1. bookVolume 29 (2020): Issue 2 (August 2020)
Journal Details
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Journal
First Published
01 Jan 1992
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access type Open Access

Statistical Analysis for Comparison of the Results Obtained by Capillary Columns and Packed Columns in the Determination of Water Yield in Smoke Condensates Analyzed in Cigarettes for the 24th Asia Collaborative Study

Published Online: 25 Sep 2020
Page range: 97 - 118
Received: 11 Jun 2020
Accepted: 30 Aug 2020
Journal Details
License
Format
Journal
First Published
01 Jan 1992
Publication timeframe
4 times per year
Languages
English
Summary

Recently, capillary columns have been widely used in the methodology for the determination of water yields in smoke condensate, even though ISO 10362-1:1999, “Cigarettes - Determination of water in smoke condensates – Part 1: Gas chromatographic method” specifies a packed gas chromatographic column. As a result of a systematic review in 2015, ISO/TC126 decided to revise the standard to include the use of capillary columns.

The goal of this study was to confirm the comparability of water yields obtained from capillary column methodology to those yields from packed columns by the statistical analysis of yield data from the 24th Asia Collaborative Study which included 86 datasets submitted by 64 laboratories. After the exclusion of outliers by Cochran’s and Grubbs’ tests, the datasets were classified by GC column type and then mean water yields, and their repeatability and reproducibility were calculated for each type of column. No significant differences were observed in water yields between capillary and packed columns. Repeatability and reproducibility of water yields using capillary column were comparable to those using packed columns as described in ISO 10362-1:1999. From these results, it was confirmed that the capillary columns are an appropriate alternative to packed columns for the gas chromatographic procedure described in ISO 10362-1:1999.

INTRODUCTION

The international standard 10362-1:1999 “Cigarette-Determination of water in smoke condensate – Part 1: Gas chromatographic method” (1) specifies only packed columns in the methodology for water yield analysis even though recently the use of capillary columns for both water and nicotine (2) has become relatively more popular across global laboratories.

Indeed, capillary columns were used in the recently updated CORESTA Recommended Method No 57, “Determination of water in tobacco and tobacco products by gas chromatographic analysis” (3).

Based on this situation, ISO/TC 126 decided in 2015 to create a Working Group 17 (WG 17) to revise ISO10362-1:1999 to include capillary columns as one of the methodology options, starting with discussion and a systematic review. At the first ISO/TC 126/WG 17 meeting, the necessity for a comparison of water yields using either packed or capillary columns in the methodology, was identified.

Yield data were gathered and analysed from several collaborative studies e.g., of 24th Asia Collaborative Study 2015 (ACS, the meeting was held in Bali in 2016), of the European Collaborative Study 2016 (EUCS, organized by the Committee on Tobacco and Tobacco Smoke of the German Institute for Standardization (DIN)) and of the CORESTA CM8 collaborative study 2017 (4). Water yield comparability was presented and confirmed in all collaborative studies at the WG17 meeting held in November 2017. The results from the monitor cigarette (CM8) from the CORESTA collaborative study were published by Crumpleret al. (4), but only one brand for test samples was used.

On the other hand, ACS 2015 and EUCS 2016 used five different brands for test samples. Although the results of EUCS didn’t contain datasets obtained with the combination of packed columns and linear smoking machines, the results of ACS (5) contained datasets obtained with all combinations of GC columns and smoking machines. Consequently, WG17 decided to use the results of ACS for the revision of the international standard.

This paper has been written to provide a comprehensive statistical comparison in terms of water yield differences between packed and capillary columns obtained from the 24th Asia Collaborative Study (2015) covering cigarettes across a typical range of “tar” yields.

EXPERIMENTAL
Asia Collaborative Study – Participants

64 laboratories participated in the 24th Asia Collaborative Study (ACS) held in 2015. All participating laboratories are listed in Table A of Appendix A. The laboratories marked with an asterisk provided more than one dataset which were obtained by using various combinations of linear and rotary smoking machines.

In this study, 86 datasets were submitted with their water yields analysed. They consisted of 46 datasets measured by capillary column, 39 datasets measured by packed column, and 1 dataset without mention which column was used.

Protocol

Participants were requested to follow the protocol “ACS” to analyse five test samples, including CORESTA Monitor CM8 (6) as listed in Table 1, and to report on parameters as listed in Tables 2 and 3.

List of samples.

CodeSample nameSupplierOriginNFDPM level (mg/cig)Butt length (mm)
AMevius One BoxJTJapan135
BMarlboro Clear 3 BoxPMILithuania335
CKent 6 KS BoxRJRUSA635
DMevius BoxJTJapan1035
ECORESTA Monitor (CM8)CORGermany14.1*33

Suppliers: JT: Japan Tobacco Inc., PMI: Philip Morris International, RJR: R J Reynolds, COR: CORESTA

CM8 was provided by Cerulean in this year.

NFDPM was quoted from ‘CORESTA Approved Monitor No.8 (CM8) use of condition, June 2015’ (6).

List of parameters to be reported.

Outline
Test periodSeptember 1st to November 30 th, 2015
Data set / sampleOne data set consists of 6 test results obtained from 6 runs. One test result was defined as the average yield obtained from 20 cigarettes in a single run.
Test parametersTPM, water, nicotine, NFDPM, CO, puffs
Original data sets86 data sets from 64 laboratories for each sample

Dataset per sample.

Test parameterSmoking machineNumber of runsReported data / sample
TPM (mg/cig)Linear 20 port6 runs 5 cig/port × 4 ports/run6 test results, mean and standard deviation
Water (mg/cig)
Nicotine (mg/cig)
NFDPM (mg/cig)Linear 16 port
CO (mg/cig)Linear 10 port
Puff count (puffs/cig)Rotary6 runs (20 cig/run)

As shown in Table 1, the four sample brands covered the range in NFDPM from 1 to 10 mg/cig, NFDPM of CM8 was reported to be 14.1 mg/cig (6). CORESTA Monitor CM8 was provided by Cerulean or Borgwaldt KC year by year in turn and Cerulean provided it in that particular year.

One dataset consists of six test results obtained from six runs, as shown in Table 2. One test result was defined as the average yield obtained from 20 cigarettes in a single run. For linear smoking machines, four ports per brand were used within each run, and five cigarettes were smoked per port. Rotary smoking machine always used 20 cigarettes per run.

Raw data

Raw datasets are listed in APPENDIX B with the type of smoking machine and GC column, water yields for each run, mean and standard deviation (SD) for five test samples.

Statistical analysis – Exclusion of outliers

Numerical outlier technique: Cochran’s and Grubbs’ tests were applied in accordance with ISO 5725-2:1994 (7) to exclude outlying datasets prior to the determination of repeatability and reproducibility. Cochran’s test was applied to identify an outlier with statistically deviant standard deviation. Grubbs’ test was applied to identify an outlier in a univariate dataset that follows an approximately normal distribution.

After Cochran’s test, Grubbs’ test was applied to the mean values of the remaining datasets according to chapter 7.3.4.3 in ISO5725-2 (7). Grubbs’ test consists of two types of tests. One is to determine whether the largest or smallest observation is the outlier, this is called the single Grubbs’ test (chapter 7.3.4.1 in ISO 5725-2). The second test is to determine whether the two largest observations or two smallest observations are the outliers, it is called the double Grubbs’ test (chapter 7.3.4.2 in ISO 5725-2).

In the first step, the datasets were sorted in descending order for mean value. The Grubbs’ statistics Gp was calculated using the maximum mean value xp, ground mean and standard deviation s. Where the Grubbs’ statistics was higher than 1% of critical value (8), the maximum value was considered as outlier. The same process was applied for the dataset with the minimum mean value. When outliers are determined by single Grubbs’ test, the Grubbs’ test is completed. If there is no outlier in single Grubbs’ test, double Grubbs’ test for the two smallest or two largest observations should be applied.

Repeatability and reproducibility estimation

Water yield repeatability (r) and reproducibility (R) were calculated for all types of gas chromatographic columns and each type of GC column seperately, with all types of smoking machines according to ISO 5725-2:1994 (7), by using the data that remained after the removal of outliers.

RESULTS
Statistical analysis
Mean and standard deviation

Mean and standard deviation for each dataset were calculated and are listed in Table 4.

Mean and standard deviation (SD) of water yields for each data set (unit: mg/cig).

No.Smoking machine aGC column bLab. codeSample ASample BSample CSample DSample E
MeanSDMeanSDMeanSDMeanSDMeanSD
1RC01R0.070.0310.140.0370.960.1031.690.0861.900.109
2RC02R0.090.0610.300.0841.010.1541.930.2072.230.172
3LP03AL0.080.0660.170.0530.450.0461.030.0531.210.052
4RP03BR0.070.0520.150.0310.550.1111.220.1671.340.182
5LP04L0.150.0240.330.0460.690.0651.340.0781.560.121
6LP05L0.100.0290.290.0420.680.0571.540.0761.720.092
7LC06AL0.090.0300.380.1760.610.1211.380.2281.620.393
8LC06BL0.200.1040.350.2370.550.1801.000.2161.500.481
9RC07AR0.120.0350.430.0560.960.0481.900.0972.160.132
10RC07BR0.100.0360.350.0390.920.0361.830.1162.170.033
11LC07CL0.070.0220.190.0420.580.0171.230.1511.430.050
12RC08R0.090.0410.270.0420.870.0561.690.0891.970.115
13RC09R0.080.0800.230.0410.800.1181.550.1071.900.090
14RC10R0.040.0230.260.0210.860.0512.020.0492.140.080
15LC11L0.060.0430.210.0430.490.1311.210.1301.320.074
16RP12R0.080.0230.310.0681.050.0851.720.0332.190.126
17RC13AR0.130.0370.290.0380.930.0121.450.1151.520.115
18RC13BR0.130.0170.340.0790.880.0531.540.0951.680.170
19RP14R0.170.0170.370.0710.860.0881.670.1791.900.096
20RC15AR0.140.0530.320.0420.970.0551.690.0371.920.066
21LC15BL0.130.0850.170.1000.510.1131.130.1381.520.215
22RP16R0.080.0590.270.1050.740.1341.540.1131.700.148
23RP17AR0.090.0150.270.0310.770.1031.520.1451.820.112
24LP17BL0.100.0220.210.0340.530.0721.150.1411.310.076
25RC18AR0.100.0040.350.0340.880.0781.630.0961.780.145
26LC18BL0.090.0190.300.0560.660.1581.450.1841.390.203
27LC19AL0.060.0170.250.0130.620.0441.470.0781.630.089
28RC19BR0.130.0380.280.0390.900.0611.690.0732.030.066
29LC19CL0.080.0140.270.0180.670.0241.470.0851.730.112
30RC19DR0.080.0610.250.0540.820.0781.470.0831.820.033
31LP19EL0.060.0130.220.0100.550.0331.360.0291.440.040
32LP20L0.060.0140.270.0390.630.0731.450.0581.620.054
33LC21L0.130.0040.260.0120.770.0121.450.0101.840.039
34RC22R0.110.0830.290.0610.870.1561.800.1972.060.101
35RC23R0.000.0050.240.0760.800.1251.460.0721.800.052
36RC24AR0.110.0050.230.0170.730.0141.430.1191.790.088
37LC24BL0.120.0080.330.0090.640.0161.380.1281.660.050
38RP25R0.100.0140.370.0431.030.1161.940.1702.200.213
39RC26AR0.140.0510.310.0660.910.0451.920.2272.130.137
40RC26BR0.140.0520.380.0441.070.0632.030.1302.330.077
41LC27L0.090.1050.190.0820.570.0881.210.1771.350.108
42LP28L0.210.0780.330.1030.700.1191.550.1541.870.167
43LP29L--0.270.1040.700.0731.410.2621.600.212
44RP30R0.090.0220.350.0641.030.0772.030.1212.100.105
45LP31L0.080.0530.400.3450.550.2131.330.2021.530.236
46RC32AR0.060.0310.200.0930.810.1021.610.0831.880.075
47RC32BR0.070.0410.290.1060.880.1381.730.1201.950.161
48RC33R0.050.0110.240.0410.700.0851.360.1551.580.110
49RP34R0.160.0720.390.0841.210.1342.260.2442.570.321
50LP35L0.110.0920.620.3710.840.2341.750.2612.210.219
51RC36AR0.170.0150.520.0300.890.0561.370.0532.300.060
52RC36BR0.190.0340.520.0250.940.0361.460.0692.430.051
53RC37AR0.080.0840.200.0980.700.1831.530.2311.780.341
54LC37BL0.110.0870.420.1810.850.1711.310.1781.700.152
55RP38R0.140.0710.280.0240.860.0601.730.1001.880.073
56RP39R0.130.0480.350.0691.030.1501.910.2032.010.518
57RP40R0.140.0840.370.0761.300.3292.440.2872.700.219
58RC41R0.110.0310.250.0100.830.1001.420.1171.780.106
59LC42L0.100.0170.260.0440.570.0521.190.0401.520.104
60LP43AL0.210.0570.440.1120.750.0321.360.0721.630.136
61LP43BL0.200.0140.470.1780.730.0151.350.0641.580.069
62LC44AL0.110.1050.270.1860.550.1501.290.1511.660.129
63LC44BL0.070.1080.220.0350.610.1381.350.1861.580.156
64RP45R0.060.0260.230.0320.700.0741.580.1681.710.073
65LP46L0.030.0540.140.1080.500.0871.030.1261.010.079
66LP47L0.190.0720.420.1250.780.0991.550.1721.700.259
67LC48L0.100.0040.300.0100.770.0181.300.0371.780.028
68RP49R0.210.0710.330.1171.050.1041.850.1081.940.129
69RP50AR0.070.0540.230.0400.770.0341.630.1281.830.113
70RP50BR0.040.0310.190.0390.750.0841.650.0831.850.047
71LP50CL0.090.0450.250.0810.560.0741.380.0981.460.127
72RC51R0.110.0230.400.0530.980.1211.950.1222.190.160
73RC52R0.000.0000.050.0620.640.1231.790.1672.180.192
74LP53L0.060.0150.260.0250.750.0101.600.0701.690.047
75RC54R0.090.0210.250.0260.810.0911.500.0901.850.064
76RUN55R0.440.1500.410.1390.940.1201.250.1921.970.195
77LP56L1.430.3681.840.7132.470.9363.821.0504.331.388
78RP57R0.130.0230.350.0530.970.0451.990.1042.260.088
79LP58L0.070.0280.230.0910.520.0511.220.1121.500.113
80LP59L0.720.6071.000.6601.240.6371.790.4933.270.758
81RP60AR0.070.0150.300.0390.850.0991.580.0852.170.127
82LP60BL0.070.0210.270.0460.660.0791.610.1142.410.243
83RP61R0.130.0080.300.0240.710.0161.010.0161.900.012
84RC62R0.040.0430.310.1341.040.1622.260.2882.350.326
85LC63L0.180.0080.340.0150.730.0351.240.0151.690.041
86RP64R0.040.0150.220.0730.590.1021.410.1621.430.170

Smoking machine R: rotary smoking machine, L: linear smoking machine

GC column C: capillary column, P: packed column, UN: unknown

The labcode was randomly assigned and is in no way related to the participation numbers of the laboratories, which were given in numerical order of data submission.

Exclusion of outliers

85 datasets, shown in Table 4, were sorted in descending order of their standard deviation. The test statistic C was calculated and compared with 1% of critical value. Cochran’s critical values are given in ISO 5725-2 (7) only up to 40 numbers of data sets.

As the numbers of datasets exceeded 40 in this study, Cochran’s critical value at corresponding numbers of datasets were calculated by use of the approximation in (9) which extends the Cochran’s test beyond 40 data sets.

When the test statistics was higher than the critical value, the dataset was considered an outlier. After the exclusion of an outlier dataset, the test statistic C for the next dataset with a higher standard deviation was calculated and compared to the critical value. Prior to the analysis the maximum number of outlier tests was restricted to four to avoid an excessive exclusion of dataset. The results of Cochran’s test are listed in Table 5. Applying Cochran’s test, two or three datasets were excluded as outliers. Grubbs’ test was applied for the mean values of the remaining datasets. There was no outlier in Grubbs’ test. The excluded datasets determined by Cochran’s test and Grubbs’ test are listed in Table 5.

Results of outlier tests.

SampleCochran’s testGrubbs’ testRemaining data sets
A59 L, 56 L, 55 RN/A82
B56 L, 59 L, 35 LN/A82
C56 L, 59 L, 40 RN/A82
D56 L, 59 LN/A83
E56 L, 59 L, 39 RN/A82

N/A: Not applicable

Two or three datasets from a total of 85 datasets were excluded from further statistical evaluation. The number of datasets classified by GC column type and smoking machine type is listed in Table 6.

Number of datasets classified by GC column type and smoking machine type.

Sample codeTotal datasetsColumn typeTotal by GC columnLinear smokingRotary smoking
A82Capillary461729
Packed361719
B82Capillary461729
Packed361719
C82Capillary461729
Packed361818
D83Capillary461729
Packed371819
E82Capillary461729
Packed361818
Comparison of capillary column with packed column

Datasets were classified by GC column type into capillary data and packed column data. Box plots of each column type for each test sample are shown in Figures 1 to 5.

Figure 1

Box plots of water yield for sample A. ⋄ indicate mean values

Figure 2

Box plots of water yield for sample B.

Figure 3

Box plots of water yield for sample C.

Figure 4

Box plots of water yield for sample D.

Figure 5

Box plots of water yield for sample E.

The diamond-shaped symbols indicate the mean values. The interquartile range (IQR) of capillary columns for sample A was narrower than the IQR of packed columns. IQR of capillary columns for samples B, C, D and E were almost identical to those of the packed columns. The t-test of Welch was applied to confirm the statistical difference in water yield determination by packed columns and capillary columns. The results of the t-test are listed in Table 7.

Results of t-test in water yields between capillary columns and packed columns.

Sample code“Tar” (mg/cig)Capillary (mg/cig)Packed (mg/cig)t-test a
MeanSDMeanSD
A10.0970.0430.1040.052ns
B30.2870.0890.2900.074ns
C60.7850.1550.7530.188ns
D101.5340.2721.5580.321ns
E14.11.8360.2871.7910.376ns

t-test ns: not significant

No significant difference between packed columns and capillary columns in water yield determination was observed in all test samples.

Comparison of water yields by smoking machine type and GC column type

Datasets were classified into four groups by the combination of GC column type and smoking machine type.

Box plots for each test sample are shown in Figures 6 to 10.

Figure 6

Box plots of water yield for sample A.

Figure 7

Box plots of water yield for sample B.

Figure 8

Box plots of water yield for sample C.

Figure 9

Box plots of water yield for sample D.

Figure 10

Box plots of water yield for sample E.

L/Cap means a combination of linear smoking machine and capillary column. L/Packed means a com bination of linear smoking machine and packed column. R/Cap means a combination of rotary smoking machine and capillary column. R/Packed means a combination of rotary smoking machine and capillary column.

IQR and median of the four groups for samples A and B were almost identical. But IQR and median of rotary and linear smoking machines seemed to be different for samples C, D and E. The results of the t-test are listed in Tables 8 and 9. A statistically significant difference in water yields was not observed between capillary columns and packed columns within the same type of smoking machine. On the other hand, statistically significant differences in water yields were observed for samples C, D and E between rotary smoking machines and linear smoking machines within the same type of GC column.

Results of t-test in water yields between capillary and packed column within same type of smoking machine (unit: mg/cig).

Sample codeLinearRotary
CapillaryPackedt-test aCapillaryPackedt-test a
MeanSDMeanSDMeanSDMeanSD
A0.1060.0410.1020.058ns0.0920.0440.1010.047ns
B0.2730.0650.2860.082ns0.290.1010.2960.068ns
C0.6320.1000.6450.113ns0.8740.1030.8610.188ns
D1.2870.1371.3910.193ns1.6760.2291.7180.338ns
E1.5760.1591.6140.324ns1.9880.231.9690.346ns

t-test ns: not significant

Results of t-test in water yields between linear and rotary smoking machine within same type of GC column (unit: mg/cig).

Sample codeCapillaryPacked
LinearRotaryt-test aLinearRotaryt-test a
MeanSDMeanSDMeanSDMeanSD
A0.1060.0410.0920.044ns0.1020.0580.1010.047ns
B0.2730.0650.2900.101ns0.2860.0820.2960.068ns
C0.6320.1000.8740.103**0.6450.1130.8610.188**
D1.2870.1371.6760.229**1.3910.1931.7180.338**
E1.5760.1591.9880.230**1.6140.3241.9690.346**

t-test ns: not significant,

1% significant

Repeatability and reproducibility estimation

The estimated values, which were calculated for all types of GC columns, capillary columns and packed columns are listed in Table 10. In comparison with repeatability and reproducibility defined in ISO 10362-1:1999, the estimated repeatability and reproducibility tends to be smaller than in ISO 10362-1:1999.

Estimated r and R for all water data, capillary columns and packed columns (unit: mg/cig).

Sample codeAll dataCapillary columnsPacked columns
MeanrRMeanrRMeanrR
A0.1010.1290.1760.0970.1310.1690.1040.130.187
B0.2860.2250.3070.2840.2090.3120.290.2430.302
C0.7710.2670.5340.7850.2810.5050.7530.2460.572
D1.5250.3650.8181.5180.3490.7731.5340.3790.883
E1.8160.4240.9991.8360.4320.8951.7910.4141.121
DISCUSSION
Comparison of capillary column with packed column

Crumpleret al. (4) also reported that there was no significant difference in water yield of CM8 between packed columns and capillary columns.

In our study, we could show that no significant difference was observed for water yields in cigarette smoke condensate between capillary and packed columns, not only from CM8 but also from other test samples, covering the majority of “tar” value products that are sold in the market.

Comparison of water yields by smoking machine type and GC column type

There was no significant difference in water yields between linear type smoking machines and rotary type smoking machines for samples A and B, which had the lowest water yields. On the other hand, the water yields for samples C, D and E by rotary type smoking machines were higher than those by linear type smoking machine.

The differences in water yields between rotary and linear smoking machines were already observed in the CORESTA Harmonization Study in 1991 (10) and in the CORESTA Collaborative Study conducted by CORESTA CO Sub-Committee (11). Although the differences in CO yields and NFDPM were improved and the differences in water yields became smaller through the improvement of air flow around cigarettes, higher water yields were still observed in the results obtained with rotary smoking machines under the ISO smoking regime (4, 12). Nevertheless, such a difference is no real influence in case of evaluation of the data from each smoking machine type. Comparisons between the two types of columns were carried out with a wider range of “tar” yields for each smoking machine type. This evaluation did not show significant difference between the data from packed columns and capillary columns.

Furthermore it was confirmed that there was no significant difference in the lower range of water yields between packed columns and capillary columns, with or without distinction of smoking machine type.

Comparison of estimated repeatability and reproducibility with the past results

The comparison of repeatability and reproducibility estimated by using all datasets as well as datasets classified by GC column type were made via an F-ratio test with a Bonferroni adjustment for multiple comparisons. No significant differences between capillary and packed columns were observed when comparing repeatability and reproducibility among the samples.

Estimated r and R listed in Table 10 were compared to those of ISO 10362-1:1999 (1) listed in Table 11 by use of 95% of upper limit of prediction bands (ULP) and lower limit of prediction bands (LLP). The ULP and LLP were determined by a linear regression analysis of mean, repeatability and reproducibility defined in ISO 10362-1:1999 (1).

Repeatability and reproducibility in ISO 10362-1:1999.

Mean value mw (mg/cig)Repeatability limit r (mg/cig)Reproducibility limit R (mg/cig)
0.0830.1540.241
0.1530.2280.353
0.3380.2720.381
0.9620.4070.734
1.5950.5610.935
3.1870.9081.680

The repeatability estimated by using all datasets as well as datasets classified by GC column type were plotted with those of ISO 10362-1:1999 and 95% of upper and lower limits for prediction bands (Figure 11).

Figure 11

Comparison of estimated repeatability (r) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.

95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands

The estimated repeatability for samples A and B were within the upper and lower limits for prediction bands. All of the estimated repeatability for samples C, D and E were smaller than 95% of lower limit for prediction band. This means that the estimated repeatability might be similar or smaller than the values in ISO 10362-1:1999.

The reproducibility estimated by using all datasets as well as datasets classified by GC column types were plotted with those of ISO 10362-1:1999 and 95% of upper and lower limits for prediction bands (Figure 12).

Figure 12

Comparison of estimated reproducibility (R) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.

95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands

The estimated reproducibility of packed columns was almost within the 95% upper and lower limit of prediction bands. On the other hand, the estimated reproducibility of capillary columns was smaller than 95% of lower limit of prediction band. This means that the estimated reproducibility of capillary columns is better than the reproducibility in ISO10362-1: 1999.

The estimated r and R by capillary column, packed column and all types of GC column are within 95% of upper limit for prediction band.

The estimated r and R for all data, capillary column and packed column are confirmed to be comparable to those of ISO 10362-1:1999, and these values can cover a wider range of water yields by ISO Smoking Regime.

The comparative results of water yields and estimated r and R strongly suggests that capillary columns are an appropriate alternative column for the gas chromatographic procedure of ISO 10362-1.

Figure 1

Box plots of water yield for sample A. ⋄ indicate mean values
Box plots of water yield for sample A. ⋄ indicate mean values

Figure 2

Box plots of water yield for sample B.
Box plots of water yield for sample B.

Figure 3

Box plots of water yield for sample C.
Box plots of water yield for sample C.

Figure 4

Box plots of water yield for sample D.
Box plots of water yield for sample D.

Figure 5

Box plots of water yield for sample E.
Box plots of water yield for sample E.

Figure 6

Box plots of water yield for sample A.
Box plots of water yield for sample A.

Figure 7

Box plots of water yield for sample B.
Box plots of water yield for sample B.

Figure 8

Box plots of water yield for sample C.
Box plots of water yield for sample C.

Figure 9

Box plots of water yield for sample D.
Box plots of water yield for sample D.

Figure 10

Box plots of water yield for sample E.
Box plots of water yield for sample E.

Figure 11

Comparison of estimated repeatability (r) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands
Comparison of estimated repeatability (r) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands

Figure 12

Comparison of estimated reproducibility (R) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands
Comparison of estimated reproducibility (R) for all, capillary and packed columns with those of ISO 10362-1 and upper and lower limits for prediction bands.95% LLP: 95% of lower limit for prediction bands 95% ULP: 95% of upper limit for prediction bands

Dataset per sample.

Test parameterSmoking machineNumber of runsReported data / sample
TPM (mg/cig)Linear 20 port6 runs 5 cig/port × 4 ports/run6 test results, mean and standard deviation
Water (mg/cig)
Nicotine (mg/cig)
NFDPM (mg/cig)Linear 16 port
CO (mg/cig)Linear 10 port
Puff count (puffs/cig)Rotary6 runs (20 cig/run)

Estimated r and R for all water data, capillary columns and packed columns (unit: mg/cig).

Sample codeAll dataCapillary columnsPacked columns
MeanrRMeanrRMeanrR
A0.1010.1290.1760.0970.1310.1690.1040.130.187
B0.2860.2250.3070.2840.2090.3120.290.2430.302
C0.7710.2670.5340.7850.2810.5050.7530.2460.572
D1.5250.3650.8181.5180.3490.7731.5340.3790.883
E1.8160.4240.9991.8360.4320.8951.7910.4141.121

Results of t-test in water yields between capillary and packed column within same type of smoking machine (unit: mg/cig).

Sample codeLinearRotary
CapillaryPackedt-test aCapillaryPackedt-test a
MeanSDMeanSDMeanSDMeanSD
A0.1060.0410.1020.058ns0.0920.0440.1010.047ns
B0.2730.0650.2860.082ns0.290.1010.2960.068ns
C0.6320.1000.6450.113ns0.8740.1030.8610.188ns
D1.2870.1371.3910.193ns1.6760.2291.7180.338ns
E1.5760.1591.6140.324ns1.9880.231.9690.346ns

Results of outlier tests.

SampleCochran’s testGrubbs’ testRemaining data sets
A59 L, 56 L, 55 RN/A82
B56 L, 59 L, 35 LN/A82
C56 L, 59 L, 40 RN/A82
D56 L, 59 LN/A83
E56 L, 59 L, 39 RN/A82

Results of t-test in water yields between capillary columns and packed columns.

Sample code“Tar” (mg/cig)Capillary (mg/cig)Packed (mg/cig)t-test a
MeanSDMeanSD
A10.0970.0430.1040.052ns
B30.2870.0890.2900.074ns
C60.7850.1550.7530.188ns
D101.5340.2721.5580.321ns
E14.11.8360.2871.7910.376ns

Mean and standard deviation (SD) of water yields for each data set (unit: mg/cig).

No.Smoking machine aGC column bLab. codeSample ASample BSample CSample DSample E
MeanSDMeanSDMeanSDMeanSDMeanSD
1RC01R0.070.0310.140.0370.960.1031.690.0861.900.109
2RC02R0.090.0610.300.0841.010.1541.930.2072.230.172
3LP03AL0.080.0660.170.0530.450.0461.030.0531.210.052
4RP03BR0.070.0520.150.0310.550.1111.220.1671.340.182
5LP04L0.150.0240.330.0460.690.0651.340.0781.560.121
6LP05L0.100.0290.290.0420.680.0571.540.0761.720.092
7LC06AL0.090.0300.380.1760.610.1211.380.2281.620.393
8LC06BL0.200.1040.350.2370.550.1801.000.2161.500.481
9RC07AR0.120.0350.430.0560.960.0481.900.0972.160.132
10RC07BR0.100.0360.350.0390.920.0361.830.1162.170.033
11LC07CL0.070.0220.190.0420.580.0171.230.1511.430.050
12RC08R0.090.0410.270.0420.870.0561.690.0891.970.115
13RC09R0.080.0800.230.0410.800.1181.550.1071.900.090
14RC10R0.040.0230.260.0210.860.0512.020.0492.140.080
15LC11L0.060.0430.210.0430.490.1311.210.1301.320.074
16RP12R0.080.0230.310.0681.050.0851.720.0332.190.126
17RC13AR0.130.0370.290.0380.930.0121.450.1151.520.115
18RC13BR0.130.0170.340.0790.880.0531.540.0951.680.170
19RP14R0.170.0170.370.0710.860.0881.670.1791.900.096
20RC15AR0.140.0530.320.0420.970.0551.690.0371.920.066
21LC15BL0.130.0850.170.1000.510.1131.130.1381.520.215
22RP16R0.080.0590.270.1050.740.1341.540.1131.700.148
23RP17AR0.090.0150.270.0310.770.1031.520.1451.820.112
24LP17BL0.100.0220.210.0340.530.0721.150.1411.310.076
25RC18AR0.100.0040.350.0340.880.0781.630.0961.780.145
26LC18BL0.090.0190.300.0560.660.1581.450.1841.390.203
27LC19AL0.060.0170.250.0130.620.0441.470.0781.630.089
28RC19BR0.130.0380.280.0390.900.0611.690.0732.030.066
29LC19CL0.080.0140.270.0180.670.0241.470.0851.730.112
30RC19DR0.080.0610.250.0540.820.0781.470.0831.820.033
31LP19EL0.060.0130.220.0100.550.0331.360.0291.440.040
32LP20L0.060.0140.270.0390.630.0731.450.0581.620.054
33LC21L0.130.0040.260.0120.770.0121.450.0101.840.039
34RC22R0.110.0830.290.0610.870.1561.800.1972.060.101
35RC23R0.000.0050.240.0760.800.1251.460.0721.800.052
36RC24AR0.110.0050.230.0170.730.0141.430.1191.790.088
37LC24BL0.120.0080.330.0090.640.0161.380.1281.660.050
38RP25R0.100.0140.370.0431.030.1161.940.1702.200.213
39RC26AR0.140.0510.310.0660.910.0451.920.2272.130.137
40RC26BR0.140.0520.380.0441.070.0632.030.1302.330.077
41LC27L0.090.1050.190.0820.570.0881.210.1771.350.108
42LP28L0.210.0780.330.1030.700.1191.550.1541.870.167
43LP29L--0.270.1040.700.0731.410.2621.600.212
44RP30R0.090.0220.350.0641.030.0772.030.1212.100.105
45LP31L0.080.0530.400.3450.550.2131.330.2021.530.236
46RC32AR0.060.0310.200.0930.810.1021.610.0831.880.075
47RC32BR0.070.0410.290.1060.880.1381.730.1201.950.161
48RC33R0.050.0110.240.0410.700.0851.360.1551.580.110
49RP34R0.160.0720.390.0841.210.1342.260.2442.570.321
50LP35L0.110.0920.620.3710.840.2341.750.2612.210.219
51RC36AR0.170.0150.520.0300.890.0561.370.0532.300.060
52RC36BR0.190.0340.520.0250.940.0361.460.0692.430.051
53RC37AR0.080.0840.200.0980.700.1831.530.2311.780.341
54LC37BL0.110.0870.420.1810.850.1711.310.1781.700.152
55RP38R0.140.0710.280.0240.860.0601.730.1001.880.073
56RP39R0.130.0480.350.0691.030.1501.910.2032.010.518
57RP40R0.140.0840.370.0761.300.3292.440.2872.700.219
58RC41R0.110.0310.250.0100.830.1001.420.1171.780.106
59LC42L0.100.0170.260.0440.570.0521.190.0401.520.104
60LP43AL0.210.0570.440.1120.750.0321.360.0721.630.136
61LP43BL0.200.0140.470.1780.730.0151.350.0641.580.069
62LC44AL0.110.1050.270.1860.550.1501.290.1511.660.129
63LC44BL0.070.1080.220.0350.610.1381.350.1861.580.156
64RP45R0.060.0260.230.0320.700.0741.580.1681.710.073
65LP46L0.030.0540.140.1080.500.0871.030.1261.010.079
66LP47L0.190.0720.420.1250.780.0991.550.1721.700.259
67LC48L0.100.0040.300.0100.770.0181.300.0371.780.028
68RP49R0.210.0710.330.1171.050.1041.850.1081.940.129
69RP50AR0.070.0540.230.0400.770.0341.630.1281.830.113
70RP50BR0.040.0310.190.0390.750.0841.650.0831.850.047
71LP50CL0.090.0450.250.0810.560.0741.380.0981.460.127
72RC51R0.110.0230.400.0530.980.1211.950.1222.190.160
73RC52R0.000.0000.050.0620.640.1231.790.1672.180.192
74LP53L0.060.0150.260.0250.750.0101.600.0701.690.047
75RC54R0.090.0210.250.0260.810.0911.500.0901.850.064
76RUN55R0.440.1500.410.1390.940.1201.250.1921.970.195
77LP56L1.430.3681.840.7132.470.9363.821.0504.331.388
78RP57R0.130.0230.350.0530.970.0451.990.1042.260.088
79LP58L0.070.0280.230.0910.520.0511.220.1121.500.113
80LP59L0.720.6071.000.6601.240.6371.790.4933.270.758
81RP60AR0.070.0150.300.0390.850.0991.580.0852.170.127
82LP60BL0.070.0210.270.0460.660.0791.610.1142.410.243
83RP61R0.130.0080.300.0240.710.0161.010.0161.900.012
84RC62R0.040.0430.310.1341.040.1622.260.2882.350.326
85LC63L0.180.0080.340.0150.730.0351.240.0151.690.041
86RP64R0.040.0150.220.0730.590.1021.410.1621.430.170

List of parameters to be reported.

Outline
Test periodSeptember 1st to November 30 th, 2015
Data set / sampleOne data set consists of 6 test results obtained from 6 runs. One test result was defined as the average yield obtained from 20 cigarettes in a single run.
Test parametersTPM, water, nicotine, NFDPM, CO, puffs
Original data sets86 data sets from 64 laboratories for each sample

Raw data of water yields for sample C (unit: mg/cig).

No.Smoking machineGC column typeLab. codeNo. of runMeanSD
123456
1RCapillary01R0.870.831.091.000.901.040.960.103
2RCapillary02R1.251.060.810.921.090.951.010.154
3LPacked03AL0.460.490.500.450.410.380.450.046
4RPacked03BR0.500.680.490.680.500.420.550.111
5LPacked04L0.720.620.660.630.740.780.690.065
6LPacked05L0.600.690.680.630.760.710.680.057
7LCapillary06AL0.630.640.670.480.450.770.610.121
8LCapillary06BL0.600.380.410.430.840.660.550.180
9RCapillary07AR1.000.981.010.930.900.920.960.048
10RCapillary07BR0.970.960.870.910.910.910.920.036
11LCapillary07CL0.580.600.580.570.550.590.580.017
12RCapillary08R0.940.880.900.800.800.870.870.056
13RCapillary09R0.880.730.790.610.950.810.800.118
14RCapillary10R0.920.880.800.910.860.810.860.051
15LCapillary11L0.390.530.570.270.560.610.490.131
16RPacked12R1.120.911.101.041.011.141.050.085
17RCapillary13AR0.930.940.940.940.910.930.930.012
18RCapillary13BR0.820.810.910.920.920.920.880.053
19RPacked14R0.870.810.770.970.790.960.860.088
20RCapillary15AR1.010.931.010.880.991.010.970.055
21LCapillary15BL0.600.460.690.400.450.440.510.113
22RPacked16R0.580.690.660.790.720.970.740.134
23RPacked17AR0.700.760.960.710.780.680.770.103
24LPacked17BL0.620.570.550.470.520.420.530.072
25RCapillary18AR0.750.900.890.881.000.880.880.078
26LCapillary18BL0.660.650.900.670.650.400.660.158
27LCapillary19AL0.560.580.640.640.680.610.620.044
28RCapillary19BR0.980.810.930.910.900.840.900.061
29LCapillary19CL0.660.670.640.700.660.700.670.024
30RCapillary19DR0.810.820.960.830.740.760.820.078
31LPacked19EL0.560.520.560.510.530.600.550.033
32LPacked20L0.710.630.590.730.550.580.630.073
33LCapillary21L0.780.760.770.790.780.760.770.012
34RCapillary22R0.710.770.780.841.031.090.870.156
35RCapillary23R0.900.900.610.680.810.890.800.125
36RCapillary24AR0.750.730.720.720.720.710.730.014
37LCapillary24BL0.640.610.640.660.640.630.640.016
38RPacked25R1.201.120.871.040.960.991.030.116
39RCapillary26AR0.890.910.990.860.910.880.910.045
40RCapillary26BR1.081.021.130.971.101.131.070.063
41LCapillary27L0.640.600.690.520.470.490.570.088
42LPacked28L0.510.700.850.790.640.720.700.119
43LPacked29L0.670.630.720.830.710.640.700.073
44RPacked30R1.121.111.010.951.020.941.030.077
45LPacked31L0.710.520.670.140.600.670.550.213
46RCapillary32AR0.720.800.770.940.710.930.810.102
47RCapillary32BR1.021.000.840.950.760.680.880.138
48RCapillary33R0.720.810.760.710.600.610.700.085
49RPacked34R1.381.291.331.081.131.071.210.134
50LPacked35L0.890.761.171.040.610.590.840.234
51RCapillary36AR0.970.860.940.910.820.860.890.056
52RCapillary36BR0.950.930.980.930.970.880.940.036
53RCapillary37AR0.820.620.600.480.671.000.700.183
54LCapillary37BL0.660.831.050.680.841.050.850.171
55RPacked38R0.880.790.960.810.830.890.860.060
56RPacked39R1.100.851.280.981.020.941.030.150
57RPacked40R1.090.931.231.191.841.531.300.329
58RCapillary41R0.920.950.730.730.880.750.830.100
59LCapillary42L0.600.560.500.600.530.640.570.052
60LPacked43AL0.790.750.740.740.700.780.750.032
61LPacked43BL0.700.720.730.740.740.730.730.015
62LCapillary44AL0.600.310.700.670.430.580.550.150
63LCapillary44BL0.490.680.460.610.840.580.610.138
64RPacked45R0.690.680.850.670.640.690.700.074
65LPacked46L0.460.430.440.660.460.520.500.087
66LPacked47L0.880.900.830.680.680.730.780.099
67LCapillary48L0.770.790.780.780.740.760.770.018
68RPacked49R1.100.851.141.101.051.081.050.104
69RPacked50AR0.780.790.810.780.770.710.770.034
70RPacked50BR0.780.640.820.650.810.810.750.084
71LPacked50CL0.610.540.610.620.430.520.560.074
72RCapillary51R0.920.990.790.971.111.110.980.121
73RCapillary52R0.680.510.480.680.670.810.640.123
74LPacked53L0.730.750.760.750.750.740.750.010
75RCapillary54R0.920.680.810.800.730.890.810.091
76Runknown55R0.750.940.941.130.940.940.940.120
77LPacked56L1.401.452.242.813.223.682.470.936
78RPacked57R0.920.980.990.911.001.020.970.045
79LPacked58L0.530.570.500.580.480.450.520.051
80LPacked59L0.621.550.881.340.752.321.240.637
81RPacked60AR0.861.020.900.750.810.770.850.099
82LPacked60BL0.660.550.720.650.600.770.660.079
83RPacked61R0.720.730.700.700.690.690.710.016
84RCapillary62R0.870.821.131.081.241.101.040.162
85LCapillary63L0.740.750.700.790.700.710.730.035
86RPacked64R0.430.630.500.610.690.670.590.102

List of Participating Laboratories

No.Name of participating laboratoriesCountry
1Papierfabrik Wattens GmbH & Co KGAustria
2British American Tobacco BangladeshBangladesh
3Philip Morris Brazil Industria & Comercio LtdaBrazil
4*RBH Inc.Canada
5Beijing Tobacco Monopoly BureauChina
6China National Tobacco Corporation Shandong BranchChina
7China National Tobacco Corporation Sichuan BranchChina
8*China National Tobacco Quality Supervision & Test CentreChina
9China Tobacco Co. Shannxi Provincial Co.China
10Guangdong Tobacco Quality Supervision and Test StationChina
11Guizhou Province Tobacco Quality Supervision & Test StationChina
12Henan Tobacco Quality Supervision & Test StationChina
13Hubei Tobacco Quality Supervision and Test StationChina
14Inner Mongolia Tob. Monopoly Quality Supervision and Test CenterChina
15Ji Lin Tobacco Quality Supervision & Inspection StationChina
16Shanghai Tobacco Group Co., LtdChina
17Yunnan Comtestor co., LTDChina
18Yunnan Tobacco Quality Supervision & Test StationChina
19Borgwaldt KC GmbHGermany
20*JT International Germany GmbHGermany
21Reemtsma Cigarettenfabriken GmbHGermany
22Hong Kong Government LaboratoryHong Kong
23*Godfrey Phillips India Ltd.India
24*ITC Ltd.India
25VST Industries Ltd.India
26*PT. Bentoel PrimaIndonesia
27*PT. DjarumIndonesia
28*PT. Gudang Garam Tbk.Indonesia
29PT. Gelora DjajaIndonesia
30*PT. HM Sampoerna. TbkIndonesia
31PT. Nojorono Tob. Intl.Indonesia
32PT. Sentosa Abadi PurwosariIndonesia
33*PT Sumatra Tobacco Trading CompanyIndonesia
34UPT PSMB-Lembaga Tembakau JemberIndonesia
35*Japan Tobacco Inc.Japan
36TIOJ Testing LaboratoryJapan
37Royal Scientific SocietyJordan
38BAT KoreaKorea
39Korea Conformity Laboratories (KCL)Korea
40KT&GKorea
41Ministry of Food and Drug SafetyKorea
42*Philip Morris KoreaKorea
43Tobacco Smoke Analysis CenterKorea
44Public Health LaboratoryMacao
45BAT AsPac Service CentreMalaysia
46National Public Health LaboratoryMalaysia
47*Philip Morris Mexico Productos Y ServiciosMexico
48Surya Nepal Pvt. Ltd.Nepal
49Pakistan Tobacco CompanyPakistan
50*Mighty CorporationPhilippines
51PMFTC Inc.Philippines
52British American Tobacco SingaporeSingapore
53Philip Morris InternationalSwitzerland
54Food & Drug Administration, Ministry of Health & WelfareTaiwan
55*Taiwan Cigarette and Liquor Cop.Taiwan
56Taiwan Tobacco and Liquor Corporation -1Taiwan
57Taiwan Tobacco and Liquor Corporation -2Taiwan
58Thailand Tobacco MonopolyThailand
59*Essentra Scientific ServicesU.K.
60Altria Client ServicesU.S.A.
61Enthalpy Analytical, Inc.U.S.A.
62R.J. Reynolds Tobacco Co.U.S.A.
63National Laboratory & Research CenterUAE
64Compañia Industrial de Tabacos Montepaz S.A.Uruguay

Number of datasets classified by GC column type and smoking machine type.

Sample codeTotal datasetsColumn typeTotal by GC columnLinear smokingRotary smoking
A82Capillary461729
Packed361719
B82Capillary461729
Packed361719
C82Capillary461729
Packed361818
D83Capillary461729
Packed371819
E82Capillary461729
Packed361818

List of samples.

CodeSample nameSupplierOriginNFDPM level (mg/cig)Butt length (mm)
AMevius One BoxJTJapan135
BMarlboro Clear 3 BoxPMILithuania335
CKent 6 KS BoxRJRUSA635
DMevius BoxJTJapan1035
ECORESTA Monitor (CM8)CORGermany14.1*33

Raw data of water yields for sample B (unit: mg/cig).

No.Smoking machineGC column typeLab. codeNo. of runMeanSD
123456
1RCapillary01R0.080.110.140.140.190.150.140.037
2RCapillary02R0.300.370.200.220.300.420.300.084
3LPacked03AL0.150.240.230.180.120.120.170.053
4RPacked03BR0.160.180.130.180.110.130.150.031
5LPacked04L0.330.250.350.330.310.390.330.046
6LPacked05L0.270.260.250.260.340.340.290.042
7LCapillary06AL0.270.440.290.360.230.710.380.176
8LCapillary06BL0.500.190.140.750.300.190.350.237
9RCapillary07AR0.490.470.390.360.480.390.430.056
10RCapillary07BR0.370.360.310.300.350.410.350.039
11LCapillary07CL0.210.130.250.210.200.160.190.042
12RCapillary08R0.320.300.260.200.260.250.270.042
13RCapillary09R0.280.240.200.160.240.240.230.041
14RCapillary10R0.280.250.250.290.270.240.260.021
15LCapillary11L0.170.200.250.270.170.180.210.043
16RPacked12R0.300.320.360.420.230.270.310.068
17RCapillary13AR0.280.280.320.230.330.320.290.038
18RCapillary13BR0.500.320.290.300.320.310.340.079
19RPacked14R0.240.350.440.380.420.400.370.071
20RCapillary15AR0.350.350.280.340.330.250.320.042
21LCapillary15BL0.270.190.300.140.070.060.170.100
22RPacked16R0.130.340.300.250.190.420.270.105
23RPacked17AR0.240.260.230.300.300.290.270.031
24LPacked17BL0.230.250.250.190.190.170.210.034
25RCapillary18AR0.290.380.360.370.350.340.350.034
26LCapillary18BL0.210.280.310.320.380.310.300.056
27LCapillary19AL0.230.260.250.240.260.260.250.013
28RCapillary19BR0.290.270.250.340.260.230.280.039
29LCapillary19CL0.280.280.260.240.280.250.270.018
30RCapillary19DR0.260.270.260.330.220.170.250.054
31LPacked19EL0.230.230.220.210.210.230.220.010
32LPacked20L0.310.300.220.240.310.260.270.039
33LCapillary21L0.270.250.260.260.270.240.260.012
34RCapillary22R0.210.250.290.300.380.340.290.061
35RCapillary23R0.300.260.120.280.310.170.240.076
36RCapillary24AR0.210.220.230.260.240.230.230.017
37LCapillary24BL0.320.320.340.330.330.340.330.009
38RPacked25R0.350.340.430.410.380.320.370.043
39RCapillary26AR0.330.440.310.270.250.290.310.066
40RCapillary26BR0.400.390.360.300.440.380.380.044
41LCapillary27L0.320.230.180.070.190.170.190.082
42LPacked28L0.190.380.220.400.370.440.330.103
43LPacked29L0.170.280.410.330.130.300.270.104
44RPacked30R0.420.420.300.270.360.310.350.064
45LPacked31L0.140.130.770.650.000.710.400.345
46RCapillary32AR0.210.220.160.200.060.350.200.093
47RCapillary32BR0.220.180.250.270.330.480.290.106
48RCapillary33R0.210.280.250.210.300.210.240.041
49RPacked34R0.540.390.350.390.400.280.390.084
50LPacked35L0.920.261.080.840.350.250.620.371
51RCapillary36AR0.560.520.480.550.530.500.520.030
52RCapillary36BR0.480.530.510.500.550.530.520.025
53RCapillary37AR0.170.330.040.190.180.270.200.098
54LCapillary37BL0.120.320.640.490.410.520.420.181
55RPacked38R0.270.250.320.280.260.290.280.024
56RPacked39R0.460.260.370.310.360.320.350.069
57RPacked40R0.300.320.400.370.510.340.370.076
58RCapillary41R0.260.240.250.250.240.240.250.010
59LCapillary42L0.240.200.320.230.280.290.260.044
60LPacked43AL0.650.400.350.380.370.470.440.112
61LPacked43BL0.830.400.360.420.400.410.470.178
62LCapillary44AL0.280.080.420.400.440.010.270.186
63LCapillary44BL0.210.160.240.220.260.240.220.035
64RPacked45R0.270.260.230.200.230.190.230.032
65LPacked46L0.000.050.140.240.280.110.140.108
66LPacked47L0.550.550.250.450.300.400.420.125
67LCapillary48L0.310.290.300.280.300.290.300.010
68RPacked49R0.540.310.190.310.280.360.330.117
69RPacked50AR0.240.210.280.280.200.190.230.040
70RPacked50BR0.170.160.180.190.270.190.190.039
71LPacked50CL0.220.240.230.320.370.140.250.081
72RCapillary51R0.440.420.410.350.310.440.400.053
73RCapillary52R0.010.050.000.060.170.020.050.062
74LPacked53L0.250.290.240.250.300.250.260.025
75RCapillary54R0.260.250.290.220.250.220.250.026
76Runknown55R0.560.560.380.380.190.380.410.139
77LPacked56L1.230.922.192.431.562.721.840.713
78RPacked57R0.350.450.340.330.320.300.350.053
79LPacked58L0.210.390.130.250.230.160.230.091
80LPacked59L0.251.201.150.412.090.871.000.660
81RPacked60AR0.330.300.280.260.250.350.300.039
82LPacked60BL0.320.240.200.280.240.310.270.046
83RPacked61R0.300.290.300.280.340.270.300.024
84RCapillary62R0.300.120.260.250.460.470.310.134
85LCapillary63L0.350.340.310.350.330.340.340.015
86RPacked64R0.160.120.210.290.310.230.220.073

Raw data of water yields for sample E (unit: mg/cig).

No.Smoking machineGC column typeLab. codeNo. of runMeanSD
123456
1RCapillary01R1.962.061.931.791.781.851.900.109
2RCapillary02R2.402.192.102.092.482.092.230.172
3LPacked03AL1.201.221.211.301.161.161.210.052
4RPacked03BR1.151.471.321.581.441.121.340.182
5LPacked04L1.471.601.531.651.401.731.560.121
6LPacked05L1.581.641.741.811.811.711.720.092
7LCapillary06AL1.411.631.562.201.041.851.620.393
8LCapillary06BL1.140.741.971.871.461.801.500.481
9RCapillary07AR2.272.291.922.192.182.142.160.132
10RCapillary07BR2.162.162.182.202.122.212.170.033
11LCapillary07CL1.481.461.431.411.451.341.430.050
12RCapillary08R2.032.112.041.941.781.931.970.115
13RCapillary09R1.991.971.911.841.931.751.900.090
14RCapillary10R2.202.192.232.132.072.022.140.080
15LCapillary11L1.321.281.361.261.241.441.320.074
16RPacked12R2.082.322.372.102.092.152.190.126
17RCapillary13AR1.691.531.481.421.601.381.520.115
18RCapillary13BR1.801.651.691.361.811.781.680.170
19RPacked14R2.041.761.901.901.841.961.900.096
20RCapillary15AR1.981.971.831.881.971.861.920.066
21LCapillary15BL1.411.851.731.461.331.361.520.215
22RPacked16R1.581.731.511.881.641.851.700.148
23RPacked17AR1.761.841.871.631.961.851.820.112
24LPacked17BL1.201.411.311.361.331.251.310.076
25RCapillary18AR1.721.681.711.641.961.971.780.145
26LCapillary18BL1.321.771.301.171.411.371.390.203
27LCapillary19AL1.481.601.591.711.711.671.630.089
28RCapillary19BR1.922.052.082.012.112.042.030.066
29LCapillary19CL1.761.591.761.611.881.801.730.112
30RCapillary19DR1.831.821.851.761.831.831.820.033
31LPacked19EL1.491.491.451.401.411.421.440.040
32LPacked20L1.601.671.671.661.571.551.620.054
33LCapillary21L1.761.851.861.861.851.851.840.039
34RCapillary22R2.071.892.102.022.182.122.060.101
35RCapillary23R1.881.831.801.741.741.781.800.052
36RCapillary24AR1.661.891.841.791.701.831.790.088
37LCapillary24BL1.641.671.741.631.591.661.660.050
38RPacked25R2.132.442.372.341.912.032.200.213
39RCapillary26AR2.121.962.242.332.032.072.130.137
40RCapillary26BR2.282.292.322.342.482.282.330.077
41LCapillary27L1.461.481.301.221.371.251.350.108
42LPacked28L1.672.151.951.841.861.751.870.167
43LPacked29L1.221.621.641.681.591.871.600.212
44RPacked30R2.172.162.131.942.212.012.100.105
45LPacked31L1.331.721.881.301.381.591.530.236
46RCapillary32AR1.991.811.801.941.921.841.880.075
47RCapillary32BR2.111.942.161.861.911.721.950.161
48RCapillary33R1.711.691.561.551.551.411.580.110
49RPacked34R2.972.832.552.622.072.362.570.321
50LPacked35L2.202.312.501.982.351.942.210.219
51RCapillary36AR2.252.222.382.292.352.282.300.060
52RCapillary36BR2.442.492.402.452.472.352.430.051
53RCapillary37AR1.961.501.561.392.122.181.780.341
54LCapillary37BL1.531.771.841.551.641.891.700.152
55RPacked38R1.781.841.941.851.961.941.880.073
56RPacked39R2.061.962.322.182.501.022.010.518
57RPacked40R2.472.522.752.542.982.922.700.219
58RCapillary41R1.901.821.791.581.801.801.780.106
59LCapillary42L1.441.431.681.551.601.441.520.104
60LPacked43AL1.861.551.461.621.601.691.630.136
61LPacked43BL1.551.611.461.591.651.631.580.069
62LCapillary44AL1.601.661.561.581.911.641.660.129
63LCapillary44BL1.711.431.491.451.821.601.580.156
64RPacked45R1.741.681.801.751.691.591.710.073
65LPacked46L0.890.971.050.961.051.111.010.079
66LPacked47L1.851.881.532.051.501.401.700.259
67LCapillary48L1.801.781.771.771.731.811.780.028
68RPacked49R1.901.951.911.792.181.911.940.129
69RPacked50AR1.771.772.021.911.791.721.830.113
70RPacked50BR1.821.891.911.821.871.791.850.047
71LPacked50CL1.391.521.451.681.421.311.460.127
72RCapillary51R1.942.442.212.162.222.152.190.160
73RCapillary52R2.151.932.112.242.132.512.180.192
74LPacked53L1.711.731.631.741.641.671.690.047
75RCapillary54R1.921.741.871.881.861.801.850.064
76Runknown55R2.062.252.061.691.881.881.970.195
77LPacked56L2.144.086.494.214.494.594.331.388
78RPacked57R2.282.192.392.242.322.152.260.088
79LPacked58L1.451.401.371.541.681.531.500.113
80LPacked59L2.293.613.992.464.063.233.270.758
81RPacked60AR2.212.052.211.982.282.292.170.127
82LPacked60BL2.182.192.682.742.322.352.410.243
83RPacked61R1.901.911.891.881.911.901.900.012
84RCapillary62R2.091.992.732.752.182.342.350.326
85LCapillary63L1.751.661.651.731.671.671.690.041
86RPacked64R1.561.341.321.231.421.691.430.170

Repeatability and reproducibility in ISO 10362-1:1999.

Mean value mw (mg/cig)Repeatability limit r (mg/cig)Reproducibility limit R (mg/cig)
0.0830.1540.241
0.1530.2280.353
0.3380.2720.381
0.9620.4070.734
1.5950.5610.935
3.1870.9081.680

Results of t-test in water yields between linear and rotary smoking machine within same type of GC column (unit: mg/cig).

Sample codeCapillaryPacked
LinearRotaryt-test aLinearRotaryt-test a
MeanSDMeanSDMeanSDMeanSD
A0.1060.0410.0920.044ns0.1020.0580.1010.047ns
B0.2730.0650.2900.101ns0.2860.0820.2960.068ns
C0.6320.1000.8740.103**0.6450.1130.8610.188**
D1.2870.1371.6760.229**1.3910.1931.7180.338**
E1.5760.1591.9880.230**1.6140.3241.9690.346**

Raw data of water yields for sample A (unit: mg/cig).

No.Smoking machineGC column typeLab. CodeNo. of runMeanSD
123456
1RCapillary01R0.020.040.080.100.060.090.070.031
2RCapillary02R0.150.170.020.040.120.060.090.061
3LPacked03AL0.040.150.170.030.020.050.080.066
4RPacked03BR0.130.050.130.010.030.050.070.052
5LPacked04L0.170.110.170.170.140.160.150.024
6LPacked05L0.070.080.090.110.110.150.100.029
7LCapillary06AL0.120.080.100.040.120.080.090.030
8LCapillary06BL0.330.220.060.290.120.150.200.104
9RCapillary07AR0.190.080.110.110.130.110.120.035
10RCapillary07BR0.140.130.050.100.080.070.100.036
11LCapillary07CL0.060.080.080.030.090.080.070.022
12RCapillary08R0.160.080.060.120.060.060.090.041
13RCapillary09R0.190.010.100.010.160.020.080.080
14RCapillary10R0.000.030.060.060.060.020.040.023
15LCapillary11L0.100.020.110.080.020.020.060.043
16RPacked12R0.070.050.080.090.100.120.080.023
17RCapillary13AR0.100.120.100.130.120.200.130.037
18RCapillary13BR0.140.140.110.110.120.150.130.017
19RPacked14R0.160.170.160.190.180.140.170.017
20RCapillary15AR0.200.220.130.100.110.100.140.053
21LCapillary15BL0.110.090.090.020.190.260.130.085
22RPacked16R0.030.050.130.070.020.170.080.059
23RPacked17AR0.080.100.080.090.090.120.090.015
24LPacked17BL0.130.120.090.090.070.110.100.022
25RCapillary18AR0.090.100.100.100.090.100.100.004
26LCapillary18BL0.090.080.110.060.070.100.090.019
27LCapillary19AL0.030.070.060.050.060.080.060.017
28RCapillary19BR0.130.180.120.090.170.090.130.038
29LCapillary19CL0.090.090.060.060.080.070.080.014
30RCapillary19DR0.070.100.170.110.010.010.080.061
31LPacked19EL0.070.070.040.070.050.060.060.013
32LPacked20L0.090.060.060.060.060.050.060.014
33LCapillary21L0.130.120.130.130.130.130.130.004
34RCapillary22R0.040.100.050.090.110.270.110.083
35RCapillary23R0.010.010.000.000.010.000.000.005
36RCapillary24AR0.100.110.110.100.110.100.110.005
37LCapillary24BL0.120.120.110.130.120.110.120.008
38RPacked25R0.090.080.110.100.100.120.100.014
39RCapillary26AR0.180.150.090.090.090.210.140.051
40RCapillary26BR0.180.140.090.060.200.150.140.052
41LCapillary27L0.280.120.030.000.010.080.090.105
42LPacked28L0.090.190.170.310.250.260.210.078
43LPacked29Ln.s. an.s.n.s.n.s.n.s.n.s.n.s.n.s.
44RPacked30R0.120.080.100.110.080.060.090.022
45LPacked31L0.030.110.080.130.000.120.080.053
46RCapillary32AR0.080.020.090.090.030.070.060.031
47RCapillary32BR0.010.050.080.130.060.100.070.041
48RCapillary33R0.050.070.050.030.050.060.050.011
49RPacked34R0.270.100.120.230.170.090.160.072
50LPacked35L0.060.100.150.270.000.090.110.092
51RCapillary36AR0.200.180.160.170.170.160.170.015
52RCapillary36BR0.180.170.240.170.160.230.190.034
53RCapillary37AR0.000.040.210.050.010.140.080.084
54LCapillary37BL0.010.160.130.130.220.000.110.087
55RPacked38R0.070.070.090.250.170.170.140.071
56RPacked39R0.220.060.130.120.140.120.130.048
57RPacked40R0.040.040.200.200.230.130.140.084
58RCapillary41R0.160.120.100.130.070.090.110.031
59LCapillary42L0.120.090.080.100.090.120.100.017
60LPacked43AL0.200.170.180.180.180.320.210.057
61LPacked43BL0.190.180.180.210.200.210.200.014
62LCapillary44AL0.130.200.140.140.14−0.100.110.105
63LCapillary44BL−0.04−0.030.050.030.190.210.070.108
64RPacked45R0.080.040.050.090.060.020.060.026
65LPacked46L0.000.130.000.000.000.060.030.054
66LPacked47L0.300.180.100.230.200.130.190.072
67LCapillary48L0.090.100.100.100.100.100.100.004
68RPacked49R0.240.280.090.280.190.190.210.071
69RPacked50AR0.010.070.100.150.070.010.070.054
70RPacked50BR0.030.050.050.000.080.000.040.031
71LPacked50CL0.060.040.100.130.140.040.090.045
72RCapillary51R0.120.100.130.130.080.080.110.023
73RCapillary52R0.000.000.000.000.000.000.000.000
74LPacked53L0.080.060.050.050.070.040.060.015
75RCapillary54R0.110.100.070.100.060.110.090.021
76Runknown55R0.560.380.190.380.560.560.440.150
77LPacked56L0.881.581.501.991.341.271.430.368
78RPacked57R0.130.140.130.130.100.170.130.023
79LPacked58L0.040.050.080.110.080.040.070.028
80LPacked59L0.230.571.820.351.000.330.720.607
81RPacked60AR0.080.090.060.070.050.060.070.015
82LPacked60BL0.050.070.070.110.060.060.070.021
83RPacked61R0.130.130.140.130.120.140.130.008
84RCapillary62R0.010.120.020.000.050.040.040.043
85LCapillary63L0.190.170.180.190.180.190.180.008
86RPacked64R0.040.020.060.020.040.030.040.015

Raw data of water yields for sample D (unit: mg/cig).

No.Smoking machineGC column typeLab. codeNo. of runMeanSD
123456
1RCapillary01R1.581.591.791.731.751.701.690.086
2RCapillary02R2.162.031.761.662.02-1.930.207
3LPacked03AL1.011.001.081.051.090.951.030.053
4RPacked03BR1.201.481.061.361.181.071.220.167
5LPacked04L1.311.331.241.421.311.451.340.078
6LPacked05L1.511.481.471.541.681.551.540.076
7LCapillary06AL1.281.251.491.801.221.241.380.228
8LCapillary06BL1.191.070.730.891.280.831.000.216
9RCapillary07AR2.001.842.051.861.801.881.900.097
10RCapillary07BR1.952.001.711.771.801.751.830.116
11LCapillary07CL1.251.191.441.321.151.001.230.151
12RCapillary08R1.701.691.751.791.671.531.690.089
13RCapillary09R1.621.461.611.471.691.431.550.107
14RCapillary10R2.012.112.011.972.042.022.020.049
15LCapillary11L1.091.141.081.381.191.351.210.130
16RPacked12R1.711.751.711.761.741.671.720.033
17RCapillary13AR1.551.501.361.281.581.451.450.115
18RCapillary13BR1.621.421.551.461.671.511.540.095
19RPacked14R1.811.741.391.801.491.771.670.179
20RCapillary15AR1.741.671.641.701.671.721.690.037
21LCapillary15BL1.121.051.291.001.311.011.130.138
22RPacked16R1.451.441.531.701.451.651.540.113
23RPacked17AR1.581.541.711.331.601.371.520.145
24LPacked17BL1.251.181.251.221.140.881.150.141
25RCapillary18AR1.521.641.511.681.661.761.630.096
26LCapillary18BL1.571.171.651.461.541.281.450.184
27LCapillary19AL1.381.361.511.561.501.481.470.078
28RCapillary19BR1.731.621.791.711.691.591.690.073
29LCapillary19CL1.531.541.381.361.441.551.470.085
30RCapillary19DR1.541.401.561.481.481.341.470.083
31LPacked19EL1.381.361.391.341.391.321.360.029
32LPacked20L1.381.391.491.501.411.501.450.058
33LCapillary21L1.471.451.461.451.451.441.450.010
34RCapillary22R1.521.651.821.821.942.071.800.197
35RCapillary23R1.491.501.341.411.501.521.460.072
36RCapillary24AR1.511.421.201.531.461.461.430.119
37LCapillary24BL1.561.341.241.271.341.501.380.128
38RPacked25R2.162.032.021.961.801.691.940.170
39RCapillary26AR2.001.602.152.161.721.901.920.227
40RCapillary26BR2.121.842.191.952.101.982.030.130
41LCapillary27L1.321.361.371.081.170.931.210.177
42LPacked28L1.331.571.651.761.581.431.550.154
43LPacked29L1.061.231.391.781.371.631.410.262
44RPacked30R2.212.041.981.842.072.032.030.121
45LPacked31L1.561.081.311.551.131.341.330.202
46RCapillary32AR1.701.621.691.601.521.511.610.083
47RCapillary32BR1.941.801.591.721.681.681.730.120
48RCapillary33R1.251.501.551.411.151.291.360.155
49RPacked34R2.612.502.172.152.161.972.260.244
50LPacked35L1.901.852.031.821.571.311.750.261
51RCapillary36AR1.391.331.361.311.461.361.370.053
52RCapillary36BR1.451.361.411.511.551.481.460.069
53RCapillary37AR1.701.591.551.131.461.791.530.231
54LCapillary37BL1.111.291.361.311.171.621.310.178
55RPacked38R1.651.631.731.911.731.741.730.100
56RPacked39R1.881.672.162.101.961.701.910.203
57RPacked40R2.132.152.442.372.842.702.440.287
58RCapillary41R1.641.401.361.291.411.431.420.117
59LCapillary42L1.141.141.201.211.201.241.190.040
60LPacked43AL1.451.251.361.341.341.431.360.072
61LPacked43BL1.401.281.361.281.441.351.350.064
62LCapillary44AL1.271.141.501.431.251.131.290.151
63LCapillary44BL1.501.571.291.211.091.461.350.186
64RPacked45R1.841.411.741.491.491.521.580.168
65LPacked46L1.010.871.050.941.241.061.030.126
66LPacked47L1.631.501.751.301.701.431.550.172
67LCapillary48L1.271.331.321.301.331.241.300.037
68RPacked49R1.941.841.951.761.931.691.850.108
69RPacked50AR1.701.701.661.771.521.431.630.128
70RPacked50BR1.601.541.721.761.691.611.650.083
71LPacked50CL1.401.321.401.271.551.331.380.098
72RCapillary51R1.982.021.852.081.991.751.950.122
73RCapillary52R1.661.721.711.761.752.121.790.167
74LPacked53L1.591.611.661.631.461.621.600.070
75RCapillary54R1.441.531.551.351.601.531.500.090
76Runknown55R1.311.501.311.130.941.311.250.192
77LPacked56L2.432.723.915.004.114.763.821.050
78RPacked57R2.002.131.992.061.831.931.990.104
79LPacked58L1.191.321.041.331.281.161.220.112
80LPacked59L1.221.992.132.471.641.291.790.493
81RPacked60AR1.451.641.551.531.691.601.580.085
82LPacked60BL1.691.741.681.491.461.621.610.114
83RPacked61R1.001.021.000.991.030.991.010.016
84RCapillary62R1.921.982.542.192.302.632.260.288
85LCapillary63L1.231.231.261.221.241.251.240.015
86RPacked64R1.271.651.261.301.421.551.410.162

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