.; Schauer, J. J.; Zheng, M.; Wang, B. Sensitivity ofmolecular marker-based CMB models to biomass burning sourceprofiles. Atmos. Environ. 2007, 41 (39), 9050–9063.

(21) Lough, G. C.; Christensen, C. G.; Schauer, J. J.; Tortorelli, J.;Mani, E.; Lawson, D. R.; Clark, N. N.; Gabele, P. A. Development ofmolecular marker source profiles for emissions from on-road gasoline anddiesel vehicle fleets. J. Air Waste Manage. Assoc. 2007, 57 (10), 1190–1199.

(22) Kleindienst, T. E.; Jaoui, M.; Lewandowski, M.; Offenberg,J. H.; Lewis, C. W.; Bhave, P. V.; Edney, E. O. Estimates of thecontributions of biogenic and anthropogenic hydrocarbons to secondaryorganic aerosol at a southeastern US location. Atmos. Environ. 2007, 41(37), 8288–8300.

(23) Rutter, A. P.; Snyder, D. C.; Schauer, J. J.; Sheesley, R. J.; Olson,M. R.; DeMinter, J. Contributions of resuspended soil and road dust toorganic carbon in fine particulate matter in the Midwestern US. Atmos.Environ. 2011, 45 (2), 514–518.

(24) American Society of Heating Refrigeration and Air ConditioningEngineers (ASHRAE).Museums, galleries, archives, and libraries. InHeating,

J dx.doi.org/10.1021/es202736a |Environ. Sci. Technol. XXXX, XXX, 000–000

Environmental Science & Technology ARTICLE

Ventilating, and Air-Conditioning Applications; ASHRAE: Atlanta, 2011;Chapter 23.(25) T�etreault, J., Airborne Polluants in Museums, Galleries and

Archives: Risk Assessment, Control Strategies and Preservation Manage-ment; Canadian Conservation Institute: Ottawa, 2003.(26) Turpin, B. J.; Lim, H. J. Species Contributions to PM2.5 Mass

Concentrations: Revisiting Common Assumptions for Estimating Or-ganic Mass. Aerosol Sci. Technol. 2001, 35, 602–610.(27) Russell, L. M. Aerosol Organic-Mass-to-Organic-Carbon Ratio

Measurements. Environ. Sci. Technol. 2003, 37 (13), 2982–2987.(28) Sheesley, R. J.; Schauer, J. J.; Bean, E.; Kenski, D. Trends in

secondary organic aerosol at a remote site inMichigan’s upper peninsula.Environ. Sci. Technol. 2004, 38 (24), 6491–6500.(29) Jones, N. Indoor/outdoor relationships of particulate matter in

domestic homes with roadside, urban and rural locations.Atmos. Environ.2000, 34 (16), 2603–2612.(30) Sarnat, J. A.; Long, C. M.; Koutrakis, P.; Coull, B. A.; Schwartz,

J.; Suh, H. H. Using sulfur as a tracer of outdoor fine particulate matter.Environ. Sci. Technol. 2002, 36 (24), 5305–5314.(31) Na, K.; Cockeriii, D. Organic and elemental carbon concentra-

tions in fine particulate matter in residences, schoolrooms, and outdoorair in Mira Loma, California. Atmos. Environ. 2005, 39 (18), 3325–3333.(32) Thatcher, T. L.; Layton, D. W. Deposition, resuspension, and

penetration of particles within a residence. Atmos. Environ. 1995, 29 (13),1487–1497.(33) Abt, E.; Suh, H. H.; Catalano, P.; Koutrakis, P. Relative

contribution of outdoor and indoor particle sources to indoor concen-trations. Environ. Sci. Technol. 2000, 34 (17), 3579–3587.(34) Weber, R. J.; Sullivan, A. P.; Peltier, R. E.; Russell, A.; Yan, B.;

Zheng, M.; Gouw, J. d.; Warneke, C.; Brock, C.; Holloway, J. S.; Atlas,E. L.; Edgerton, E. A study of secondary organic aerosol formation in theanthropogenic-influenced southeastern United States. J. Geophys. Res.2007, 112, 13 PP–13 PP.(35) Schauer, J. J. Evaluation of elemental carbon as a marker for

diesel particulate matter. J. Expo Anal Environ. Epidemiol. 2003, 13 (6),443–453.(36) Marcazzan, G. M.; Vaccaro, S.; Valli, G.; Vecchi, R. Character-

isation of PM10 and PM2.5 particulate matter in the ambient air of Milan(Italy). Atmos. Environ. 2001, 35 (27), 4639–4650.(37) Cass, G. R.; McRae, G. J. Source-receptor reconciliation of

routine air monitoring data for trace metals: An emission inventoryassisted approach. Environ. Sci. Technol. 1983, 17 (3), 129–139.(38) Singh,M.; Jaques, P. A.; Sioutas, C. Size distribution and diurnal

characteristics of particle-bound metals in source and receptor sites ofthe Los Angeles Basin. Atmos. Environ. 2002, 36 (10), 1675–1689.(39) Kim, N.; Fergusson, J. Concentrations and sources of cadmium,

copper, lead and zinc in house dust in Christchurch, New Zealand. Sci.The Total Environ. 1993, 138 (1�3), 1–21.(40) Butte, W., Reference values of environmental pollutants in house

dust . In Indoor Environment: Airborne Particles and Settled Dust; Mor-awska, L., Salthammer, T., Eds.; Wiley-VCH: Weinheim: 2003; p 416.(41) Oros, D. R.; Simoneit, B. R. T. Identification and emission rates

of molecular tracers in coal smoke particulate matter. Fuel 2000, 79 (5),515–536.(42) Manchester-Neesvig, J. B.; Schauer, J. J.; Cass, G. R., The

distribution of particle-phase organic compounds in the atmosphere andtheir use for source apportionment during the Southern CaliforniaChildren’s Health Study. (Technical Paper). J. Air Waste Manage. Assoc.2003, pp 1065(15)-1065(15).(43) Schauer, J. J.; Fraser, M. P.; Cass, G. R.; Simoneit, B. R. T.

Source reconciliation of atmospheric gas-phase and particle-phasepollutants during a severe photochemical smog episode. Environ. Sci.Technol. 2002, 36 (17), 3806–3814.(44) Simoneit, B. Characterization of organic constituents in aero-

sols in relation to their origin and transport: A review. Int. J. Environ.Anal. Chem. 1986, 23 (3), 207–237.(45) Rogge, W. F.; Mazurek, M. A.; Hildemann, L. M.; Cass, G. R.;

Simoneit, B. R. T. Quantification of urban organic aerosols at a

molecular level: Identification, abundance and seasonal variation. Atmos.Environ.,Part A 1993, 27 (8), 1309–1330.

(46) Parente, M. E.; G�ambaro, A.; Solana, G. Study of sensoryproperties of emollients used in cosmetics and their correlation withphysicochemical properties. J.Cosmet.Sci. 2005, 56 (3), 175–182.

(47) Kato, S.; Aoshima, H.; Saitoh, Y.; Miwa, N. Biological safety ofLipoFullerene composed of squalane and fullerene-C60 upon mutagen-esis, photocytotoxicity, and permeability into the human skin tissue.Basic Clinical Pharmacol.Toxicol. 2009, 104 (6), 483–487.

(48) Nicolaides, N. Skin lipids: Their biochemical uniqueness.Science 1974, 186 (4158), 19–26.

(49) Naik, D. V.; Weschler, C. J.; Shields, H. C., Indoor and outdoorconcentrations of organic compounds associated with airborne particles:Results using a novel solvent system. In Indoor Air Pollution: Radon,Bioaerosols & VOCs; Kay, J. G., Keller, G. E., Miller, J. F., Eds.; LewisPublishers: MI, 1991; p 67.

(50) Mannucci, E.; Zerbi, G., Art and spectroscopy: Looking topaints and parchments. InGNSR 2001: State of Art and Future Developmentin Raman Spectroscopy and Related Techniques; Messina, G.,Santangelo, S.,Eds.; IOS press: Amsterdam, 2002.

(51) Robinson, A. L.; Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F. Source apportionment of molecular markersand organic aerosol. 3. Food cooking emissions. Environ. Sci. Technol.2006, 40 (24), 7820–7827.

(52) Nazaroff, W. W.; Weschler, C. J. Cleaning products and airfresheners: Exposure to primary and secondary air pollutants. Atmos.Environ. 2004, 38 (18), 2841–2865.

(53) Kirk-Othmer, Encyclopedia of Chemical Technology, 4th ed.;Wiley: New York, 1998.

(54) Ayoko, G. A.; Uhde, E., Organic compounds adsorbed onparticles and settled house dust. In Indoor Environment: Airborne Particlesand Settled Dust; Morawska, L., Salthammer, T., Eds.; Wiley-VCH:Weinheim: 2003; p 150.

(55) Otake, T.; Yoshinaga, J.; Yanagisawa, Y. Exposure to phthalateesters from indoor environment. J. Exposure Anal. Environ. Epidemiol.2004, 14, 524–528.

(56) Kawamura, K.; Kasukabe, H.; Barrie, L. A. Source and reactionpathways of dicarboxylic acids, ketoacids and dicarbonyls in arcticaerosols: One year of observations. Atmos. Environ. 1996, 30 (10�11),1709–1722.

(57) Simoneit, B. R. T.; Schauer, J. J.; Nolte, C. G.; Oros, D. R.; Elias,V. O.; Fraser, M. P.; Rogge, W. F.; Cass, G. R. Levoglucosan, a tracer forcellulose in biomass burning and atmospheric particles. Atmos. Environ.1999, 33 (2), 173–182.

(58) Sannigrahi, P.; Sullivan, A. P.; Weber, R. J.; Ingall, E. D.Characterization of water-soluble organic carbon in urban atmosphericaerosols using solid-state 13C NMR spectroscopy. Environ. Sci. Technol.2006, 40 (3), 666–672.

(59) Ayoko, G. A.; Uhde, E., Organic compounds adsorbed onparticles and settled house dust. In Indoor Environment: Airborne Particlesand Settled Dust; Morawska, L., Salthammer, T., Eds.; Wiley-VCH:Weinheim, 2003; p 159.