- Email: [email protected]
Indoor and outdoor air carbonyl compounds correlation elucidated by principal component analysis
ARTICLE IN PRESS
Environmental Research 106 (2008) 139–147 www.elsevier.com/locate/envres
Indoor and outdoor air carbonyl compounds correlation elucidated by principal component analysis A. Santarsiero, S. Fuselli Istituto Superiore di Sanita`, Dipartimento di Ambiente e Connessa Prevenzione Primaria, Viale Regina Elena 299-00161 Rome, Italy Received 22 March 2007; received in revised form 21 September 2007; accepted 25 October 2007 Available online 3 December 2007
Abstract In this study indoor and outdoor air carbonyl compounds concentrations data are processed by means of principal component analysis (PCA). The analysis pointed to the carbonyl compounds sources as well as to their mutual interrelations. A global six sources (components) solution, accounting for the joint variability of the measured variables, was obtained. The existence of a linear function connecting outdoor and indoor components allowed for an exchange model between indoor and outdoor carbonyl compounds to be outlined. The different sources of carbonyl compounds were tentatively identified. Overall, this work demonstrates the presence of a delicate balance between indoor and outdoor carbonyl compounds contamination with the two compartments (indoor and outdoor) engaged in a close relationship. r 2007 Elsevier Inc. All rights reserved. Keywords: Principal component analysis; Indoor; Outdoor; Air; Carbonyl compounds
1. Introduction Carbonyl compounds in urban air have received attention due to their potential adverse health effects on humans and due to their important role in atmospheric chemistry, as precursors to free radicals, ozone, and peroxyacyl nitrates (Carlier et al., 1986; Grosjean et al., 1993a, b, 1996; Carter, 1995). Carbonyl compounds can be produced directly from incomplete combustion of biomass, fossil fuels or both, and through the atmospheric photooxidation of hydrocarbons (Satsumabayashi et al., 1995). In indoor air, some carbonyl compounds may be released from building materials, furniture, and consumer products and through reactions between indoor ozone and alkenes (Crump and Gardiner, 1989; Kelly et al., 1999). Cigarette smoke is another significant indoor source of several carbonyls (Lo¨froth et al., 1989; Morrison and Nazaroff, 2002). Ambient air concentrations of carbonyl compounds in urban and rural areas have been widely measured Corresponding author. Fax: +39 0649387083.
E-mail address: [email protected] (A. Santarsiero). 0013-9351/$ - see front matter r 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.envres.2007.10.011
(Grosjean, 1982; Shepson et al., 1991; Szilagyi et al., 1991; Possanzini et al., 1996; Slemr and Junkermann, 1996; Granby and Christensen, 1997; Montero et al., 2001; Nguyen et al., 2001; Ba´ez et al., 2001). Studies on indoor/ outdoor carbonyl compounds have been also reported (Zhang et al., 1994a; Reiss et al., 1995; Williams et al., 1996; Ba´ez et al., 2003). Zhang et al. (1994a) measured nine aldehydes in both indoor and outdoor air of six New Jersey homes, which showed the indoor to outdoor ratios (I/O)41. Feng et al. (2004) detected 18 carbonyl compounds in both indoor and outdoor air. In outdoor air, formaldehyde was the most abundant compound, followed by acetaldehyde while for the indoor concentrations the order was reversed. Fuselli et al. (2006) detected eight carbonyl compounds (formaldehyde, acetaldehyde, acetone+acrolein, propionaldeyde, benzaldehyde, n-butyraldehyde, isovaleraldehyde, and valeraldehyde) simultaneously in kitchen, living room, and apartment outdoor balcony of 10 apartments, in the residential area of Rome. The results confirmed the well-known finding of most studies reported in literature, that the indoor air pollutant concentrations are much higher than the outdoor concentrations.
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
140
As listed in Table 1 (Fuselli et al., 2006), the main statistical parameters of the obtained carbonyl concentrations, showed a wide variability range of carbonyl compound concentrations. Such wide variability of concentrations was unexpected, since apartments were selected with the same constant defined elements: two separately tested rooms (kitchen and living room) and a balcony all having been totally refurbished in the last 10 years, and with same number of apartment occupants. However, from the large amount of information derived from the carbonyl compounds concentration correlations matrix (Table 2), only three paradigmatic cases were selected: acetone+acrolein, acetaldehyde and n-butyraldehyde. In the case of acetaldehyde, the kitchen concentrations are strongly related to living room concentrations (r ¼ 0.70, po0.0001) while both indoor concentrations are independent of the outdoor concentration (r ¼ 0.09, p ¼ 0.56, r ¼ 0.07, p ¼ 0.68), thus pointing to an indoor source. The same is true (and still more cogent) for acetone+acrolein showing a correlation coefficient near to unity (r ¼ 0.93, po0.0001) between kitchen and living room and a lack of correlation with outdoor concentrations (r ¼ 0.04, p ¼ 0.819, r ¼ 0.01, p ¼ 0.958). In the case of n-butyraldehyde the correlation coefficients pointed to a strict link between indoor and outdoor concentrations (r ¼ 0.61, po0.0001 for outdoor, and indoor r ¼ 0.73, po0.0001 for kitchen and living room).
Indoor carbonyl compounds were abundant in the following order: formaldehyde, butyraldehyde, acetone+acrolein, acetaldehyde, valeraldehyde, propionaldehyde, isovalealdehyde, and benzaldehyde). The same carbonyl compounds abundance (in the order: butyraldehyde, formaldehyde, acetone+acrolein, acetaldehyde, propionaldehyde, valeraldehyde, benzaldehyde, and isovalealdehyde) was shown for the outdoor with the exception of butyraldehyde and benzaldehyde. Based on the above results of Fuselli et al. (2006), the practice of limiting the measurements only to outdoor air was considered not appropriate for estimating indoor air carbonyl compounds, as shown also by other studies (Schneider et al., 1999). Since outdoor air quality represents a factor for the removal and dilution of indoor pollutants, in this work we process the obtained carbonyl compounds concentrations data set in order to go deeper into the links existing between indoor and outdoor sources. This was now performed by means of principal component analysis (PCA). To get a clearer picture of the exchange between outdoor and indoor air carbonyl compounds pollution, we performed PCA separately on outdoor and indoor sub-sets data. The relationship between outdoor and indoor sources was clarified in the present work and the joint analysis of component loading and score spaces allowed for source identification.
Table 1 Simple descriptive statistics of indoor and outdoor carbonyl compounds concentrations (mg/m3) data Variables
Na
Mean
Median
Mode
Std. Dev.
Min
Max
Quantile 95%
Quantile 5%
Kitchenacetaldehyde Living roomacetaldehyde Outdoooracetaldehyde Kitchenacetone+acroleina Living roomacetone+acrole Outdooracetone+acroleina Kitchenpropionaldehyde Living roompropionaldehyde Outdoorpropionaldehyde Kitchenn-butyaldehyde Living roomn-butyraldehyde Outdoorn-butyraldehyde Kitchenbenzaldehyde Living roombenzaldehyde Outdoorbenzaldehyde Kitchenisovaleraldehyde Living roomisovaleraldehyde Outdoorisovaleraldehyde Kitchenvaleraldehyde Living roomvaleraldehyde Outdoorvaleraldehyde Kitchenformaldehyde Living roomformaldehyde Outdoorformaldehyde
40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 39b 40 40 40 40
9.37 8.03 2.34 9.44 8.44 2.46 2.63 2.48 1.0 10.99 10.79 4.91 0.84 0.56 0.24 0.90 0.64 0.22 3.25 2.17 0.48 13.18 12.31 2.75
9.90 7.75 1.95 7.80 6.40 2.00 2.70 2.30 0.90 8.60 6.00 2.80 0.75 0.50 0.20 1.00 0.60 0.20 2.85 2.00 0.35 12.90 10.55 2.45
10.00 8.60 1.40 5.00 6.20 1.40 2.20 1.40 0.80 9.00 6.70 2.00 0.05 0.05 0.05 0.05 0.05 0.05 2.30 1.80 0.05 7.50 9.40 2.00
3.69 3.62 1.30 8.84 8.63 1.45 0.92 1.24 0.50 8.68 11.52 5.29 0.59 0.42 0.17 0.67 0.51 0.17 1.68 1.29 0.43 4.28 6.26 1.13
0.80 3.20 1.10 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.70 0.10 0.05 6.90 4.80 1.20
19.70 20.90 7.60 58.00 57.30 6.10 4.60 6.00 2.30 34.60 44.40 26.20 2.20 1.80 0.70 22.20 2.00 0.70 7.80 7.00 1.60 23.00 32.90 7.00
16.35 15.35 5.10 16.50 16.25 5.65 4.15 5.65 2.05 33.05 37.35 15.85 2.10 1.30 0.60 2.00 1.55 0.50 6.90 5.5 1.25 21.75 25.90 4.45
4.45 3.45 1.20 2.55 2.25 0.95 0.95 1.10 0.20 0.70 1.80 1.00 0.05 0.05 0.05 0.05 0.05 0.05 1.20 0.6 0.05 7.50 5.50 1.40
a
N ¼ number of observations (number of samples). Detection limit for carbonyl compound concentration is 0.05 mg/m3.
b
Table 2 Concentration correlations of indoor and outdoor air carbonyl compounds 2
3
4
5
6
7
Kitchacetal 1 Livacetal 2 Outacetal 3 Kitchac+acrol 4 Livac+acrol 5 Outac+acrol 6 Kitchpropion 7 Livpropion 8 Outpropion 9 Kitchbutyr 10 Livbutyr 11 Outbutyr 12 Kitchbenzal 13 Livbenzal 14 Outbenzal 15 Kitchisovale 16 Livisovale 17 Outisovale 18 Kitchvale 19 Livvale 20 Outvale 21 Kitchforma 22 Livforma 23 Outforma 24
1 0.70 0.09 0.09 0.10 0.04 0.23 0.15 0.04 0.30 0.31 0.29 0.30 0.07 0.16 0.01 0.26 0.26 0.54 0.36 0.16 0.29 0.11 0.24
1 0.04 1 0.07 0.02 1 0.14 0.12 0.93 1 0.01 0.45 0.20 0.17 1 0.01 0.17 0.32 0.20 0.37 1 0.07 0.51 0.08 0.07 0.33 0.20 0.06 0.36 0.13 0.20 0.61 0.17 0.19 0.05 0.10 0.02 0.08 0.08 0.12 0.00 0.20 0.10 0.05 0.21 0.08 0.07 0.16 0.09 0.18 0.22 0.20 0.10 0.27 0.19 0.18 0.58 0.06 0.41 0.01 0.07 0.27 0.28 0.13 0.48 0.27 0.22 0.48 0.30 0.10 0.05 0.39 0.26 0.23 0.58 0.12 0.30 0.19 0.20 0.22 0.37 0.17 0.62 0.11 0.09 0.56 0.19 0.54 0.11 0.07 0.02 0.33 0.09 0.67 0.11 0.06 0.16 0.11 0.00 0.05 0.53 0.22 0.28 0.49 0.19 0.40 0.09 0.19 0.11 0.18 0.12 0.34 0.21 0.13 0.22 0.10 0.21 0.16 0.54 0.36 0.38 0.62 0.16
8
9
10
11
12
13
14
15
16
17
18
19
20
1 0.40 1 0.05 0.13 1 0.05 0.07 0.84 1 0.15 0.24 0.61 0.73 1 0.13 0.08 0.34 0.44 0.40 1 0.35 0.28 0.34 0.32 0.34 0.52 1 0.33 0.30 0.52 0.48 0.42 0.45 0.57 1 0.29 0.10 0.49 0.57 0.59 0.74 0.44 0.62 1 0.33 0.52 0.55 0.69 1 0.54 0.19 0.41 0.46 0.51 0.45 0.38 0.46 0.44 0.35 0.32 0.54 0.84 0.50 0.57 1 0.29 0.34 0.03 0.01 0.04 0.00 0.16 0.33 0.28 0.42 0.40 1 0.15 0.03 0.33 0.23 0.19 0.12 0.11 0.22 0.14 0.06 0.21 0.28 1 0.41 0.30 0.28 0.37 0.37 0.33 0.46 0.59 0.45 0.48 0.68 0.15 0.03 0.12 0.03 0.05 0.19 0.08 0.14 0.03 0.13 0.04 0.19 0.13 0.49 0.20 0.11 0.21 0.02 0.10 0.11 0.07 0.15 0.09 0.13 0.09 0.17 0.02 0.32 0.28 0.44 0.04 0.08 0.00 0.15 0.19 0.50 0.24 0.16 0.60 0.00 0.02
21
22
23
24
1 0.11 1 0.27 0.36 1 0.51 0.46 0.19 1
ARTICLE IN PRESS
1
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
Compounds
141
ARTICLE IN PRESS 142
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
2. Materials and methods 2.1. Carbonyl concentration data The data set used in this work has been generated by the study of Fuselli et al. (2006) on carbonyl compounds concentrations in indoor air and related outdoor balconies of 10 apartments in Rome residential area. The data set is available as support material. Table 1 reports the simple descriptive statistics of the raw data set. Such carbonyl compounds concentration data are referred to a consecutive 10day sampling of carbonyl compounds carried out during a year, in the months of May, September, November, and February. Simultaneous samplings took place at kitchen, living room and outdoor apartment. The apartments were selected with similar factors, such as traffic conditions, building features, floor area, ventilation, and layout. Carbonyl compounds were sampled using the passive Radiello Aldehyde samplers (code no. 165) and the chemical analysis procedure met the requirements of the US EPA Method TO-11A (US EPA, 1999, US EPA IP-6A, ASTM D5197). The carbonyl compounds detected were formaldehyde, acetaldehyde, acetone+acrolein (quantified as sum), propionaldehyde, benzaldehyde, nbutyraldehyde, isovaleraldehyde, and valeraldehyde. The sum of acetone and acrolein was reported because they could not be separated by the used analytical method.
Fig. 1. Eigenvalue distribution for the whole data set, in abscissa the component number, in ordinate the eigenvalue. The arrow points to the scree test selected number of signal components.
seasonal effect on components was assessed by means of analysis of variance.
2.2. Statistical analyses PCA was applied to a 40 24 matrix (see table of whole data set in support material), having as statistical units the 40 independent measurements [four measurements for each of the 10 apartments: one measurement for each of the four given months (September, May, November, February)] and as variables the 24 measurements corresponding to the eight carbonyl compounds concentrations relative to two indoor locations (kitchen and living room) and one outdoor (balcony) location. PCA was carried out both on the whole data set and separately (Richardson et al., 2006) on the indoor and outdoor data sub-sets. The indoor and outdoor extracted component scores were then correlated to each other. A model, able to predict the first component of indoor carbonyl compounds by means of the first two outdoor components, was built by means of multiple linear regressions. The whole data set is a matrix having the apartments (40 statistical units) as rows and the measured carbonyl compounds concentrations (24 variables) as columns. PCA projects this multidimensional space into a derived space spanned by new variables, called principal components, ordered in decreasing amount of explained variability (Santarsiero et al., 1996; Benigni and Giuliani, 1994). Thus, the first components will retain the maximal amount of correlated information (that is, indoor/outdoor correlation) confining the uncorrelated portion of information to higher order components. This allows for a strong compression of the original information by simply retaining the first extracted components and discarding the others. The components are independent by construction to each other, thus each component points to a linear independent source of carbonyl compounds. Descriptive statistics and distribution analysis were performed for all the variables. Computations were performed with the statistical software SAS for personal computers. A direct visual scree test (Benigni and Giuliani, 1994; Crescenzi and Giuliani, 2001; Giuliani et al., 2001) on the eigenvalue distribution allowed us to select the bona fide signal components (Fig. 1). The same procedure was used for the sub-set data matrix with 40 statistical units and eight variables (outdoor data set) (Fig. 2(a)) and for the sub-set data matrix with 40 statistical units and 16 variables (indoor data set) (Fig. 2(b)). The mutual correlations between indoor and outdoor components were assessed by means of Pearson correlation coefficients. The model explaining the indoor component by means of the first two outdoor components was built by classical multiple regression analysis. The
3. Results and discussion 3.1. Data structure The eigenvalue distribution on the components for the whole set is reported in Fig. 1. The arrow points to the putative beginning of the noise floor: a six-component solution explaining 77.45% of the total variability is detected as bona fide signal by means of the scree test criterion. 3.2. Carbonyl sources interpretation of the components From the interpretative point of view, the major merit of PCA resides in the possibility to attach an indoor/outdoor source of carbonyl compounds to the components (Giuliani et al., 2001; Burstyn, 2004). Interpretation is based on component loadings, that is, on the correlation coefficients between original variables (carbonyl compounds) and the components. The extracted dimensions (components) represent the ‘‘linearly independent systems’’ organizing the data. The carbonyl compounds more correlated with the specific components are the ones more important to assign sources. Each carbonyl compound participates in all the extracted components, to different degrees, so fulfilling the notion that the same compound can come from more than one source. The relationship between observed variables and principal components (and thus carbonyl compounds sources) in terms of loadings is reported in Table 3. The first principal component is by far the major order parameter structuring the observed variability (28.67% of explained variance). In order to assign a meaning to this component, we
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
143
Table 3 Whole set factor loadings pattern
Fig. 2. Eigenvalue distribution for the outdoor data set (Fig. 2(a)) and indoor data set (Fig. 2(b)), in abscissa the component number, in ordinate the eigenvalue. The arrow points to the scree test selected number of signal components.
considered the carbonyl compounds variables possessing the highest absolute loadings, that is, the carbonyl compounds showing the highest positive or negative correlation with component 1, and thus mostly involved in the corresponding indoor or outdoor carbonyl source. Inspection of the component loadings pattern (Table 2) readily shows that most of outdoor carbonyl compounds are loaded on the first component (F1). The first component (F1), can thus be named as ‘‘outdoor sources’’ with butyraldehyde negatively correlated in both indoor and outdoor locations, so pointing to a singular behavior of this compound with respect to others. The negative sign tells us that butyraldehyde has an opposite behavior with respect to the other compounds loaded on F1: high values of these compounds, as for F1 source, correspond to comparatively low values of butyraldehyde.
Variables
F1
F2
F3
F4
F5
F6
Kitchen acetaldehyde Living room acetaldehyde Outdoor acetaldehyde Kitchen acetone+acrolein Living room acetone+acrolein Outdoor acetone+acrolein Kitchen propionaldehyde Living room propionaldehyde Outdoor propionaldehyde Kitchen n-butyraldehyde Living room n-butyraldehyde Outdoor n-butyraldehyde Kitchen benzaldehyde Living room benzaldehyde Outdoor benzaldehyde Kitchen isovaleraldehyde Living room isovaleraldehyde Outdoor isovaleraldehyde Kitchen valeraldehyde Living room valeraldehyde Outdoor valeraldehyde Kitchen formaldehyde Living room formaldehyde Outdoor formaldehyde
0.20 0.13 0.50 0.38 0.34 0.54 0.45 0.52 0.39 0.54 0.60 0.53 0.58 0.66 0.86 0.77 0.75 0.86 0.36 0.15 0.75 0.12 0.17 0.54
0.68 0.72 0.33 0.30 0.39 0.39 0.10 0.10 0.33 0.47 0.38 0.40 0.11 0.04 0.03 0.16 0.22 0.01 0.38 0.60 0.14 0.52 0.37 0.56
0.36 0.42 0.47 0.26 0.17 0.46 0.29 0.36 0.53 0.38 0.49 0.53 0.50 0.03 0.05 0.36 0.01 0.26 0.57 0.20 0.11 0.36 0.02 0.19
0.24 0.21 0.38 0.45 0.35 0.20 0.60 0.03 0.18 0.29 0.25 0.22 0.25 0.16 0.07 0.32 0.06 0.22 0.32 0.15 0.20 0.33 0.53 0.05
0.31 0.23 0.08 0.63 0.61 0.02 0.26 0.30 0.03 0.11 0.16 0.06 0.35 0.41 0.01 0.12 0.18 0.02 0.04 0.27 0.06 0.20 0.29 0.24
0.23 0.15 0.02 0.22 0.35 0.32 0.11 0.36 0.02 0.13 0.07 0.12 0.04 0.14 0.18 0.01 0.36 0.19 0.22 0.54 0.02 0.39 0.37 0.36
F1 is mostly linked to outdoor sources, almost all the outdoor carbonyl compounds are significantly loaded on F1 and the most important variables for defining the significance of the component are outdoor benzaldehyde, outdoor isovaleraldehyde, and outdoor valeraldehyde. Component 2 (F2) is more linked to ‘‘indoor sources’’ predominantly acetaldehyde, and valeraldehyde. It is worth noting the case of the outdoor formaldehyde that is likewise charged both on first (F1) and second (F2) components. This points out two different sources (or sinks, if we imagine a dynamic indoor/outdoor balance) of this compound, the first (F1) being of probable outdoor origin and the second of dubious provenience. This behavior of formaldehyde allows us to grasp the meaning of the components that, even if being linear combinations of the initial variables, nevertheless give a picture of the studied phenomenon posited at a different level with respect to the original measures. Component 3 (F3) is linked to the ‘‘butyraldehyde singularity’’ that separates the concentration dynamics of this compound from the others. Component 4 (F4) is heavily loaded by kitchen propionaldehyde pointing to an ‘‘indoor source’’ typically kitchen source probably linked to materials or activities specifically of the kitchen. Component 5 (F5) is heavily negatively loaded by kitchen acetone+acrolein and living-room acetone+acrolein pointing to ‘‘an indoor source’’ of this compound separated from the main pollution sources. This finding is proven by the near to unity Pearson correlation coefficient
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
144
between kitchen acetone+acrolein and living-room acetone+acrolein (r ¼ 0.93, po0.0001) that in turn are only weakly correlated to other indoor and outdoor carbonyl compounds. Considering progressively higher order components, it becomes more difficult to distinguish a dominant key. Accordingly, we found it difficult to assign a source specificity to component 6 (F6). These difficulties are easily explained considering that each successive component accounts for a smaller amount of signal variability while it is more affected by both intrinsic and experimental noise. In conclusion we can say that benzaldehyde and isovaleraldehyde have a major relevance as outdoor sources, while butyraldehyde, acetaldehyde, and valeraldehyde as indoor sources. For formaldehyde we have an intermediate situation. The non-noisy character of the extracted components is proven by the fact that these components display a marked seasonal effect, as demonstrated by the results obtained from the analysis of variance using month effect as variability source. By means of the generalized linear model (GLM) applied to the six principal components we note that the first four principal components (F1, F2, F3, and F4) display a statistically significant variation among the months. In fact, we obtained, for the dependent variables (F1, F2, F3, and F4) on the considered months, the following level of significance: dependent dependent dependent dependent
variable: variable: variable: variable:
F1 F2 F3 F4
(F ¼ 18.08, po0.0001), (F ¼ 3.96, po0.0157), (F ¼ 3.56, po0.0238), (F ¼ 3.14, po0.0376).
This seasonal effect is difficult interpret due to the paucity of different time points, but it seems to suggest that in winter (lower temperatures) the pollution from the most important carbonyl compounds sources is lower than summertime. No significant apartment effect was highlighted by Analysis of variance so pointing to a substantial homogeneity of the different studied apartments.
3.3. PCA on the outdoor sub-set data PCA on the outdoor carbonyl compounds concentrations sub-set data, measured at the balcony of each apartment, points to a relatively simple two-component solution (Fig. 2a) with a first component measuring the ‘‘general outdoor sources’’ and a second component explaining the singular behavior of butyraldehyde. We chose a two-component solution as bona fide signal, explaining 72% of the total variability carried out by the carbonyl compounds concentration data. Table 4 (bolded) shows the outdoor carbonyl compounds in this sub-set possessing the highest absolute
Table 4 Outdoor factor loadings pattern Variables Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor
acetaldehyde acetone+acrolein propionaldehyde n-butyraldehyde benzaldehyde isovaleraldehyde valeraldehyde formaldehyde
Fout1
Fout2
0.74 0.76 0.58 0.18 0.80 0.90 0.78 0.77
0.15 0.41 0.53 0.91 0.36 0.25 0.27 0.21
loadings on the components and thus important for defining the meaning of the component itself. Component 1 (Fout1) is mainly driven by outdoor isovaleraldehyde, outdoor benzaldehyde, outdoor acetone+acrolein, and outdoor formaldehyde, while component 2 (Fout2) goes together with outdoor n-butyraldehyde so confirming the singular nature of this compound contamination. Outdoor n-butyraldehyde has a source different from the outdoor carbonyl compounds as also evident by PCA on the wholeset-data. Component 2 is mostly loaded by outdoor n-butyraldehyde that comes from ‘‘indoor sources’’ that are kitchen and living-room as above shown, this character of ‘‘sink’’ of the indoor contamination for Fout2 will be evident in the following. Only Fout1 displays a significant seasonal variation (po0.001), while this is not the case of Fout2, this could in principle be related to the fact that Fout1 is a source (a seasonally varied source allowing outdoor generated compounds to come into apartments) while Fout2 could be a sink (the outdoor deposit of internally generated pollution). 3.4. PCA on the indoor sub-set data The eigenvalue distribution on the components is reported in Fig. 2(b). We chose a five-component solution as bona fide signal, explaining 78% (Fig. 2(b), the start of noise floor is marked by an arrow) of the total variability carried out by the indoor carbonyl compounds concentrations data. Table 5 (bolded) shows the carbonyl compounds in this sub-set possessing the highest absolute loadings on the first components. Component 1 (Fin1) is mainly driven by kitchen isovaleraldehyde, living-room isovaleraldehyde, and kitchen benzaldehyde. Kitchen n-butyraldehyde and living-room n-butyraldehyde are charged on Fin1 with a negative sign, so confirming the singular nature of this compound. In fact component 3 is mostly loaded by indoor butyraldehyde that comes from an ‘‘indoor source’’ different from the sources of other indoor carbonyl compounds. This result mirrors the behavior of the whole data set. Component 2 (Fin2) is predominantly loaded by acetaldehyde, valeraldehyde, and kitchen formaldehyde
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
145
Table 5 Indoor factor loadings pattern Variables
Fin1
Fin2
Fin3
Fin 4
Kitchen acetaldehyde Living room acetaldehyde Kitchen acetone+acrolein Living room acetone+acrolein kitchen propionaldehyde Living room propionaldehyde Kitchen n-butyraldehyde Living room n-butyraldehyde kitchen benzaldehyde Living room benzaldehyde Kitchen isovaleraldehyde Living room isovaleraldehyde Kitchen valeraldehyde Living room valeraldehyde Kitchen formaldehyde Living room formaldehyde
0.228 0.751 0.092 0.339 0.202 0.848 0.054 0.135 0.433 0.395 0.445 0.540 0.347 0.423 0.532 0.531 0.568 0.278 0.058 0.337 0.420 0.051 0.436 0.317 0.643 0.162 0.541 0.291 0.707 0.032 0.506 0.331 0.678 0.416 0.206 0.291 0.609 0.122 0.046 0.316 0.891 0.105 0.060 0.123 0.798 0.109 0.201 0.156 0.372 0.596 0.490 0.076 0.178 0.654 0.274 0.213 0.019 0.607 0.338 0.304 0.006 0.319 0.169 0.414
Fin5 0.316 0.232 0.373 0.244 0.403 0.386 0.139 0.133 0.176 0.391 0.188 0.254 0.040 0.375 0.132 0.696
and again mirrors the behavior of the wholedata set. Component 3 (Fin3) as stated above, marks the singular indoor source of butyraldehyde. Component 4 (Fin4) identifies a specific acetone+acrolein pollution source. Component 5 (Fin5) points to a balance (opposite signs) between propionaldehyde and formaldehyde. 3.5. Correlation between indoor and outdoor In order to investigate both the presence and nature of indoor/outdoor air exchange, the correlation coefficients between indoor (Fin#) and outdoor (Fout#) were computed. Simple Pearson correlation highlights two statistically significant pairwise correlations between outdoor and indoor components, the first indoor component (Fin1) has a Pearson coefficient r ¼ 0.568 with the first outdoor component (Fout1) and a Pearson coefficient r ¼ 0.522 with the second outdoor component (Fout2). The link between indoor and outdoor data is further clarified by multiple regression analysis in which Fin1 is modelled by Fout1 and Fout2 in combination. Fig. 3 reports the prediction of the observed Fin1 (first principal component of indoor data) as estimated by the values of the two first outdoor components by means of the following equation: Fin1 ¼ 0:0023 þ 0:5586ðFout1Þ 0:5141ðFout2Þ.
(1)
The congruence between observed and estimated data is proof of the concept of exchange between indoor and outdoor compartments. The model was very significant showing an F value of 26.04 (po0.0001) and a Pearson coefficient r ¼ 0.77. The opposite signs of Fout1 and Fout2 in the equation allow us to identify Fout1 as a source for indoor global pollution (as measured by Fin1) and Fout2 as a sink. Globally the model tells us that a well-defined balance does exist between indoor and outdoor pollution.
Fig. 3. The prediction of the first indoor component by means of the first and second outdoor component is reported.
4. Conclusion Overall, global carbonyl compounds contamination was characterized by six different sources of which four having a seasonal variation. Furthermore, we observe a strong indoor/outdoor carbonyl compounds exchange that we can model with a fair accuracy. Simple outdoor carbonyl compounds contamination was characterized by a two-component solution, with a first component measuring the ‘‘outdoor sources’’ and a second explaining the singular behavior of butyraldehyde and acting as ‘‘sink’’ for indoor contamination. In conclusion, we can say that benzaldehyde and isovaleraldehyde are mainly pollutants coming inside apartments from the outside environment, while butyraldehyde, formaldehyde and valeraldehyde are produced by indoor sources. Acetone+acrolein is both a marker of outdoor source and a singular indoor source represented by the fourth component of indoor data (Fin4). However, as the used analytical method did not allow us to quantify acetone and acrolein as individual compounds, we cannot hypothesis their indoor and outdoor origin. In this regard, a separation of the two compounds would be essential to qualify the actual nature of that marker (acetone or acrolein) and to apportion each compound to an indoor or outdoor source. For propionaldehyde, we have an intermediate situation. Propionaldehyde is a highly volatile compound that is emitted into the air from arboreous plants and anthropogenic releases. The outdoor acetaldehyde/propionaldehyde concentrations ratio (C2/C3) was often used as effective indicator of anthropogenic origin for ambient carbonyl compounds, C2/C3 ratios would be high in rural air and low in polluted urban air. The average value C2/C3 ratio is 2.34 in the present study, indicating the presence of anthropogenic sources in the residential area of Rome. In fact, comparing
ARTICLE IN PRESS 146
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
the ratios of other urban areas (range 1.7–6.0) (Grosjean, 1988; Zhang et al., 1994a; Possanzini et al., 1996), the ratio of Rome falls within such a range. Considering this, the indoor propionaldehyde source may be a sort of ‘‘sink’’ due to outdoor propionaldehyde entering inside the apartments. Since indoor air carbonyl compounds were thought to result from indoor (Shaughnessy et al., 2001) emissions, from indoor chemical formation and outdoor infiltration, there is always possibility for the penetration of an outdoor air pollutant into the apartments. Previous studies have found that carbonyls could be produced by the complex chemical reaction by ozone or other oxidants with some hydrocarbon emissions from carpets (Weschler et al., 1992) or tobacco smoke. Nonetheless, direct emissions of these carbonyl compounds, either from construction materials and furnishings or from human presence and activity, might be the dominant indoor sources (Crump and Gardiner, 1989; Zhang et al., 1994b). In the present study, the indoor carbonyl compounds concentrations were always higher than the outdoors (the mean I/Ob1), indicating the major sources from indoor materials. However, if we consider the outdoor formaldehyde/ acetaldehyde concentrations (C1/C2) ratio as an indicator of biogenic sources of formaldehyde (Shepson et al., 1991), the average C1/C2 ratio value in our study was 1.17, indicating as expected, to an urban area. In fact, it is suggested that C1/C2 ratios usually varies from 1 to 2 for urban areas and about 10 (rural or forested areas). Globally our work demonstrates the presence of a delicate balance between indoor and outdoor contamination with the two compartments engaged in a close relation. The combined use of PCA and GLM allowed us to explore the existence of a seasonal variation for the first four principal components carbonyl compounds concentrations variables. The proposed approach may provide important clues to discriminate among alternative models used to explain links. It reveals a number of complex and not immediately recognizable relationships among data, with a consequent net increase in sensitivity. We can ascribe Fin1 (and consequently F1 that is mirrored by the corresponding indoor component) to the outdoor sources emissions that accumulate in the indoor location. Outdoor sources emissions are at the basis of Fout1 that in fact in the exchange model is the ‘‘source’’ of Fin1 (positive sign in the equation). Fout2 instead represents the output toward the external air of the indoor contamination (negative sign in the exchange model) and collects the indoor generated butyraldehyde contamination. In this regard, there is to consider that butyraldehyde is present mostly in consumer products such as cleaning products, fragrances, plants, and so on (Edwards et al., 2005; de Bruin et al., 2006) that exist in apartments. The presence of valeraldehyde that is contained in the same products (cleaning products, fragrances) is again proof of the indoor butyraldehyde origin.
As reported in literature, the emissions of building materials and human activities—defined as those coming from household and consumer products, humans, and office equipment—are major sources of the indoor environment (Seifert et al., 1989; Wolkoff et al., 1991). In addition, the behavior of people and the ventilation characteristics of apartments may significantly affect the concentrations of pollutants in indoor environments (Edwards et al., 2001). To apportion the found level of carbonyl compounds to sources present in indoor, in outdoor air and generated through daily time-activity patterns is a highly complex task. This would require the knowledge on occurrence, source strengths and number of sources, distribution and fate of chemical substances. In practice a source apportionment study requires the selection of the compounds representing the obvious sources that may contribute to the location where the measurements will be carried out. Furthermore, the selected compounds should not be reactive during transportation from an emission source to a receptor. It becomes impossible to relate concentrations to sources if the variation of the concentration in a receptor does not reflect the variation of the emission strength in a source (de Bruin et al., 2006). However, multivariate data analysis methods, even if at a preliminary coarse grain level, could represent a very important tool in the elucidation of the pollution patterns. Acknowledgment We thank Dr. Alessandro Giuliani, senior scientist of Computational Carcinogenesis Division—Istituto Superiore di Sanita`—for his continued interest. Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version at 10.1016:/j.envres.2007.10.011.
References Ba´ez, A.P., Padilla, H., Cervantes, J., Pereyra, D., Torres, M.C., Garcia, R., Belmont, R., 2001. Preliminary study of the determination of ambient carbonyls in Xalapa City, Veracruz, Mexico. Atmos. Environ. 35, 1813–1819. Ba´ez, A.P., Padilla, H., Garcia, R., Torres, M.C., Rosas, I., Belmont, R., 2003. Carbonyl levels in indoor and outdoor air in Mexico City and Xalapa, Mexico. Sci. Total Environ. 302, 211–226. Carlier, P., Hannachi, H., Mouvier, G., 1986. The chemistry of carbonyl compounds in the atmosphere—a review. Atmos. Environ. 20, 2079–2099. Benigni, R., Giuliani, A., 1994. Quantitative modeling and biology: the multivariate approach. Am J. Physiol. 266, R1697–R1704. Burstyn, I., 2004. Principal component analysis is a powerful instrument in occupational hygiene inquiries. Ann. Occup. Hyg. 48 (8), 655–661.
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147 Carter, W.P.L., 1995. Computer modeling of environmental chamber studies of maximum incremental reactivities of volatile organic compounds. Atmos. Environ. 29, 2513–2527. Crescenzi, M., Giuliani, A., 2001. The main biological determinants of tumor line taxonomy elucidated by a principal component analysis of microarray data. FEBS Lett. 507 (1), 114–118. Crump, D.R., Gardiner, D., 1989. Sources and concentrations of aldehydes and ketones in indoor environments in the UK. Environ. Int. 15, 455–462. de Bruin, Y.B., Koistinen, K., Yli-Tuomi, T., Kephalopoulos, S., Jantunen, M., 2006. A review of source apportionment techniques and marker substances available for identification of personal exposure, indoor and outdoor sources of chemicals, 2006, 49pp. EUR 22349 EN—Scientific and Technical Research series; ISSN 10185593 ISBN 92-79-02981-9. Luxembourg: Office for Official Publications of the European Communities). Edwards, R.D., Jurvelin, J., Koistinen, K., Saarela, K., Jantunen, M., 2001. VOC concentration measured in personal samples and residential indoor, outdoor and workplace microenvironments in EXPOLISHelsinki, Finland. Atmos. Environ. 35, 4531–4543. Edwards, R.D., Schweizer, C., Jantunen, M., Laie, H.K., Ayer-Oglesby, L., Katsouyanni, K., Nieuwenhuijsen, M., Saarela, K., Sramh, R., Ku¨nzli, N., 2005. Personal exposures to VOC in the upper End of the distribution—relationships to indoor, outdoor and workplace concentrations. Atmos. Environ. 39, 2299–2307. Feng, Y., Wen, S., Xinming, W., Sheng, G., He, Q., Tang, J., Fu, J.J., 2004. Indoor and outdoor carbonyl compounds in the hotel ballrooms in Guangzhou, China. Atmos. Environ. 38, 103–112. Fuselli, S., Zanetti, C., Santarsiero, A., 2006. Residential indoor and outdoor concentrations of carbonyl compounds in the Rome Metropolitan Area, Italy. In: Proceedings of ECOpole’06, Duszniki, Poland, 19–21 October 2006. Giuliani, A., Colafranceschi, M., Webber, C.L., Zbilut, J.P., 2001. A complexity score derived from principal components analysis of nonlinear order measures. Physica A 301 (1–4), 567–588. Granby, K., Christensen, C.S., 1997. Urban and semi-rural observations of carboxylic acids and carbonyls. Atmos. Environ. 31, 1403–1415. Grosjean, D., 1982. Formaldehyde and other carbonyls in Los Angeles ambient air. Environ. Sci. Technol. 16, 254–262. Grosjean, D., 1988. Aldehydes, carboxylic acids and inorganic nitrate during NSMCS. Atmos. Environ. 22, 1637–1648. Grosjean, D., Williams, E.L., Grosjean, E., 1993a. Peroxyacyl nitrates at southern California Mountain forest locations. Environ. Sci. Technol. 27, 110–121. Grosjean, E., Williams II., E.L., Grosjean, D., 1993b. Ambient levels of formaldehyde and acetaldehyde in Atlanta, Georgia. Air Waste 43, 469–474. Grosjean, E., Grosjean, D., Fraser, M.P., Cass, G.R., 1996. Air quality model evaluation data for organics. 3. Peroxyacetyl nitrate and peroxypropionyl nitrate in Los Angeles air. Environ. Sci. Technol. 30, 2704–2714. Kelly, T.J., Smith, D.L., Satola, J., 1999. Emission rates of formaldehyde form materials and consumer products found in California homes. Environ. Sci. Technol. 33, 81–88. Lo¨froth, G., Burton, R.M., Forehand, L., Hammond, S.K., Seila, R.L., Zwejdinger, R.B., Lewtas, J., 1989. Characterization of environmental tobacco smoke. Environ. Sci. Technol. 23, 610–661. Montero, L., Vasconcellos, P.C., Souza, S.R., Pires, M.A.F., SanchezCcoyllo, O.R., Andrade, M.F., Carvalho, L.R.F., 2001. Measurements
147
of atmospheric carboxylic acids and carbonyl compounds in Sa˜o Paulo City, Brazil. Environ. Sci. Technol. 35, 3071–3081. Morrison, G.C., Nazaroff, W.W., 2002. Ozone interactions with carpet— secondary emissions of aldehydes. Environ. Sci. Technol. 36, 2185–2192. Nguyen, H.T., Takenaka, N., Bandow, H., Maeda, Y., Oliva, S.T.D., Botelho, M.M.F., Tavares, T.M., 2001. Atmospheric alcohols and aldehydes concentrations measured in Osaka, Japan and Sa˜o Paulo City, Brazil. Environ. Sci. Technol. 35, 3038–3057. Possanzini, M., Di Palo, V., Petricca, R., Fratarcangeli, R., Brocco, D., 1996. Measurements of lower carbonyls in Rome ambient air. Atmos. Environ. 30, 3757–3764. Reiss, R., Ryan, P.B., Tibbatts, S.J., Koutrakis, P., 1995. Measurement of organic acids, aldehydes, and ketones in residential environments and their relation to ozone. Air Waste 45, 811–822. Richardson, G., Eick, S.R., Shaw, S.A., 2006. Designing a simple tool kit and protocol for the investigation of the indoor environment in homes. Indoor Built. Environ. 15, 411–424. Santarsiero, A., Veschetti, E., Ottaviani, M., 1996. Elements in wastewater for agricultural use. Microchem. J. 54, 338–347. Satsumabayashi, H., Kurita, H., Chang, Y.S., Carmichael, G.R., Ueda, H., 1995. Photochemical formations of lower aldehydes and lower fatty acids under long-range transport in central Japan. Atmos. Environ. 29, 255–266. Schneider, P., Lo¨rinci, G., Gebefu¨gi, I.L., Heinrich, J., Kettrup, A., Wichmann, H., 1999. J. Expo. Anal. Environ. Epidemiol. 9, 282–292. Seifert, B., Mailahn, W., Schultz, C., Ullrich, D., 1989. Seasonal variations of concentrations of volatile organic compounds in selected German homes. Environ. Int. 15, 397–408. Shaughnessy, R.J., Mcdaniels, T.J., Weschler, C.J., 2001. Indoor chemistry—ozone and volatile organic compounds found in tobacco smoke. Environ. Sci. Technol. 35, 2758–2764. Shepson, P.B., Hastie, D.R., Schiff, H.I., Polizzi, M., Bottenheim, J.W., Anlauf, K., Mackay, G.I., Karecki, D.R., 1991. Atmospheric concentrations and temporal variations of C1–C3 carbonyl compounds at two rural sites in central Ontario. Atmos. Environ. 25A, 2001. Slemr, J., Junkermann, W., 1996. Temporal variations in formaldehyde, acetaldehyde and acetone and budget of formaldehyde at a rural site in southern Germany. Atmos. Environ. 30, 3667–3676. Szilagyi, I., Demeter, A., Turanyi, T., Berces, T., 1991. Non-methane hydrocarbon and aldehyde measurements in Budapest, Hungary. Atmos. Environ. 25A, 2103–2110. US EPA, 1999. Index to EPA Test Methods, April 2003 revised edition. (Chemical Number index p.10). Weschler, C.J., Hodgson, A.T., Wooley, J.D., 1992. Indoor chemistry— ozone, volatile organic compounds, and carpets. Environ. Sci. Technol. 26, 2371–2377. Williams, I.D., Revitt, D.M., Hamilton, R.S., 1996. A comparison of carbonyl compound concentrations at urban roadside and indoor sites. Sci. Total Environ. 189/190, 475–483. Wolkoff, O., Clausen, P.A., Nielsen, P.A., Mølhave, L., 1991. The Danish twin apartment study; part I: formaldehyde and long-term VOC measurements. Indoor Air 1 (4), 478–490. Zhang, J., He, Q., Lioy Paul, J., 1994a. Characteristics of aldehydes— concentrations, sources, and exposures for indoor and outdoor residential microenvironments. Environ. Sci. Technol. 28, 146–152. Zhang, J., Wiison, W.E., Lioy, P.J., 1994b. Indoor air chemistry— formation of organic acids and aldehydes. Environ. Sci. Technol. 28, 1975–1982.
Environmental Research 106 (2008) 139–147 www.elsevier.com/locate/envres
Indoor and outdoor air carbonyl compounds correlation elucidated by principal component analysis A. Santarsiero, S. Fuselli Istituto Superiore di Sanita`, Dipartimento di Ambiente e Connessa Prevenzione Primaria, Viale Regina Elena 299-00161 Rome, Italy Received 22 March 2007; received in revised form 21 September 2007; accepted 25 October 2007 Available online 3 December 2007
Abstract In this study indoor and outdoor air carbonyl compounds concentrations data are processed by means of principal component analysis (PCA). The analysis pointed to the carbonyl compounds sources as well as to their mutual interrelations. A global six sources (components) solution, accounting for the joint variability of the measured variables, was obtained. The existence of a linear function connecting outdoor and indoor components allowed for an exchange model between indoor and outdoor carbonyl compounds to be outlined. The different sources of carbonyl compounds were tentatively identified. Overall, this work demonstrates the presence of a delicate balance between indoor and outdoor carbonyl compounds contamination with the two compartments (indoor and outdoor) engaged in a close relationship. r 2007 Elsevier Inc. All rights reserved. Keywords: Principal component analysis; Indoor; Outdoor; Air; Carbonyl compounds
1. Introduction Carbonyl compounds in urban air have received attention due to their potential adverse health effects on humans and due to their important role in atmospheric chemistry, as precursors to free radicals, ozone, and peroxyacyl nitrates (Carlier et al., 1986; Grosjean et al., 1993a, b, 1996; Carter, 1995). Carbonyl compounds can be produced directly from incomplete combustion of biomass, fossil fuels or both, and through the atmospheric photooxidation of hydrocarbons (Satsumabayashi et al., 1995). In indoor air, some carbonyl compounds may be released from building materials, furniture, and consumer products and through reactions between indoor ozone and alkenes (Crump and Gardiner, 1989; Kelly et al., 1999). Cigarette smoke is another significant indoor source of several carbonyls (Lo¨froth et al., 1989; Morrison and Nazaroff, 2002). Ambient air concentrations of carbonyl compounds in urban and rural areas have been widely measured Corresponding author. Fax: +39 0649387083.
E-mail address: [email protected] (A. Santarsiero). 0013-9351/$ - see front matter r 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.envres.2007.10.011
(Grosjean, 1982; Shepson et al., 1991; Szilagyi et al., 1991; Possanzini et al., 1996; Slemr and Junkermann, 1996; Granby and Christensen, 1997; Montero et al., 2001; Nguyen et al., 2001; Ba´ez et al., 2001). Studies on indoor/ outdoor carbonyl compounds have been also reported (Zhang et al., 1994a; Reiss et al., 1995; Williams et al., 1996; Ba´ez et al., 2003). Zhang et al. (1994a) measured nine aldehydes in both indoor and outdoor air of six New Jersey homes, which showed the indoor to outdoor ratios (I/O)41. Feng et al. (2004) detected 18 carbonyl compounds in both indoor and outdoor air. In outdoor air, formaldehyde was the most abundant compound, followed by acetaldehyde while for the indoor concentrations the order was reversed. Fuselli et al. (2006) detected eight carbonyl compounds (formaldehyde, acetaldehyde, acetone+acrolein, propionaldeyde, benzaldehyde, n-butyraldehyde, isovaleraldehyde, and valeraldehyde) simultaneously in kitchen, living room, and apartment outdoor balcony of 10 apartments, in the residential area of Rome. The results confirmed the well-known finding of most studies reported in literature, that the indoor air pollutant concentrations are much higher than the outdoor concentrations.
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
140
As listed in Table 1 (Fuselli et al., 2006), the main statistical parameters of the obtained carbonyl concentrations, showed a wide variability range of carbonyl compound concentrations. Such wide variability of concentrations was unexpected, since apartments were selected with the same constant defined elements: two separately tested rooms (kitchen and living room) and a balcony all having been totally refurbished in the last 10 years, and with same number of apartment occupants. However, from the large amount of information derived from the carbonyl compounds concentration correlations matrix (Table 2), only three paradigmatic cases were selected: acetone+acrolein, acetaldehyde and n-butyraldehyde. In the case of acetaldehyde, the kitchen concentrations are strongly related to living room concentrations (r ¼ 0.70, po0.0001) while both indoor concentrations are independent of the outdoor concentration (r ¼ 0.09, p ¼ 0.56, r ¼ 0.07, p ¼ 0.68), thus pointing to an indoor source. The same is true (and still more cogent) for acetone+acrolein showing a correlation coefficient near to unity (r ¼ 0.93, po0.0001) between kitchen and living room and a lack of correlation with outdoor concentrations (r ¼ 0.04, p ¼ 0.819, r ¼ 0.01, p ¼ 0.958). In the case of n-butyraldehyde the correlation coefficients pointed to a strict link between indoor and outdoor concentrations (r ¼ 0.61, po0.0001 for outdoor, and indoor r ¼ 0.73, po0.0001 for kitchen and living room).
Indoor carbonyl compounds were abundant in the following order: formaldehyde, butyraldehyde, acetone+acrolein, acetaldehyde, valeraldehyde, propionaldehyde, isovalealdehyde, and benzaldehyde). The same carbonyl compounds abundance (in the order: butyraldehyde, formaldehyde, acetone+acrolein, acetaldehyde, propionaldehyde, valeraldehyde, benzaldehyde, and isovalealdehyde) was shown for the outdoor with the exception of butyraldehyde and benzaldehyde. Based on the above results of Fuselli et al. (2006), the practice of limiting the measurements only to outdoor air was considered not appropriate for estimating indoor air carbonyl compounds, as shown also by other studies (Schneider et al., 1999). Since outdoor air quality represents a factor for the removal and dilution of indoor pollutants, in this work we process the obtained carbonyl compounds concentrations data set in order to go deeper into the links existing between indoor and outdoor sources. This was now performed by means of principal component analysis (PCA). To get a clearer picture of the exchange between outdoor and indoor air carbonyl compounds pollution, we performed PCA separately on outdoor and indoor sub-sets data. The relationship between outdoor and indoor sources was clarified in the present work and the joint analysis of component loading and score spaces allowed for source identification.
Table 1 Simple descriptive statistics of indoor and outdoor carbonyl compounds concentrations (mg/m3) data Variables
Na
Mean
Median
Mode
Std. Dev.
Min
Max
Quantile 95%
Quantile 5%
Kitchenacetaldehyde Living roomacetaldehyde Outdoooracetaldehyde Kitchenacetone+acroleina Living roomacetone+acrole Outdooracetone+acroleina Kitchenpropionaldehyde Living roompropionaldehyde Outdoorpropionaldehyde Kitchenn-butyaldehyde Living roomn-butyraldehyde Outdoorn-butyraldehyde Kitchenbenzaldehyde Living roombenzaldehyde Outdoorbenzaldehyde Kitchenisovaleraldehyde Living roomisovaleraldehyde Outdoorisovaleraldehyde Kitchenvaleraldehyde Living roomvaleraldehyde Outdoorvaleraldehyde Kitchenformaldehyde Living roomformaldehyde Outdoorformaldehyde
40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 39b 40 40 40 40
9.37 8.03 2.34 9.44 8.44 2.46 2.63 2.48 1.0 10.99 10.79 4.91 0.84 0.56 0.24 0.90 0.64 0.22 3.25 2.17 0.48 13.18 12.31 2.75
9.90 7.75 1.95 7.80 6.40 2.00 2.70 2.30 0.90 8.60 6.00 2.80 0.75 0.50 0.20 1.00 0.60 0.20 2.85 2.00 0.35 12.90 10.55 2.45
10.00 8.60 1.40 5.00 6.20 1.40 2.20 1.40 0.80 9.00 6.70 2.00 0.05 0.05 0.05 0.05 0.05 0.05 2.30 1.80 0.05 7.50 9.40 2.00
3.69 3.62 1.30 8.84 8.63 1.45 0.92 1.24 0.50 8.68 11.52 5.29 0.59 0.42 0.17 0.67 0.51 0.17 1.68 1.29 0.43 4.28 6.26 1.13
0.80 3.20 1.10 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.70 0.10 0.05 6.90 4.80 1.20
19.70 20.90 7.60 58.00 57.30 6.10 4.60 6.00 2.30 34.60 44.40 26.20 2.20 1.80 0.70 22.20 2.00 0.70 7.80 7.00 1.60 23.00 32.90 7.00
16.35 15.35 5.10 16.50 16.25 5.65 4.15 5.65 2.05 33.05 37.35 15.85 2.10 1.30 0.60 2.00 1.55 0.50 6.90 5.5 1.25 21.75 25.90 4.45
4.45 3.45 1.20 2.55 2.25 0.95 0.95 1.10 0.20 0.70 1.80 1.00 0.05 0.05 0.05 0.05 0.05 0.05 1.20 0.6 0.05 7.50 5.50 1.40
a
N ¼ number of observations (number of samples). Detection limit for carbonyl compound concentration is 0.05 mg/m3.
b
Table 2 Concentration correlations of indoor and outdoor air carbonyl compounds 2
3
4
5
6
7
Kitchacetal 1 Livacetal 2 Outacetal 3 Kitchac+acrol 4 Livac+acrol 5 Outac+acrol 6 Kitchpropion 7 Livpropion 8 Outpropion 9 Kitchbutyr 10 Livbutyr 11 Outbutyr 12 Kitchbenzal 13 Livbenzal 14 Outbenzal 15 Kitchisovale 16 Livisovale 17 Outisovale 18 Kitchvale 19 Livvale 20 Outvale 21 Kitchforma 22 Livforma 23 Outforma 24
1 0.70 0.09 0.09 0.10 0.04 0.23 0.15 0.04 0.30 0.31 0.29 0.30 0.07 0.16 0.01 0.26 0.26 0.54 0.36 0.16 0.29 0.11 0.24
1 0.04 1 0.07 0.02 1 0.14 0.12 0.93 1 0.01 0.45 0.20 0.17 1 0.01 0.17 0.32 0.20 0.37 1 0.07 0.51 0.08 0.07 0.33 0.20 0.06 0.36 0.13 0.20 0.61 0.17 0.19 0.05 0.10 0.02 0.08 0.08 0.12 0.00 0.20 0.10 0.05 0.21 0.08 0.07 0.16 0.09 0.18 0.22 0.20 0.10 0.27 0.19 0.18 0.58 0.06 0.41 0.01 0.07 0.27 0.28 0.13 0.48 0.27 0.22 0.48 0.30 0.10 0.05 0.39 0.26 0.23 0.58 0.12 0.30 0.19 0.20 0.22 0.37 0.17 0.62 0.11 0.09 0.56 0.19 0.54 0.11 0.07 0.02 0.33 0.09 0.67 0.11 0.06 0.16 0.11 0.00 0.05 0.53 0.22 0.28 0.49 0.19 0.40 0.09 0.19 0.11 0.18 0.12 0.34 0.21 0.13 0.22 0.10 0.21 0.16 0.54 0.36 0.38 0.62 0.16
8
9
10
11
12
13
14
15
16
17
18
19
20
1 0.40 1 0.05 0.13 1 0.05 0.07 0.84 1 0.15 0.24 0.61 0.73 1 0.13 0.08 0.34 0.44 0.40 1 0.35 0.28 0.34 0.32 0.34 0.52 1 0.33 0.30 0.52 0.48 0.42 0.45 0.57 1 0.29 0.10 0.49 0.57 0.59 0.74 0.44 0.62 1 0.33 0.52 0.55 0.69 1 0.54 0.19 0.41 0.46 0.51 0.45 0.38 0.46 0.44 0.35 0.32 0.54 0.84 0.50 0.57 1 0.29 0.34 0.03 0.01 0.04 0.00 0.16 0.33 0.28 0.42 0.40 1 0.15 0.03 0.33 0.23 0.19 0.12 0.11 0.22 0.14 0.06 0.21 0.28 1 0.41 0.30 0.28 0.37 0.37 0.33 0.46 0.59 0.45 0.48 0.68 0.15 0.03 0.12 0.03 0.05 0.19 0.08 0.14 0.03 0.13 0.04 0.19 0.13 0.49 0.20 0.11 0.21 0.02 0.10 0.11 0.07 0.15 0.09 0.13 0.09 0.17 0.02 0.32 0.28 0.44 0.04 0.08 0.00 0.15 0.19 0.50 0.24 0.16 0.60 0.00 0.02
21
22
23
24
1 0.11 1 0.27 0.36 1 0.51 0.46 0.19 1
ARTICLE IN PRESS
1
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
Compounds
141
ARTICLE IN PRESS 142
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
2. Materials and methods 2.1. Carbonyl concentration data The data set used in this work has been generated by the study of Fuselli et al. (2006) on carbonyl compounds concentrations in indoor air and related outdoor balconies of 10 apartments in Rome residential area. The data set is available as support material. Table 1 reports the simple descriptive statistics of the raw data set. Such carbonyl compounds concentration data are referred to a consecutive 10day sampling of carbonyl compounds carried out during a year, in the months of May, September, November, and February. Simultaneous samplings took place at kitchen, living room and outdoor apartment. The apartments were selected with similar factors, such as traffic conditions, building features, floor area, ventilation, and layout. Carbonyl compounds were sampled using the passive Radiello Aldehyde samplers (code no. 165) and the chemical analysis procedure met the requirements of the US EPA Method TO-11A (US EPA, 1999, US EPA IP-6A, ASTM D5197). The carbonyl compounds detected were formaldehyde, acetaldehyde, acetone+acrolein (quantified as sum), propionaldehyde, benzaldehyde, nbutyraldehyde, isovaleraldehyde, and valeraldehyde. The sum of acetone and acrolein was reported because they could not be separated by the used analytical method.
Fig. 1. Eigenvalue distribution for the whole data set, in abscissa the component number, in ordinate the eigenvalue. The arrow points to the scree test selected number of signal components.
seasonal effect on components was assessed by means of analysis of variance.
2.2. Statistical analyses PCA was applied to a 40 24 matrix (see table of whole data set in support material), having as statistical units the 40 independent measurements [four measurements for each of the 10 apartments: one measurement for each of the four given months (September, May, November, February)] and as variables the 24 measurements corresponding to the eight carbonyl compounds concentrations relative to two indoor locations (kitchen and living room) and one outdoor (balcony) location. PCA was carried out both on the whole data set and separately (Richardson et al., 2006) on the indoor and outdoor data sub-sets. The indoor and outdoor extracted component scores were then correlated to each other. A model, able to predict the first component of indoor carbonyl compounds by means of the first two outdoor components, was built by means of multiple linear regressions. The whole data set is a matrix having the apartments (40 statistical units) as rows and the measured carbonyl compounds concentrations (24 variables) as columns. PCA projects this multidimensional space into a derived space spanned by new variables, called principal components, ordered in decreasing amount of explained variability (Santarsiero et al., 1996; Benigni and Giuliani, 1994). Thus, the first components will retain the maximal amount of correlated information (that is, indoor/outdoor correlation) confining the uncorrelated portion of information to higher order components. This allows for a strong compression of the original information by simply retaining the first extracted components and discarding the others. The components are independent by construction to each other, thus each component points to a linear independent source of carbonyl compounds. Descriptive statistics and distribution analysis were performed for all the variables. Computations were performed with the statistical software SAS for personal computers. A direct visual scree test (Benigni and Giuliani, 1994; Crescenzi and Giuliani, 2001; Giuliani et al., 2001) on the eigenvalue distribution allowed us to select the bona fide signal components (Fig. 1). The same procedure was used for the sub-set data matrix with 40 statistical units and eight variables (outdoor data set) (Fig. 2(a)) and for the sub-set data matrix with 40 statistical units and 16 variables (indoor data set) (Fig. 2(b)). The mutual correlations between indoor and outdoor components were assessed by means of Pearson correlation coefficients. The model explaining the indoor component by means of the first two outdoor components was built by classical multiple regression analysis. The
3. Results and discussion 3.1. Data structure The eigenvalue distribution on the components for the whole set is reported in Fig. 1. The arrow points to the putative beginning of the noise floor: a six-component solution explaining 77.45% of the total variability is detected as bona fide signal by means of the scree test criterion. 3.2. Carbonyl sources interpretation of the components From the interpretative point of view, the major merit of PCA resides in the possibility to attach an indoor/outdoor source of carbonyl compounds to the components (Giuliani et al., 2001; Burstyn, 2004). Interpretation is based on component loadings, that is, on the correlation coefficients between original variables (carbonyl compounds) and the components. The extracted dimensions (components) represent the ‘‘linearly independent systems’’ organizing the data. The carbonyl compounds more correlated with the specific components are the ones more important to assign sources. Each carbonyl compound participates in all the extracted components, to different degrees, so fulfilling the notion that the same compound can come from more than one source. The relationship between observed variables and principal components (and thus carbonyl compounds sources) in terms of loadings is reported in Table 3. The first principal component is by far the major order parameter structuring the observed variability (28.67% of explained variance). In order to assign a meaning to this component, we
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
143
Table 3 Whole set factor loadings pattern
Fig. 2. Eigenvalue distribution for the outdoor data set (Fig. 2(a)) and indoor data set (Fig. 2(b)), in abscissa the component number, in ordinate the eigenvalue. The arrow points to the scree test selected number of signal components.
considered the carbonyl compounds variables possessing the highest absolute loadings, that is, the carbonyl compounds showing the highest positive or negative correlation with component 1, and thus mostly involved in the corresponding indoor or outdoor carbonyl source. Inspection of the component loadings pattern (Table 2) readily shows that most of outdoor carbonyl compounds are loaded on the first component (F1). The first component (F1), can thus be named as ‘‘outdoor sources’’ with butyraldehyde negatively correlated in both indoor and outdoor locations, so pointing to a singular behavior of this compound with respect to others. The negative sign tells us that butyraldehyde has an opposite behavior with respect to the other compounds loaded on F1: high values of these compounds, as for F1 source, correspond to comparatively low values of butyraldehyde.
Variables
F1
F2
F3
F4
F5
F6
Kitchen acetaldehyde Living room acetaldehyde Outdoor acetaldehyde Kitchen acetone+acrolein Living room acetone+acrolein Outdoor acetone+acrolein Kitchen propionaldehyde Living room propionaldehyde Outdoor propionaldehyde Kitchen n-butyraldehyde Living room n-butyraldehyde Outdoor n-butyraldehyde Kitchen benzaldehyde Living room benzaldehyde Outdoor benzaldehyde Kitchen isovaleraldehyde Living room isovaleraldehyde Outdoor isovaleraldehyde Kitchen valeraldehyde Living room valeraldehyde Outdoor valeraldehyde Kitchen formaldehyde Living room formaldehyde Outdoor formaldehyde
0.20 0.13 0.50 0.38 0.34 0.54 0.45 0.52 0.39 0.54 0.60 0.53 0.58 0.66 0.86 0.77 0.75 0.86 0.36 0.15 0.75 0.12 0.17 0.54
0.68 0.72 0.33 0.30 0.39 0.39 0.10 0.10 0.33 0.47 0.38 0.40 0.11 0.04 0.03 0.16 0.22 0.01 0.38 0.60 0.14 0.52 0.37 0.56
0.36 0.42 0.47 0.26 0.17 0.46 0.29 0.36 0.53 0.38 0.49 0.53 0.50 0.03 0.05 0.36 0.01 0.26 0.57 0.20 0.11 0.36 0.02 0.19
0.24 0.21 0.38 0.45 0.35 0.20 0.60 0.03 0.18 0.29 0.25 0.22 0.25 0.16 0.07 0.32 0.06 0.22 0.32 0.15 0.20 0.33 0.53 0.05
0.31 0.23 0.08 0.63 0.61 0.02 0.26 0.30 0.03 0.11 0.16 0.06 0.35 0.41 0.01 0.12 0.18 0.02 0.04 0.27 0.06 0.20 0.29 0.24
0.23 0.15 0.02 0.22 0.35 0.32 0.11 0.36 0.02 0.13 0.07 0.12 0.04 0.14 0.18 0.01 0.36 0.19 0.22 0.54 0.02 0.39 0.37 0.36
F1 is mostly linked to outdoor sources, almost all the outdoor carbonyl compounds are significantly loaded on F1 and the most important variables for defining the significance of the component are outdoor benzaldehyde, outdoor isovaleraldehyde, and outdoor valeraldehyde. Component 2 (F2) is more linked to ‘‘indoor sources’’ predominantly acetaldehyde, and valeraldehyde. It is worth noting the case of the outdoor formaldehyde that is likewise charged both on first (F1) and second (F2) components. This points out two different sources (or sinks, if we imagine a dynamic indoor/outdoor balance) of this compound, the first (F1) being of probable outdoor origin and the second of dubious provenience. This behavior of formaldehyde allows us to grasp the meaning of the components that, even if being linear combinations of the initial variables, nevertheless give a picture of the studied phenomenon posited at a different level with respect to the original measures. Component 3 (F3) is linked to the ‘‘butyraldehyde singularity’’ that separates the concentration dynamics of this compound from the others. Component 4 (F4) is heavily loaded by kitchen propionaldehyde pointing to an ‘‘indoor source’’ typically kitchen source probably linked to materials or activities specifically of the kitchen. Component 5 (F5) is heavily negatively loaded by kitchen acetone+acrolein and living-room acetone+acrolein pointing to ‘‘an indoor source’’ of this compound separated from the main pollution sources. This finding is proven by the near to unity Pearson correlation coefficient
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
144
between kitchen acetone+acrolein and living-room acetone+acrolein (r ¼ 0.93, po0.0001) that in turn are only weakly correlated to other indoor and outdoor carbonyl compounds. Considering progressively higher order components, it becomes more difficult to distinguish a dominant key. Accordingly, we found it difficult to assign a source specificity to component 6 (F6). These difficulties are easily explained considering that each successive component accounts for a smaller amount of signal variability while it is more affected by both intrinsic and experimental noise. In conclusion we can say that benzaldehyde and isovaleraldehyde have a major relevance as outdoor sources, while butyraldehyde, acetaldehyde, and valeraldehyde as indoor sources. For formaldehyde we have an intermediate situation. The non-noisy character of the extracted components is proven by the fact that these components display a marked seasonal effect, as demonstrated by the results obtained from the analysis of variance using month effect as variability source. By means of the generalized linear model (GLM) applied to the six principal components we note that the first four principal components (F1, F2, F3, and F4) display a statistically significant variation among the months. In fact, we obtained, for the dependent variables (F1, F2, F3, and F4) on the considered months, the following level of significance: dependent dependent dependent dependent
variable: variable: variable: variable:
F1 F2 F3 F4
(F ¼ 18.08, po0.0001), (F ¼ 3.96, po0.0157), (F ¼ 3.56, po0.0238), (F ¼ 3.14, po0.0376).
This seasonal effect is difficult interpret due to the paucity of different time points, but it seems to suggest that in winter (lower temperatures) the pollution from the most important carbonyl compounds sources is lower than summertime. No significant apartment effect was highlighted by Analysis of variance so pointing to a substantial homogeneity of the different studied apartments.
3.3. PCA on the outdoor sub-set data PCA on the outdoor carbonyl compounds concentrations sub-set data, measured at the balcony of each apartment, points to a relatively simple two-component solution (Fig. 2a) with a first component measuring the ‘‘general outdoor sources’’ and a second component explaining the singular behavior of butyraldehyde. We chose a two-component solution as bona fide signal, explaining 72% of the total variability carried out by the carbonyl compounds concentration data. Table 4 (bolded) shows the outdoor carbonyl compounds in this sub-set possessing the highest absolute
Table 4 Outdoor factor loadings pattern Variables Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor Outdoor
acetaldehyde acetone+acrolein propionaldehyde n-butyraldehyde benzaldehyde isovaleraldehyde valeraldehyde formaldehyde
Fout1
Fout2
0.74 0.76 0.58 0.18 0.80 0.90 0.78 0.77
0.15 0.41 0.53 0.91 0.36 0.25 0.27 0.21
loadings on the components and thus important for defining the meaning of the component itself. Component 1 (Fout1) is mainly driven by outdoor isovaleraldehyde, outdoor benzaldehyde, outdoor acetone+acrolein, and outdoor formaldehyde, while component 2 (Fout2) goes together with outdoor n-butyraldehyde so confirming the singular nature of this compound contamination. Outdoor n-butyraldehyde has a source different from the outdoor carbonyl compounds as also evident by PCA on the wholeset-data. Component 2 is mostly loaded by outdoor n-butyraldehyde that comes from ‘‘indoor sources’’ that are kitchen and living-room as above shown, this character of ‘‘sink’’ of the indoor contamination for Fout2 will be evident in the following. Only Fout1 displays a significant seasonal variation (po0.001), while this is not the case of Fout2, this could in principle be related to the fact that Fout1 is a source (a seasonally varied source allowing outdoor generated compounds to come into apartments) while Fout2 could be a sink (the outdoor deposit of internally generated pollution). 3.4. PCA on the indoor sub-set data The eigenvalue distribution on the components is reported in Fig. 2(b). We chose a five-component solution as bona fide signal, explaining 78% (Fig. 2(b), the start of noise floor is marked by an arrow) of the total variability carried out by the indoor carbonyl compounds concentrations data. Table 5 (bolded) shows the carbonyl compounds in this sub-set possessing the highest absolute loadings on the first components. Component 1 (Fin1) is mainly driven by kitchen isovaleraldehyde, living-room isovaleraldehyde, and kitchen benzaldehyde. Kitchen n-butyraldehyde and living-room n-butyraldehyde are charged on Fin1 with a negative sign, so confirming the singular nature of this compound. In fact component 3 is mostly loaded by indoor butyraldehyde that comes from an ‘‘indoor source’’ different from the sources of other indoor carbonyl compounds. This result mirrors the behavior of the whole data set. Component 2 (Fin2) is predominantly loaded by acetaldehyde, valeraldehyde, and kitchen formaldehyde
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
145
Table 5 Indoor factor loadings pattern Variables
Fin1
Fin2
Fin3
Fin 4
Kitchen acetaldehyde Living room acetaldehyde Kitchen acetone+acrolein Living room acetone+acrolein kitchen propionaldehyde Living room propionaldehyde Kitchen n-butyraldehyde Living room n-butyraldehyde kitchen benzaldehyde Living room benzaldehyde Kitchen isovaleraldehyde Living room isovaleraldehyde Kitchen valeraldehyde Living room valeraldehyde Kitchen formaldehyde Living room formaldehyde
0.228 0.751 0.092 0.339 0.202 0.848 0.054 0.135 0.433 0.395 0.445 0.540 0.347 0.423 0.532 0.531 0.568 0.278 0.058 0.337 0.420 0.051 0.436 0.317 0.643 0.162 0.541 0.291 0.707 0.032 0.506 0.331 0.678 0.416 0.206 0.291 0.609 0.122 0.046 0.316 0.891 0.105 0.060 0.123 0.798 0.109 0.201 0.156 0.372 0.596 0.490 0.076 0.178 0.654 0.274 0.213 0.019 0.607 0.338 0.304 0.006 0.319 0.169 0.414
Fin5 0.316 0.232 0.373 0.244 0.403 0.386 0.139 0.133 0.176 0.391 0.188 0.254 0.040 0.375 0.132 0.696
and again mirrors the behavior of the wholedata set. Component 3 (Fin3) as stated above, marks the singular indoor source of butyraldehyde. Component 4 (Fin4) identifies a specific acetone+acrolein pollution source. Component 5 (Fin5) points to a balance (opposite signs) between propionaldehyde and formaldehyde. 3.5. Correlation between indoor and outdoor In order to investigate both the presence and nature of indoor/outdoor air exchange, the correlation coefficients between indoor (Fin#) and outdoor (Fout#) were computed. Simple Pearson correlation highlights two statistically significant pairwise correlations between outdoor and indoor components, the first indoor component (Fin1) has a Pearson coefficient r ¼ 0.568 with the first outdoor component (Fout1) and a Pearson coefficient r ¼ 0.522 with the second outdoor component (Fout2). The link between indoor and outdoor data is further clarified by multiple regression analysis in which Fin1 is modelled by Fout1 and Fout2 in combination. Fig. 3 reports the prediction of the observed Fin1 (first principal component of indoor data) as estimated by the values of the two first outdoor components by means of the following equation: Fin1 ¼ 0:0023 þ 0:5586ðFout1Þ 0:5141ðFout2Þ.
(1)
The congruence between observed and estimated data is proof of the concept of exchange between indoor and outdoor compartments. The model was very significant showing an F value of 26.04 (po0.0001) and a Pearson coefficient r ¼ 0.77. The opposite signs of Fout1 and Fout2 in the equation allow us to identify Fout1 as a source for indoor global pollution (as measured by Fin1) and Fout2 as a sink. Globally the model tells us that a well-defined balance does exist between indoor and outdoor pollution.
Fig. 3. The prediction of the first indoor component by means of the first and second outdoor component is reported.
4. Conclusion Overall, global carbonyl compounds contamination was characterized by six different sources of which four having a seasonal variation. Furthermore, we observe a strong indoor/outdoor carbonyl compounds exchange that we can model with a fair accuracy. Simple outdoor carbonyl compounds contamination was characterized by a two-component solution, with a first component measuring the ‘‘outdoor sources’’ and a second explaining the singular behavior of butyraldehyde and acting as ‘‘sink’’ for indoor contamination. In conclusion, we can say that benzaldehyde and isovaleraldehyde are mainly pollutants coming inside apartments from the outside environment, while butyraldehyde, formaldehyde and valeraldehyde are produced by indoor sources. Acetone+acrolein is both a marker of outdoor source and a singular indoor source represented by the fourth component of indoor data (Fin4). However, as the used analytical method did not allow us to quantify acetone and acrolein as individual compounds, we cannot hypothesis their indoor and outdoor origin. In this regard, a separation of the two compounds would be essential to qualify the actual nature of that marker (acetone or acrolein) and to apportion each compound to an indoor or outdoor source. For propionaldehyde, we have an intermediate situation. Propionaldehyde is a highly volatile compound that is emitted into the air from arboreous plants and anthropogenic releases. The outdoor acetaldehyde/propionaldehyde concentrations ratio (C2/C3) was often used as effective indicator of anthropogenic origin for ambient carbonyl compounds, C2/C3 ratios would be high in rural air and low in polluted urban air. The average value C2/C3 ratio is 2.34 in the present study, indicating the presence of anthropogenic sources in the residential area of Rome. In fact, comparing
ARTICLE IN PRESS 146
A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147
the ratios of other urban areas (range 1.7–6.0) (Grosjean, 1988; Zhang et al., 1994a; Possanzini et al., 1996), the ratio of Rome falls within such a range. Considering this, the indoor propionaldehyde source may be a sort of ‘‘sink’’ due to outdoor propionaldehyde entering inside the apartments. Since indoor air carbonyl compounds were thought to result from indoor (Shaughnessy et al., 2001) emissions, from indoor chemical formation and outdoor infiltration, there is always possibility for the penetration of an outdoor air pollutant into the apartments. Previous studies have found that carbonyls could be produced by the complex chemical reaction by ozone or other oxidants with some hydrocarbon emissions from carpets (Weschler et al., 1992) or tobacco smoke. Nonetheless, direct emissions of these carbonyl compounds, either from construction materials and furnishings or from human presence and activity, might be the dominant indoor sources (Crump and Gardiner, 1989; Zhang et al., 1994b). In the present study, the indoor carbonyl compounds concentrations were always higher than the outdoors (the mean I/Ob1), indicating the major sources from indoor materials. However, if we consider the outdoor formaldehyde/ acetaldehyde concentrations (C1/C2) ratio as an indicator of biogenic sources of formaldehyde (Shepson et al., 1991), the average C1/C2 ratio value in our study was 1.17, indicating as expected, to an urban area. In fact, it is suggested that C1/C2 ratios usually varies from 1 to 2 for urban areas and about 10 (rural or forested areas). Globally our work demonstrates the presence of a delicate balance between indoor and outdoor contamination with the two compartments engaged in a close relation. The combined use of PCA and GLM allowed us to explore the existence of a seasonal variation for the first four principal components carbonyl compounds concentrations variables. The proposed approach may provide important clues to discriminate among alternative models used to explain links. It reveals a number of complex and not immediately recognizable relationships among data, with a consequent net increase in sensitivity. We can ascribe Fin1 (and consequently F1 that is mirrored by the corresponding indoor component) to the outdoor sources emissions that accumulate in the indoor location. Outdoor sources emissions are at the basis of Fout1 that in fact in the exchange model is the ‘‘source’’ of Fin1 (positive sign in the equation). Fout2 instead represents the output toward the external air of the indoor contamination (negative sign in the exchange model) and collects the indoor generated butyraldehyde contamination. In this regard, there is to consider that butyraldehyde is present mostly in consumer products such as cleaning products, fragrances, plants, and so on (Edwards et al., 2005; de Bruin et al., 2006) that exist in apartments. The presence of valeraldehyde that is contained in the same products (cleaning products, fragrances) is again proof of the indoor butyraldehyde origin.
As reported in literature, the emissions of building materials and human activities—defined as those coming from household and consumer products, humans, and office equipment—are major sources of the indoor environment (Seifert et al., 1989; Wolkoff et al., 1991). In addition, the behavior of people and the ventilation characteristics of apartments may significantly affect the concentrations of pollutants in indoor environments (Edwards et al., 2001). To apportion the found level of carbonyl compounds to sources present in indoor, in outdoor air and generated through daily time-activity patterns is a highly complex task. This would require the knowledge on occurrence, source strengths and number of sources, distribution and fate of chemical substances. In practice a source apportionment study requires the selection of the compounds representing the obvious sources that may contribute to the location where the measurements will be carried out. Furthermore, the selected compounds should not be reactive during transportation from an emission source to a receptor. It becomes impossible to relate concentrations to sources if the variation of the concentration in a receptor does not reflect the variation of the emission strength in a source (de Bruin et al., 2006). However, multivariate data analysis methods, even if at a preliminary coarse grain level, could represent a very important tool in the elucidation of the pollution patterns. Acknowledgment We thank Dr. Alessandro Giuliani, senior scientist of Computational Carcinogenesis Division—Istituto Superiore di Sanita`—for his continued interest. Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version at 10.1016:/j.envres.2007.10.011.
References Ba´ez, A.P., Padilla, H., Cervantes, J., Pereyra, D., Torres, M.C., Garcia, R., Belmont, R., 2001. Preliminary study of the determination of ambient carbonyls in Xalapa City, Veracruz, Mexico. Atmos. Environ. 35, 1813–1819. Ba´ez, A.P., Padilla, H., Garcia, R., Torres, M.C., Rosas, I., Belmont, R., 2003. Carbonyl levels in indoor and outdoor air in Mexico City and Xalapa, Mexico. Sci. Total Environ. 302, 211–226. Carlier, P., Hannachi, H., Mouvier, G., 1986. The chemistry of carbonyl compounds in the atmosphere—a review. Atmos. Environ. 20, 2079–2099. Benigni, R., Giuliani, A., 1994. Quantitative modeling and biology: the multivariate approach. Am J. Physiol. 266, R1697–R1704. Burstyn, I., 2004. Principal component analysis is a powerful instrument in occupational hygiene inquiries. Ann. Occup. Hyg. 48 (8), 655–661.
ARTICLE IN PRESS A. Santarsiero, S. Fuselli / Environmental Research 106 (2008) 139–147 Carter, W.P.L., 1995. Computer modeling of environmental chamber studies of maximum incremental reactivities of volatile organic compounds. Atmos. Environ. 29, 2513–2527. Crescenzi, M., Giuliani, A., 2001. The main biological determinants of tumor line taxonomy elucidated by a principal component analysis of microarray data. FEBS Lett. 507 (1), 114–118. Crump, D.R., Gardiner, D., 1989. Sources and concentrations of aldehydes and ketones in indoor environments in the UK. Environ. Int. 15, 455–462. de Bruin, Y.B., Koistinen, K., Yli-Tuomi, T., Kephalopoulos, S., Jantunen, M., 2006. A review of source apportionment techniques and marker substances available for identification of personal exposure, indoor and outdoor sources of chemicals, 2006, 49pp. EUR 22349 EN—Scientific and Technical Research series; ISSN 10185593 ISBN 92-79-02981-9. Luxembourg: Office for Official Publications of the European Communities). Edwards, R.D., Jurvelin, J., Koistinen, K., Saarela, K., Jantunen, M., 2001. VOC concentration measured in personal samples and residential indoor, outdoor and workplace microenvironments in EXPOLISHelsinki, Finland. Atmos. Environ. 35, 4531–4543. Edwards, R.D., Schweizer, C., Jantunen, M., Laie, H.K., Ayer-Oglesby, L., Katsouyanni, K., Nieuwenhuijsen, M., Saarela, K., Sramh, R., Ku¨nzli, N., 2005. Personal exposures to VOC in the upper End of the distribution—relationships to indoor, outdoor and workplace concentrations. Atmos. Environ. 39, 2299–2307. Feng, Y., Wen, S., Xinming, W., Sheng, G., He, Q., Tang, J., Fu, J.J., 2004. Indoor and outdoor carbonyl compounds in the hotel ballrooms in Guangzhou, China. Atmos. Environ. 38, 103–112. Fuselli, S., Zanetti, C., Santarsiero, A., 2006. Residential indoor and outdoor concentrations of carbonyl compounds in the Rome Metropolitan Area, Italy. In: Proceedings of ECOpole’06, Duszniki, Poland, 19–21 October 2006. Giuliani, A., Colafranceschi, M., Webber, C.L., Zbilut, J.P., 2001. A complexity score derived from principal components analysis of nonlinear order measures. Physica A 301 (1–4), 567–588. Granby, K., Christensen, C.S., 1997. Urban and semi-rural observations of carboxylic acids and carbonyls. Atmos. Environ. 31, 1403–1415. Grosjean, D., 1982. Formaldehyde and other carbonyls in Los Angeles ambient air. Environ. Sci. Technol. 16, 254–262. Grosjean, D., 1988. Aldehydes, carboxylic acids and inorganic nitrate during NSMCS. Atmos. Environ. 22, 1637–1648. Grosjean, D., Williams, E.L., Grosjean, E., 1993a. Peroxyacyl nitrates at southern California Mountain forest locations. Environ. Sci. Technol. 27, 110–121. Grosjean, E., Williams II., E.L., Grosjean, D., 1993b. Ambient levels of formaldehyde and acetaldehyde in Atlanta, Georgia. Air Waste 43, 469–474. Grosjean, E., Grosjean, D., Fraser, M.P., Cass, G.R., 1996. Air quality model evaluation data for organics. 3. Peroxyacetyl nitrate and peroxypropionyl nitrate in Los Angeles air. Environ. Sci. Technol. 30, 2704–2714. Kelly, T.J., Smith, D.L., Satola, J., 1999. Emission rates of formaldehyde form materials and consumer products found in California homes. Environ. Sci. Technol. 33, 81–88. Lo¨froth, G., Burton, R.M., Forehand, L., Hammond, S.K., Seila, R.L., Zwejdinger, R.B., Lewtas, J., 1989. Characterization of environmental tobacco smoke. Environ. Sci. Technol. 23, 610–661. Montero, L., Vasconcellos, P.C., Souza, S.R., Pires, M.A.F., SanchezCcoyllo, O.R., Andrade, M.F., Carvalho, L.R.F., 2001. Measurements
147
of atmospheric carboxylic acids and carbonyl compounds in Sa˜o Paulo City, Brazil. Environ. Sci. Technol. 35, 3071–3081. Morrison, G.C., Nazaroff, W.W., 2002. Ozone interactions with carpet— secondary emissions of aldehydes. Environ. Sci. Technol. 36, 2185–2192. Nguyen, H.T., Takenaka, N., Bandow, H., Maeda, Y., Oliva, S.T.D., Botelho, M.M.F., Tavares, T.M., 2001. Atmospheric alcohols and aldehydes concentrations measured in Osaka, Japan and Sa˜o Paulo City, Brazil. Environ. Sci. Technol. 35, 3038–3057. Possanzini, M., Di Palo, V., Petricca, R., Fratarcangeli, R., Brocco, D., 1996. Measurements of lower carbonyls in Rome ambient air. Atmos. Environ. 30, 3757–3764. Reiss, R., Ryan, P.B., Tibbatts, S.J., Koutrakis, P., 1995. Measurement of organic acids, aldehydes, and ketones in residential environments and their relation to ozone. Air Waste 45, 811–822. Richardson, G., Eick, S.R., Shaw, S.A., 2006. Designing a simple tool kit and protocol for the investigation of the indoor environment in homes. Indoor Built. Environ. 15, 411–424. Santarsiero, A., Veschetti, E., Ottaviani, M., 1996. Elements in wastewater for agricultural use. Microchem. J. 54, 338–347. Satsumabayashi, H., Kurita, H., Chang, Y.S., Carmichael, G.R., Ueda, H., 1995. Photochemical formations of lower aldehydes and lower fatty acids under long-range transport in central Japan. Atmos. Environ. 29, 255–266. Schneider, P., Lo¨rinci, G., Gebefu¨gi, I.L., Heinrich, J., Kettrup, A., Wichmann, H., 1999. J. Expo. Anal. Environ. Epidemiol. 9, 282–292. Seifert, B., Mailahn, W., Schultz, C., Ullrich, D., 1989. Seasonal variations of concentrations of volatile organic compounds in selected German homes. Environ. Int. 15, 397–408. Shaughnessy, R.J., Mcdaniels, T.J., Weschler, C.J., 2001. Indoor chemistry—ozone and volatile organic compounds found in tobacco smoke. Environ. Sci. Technol. 35, 2758–2764. Shepson, P.B., Hastie, D.R., Schiff, H.I., Polizzi, M., Bottenheim, J.W., Anlauf, K., Mackay, G.I., Karecki, D.R., 1991. Atmospheric concentrations and temporal variations of C1–C3 carbonyl compounds at two rural sites in central Ontario. Atmos. Environ. 25A, 2001. Slemr, J., Junkermann, W., 1996. Temporal variations in formaldehyde, acetaldehyde and acetone and budget of formaldehyde at a rural site in southern Germany. Atmos. Environ. 30, 3667–3676. Szilagyi, I., Demeter, A., Turanyi, T., Berces, T., 1991. Non-methane hydrocarbon and aldehyde measurements in Budapest, Hungary. Atmos. Environ. 25A, 2103–2110. US EPA, 1999. Index to EPA Test Methods, April 2003 revised edition. (Chemical Number index p.10). Weschler, C.J., Hodgson, A.T., Wooley, J.D., 1992. Indoor chemistry— ozone, volatile organic compounds, and carpets. Environ. Sci. Technol. 26, 2371–2377. Williams, I.D., Revitt, D.M., Hamilton, R.S., 1996. A comparison of carbonyl compound concentrations at urban roadside and indoor sites. Sci. Total Environ. 189/190, 475–483. Wolkoff, O., Clausen, P.A., Nielsen, P.A., Mølhave, L., 1991. The Danish twin apartment study; part I: formaldehyde and long-term VOC measurements. Indoor Air 1 (4), 478–490. Zhang, J., He, Q., Lioy Paul, J., 1994a. Characteristics of aldehydes— concentrations, sources, and exposures for indoor and outdoor residential microenvironments. Environ. Sci. Technol. 28, 146–152. Zhang, J., Wiison, W.E., Lioy, P.J., 1994b. Indoor air chemistry— formation of organic acids and aldehydes. Environ. Sci. Technol. 28, 1975–1982.