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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 ‡
bS Supporting Information 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 outdoor sites of the painting’s location, where time-integrated fine and coarse PM (PM2.5 and PM2.5 10) samples were simultaneously collected. Findings showed that PM2.5 and PM2.5 10 concentrations were reduced indoors by 88 and 94% on a yearly average basis, respectively. This large reduction is mainly attributed 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 Damage to cultural assets has been of growing interest to museum conservators and curators. There is mounting evidence correlating indoor air pollution, biological contamination, mass tourism, and variability in microclimate conditions with material deterioration.1,2 A major concern is damage by particulate matter (PM) to masterworks of art displayed in museums. Potential hazards include “soiling” (perceptible degradation of visual qualities) due to deposition of airborne particles, particularly elemental carbon, and soil dust.3 Further damage can be induced by chemically reactive species, such as ammonium sulfate and organic acids.2,4 Typically, indoor PM consists of outdoor-infiltrating and indoor-emitted particles in addition to indoor-formed particles through reactions of gas-phase precursors emitted both indoors and outdoors.5,6 Moreover, the level and composition of indoor PM are governed by a myriad of factors. These mainly consist of the ventilation system, filtration effect of the building envelope, deposition rate of particles as well as the intensity of indoor and r 2011 American Chemical Society
outdoor sources.7,8 An accurate characterization of airborne PM in museums is therefore essential for conserving the exhibited artifacts. An emerging concern is with PM-induced damage to the “Last Supper” painting, one of Leonardo da Vinci’s most famous artworks, located in the refectory of Santa Maria delle Grazie Church in Milan, Italy. Although this painting has survived many challenges, including bombing during World War II, it is yet facing another challenge. The “Last Supper” painting, which was majorly restored in the 20th century, is at risk with air pollution arising from its surrounding Milan area. Milan is one of the most polluted areas in Western Europe9 with PM10 air quality standards frequently exceeded.10 In an attempt to protect the painting, a sophisticated heating, ventilation, and Received: August 5, 2011 Accepted: November 9, 2011 Revised: October 31, 2011 Published: November 09, 2011 10344
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Environmental Science & Technology air conditioning (HVAC) system equipped with particle filtration has been installed. To assess the effectiveness of this control measure, we conducted a one-year sampling campaign at indoor and outdoor sites of the refectory. At both locations, fine and coarse PM (PM2.5 and PM2.5 10, respectively) samples were simultaneously collected then analyzed for their chemical properties. In the present article, the indoor-to-outdoor relationship of key tracers of PM sources is investigated in order to evaluate the impact of indoor and outdoor sources on indoor particle levels. Furthermore, the chemical mass balance model is applied to identify and estimate sources contributions to indoor PM2.5 concentration. Results of this study provide a quantitative understanding on the composition, origin and level of PM inside the refectory. Ultimately, these findings can be used as guidelines for the implementation of additional, and particularly source-specific, control strategies to mitigate the concentration of particle components potentially detrimental to the “Last Supper” painting. They can also be used as a benchmark in future studies aimed at protecting indoor artworks and antiquities.
2. MATERIALS AND METHODS 2.1. Sampling Description. To characterize PM inside the refectory, PM2.5 and PM2.5 10 were simultaneously sampled at indoor and outdoor sites of the refectory. The sampling campaign lasted from December 2009 to November 2010. During this period, 24-hour size-segregated PM samples were collected on a weekly basis by means of two sets of Sioutas personal cascade impactor samplers (Sioutas PCIS, SKC Inc., Eighty Four, PA11). Every set consisted of two collocated PCIS loaded with 37 and 25 mm filters for fine and coarse PM analyses, respectively. Each of the PCIS was placed at the indoor or outdoor site and operated at a flow rate of 9 lpm. For the purpose of chemical analysis, one set of the PCIS was loaded with Teflon filters (Pall Life Sciences, Ann Arbor, MI), whereas the other one was loaded with quartz microfiber filters (Whatman International Ltd., Maidstone, England). PM mass concentration was determined from the mass loadings of the weekly Teflon filters as described in the Supporting Information (SI). The indoor sampling location was inside the refectory of Santa Maria delle Grazie Church, where da Vinci painted the “Last Supper” on one of its walls. Samples were collected at approximately 1 m directly below the painting and a few centimeters from the wall surface. The site is equipped with a newly deployed HVAC system, supplying 4000 m3/h total air flow, of which 2000 m3/h are external fresh air. This system is operated continuously. The air-flow rate inside the refectory, whose volume is 3130 m3, is 3000 m3/h, resulting in an air exchange rate of roughly 1 h 1. This relatively low air change rate helps avoid convective air velocities on the painting to the degree possible. The remaining air flow rate goes into two 130 m3 isolating zones, located at the entrance and exit of the refectory, through which visitors pass for isolation and decontamination from outdoor pollution. Furthermore, the air is filtered with plane, pocket and absolute filters as well as chemical filters (Purafil, Inc.); more details about these filters as well as the design and operation of the HVAC system can be found in the SI. The number of visitors and duration of visit are limited to 25 persons and 15 min at any time between 8:15 a.m. and 6:45 p.m. Visits are allowed each day, except for Monday, with number of visitors averaging 1000 visitors/day. The temperature and relative humidity are automatically controlled
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to maintain constant conditions. Large variations in the thermohygrometric factors in the refectory, enhanced by the presence of visitors, may lead to an increase in the deposition rate of airborne pollutants on the painting, as previously demonstrated by Camuffo and Bernardi.12 The temperature of the backside room is also maintained at about 2 °C higher than the refectory’s temperature to avoid PM deposition on the painting due to thermophoresis effects.3,13 Finally, it should be noted that the HVAC system failed for few days during one week of April. PM concentration substantially increased during that week, compared to the remaining weeks with noninterrupted system functioning. This effect was more noticeable for PM2.5 10, for which a nearly 9-fold increase was observed, as shown in SI Figure S3. This occurrence, however, has minor impacts on the results where monthly averages are reported throughout this study. 2.2. Chemical Analyses. To conduct the chemical analyses, the Teflon and quartz filters were sectioned into portions. The fractions used for elemental and organic carbon (EC and OC, respectively) quantification were grouped into weekly samples and quantified using the NIOSH thermal optical transmission method.14 All remaining fractions, with the exception of few PM2.5 10 sections, were composited monthly. Given their low mass loading, February/March, April/May, and October/November coarse samples were composited bimonthly. These monthly and bimonthly fractions were analyzed for water-soluble OC (WSOC) and ions using a Sievers 900 Total Organic Carbon Analyzer15 and ion chromatography, respectively. Total elemental content of these composites was also measured using high resolution magnetic sector inductively coupled plasma mass spectrometry (Thermo-Finnigan Element 2).16 Additionally, organic speciation was conducted on PM2.5 filter sections using gas chromatography mass spectrometry (GC-6980, quadrupole MS-5973, Agilent Technologies). PM2.5 10 lacked sufficient mass for this analysis. Details of these analyses are provided in the SI. 2.3. Source Apportionment. A molecular marker chemical mass balance model (MM-CMB) that was mathematically solved with the U.S. Environmental Protection Agency CMB (EPACMB8.2) software was used to estimate primary and secondary source contributions to indoor fine OC on a monthly basis. The effective variance weighted least-squares algorithm was applied to apportion the receptor data to the source profiles.17 MM-CMB was conducted using primary molecular source tracers that were quantified in the PM2.5 samples. Markers that are chemically stable and secondary organic aerosol (SOA) tracers that are unique to their precursor gases were selected as fitting species.18 These included levoglucosan, αββ-20R&S C27-cholestane, αββ-20R&S-C29-sitostane, 17α(H)-22,29,30trisnorhopane, 17α(H)-21β(H)-hopane, 17β(H)-21α(H)-30norhopane, benzo(b)fluoranthene, benzo(k)fluoranthene, indeno[c,d]pyrene, benzo(ghi)perylene, EC, aluminum (Al), and titanium (Ti). The input source profiles were based on the observed molecular markers and assumed representative of sources in Milan. These profiles included wood-smoke,19,20 urban soil, gasoline vehicles,21 and diesel emissions.21 Biogenic-derived SOA was not included in the model but its contribution was estimated using fixed tracer-to-OC ratios.22 Moreover, the selected urban soil profile is not specific to Milan. However, the choice of this profile is not critical for the overall apportionment of fine OC as its contribution to total OC mass is small23. Its selection was 10345
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Figure 1. Monthly average indoor concentration (compared to outdoor concentration) and bulk composition for (a, c) PM2.5 and (b, d) PM2.5 Error bars represent one standard error.
nonetheless based on a comparison of the elemental ratios of the measured data to those of available soil profiles, where the urban soil profile of St. Louis (Missouri)23 provided a best fit. In contrast, natural gas, coal soot and toluene-derived (anthropogenic) SOA sources were not considered in the model, as their molecular markers were not detected in the samples. Furthermore, contributions from vegetative detritus were not apportioned because n-alkanes (C29 C33) did not exhibit an odd-carbon preference indicative of modern plant material. Lastly, the CMB model results were considered valid if they met specific acceptance criteria as outlined in the SI.
10.
3. RESULTS AND DISCUSSION 3.1. Indoor Outdoor Relationship. 3.1.1. Particulate Mass and 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 outdoors for both particle modes. This significant reduction in PM2.5 and PM2.5 10 concentration (88 ( 7% and 94 ( 3% on a yearly average ((standard deviation) basis, respectively) can be largely attributed to the efficacy of the HVAC system in removing infiltrating outdoor PM. Moreover, coarse PM exhibited 10346
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Environmental Science & Technology extremely low indoor levels ranging between 0.12 and 0.83 μg/m3 with no specific seasonal trend. PM2.5 was the dominant indoor PM component with a concentration range of 1.7 4.9 μg/m3. It also followed a pattern dissimilar to that of its outdoor component, indicating that indoor sources may have major contributions to fine PM indoors. Finally, it is noteworthy that currently there are no regulations for PM levels in museums, galleries, and archives. However, the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)24 as well as the Canadian Conservation Institute,25 provide recommendations for PM2.5. They suggest concentration limits of
