Environ. Sci. Technol. 1996, 30, 3341-3350
Microanalysis of Museum Aerosols To Elucidate the Soiling of Paintings: Case of the Correr Museum, Venice, Italy L I E V E A . D E B O C K , * ,† R E N EÄ E . V A N G R I E K E N , † DARIO CAMUFFO,‡ AND G. W. GRIME§ Department of Chemistry, University of Antwerp (UIA), Universiteitsplein 1, B-2610 Antwerp, Belgium, Consiglio Nazionale delle Ricerche, Istituto di Chimica e Tecnologie, Inorganichee dei Materiali Avanzati, Corso Stati Uniti 4, I-35020 Padova, Italy, and Scanning Proton Microprobe Unit, Nuclear Physics Laboratory, University of Oxford, Keble Road, Oxford, U.K.
The results of the characterization of individual airborne particles collected during two separate sampling campaigns at the Correr Museum, situated at the San Marco Square in Venice, Italy, are reported. The chemical composition and associated diameter of individual aerosol particles in the size range of 0.220 µm were determined by electron probe X-ray microanalysis and scanning electron microscopy with energy dispersive X-ray measurement (SEM-EDX). Multivariate techniques were used for the reduction of the data set. Based on hierarchical cluster analysis results, the majority of samples from both campaigns appeared to be composed of six to eight different particle types from which the Ca-rich particles together with the aluminosilicates and organic material can be identified as the most important ones. The correlation between the abundance of the particle types and their diameters as well as between the sampling periods was investigated. Factor analysis revealed similar results. To provide a better view on the nature, composition, and possible sources of the indoor aerosol particles, the indoor and outdoor aerosol compositions of three sampling periods were compared, and additionally two possible indoor particle sources were investigated. The results indicated the existence of a Ca-rich indoor particle source, probably the deterioration of the interior plaster walls. The homogeneity study of giant aerosol particles >8 µm, using the X-ray mapping facilities on the SEMEDX instrument under optimal conditions, revealed that these particles are heterogeneous and mainly consist of Ca and Si. The other particle types were identified as small aluminosilicate and CaSO4 particles or very small Fe-rich particles, and they seemed to be adsorbed at the surface of the Ca-Si-rich particles. Preliminary results of scanning transmission
S0013-936X(96)00200-3 CCC: $12.00
1996 American Chemical Society
electron microscopy and scanning proton microprobe measurements on submicrometer indoor aerosol particles and giant indoor Ca-rich aerosol particles, respectively, are discussed as well.
Introduction Due to the fact that people spend 75-90% of their time indoors, indoor air quality research was originally focused on the determination of the effects on public health of the atmosphere inside offices, laboratories, and residences (1, 2). Based on these studies, it became clear that indoor air pollution could appear as a consequence of both indoor and outdoor factors and could also cause, besides serious health effects, chemical damage or soiling to surfaces by deposition of particulate material or absorption of gases. The conservation of our cultural heritage and its protection against possible damage due to indoor air pollution is now receiving increasing scientific interest. Some very interesting reviews on the general composition of museum atmospheres and its effect on cultural and historic materials have already been published by Thomson (3), Baer and Banks (4), Brimblecombe (5), and Hisham and Grosjean (6). Recently, some innovative work has been performed to obtain a characterization of indoor particles, their sizes, and sources (7, 8). Raunemaa et al. (9) introduced an indoor aerosol model to describe the indoor transport and deposition of fine and coarse particles. The concentration and fate of airborne particles inside museums was studied by Nazzaroff et al. (10, 11) based on a model of indoor aerosol dynamics. Due to the slow realization of the importance of a controlled environment inside museums, many problems still remain unsolved, and further research is necessary. The present study reports on the characterization of individual airborne particles collected during two separate sampling campaigns in December 1992 and at February 1994, in the Correr Museum situated at the San Marco Square in Venice, Italy. The purposes of campaign 1 were primarily the determination of the chemical composition of individual sizesegregated aerosol particles with a diameter range of 0.220 µm and secondly the investigation of the possible changes between successive sampling periods. Automated singleparticle analysis was performed by electron probe X-ray microanalysis (EPXMA) and scanning electron microscopy with energy-dispersive X-ray detection (SEM-EDX); both belong to the most commonly used nondestructive microanalytical techniques. The classification of the analyzed particles in separate particle types and the identification of different aerosol sources were obtained by multivariate techniques, namely, hierarchical cluster analysis (HCA) and factor analysis (FA), respectively. Additional aims for campaign 2 were to optimize the characterization of particles smaller that 0.2 µm diameter * Address correspondence to this author, e-mail address:
[email protected]. † University of Antwerp. ‡ Inorganichee dei Materiali Avanzati. § University of Oxford.
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by using a scanning transmission electron microscope (STEM) coupled to an EDX detector; to investigate the possibilities of X-ray mapping on a JEOL JSM 6300 SEMEDX system for acquiring the elemental distribution inside individual giant aerosol particles with diameters above 8 µm; to obtain information on the trace element composition of those giant aerosols using scanning proton microscopy (SPM); and finally to compare the indoor and the outdoor aerosol compositions at the Correr museum.
Experimental Section Sampling Strategy. Both sampling campaigns were organized at the Correr Museum, which is part of the “Procuratie Nuove”, one of the historical buildings enclosing the San Marco Square in Venice. The building was originally constructed in 1582. A new part was added in 1640, after which it was converted into a Royal Palace by Napoleon. Later it became a museum in which at the moment Byzantine, Gothic, and Renaissance paintings by different artists are on exhibition. The museum is equipped with a heating, ventilation, and air conditioning system (HVAC system) and humidifiers are present in some of the exhibition rooms. On the average, the museum is daily visited by 200 people, and cleaning of the different rooms is performed on Tuesday, the weekly closing day of the museum. Venice itself is situated in the middle of a lagoon and is characterized by frequent severe pollution episodes, especially during the winter season in the presence of fog when winds are associated with North-West directions (12). The fumigation of pollutants emitted by industrial plants at Porto Maghera and Mestre, on the hinterland close to the Shore, contribute probably to a large extent to this pollution level. The transport and dispersion of pollutants from the industrial zones into the Venetian area depend mainly on the wind speed, the urban topography, and the convective regime over the city. A definite behavior of the dispersion can even be associated to each wind speed class, but a detailed pollution forecast at Venice is still very difficult because the situation in Venice is rather unique and cannot be fit into the usual models (13). During campaign 1 in December 1992, four aerosol sample collections were performed in the “Bellini” exhibition room of the Correr Museum, using a May cascade impactor. Based on inertial characteristics, aerosol particles are segregated in size with theoretical cutoffs for stages 1-6 at 20, 8, 4, 2, 1, and 0.5 µm. Microscope slides covered with Apiezon-coated Nuclepore filters (Nuclepore, Pleasanton, CA) were used as impaction surface. The Apiezon coating reduces effects like “bounce off” and “re-entrainment”, which influence the collection efficiency and change the apparent size distribution. To investigate the effect of outdoor aerosol particles on the indoor particle composition, one of the windows in the Bellini exhibition room was kept open for 7 min before and after 1 hour of sampling during the fourth collection period. The rainy weather associated with heavy winds caused strong circulations indoors by which the outdoor aerosol concentration was increased. During those 7-min periods, aerosol sampling was stopped. Two possible indoor aerosol sources were studied by analyzing the powder removed from both the marblesimulating plaster on the wall as well as from a coating present on the vertical wood panels to which the Bellini paintings were connected. Due to the impossibility of direct
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EPXMA powder analysis, both samples were filtered on a Nuclepore filter after suspension in hexane. To obtain a complete characterization of the total aerosol composition present in the Bellini exhibition room, particles with diameters between 20 and 0.06 µm were sampled during campaign 2 in February 1994. A May impactor provided with microscope slides covered with Apiezoncoated Nuclepore filters, as described above, was used for the collection of the indoor aerosol samples with particle diameters above 0.2 µm during eight sampling periods. Indoor aerosol particles down to 0.06 µm diameter could be collected simultaneously with a Berner cascade impactor due to the low cutoff values on its last two stages (0.125 and 0.06 µm). Since individual particle analysis with EPXMA and SEM-EDX is limited to particle diameters above 0.2 µm, STEM-EDX was performed to analyze particles below 0.2 µm. This technique requires the application of Cu grids coated with a very thin support film. The 20 Finder 200mesh Cu grids, used for aerosol collection during the second sampling campaign, were coated with a Formvar film according to Hayat’s floatation method (14). To overcome the inherent weakness of the support film, the Formvarcoated Cu grids were stabilized with a thin layer of carbon. Additionally, for three sampling periods, outdoor aerosol particles with diameters ranging from 20 to 0.06 µm were sampled simultaneously with the indoor measurements using the available impactors. This would allow a comparison between the indoor and outdoor aerosol compositions. Instrumentation. The set of 30 size-segregated aerosol samples collected during campaign 1 was analyzed by EPXMA. The automated analyses of 9000 particles was performed on a JEOL 733 Superprobe (JEOL, Tokyo, Japan) equipped with a Tracor Northern TN-2000 system (Tracor Northern, Middleton, WI), using the particle analysis program 733B written in FORTRAN. For every impactor stage, 300 particles were analyzed. Each analysis was carried out at an acceleration voltage of 25 kV and a beam current of 1 nA. The energy-dispersive X-ray spectra accumulation time was fixed at 20 s to obtain satisfactory signal/noise ratios. A description of the 733B program can be found elsewhere (15). The 48 indoor aerosol samples and 15 outdoor samples from campaign 2 were analyzed using the JEOL JSM 6300 SEM. This instrument is equipped with a PGT (Princeton Gamma Tech, Princeton, NJ) energy-dispersive X-ray detector. Compared to the JEOL JXA-733 EPXMA, several interesting new applications are possible. Image processing and element mapping are more efficient due to the new data system, and particle analysis is even faster. The PA6300 program was applied for the automated analysis of 24 000 indoor and 7500 outdoor aerosol particles. The analysis of 500 individual particles on each sample was carried out at an acceleration voltage of 20 kV and a beam current of 1 nA. The X-ray accumulation time was again fixed at 20 s. Using the PA6300 program, the area to be analyzed is also subdivided in different fields, and the particle analysis starts with the collection of a backscattered electron image (BSE) of the field. The area, perimeter, and diameter of the particles within the field are calculated from the image and are also compared with a selection criterion. Based on the particle’s contour, an X-ray spectrum is accumulated by rastering the electron beam on 40 points within its contour. A tophat filter is applied for spectrum evaluation. BSE images and spectra are stored on an optical disk, allowing
a possible re-evaluation of the obtained data. Clear drawbacks of EPXMA and SEM-EDX are the poor detection limits (about 0.1%) and the limitation to detect only elements with Z > 10, due to the presence of a Be window in front of the Si-Li detector. The X-rays of elements like C, O, and N are too low in energy to penetrate this window. In EPXMA and SEM-EDX, a particle is classified as organic if no X-rays are collected or, in other words, when the sum of characteristic X-ray peak intensities in the spectrum is very low. However, both automated analysis methods provide in combination with multivariate techniques and/ or cluster analysis a powerful method for discriminating different particle types and for source apportionment. To study the spatial distribution of the elements inside individual Ca-rich giant aerosol particles (>8 µm), the possibilities of the JEOL JSM 6300 SEM in the field of X-ray mapping were investigated. The effects of the variation of different instrumental parameters on the collection of an X-ray mapping were tested, and this led to the following optimal parameter adjustment: a beam current of 1 nA, an acceleration voltage of 15 kV, a take-off angle of 30°, a working distance of 19 mm, and an analysis time set at 1-2 h. An increase of the number of counts per pixel during the same accumulation time, revealing more information in the same time period, became possible by reducing the detector-sample distance from 60 to 35 mm and reducing the shaping time of the EDS amplifier. Enhancement of the beam current from 1 to 6 nA, producing a large increase of the number of counts per pixel, was associated with a very strong charging and heating of the particle, leading to the volatilization of certain compounds or to particle drifting. Processing of the collected X-ray mappings was performed by Image Math, a program that enables mathematical operations on images. The collected X-ray mappings of the indoor aerosol particles were subjected to a background subtraction, and only statistically relevant intensities were presented. Measurements with the Oxford scanning proton microprobe (SPM), using a 100-pA proton beam of 3 MeV focused down to a diameter of 1-2 µm, revealed semiquantitative information on the trace element composition of the giant Ca-rich aerosol particles. Based on the elemental X-ray intensity maps and off-axis scanning transmission ion microscopy images (STIM) obtained for 13 individual aerosol particles, proton-induced X-ray emission (PIXE) spectra were accumulated at different points of interest inside the particles contour. Processing of the PIXE energy spectra was performed by PIXAN (16). Using this program, the concentrations in ppm of elements with Z > 11 are calculated based on the estimated composition, thickness, and density of the analyzed particle. The most important advantage of PIXE over electron-induced X-ray analysis techniques lies in the fact that in PIXE spectra a background of 2-3 orders of magnitude lower (from Z ) 15 onward) can be obtained because no continuum radiation is produced by the stopping of the projectile ions. Analysis of particles smaller than 0.2 µm was performed on a JEOL JEM 1200 EX STEM system equipped with a TRACOR TN 5500 energy-dispersive X-ray detector. Since this technique is not automated yet, the spectrum collection of over 60 individual submicrometer aerosol particles, sampled during campaign 2, was performed manually. During particle analysis, the energy of the electron beam was 120 keV, and X-rays were collected for 20-100 s in the “picture mode”, which offers the possibility to analyze only
a limited area of the sample. To improve the X-ray detection, the sample was tilted over an angle of 40°. To reduce the evaporating effect of the intense electron beam on the individual aerosol particles, a liquid nitrogen-cooled sample holder was used during the analysis. Morphological information was obtained by recording dark field electron images of the individual aerosol particles or particle groups. Since those images are recorded in the scanning mode as serial electrical signals, a flexible on-line image evaluation and processing is possible. In comparison with SEM-EDX, the main advantages of STEM-EDX are the production and positioning of a small electron probe for imaging and X-ray analysis of small specimen areas. Using thin specimens minimizes the interaction volume and thus improves the lateral resolution for X-ray microanalysis. Multivariate Techniques. Reduction of the data set was obtained by performing the Cluster Analysis (CA) program in the Integrated Data Analysis System (IDAS), a Windowsbased software package for both CA (17) and factor analysis (FA) on each of the aerosol samples, producing a classification into groups of particles with chemically similar composition. The hierarchical cluster analysis (HCA), used in this paper, starts with n particles or clusters from which the most similar ones are joined successively into new clusters. In this way a tree-like structure, called a dendrogram, is obtained. Different hierarchical strategies are possible to join two similar clusters; Ward’s error sum method is the one we applied because it creates a maximum internal homogeneity into the separated groups (18) and is considered to be the most suitable. To facilitate the choice of the correct number of clusters, so-called stopping rules can be used in IDAS which indicate at what level the dendrogram should be cut. From the three available stopping rules, the consistent akaike information criterion (CAIC) revealed the best results. The Davies-Bouldin index and the total error sum of squares criterion cannot always provide useful information due to their smaller application field as compared to CAIC and due to the sometimes complicated character of the experimental data set. The FA in IDAS was used to discover the interrelationships between the variables (Na, Mg, Al, Si, Ca, ...) and/or objects (different samples) in the analyzed indoor aerosol data set of both campaigns. The aim of FA is to describe all experimental data, measured on a set of variables, with a small number of new unmeasurable variables, called factors. To determine the correct number of factors, the FA program provides five different estimation criteria. The imbedded error function (IE) and the factor indicator function (IND) reach both a minimum at the most reasonable number of factors. The average eigenvalue criterion rejects all eigenvalues of less than an average eigenvalue. The variance, which is accounted for by the particular eigenvalue, can be obtained by the cumulative percent variance graph, and the root mean square error (RMS) criterion represents the difference between initial (raw) data and reproduced data. To simplify the interpretation of the obtained factors, a normal factor rotation was performed. This rotation helps to clarify the unclear features of the FA through changing the loadings of certain variables on certain factors. Visual representation of factor loadings, which show the relative contribution of a factor into a variable, and of factor scores, which reveal the structure of the data in the factor space, was used for the interpretation of the FA results.
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Elements in the FA data set were considered to be detected if the X-ray intensities were found above the detection limit in one of the 300 or 500 analyzed particles for each impactor sample. Elements like P, Cu, and Ba were only occasionally detected in particles. Since these elements were found, in HCA results, in particles that contributed less than 0.5% of the total aerosol abundance, they were further excluded from the FA data set.
Results and Discussion Factor Analysis. The data matrix, composed of the number of times a certain element (columns) is detected in each of the 30 analyzed samples (rows) from campaign 1, was subjected to FA with normal factor rotation and without scaling. A total of 14 variables was considered in the data matrix: Na, Mg, Al, Si, S, Cl, K, Ca, Ti, Fe, Zn, Cr, Mn, and Pb. To estimate the correct number of factors that should be taken into account in the FA model, the five different criteria described above were utilized. The IE and IND functions both reached a minimum at two, and four factors and considering the average eigenvalue criterion, 12 eigenvalues seemed to be rejected, thus only two factors remain. Based on the cumulative percent variance graph, the additional information provided by the third and fourth factor to explain the total variance in the data matrix seemed to be rather small. No useful information was obtained from the RMS graph. Based on four out of five estimation criteria, the most convenient solution appeared to be a FA model using two factors. The two factors together explain 97% of the total variance of the variables, and the total information given by their factor loadings is visually represented in Figure 1, panels a and b, respectively. Factor 1 (Figure 1a) is characterized by high loadings for Ca, S, and Si, followed by lower values for Fe, Cl, K, Al, and Mg. The contribution of Ti, Zn, Cr, Mn, and Pb seems to be almost negligible. This factor seems, based on the HCA results that will be discussed later, to represent different particle types produced by various processes. Decomposition arising through the aging of wall plaster or coatings present in the Bellini exhibition room provides a possible source of particles rich in Ca and S. The SEM-EDX analysis results obtained for the powder removed from both the marble-simulating plaster on the wall and the dust present on the vertical wood panels supports this assumption. The HCA results of both powders will be discussed below. Moreover CaSO4 -rich particles can be the result of a chemical transformation of CaCO3 due to the absorption of SOx gases in the indoor atmosphere. These gases can be introduced in the museum environment by HVAC systems (4) or by direct contact with the outdoor atmosphere in the morning and the evening when the museum windows are opened. Generally, the transport of particles to the indoor environment can take place through diffusion or direct contact with the outdoor environment or particles can be introduced by museum visitors. The anthropogenic release of gypsum from flue gas in desulfurization processes as well as the fractional crystallization of seawater appearing by evaporation of seawater droplets can be recognized as possible outdoor CaSO4 particle sources. According to Leysen et al. (19), 37-56% of the total amount of particles collected close to the Saint Rombouts Cathedral in Mechelen could be identified as Ca-rich particles. These CaCO3 particles find their origin in the deterioration of the limestone building material. Since limestone was also used to build the
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FIGURE 1. Factor analysis results of campaign 1, PA model with two factors. (a) Factor loadings of factor 1. (b) Factor loadings of factor 2. (c) Factor scores of factors 1 and 2, with the 30 samples of the data set represented as numbers.
Procuratie Nuove, the Ca-rich particles found in the Correr Museum can probably be attributed to this source. The combination of Ca with Si can be identified as calcium silicates, of which the C3S [(CaO)3SiO2)] and the C2S [(CaO)2SiO2)] are known to be among the basic components used in the cement production (20). The morphology of this particle type present in the indoor and outdoor museum environment matches the description found in the particle atlas (21). Calcium silicates as well as Ca-rich aluminosilicates can also occur by erosion of natural minerals. Si associated with Al, Fe, S, and K as major elements and with Ca, Ti, Mg, Zn, and Cr as minor elements are classified into the group of aluminosilicates. Based on morphological characteristics, aluminosilicates are subdivided into fly ash and soil dust; often no significant difference in composition is found. Fly ash is often spherically shaped, and it is emitted by high-temperature combustion processes in power plants. Soil dust particles are irregularly shaped and the result of soil erosion. Morphologically, the majority of aluminosilicate particles detected appeared to be irregularly shaped. Sometimes high concentrations of S can be found (15), pointing out the existence of secondary reactions with anthropogenic emissions of SO2 and H2SO4. Combustion processes could also be a possible source of Si-rich particles; their associated diameters should than be smaller than 1 µm. Factor 2 (Figure 1b) contains mainly Na and Cl, which
indicates the presence of a marine influence on the indoor aerosol composition. In the case of Venice, sea spray particles originate from the lagoon or the Adriatic Sea and are mainly produced by the bubble bursting mechanism. This mechanism is more effective with increasing wind speeds (22) and elevated water turbulences. In Venice, these turbulences are produced by cargo and taxi boats navigating on the different channels. During transport in the atmosphere, pure NaCl particles can react with H2SO4 or SO2 to produce transformed or aged sea salt particles. Those sea salt particles could show high concentrations of S besides Na and Cl. The correlation between the analyzed samples can be represented in the FA model by the factor scores. Considering the scores of factor 1 and 2 in Figure 1c, it is obvious that there is no correlation between both factors; they seem to be independent from each other, and moreover three different sample groups can be differentiated out of this graph. The first group is explained by factor 2 and includes those samples that were collected during the last two sampling periods on the small particle stages of the May impactor (cutoffs: 2, 1, and 0.5 µm). This means that high NaCl concentrations are particularly associated with the smaller particle size fraction. Their presence can probably be explained by the higher number of visitors as compared to the other sampling periods and by the opening of a window 7 min before and after 1 hour of sampling during the last period. The heavy winds from outside caused strong circulation indoors, increasing the outdoor aerosol concentration. The second group contains those samples that were associated with the large particle stages (cutoffs: 20, 8, and 4 µm) and is characterized by factor 1. These results indicate that the majority of particles rich in Ca, associated with other elements, as well as the aluminosilicates belong to the large particle size fraction. The remaining samples in the third group cannot be classified to one specific factor but show some correlation with both factors. These five samples are characterized, as will be discussed in more detail below, by high amounts of organic material and include elements like S, Fe, Zn, Pb, and K. The majority of these samples were collected on the small particle stages during the second sampling period and probably represent a smaller anthropogenic factor. This third group refers to an additional factor 3, which can indeed be obtained by including three instead of two factors into the FA model. In this way, the scores of factors 1 and 3 for each of the analyzed samples seems to be clearly correlated except for the five samples that can only be characterized by factor 3. Thus, based on the FA results, the total experimental data set from the first campaign can be described by two major factors and one minor factor. A similar procedure was followed for the FA on the data matrix of the 48 samples collected indoors during campaign 2. The same 14 variables were considered in the data matrix, and based on the estimation criteria, a FA model with two factors was also selected. The factor loadings of both factors are illustrated visually in Figure 2a,b. Factor 1 contains three major particle types: Ca-rich particles in combination with Si, Cl, and S; aluminosilicates; and sea salt particles. Based on the factor score results, it can be associated with the larger particle size fraction. Factor 2 is characterized on one hand by high loadings for S and lower ones for K, Ca, Fe, Zn, and Pb and on the other hand, in anti-correlation, by lower loadings of Cl, Si, Al, and Mg. Based also on the factor scores, these results suggest that high abundances
FIGURE 2. Factor analysis results of campaign 2, PA model with two factors. (a) Factor loadings of factor 1. (b) Factor loadings of factor 2.
of small organic particles relatively rich in S, K, Ca, Fe, Zn, Mn, and Pb correspond to low abundances of particles containing aluminosilicate elements and vice versa. By taking into account three factors instead of two, the aluminosilicate particles are separated from factor 1 and are represented by the third factor. Compared to campaign 1, NaCl is no longer a separate factor but is included in factor 1, in contrast with the minor third factor containing high amounts of organic material and including S, Fe, Zn, Pb, and K, which was identified as the second factor in campaign 2. Hierarchical Cluster Analysis. Particle classification into different groups based on their chemical composition was achieved by HCA. The minimum in the CAIC curve was used for each of the analyzed samples as an indication for the correct number of clusters to be taken into account. Figure 3 illustrates the results obtained for the HCA on a set of 500 particles. Based on the CAIC curve (Figure 3a), six different particle types could be distinguished. The corresponding dendrogram, cut at six clusters, is represented in Figure 3b. The visual representation of the mean value of each variable in a cluster and the cluster populations for this sample are presented in Figure 3, panels c and d, respectively. In the following paragraphs, the clustering results for the indoor aerosol samples will be discussed; a comparison will be made between the indoor and outdoor compositions, and finally the particle analysis results for the two possible indoor aerosol sources are represented. (1) Indoor Aerosols. Campaign 1. Depending on the sample, four to nine particle types were distinguished; the majority showed six to eight types. The comparison between the impactor samples, collected on December 4 in the morning and afternoon, revealed only small differences in abundance. Both sampling periods are dominated, on stages 1-5, by Ca-rich particles in combination with S, Si, and Cl and sometimes Fe and K. For possible sources, reference is made to the FA results. Aluminosilicates were found on all six impactor stages but in lower abundances
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FIGURE 3. Hierarchical cluster analysis results of one of the analyzed samples. (a) Consistent akaike criterion. (b) Dendrogram cut at six groups. (c) Mean value of the variables in each cluster. (d) Cluster population.
(14.5%). Fe-rich particles in combination with S and or Zn, organic S-rich particles, and pure organic particles sometimes containing some S, Ca, Si, Fe, and Zn were mainly detected in the submicrometer particle class (0.5-1 µm). These three particle types can probably be assigned to anthropogenic sources; they can easily penetrate to the indoor environment due to their small diameter. They were
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also detected on stages 4 and 5 but to a lesser extent. Due to technique limitations, we are not able to identify the exact nature of the organic material, meaning that these particles could consist of several types of materials including elemental carbon (black soot) or NH4NO3 as well as organic compounds. Sometimes it is possible to distinguish soot particles from other “low spectrum” particles based on their shape, but no manual SEM-EDX analysis was performed yet to investigate this. Low abundances of Pb-rich particles (∼5%) associated with K and organic material were also identified in the smallest size fraction. The exhaust particles produced by the combustion of leaded petrol during car traffic from and to Venice, Mestre, and Marghera can be considered as the main source of Pb-rich particles because the majority of taxi boats, used for the transport of people and goods, use diesel oil. On December 5, the Ca-rich particles as well as the aluminosilicates could be detected on the same stages as mentioned for December 4, but their relative abundances seemed to be suppressed, sometimes even to a large extent, by the presence of NaCl and crystallization products such as CaSO4, Na2SO4, K2SO4, and KCl. The stormy wind is responsible for the more efficient production of sea salt particles and associated crystallization products. The increase of this outdoor contribution to the indoor museum environment can probably be explained by the larger number of visitors. Additionally low abundances of Fe-rich particles were found in the afternoon on stages 1, 3, 4, 5, and 6. The outdoor contribution was even more pronounced in the samples collected in the afternoon, due to the fact that before and after 1 h of sampling, the window was opened for a short period. Particles rich in organic material, in combination with the same elements as mentioned before, were found on stages 5 and 6. For both days, 93% of the samples were also characterized by certain amounts of pure CaSO4 particles, sometimes containing even traces of Si and Cl or K. Campaign 2. Depending on the sample, 5-10 different groups could be detected, with the majority of samples also showing six to eight groups. Ca-rich particles in combination with S, Si, and Cl and sometimes Fe, K, and Al were found in all samples and seemed to be the most abundant particle type on the first four stages. The percent abundance tends to decrease with the particle diameter. The majority of pure Ca-rich particles was, as for the first campaign, detected on stages 4 and 5 with a mean diameter of 2.1 and 1.2 µm, respectively. Aluminosilicates composed of Si, Al, and Ca as the major elements and of K, Cl, Fe, and S as minor elements were present at all stages with a mean abundance of 11%. Organic material in high abundances was again predominantly found on stages 5 and 6 as pure organic particles, for which no elements with Z < 11 could be detected, and in association with high amounts of S. Pure Cl- and Na-rich particles were, when present, only found on stage 5. Aged or transformed sea salt particles were only detected a few times. The percent abundance was determined to be below 11%. The highest percentage of Fe-rich particles was present on stages 5 and 6 as pure Fe or Fe2O3 particles or sometimes in combination with S as Fe2(SO4)3. This combination with S can be the result of reactions between iron oxides and H2SO4 during metallurgical combustion processes (23). Sometimes, elements like S and Si associated with Ca and Cl were present on other stages with an abundance of 1.2-3.6%. CaSO4 particles were detected in 77% of the samples; 54% of them were present as pure CaSO4 and 46% in combination with
to a somewhat larger extent inside the museum, especially for Ca. In some of the samples, pure NaCl or transformed sea salt was found also. The contribution of marine particles to the total aerosol abundance decreased with smaller particle sizes and became negligible for the last stage (0.7 µm).
FIGURE 4. Aluminosilicate and Ca-rich particle abundances indoors and outdoors for three sampling periods during campaign 2.
Si and or Cl. Traces of Cu-, Zn-, and Ti-rich particles were only identified in 12% of the samples with abundances below 4%, and no Pb-rich particles were found. In general, the same particle types could be distinguished for both campaigns, and the differences in abundance can mainly be attributed to the different experimental setup and weather conditions during both campaigns. No significant differences were observed between samples collected in the morning and in the afternoon for both campaigns. (2) Comparison Indoor-Outdoor Aerosol Composition. The Ca-rich particles in combination with Mg, Si, Cl, and S in the largest size fraction (6.3 µm) seemed to be present in outdoor air in comparable amounts for the three sampling periods, accounting for up to 45%. Indoor the same particle type could be detected in association with traces of other elements like K, Al, Fe, and Na and with an abundance of around 80%. The fact that the indoor relative particle abundance appeared to be almost twice as high as the one outdoors, as illustrated in Figure 4, is indicative of the existence of one or more indoor Ca-rich aerosol sources, for a strong accumulation and resuspension of this particle type indoors or for the presence of some outdoor sources of similar particle types. The coagulation with submicrometer particles at the surface of these Ca-rich particles could provide a possible explanation for the larger number of elements present in the Ca-rich particles indoors. The differences between the indoor and outdoor Ca-rich particle abundance become smaller with decreasing particle diameters down to 2.1 µm. Up to this size, Ca-rich particles in combination with Si, S, Mg, Cl, and some trace elements remain the dominant particle type both indoors and outdoors. When going down to even smaller aerosols (0.9 µm), this particle type seems to appear as pure Ca-rich particles or sometimes Ca associated with S and Si but without Cl, and it almost disappears on the smallest particle stage (0.7 µm). No significant traces of other elements like K, Al, Fe, and Na were found in the last two size fractions. CaSO4 particles could be detected on all stages, inside as well as outside, but no clear tendency was found in their abundance. Marine particles with NaCl as the main component on the first two stages (6.3-3.8 µm) were also mixed together with other elements (S, K, Ca, Si) and this
Compared to the Ca-rich particle abundances, opposite results were found for the aluminosilicate particle abundance (Figure 4), which was twice as abundant outside the museum (20%) than inside (9.8%) for the largest size fraction (6.3 µm). Again additional trace elements could be detected in the indoor aluminosilicate particles. Gradually the contrast between the indoor and the outdoor aluminosilicate abundance and composition diminishes with decreasing particle size. The smallest particles (0.7 µm) contributed only 6% to the total aerosol abundance. Anthropogenic particles rich in Fe and associated with Cl, Si, S, and Ca could on the largest particle stages (6.3-3.8 µm) only be identified in the outdoor samples. The percent abundance increased with smaller aerosol particles and from stage 4 (2.1 µm) down these anthropogenic particles were also detected indoors. Similar results were obtained for the organic material that was also found on the first two stages (6.3-3.8 µm) only in the outside environment, and this often in combination with low concentrations of Cl, K, Ca, Si, and S. On the following stages, organic material appeared as pure organic particles, containing only low-Z elements (Z < 11) or in combination with high S concentrations. The abundances inside and outside the museum became also comparable on the last two stages (0.9-0.7 µm), and on these stages organic material could be identified as the main particle type with mean abundances up to 27% and 60%, respectively. Certain amounts of organic material were also found in some of the anthropogenic particles, discussed above. The general trend that particle abundances became comparable indoors and outdoors in the smallest size fraction is due to the higher mobility of smaller particles. (3) Composition of Two Possible Indoor Aerosol Sources. The SEM-EDX results confirm clearly that decomposition products arising through the aging of wall plaster or coatings present in the exhibition room are an obvious source for CaSO4- and Ca-rich aerosols found in the largest size fraction. Based on the minimum of the CAIC curve, obtained from the IDAS clustering results of the wall plaster powder, three different particle clusters could be distinguished for each cluster with an average particle diameter of 7.6 µm. The dominant particles types were indeed identified as CaSO4 (75%) and lesser amounts of Si- and Ca-rich particles (18%) associated with low concentrations of S, which are known to be the basic compounds of plaster. The remaining 7.3% (composed of Si, Ca, S, Mg, and traces of Fe, K, Cl, Mg, Al, and Zn) can probably be assigned to mixing with impacted soil dust on the walls. The dust on the vertical wood panels was composed of 90% CaSO4 particles with an average diameter of 9.3 µm. Aluminosilicate particles, associated with some organic material, contributed 7.7% to the total particle abundance and only 2.3% consisted of S-rich particles in combination with Cr. Optimization of SEM-EDX Mappings on the JEOL JSM 6300. The results obtained from the 60 collected X-ray mappings indicate clearly that the indoor aerosol particles (>8 µm) containing Ca, Si, Al, S, K, Mg, Na, Cl, and Fe are
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FIGURE 5. Heterogeneity study on a giant indoor aerosol particle. (a) SEM-EDX X-ray elemental mappings of Al, Si, K, and Ca in the giant aerosol particle. (b and c) Application of the Image Math program on the X-ray elemental mappings. Ca and Si are clearly associated, and a few aluminosilicate particles as well as some smaller CaSO4 particles seemed to be adsorbed at the particle surface.
FIGURE 6. SPM X-ray elemental intensity mappings of different elements present in one particle.
heterogeneous. They mainly consist of Ca and Si with small particles adsorbed at their surface, which were identified as aluminosilicates, CaSO4 particles, or very small Fe-rich
particles. Na and Cl were detected together in salt crystals or as a coating on the particle surface. These giant particles are probably the result of the coagulation of giant Ca-Sirich particles, produced by the decomposition of wall plaster and cement through aging or introduced from the outside, with small particles present in the indoor environment. An example of the processing of the X-ray mappings of a Ca-rich particle, using Image math, is illustrated in Figure 5 a-c. Giant Aerosol Particle Analysis Using SPM. Preliminary results obtained from the elemental X-ray intensity maps of 13 giant indoor aerosol particles confirm clearly the SEMEDX mapping results described above. The analyzed particles could indeed be considered as heterogeneous, as illustrated in Figure 6, and element associations appeared to be similar. Due to the better detection limits over SEM-EDX, elements from Z ) 22 to Z ) 30 were frequently detected in the 27 PIXE energy spectra. Of these elements, Fe and Zn were identified in over 92% of the spectra, sometimes down to concentrations of 240 and 90 ppm, respectively, and they are indicative for industrial processes. An additional correlation seems to exist between Ti and Cr. These elements were simultaneously present in 41% of the spectra and can also be attributed to industrial processes. The five different elemental concentrations obtained for Z > 22 inside one single aerosol particle are illustrated in Figure 7. Submicrometer Aerosol Analysis Using STEM-EDX. Interpretation of the 63 X-ray spectra resulted in the
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thropogenic emissions of SO2. Sometimes NaCl coatings were present as well. Generally, it can be concluded that the signal yield, particularly for particles in the order of 100 nm, is very low. Under the present conditions, it only seems possible to perform morphological studies and not chemical analysis on particles below 100 nm. Better results are expected from nanoprobe analyses in the near future.
Acknowledgments This work was, in its later stage, financed by the European Commission in the framework of AER, the Assessment of Environmental Risk Program (under Contract ENV4-CT950088). The authors want to thank the Museum Director Prof. Giandomenico Romanelli and co-worker Dr. I. Ariano for the cooperation at the museum. L.D.B. acknowledges financial support by the Instituut voor de Bevordering van het Wetenschappelijk-Technologisch Onderzoek in de Industrie (IWT) and Prof. B. Treiger and Dr. I. Bondarenko for providing the IDAS software.
Literature Cited (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
FIGURE 7. Elemental concentrations (ppm) obtained for Z > 22 inside one single aerosol particle.
identification of two major groups of indoor submicrometer aerosol particles. Si-rich particles accounted for up to 59% of the analyzed aerosols, of which 84% were associated with S, showing an average diameter of 0.5 µm. Only 16% were identified as pure Si-rich particles with an average diameter of 0.1 µm. The shape of these Si-rich particles was found to be spherical or irregular. These particles were probably produced by combustion processes. S concentrations, associated with low Cr concentrations, refer also to an anthropogenic origin. Na and K were detected as minor elements. Some 35% of the remaining aerosol particles with an average diameter of 0.5 µm were identified as aluminosilicates with Al, Si, and S as major elements and Mg, K, P, Na, and Cl as minor elements. Based on the morphological information, aluminosilicates appeared to be present as both fly ash and soil dust particles. The dominant S peak, detected in 64% of these particles, could indicate the existence of secondary reactions during an-
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(13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23)
Yocom, J. E. J. Air Pollut. Control Assoc. 1982, 32, 500-520. Spengler, J. D.; Sexton, K. Science 1983, 221, 9-17. Thomson, G. Stud. Conserv. 1965, 10, 147-167. Baer, N. S.; Banks, P. N. Int. J. Museum Manage. Curatorship 1985, 4, 9-20. Brimblecombe, P. Atmos. Environ. 1990, 24B, 1-8. Hisham, M. W. M.; Grosjean, D. Environ. Sci. Technol. 1991, 25, 857-862. Owen, M. K.; Ensor, D. S. Atmos. Environ. 1992, 26A, 21492162. Ligocki, M. P.; Salmon, L. G.; Fall, T.; Jones, M. C.; Nazaroff, W. W.; Cass, G. R. Atmos. Environ. 1993, 27A, 697-711. Raunemaa, T.; Kulmala, M.; Saari, H.; Olin, M.; Kulmala, M. H. Aerosol Sci. Technol. 1989, 11, 11-25. Nazaroff, W. W.; Salmon, L. G.; Cass, G. R. Environ. Sci. Technol. 1990, 24, 66-77. Nazaroff, W. W.; Cass, G. Atmos. Environ. 1991, 25A, 841-852. Camuffo, D.; Tampieri, F.; Zambon, G. Boundary-Layer Meteorol. 1979, 16, 83-92. Camuffo, D.; Cavaleri, L. Atmos. Environ. 1980, 14, 1255-1262. Hayat, M. A. Principles and Techniques of Electron Microscopy; MacMillan Press Ltd.: London, 1989. De Bock, L. A.; Van Malderen, H.; Van Grieken, R. Environ. Sci. Technol. 1994, 28, 1513-1520. Doolitle, R. L. Nucl. Instrum. Methods Phys. Res. Sect. B 1985, 9, 344. Treiger, B.; Bondarenko, I.; Van Malderen, H.; Van Grieken, R. Anal. Chim. Acta 1995, 317, 33. Bernard, P. C.; Van Grieken, R. E.; Eisma, D. Environ. Sci. Technol. 1986, 20, 467-473. Leysen, L.; Roekens, E.; Van Grieken, R. Sci. Total Environ. 1989, 78, 263-287. Bye, G. C. Portland Cement, Composition, Production and Properties; Pergamon Press: London, U.K. 1983. McCrone, W. C.; Delly, J. G. The Particle Atlas III; Ann Arbor Science Publishers Inc.: Ann Arbor, MI, 1973; pp 670-674. Deleeuw, G. Tellus 1986, 38B, 51-61. Xhoffer, C.; Bernard P.; Van Grieken, R. Environ. Sci. Technol. 1991, 25, 1470-1478.
Received for review February 29, 1996. Revised manuscript received June 19, 1996. Accepted June 21, 1996.X ES9602004 X
Abstract published in Advance ACS Abstracts, September 15, 1996.
