1. A one-year sampling campaign was conducted to characterize particulate matter (PM) inside the refectory of Santa Maria Delle Grazie Church in Milan, home to Leonardo Da Vinci's famous painting "The Last Supper". 2. Fine (PM2.5) and coarse (PM2.5-10) particulate matter samples were simultaneously collected indoors and outdoors on a weekly basis. Indoor PM2.5 and PM2.5-10 concentrations were reduced by 88% and 94%, respectively, compared to outdoor levels, due to the refectory's ventilation system. 3. Organic matter dominated indoor PM2.5 levels. Source apportionment modeling found that

1. ARTICLE
pubs.acs.org/est
Chemical Characterization and Source Apportionment of Fine and
Coarse Particulate Matter Inside the Refectory of Santa Maria Delle
Grazie 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
b Supporting Information
S
ABSTRACT: The association between exposure to indoor
particulate matter (PM) and damage to cultural assets has been
of primary relevance to museum conservators. PM-induced
damage to the “Last Supper” painting, one of Leonardo da Vinci’s
most famous artworks, has been a major concern, given the
location of this masterpiece inside a refectory in the city center of
Milan, one of Europe’s most polluted cities. To assess this risk, a
one-year sampling campaign was conducted at indoor and out-
door sites of the painting’s location, where time-integrated fine
and coarse PM (PM2.5 and PM2.5À10) samples were simulta-
neously collected. Findings showed that PM2.5 and PM2.5À10
concentrations were reduced indoors by 88 and 94% on a yearly
average 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 and
secondary sources to monthly indoor fine organic carbon (OC) and PM mass. Results revealed that gasoline vehicles, urban soil, and
wood-smoke only contributed to an annual average of 11.2 ( 3.7% of OC mass. Tracers for these major sources had minimal
infiltration factors. On the other hand, fatty acids and squalane had high indoor-to-outdoor concentration ratios with fatty acids
showing a good correlation with indoor OC, implying a common indoor source.
1. INTRODUCTION outdoor sources.7,8 An accurate characterization of airborne
Damage to cultural assets has been of growing interest to PM in museums is therefore essential for conserving the ex-
museum conservators and curators. There is mounting evidence hibited artifacts.
correlating indoor air pollution, biological contamination, mass An emerging concern is with PM-induced damage to the
tourism, and variability in microclimate conditions with material “Last Supper” painting, one of Leonardo da Vinci’s most
deterioration.1,2 A major concern is damage by particulate mat- famous artworks, located in the refectory of Santa Maria delle
ter (PM) to masterworks of art displayed in museums. Poten- Grazie Church in Milan, Italy. Although this painting has
tial hazards include “soiling” (perceptible degradation of visual survived many challenges, including bombing during World
qualities) due to deposition of airborne particles, particularly War II, it is yet facing another challenge. The “Last Supper”
elemental carbon, and soil dust.3 Further damage can be induced painting, which was majorly restored in the 20th century, is at
by chemically reactive species, such as ammonium sulfate and risk with air pollution arising from its surrounding Milan area.
organic acids.2,4 Milan is one of the most polluted areas in Western Europe9 with
Typically, indoor PM consists of outdoor-infiltrating and PM10 air quality standards frequently exceeded.10 In an attempt
indoor-emitted particles in addition to indoor-formed particles to protect the painting, a sophisticated heating, ventilation, and
through reactions of gas-phase precursors emitted both indoors
and outdoors.5,6 Moreover, the level and composition of indoor Received: August 5, 2011
PM are governed by a myriad of factors. These mainly consist of Accepted: November 9, 2011
the ventilation system, filtration effect of the building envelope, Revised: October 31, 2011
deposition rate of particles as well as the intensity of indoor and
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2. Environmental Science & Technology ARTICLE
air conditioning (HVAC) system equipped with particle filtra- to maintain constant conditions. Large variations in the thermo-
tion has been installed. hygrometric factors in the refectory, enhanced by the presence of
To assess the effectiveness of this control measure, we con- visitors, may lead to an increase in the deposition rate of
ducted a one-year sampling campaign at indoor and outdoor airborne pollutants on the painting, as previously demonstrated
sites of the refectory. At both locations, fine and coarse PM by Camuffo and Bernardi.12 The temperature of the backside
(PM2.5 and PM2.5À10, respectively) samples were simultaneously room is also maintained at about 2 °C higher than the refectory’s
collected then analyzed for their chemical properties. In the temperature to avoid PM deposition on the painting due to
present article, the indoor-to-outdoor relationship of key tracers thermophoresis effects.3,13 Finally, it should be noted that the
of PM sources is investigated in order to evaluate the impact of HVAC system failed for few days during one week of April.
indoor and outdoor sources on indoor particle levels. Further- PM concentration substantially increased during that week,
more, the chemical mass balance model is applied to identify and compared to the remaining weeks with noninterrupted system
estimate sources contributions to indoor PM2.5 concentration. functioning. This effect was more noticeable for PM2.5À10, for
Results of this study provide a quantitative understanding on which a nearly 9-fold increase was observed, as shown in SI
the composition, origin and level of PM inside the refectory. Figure S3. This occurrence, however, has minor impacts on the
Ultimately, these findings can be used as guidelines for the results where monthly averages are reported throughout
implementation of additional, and particularly source-specific, this study.
control strategies to mitigate the concentration of particle 2.2. Chemical Analyses. To conduct the chemical analyses,
components potentially detrimental to the “Last Supper” paint- the Teflon and quartz filters were sectioned into portions. The
ing. They can also be used as a benchmark in future studies aimed fractions used for elemental and organic carbon (EC and OC,
at protecting indoor artworks and antiquities. respectively) quantification were grouped into weekly samples
and quantified using the NIOSH thermal optical transmission
2. MATERIALS AND METHODS method.14 All remaining fractions, with the exception of few
PM2.5À10 sections, were composited monthly. Given their low
2.1. Sampling Description. To characterize PM inside the mass loading, February/March, April/May, and October/No-
refectory, PM2.5 and PM2.5À10 were simultaneously sampled at vember coarse samples were composited bimonthly. These
indoor and outdoor sites of the refectory. The sampling cam- monthly and bimonthly fractions were analyzed for water-soluble
paign lasted from December 2009 to November 2010. During OC (WSOC) and ions using a Sievers 900 Total Organic Carbon
this period, 24-hour size-segregated PM samples were collected Analyzer15 and ion chromatography, respectively. Total elemental
on a weekly basis by means of two sets of Sioutas personal content of these composites was also measured using high
cascade impactor samplers (Sioutas PCIS, SKC Inc., Eighty Four, resolution magnetic sector inductively coupled plasma mass
PA11). Every set consisted of two collocated PCIS loaded with spectrometry (Thermo-Finnigan Element 2).16 Additionally,
37 and 25 mm filters for fine and coarse PM analyses, respectively. organic speciation was conducted on PM2.5 filter sections using
Each of the PCIS was placed at the indoor or outdoor site and gas chromatography mass spectrometry (GC-6980, quadrupole
operated at a flow rate of 9 lpm. For the purpose of chemical MS-5973, Agilent Technologies). PM2.5À10 lacked sufficient
analysis, one set of the PCIS was loaded with Teflon filters (Pall mass for this analysis. Details of these analyses are provided in
Life Sciences, Ann Arbor, MI), whereas the other one was loaded the SI.
with quartz microfiber filters (Whatman International Ltd., 2.3. Source Apportionment. A molecular marker chemical
Maidstone, England). PM mass concentration was determined mass balance model (MM-CMB) that was mathematically solved
from the mass loadings of the weekly Teflon filters as described in with the U.S. Environmental Protection Agency CMB (EPA-
the Supporting Information (SI). CMB8.2) software was used to estimate primary and secondary
The indoor sampling location was inside the refectory of Santa source contributions to indoor fine OC on a monthly basis. The
Maria delle Grazie Church, where da Vinci painted the “Last effective variance weighted least-squares algorithm was applied
Supper” on one of its walls. Samples were collected at approxi- to apportion the receptor data to the source profiles.17
mately 1 m directly below the painting and a few centimeters MM-CMB was conducted using primary molecular source
from the wall surface. The site is equipped with a newly deployed tracers that were quantified in the PM2.5 samples. Markers that
HVAC system, supplying 4000 m3/h total air flow, of which are chemically stable and secondary organic aerosol (SOA)
2000 m3/h are external fresh air. This system is operated continu- tracers that are unique to their precursor gases were selected as
ously. The air-flow rate inside the refectory, whose volume is 3130 m3, fitting species.18 These included levoglucosan, αββ-20R&SÀ
is 3000 m3/h, resulting in an air exchange rate of roughly 1 hÀ1. C27-cholestane, αββ-20R&S-C29-sitostane, 17α(H)-22,29,30-
This relatively low air change rate helps avoid convective air trisnorhopane, 17α(H)-21β(H)-hopane, 17β(H)-21α(H)-30-
velocities on the painting to the degree possible. The remaining norhopane, benzo(b)fluoranthene, benzo(k)fluoranthene, indeno-
air flow rate goes into two 130 m3 isolating zones, located at the [c,d]pyrene, benzo(ghi)perylene, EC, aluminum (Al), and
entrance and exit of the refectory, through which visitors pass for titanium (Ti).
isolation and decontamination from outdoor pollution. Further- The input source profiles were based on the observed molec-
more, the air is filtered with plane, pocket and absolute filters as ular markers and assumed representative of sources in Milan.
well as chemical filters (Purafil, Inc.); more details about these These profiles included wood-smoke,19,20 urban soil, gasoline
filters as well as the design and operation of the HVAC system vehicles,21 and diesel emissions.21 Biogenic-derived SOA was not
can be found in the SI. The number of visitors and duration of included in the model but its contribution was estimated using
visit are limited to 25 persons and 15 min at any time between fixed tracer-to-OC ratios.22 Moreover, the selected urban soil
8:15 a.m. and 6:45 p.m. Visits are allowed each day, except for profile is not specific to Milan. However, the choice of this profile
Monday, with number of visitors averaging 1000 visitors/day. is not critical for the overall apportionment of fine OC as its
The temperature and relative humidity are automatically controlled contribution to total OC mass is small23. Its selection was
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3. Environmental Science & Technology ARTICLE
Figure 1. Monthly average indoor concentration (compared to outdoor concentration) and bulk composition for (a, c) PM2.5 and (b, d) PM2.5À10.
Error bars represent one standard error.
nonetheless based on a comparison of the elemental ratios of the 3. RESULTS AND DISCUSSION
measured data to those of available soil profiles, where the urban
soil profile of St. Louis (Missouri)23 provided a best fit. In contrast, 3.1. IndoorÀOutdoor Relationship. 3.1.1. Particulate Mass
natural gas, coal soot and toluene-derived (anthropogenic) SOA and Composition. Indoor and outdoor monthly average PM2.5
sources were not considered in the model, as their molecular and PM2.5À10 mass concentrations are shown in Figure 1(a, b).
markers were not detected in the samples. Furthermore, contribu- Indoor concentrations were substantially lower than those out-
tions from vegetative detritus were not apportioned because doors for both particle modes. This significant reduction in PM2.5
n-alkanes (C29ÀC33) did not exhibit an odd-carbon preference and PM2.5À10 concentration (88 ( 7% and 94 ( 3% on a yearly
indicative of modern plant material. Lastly, the CMB model average ((standard deviation) basis, respectively) can be largely
results were considered valid if they met specific acceptance attributed to the efficacy of the HVAC system in removing
criteria as outlined in the SI. infiltrating outdoor PM. Moreover, coarse PM exhibited
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4. Environmental Science & Technology ARTICLE
extremely low indoor levels ranging between 0.12 and 0.83 μg/m3 (MarchÀMay), summer (JuneÀAugust), and fall (SeptemberÀ
with no specific seasonal trend. PM2.5 was the dominant indoor November). Data for PM2.5À10, a minor component of indoor
PM component with a concentration range of 1.7À4.9 μg/m3. It PM, is reported in SI Table S2. In consistence with its extremely
also followed a pattern dissimilar to that of its outdoor compo- low indoor mass, coarse PM exhibited small I/O ratios (e8%).
nent, indicating that indoor sources may have major contribu- For a given species, the combination of the I/O ratio and
tions to fine PM indoors. Finally, it is noteworthy that currently correlation provides an estimate of its I/O source relationship. The
there are no regulations for PM levels in museums, galleries, and latter can be described by the following categories. First, a low I/O
archives. However, the American Society of Heating, Refrigerat- ratio accompanied by a good positive I/O correlation indicates a
ing and Air-Conditioning Engineers (ASHRAE)24 as well as the low but non-negligible infiltration factor and the lack of substantial
Canadian Conservation Institute,25 provide recommendations indoor sources for a given species. Sulfate, which is a classic tracer
for PM2.5. They suggest concentration limits of <0.1 and 1À10 μg/m3 of atmospheric outdoor aerosols with no known indoor
for sensitive materials and general collections, respectively. PM2.5 sources29,30, presents a similar I/O source relationship, despite
levels in the refectory are within the limit values for general its usual association with high I/O ratios. However, in the current
collections, but greater than those for sensitive materials. How- study, species that are usually considered to originate from out-
ever, it is important to recognize that attaining such limits doors (e.g., sulfate, EC in nonsmoking environments)29À31, have
requires controls that may not be feasible and realistic. low I/O ratios due to their effective removal by the HVAC system.
To determine the monthly bulk composition of indoor PM2.5 Second, a species associated with a low I/O ratio and poor I/O
and PM2.5À10, a chemical mass balance was conducted as correlation has a very low infiltration factor and no significant
illustrated in Figure 1(c, d). PM chemical species were classified sources impacting its indoor levels. Furthermore, a species with a
into water-insoluble organic matter (WIOM), water-soluble high I/O ratio and a poor I/O correlation has a relatively low
organic matter (WSOM), EC, ions, crustal material (CM), and infiltration ratio but important indoor sources. For instance, OC,
trace elements (TE). WIOM and WSOM were determined by which is commonly associated with indoor sources29,31, exhibits a
multiplying both WSOC and water-insoluble OC (WIOC = OC- similar behavior. Lastly, a species with a high I/O ratio and good
WSOC) concentrations by a factor of 1.7.26À28 Further details positive I/O correlation displays high infiltration efficiency and
about the reconstruction are provided in the SI. lacks important indoor sources.
WIOM was the dominant component of PM2.5 and PM2.5À10, As can be inferred from Table 1, the I/O ratios were generally
accounting for an average ((one standard deviation) of 70.9 ( greater for PM2.5 than PM2.5À10 species, reflecting the lower
16.4% and 61.3 ( 29.7% of total PM mass, respectively. PM2.5- infiltration efficiency and larger deposition velocity of coarse
WIOM concentrations exhibited some variation, ranging between particles.32,33 Moreover, I/O ratios for fine PM mass were below
1.7 μg/m3 in December and 3.1 μg/m3 in July. Conversely, coarse unity and presented some seasonality reaching a minimum (0.04 (
mode WIOM displayed lower concentrations, varying between 0.03) in winter and a maximum (0.18 ( 0.06) in summer. These
0.10 μg/m3 in December and 0.38 μg/m3 in April/May. WSOM ratios were also accompanied by a negative I/O correlation
was the next most abundant component of PM2.5 but only a minor (R = À0.31), indicating that indoor sources have major contribu-
fraction of OM, comprising 17.8 ( 4.4% and 19.9 ( 2.9% of their total tions to PM2.5. On the other hand, ionic species, sulfate, nitrate and
mass, respectively. Moreover, WSOM only accounted for 8.8 ( 4.9% ammonium, originated from outdoors (R = 0.66À0.76) but with
of coarse PM mass. EC, on the other hand, only contributed to PM2.5. very low infiltration factors (I/O ratio e2%). Similarly to fine PM
Its concentration and relative proportion were however minimal mass, OC and WIOC exhibited peak I/O ratios in summer
(<0.05 μg/m3 and 1.5%). CM accounted for 8.2 ( 2.2% and 14.6 ( (0.61 and 1.07, respectively) and were negatively correlated to their
4.7% of PM2.5 and PM2.5À10, respectively. Lastly, ions accounted for outdoor components, implying the existence of significant indoor
3.1 ( 1.8% of PM2.5 and 5.4 ( 3.5% of PM2.5À10. OM sources. Furthermore, WSOC, an indicator of SOA formation
The agreement between the reconstructed and gravimetric processes and biomass burning,34 showed a weak I/O association
mass is overall good, averaging 104 ( 20% for PM2.5 and 88 ( and slightly higher I/O ratios in spring and summer (∼0.20).
29% for PM2.5À10. The observed discrepancy could be related to These results reflect a possible formation of SOA indoors. EC,
uncertainties in the conversion factors from WSOC to WSOM, a key tracer for diesel exhaust,35 displayed a weak I/O correlation
WIOC to WIOM, and metals to oxides as well as uncertainties in (R = 0.20) although it is expected to originate from outdoors given
the measured mass, particularly for coarse PM. the prohibition of smoking inside the refectory. This could be
3.1.2. Infiltration Ratios of Tracer Species. To investigate the related to its efficient removal by ventilation, where EC was present
influence of outdoor and indoor sources on PM levels inside the at levels less than 0.05 μg/m3 with low I/O ratios (∼3%). These
refectory, seasonal average indoor-to-outdoor (I/O) mass ratios findings suggest a nominal influence of outdoor diesel emissions on
and their standard deviations were determined for key tracers of indoor PM levels. Typical crustal metals, for example, Al, calcium
major PM sources as summarized in Table 1 for PM2.5. I/O (Ca), Ti and iron (Fe), exhibited I/O ratios ranging from 0.03 to
Spearman correlation coefficients (R) were also evaluated to 0.33 with similar peak occurrence in fall. Although these elements
determine whether an indoor species is attributable to infiltration are expected to originate from outdoors, they were weakly to mod-
from outdoors. This analysis, coupled with CMB results, pro- erately related to their outdoor components (R = 0.17À0.45), which
vides a quantitative assessment of the infiltration of PM from indicates their dependence on indoor sources, likely particle
specific outdoor sources. It should also be noted that concentra- resuspension during visiting hours. Moreover, in spite of its weak
tions that are below or comparable to the limit of detection I/O correspondence, potassium (K) was strongly associated with
(LOD), increase the uncertainty associated with the data, but Ti and Al (R = 0.98 and 0.62, respectively) at the indoor site,
should not cause a large overprediction. Concentration values indicating their common outdoor crustal source. Its poor I/O
that were below the LOD were assumed as half the detection correlation may be attributed to its mixed outdoor origin.
limit. LODs of all measured species are listed in SI Table S1. The Marcazzan et al.36 reported that K is associated with motor
seasons were segregated as winter (DecemberÀFebruary), spring vehicles in Milan. Conversely, Nickel (Ni), a marker of fuel oil
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5. Environmental Science & Technology ARTICLE
Table 1. Indoor-to-Outdoor (I/O) Seasonal Average (One Standard Deviation) Mass Ratios and Spearman Correlation
Coefficients (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) À0.31
SO42‑ 0.01(0.003) 0.02(0.02) 0.01(0.001) <1% 0.76
NO3À <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) À0.13
WIOC 0.11(0.04) 0.51(0.29) 1.07(0.45) 0.30(0.18) À0.64
WSOC 0.11(0.01) 0.20(0.05) 0.22(0.04) 0.15(0.03) À0.10
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) À0.45
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) À0.23
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) À0.68
pentadecanoic acid 1.1(0.35) 2.3(0.22) 6.1(1.7) 4.4(1.9) À0.88
hexadecanoic acid 0.49(0.14) 1.0(0.11) 2.1(0.83) 0.94(0.52) À0.66
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) À0.20
nonadecanoic acid 0.15(0.05) 0.45(0.19) 0.73(0.17) 0.53(0.4) À0.20
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) À0.11
azelaic acid 0.06(0.02) 0.13(0.04) 0.21(0.04) 0.14(0.05) À0.30
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) À0.43
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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6. Environmental Science & Technology ARTICLE
combustion,37,38 strongly correlated with its outdoor compo- palmitoleic and oleic acids, normally associated with cooking,51
nent (R = 0.66), signifying its mostly outdoor origin. Ni also exhibited I/O ratios much greater than 1, also indicating their
displayed comparable I/O ratios (4À7%), indicating a stable primarily indoor origin. However, given that cooking is prohib-
but rather small outdoor influence on its indoor levels. Anthro- ited inside the refectory, the most probable source is biogenic
pogenic metals, copper (Cu) and zinc (Zn), displayed I/O material45 potentially emitted from waxes.52,53 Emissions from
ratios ranging from 0.02 to 0.10 and were weakly dependent on skin surface lipids of visitors are also a likely source of oleic acid.48
their outdoor components (R = 0.31 and À0.23, respectively), These fatty acids are ubiquitous indoors and may be sorbed to
indicating a potential but small indoor influence such as their indoor airborne particles or also settled dust54 that is subse-
accumulation in indoor dust.39 This build up may in turn be quently resuspended by human/cleaning activities. Tributyl
determined by indoor and outdoor emissions.40 phosphate, a phosphate ester used in plasticizers and flame
Among the listed polycyclic aromatic hydrocarbons (PAHs), retardants,55 persistently displayed I/O ratios exceeding unity,
picene, a molecular marker for coal soot,41 was not measured in thereby indicating its indoor source, most likely wall or ceiling
the indoor samples despite its detection outdoors, implying that paint. In contrast, phtalic and methylphtalic acids, which exhib-
coal soot is not a source contributor to indoor PM levels. The ited low but non-negligible I/O ratios (e13 and 4%, re-
remaining PAHs, common products of incomplete combustion spectively), infiltrated from outdoors (R = 0.71 and 0.40,
including fossil fuel and biomass combustion,42 were mostly respectively) with emissions from mobile sources and association
undetected indoors, especially in summer, and exhibited extre- with SOA formation45 as possible sources. The I/O ratios of
mely low infiltration factors (e3%), indicating that their sources suberic and azelaic acids, which are photo-oxidation products of
do not significantly impact indoor PM levels. Hopanes, which are biogenic unsaturated fatty acids,56 suggest the presence of SOA
predominantly associated with engine lubricating oil of mobile indoors. Nonetheless, the indoor levels of SOA are probably low,
sources,43 fairly correlated with their outdoor levels (R = as WSOM only constitutes ∼20% of OM, as aforementioned.
0.53À0.73), confirming their outdoor origin. Excluding summer, Tracers for biogenic-derived SOA include photo-oxidation
during which high I/O ratios were observed for 17β(H)- products of α-pinene and isoprene. These comprise pinonic
21α(H)-30-norhopane and 17α(H)-21β(H)-hopane (0.69À0.85), acid, 2-hydroxy-4-isopropyladipic acid, 2-methylthreitol, and
seasonal infiltration factors ranged from 0.08 to 0.36. These 2-methylerythritol.22 Conversely, tracers for anthropogenic-
ratios highlight a year-long influence from vehicular sources on derived SOA include 2,3-dihydroxy-4-oxopentanoic acid,
hopanes levels indoors. The peak summertime infiltration ratio photo-oxidation product of toluene.22 Among these SOA
may be a result of measurement uncertainties associated with the tracers, only 2-hydroxy-4-isopropyladipic acid, derivative of
low outdoor hopanes levels (0.02À0.06 ng/m3). To investigate α-pinene, was detected indoors with peak I/O ratio about unity
the origin of indoor n-alkanes (C29ÀC33), the carbon preference (1.07 ( 0.48) in summer. This secondary compound also
index (CPI), defined as the concentration ratio of their odd-to- presented a poor I/O correlation (R = À0.43) suggesting its
even numbered homologues, was estimated. A CPI about 1 indoor formation. A likely pathway is gas-phase reactions
indicates a dominance of anthropogenic sources, whereas a CPI involving α-pinene constituents and oxidants. The higher sum-
greater than 2 indicates a prevalence of biogenic sources.44 These mertime I/O ratio reflects an enhanced production of SOA,
indoor compounds did not exhibit a discernible odd-to-even possibly promoted by an increase in infiltrating oxidants.
carbon number preference (CPI = 1.01 ( 0.14 on a yearly Lastly, the low I/O ratio and high I/O correlation for
average basis), indicating their anthropogenic outdoor source, levoglucosan (R = 0.66), a tracer for biomass burning,57 indicates
such as fossil fuel utilization and wood-smoke.45 Nonetheless, the its low but non-negligible indoor intrusion, mainly in winter
low I/O correspondence for some of these n-alkanes can be (12%).
related to the primarily biogenic nature of their outdoor compo- In summary, these findings show that key tracers of major
nents, which exhibited a CPI of 2.53 ( 0.61. Moreover, n-alkanes outdoor sources generally have small infiltration factors. Addi-
displayed highest I/O ratios (0.17À0.76) in summer, possibly tionally, it is particularly interesting that fatty acids were mainly of
related to condensation of infiltrating gas-phase n-alkanes onto indoor origin with palmitoleic and oleic acids exhibiting I/O
indoor particles as a result of I/O temperature differences. In ratios >1.
contrast, squalane existed in higher indoors than outdoor amounts. 3.2. CMB Results. 3.2.1. Source Apportionment of Fine OC.
This undoubtedly suggests that indoor sources significantly con- The monthly contributions of primary and secondary sources to
tribute to its presence indoors. Squalane is a naturally occurring indoor fine OC as estimated by the CMB model are shown in
compound in humans and plants as well as a compound used in Figure 2a and summarized in SI Table S3a. Three sources,
skin care products,46,47 suggesting visitors as a possible source including wood-smoke, gasoline vehicles, and urban soil were
given the absence of plants in the refectory. identified. Contributions to OC from biogenic-derived SOA were
n-alkanoic acids, C14ÀC19, were uncorrelated with their out- not statistically significant (<2 Â standard error) with an utmost
door components and displayed relatively high I/O ratios with value of 0.015 μg/m3. Similarly, diesel emissions were not
some greater than unity, indicating their predominantly indoor statistically significantly different from zero. The three sources
origin. Their I/O ratios also demonstrated a seasonal pattern collectively contributed to 6.3À20.7% of measured fine OC,
with greatest ratios occurring in summer (0.73À12.4), in accor- with the remainder representing unidentified sources, likely
dance with those of OC and WIOC. Moreover, these fatty acids including biogenic SOA. The largest contributor to OC mass
displayed a yearly average CPI of 7.55 ( 0.92, indicative of their consisted of gasoline vehicles, which accounted for 4.9À16.7%
biogenic origin. For n-alkanoic acids, CPI is estimated as the of OC. The largest percent contributions and source estimates
concentration ratio of their even-to-odd numbered homologues. occurred in cold months (DecemberÀMarch) with highest
Potential indoor sources include skin emissions from visitors48 average ((standard error) levels of 0.23 ( 0.024 μg/m3
and wax49 emissions from the painting itself. Waxes were used attained in February. The next most contributing source was
during the restoration process of the painting.50 Furthermore, wood-smoke during winter, while urban soil during the
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7. Environmental Science & Technology ARTICLE
Figure 2. Sources contribution to indoor (a) fine organic carbon (OC) and (b) PM2.5 estimated using the chemical mass balance (CMB) model.
remaining seasons. Wood-smoke contribution was only statis- Accordingly, unapportioned WIOC was determined as the
tically significant during DecemberÀApril and peaked in Feb- difference between total WIOC and the sum of all primary
ruary to reach 0.039 ( 0.015 μg/m3 (i.e., 2.8% of OC mass). source estimates (excluding wood-smoke) and WIOC from
This seasonal pattern suggests wood burning for domestic wood-smoke. These estimates are reported in SI Table S3a.
heating during cold months. On the other hand, urban soil As can be deduced, unattributed OC is largely water-insoluble
lacked any discernible seasonal trend and contributed to 1.14 ( (77.9 ( 3.2%), which indicates that uncharacterized OC sources
0.46% (0.018 ( 0.007 μg/m3) of OC mass on a yearly based are mostly primary. Given that major outdoor sources of OC
average ((standard deviation). have been included in the CMB model, and considering their low
Lastly, unidentified source contributions, denoted as “other infiltration factors and contribution estimates, unknown primary
OC”, were estimated as the difference between measured OC sources are likely dominated by indoor sources such as dust
and the contributions from the modeled sources. The percent of of biogenic origin, or PM emissions from the visitors and the
residual mass was higher during JulyÀOctober and could be painting itself.
attributed to uncharacterized primary and SOA sources. The relative importance of fine OM to indoor PM and the
3.2.2. Source Apportionment of Total PM2.5. Source contribu- likelihood of its predominantly indoor source warrant further
tions to total PM2.5 were assessed by converting CMB results for investigation of this aerosol component. Accordingly, monthly
fine OC to PM2.5 apportionment using reported fine OC-to-PM variations of indoor fine WSOC, WIOC, fatty acids with I/O
mass ratios for each source.19À23 In addition to the sources ratio >1 and CPI of n-alkanoic acids are examined as illustrated in
identified in OC apportionment, “other OM” as well as sulfate, Figure 3(aÀd).
nitrate, and ammonium ion concentrations were considered in WSOC, attributed to SOA formation processes and biomass
PM2.5 apportionment as displayed in Figure 2b and SI Table S3b. burning,34 mainly originated from indoors as previously noted. In
“Other OM” was estimated by multiplying “other OC” by a factor fact, the contribution to WSOC from wood-smoke source was
of 1.7.26À28 These sources collectively accounted for 96.2 ( only significant in winter and early spring when it averaged
18.7% of the measured PM2.5 mass, on a yearly based average ((standard deviation) 0.02 ( 0.006 μg/m3. Total WSOC, on
((standard deviation). Some of the inconsistency in apportion- the other hand, maintained a stable average concentration of
ment could be due to uncertainties associated with the conver- 0.31 ( 0.02 μg/m3 throughout the year, which further confirms a
sion factor from OC to OM and geographical differences of the continual and prevalent contribution to WSOC from indoor
sources compositions. Finally, the most significant contributions SOA formation processes. This contribution to overall OC was
were from “other OM” (80.5 ( 17.4%), followed by urban soil however minor, as WSOC only comprised 20 ( 3% of indoor
(6.9 ( 1.7%), gasoline vehicles (6.5 ( 2.8%), wood-smoke OC across the year.
(1.2 ( 0.51%), then sulfate, nitrate and ammonium ions with WIOC, on the other hand, was a major component of indoor
contributions less than 1%. fine OC, accounting for 80 ( 3% of its mass on a yearly average
3.3. Comparison of OC to Organic Acid Species in PM2.5. basis. It also follows closely unapportioned OC, which could not
To elucidate the nature of uncharacterized OC, WSOC con- be assigned to outdoor sources, supporting the likelihood that
tribution to unapportioned OC was estimated as WSOC that OC is mostly insoluble of indoor primary origin. Furthermore,
is not associated with wood-smoke emissions. This calculation WIOC was present at a yearly average concentration of 1.25 (
estimates wood-smoke contribution to OC as 71% water-soluble.58 0.25 μg/m3, with higher levels observed during MayÀOctober
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8. Environmental Science & Technology ARTICLE
Figure 3. Monthly time series of (a) water-soluble organic carbon (WSOC), (b) water-insoluble organic carbon (WIOC) and un-apportioned organic
carbon (OC), (c) palmitoleic and oleic acids, (d) carbon preference index of n-alkanoic acids (C14ÀC29), in fine PM in the indoor environment.
and peak occurrence of 1.82 μg/m3 in July. These variations dust, waxes used in the painting and human skin emissions as
imply an increase in the source strength of indoor primary potential sources.
emissions during these months. Indoor n-alkanoic acids, C14ÀC29, exhibited a year-long
To characterize potential indoor sources of OC, the monthly strong even carbon preference, with an annual average CPI of
trend of palmitoleic and oleic acids, which were present in 6.62 ( 0.55 and limited monthly variation. Carbon number
greater indoors than outdoor amounts, was investigated. These maxima occurred at C16 and C14 (SI Table S4), which are
components exhibited a temporal distribution fairly similar to commonly found indoors59 and associated with human skin
that of WIOC and unapportioned OC, reaching a collective surface lipids.48 These findings are indicative of the consistent
peak of 41.9 ng/m3 in July and low of 14.4 ng/m3 in January. biogenic source of these n-fatty acids such as waxes used in
Particularly, palmitoleic and oleic acids, biogenic components painting the “Last Supper” and skin emissions, as aforemen-
sorbed to indoor airborne PM or dust as aforementioned, were tioned. Moreover, these components highly correlate with
significantly and well correlated to WIOC (R = 0.75 and 0.76, WIOC (R = 0.73), a dominant component of OC, suggesting
respectively). Thus, this temporal correlation suggests their their shared origin with indoor dust of biogenic nature, emis-
common source with biogenic material associated with indoor sions from the painting or human skin as likely sources.
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9. Environmental Science & Technology ARTICLE
Overall, the results of this study showed that outdoor sources Jones, J.; Farrar, C.; Maberti, S. Influence of ambient (outdoor) sources
have small infiltration factors and contribution to PM2.5. OM, on residential indoor and personal PM2.5 concentrations: Analyses of
which could not be apportioned to any major outdoor sources, RIOPA data. J. Exposure Anal. Environ. Epidemiol. 2005, 15 (1), 17–28.
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should address indoor sources of biological material that is likely Facchini, M. C.; Decesari, S.; Fuzzi, S.; Gehrig, R.; H€glin, C.; Laj, P.;
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associated with indoor dust. Lastly, we should note that findings Lorbeer, G.; Maenhaut, W.; Mihalopoulos, N.; M€ller, K.; Querol, X.;
u
of this study are characteristic of the specific site location, climatic Rodriguez, S.; Schneider, J.; Spindler, G.; Brink, H. t.; Tørseth, K.;
conditions inside the refectory, visitors’ pattern and specifica- Wiedensohler, A. A European aerosol phenomenology—2: Chemical
tions of the HVAC system. These results, therefore, cannot be characteristics of particulate matter at kerbside, urban, rural and back-
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’ AUTHOR INFORMATION Research and Bollettino Geofisico, Special Issue 1991, 14 (3), 1–123.
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Corresponding Author tant removal at indoor surfaces. Environ. Int. 1989, 15 (1À6), 567–584.
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’ ACKNOWLEDGMENT (15) Stone, E. A.; Hedman, C. J.; Sheesley, R. J.; Shafer, M. M.;
Schauer, J. J. Investigating the chemical nature of humic-like substances
This research was supported by Southern California Particle (HULIS) in North American atmospheric aerosols by liquid chroma-
Center, funded by US EPA and the University of Southern tography tandem mass spectrometry. Atmos. Environ. 2009, 43 (27),
California (USC) Viterbi School of Engineering. We would 4205–4213.
like to thank the superintendent of fine arts and culture in (16) Zhang, Y.; Schauer, J. J.; Shafer, M. M.; Hannigan, M. P.;
Lombardy for his willingness to accept this study. We also wish Dutton, S. J. Source apportionment of in vitro reactive oxygen species
to acknowledge the support of USC Provost’s Ph.D. fellowship. bioassay activity from atmospheric particulate matter. Environ. Sci.
We thank Jeff DeMinter, Brandon Shelton and the staff at the Technol. 2008, 42 (19), 7502–7509.
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Wisconsin State Laboratory of Hygiene for their assistance with Control Assoc. 1984, 34 (6), 619.
the chemical measurements. We also wish to thank SIMG-Italian (18) Schauer, J. J.; Rogge, W. F.; Hildemann, L. M.; Mazurek, M. A.;
College GPs and ISDE-International Doctors for the Environ- Cass, G. R.; Simoneit, B. R. T. Source apportionment of airborne
ment for managerial support, Eng. Franco Gasparini, designer of particulate matter using organic compounds as tracers. Atmos. Environ.
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and employees of the Sovrintendenza, particularly Arch. A. (19) Fine, P. M.; Cass, G. R.; Simoneit, B. R. T. Chemical char-
Artioli, Arch. G. Stolfi, Arch. Napoleone, Mr. G. Bonnet and acterization of fine particle emissions from the fireplace combustion of
Dr. L. Dall’Aglio wood types grown in the Midwestern and Western United States.
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