Comparative study of the main characteristics and composition of the mainstream smoke of ten cigarette brands sold in Spain

Food and Chemical Toxicology 50 (2012) 1317–1333

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Comparative study of the main characteristics and composition of the mainstream smoke of ten cigarette brands sold in Spain A. Marcilla, I. Martínez, D. Berenguer, A. Gómez-Siurana, M.I. Beltrán ⇑ Dpto. Ingeniería Química, Universidad de Alicante, Apdo. 99, 03080 Alicante, Spain

a r t i c l e

i n f o

Article history: Received 23 November 2011 Accepted 31 January 2012 Available online 7 February 2012 Keywords: Commercial cigarettes smoke composition Cigarettes design Nicotine Carbon monoxide Multivariate statistical analysis

a b s t r a c t In this study 10 commercial top selling cigarette brands in Spain have been machine smoked and the mainstream smoke has been analyzed. Multifunctional analysis has been satisfactorily employed to correlate the effect of the main design features of the cigarettes including amount of tobacco, filter size or paper weight with the amount of smoked tobacco and with the ratio CO2/CO. The composition of the vapor phase and that of the particulate matter have been analyzed. The particulate matter retained in the filter of the cigarettes has also been analyzed showing a distinct behavior of the compounds condensed in the cigarette filters and in the traps, related to their retention time. A general trend for the relative yield of some compounds in the different brands have been identified and confirmed by multifunctional analysis. Nevertheless, there are some noticeable compounds that behave differently in the different brands. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Tobacco is a natural product that consists of more than 3800 constituents. The chemical composition of the tobacco leaf will depend to varying extents upon tobacco variety, leaf stalk position, geographic region in which the leaf is grown, the climate during growing, local cultivation practices, among others (Tso, 1990). Tobacco constituents range from small molecules such as hydrocarbons, terpenes, carbonilics, phenols, or nitriles, to macromolecules as cellulose, lignin or nucleic acids. During the smoking process, this complex biomass is subjected to high temperatures (up to 950 °C) and a varying concentration of oxygen, producing an incomplete combustion which generates a large amount of components. Some of these compounds are toxic and carcinogenic. The smoke composition varies not only with tobacco constituents but also with cigarette varieties, cigarette design, additives employed during processing of tobacco and smoking conditions (Baker Richard, 2006; Borgerding and Klus, 2005). About 4800 compounds have been identified in tobacco smoke. Moreover, the ageing effects and artifact formation may complicate the analysis of these complex mixtures. The tobacco smoke is composed by a particulate phase and a vapor phase. Low molecular weight hydrocarbons, such as benzene, 1,3-butadiene, or toluene or small aldehydes such as acrolein or butiraldehyde are primarily constituents of the vapor phase. Nicotine, polycyclic aromatic compounds or nitrosamines are ⇑ Corresponding author. E-mail address: [email protected] (M.I. Beltrán). 0278-6915/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.fct.2012.01.046

associated primarily with the particulate phase (PM), while others are found in both phases (Counts et al., 2005). Potentially harmful smoke constituents have been identified and reviewed (Fowles and Dybing, 2003; Smith and Hansch, 2000; Hoffmann and Hoffmann, 1997). Unfortunately there is no scientific consensus on specific smoke constituents and harm induction relationships (Rodgman and Green, 2003). Recently some papers have been published on the relationship of the design features of commercial cigarettes (such as tobacco blend type, cigarettes length, filter type, ventilation holes. . .) and tar, nicotine and CO content of the smoke. Osamu et al. (2009) studied the nicotine, tar and mutagenicity of the mainstream smoke generated under two smoking regimes for the ten major Japanese cigarette brands. Commercial bidi cigarettes sold in USA containing different flavors were studied by Stanfill et al. (2003) and Polzin et al. (2007). Calafat et al. (2004) measured nicotine, tar and CO content of smoke deliveries from 77 cigarette brands purchased in 35 countries under ISO conditions. They also determined physical parameters such as filter length and weight, cigarette weight or filter ventilation levels. Pappas et al. (2007) compared heavy metals contained in the smoke of counterfeit cigarettes to authentic USA brands. Kalaitzoglou and Samara (2006) studied the content of PAH and n-alkanes contained in MSS of 59 commercial cigarette brands from Greece. These authors studied the partitioning of these two families of compounds between the gas fraction and the particulate matter, as will be commented hereafter. The dioxin and dioxin-like compounds content in MSS of twelve commercial US cigarettes brands was more recently studied by Wilson et al. (2008).

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Relatively few studies have included a comparable range of smoke constituents for a variety of commercial cigarettes. Gregg et al. (2004) studied 25 commercial UK cigarette brands and analyzed 44 smoke constituents in the mainstream smoke. They established a reasonably good correlation between nicotine and the smoke constituents of the particulate matter, while CO yield was associated with the volatile constituents yield. By other hand, 67 compounds from the smoke of several brands and types of cigarettes sold in Italy were identified by Pieraccini et al. (2008) employing SPME–GC–MS under two smoking regimes. Counts et al. (2005) tested smoke composition of 48 Philip Morris commercial cigarettes from international market regions under three smoking regimes. They analyzed a large number of smoke constituents and established some predicting relationships between tar yield and the smoke constituents for each smoking regime. In this work the composition of the smoke obtained under the ISO smoking conditions for 10 cigarette brands among the best selling in Spain in 2010 have been analyzed and compared. Multivariant analysis (software PASW Statistics 18, version 18.0.0) has been applied to establish the relationships among the main features of the cigarettes design, the amount of smoked tobacco and the ratio CO2/CO. Thirty-five compounds were identified in the vapor fraction while 85 were identified in the particulate matter, and a general trend for the relative yield of most compounds in the different brands has been established and confirmed by multifunctional analysis. The particulate matter retained in the filter of the cigarettes has also been analyzed and compared with the particulate matter retained in the traps. The results obtained for the cigarette brands sold in Spain have been compared among them and with those for other international commercial cigarettes available in the literature. 2. Materials and methods 2.1. Materials The twelve best-selling brands in Spain for the year 2010, by market share, were: Marlboro, Winston, Fortuna, Chesterfield, Ducados Negro, Ducados Rubio, Camel, L&M, Nobel, Lucky Strike, Pall Mall and John Player SP. Among them, the ten brands shown in Table 1 were chosen for this study. Table 1 also shows information of the type of tobacco blend, as provided by the tobacco companies. For privacy reasons in the following Figures and Tables, brands have been nominated with letters from A to J in a different order than that shown in Table 1. Isopropanol (99.9% purity) used for the extraction of the compounds retained in the filter of the cigarettes and in the traps was purchased from Fluka. Standards gaseous mixtures of CO2 and CO (Reference 501670) and gaseous hydrocarbons (References 501816, 22567 and 501662) were obtained from Scott Specialty Gases and they were used to identify and quantify these compounds in the tobacco smoke. Nicotine standard (99.9% purity) was purchased from Merk. Other compounds such

Table 1 Information available for the studied brands.

Marlboro Winston Fortuna Chesterfield Ducados Rubio Camel L&M Nobel Lucky Strike John Player SP

Tobacco company

Type of blend

Market share % euros

Philip Morris R.J. Reynolds Imperial Tobacco Philip Morris Imperial Tobacco R.J. Reynolds

American blend American blend American blend

15.21 10.75 10.53

American blend

9.49 6.16

Turkish and Virginia American blend

6.13

European blend American blend

4.82 2.24

Philip Morris Imperial Tobacco BAT BAT

as benzene (Ref. 21803.291), toluene (Ref. 1.08325.1000) and acetone (Ref. 1.00014.1000) were purchased from VWR, while acetaldehyde (Ref. 00070), furan (Ref. 185922) and acetonitrile (Ref. 34967) were supplied by Sigma. 2.2. Experimental procedure Before performing the smoking experiments, 200 cigarettes of each brand were disassembled and the tobacco, the filter and the paper were weighed separately. The tobacco was tumbled and mixed and then the cigarettes were reassembled. The reassembled cigarettes were conditioned for at least 48 h at 22 °C and a relative humidity of 60% prior to smoking. The smoking machine employed allows five cigarettes to be smoked simultaneously and the pressure of aspiration was never higher than 1.5 kPa. Puff volume was 35 mL, taken during 2.0 s, with a puff frequency of 60 s, according to the ISO 3308. Cigarettes were placed in the ports of the smoking machine ensuring that the ventilating holes were not blocked. In this work the effect of the amount of tobacco in the commercial cigarettes was also considered among the variables under study. That is the reason why differently to the ISO standard, the puff number was 8 in all cases, while the ISO establishes to smoke up to a butt length of filter tipping overwrap plus 3 mm. Each smoking experiment was repeated 3 times. According to the ISO 3308, a condensing trap was located after the mouth end of the cigarettes. Therefore, the less volatile compounds of the mainstream smoke may condense in two points, i.e., in the filter of the smoking cigarette and in the trap, while the rest of the mainstream smoke was collected in a Tedlar bag. Before and after each experiment the filter tips and the traps were weighed. The difference has been called TPM-F (total particulate matter condensed in the filters) and TPM-T (total particulate matter condensed in the traps). The amount of smoked tobacco was determined as the difference between the initial amount of tobacco contained in each cigarette and the amount of tobacco remaining in the butt after the smoking process was finished. The condensed products retained in the traps, as well as those in the filters of the cigarettes, were extracted separately with isopropanol and analyzed by GC/MS. Up to 35 compounds were identified in the fraction collected in the Tedlar bag, and 85 in the two TPM fractions. The analysis and quantification have been carried out as follows. CO was quantified by GC with a TCD detector in a Shimadzu GC-14, with a CTRI column. The injector temperature was 28 °C and that of the detector was 110 °C. Helium was used as carrier gas, with a flow rate of 40 mL/min. The volume of sample injected was 2.5 mL. Other components collected in the Tedlar bag were identified and analyzed by GC with MS and FID detectors in an Agilent 6890N gas chromatograph, with a GS-GASPRO column. The injector temperature was 150 °C, and the GC oven temperature program was: 35 °C for 10 min, 5 °C/min up to 100 °C, 15 °C/min up to 200 °C and 10 min at the final temperature. Helium was used as carrier gas (2 mL/min) and the volume of sample injected was 150 lL. To quantify 1,3-butadiene, HCN, isoprene, acrolein, propionaldehyde, crotonaldehyde and isobutiraldehyde, response factors were calculated from a standard gaseous hydrocarbons (Scott Specialty Gases). To obtain the calibration curves for benzene, toluene, acetone and acetaldehyde, different amounts of the vapor in equilibrium with the corresponding pure liquid at 8 °C were injected. The area of the peak for each compound was represented versus the injected amounts, and the corresponding response factors (RF, area per gram) were calculated from the slope of the regression lines. Five-point calibration curves were constructed and regression coefficients higher than 0.999 were obtained in all cases. For other compounds identified in the gaseous fraction, the RF of the compound with the closest retention time was employed. Results corresponding to these compounds have not been considered for comparison among other studies but they have been used to compare the different brands in this study. The particulate matter condensed in both, traps and filters, was extracted separately with isopropanol, dried and analyzed by GC/MS in an Agilent 6890N gas chromatograph, with a HP-5-MS column. The injector temperature was 250 °C, and the GC oven program used in this case was: initial temperature of 40 °C during 5 min, ramp of 12 °C/min up to 320 °C and 25 min at the final temperature. The carrier gas was helium with a flow rate of 2 mL/min, and the volume of sample injected was 1 lL. Assignation of peaks to compounds was done by comparison with the Wiley MS library. 85 peaks were assigned to compounds with probability close to, or higher than, 90%. A calibration curve with standards of nicotine was used. The response factor of nicotine was employed for all compounds identified in the particulate matter. Except for nicotine, results shown for the particulate matter have to be considered as semiquantitative and only suitable for comparative purposes among the different brands studied in this work.

3. Results and discussion 6.00 5.14

3.1. Preliminary analysis Several physical properties of the cigarettes under study are shown in Table 2. It includes the initial amount of tobacco, the overall cigarette, the filter and paperlength, the cigarette diameter, the filter and paper weight, and the filter ventilation, evaluated as

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A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333 Table 2 Physical properties of the cigarettes under study (mean value ± standard deviation). All measurements were done for 5 cigarettes. Cigarette brand

Tobacco amount mg/cigarette

Cigarette length mm

Filter length mm

Paper length mm

Cigarette diameter mm

Filter weight mg/cigarette

Paper weight mg/cigarette

Ventilation (hole rows)

A B C D E F G H I J

640 ± 21 612 ± 21 648 ± 22 604 ± 22 619 ± 36 643 ± 25 655 ± 11 653 ± 40 622 ± 32 672 ± 19

81.6 ± 0.4 82.7 ± 0.2 82.3 ± 0.1 83.4 ± 0.2 82.3 ± 0.5 83.8 ± 0.4 83.5 ± 0.3 82.5 ± 0.2 83.5 ± 0.1 83.6 ± 0.4

20.4 ± 0.5 27.1 ± 0.4 21.1 ± 0.4 21.0 ± 0.2 21.0 ± 0.3 21.0 ± 0.4 20.9 ± 0.2 22.0 ± 0.3 21.1 ± 0.1 20.9 ± 0.1

57.2 ± 0.6 57.7 ± 0.4 57.2 ± 0.1 58.7 ± 0.2 57.6 ± 0.7 59.1 ± 0.5 58.6 ± 0.4 56.7 ± 0.3 58.7 ± 0.4 58.8 ± 0.5

7.4 ± 0.2 7.6 ± 0.1 7.3 ± 0.2 7.7 ± 0.1 7.5 ± 0.3 7.6 ± 0.1 7.6 ± 0.1 7.6 ± 0.2 7.7 ± 0.2 7.7 ± 0.2

120.7 ± 2.8 158.1 ± 3.0 114.6 ± 3.0 126.8 ± 2.4 122.4 ± 1.7 119.0 ± 1.4 115.0 ± 3.1 117.7 ± 4.4 119.7 ± 4.6 123.8 ± 3.5

41.0 ± 1.8 35.6 ± 0.4 39.4 ± 0.5 43.8 ± 0.8 40.3 ± 1.3 42.4 ± 1.1 41.7 ± 0.4 35.5 ± 0.6 42.9 ± 0.3 40.7 ± 1.0

4 2 3 1 3 4 4 4 1 4

the number of hole rows. All the filters were cellulose acetate tips. The average amount of tobacco smoked for each brand, the particulate matter delivered, and the CO2/CO ratio are shown in Table 3. According to ISO 4387 the particulate matter (TPM) is that collected immediately after the mouth end of the cigarette. In this work we have also considered the particulate matter retained in the filter of the cigarettes (TPM-F), determined and extracted in the same way than TPM-T. TPM-F is retained in the filter of the cigarette and consequently it is not frequently reported but, as it will be shown below, an interesting behavior of the composition of both, TPM-T and TPM-F, can be observed when they are individually analyzed. The ratio CO2/CO might indicate the extent of incomplete combustion reactions (i.e., the ratio decreases as the extent of incomplete combustion increases). As the incomplete combustion transforms carbon in CO and other species that may be toxic, such as PAHs, high values of CO2/CO are desirable. All tobacco brands show values within the range 3.3–3.8 except brands B and H which present higher ratios. Large differences in the amount of smoked tobacco were observed, despite, as mentioned above, 8 puffs were always taken. Fig. 1 represents the amount of initial tobacco contained in the cigarettes and the smoked tobacco for each brand. The general trend is the higher the amount of initial tobacco the lower the amount of tobacco consumption during smoking, probably due to the tightest packing of tobacco, and consequently to the lower availability of oxygen (Pakhale and Maru, 1998). The more obvious exception to this rule is the case of brand B which presents by far the longest filter and the shortest paper length (Table 2), so oxygen permeability must be low and pressure drop across the filter tip very high, both factors contributing to a lower consumption of tobacco. In fact, brands B and C present the same initial weight of tobacco but the volume of cigarette occupied by tobacco in B is much lower than in C, which may aid to explain that they both are also the brands showing the lowest and highest consumption of tobacco during smoking.

A statistical principal component analysis (PCA) has been performed using the software PASW Statistics 18, version 18.0.0 (see Appendix A). The cigarettes design characteristics shown in Table 2 have been considered, together with the amount of tobacco smoked and the ratio CO2/CO (Table 3). Four principal components have been extracted, accounting for the 92.0% of the total variance of the studied samples, and thus permitting us to reduce the dimensionless of the problem. The scores of the samples in the principal components space shows three clusters. The first one is formed by brands H and B, which show the lowest values of PC1. The second cluster includes brands C and A, and in less extent B, with the lowest values of PC2. Finally the third one is a homogeneous group of tobacco brands including D, F, G, I and J. More details of the PCA of these groups of samples can be found in Appendix A. 3.2. Analysis of the vapor phase Table 4 shows the yields of the compounds analyzed in the vapor fraction for the studied brands. Among them, the compounds showing the major amount are by far CO and CO2. CO is a wellknown poison and Spanish regulations allow a maximum quantity of CO of 10 mg/cigarette (Ministry of Health, BOE 19-10-2002). All tobacco brands are within the value allowed except C, which slightly exceeds. Excluding CO and CO2, the major compound present in the vapor fraction is methane. Other light hydrocarbon molecules are also present in high amounts such as ethane, ethylene, propane and propene. It is worth mentioning that the relative yield of most of the gaseous hydrocarbons in the different brands follows a similar pattern, which we have named through the text as the ‘‘general pattern’’. For example, Fig. 2 shows the histograms of some compounds present in the vapor fraction; ethane, propene and isobutene are shown, all of them showing very similar trends for all brands. The same situation can be found for methane, ethylene, ethane, propane, butane, 1-butene, isobutane and most of the

Table 3 Smoked tobacco amount, TPM-F, TPM-T, TPM-F + TPM-T and CO2/CO ratio for the different brands (mean value ± standard deviation for three experiments). Cigarette brand

Smoked tobacco amount mg/cigarette

TPM-F mg/cigarette

TPM-T mg/cigarette

TPM-F + TPM-T mg/cigarette

CO2/CO

A B C D E F G H I J Mean value

536.4 ± 33 488.7 ± 39 579.9 ± 18 486.7 ± 21 495.7 ± 20 499.0 ± 19 482.5 ± 28 480.7 ± 17 506.4 ± 29 491.1 ± 23 504.7

4.6 ± 0.7 3.4 ± 2.9 11.4 ± 1.2 3.7 ± 1.8 3.2 ± 1.0 2.9 ± 1.0 1.8 ± 2.0 4.1 ± 1.1 2.7 ± 1.9 3.8 ± 1.9 4.2

6.9 ± 1.3 4.8 ± 1.6 11.2 ± 1.0 5.5 ± 0.4 5.8 ± 1.0 5.2 ± 0.4 5.3 ± 1.0 4.5 ± 0.3 4.1 ± 0.1 5.5 ± 0.2 5.9

11.5 ± 1.0 8.2 ± 4.3 22.6 ± 2.1 9.2 ± 1.9 9.0 ± 0.6 8.1 ± 0.7 7.1 ± 1.0 8.6 ± 1.2 6.8 ± 1.9 9.3 ± 1.8 10.0

3.3 ± 0.4 4.0 ± 0.3 3.7 ± 0.2 3.8 ± 0.1 3.7 ± 0.2 3.6 ± 0.02 3.4 ± 0.2 4.5 ± 0.6 3.7 ± 0.2 3.4 ± 0.04 3.7

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µg/cigarette 800

Inital tobacco smoked tobacco

700 600 500 400 300 200 100 0 B

C

A

E

F

D

J

I

G

H

Fig. 1. Amount of tobacco contained in the cigarettes and smoked tobacco for each brand.

compounds in the gaseous fraction. In all these cases brand C followed by E show the highest amount of these compounds, while B and G yield the lowest amounts. The amount of smoked tobacco follows the same pattern shown for these compounds, and probably, the relative amount of the precursors involved in the formation of these compounds is the same in all tobacco brands studied. Counts et al. (2005) found that linear functions strongly correlate tar yield with any individual smoke constituent yield, when smoke was obtained under the ISO conditions. For the mentioned hydrocarbons we have found that the pattern obtained is very similar but, there are some compounds that depart from this ‘‘general pattern’’ as will be shown. Small aldehyde molecules present in tobacco smoke are particularly harmful, and according to the EPA these are the major contributor to cancer risk (Fowles and Dybing, 2003). Among aldehydes, acetaldehyde is that with the highest cancer risk and shows values as high as 528.3 lg/cigarette in brand C, being the lowest value 249.5 in brand B (Table 4). The average amount of acetaldehyde for all brands studied is 321.2 lg/cigarette. Isobutiraldehyde presents much lower yields but behaves similarly to acetaldehyde and to the other compounds previously commented on in the vapor fraction following the ‘‘general pattern’’, where brand C presents the highest concentration and brand B the lowest. An exception to this general pattern is that shown for some aldehydes such as propionaldehyde, acrolein and crotonaldehyde (Fig. 2). Brands C, F, E and A present the highestamounts of acrolein and propionaldehyde, while G followed by B yield the lowest amounts. Other remarkable compounds shown in Table 4 are 1,3-butadiene and hydrogen cyanide. According to Fowles and Dybing (2003), 1,3-butadiene presents the highest cancer risk index of all constituents of cigarettes smoke. Excluding brand C which doubles the amount obtained in some other brands, all brands show very close values. HCN is the smoke constituent representing the highest index for cardiovascular effects. The average value for this compound in the studied cigarettes is 6.6 lg/cigarette, being brand C that showing the largest value of 9.4 lg/cigarette. Acetone and isoprene present very high yields in all brands, reaching values as high as 287.3 and 163.5 lg/cigarette, respectively. Both compounds present patterns departing from the general one commented above, with brand E proportionating the highest yields and brand B the lowest (Fig. 2). Other compounds which appear in the vapor phase at high concentration and that are known by their high toxicity are benzene and toluene. Benzene follows a general pattern similar to light hydrocarbons and small aldehydes, with amounts that vary from 45.7 to 119.5 lg/cigarette (brands B and C, respectively). The toluene behavior is much different (Fig. 2). Brands C, D and E have concentrations of toluene

around 100 lg/cigarette, while the other brands (excluding B) are around 15 lg/cigarette. Other compound that is worth mentioning is 2,5-dimethylfuran that has been commonly used as tracer compound of the environmental tobacco smoke (ETS) (Bi et al., 2005) The behavior of the different brands for 2,5-dimethylfuran is much different than for other compounds as can be seen in Fig. 2. Summarizing, the vapor fraction of smoke of brand C is that presenting the highest amount of most of the analytes studied. For isoprene, crotonaldehyde and 2,5-dimethylfuran, brand E is the one providing the more concentrated gases, and for iso-butane and acetonitrile, the smoke from brand J is the more concentrated. The lowest yield for most of the compounds in the vapor fraction is obtained for brand B but in some particular cases, for example aldehydes (acrolein, propionaldehyde, crotonaldehyde), brand G has the lowest concentration. Brands A, D, F and H show the lowest concentration for a few compounds. Attending to the global yield of gases (Table 4), brands B and G provide the lowest yields, while by far brand C, followed by E give the highest. The results of the multivariate statistical analysis of the 35 variables included in Table 4 are shown in Appendix B. The dimensionless of the problem has been reduced, and 5 principal components have been extracted from the 35 original variables characterizing the chemical composition of vapor phase. These 5 principal components represent the 94.9% of the total variance of the problem. The main contributors to the first principal component (PC1) are those compounds showing the general pattern previously commented on, mainly light hydrocarbons and small aldehydes. The other principal components include compounds showing a different pattern than those grouped in PC1, and are in good agreement with the statements carried out after the visual inspection of the experimental results. Moreover, this analysis also permits us to distinguish other compound with similar behavior (for more details, see Appendix B). In order to summarize, Fig. 3 shows the dendogram resulting from a hierarchical cluster analysis. This graphical representation reflects the formation of groups based in the measurement of the euclidean distance among samples and/or clusters in the 35-dimmensional space defined by the variables shown in Table 4. As it can be seen, a cluster includes brands H, I, G, A, F, J, and B, another cluster only includes brands D and E, and brand C is quite different from the rest. The characteristics of the clusters can be easily deduced from the values of the principal components: brand C has a noticeably high value of PC1, accordingly with its higher global yields of the compounds included in such principal component. Brands H, I, G, A, F, J and B have low values of PC1 and PC2, whereas brands D and E also have low values of PC1, but higher values of PC2. 3.3. Particulate matter The main fraction of the smoke is formed by condensable products. In this work 85 components were identified in the particulate matter. Only the yield of the products retained in the traps is commonly reported, but in this work our interest was to compare the differences in the whole evolved products for the most common commercial cigarettes. In this way, and differing from other works, the particulate matter condensed in the filter of the cigarettes has also been extracted and analyzed in the same way than that condensed in the traps. A very interesting behavior has been observed as will be commented hereafter. Table 3 contains the data of the total particulate matter condensed in the filters and the traps and the sum of both for the ten brands. For all brands the TPM-F is much lower than TPM-T except for brand C. The nature of the filters and traps employed is the same in all the samples despite the size of the filters varies slightly (Table 2), but this does not seem to be responsible for the big differences found in the relative amount of matter

Table 4 Yield of the compounds identified in the vapour phase for the 10 commercial brands. Mean values for three experiments (all amounts are in lg/cigarette, except for CO and CO2 which are mg/cigarette) and variation coefficient (%). Compound

B

C

D

E

F

G

H

I

J

Average

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

9.0 30.0 499.2 194.0 115.7 13.5 85.7 104.1 8.8 30.0 26.1 25.3 6.6 15.2 23.0 17.6 7.2 13.3 5.7 8.0 8.9 12.9 116.5 6.3 1.3 68.6 285.2 172.6 14.5 12.3 37.1 18.2 5.1 2.9 3.1 2005

21 14 19 25 25 25 20 26 14 21 24 26 32 24 27 9 21 38 25 5 7 4 12 46 25 23 17 22 15 9 22 14 6 29 23 –

4.9 19.7 393.2 166.1 89.0 10.4 77.5 85.7 7.2 21.6 23.3 21.2 4.5 12.2 20.8 16.6 6.9 6.4 5.0 8.3 7.2 17.4 35.0 5.8 0.9 45.7 249.5 164.6 10.1 8.3 29.4 43.0 8.3 2.2 3.2 1703

38 25 20 14 20 28 8 15 17 19 12 14 29 18 14 6 11 3 11 7 37 20 1 14 31 21 15 14 27 14 10 10 35 6 35 –

10.8 39.5 742.8 299.2 195.1 27.5 136.3 176.3 14.1 43.8 42.6 42.4 12.2 27.6 38.1 30.7 12.2 22.6 9.4 15.5 16.1 34.6 119.8 11.0 1.4 119.5 528.3 270.6 20.0 15.6 66.9 113.3 10.5 4.5 5.9 3394

6 3 7 6 3 9 6 1 6 1 4 3 1 4 9 11 12 7 3 6 9 4 7 10 51 3 4 22 9 6 8 27 6 4 10 –

7.8 29.4 514.6 212.7 120.3 14.8 99.0 113.9 9.2 25.1 30.1 27.7 6.6 16.7 26.9 20.7 8.6 10.4 7.2 8.9 11.0 23.0 140.1 8.9 2.0 64.3 302.8 260.0 10.1 8.9 27.3 102.8 10.1 2.1 3.7 2291

21 17 6 8 4 9 6 7 3 3 9 10 9 7 5 16 2 12 7 5 4 7 3 6 8 2 5 10 11 8 3 2 7 10 8 –

8.3 30.4 580.2 234.1 134.1 17.0 107.2 124.7 19.0 41.5 33.1 29.2 7.0 17.9 30.7 22.5 8.7 12.0 7.7 9.9 10.1 17.7 163.5 8.0 2.0 73.1 361.1 287.3 16.0 11.4 48.9 96.0 11.9 4.7 4.1 2601

31 26 5 4 3 1 7 6 7 4 9 5 23 2 1 4 6 14 9 13 8 28 8 7 17 5 4 12 23 1 16 29 19 16 17 –

6.9 24.7 494.9 201.7 114.8 16.4 93.4 107.7 8.5 22.0 28.6 26.3 7.0 15.2 24.4 13.5 8.4 10.7 5.5 7.0 9.8 20.7 107.3 4.9 2.0 68.9 314.5 254.3 18.3 14.9 55.8 14.3 5.4 3.0 4.6 2139

18 12 5 7 1 8 2 1 7 4 2 5 13 2 3 5 7 5 9 8 14 6 3 4 4 3 4 12 10 10 9 8 9 6 6 –

6.5 22.4 433.2 177.0 99.5 12.9 81.1 94.4 7.9 18.6 25.8 23.2 5.6 14.0 22.6 15.3 7.3 9.8 5.2 7.4 8.3 18.7 119.1 8.0 1.7 56.3 283.3 184.7 7.8 7.5 28.0 12.6 6.2 2.0 3.5 1842

17 11 4 3 5 7 5 2 2 6 1 2 3 2 5 8 2 11 5 5 2 2 2 17 5 5 9 9 8 9 2 4 12 8 5 –

5.0 22.3 465.6 188.2 106.2 12.7 86.3 100.5 8.7 24.9 26.6 23.8 5.1 14.1 24.5 18.2 7.6 10.5 6.4 8.1 8.2 14.3 113.0 5.6 1.7 53.6 270.2 207.4 10.9 10.1 30.7 12.5 4.5 3.3 3.3 1921

4 7 4 1 2 4 3 3 4 5 1 5 10 1 3 17 1 4 1 8 6 8 3 7 5 6 4 10 19 12 6 1 2 8 20 –

6.5 23.8 511.2 202.3 112.5 14.6 92.7 107.1 8.6 25.5 27.3 25.7 5.8 15.8 26.3 17.5 7.9 12.9 6.8 8.3 8.7 21.2 126.4 6.8 1.7 62.1 309.6 251.1 9.5 12.0 53.2 15.8 5.3 2.8 3.4 2156

15 4 9 3 3 11 1 3 9 6 3 6 4 4 9 6 3 12 6 2 2 3 9 10 5 1 2 9 8 18 29 6 37 3 2 –

7.4 25.4 498.6 198.6 117.1 16.0 91.5 111.6 33.8 22.9 28.4 27.2 6.6 16.2 26.9 21.0 9.6 10.6 7.0 8.4 9.2 22.7 140.2 7.4 1.9 68.3 307.8 180.0 12.0 9.7 70.5 16.6 4.8 3.5 3.7 2166

18 3 4 1 2 8 2 4 3 1 1 4 1 1 7 4 10 13 5 5 5 3 4 15 6 4 9 18 15 19 23 1 4 18 7 –

7.3 26.8 513.1 207.4 120.4 15.6 95.1 112.6 12.6 27.6 29.2 27.2 6.7 16.5 26.4 19.4 8.4 11.9 6.6 9.0 9.8 20.3 118.1 7.3 1.7 68.0 321.2 223.3 12.9 11.1 44.8 44.5 7.2 3.1 3.8 2222

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

CO CO2 Methane Ethane Ethylene Ethyne Propane Propene Iso-butane Chloromethane Butane 1-Butene 1,2-Propadiene 1,3-Butadiene Isobutene Cis-2-Butene Pentane Methanethiol Hydrogen cyanide 1-Pentene Furan Isohexane Isoprene Hexane 1-Hexene Benzene Acetaldehyde Acetone Acrolein Propionaldehyde Acetonitrile Toluene 2,5-Dimethylfuran Crotonaldehyde Isobutyraldehyde Sum

A Mean

1321

1322

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

condensed in the filters and the traps. The way in which the condensed products are delivered between filters and traps may depend on a big number of factors and the nature of the compounds may play an important role. It is worth mentioning that the value of TPM-F + TPM-T (Table 2), follows the ‘‘general pattern’’ commented previously for most of the gaseous compounds. The highest value of TPM-F + TPM-T is obtained for brand C, while the lowest is for brand I and, excluding C, the differences in the TPM yields are relatively small among brands. The behavior is also valid for TPM-T that would be the particulate matter leaving the mouth end of the cigarette. The yield of the 85 compounds analyzed for the ten brands in the filters, and the traps are shown in Tables 5 and 6. The compounds have been ordered according to their retention time. In order to facilitate comparisons, both tables show the same compounds despite some of them were not found in the traps. It is worth mentioning, the case of naphthalene, that has been commonly reported as a component of tar. We have found naphthalene in the filters in amounts ranging from 0.85 to 3.34 lg/cigarettes but it was not found in the traps. The detection limit of our method is 0.2 lg/cigarette and possibly naphthalene was present in amounts very close to the detection limit or even lower. Pieraccini et al. (2008), for example, reported amounts of naphthalene in TPM ranging from 0.16 to 0.48 lg/cigarette in Italian commercial cigarettes. A remarkable aspect that can be observed is the way the different compounds are delivered between filters and traps according to their retention time. The amount of most of compounds with low retention time (i.e., compounds with relatively low molecular weight) is higher in the filters than in the traps, while the very opposite is true for the heaviest compounds. For compounds with low retention time, such as furfural and styrene, the yield in the filters is more than four times higher than that in the traps (for example for furfural, phenol or indene the yield in the filters can be even 10 times higher than in the traps). Compounds with medium retention times, such as nicotine or 2,30 -bipyridine, are more uniformly delivered between filters and traps. The heaviest compounds, i.e. cotinine, octadecane and heptacosane, present higher amounts in the traps than in the filters. This is true for most of compounds and brands but there are some exceptions. Hydroquinone, among the relatively low molecular weight compounds, and pentadecane and eicosane, among the compounds with high retention time are exceptions. The explanation to this observation may involve aspects as the different affinity of any particular compound for the filter and the trap, their relative concentration and their vapor pressures. The differences in the pressure drop during the puffs could also affect the way the different compounds are sorbed or desorbed in filters and traps, making more difficult the interpretation. Kalaitzoglou and Samara (2006) reported that an increase in the pressure drop during smoking may cause desorption of PAHs from the TPM which might favor their distribution in the gas phase. Compounds from other chemical classes (high hydrocarbons were also studied by these authors) may behave differently. The pressure drop might be related to the density and size of the filters, the ventilation rates, among other design features of the cigarettes, and also on the smoker habits. Fig. 4 shows the histograms of some compounds condensed in the filters and the traps. These compounds have been selected because they were present in high amounts or because they have been reported to be implied in human diseases. Some phenols are included in the Hoffmann list by their high toxicity. Fig. 4 and Tables 5 and 6 include the results for phenol, p-cresol and ocresol. It can be observed that, excluding brand C, the relative amount of phenols produced by the different brands is quite similar. The hydroquinone behavior (Fig. 4) is quite different, since large relative differences can be found among the different brands.

According to Borgerding and Klus (2005) the hydroquinone yield is more sensitive to tobacco blend type than other smoke constituents and is delivered in much higher extent in traps. Apart from water, nicotine is the major individual compound contained in the particulate matter and it is also the main responsible for the addictive behavior of smokers. Nicotine in the TPM-T (Fig. 4 and Table 6) for the 10 brands under study varies from 282.5 to 613 lg/cigarette (brands B and C, respectively), and presents a relatively low variation coefficient for all the brands. Brands A and C present nearly the same amount of nicotine despite TPM-T is much higher for C than for A. The histogram for myosmine is quite similar to that of nicotine. In fact, the molecular weight and chemical structure of both pyridine derivatives are very similar. The behavior of cotinine is much different as its structure is, and its concentration in traps is higher than in filters, as commented above for compounds whit high retention time. Fig. 4 also shows the histograms for some hydrocarbons present in the particulate matter. The histograms of these three hydrocarbons are very similar, as it happened with hydrocarbons in the vapor phase that followed the ‘‘general pattern’’. There are some hydrocarbons in TPM-F and TPM-T, such as eicosane and pentadecane, which present a different pattern. It is relatively frequent to assume that if a cigarette yields more tar than others it may be more toxic, and in general it may be true. In this mean the current European Community Regulations that are limiting exclusively the CO, nicotine and ‘‘tar’’ content. At this respect, Borgerding and Klus (2005) reviewed some studies that demonstrated good correlations (R2 higher than 0.9) for most of the individual Hoffmann analytes and tar, nicotine or CO. They pointed out that these relationships depend mainly on tobacco blend and other cigarette design features. Nevertheless, the relative production of a compound or a family of compounds may vary differently to tar. For example, brand E presents a content of TPM-F and TPM-T lower than the average of all brands and a nicotine yield very close to the average. Nevertheless, the content of brand E in some well-known toxic compounds such as isoprene, crotonaldehyde or toluene is the highest of all brands. Brand I is that with the lowest TPM and the lowest yield for most of the condensed compounds reported, while the lowest yields in gases are produced by brand B for most of compounds followed by brand G. On the other hand, according to Counts et al. (2004) the yield of any compound of the vapor phase is more similar for different commercial cigarettes than the TPM constituents yield. This would also be our case if among vapor phase constituents crotonaldehyde, isobutiraldehyde and toluene were excluded. The other components of the vapor phase present variation coefficients lower than those of the particulate matter. Attending to the global yield of TPM-T (Table 3), brands I and H provide the lowest yields, while by far brand C, followed by A are those providing the highest ones. The application of multivariate statistical analysis is especially valuable in this case where there are a large amount of variables and experimental results, as Tables 5 and 6 reflect. The low variability of the studied variables also supports the need of applying some technique in order to simplify the analysis of results. The results obtained (see Appendix C) indicate that the dimensionless of the problem has been reduced by application of PCA, to 8 and 9 principal components for traps and filters, respectively. The percentage of the variance explained is very high in both cases: in traps, the 8 principal components selected account for the 98.8% of the total variance, while in the filters the 9 principal components represents the 100% of the variance. The dendogram showing the formation of groups of brands based in the chemical composition of the particulate matter retained in the traps is presented in Fig. 5. As it can be seen, in good agreement with the results obtained in the analysis of the gaseous fraction (Fig. 3), brand C is noticeably separated from the rest, due to its high value of PC1

1323

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333 Ethane

µg/cigarette 350.0

Propene

µg/cigarette 200.0

300.0 250.0

180.0

40.0

160.0

35.0

140.0

30.0

120.0

200.0

Isobutene

µg/cigarette 45.0

25.0

100.0 150.0

20.0

80.0

15.0

60.0

100.0

10.0

40.0 50.0 0.0 A

B

C

D

E

F

G

H

I

5.0

0.0

0.0

J

A

Acrolein

µg/cigarette 25.0

20.0 B

C

D

F

G

H

I

B

C

D

16.0

4.5

14.0

4.0

E

F

G

H

I

J

H

I

J

H

I

J

Crotonaldehyde

µg/cigarette 5.0

3.5

12.0 15.0

A

J

Propionaldehyde

µg/cigarette 18.0

20.0

E

3.0

10.0

2.5 8.0

10.0

2.0

6.0 5.0

0.0

1.5

4.0

1.0

2.0

0.5 0.0

0.0 A

B

C

D

E

F

G

H

I

J

Isoprene

µg/cigarette 180.0

A

B

C

D

E

F

G

H

I

J

Toluene

µg/cigarette 120.0

A

B

C

D

F

G

2,5-Dimethylfuran

µg/cigarette 14.0

160.0

E

12.0

100.0

140.0 120.0

10.0

80.0

8.0

100.0 60.0

80.0

6.0

60.0

40.0

4.0

40.0 20.0

2.0

20.0 0.0

0.0

A

B

C

D

E

F

G

H

I

0.0

J

A

B

C

D

E

F

G

H

I

J

A

B

C

D

E

F

G

Fig. 2. Histograms of some compounds in the vapour phase for the studied brands.

Euclidean distance

and J, and brands A and B appear as individual clusters. The interpretation of these groups according with the respective principal components values can be found in Appendix C. Finally, Fig. 6 shows the dendogram corresponding to the classification of brands according with the chemical composition of the particulate matter retained in the filters. As it can be seen, the results are relatively similar to the classification based in the composition of the vapor phase and of the particulate matter retained in the traps. Brand C appears far away from the other brands, and groups formed by brands G, H and I, and by B, D, F and J can be defined, appearing brands A and E in individual groups (the justification of these groups according with the principal component values can be found in Appendix C). 3.4. Comparison with other studies on commercial cigarette brands

H

I

G A

F

J

B

D

E

C

Case Fig. 3. Dendogram resulting from the application of hierarchical cluster analysis to data shown in Table 4 corresponding to the vapor phase composition.

(i.e., its relatively high yields of products). Moreover, a group appears with brands D, E and F, another group with brands G, H, I

Comparisons must be done with care, taken into account the differences commonly reported when comparing tobacco smoke yields among different laboratories (Counts et al., 2004; Gregg et al., 2004). These differences have been found even for reference cigarettes smoked under the same normalized conditions. There is a considerable number of variables largely affecting to the smoking process and sometimes underestimated, such as pressure drop and packing of the tobacco in the cigarette, block of ventilation holes, collection method of smoke or even the lighten method, as it has been thoroughly discussed by different authors (Borgerding and Klus, 2005; Baker Richard, 2006; Adam et al., 2009; Li et al., 2003). Moreover, there are no internationally recognized standard methods for the determination of other compounds different from

Assignation

B

C

D

E

F

G

H

I

J

Average

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

2.5 2.7 29.8 0.9 6.1 7.5 13.1 10.7 1.1 9.0 5.3 7.0 1.3 5.5 2.6 – 0.9 1.0 1.5 3.4 17.3 3.4 4.4 26.2 2.6 7.9 2.5 4.8 6.4 2.5 8.1 2.1 1.9 15.2 0.8 7.3 4.9 2.8 7.5 2.8 3.7 5.3 5.0 3.7 1.7 2.2 3.9 3.1 4.8 4.2 7.7 9.3 3.3

6 18 13 26 15 2 8 7 8 4 22 18 7 15 15 – 28 34 23 6 11 14 1 13 13 17 8 14 8 3 14 15 15 12 5 20 17 2 11 5 14 18 2 3 7 16 5 3 29 8 8 1 14

2.1 2.2 17.4 2.2 3.0 4.7 8.1 6.2 1.6 6.8 3.9 4.3 0.6 3.5 1.4 0.7 – 1.4 1.8 1.9 11.0 2.2 2.4 18.5 – 7.2 3.8 4.3 6.0 2.5 6.9 1.3 1.3 12.5 1.6 5.7 4.9 2.3 5.3 2.6 4.5 5.4 5.7 2.8 1.0 2.4 2.5 2.7 1.7 2.4 7.6 10.3 3.9

10 30 7 9 18 9 11 21 12 11 27 7 17 7 4 16 – 20 23 1 10 19 8 7 – 2 3 19 17 5 4 2 20 7 20 3 22 66 4 9 5 38 27 24 6 19 4 2 6 13 11 14 10

4.1 4.3 42.4 1.7 14.8 11.2 17.9 14.2 2.9 15.6 10.7 12.2 2.8 9.9 4.5 3.1 1.1 1.7 3.5 4.8 28.2 6.1 7.8 49.8 5.9 22.9 4.0 – 11.1 6.0 16.0 3.6 4.0 34.2 3.1 14.7 9.6 5.2 9.9 8.0 7.3 11.0 2.6 9.1 3.3 5.1 5.7 7.0 6.0 4.6 14.4 16.7 8.0

10 1 13 21 2 19 3 2 14 4 9 16 9 2 16 11 17 5 27 3 1 5 14 4 2 10 13 – 11 18 9 7 19 8 5 2 2 13 6 11 9 6 3 4 8 2 9 2 9 9 4 10 6

3.3 2.7 21.6 2.6 3.7 5.5 8.9 7.2 2.1 8.6 5.3 4.3 1.1 3.9 1.5 1.4 1.0 0.5 1.5 2.6 11.8 2.5 2.7 22.2 3.5 8.8 4.2 6.1 5.9 2.7 6.9 1.4 1.6 13.8 0.7 6.3 4.9 1.5 – 2.9 3.4 6.5 5.8 3.0 1.6 2.7 3.3 4.3 3.6 2.2 4.7 10.4 3.8

36 7 19 11 18 17 17 12 6 23 7 6 9 2 2 34 8 10 17 6 18 31 4 8 29 1 6 11 9 7 11 6 17 5 66 9 1 18 – 3 4 6 2 2 10 21 3 8 13 44 21 9 4

4.0 3.5 27.4 2.5 6.0 7.3 12.1 8.6 2.7 10.7 7.8 7.1 1.5 5.1 1.9 1.5 1.2 2.2 2.8 3.3 16.0 1.7 4.1 26.1 4.4 10.9 5.1 – 6.0 3.1 8.9 1.9 2.2 17.6 3.3 7.9 5.9 3.0 7.0 3.7 7.7 7.8 5.4 4.0 2.0 3.2 3.8 4.8 7.8 2.9 2.7 9.2 4.7

17 10 21 10 25 31 26 21 11 22 5 28 40 31 53 7 26 50 31 26 22 26 27 14 1 9 2 – 10 24 6 10 29 15 6 13 23 6 27 9 1 9 10 17 28 34 6 11 2 26 9 17 1

3.1 2.8 24.4 1.9 6.5 6.6 10.5 9.5 2.4 8.9 4.7 5.0 1.3 5.0 1.0 0.6 1.0 0.4 2.4 2.6 14.0 3.3 3.5 23.6 3.0 9.1 4.1 – 5.2 3.9 7.9 2.3 1.7 15.5 1.5 7.7 5.7 3.5 6.5 3.5 2.9 7.7 4.7 3.3 1.5 2.9 3.9 3.6 4.7 2.2 3.8 8.8 4.4

8 5 9 11 3 8 12 6 35 11 12 8 16 7 11 15 12 49 8 7 9 3 10 2 3 8 10 – 3 9 2 2 5 1 13 5 5 9 17 8 4 5 9 1 18 12 2 6 23 26 22 2 2

1.9 1.4 13.4 2.1 – 2.6 5.8 5.4 1.2 5.1 2.8 2.9 0.6 2.9 1.1 0.4 0.4 0.6 1.2 1.8 7.5 1.1 1.7 15.6 1.2 4.6 1.5 – 3.3 1.3 5.5 0.9 0.9 8.3 0.8 3.6 2.4 0.6 3.1 1.9 1.9 1.7 2.3 1.2 0.8 1.3 1.4 3.0 1.4 – 6.0 5.2 2.2

15 4 17 33 – 15 8 2 4 13 20 8 27 8 30 11 23 27 3 14 21 1 26 11 5 10 26 – 13 5 18 8 6 11 14 9 12 66 2 30 5 13 17 41 3 19 9 1 20 – 21 5 8

2.7 1.8 14.7 3.7 0.7 4.5 6.6 5.7 1.2 6.1 4.7 3.3 0.9 3.2 1.2 0.8 0.6 1.4 1.1 1.8 8.0 1.7 2.2 16.7 1.8 5.6 2.8 1.0 4.0 1.8 5.6 1.1 1.2 10.2 0.4 4.3 3.0 1.5 – 2.5 2.1 2.6 3.3 1.9 1.3 1.9 2.2 2.7 2.3 0.8 2.2 7.2 2.8

9 15 19 36 12 7 3 3 3 5 2 4 3 16 2 10 10 3 4 11 6 13 15 4 4 6 2 7 10 1 5 4 2 4 2 5 9 8 – 3 19 10 2 11 17 9 4 11 45 40 16 8 3

2.3 1.9 16.4 2.1 1.2 3.7 6.6 9.2 1.6 6.3 3.6 3.9 0.9 3.4 1.5 0.9 0.5 0.6 1.1 2.0 9.8 1.7 2.2 16.5 2.3 6.2 2.9 0.9 3.5 1.5 5.6 1.2 0.9 9.1 0.8 4.8 1.6 – 2.1 1.3 2.1 0.5 1.0 1.5 1.3 1.7 2.4 2.6 1.0 1.8 – 4.9 2.5

27 13 13 2 16 7 5 6 5 6 17 18 7 3 1 5 8 59 10 19 17 3 21 1 5 13 24 60 5 7 16 14 5 10 9 8 14 – 7 55 2 2 11 6 12 2 7 17 15 2 – 6 9

3.6 3.1 24.1 1.8 – 6.0 9.6 11.0 1.7 8.7 4.9 4.7 1.1 4.9 2.2 1.5 – 1.8 2.3 2.8 13.1 3.4 3.1 23.1 2.6 8.9 3.5 – 5.8 2.8 9.4 1.6 1.3 14.4 0.9 6.6 3.6 1.4 4.1 3.4 3.4 2.0 1.5 3.2 1.6 2.7 3.2 2.7 – 3.4 2.9 9.2 3.3

2 9 7 46 – 10 1 9 1 6 1 5 17 1 22 19 – 22 8 17 2 8 5 2 11 2 15 – 4 16 4 1 6 1 22 12 10 13 3 3 9 6 5 6 1 9 14 5 – 10 4 1 17

2.96 2.62 23.17 2.16 4.20 5.96 9.92 8.76 1.85 8.59 5.38 5.45 1.21 4.74 1.89 1.09 0.66 1.15 1.93 2.71 13.69 2.71 3.40 23.81 2.71 9.22 3.43 1.72 5.72 2.80 8.07 1.75 1.70 15.07 1.38 6.91 4.66 2.18 4.54 3.27 3.90 5.06 3.72 3.38 1.64 2.62 3.23 3.64 3.34 2.47 5.19 9.11 3.89

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

Pyridine, 4-methylPyrazine, methylFurfural 2-Pentanone, 4-hydroxy-4-methyl2-Furanmethanol Pyridine, 3-methyl2-Propanone, 1-(acetyloxy)4-Cyclopentene-1,3-dione Styrene 2-Cyclopenten-1-one, 2-methyl2-Acetylfuran 2(5H)-furanone Pyrazine, 2,3-dimethyl2-Hydroxycyclopent-2-en-1-one Pyridine, 3,5-dimethyl2,5-Dimethyl-2-cyclopentenone 2(3H)-furanone, 5-methylButanoic acid, 3-methylEthanol, 2-butoxyBenzaldehyde Furfural, 5-methylPyridine, 3-ethenyl2(5H)-Furanone, 3-methylPhenol 2-isopropylfuran 2-Cyclopenten-1-one, 2-hydroxy-3-methylLimonene Benzenemethanol 2,3-Dimethyl-2-cyclopenten-1-one Indene o-Cresol 2-Acetylpyrrole Ethanone, 1-phenylp-Cresol 2 ethyl tiophene Phenol, 2-methoxy2-Propanamine 2,4-Dimethyl-4-cyclohexen-1,3-dione–one Nicotinamide 3-Ethyl-2-hydroxy-2-cyclopenten-1-one Benzeneacetonitrile 2,3-Dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one Phenol, 2,4-dimethylPhenol, 4-ethylNaphthalene Ethanone, 1-(3-methylphenyl)p-Cresol 2 methoxy 2,3-Dihydro-benzofuran 2-Furancarboxaldehyde, 5-(hydroxymethyl)1H-Inden-1-one, 2,3-dihydroHydroquinone 1H-Indole 4-Vinyl-2-methoxy-phenol

A

1324

Table 5 Yield of the compounds identified in the filter (TPM-F) for the 10 commercial brands. Mean values for three experiments (lg/cigarette) and variation coefficient (%).

350.2 3.5 4.3 1.0 2.7 1.6 0.7 3.1 1.3 1.3 1.4 0.9 2.4 0.3 1.1 0.9 0.5 18.4 1.3 1.1 – 1.8 – 3.3 1.0 2.1 0.6 2.2 2.5

12 5 18 17 26 26 11 8 28 18 8 6 21 15 19 8 22 2 4 3 – 8 – 10 3 20 8 1 7

294.5 2.6 4.0 1.5 1.2 1.7 0.7 3.3 1.3 0.8 1.3 1.3 3.2 1.5 1.0 1.5 2.7 22.1 1.3 0.8 2.2 1.2 3.5 9.8 4.0 3.1 1.5 1.8 1.7

23 3 9 41 20 27 10 11 23 9 36 27 13 16 27 13 17 20 55 26 2 43 2 2 63 25 14 28 44

656.9 4.6 7.9 4.0 3.6 1.5 1.4 5.2 3.8 0.8 2.0 1.2 6.2 0.4 3.6 1.9 – 55.1 2.4 2.3 1.7 2.4 1.1 14.1 2.2 0.5 16.6 6.9 2.6

5 6 2 10 9 7 20 12 6 33 5 62 2 64 8 13 – 19 2 12 27 3 13 24 49 20 23 18 23

352.6 3.4 3.8 2.3 1.9 1.9 0.9 2.8 2.9 – 1.8 1.4 4.2 – 1.2 0.9 – 38.4 1.4 – 0.8 3.0 1.8 8.7 1.1 4.9 32.4 4.4 1.0

8 8 3 47 9 5 14 4 11 – 4 14 2 – 6 2 – 1 24 – 18 2 34 32 5 15 17 37 23

439.9 4.6 5.9 2.2 1.7 1.9 1.7 3.7 2.2 0.8 2.0 2.2 4.9 1.1 2.3 2.1 2.9 35.4 1.5 1.0 – 2.1 0.9 12.1 2.1 3.5 0.8 5.9 5.1

11 5 7 48 35 12 46 28 12 4 1 1 15 8 13 3 21 17 4 9 – 11 3 57 2 16 12 4 17

418.1 2.8 4.9 1.8 2.1 2.4 1.1 3.3 0.7 4.1 1.7 1.0 4.1 – 1.7 1.8 – 31.4 4.1 2.1 0.5 1.5 1.3 9.7 0.0 4.8 38.3 4.8 2.8

10 12 13 7 2 11 10 12 41 1 7 5 2 – 4 15 – 1 22 37 9 24 0 7 13 14 13 14 7

230.8 2.1 2.4 0.6 0.9 0.7 0.3 1.9 0.6 0.4 0.5 0.9 2.0 – 0.9 0.6 – 18.4 – 1.1 – 1.3 1.8 5.2 2.3 4.4 10.0 3.1 2.1

3 20 5 10 16 35 37 12 60 9 17 5 11 – 12 6 – 13 – 15 – 18 10 9 5 10 11 3 4

333.5 2.7 4.8 1.1 1.0 2.1 0.5 3.0 1.2 – – 0.9 3.4 0.4 0.7 1.7 0.5 20.8 0.6 – – 0.8 0.7 8.7 1.8 2.9 25.2 4.3 2.5

6 15 2 12 9 1 9 8 16 – – 18 1 12 59 1 5 4 60 – – 58 0 14 13 8 11 14 1

295.6 2.0 2.4 0.9 2.1 1.7 0.8 1.6 0.8 0.7 1.3 0.9 1.9 – 1.2 – – 33.2 1.8 – – 1.9 1.2 6.2 1.4 3.0 31.7 3.0 1.6

9 14 6 6 6 13 4 8 6 2 3 41 4 – 13 – – 10 3 – – 7 6 0 13 11 17 9 10

392.9 3.4 4.7 1.3 2.7 2.8 1.8 3.0 1.9 0.0 1.4 1.2 3.3 – 1.4 0.8 – 28.6 1.5 2.1 – 4.2 1.2 8.8 1.1 3.7 49.4 3.6 3.1

2 2 14 7 3 5 8 8 8 0 11 5 5 – 5 4 – 12 7 22 – 5 29 61 25 2 15 2 8

376.5 3.18 4.50 1.67 1.99 1.83 0.99 3.11 1.67 0.91 1.33 1.19 3.56 0.37 1.50 1.21 0.66 30.18 1.61 1.06 0.52 2.02 1.36 8.65 1.70 3.29 20.65 4.01 2.49

3.2 1.6 2.2

7 6 27

5.4 4.1 2.5

11 21 19

7.6 6.2 7.4

10 3 11

4.8 3.9 4.2

9 3 14

5.2 5.7 6.8

16 3 16

4.5 4.7 3.3

5 2 12

2.9 2.5 –

5 6 –

5.3 4.5 2.8

32 13 6

4.4 2.4 –

9 6 –

6.4 2.4 2.0

4 5 4

4.97 3.81 3.10

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

Nicotine 1H-Indole, 3-methylMyosmine Phenol, 2-methoxy-4-(2-propenyl)Nicotyrine Norsolanadiona Phenol, 2,6-bis(1,1-dimethylethyl)-4-methyl2,30 -Bipyridine 1,4-Dihydrophenantrhene Diethyl phatalate Megastigmatrienone N-propyl nornicotine Cotinine 1H-Indene, 2,3-dihydro-1,1,3-trimethyl-3-phenyl5-Tetradecene N(b)-formylnornicotine 2,4-Diphenyl-4-methyl-penten-1ene Neophytadiene Farnesol 8-Quinolinemethanol DBP Hexadecanoic acid, ethyl ester Pentadecane Octadecane Eicosane Docosane Citric acid, tributyl ester Tricosane 2,6,10,14,18,22-Tetracosahexaene, 2,6,10,15,19,23hexamethylHeptacosane Triacontane Tocopherol

1325

Assignation

B

C

D

E

F

G

H

I

J

Average

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

Mean

CoV

0.5 0.6 3.5 1.4 – 0.3 0.8 2.4 0.3 0.9 0.4 1.8 – 1.5 – – 0.4 1.2 1.6 0.6 1.4 0.7 0.7 5.8 – 3.1 1.5 – 0.8 0.9 3.0 0.6 – 5.5 0.8 1.6 3.3 – 10.0 1.9 – 6.0 1.7 1.6 – – 1.6 3.0 3.9 0.8 15.4 9.3 2.5

3 11 16 22 – 3 14 6 5 10 33 2 – 1 – – 5 19 6 16 4 5 3 4 – 1 13 – 8 5 3 10 – 4 2 1 6 – 10 11 – 12 14 5 – – 13 16 8 1 8 1 8

0.2 0.3 1.8 1.3 – 0.1 0.2 1.0 1.0 0.7 0.2 0.7 – 0.6 – – – – 0.9 0.4 0.5 0.2 – 2.6 – 0.6 0.7 – 0.3 0.2 1.3 – – 2.7 1.0 0.8 1.2 – – 0.3 – 3.1 0.9 0.5 – – 0.4 1.3 1.9 0.6 7.3 2.6 1.0

7 60 15 2 – 9 7 21 39 3 8 31 – 17 – – – – 13 9 13 34 – 37 – 16 9 – 66 10 29 – – 24 13 27 6 – – 36 – 22 18 45 – – 10 11 40 7 2 12 42

2.0 2.0 14.1 3.4 2.8 0.9 2.4 4.0 1.9 4.5 2.0 2.0 0.6 2.1 0.4 0.7 – 1.0 2.5 1.4 3.7 1.0 1.2 8.3 0.6 3.7 1.5 – 1.8 1.1 3.7 0.4 0.6 7.4 1.2 2.4 3.5 – – 1.9 – 4.9 2.7 2.9 – 2.2 1.1 3.8 2.1 1.8 22.2 9.8 3.4

27 29 15 51 14 26 2 21 4 23 1 5 1 13 4 14 – 9 8 19 8 21 4 6 28 17 1 – 6 4 12 27 15 16 31 1 12 – – 9 – 14 30 23 – 20 8 2 48 64 8 23 3

0.1 0.3 2.0 1.7 – – 0.5 1.2 1.2 0.7 0.3 0.8 – 0.9 – – – – 1.1 0.4 0.7 – – 3.6 – 1.2 0.8 – 0.7 0.2 1.4 – – 3.7 1.2 0.8 2.6 – – 0.8 – 5.1 1.0 1.4 – – 0.3 3.3 3.7 – 13.6 3.6 1.7

28 12 12 11 – – 3 15 15 9 5 9 – 27 – – – – 21 7 4 – – 19 – 21 2 – 35 55 7 – – 29 26 27 23 – – 20 – 6 16 5 – – 12 16 11 – 24 13 9

0.4 0.7 2.7 2.1 – 0.4 0.6 1.5 1.1 0.8 0.4 1.0 – 0.7 – – – 0.4 1.3 0.4 0.8 – – 3.6 0.5 2.5 1.6 – – – 2.1 – – 3.1 1.8 0.9 2.6 – 5.0 – – 6.0 0.7 2.0 – – – 2.1 4.6 – 7.0 2.6 2.6

47 19 5 32 – 45 24 19 3 9 17 43 – 8 – – – 2 31 16 26 – – 18 15 1 32 – – – 2 – – 12 7 37 10 – 5 – – 3 33 18 – – – 6 3 – 9 4 2

– 0.4 1.8 1.1 – 0.2 0.5 1.3 1.0 0.7 0.4 0.7 – 1.0 – – – 0.9 1.6 0.5 0.8 – – 5.3 – 1.8 0.9 – 0.9 0.4 2.1 – – 5.3 1.5 1.3 3.7 – 5.3 1.4 – 7.0 1.8 2.6 – – – 3.1 4.9 0.8 10.9 4.1 3.5

– 25 6 6 – 19 4 4 5 4 2 5 – 9 – – – 7 12 22 4 – – 6 – 6 1 – 30 22 6 – – 6 3 11 3 – 1 10 – 9 3 6 – – – 6 12 45 1 13 7

– – 1.8 1.2 – 0.1 0.5 1.1 0.3 0.5 0.2 0.8 – 0.7 – – – 0.5 0.9 0.4 0.7 – 0.2 3.4 – 1.1 0.5 – 0.5 0.2 1.9 – – 2.6 0.8 0.5 1.5 – 3.7 0.5 0.3 2.1 3.4 0.9 – – 0.7 1.6 – 0.5 10.3 2.6 1.4

– – 11 26 – 63 1 12 3 7 3 3 – 11 – – – 11 11 20 1 – 9 7 – 8 2 – 24 21 8 – – 3 11 27 2 – 5 6 32 5 16 1 – – 29 1 – 35 28 3 19

– – 0.9 2.8 – – 0.3 0.9 0.2 0.4 0.2 0.5 – 0.6 – – – 1.2 0.8 0.4 0.4 – – 3.0 – 0.9 0.6 – 0.6 0.2 2.0 – – 2.8 0.4 0.5 1.6 – 5.4 0.6 – 4.0 1.0 1.0 – – 0.6 1.7 – 0.5 7.6 3.6 1.0

– – 6 9 – – 14 6 3 4 15 19 – 2 – – – 1 27 1 5 – – 1 – 14 3 – 6 8 2 – – 7 23 8 7 – 12 4 – 27 44 3 – – 2 12 – 1 7 11 3

0.7 0.5 3.4 1.7 – 0.4 0.7 1.5 0.3 1.0 0.5 0.9 – 0.5 – – – 0.6 0.7 0.6 1.0 0.2 – 2.2 – 0.8 0.9 – 0.4 0.2 1.3 – – 1.7 0.8 0.5 0.7 – 1.2 – – 1.1 1.3 0.8 – – 1.0 2.1 0.7 0.7 7.6 1.9 1.3

12 9 7 5 – 4 21 5 13 15 18 14 – 12 – – – 15 5 9 20 18 – 13 – 9 21 – 28 3 6 – – 6 3 21 3 – 7 – – 7 11 7 – – 9 11 3 17 4 5 11

– – 1.5 1.6 – 0.2 0.6 1.3 0.2 0.5 0.1 0.9 – 0.7 – – – 1.3 1.4 0.3 0.8 – – 2.9 – 1.0 0.8 – 0.3 0.1 2.2 – – 3.0 0.7 0.6 1.5 – – 0.8 – 2.9 3.4 1.1 – – 0.9 2.9 0.7 1.5 11.8 4.4 1.6

– – 20 10 – 54 36 3 12 22 12 9 – 9 – – – 4 2 2 2 – – 8 – 11 4 – 13 9 7 – – 5 9 4 7 – – 2 – 15 23 23 – – 10 8 2 63 13 23 15

0.38 0.47 3.35 1.82 0.27 0.26 0.69 1.61 0.74 1.05 0.46 1.02 0.05 0.93 0.04 0.06 0.04 0.72 1.27 0.54 1.08 0.21 0.20 4.06 0.10 1.65 0.98 0.00 0.62 0.35 2.09 0.10 0.06 3.77 1.02 0.98 2.22 0.00 3.07 0.82 0.03 4.22 1.79 1.49 0.00 0.22 0.64 2.49 2.22 0.70 11.36 4.45 2.00

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

Pyridine, 4-methylPyrazine, methylFurfural 2-Pentanone, 4-hydroxy-4-methyl2-Furanmethanol Pyridine, 3-methyl2-Propanone, 1-(acetyloxy)4-Cyclopentene-1,3-dione Styrene 2-Cyclopenten-1-one, 2-methyl2-Acetylfuran 2(5H)-furanone Pyrazine, 2,3-dimethyl2-Hydroxycyclopent-2-en-1-one Pyridine, 3,5-dimethyl2,5-Dimethyl-2-cyclopentenone 2(3H)-furanone, 5-methylButanoic acid, 3-methylEthanol, 2-butoxyBenzaldehyde Furfural, 5-methylPyridine, 3-ethenyl2(5H)-Furanone, 3-methylPhenol 2-Isopropylfuran 2-Cyclopenten-1-one, 2-hydroxy-3-methylLimonene Benzenemethanol 2,3-Dimethyl-2-cyclopenten-1-one Indene o-Cresol 2-Acetylpyrrole Ethanone, 1-phenylp-Cresol 2 ethyl tiophene Phenol, 2-methoxy2-Propanamine 2,4-Dimethyl-4-cyclohexen-1,3-dione–one Nicotinamide 3-Ethyl-2-hydroxy-2-cyclopenten-1-one Benzeneacetonitrile 2,3-Dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one Phenol, 2,4-dimethylPhenol, 4-ethylNaphthalene Ethanone, 1-(3-methylphenyl)p-Cresol 2 methoxy 2,3-Dihydro-benzofuran 2-Furancarboxaldehyde, 5-(hydroxymethyl)1H-Inden-1-one, 2,3-dihydroHydroquinone 1H-Indole 4-Vinyl-2-methoxy-phenol

A

1326

Table 6 Yield of the compounds identified in the trap (TPM-T) for the 10 commercial brands. Mean values for three experiments (lg/cigarette) and variation coefficient (%).

613.1 2.8 5.4 2.3 4.6 4.5 8.4 4.2 3.6 4.2 2.1 2.4 6.7 3.7 1.9 5.0 0.7 30.8 2.2 – – 3.5 1.3 11.4 1.7 2.7 – 6.3 4.2

2 6 3 3 15 1 2 6 7 10 12 1 4 1 3 7 20 8 15 – – 3 1 12 3 11 – 8 3

282.5 1.5 2.4 1.5 1.1 1.2 4.0 2.2 – 1.0 0.4 1.0 3.4 – 0.6 – – 15.2 1.9 – 1.4 1.4 1.6 8.7 1.3 4.6 2.5 5.3 0.5

18 10 5 23 33 32 11 9 – 9 40 29 26 – 13 – – 27 20 – 8 18 7 24 7 43 9 50 9

612.3 3.6 5.7 4.5 5.5 5.4 5.1 5.4 2.3 1.3 3.2 2.3 9.9 – 2.7 5.2 – 51.5 3.2 – – 3.1 3.1 20.0 3.3 4.4 5.3 9.0 2.8

22 1 15 11 39 1 9 13 12 59 8 5 4 – 3 11 – 3 9 – – 7 8 1 15 14 19 19 15

419.2 2.0 3.4 2.3 2.3 2.3 5.2 3.3 1.9 1.8 1.9 2.4 7.0 1.6 2.0 3.5 2.7 33.1 2.0 – 0.4 3.6 1.5 16.2 1.7 3.9 1.8 6.9 1.5

2 10 4 3 21 12 2 10 4 20 16 30 6 9 20 31 13 16 24 – 6 7 7 9 51 47 11 16 8

482.3 2.3 4.1 2.6 1.5 1.7 6.1 3.6 2.9 3.1 1.3 2.1 5.7 3.2 1.8 6.6 5.9 26.8 3.1 1.0 – 2.2 1.0 13.0 1.7 3.6 – 5.8 3.2

18 19 11 11 29 23 5 19 16 1 9 16 10 31 1 19 21 19 2 59 – 5 29 18 11 12 – 27 4

557.0 2.6 4.7 2.8 1.7 2.1 7.5 3.6 3.6 6.5 1.5 2.6 6.2 3.0 1.3 5.3 5.3 27.9 2.9 0.7 – 2.8 1.1 15.3 1.7 3.4 – 6.8 4.5

6 1 3 24 3 19 19 14 9 8 4 15 1 2 4 7 2 6 16 7 – 10 2 8 19 16 – 12 1

352.8 2.0 2.7 1.3 1.1 1.6 6.1 2.6 2.4 3.1 0.8 1.2 3.8 2.4 1.2 3.7 3.9 20.5 1.5 0.6 – 1.9 0.7 10.4 1.5 2.7 – 5.4 2.4

14 4 17 17 17 13 23 4 7 3 3 11 13 30 18 9 23 9 13 15 – 12 11 3 9 14 – 19 16

390.9 2.6 5.0 2.7 1.7 2.3 7.3 3.6 2.6 3.4 1.3 1.8 4.9 3.2 1.2 3.2 4.2 22.6 1.8 0.7 – 2.0 1.0 15.0 2.0 2.5 – 7.1 4.5

6 13 9 9 20 14 9 15 2 1 13 4 8 6 9 41 3 5 14 32 – 11 8 2 3 15 – 13 25

408.4 2.2 2.9 0.9 1.9 2.2 8.1 2.8 2.6 3.5 1.5 1.3 3.3 3.1 1.3 4.4 4.7 31.3 2.1 0.9 – 2.4 0.8 10.9 1.4 2.5 – 6.3 1.7

12 1 3 1 2 12 4 7 2 1 1 5 5 6 15 17 17 1 22 15 – 9 15 19 5 7 – 4 12

475.3 2.3 4.0 1.9 2.4 3.1 8.7 3.7 3.2 2.5 1.4 1.8 5.3 3.6 1.5 4.5 4.9 26.8 2.2 0.8 – 3.2 1.0 14.3 1.3 2.5 – 6.7 3.8

2 4 4 6 10 4 3 3 5 12 12 2 8 12 8 4 11 6 25 9 – 7 7 8 2 13 – 28 17

459.3 2.38 4.01 2.28 2.36 2.63 6.65 3.50 2.49 3.05 1.53 1.89 5.61 2.38 1.56 4.14 3.22 28.64 2.28 0.48 0.17 2.61 1.31 13.52 1.74 3.27 0.97 6.55 2.91

7.5 5.5 4.5

6 8 16

5.6 3.8 3.1

26 6 12

10.3 9.9 13.0

5 12 8

7.1 6.1 8.5

2 11 13

6.8 8.2 8.3

7 21 11

8.2 6.4 7.1

5 8 21

5.4 4.7 2.3

9 3 3

8.8 6.1 4.6

4 3 1

7.1 5.2 2.4

15 6 5

8.2 5.7 3.3

5 1 8

7.50 6.17 5.71

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

Nicotine 1H-Indole, 3-methylMyosmine Phenol, 2-methoxy-4-(2-propenyl)Nicotyrine Norsolanadiona Phenol, 2,6-bis(1,1-dimethylethyl)-4-methyl2,30 -Bipyridine 1,4-Dihydrophenantrhene Diethyl phatalate Megastigmatrienone N-propyl nornicotine Cotinine 1H-Indene, 2,3-dihydro-1,1,3-trimethyl-3-phenyl5-Tetradecene N(b)-formylnornicotine 2,4-Diphenyl-4-methyl-penten-1ene Neophytadiene Farnesol 8-Quinolinemethanol DBP Hexadecanoic acid, ethyl ester Pentadecane Octadecane Eicosane Docosane Citric acid, tributyl ester Tricosane 2,6,10,14,18,22-Tetracosahexaene, 2,6,10,15,19,23hexamethylHeptacosane Triacontane Tocopherol

1327

1328

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

µg/cigarette 60.0

µg/cigarette 40.0

Phenol

35.0

TPM-F TPM-T

50.0

µg/cigarette 25.0

p-cresol

TPM-F TPM-T

30.0

40.0

Hydroquinone

TPM-F TPM-T

20.0

25.0

15.0

20.0

30.0

10.0

15.0

20.0

10.0 10.0

5.0

5.0

0.0

0.0 A

B

C

D

µg/cigarette 700.0

E

F

G

H

I

J

0.0 A

B

C

D

µg/cigarette 9.0

Nicotine

600.0

E

F

G

TPM-F TPM-T

I

A

J

TPM-F TPM-T

7.0

C

D

E

F

G

H

I

J

I

J

I

J

Cotinine

TPM-F TPM-T

10.0 8.0

6.0

400.0

B

µg/cigarette 12.0

Myosmine

8.0

500.0

H

5.0 6.0 4.0

300.0

4.0

3.0

200.0

2.0 2.0

100.0

1.0

0.0

0.0 A

B

C

D

µg/cigarette 25.0

E

F

G

H

I

J

0.0 A

B

C

D

µg/cigarette 12.0

Octadecane

TPM-F TPM-T

20.0

E

F

G

H

I

A

J

B

C

D

µg/cigarette 12.0

Heptacosane TPM-F TPM-T

10.0

E

F

G

H

Triacontane

TPM-F TPM-T

10.0

8.0

8.0

6.0

6.0

15.0

10.0

5.0

0.0

4.0

4.0

2.0

2.0

0.0 A

B

C

D

E

F

G

H

I

0.0

J

A

B

C

D

E

F

G

H

I

J

A

B

C

D

E

A

F

F

G

H

Euclidean distance

Euclidean distance

Fig. 4. Histograms of some compounds contained in TPM-F and TPM-T for the different brands.

H

J G

I

E

F

D

B

A

C

Case Fig. 5. Dendogram resulting from the application of hierarchical cluster analysis to data of particulate matter retained in the traps.

G

I

H

B

D

J

E

C

Case Fig. 6. Dendogram resulting from the application of hierarchical cluster analysis to data of particulate matter retained in the filters.

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

CO, water, nicotine and tar. The need of implementation of standards methods for other compounds has been questioned due to the analytical variability and unknown tolerances around the published measurements (Gregg et al., 2004). Osamu et al. (2009) tested nicotine and tar for the ten top selling Japanese cigarettes with the ISO and the Health Canada Intense method. They found that the nicotine value under the ISO method varied from 0.19 to 1.11 mg/cigarette. Counts et al. (2005) tested forty-eight Philip Morris USA and Philip Morris International commercial filtered cigarettes with three smoking regimes (ISO, Canadian Intense and Massachusetts Department of Public Health). With the ISO method they reported variations of nicotine from 0.1 to 1.13 mg/cigarette and of carbon monoxide from 1.1 to 13.4 mg/cigarette in the different brands. Calafat et al. (2004) examined levels of nicotine, carbon monoxide and tar of 77 cigarette brands purchased in 35 countries which were divided in different regions according to the World Health Organization. According to these authors the European cigarette deliveries varied widely in the brands that they studied, from 0.5 to 1.6 mg of nicotine/cigarette and 5.9 to 17.4 mg of CO/cigarette. The results obtained by Gregg et al. (2004) for nicotine and CO for commercial UK cigarettes were 0.11–0.94 mg of nicotine/cigarette, and 1.5– 13.8 mg of CO/cigarette, which are lower than those obtained by Calafat for European cigarettes and closer to our results. In our work, for the ten top selling brands in Spain, the nicotine varies from 0.28 to 0.61 mg/cigarette, while carbon monoxide ranges from 5.1 to 11.1 mg/cigarette. The reported values in our work are within those obtained by other workers, and assuming the risk of comparisons, CO content would be in the medium to high level in the studied Spanish cigarettes as compared to commercial cigarettes from other countries, while nicotine would be in the low to medium level. Another remarkable fact is that there are relatively low differences among the Spanish brands studied, despite, as the multivariate statistical analysis has pointed out, in general brand C differentiates from the rest by its higher yields, and samples G, H and I seem to show higher similarities (and lower yields).

1329

In general, the amount of most of the compounds with low retention time is higher in the filters than in the traps, while the very opposite is true for most of the heaviest compounds. Any case, the importance of filters in retaining toxic compounds has been once again observed. Multivariate statistical analysis facilitates the interpretation of results in this kind of studies, where a noticeable amount of variables have to be simultaneously taken into account. In this work, the analysis of principal components and the cluster analysis have been satisfactorily used to reduce the dimensions of the problem, for the identification of the variables with higher variability and with higher influence in the variability among samples and for the definition of groups or clusters of similar brands. According with the results obtained from multivariate statistical analysis, the classification of the studied tobacco brands based on the chemical composition of the vapor phase, the particulate matter retained in the traps and the particulate matter retained in the filters is relatively similar. Brand C always appears noticeably separated from the other brands due to its high yields of compounds in all the fractions of the mainstream smoke. The differences among the other brands are lower. Nevertheless, globally, it seems that brands G, H and I, and in lower extent, samples D and E form homogeneous groups, which are joined with the overall set of studied brands in a different way depending on the variables included in the statistical analysis. Conflict of Interest The authors have declared that there is no conflict of interest. Acknowledgments Financial support for this investigation has been provided by the Spanish ‘‘Secretaría de Estado de Investigación’’ del Ministerio de Ciencia e Innovación (CTQ2008-01023 and MAT2011-24991).

4. Conclusions

Appendix A. Principal component analysis of preliminary analysis data

The design features of 10 commercial brands of cigarettes sold in Spain has been reported. It has been observed that in general, the higher the amount of tobacco initially contained in the cigarette the lower the tobacco consumption during smoking at a fix number of puffs. This is probably a consequence of the lower availability of oxygen in tighter packings. Other variables, such as filter and paper length, may play an important role during the smoking process as has been demonstrated. Gaseous hydrocarbons and most of compounds of the vapor phase present similar relative proportions among brands, but there are some noticeable compounds such as crotonaldehyde, isoprene or toluene which depart from the pattern obtained for most of the compounds. The brands that present the lowest total yield for the compounds in the vapor fraction are not coincident with those showing the lowest yield in TPM-T. The tobacco brands studied present similarities in the composition of the compounds studied but there are also some important differences. The relative yield of some known toxic compounds may vary substantially from brand to brand. Since the toxicity of any individual compound can be very different and the relative proportion of them is not always proportional to tar, CO or nicotine, more adequate parameters to determine tobacco toxicity must be established.

A statistical principal component analysis (PCA) has been performed using the software PASW Statistics 18, version 18.0.0. The cigarettes design characteristics shown in Table 2 have been considered, together with the amount of tobacco smoked and the ratio CO2/CO (Table 3). The results obtained indicate that, among these variables, CO2/CO shows the highest correlation with the length of filter (positive correlation) and with the weight of paper (negative correlation), which is in agreement with the comments included in the text. On the other hand, four principal components can be extracted, which account for the 92.0% of the total variance of the studied samples. The first principal component (PC1) represents the 32.3% of the total variance and includes, mainly, the contribution to the variability of the length of filter, weight and length of paper, and CO2/CO. The length of filter and CO2/CO show negative contributions and the other two variables, positive contributions. The second principal component (PC2) includes the amount of tobacco smoked (with negative contribution) and the weight of tobacco in the cigarettes and the length of cigarette (both with positive contributions), and represents the 24.3% of total variance. The third principal component (PC3) explains the 18.4% of total variance, and mainly depends (positively) on the weight of the filter and the perimeter. Finally, the fourth principal component (PC4) includes the ventilation (with positive contribution) and represents the 17% of the variance. These results mean that

1330

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

co brands, in relation to their morphological characteristics and their CO2/CO ratio, which includes the other studied brands, i.e.: D, F, G, I and J.

PC 2

1.5 1

H

0.5 E

PC 1

0 -2.5

-2

-1.5

-1

-0.5

0

0.5

1

-0.5 B

-1 A

-1.5 -2

C

-2.5

PC2

Fig. A1. Graphical representation of the first and the second principal components obtained from the PCA of the morphological characteristics of the cigarettes and the amount of tobacco and the CO2/CO ratio.

2 E 1.5

D

1

-1.5

-1

C

0.5

B A

Appendix B. Principal component analysis of the variables corresponding to the composition of the phase vapor PCA has been applied to the 35 variables included in Table 4, corresponding to the composition of the vapor fraction of the mainstream smoke obtained from the 10 studied cigarette brands. The above-mentioned software permit us to reduce the dimensionless of the problem passing from the 35 original variables to only 5 principal components, which represents the 94.9% of the total variance of the problem. Table B1 shows the coefficients of the rotated component matrix, which indicate the contribution of each one of the original variables to each principal component. As it can be seen, the main contributors to the first principal component (PC1) are 25 of the 35 studied variables, including CO, CO2, the major part of the analyzed hydrocarbons, methanethiol, hydrogen cyanide, furane, acetaldehyde, acetonitrile and isobutiraldehyde, and represents the 48.8% of total variance. These compounds are those showing the general pattern previously commented on for most of the light hydrocarbons and small aldehydes. The second principal component (PC2) includes chloromethane, toluene and 2,5-dimethylfurane (with positive contributions). Toluene and 2,5-dimethylfurane have been above-mentioned as compounds showing a different pattern than those grouped in PC1 (see Fig. 2). Therefore, in this case, PCA is also in agreement with the statements carried out after the visual

PC1 0

H -0.5

0 -0.5

0.5

G I

1.5

2

2.5

3

J

-1 -1.5

1

F

-2 Fig. B1. Graphical representation of the first and the second principal components obtained from the PCA of the variables shown in Table B1.

the variables contributing in higher extent to the variability among samples are those represented in PC1, and that the highest values of PC1 correspond to samples with high values of length and weight of paper, whereas samples with high values of length of filter and CO2/CO exhibit low values of PC1. Similar analysis could be done for the other principal components. In this way, PCA permits us to reduce the dimensions of this problem, with a very low loss of information, by passing from the original 10 variables to the 4 principal components. Fig. A1 shows the graphical representation of the two first principal components, both representing the 56.6% of the total variance. As it can be seen, the samples H and B show the lowest values of PC1, i.e., the highest values of CO2/CO. This is probably related with their higher values of length of filter and lower length and weight of paper (Table 2), which favor a better combustion process and, therefore, higher yield of CO2 at expenses of CO. Brand H has low length of filter too, thus supporting the validity of PCA to assist in the interpretation of the results in the cases where the number of variables considered is high. C and A brands, and in less extent B brand, show the lowest values of PC2, which is related to the fact they have the highest values of amount of tobacco smoked, the shortest cigarettes and the highest amount of tobacco smoked. Finally, PCA indicates that there is a homogeneous group of tobac-

Table B1 Rotated component matrix corresponding to PCA of the original variables shown in Table 4. Original variable

PC1

PC2

PC3

PC4

PC5

CO CO2 Methane Ethane Ethylene Ethyne Propane Propene Iso-butane Chloromethane Butane 1-Butene 1,2-Propadiene 1,3-Butadiene Isobutene Cis-2-Butene Pentane Methanethiol Hydrogen cyanide 1-Pentene Furan Isohexane Isoprene Hexane 1-Hexene Benzene Acetaldehyde Acetone Acrolein Propionaldehyde Acetonitrile Toluene 2,5-Dimethylfuran Crotonaldehyde Isobutyraldehyde % Of variance explained

0.625 0.673 0.758 0.781 0.813 0.870 0.794 0.828 0.161 0.400 0.801 0.856 0.863 0.856 0.762 0.696 0.879 0.791 0.691 0.789 0.876 0.966 0.127 0.736 0.033 0.840 0.843 0.392 0.458 0.507 0.561 0.477 0.293 0.299 0.842 48.8

0.370 0.494 0.401 0.427 0.374 0.217 0.426 0.369 0.023 0.673 0.423 0.340 0.242 0.365 0.440 0.581 0.196 0.225 0.493 0.506 0.346 0.097 0.247 0.572 -0.058 0.252 0.331 0.386 0.099 0.117 0.262 0.817 0.857 0.360 0.126 16.5

0.407 0.415 0.446 0.407 0.408 0.393 0.371 0.372 0.028 0.575 0.352 0.349 0.408 0.326 0.318 0.151 0.217 0.449 0.221 0.240 0.289 0.038 0.124 0.201 0.033 0.437 0.380 0.354 0.819 0.830 0.416 0.043 0.023 0.649 0.404 15.3

0.097 0.092 0.156 0.159 0.065 0.112 0.186 0.100 0.190 0.029 0.175 0.077 0.026 0.048 0.205 0.057 0.129 0.022 0.238 0.171 0.110 0.096 0.780 0.102 0.983 0.033 0.055 0.669 0.048 0.105 0.175 0.145 0.125 0.150 0.131 7.2

0.193 0.127 0.169 0.116 0.148 0.153 0.101 0.162 0.930 0.202 0.127 0.147 0.095 0.143 0.247 0.358 0.311 0.102 0.317 0.131 0.005 0.052 0.410 0.173 0.119 0.151 0.114 0.206 0.040 0.095 0.557 0.074 0.121 0.513 0.050 7.0

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inspection of the experimental results. Moreover, also has permitted us to distinguish other compound with similar behavior (chloromethane). The third principal component (PC3) includes acrolein, propionaldehyde and crotonaldehyde (with positive contributions), which were marked as exceptions of the general pattern shown by aldehydes. Both, PC2 and PC3 explain similar percentages of the total variance, 16.5% and 15.3%, respectively, which are significantly lower to that explained by PC1. The fourth and fifth principal components (PC4 and PC5, respectively) repre-

sent, each one of them, around 7% of total variance and include, respectively isoprene, hexene and acetone, and isobutene (note that isoprene has been also mentioned as a compound departing from the general pattern). These results, besides confirming the validity of PCA to systematize and to simplify the analysis of data sets with high number of variables, highlight the interest of the variable PC1, because this component accounts for a lot of information accumulated in most of the single variables. PC3 also is interesting because includes compounds noticeably toxic.

Table C1 Variables included in the fourth first principal components resulting from the PCA of the chemical analysis of the compounds retained in the traps. PC1 Group 1

Group 2

Group 3

Group 4

Group 7 Group 8

Group 11

Uncorrelated

PC4

2-Acetylpyrrole

2-Propanamine 2,3-Dihydro-3,5-dihydroxy-6-methyl4H-pyran-4-one Megastigmatrienone 5-Tetradecene Neophytadiene Myosmine 2,30 -Bipyridine Phenol, 2-methoxy-4-(2propenyl)Tocopherol

Group 9 Group 10

PC3

Pyridine, 4-methylPyrazine, methylFurfural 2-Furanmethanol Pyridine, 3-methyl2-Propanone, 1-(acetyloxy)4-Cyclopentene-1,3-dione 2-Cyclopenten-1-one, 2-methyl2-Acetylfuran Pyrazine, 2,3-dimethylPyridine, 3,5-dimethyl2,5-Dimethyl-2-cyclopentenone Benzaldehyde Furfural, 5-methylEthanone, 1-phenylEthanone, 1-(3-methylphenyl)2(5H)-furanone 2-Hydroxycyclopent-2-en-1-one Pyridine, 3-ethenyl2(5H)-Furanone, 3-methylIndene Phenol, 2-methoxy1H-Indole Nicotyrine Norsolanadiona Ethanol, 2-butoxyPhenol 2-Cyclopenten-1-one, 2hydroxy-3-methylo-Cresol p-Cresol Cotinine 2-Isopropylfuran Triacontane

Group 5

Group 6

PC2

1,4-Dihydrophenantrhene DBP Pentadecane Eicosane Citric acid, tributyl ester Octadecane Tricosane Heptacosane 2-Pentanone, 4-hydroxy-4methylStyrene Limonene 1H-Inden-1-one, 2,3-dihydro1H-Indole, 3-methyl-

2-Ethyl tiophene

Butanoic acid, 3-methyl-

2(3H)-Furanone, 5-methyl-

Phenol, 4-ethyl-

Phenol, 2,6-bis(1,1-dimethylethyl)-4methyl1H-Indene, 2,3-dihydro-1,1,3trimethyl-3-phenylN(b)-Formylnornicotine 2,4-Diphenyl-4-methyl-penten-1ene 8-Quinolinemethanol

Nicotinamide

2-Furancarboxaldehyde, 5(hydroxymethyl)4-Vinyl-2-methoxy-phenol Nicotine N-Propyl nornicotine

3-Ethyl-2-hydroxy-2cyclopenten-1-one p-Cresol 2 methoxy

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A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

PC2

Fig. B1 shows the graphical representation of PC2 versus PC1. In order to obtain significant groups of samples, a hierarchical cluster analysis has been performed. The cluster solution obtained (Fig. 3 of the text) has been marked in Fig. B1, and reflects the formation of groups based in the measurement of the euclidean distance among samples and/or clusters in the 35-dimmensional space defined by the variables shown in Table B1, as commented in the text.

2.5 2

F

1.5 E

1 A 0.5 D

The application of multivariate statistical analysis would be especially valuable in this case where there are a large amount of variables and experimental results, as Tables 5 and 6 reflect. The low variability of the studied variables also supports the need of applying some technique in order to simplify the analysis of results. In fact, the univariate statistics of each variable analyzed in the traps show that most of them (85 variables) have variation coefficients (calculated as 100  standard deviation/mean) lower than 100, and the variation coefficient for the remaining seven variables is lower than 200. Similar results have been obtained for the filters. Thus, the PCA permits us to reduce the dimensionless of the problem, and 8 and 9 principal components, respectively, have been obtained for traps and filters. The percentage of the variance explained is very high in both cases: in the traps, the 8 principal components selected account for the 98.8% of the total variance, and 71% of the variance is already represented by the three first principal components. This indicates that these components would provide a satisfactory interpretation of the results. The 9 principal components obtained for the filters represent the 100% of the variance. In this case, the first principal component (PC1) accounts for the 57% of total variance, the second one (PC2) the 9%, and the third, fourth and fifth ones around 6%. In order to resume the results obtained, a previous grouping of variables has been performed, considering the correlation degree (i.e., the correlation coefficient calculated as the ratio of the covariance and the square root of the product of variances). Thus, Table C1 shows the groups of variables according their correlation coefficient (thus, with similar behavior), and the principal components where they are represented in the PCA of the results corresponding to the traps. In order to avoid an excess of low relevant information, only the fourth first principal components are shown. According with these results, the study of the differences among tobacco brands could be performed by centering the attention in the interpretation of the results corresponding to the variables included in these tables and, moreover, only one variable as representative of each group could be chosen. In general, the PCA analysis of the compounds retained in the filters is very similar to that of the traps. In this case a single group of variables highly correlated is obtained, which includes most of the variables of groups 1, 2 and 3 of the traps (see Table C1). The other groups only include two variables and do not provide too much interesting information. The results obtained from the PCA of the liquids retained in the filters and in the traps indicate that PC1 could be a good indicator of the overall yields. Fig. C1 shows the graphical representation of the two first principal components obtained from the PCA analysis of the results of the liquids retained in the traps. As it can be seen, in good agreement with the results obtained in the analysis of the gaseous fraction (Fig. B1), brand C is noticeably separated from the rest, due to its high value of PC1 (i.e., its relatively high yields of products). The groups provided by the cluster analysis (Fig. 6 in the text) have been marked in Fig. C1. As it can be seen, it appears a group with brands D, E and F with positive and relatively high

-1

-0.5 0 B G -0.5 J -1 H I

0.5

1

1.5

2

2.5

3 PC1

-1.5 Fig. C1. Graphical representation of the two first principal components obtained in the PCA analysis of the particulate matter retained in the traps.

values of PC2, another group with brands G, H, I and J, with negative and relatively high absolute values of PC2, and brands A and B appear as individual clusters, with intermediate values of PC2. All brands, with the only exception of C, have values of PC1 which are negative or close to zero. The differences among brands A and B and the other groups lie in the positive and high values of PC4 of these brands, in front to the other samples, which show negative values of PC4 in all the cases. With respect to the filters (Fig. C2), the application of hierarchical cluster analysis (Figure 7 in the text) permits us to define the following groups of tobacco brands according with the chemical composition of the particulate matter retained: – Brand C, with a positive and noticeably high value of PC1. In good agreement with the results obtained for the gases and for the liquids retained in traps, this is the brand with the highest yields. – Brands G, H and I, characterized by negative and relatively high absolute values of PC1, and negative values of PC2. These brands also appear within homogeneous groups when the chemical composition of gases and liquids retained in the traps were considered. – Brand A appears in an individual group because it has positive PC1 (but noticeably lower than brand C). – Brand E appears in an individual group because it has the highest positive value of PC2.

2.5 PC2

Appendix C. Principal component analysis of the variables corresponding to the composition of the particulate matter

C

0

E

2 1.5

B

1 0.5 A

0 -1.5

-1

G

H

I

-0.5

0J

F

-0.5 -1

0.5

1

1.5

2

2.5 PC1

3

C

D

Fig. C2. Graphical representation of the two first principal components obtained in the PCA analysis of the particulate matter retained in the filters.

A. Marcilla et al. / Food and Chemical Toxicology 50 (2012) 1317–1333

– The rest of brands (B, D, F and J) appear in another group, with intermediate negative values of PC1. B has positive PC2 and the other samples of this group have negative values of PC2.

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