ORIGINAL RESEARCH ARTICLE

Nicotine Quantification In Vitro:A Consistent Dosimetry Marker for e-Cigarette

Aerosol and Cigarette Smoke Generation

Jason Adamson,1,* Xiang Li,2,* Huapeng Cui,2 David Thorne,1 Fuwei Xie,2 and Marianna Gaca1

Abstract

The e-cigarette category is evolving rapidly, providing consumers with a variety of formats, ranging from cig-a-like products to larger, high-powered modular devices. When generating an in vitro assessment approach acrosssuch diverse products, dosimetry considerations are paramount. In this article, we have compared nicotine quan-tification techniques in two studies using a Vitrocell VC 10 Smoking Robot to generate aerosols from different e-cigarettes. In Study 1, a 3R4F reference cigarette and four different commercially available e-cigarettes werecompared: puff-by-puff nicotine concentration was quantified at the same e-cigarette puffing regime (CRMNo81) or with different puff durations, (2 or 3 seconds), comparing 3R4F puff-by-puff yields following ISOand HCI smoking regimes. In Study 2, 3R4F and one e-cigarette were assessed for puff-by-puff nicotine concen-tration in different locations (China and United Kingdom) comparing different nicotine quantification methodswith gas chromatography–mass spectrometry and UPLC-MS/MS used in the two laboratories. Study 1 showedthat 3R4F cigarette delivers different nicotine concentrations across the different regimes and puff number, sup-porting the nicotine methodology; e-cigarettes tested generated different amounts of nicotine across the devicestested, but showed consistent puff-by-puff delivery per device. Study 2 showed positive agreement between re-sults across two different laboratories utilizing different methods for nicotine quantification; statistical analysis,combining all interlaboratory variables, indicated that laboratory differences and the interaction of laboratoryand puff number were not significant ( p = 0.067 and 0.960, respectively). These studies will add further knowl-edge to support the in vitro assessment of novel nicotine products, providing reliability and assurance in the areaof in vitro dosimetry.

Keywords: dosimetry, e-cigarette, interlaboratory, nicotine, vitrocell VC 10

Introduction

Traditional combustible cigarettes have been aroundfor over 150 years, and despite numerous product changes

and innovations in this time—tobacco blend, paper technol-ogy, filters containing charcoal, or capsules—both the funda-mental smoke formation mechanism and the external visualappearance do not appear to have changed significantly. Bycontrast, new or next-generation tobacco and nicotine prod-ucts (NGPs) such as electronic cigarettes (e-cigarettes) haveappeared only within the last decade or so and, in the shorttime compared with cigarettes, have evolved rapidly andchanged in appearance and functionalities.1 The latest formats

of modular and customizable e-cigarettes are esthetically dif-ferent to the first-generation cig-a-like devices, which resem-bled a traditional cigarette (Fig. 1).

The NGP category is growing fast and awareness andusage of e-cigarettes in particular have increased exponen-tially to the point of near-universal awareness.2 Recent scien-tific data have demonstrated the comparative simplicity ofthe e-cigarette aerosol in comparison with tobacco cigarettesmoke, with substantial (88%–99%) differences between thelevels of e-cigarette and cigarette emissions.3 However, tox-icological evaluation must follow, including the use of cur-rent and future in vitro test systems that can be exposedby aerosols from these new and diverse devices. The basic

1British American Tobacco, R&D, Southampton, United Kingdom.2Zhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, PR China.*Joint first authors.

ª Jason Adamson et al., 2017; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the CreativeCommons Attribution Noncommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use,distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

APPLIED IN VITRO TOXICOLOGYVolume 3, Number 1, 2017Mary Ann Liebert, Inc.DOI: 10.1089/aivt.2016.0025

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requirement is that the test method should be able to generateand deliver the cigarette smoke or aerosol from differentvapor products effectively and repeatedly to enable robustand reliable in vitro toxicological and biological evaluation.

E-cigarettes in particular have changed in their external ap-pearance, functional design, and e-liquid formulations; be-tween 2012 and 2016, there have already been 4 or 5 majoriterations of product evolution (Fig. 1). The first modern e-cigarette was invented in China in 2003, but only started tobecome popular with consumers some years later.

The first generation of e-cigarette was a cig-a-like dis-posable device (looking like a traditional cigarette) withmany companies entering the U.S. and U.K. markets around2012 (Fig. 1B). Soon thereafter, rechargeable cig-a-like-devices emerged; some devices were the same size as a cig-arette, but some devices were growing in size to accommo-date higher powered batteries and variable power settingsto drive the generation and delivery of larger amounts ofaerosol (Fig. 1C). In the last few years, the vapor categoryhas diversified further from pen-like devices (Fig. 1D) onto modular, open system tank devices (Fig. 1E). With suchdiversity in product designs and consumer’s choice in differ-ent e-liquids, this poses a significant challenge to those in-volved in toxicological in vitro testing, risk assessment,and regulation of these products.

The U.S. Food and Drug Administration published itsdraft guidance on the scientific studies required to evaluateand demonstrate significantly reduced harm and risk ofNGPs, including the use of in vitro assessment tools.4 Withtraditional combustible tobacco products, we and othershave established a foundation of testing approaches whereair–liquid interface (ALI) in vitro exposure systems havebeen used and their results published. More recently, thesame approaches have been employed to evaluate NGPs.5–8

There are many different in vitro systems available with dif-ferent modes of dilution, delivery, and aerosol losses betweenthe point of smoke/aerosol generation and the exposure inter-face.9 These systems are largely dissimilar in function and ap-

pearance, but aim to achieve the same outcome by exposing abiological system (in vitro model or regulatory toxicologyassay) at the ALI. Therefore, understanding each exposuresystem thoroughly and the test article being assessed becomesan essential and first investigation. Understanding the aerosolsource (Fig. 2) and being able to show consistent and robustaerosol generation help to give confidence in the dose determi-nation later at the exposure interface and biological responsesdownstream.

Two reviews have described a number of exposure systemsavailable, including smoking machines/robots and in vitroexposure chambers,9 and more recently, the in vitro end-points that have been published from such tobacco smokeALI systems.10

As commercially available exposure systems and their useare becoming more advanced, there is a need to harmonizeapproaches and standardize methods. For example, a com-prehensive interlaboratory study using the Vitrocell VC 10Smoking Robot (Fig. 2) was undertaken involving six inde-pendent VC 10s in four laboratories in three countries.11 Inthis study, quartz crystal microbalances (QCMs) wereemployed as a gravimetric dosimetry tool installed into theexposure modules, enabling assessment of tobacco smokeparticle deposition in real time.

QCMs enable a greater understanding of tobacco smokeparticle dose and delivery, presenting data as quantifiabledeposited mass per surface area, rather than an arbitrarydilution factor/ratio/percentage.11 Regional deposition wascompared across exposure module positions in the six VC10s: it was reported that the dose–responses obtained fromthe six machines across four different locations demonstratedexcellent agreement with gauge R&r at 7.7%.11 Gauge R&r(reproducibility [R] and repeatability [r]) is an analysis ofvariance (ANOVA) test employed to assess multiples ofthe same measurement system in different locations/with dif-ferent operators (R) and also within the same measurementsystem in one location (r). Gauge R&r is the sum of intra-(r) and interlaboratory (R) variability, and measurement

FIG. 1. The test articles in this study and their evolution timeline: cigarette (reference) (A); commercially available first-generation disposable e-cigarette (cig-a-like) (B); commercially available rechargeable e-cigarette (cig-a-like) (C); commer-cially available second-generation closed modular e-cigarette (D); commercially available open modular tank system (E).

2 ADAMSON ET AL.

system values less than 10% overall are considered statisti-cally fit for purpose.11

In this article, we have compared VC 10 aerosol genera-tion at source by nicotine quantification. The research wasdivided into two studies. In Study 1, a single laboratoryassessed methodology and a range of products before mov-ing into Study 2, where we repeated aspects of Study 1 byadding a second laboratory at a different geographical loca-tion. As both laboratories/machines had been involved in theprevious larger interlaboratory study,11 their unique anony-mized codes were retained herein for continuity purposes:Lab A and Lab D.

In Study 1, we investigated a 3R4F reference cigarette(product A, Fig. 1) and a selection of different vapor productsranging from first-generation e-cigarette to one of the mostrecent e-cigarette device types available (products B–E,Fig. 1); for Study 2, only two products were selected to betested in Lab A and Lab D—a cigarette (product A) andone e-cigarette (product B). Product selection was drivenby the availability of the products in both countries. As thetwo VC 10s in Lab A and Lab D were previously demon-strated to be delivering the same cigarette smoke at the expo-sure interface,11 this study was designed to compare thegeneration of cigarette and e-cigarette aerosols, quantifying

nicotine level per puff, and crucially with each laboratory’s in-dependent nicotine quantification method.

An additional nicotine extract stability shelf life investiga-tion was included in Lab A to assess that the nicotine in e-cigarette samples (solvent extracted) would not degradeover the time of the study for future studies where samplesmay be exchanged and analyzed by different laboratories.Results of these current studies suggest that assessment ofnicotine extract samples may provide a more reproducibleand reliable range of diluted effluents for toxicology testing,rather than using QCMs (which are not compatible for real-time, e-cigarette aerosol measurements longer than a fewminutes—discussed in more detail later). This approachwill also likely provide useful supplementary data in charac-terizing the dosimetry of in vitro exposure systems.

Materials and Methods

Our research was conducted in two linked studies to en-able a more thorough assessment of the generation and sta-bility of e-cigarette aerosols in one laboratory (Study 1 inLab A), followed by the interlaboratory assessment of a ref-erence cigarette and e-cigarette in two locations (Study 2 inLab A and Lab D) (Fig. 3).The VC 10s in Lab A (Serial# VC

FIG. 2. The Vitrocell VC 10 Smoking Machine: nicotine measurements were made at source with a Cambridge filter pad(indicated*), undiluted at the point of generation; product D is shown in this case. Dose measurements can also be made at theair–liquid interface (indicated#) with real-time quartz crystal microbalance monitoring or with other analytical quantificationmethods postexposure. Figure adapted from Adamson et al.5

FIG. 3. Experimental design summary:test articles and smoking/puffing regimes forStudy 1 and Study 2.

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 3

10/141209) and Lab D (Serial# VC 10/200410) have beenpart of a previously published interlaboratory in vitro assess-ment study11 and hence have retained their code letters; thisis to be able to link back to previous studies and for inclusionand traceability in this and future comparative studies, wherethe systems will be employed for evaluating NGPs in vitro.

Test article selection and smoking/puffing regimes

One ISO-conditioned reference 3R4F cigarette (Univer-sity of Kentucky) was selected and four e-cigarettes spanningthe evolution of the vapor product category, including simplefirst-generation disposable cig-a-like device, to rechargeablecig-a-like device, closed modular device, and open modu-lar device (Fig. 1 and Table 1). The lower delivery ISO12

and higher delivery HCI13 cigarette smoking regimes wereemployed for the reference product A (Table 1), with onecigarette smoked per run and three replicate experiments.Puffing regimes are described by three numbers that areparamount in determining and controlling aerosol generation–puff volume in milliliters, followed by puff duration in sec-onds, and finishing with puffing interval also in seconds.

Thus, the Health Canada Intense 55:2:30 regime stipulatesthat a 55 mL puff of smoke is taken over 2 s, and this occursevery 30 s after cigarette lighting and taking of the first puff.A smaller puff volume (35 mL) at the same duration (2 s), butwith a longer puffing interval (of 60 s), would be termed35:2:60 and this is the ISO smoking regime. Both ISO andHCI cigarette regimes puff with a bell profile, where theflow rate steadily increases to the specified volume andthen decreases for the duration of the puff (Fig. 3). Squarepuff profiles (Fig. 3) are employed for e-cigarettes as the con-tinuous puff flow ensures that aerosol is being generatedfrom the first moment the puff activates.5

In this study, all e-cigarette products were machine puffedfollowing the CRM No81 regime 55:3:30 (55 mL puff over3 s every 30 s) and with a square puff profile14. In an addi-tional experiment, one e-cigarette (product D) was puffedat the modified HCI regime of 55:2:30 (termed HCIm,where m = modified as there were no filter vents to block, andthe square puff profile is used instead of the bell profile) andthis was to show the effect of varying puff duration on aerosoldelivery. Products B and C were puff activated at their defaultvoltage (not specified on the pack), and products D and Ewere button activated 1 second before puffing to warm thecoil; both of the latter were operated at their highest voltage set-ting of 4 V and 5 V, respectively (Table 1).

Each e-cigarette was vaped for 10 puffs per run, three rep-licate experiments with the same device. Cig-a-like productsB and C were held in the VC 10 mouthpiece perpendicular tothe smoking carousel (as a cigarette would be held). For thelarger devices, which were unable to be held in the VC 10like a cigarette (products D and E), a mouthpiece attachedto the VC 10 syringe was clamped to allow the devices tobe connected at 45� (this was important to avoid dry wickingin these types of devices).

Aerosol generation on the VC 10 and collectionof aerosol at source

The operation of the VC 10 and method employed for cap-turing puff-by-puff aerosol generation at source are based onthose previously discussed.5 Whole aerosol from each prod-uct was trapped by in-line Cambridge filter pad (CFP)(44 mm diameter) pre-syringe, thus no airflow dilution wasrequired. CFPs have been used for decades to determinetotal particulate matter (TPM) yields for cigarettes, and re-cently a study has indicated that nicotine and humectants,

Table 1. The Test Articles and Smoking/Puffing Regimes

Product

A B C D E

Product type Referencecigarette

Cig-a-like disposablee-cigarette

Cig-a-likerechargeablee-cigarette

Closed modularsystem rechargeable

e-cigarette

Open modularsystem tank

deviceLength (mm) 84 84 117 154 98 L · 51 WDiameter (mm) 8 8 9 20 (10 at mouthpiece) 8 (mouthpiece)Nicotine content 0.7–1.9 mg/ciga 4.5% by weightb 1.8% per mLb 1.8% by volumeb

(18 mg/mL)1.8% by volumeb

(18 mg/mL)E-liquid — Rich tobaccob Unspecified Blended tobaccob Blended tobaccob

Puff number 8–10a 300b 250–300 250–300 250–300Puffs assessed 1–8a and 1–10a 1–10 1–10 1–10 1–10Activation

(for e-cigarettes)N/A Puff activated Puff activated Button Button

Regime assessedc ISO and HCI CRM No81 CRM No81 HCIm and CRM No81 CRM No81Puff profile Bell Square Square Square Square

Reference cigarette 3R4F [A]; commercially available first-generation disposable e-cigarette (cig-a-like) [B]; commercially available first-generation rechargeable e-cigarette (cig-a-like) [C]; commercially available second-generation modular e-cigarette (with own cartridge) [D];commercially available open tank device [E].

aDependent on smoking regime used (ISO or HCI).bAs stated on pack.cRegimes assessed are detailed: ISO = 35 mL puff volume: 2-s duration: 60-s intervals. Filter vents open; HCI = 55 mL puff volume: 2-s

duration: 30-s intervals. Filter vents blocked; HCIm = 55 mL puff volume: 2-s duration: 30-s intervals. For NGPs, thus no filter vents; CRM81 = 55 mL puff volume: 3-s duration: 30-s intervals.

NGPs, nicotine products.

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largely residing in the condensed particulate fraction of e-cigarette aerosols, are also captured with an efficiency of>98%.15

A fresh CFP was sealed into a clean holder and installedinto the aerosol transit line as close to the point of generationas possible (Fig. 2). Between puffs, the exposed CFP was re-moved and placed in a clean flask and stoppered; the in-linepad holder was reinstalled with a fresh unexposed CFP andsealed. Thus, we collected emissions on a per puff basisfor the duration of 10 puffs (8 for ISO cigarette). Each prod-uct was smoked/vaped in three independent replicate exper-iments (n = 3/product). Quantification of nicotine from thestoppered flasks containing CFPs was conducted by each lab-oratory’s standard method; each method is described next,with the main differences in nicotine quantification betweenlaboratories listed in Table 2. Differences between nicotineper puff for each product and mean puff nicotine concentra-tion for the same product between laboratories were analyzedusing one-way ANOVA.

Quantification of nicotine in Lab A by ultrahigh-performanceliquid chromatography–triple quad mass spectrometry

Nicotine quantification by ultrahigh-performance liquidchromatography–triple quad mass spectrometry (UPLC-MS/MS) was based on published methods.5,16,17 All CFPsamples in individual stoppered flasks were extracted in20 mL HPLC methanol. Flask samples were spiked withd4-nicotine at a final concentration of 10 ng/mL as internalstandard. Flasks were shaken for 30 min at 180 rpm to extractthe trapped aerosol from the pad. Thereafter, 1 mL extracts(1 mL from each sample flask) were condensed in an Eppen-dorf concentrator for 80 min at 30�C until only a visible me-niscus at the bottom was visible. The condensed sampleswere resuspended in 1 mL of 5% acetonitrile in water, pipet-ted into gas chromatography (GC) vials, and crimped withfoil caps before quantification.

Quantification of nicotine in Lab D by gaschromatography–mass spectrometry

Nicotine was quantified by GC-mass spectrometry (GC-MS). All CFP samples were placed in individual stopperedflasks and were extracted in 10 mL HPLC methanol solution.Samples were spiked with n-heptadecane at a final concen-tration of 50 ng/mL as the internal standard. Flasks were

shaken for 30 min at 180 rpm to extract the trapped aerosolfrom the pad. Thereafter, 1.5 mL extracts were syringe fil-tered through a 0.22-lm membrane directly into an autosam-pler vial and sealed and then analyzed by GC-MS, with aDB-5MS (30 m · 250 lm · 0.25 lm) capillary column. Thefollowing conditions of GC-MS were set: injector tempera-ture 250�C; injection volume 2 lL; split ratio of 10:1; flowrate of 1.0 mL/min; and transfer line temperature 280�C.The capillary column temperatures were as follows: initialtemperature 100�C, hold for 3 min, 8�C/min to 260�C, andhold for 5 min. Electron impact ionization (70 eV) wasused with a 4-min solvent delay. The selected ion monitoringmode was used for determining nicotine (m/z 84) and n-heptadecane (m/z 57).

Nicotine (sample extract) stability shelf life

Solvent extract aliquots (from product D puffed at theCRM No81 regime) produced from Study 1 were takenfrom numerous flasks at random and stored in 1 mL Eppen-dorfs at room temperature and out of direct sunlight. Sampleswere taken at random as it was already proven that there wasno difference between nicotine concentration at any puffnumber from this sample ( p = 0.162, see results later). Atregular intervals, five samples were taken at random fromthe stock of aliquots and analyzed for nicotine using theUPLC-MS/MS method previously described (n = 5). Meas-urements were taken at days 1, 5, 12, 20, 26, 34, 54, 76,and 85 and comparisons made.

Graphics, analysis, and statistics

All raw data were processed in Excel 2016 (Microsoft).Excel was used for all tables, bar charts, and line graphs(Figs. 4A–C, 5, 6, Tables 1 and 2, Appendix Table 1). Box-plots were produced in Minitab� 17.1.0 (Minitab, Inc.)(Figs. 4D, 7, and 8). Differences between puff numbers forthe same product (Figs. 4A–C, 5, and 6) and all productmeans (Fig. 4D) were compared in Minitab with a generallinear model (GLM) ANOVA, non-nested with experimen-tal repeat as a random effect. A GLM was also used tomake cross-comparisons between all combined variables inStudy 2 (interlaboratory comparisons [Fig. 7]).

Bias was calculated as the percentage difference at all puffnumbers between one laboratory (the reference) and theother laboratory. For nicotine stability shelf life (Fig. 8),

Table 2. Nicotine Quantification: Summary of the Differences Between Methods in Lab A and Lab D

Lab A machine A1(serial# VC 10/141209)

Lab D machine D1(serial# VC 10/200410)

Analytical detection method UPLC-MS/MS GC-MSExtraction solvent HPLC methanol HPLC methanolVolume of solvent for CFP extraction (mL) 20 10Internal standard d4-nicotine Heptadecane[Internal standard] for the samples (ng/mL) 10 50Concentration range for calibration (ng/mL) 10–10,000 5–100Points on the calibration curve 10 5Usage of e-cigarette (product B) Same device, three successive runs

(no cooling period between runs)Same device allowed to cool to room

temperature between three runs

CFP, Cambridge filter pad; GC-MS, gas chromatography–mass spectrometry; HPLC, high-performance liquid chromatography; UPLC-MS/MS, ultra high-performance liquid chromatography–triple quad mass spectrometry.

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 5

FIG. 4. Product and smoking/puffing regime comparisons: nicotine generation at source on one VC 10 Smoking Robot.Puff-by-puff analysis of reference cigarette nicotine concentration at the ISO and HCI regime (A); puff-by-puff comparisonof four different e-cigarettes at the same regime (CRM No81) (products B–E) (B); puff-by-puff comparison of the same e-cigarette (product D) at a 2-second (HCIm) and 3-second puffing duration (CRM No81) (C); a boxplot of mean nicotine con-centration per puff for all products/regimes; asterisks denote outliers (D). All products/regimes were repeated three times(n = 3). Bar charts (A–C) display the means – SDs. Boxplots (D) display the mean (central line), the 25th and 75th percentiles(bottom and top lines of box, respectively), and the 5th and 95th percentiles (bottom and top whiskers, respectively). Outlierswere calculated as data points falling outside 1.5 · 25th–75th percentile range; numbers above boxes are the mean values.

FIG. 5. Interlaboratory nicotine at source from a cigarette (product A): puff-by-puff analysis of nicotine concentration atthe ISO and HCI regime in Lab A and Lab D (n = 3).

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repeat measurements up to day 85 were compared using one-way ANOVA of nicotine concentration versus day, with thenull hypothesis that all means were equal, and a significancelevel a = 0.05. One-way ANOVA was selected over GLM asthere was only one variable being measured: the day. Out-liers (shown in Figs. 4D and 7 as asterisks) were calculatedby Minitab as any data point 1.5 · the interquartile (25th–75th) range (Tukey’s method). No outliers were excludedfrom the analyses as there was no recorded justification(such as experimental error) to do so.

Results

Study 1: e-cigarette comparisons

One VC 10 Smoking Robot (Lab A) was designated tolook at the generated aerosol nicotine concentration at sourcefrom a selection of e-cigarettes (products B–E) comparedwith the 3R4F reference cigarette (product A) (Fig. 4 andAppendix Table 1). Mean nicotine concentration for the cig-arette (product A) following the ISO and HCI smoking re-gime was 0.080 – 0.026 mg/puff and 0.193 – 0.055 mg/puff,

respectively. As shown in Figure 4A, the mean nicotine de-livery (mg/puff) increased with each successive puff for thereference cigarettes, and this increase was statistically signif-icant for both the ISO and HCI smoking regimes (GLM,p < 0.001 for both regimes). In addition, Figure 4D showsthat the overall cigarette means (mg/puff) were significantlyhigher for the HCI regime compared with the ISO regime(GLM, p < 0.001), but were both consistent with publishedvalues per stick for ISO and HCI.18

We then investigated the delivery and assessment ofnicotine from a range of e-cigarettes (products B–E).Mean nicotine concentration for product B was 0.112 –0.004 mg/puff and there were no significant differencesbetween puffs 1–10 (GLM, p = 0.708). Mean nicotine con-centration for product C was 0.048 – 0.003 mg/puff andthere were no significant differences between puffs 1–10(GLM, p = 0.204). Mean nicotine concentration for prod-uct E was 0.097 – 0.015 mg/puff and there were statisti-cally significant differences between puffs 1–10 (GLM,p = 0.007), but no differences when puff #1 was omitted(GLM, p = 0.112) (Fig. 4B).

FIG. 6. Interlaboratorynicotine at source from an e-cigarette (product B): puff-by-puff analysis of nicotineconcentration in Lab A andLab D (n = 3).

FIG. 7. Interlaboratory nicotine at source:boxplots showing mean nicotine concentra-tion per puff from the products tested (A, B)in the two laboratories (A and D). Boxplotsdisplay the mean (central line), the 25th and75th percentiles (bottom and top lines of box,respectively), and the 5th and 95th percen-tiles (bottom and top whiskers, respectively).Outliers were calculated as data points fall-ing outside 1.5 · 25th–75th percentile range;numbers above boxes are the mean values.

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 7

As expected, the per puff nicotine concentration meansof all products tested were significantly different fromeach other as they all vary in source nicotine concentrationand have different modes of delivery (GLM, p < 0.001)(Fig. 4D). To assess the impact of puffing duration on e-cigarette aerosol nicotine concentration at source, productD was selected and puffed at 55 mL for 2 s (HCIm) and in an-other experiment at 3 s (CRM No81) at a 30-s puffing inter-val. Mean nicotine concentration was 0.053 – 0.012 mg/puffand 0.069 – 0.006 mg/puff for the 2- and 3-s puff duration,respectively. There were no significant differences betweenpuffs 1 and 10 for 2-s puffing (GLM, p = 0.530) or the 3-spuffing regimes (GLM, p = 0.101) (Fig. 4C); however, themean of 2-second and the mean of 3-second regimes weresignificantly different from each other (GLM, p < 0.001)(Fig. 4D).

Study 2: interlaboratory comparisons

The reference cigarette (product A) was assessed follow-ing the ISO and HCI smoking regimes in Lab A and LabD (Fig. 5). In Lab A, the puff-by-puff range of the cigaretteat ISO (puff 1–8, n = 3) was 0.032 – 0.005–0.109 – 0.014 mg/puff (lowest and highest recorded values, not the first and

last puffs); in Lab D, the puff-by-puff range of the cigaretteat ISO (lowest and highest recorded values between puffs1 and 8, n = 3) was 0.014 – 0.001–0.114 – 0.009 mg/puff(Appendix Table 1). At the ISO regime, there was goodagreement between the two laboratories, particularly atpuff 2 (0.032 and 0.030 mg/puff), puff 3 (0.073 and0.064 mg/puff), puff 7 (0.098 and 0.097 mg/puff), and puff8 (0.109 and 0.114 mg/puff); only puff 1 at ISO showed sub-stantial disagreement between Lab A and Lab D (0.058 and0.014 mg/puff) (Fig. 5, dotted lines).

Bias was calculated by constructing a scatter plot of thevalue differences between Lab A and Lab D against puffnumber with a zero reference line (figure not shown); ISOLab D showed a negative bias of 21% (lower than Lab A).Following the HCI smoking regime, the difference betweenLab A and Lab D was a 21% negative bias again; so, al-though lower at both regimes, it was consistently so. InLab A, the puff-by-puff range of the cigarette at HCI (lowestand highest recorded values between puffs 1 and 10, n = 3)was 0.097 – 0.013–0.259 – 0.034 mg/puff; in Lab D, thepuff-by-puff range of the cigarette at HCI (lowest and high-est recorded values between puffs 1 and 10, n = 3) was0.045 – 0.005–0.225 – 0.031 mg/puff (Appendix Table 1).At the HCI regime, there was still some similarity between

FIG. 8. Nicotine extracts stability overtime. Nicotine extracts from product D at3-second puff duration show no degrada-tion in nicotine days 1–54 (A), but then adecline thereafter up to day 85 (where nofurther measurements were taken) (B);(n = 5). Boxplots display the mean (cen-tral line), the 25th and 75th percentiles(bottom and top lines of box, respective-ly), and the 5th and 95th percentiles(bottom and top whiskers, respectively);numbers above boxes are the meanvalues.

8 ADAMSON ET AL.

laboratories, with the greatest agreement between the twobeing at puff 4 (0.162 and 0.146 mg/puff) and puff 8 (0.249and 0.225 mg/puff) (Fig. 5, solid lines). Independently, the re-gimes were compared between laboratories: the ISO regimein Lab A was compared with the ISO regime in Lab D andthere were statistically significant differences between thetwo (GLM, p < 0.001); a significant difference was also ob-served at the HCI regime (GLM, p < 0.001).

A disposable cig-a-like e-cigarette (product B) was alsoassessed in Lab A and Lab D following the CRM No81 re-gime (55:3:30 square) (Fig. 6). The puff-by-puff range ofthe e-cigarette was much more conserved compared withthe cigarette. In Lab A, the range (lowest and highest recordedvalues between puffs 1 and 10, n = 3) was 0.108 – 0.002–0.115 – 0.004 mg/puff; in Lab D, the puff-by-puff range ofthe e-cigarette (lowest and highest recorded values betweenpuffs 1 and 10, n = 3) was 0.099 – 0.006–0.126 – 0.004 mg/puff (Appendix Table 1). In Lab A, there were no significantdifferences between puffs 1 and 10 (GLM, p = 0.708).

As observed in Figure 6, in Lab D, there was a significantdifference between all puffs due primarily to a lower value atpuff one, which was consistent across the three replicate ex-periments (GLM, p < 0.001). There was no difference, how-ever, between puffs 2 and 10 (GLM, p = 0.848). As observed,there was large agreement between the two laboratories forthe e-cigarette, particularly at puff 3, 5, 7, 9, and 10 wherethey had overlapping standard deviations. Bias was calcu-lated as before: for the e-cigarette, Lab A showed a nega-tive bias of 7% (lower than Lab D).

The mean nicotine concentrations per puff (mean of allpuffs 1–8 or 1–10) for both products in both laboratorieswere compared; product A following the ISO regime was0.080 – 0.026 mg/puff and 0.064 – 0.031 mg/puff for Lab Aand Lab D, respectively; product A following the HCI re-gime was 0.193 – 0.055 mg/puff and 0.149 – 0.054 mg/pufffor Lab A and Lab D, respectively; and product B was0.112 – 0.004 mg/puff and 0.121 – 0.010 mg/puff for Lab Aand Lab D, respectively (Fig. 7 and Appendix Table 1).After single regime/product comparisons between laboratories,a GLM test was applied to assess all interlaboratory variablesfrom Study 2 together. When the three test observations werecombined from both locations (product A following ISO,product A following HCI, and product B [Fig. 7]), laboratorydifferences were not significant ( p = 0.067). Test article andpuff number differences were significantly different fromeach other, as expected. Finally, the interaction of laboratoryand puff number was also not significant ( p < 0.960) (Fig. 7).

Nicotine extract stability was assessed in a shelf life inves-tigation to determine whether nicotine in the samples woulddegrade over time and, if so, how long this would take. Thesame e-cigarette nicotine extracts in methanol were stored inthe dark at room temperature and assessed over a period of85 days. This investigation was intended to support a futuresample cross-check between laboratory methods, thus weneeded to ensure e-cigarette nicotine stability at room tem-perature for as long as it might take to dispatch products be-tween United Kingdom and China (days to weeks).

Five randomized extract samples from the same experi-mental batch of extracts were analyzed at a time in Lab A(product D at 3 seconds) at first at regular weekly intervals,progressing to longer intervals when no difference was firstobserved. Between days 1 and 54, there was no observed sta-

tistical difference in nicotine concentration from the samebatch of samples (one-way ANOVA nicotine versus day,p = 0.985); mean nicotine concentration fluctuated between0.065 and 0.069 mg/puff, with the standard deviation ranging0.002–0.005 mg/puff (Fig. 8A). When five more sampleswere selected for analysis thereafter, on day 76, the nicotineconcentration had dropped significantly to 0.040 – 0.005 mg/puff and confirmed once again on day 85 at 0.038 –0.005 mg/puff (Fig. 8B).

Discussion

Dosimetry plays an important role in understanding thedose delivery of test article aerosols to in vitro cultures dur-ing exposure. There is a key requirement to understand fullyhow the exposure system works to generate, dilute, and de-liver aerosols to in vitro systems. It is, however, paramountto understand fully what the exposure system is generatingat source and delivery to the cells. Use of QCMs can helpto assess the particulate mass deposited as shown in previousstudies.5,11,19,20 Nevertheless, currently, this is an expensiveadd-on for most of the in vitro exposure systems and requiresdedicated software and user training. There is the additionalchallenge of using QCMs with some NGPs, especially e-cigarettes, where the crystal can be overloaded in a veryshort time because of the composition of the aerosol beinggenerated by these products and their high humectant (glyc-erol and propylene glycol) content.

Observations in the laboratory (not shown) generally indi-cate that with e-cigarette aerosols, the crystal will overloadand not read an increase in mass above *80 lg/cm2,which can be achieved in only a matter of minutes (devicepower, e-liquid composition, and aerosol dilution depen-dent). By contrast, with tobacco smoke particle deposition,QCMs can reliably record mass increases for up to 3 hours,where at a diluting airflow of 1 L/min, a final mass of23 lg/cm2 was achieved in 184 minutes.21 QCMs can stilladd value, but they should be used in shorter exposuretimes for product comparisons or for exposure system qualitycontrol purposes in conjunction with the use of reference cig-arettes. A more facile method that can be used across manylaboratories has been investigated in this study and involvesthe assessment of source-generated nicotine extracted froma CFP.

An in vitro aerosol exposure system will generate, dilute,and deliver smoke from cigarettes and aerosols from e-cigarettes (or other NGPs) to cell cultures at the ALI, mimick-ing a physiological exposure condition (for lung models inparticular). Due to the diversity and complexity in typical ex-posure systems, the diversity of NGPs, and their aerosolsbeing tested, one important aspect is to understand the dosim-etry of the test article at source before dilution and delivery tothe cells. As well as understanding the dose delivered to thecultures in vitro, understanding repeatability and variabilityat source and at ALI will help with interpreting biological re-sponse data and maintaining confidence in exposure systemsand their results.

Furthermore, cigarettes and various NGPs cannot be as-sumed to result in comparable aerosol delivery and transferwithin the exposure system due to differences in chemicalcomposition, unless this was confirmed by quantificationor by detailed exposure system characterization.22 In other

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 9

words, with differing product characteristics, the resultsobtained from a given e-cigarette might not read across toother NGPs.23

Interlaboratory studies are another means to gain confi-dence in systems/methods before the method can gainwider acceptance and validation. Such studies are not with-out their own challenges: product variability, operator andenvironmental variability, analytical method differences,and of course the logistics of such tasks across large geo-graphical distances and possible impact on product stability.In this study, we kept the in vitro exposure system (the VC10) and products (one cigarette and one e-cigarette) thesame, but purposefully wanted to investigate the differencesbetween analytical methods for nicotine quantification oncethe test article had been trapped on a CFP.

Study 1: e-cigarette comparisons

The first part of our research examined different NGPcomparisons in one laboratory. The puff-by-puff profile ofnicotine concentration was assessed from one reference cig-arette and four e-cigarettes (Figs. 1, 3, and Table 1). The re-sults demonstrated different profiles between the cigaretteand e-cigarette, as well as different deliveries between e-cigarettes [three e-cigarettes were matched for nicotine con-centration in the e-liquid (products C–E were 1.8%) and onewas higher (product B at 4.5%)] (Table 1 and Fig. 4).

The cigarette showed a distinct profile where the concen-tration of nicotine increased per puff and where HCI deliv-ered higher nicotine than ISO (Fig. 4A). This increasetypically occurs because the tobacco acts as a filter whensmoked, where nicotine will deposit downstream of the cig-arette as the rod is consumed per puff, thus enriching the dis-tillable material, including nicotine, in the latter puffs.5

After the reference cigarette, a range of e-cigarettes weretested, each a major progression in product design evolution(Fig. 1). Product B had the highest concentration of e-liquidnicotine and thus delivered the most nicotine per puff, despitebeing the first-generation cig-a-like device type (Fig. 4B, D).The profiles for products C–E showed increased nicotine de-livery with each product despite the same nicotine concentra-tion of 1.8%; this may be caused by the difference in theiraerosol formation efficiency, rendered by different coil andpower configurations from the rechargeable cig-a-like product(product C), through to the pen-like device (product D) andthen the box-like device (product E).

A final comparison was made looking at nicotine concen-tration for the mean of all puffs per product (Fig. 4D). Clearly,the standard deviation was greater for the cigarette than the e-cigarette in all cases. The cigarette had a distinct and statisti-cally significant difference between the first and last puff asthe rod shortens. Reference cigarettes are usually made in asingle batch (this is the case for the 3R4F) and that is whythey can act as a reference, thus the parallel trend shown inFigure 5 between the two laboratories suggests a systematicbias, which requires further investigation. The e-cigarettes in-vestigated in this study on the other hand comprised four mainingredients (nicotine, flavor, humectant, and water) and there-fore appear to give a more repeatable delivery between puffswhen the device is charged and operated correctly.

Delivery from the same e-cigarette (product D) at differentpuffing durations (2 or 3 seconds) showed a statistically sig-

nificant difference in nicotine delivery (Fig. 4C). With an in-crease of just 1 second longer in the puff, the mean nicotinedelivery increased by 0.016 mg/puff (from 0.053 to 0.069).This information is useful when different regimes areemployed in different studies. The 55:3:30 puffing regime isrecommended for e-cigarette testing (CRM No81), but some-times the 55:2:30 square regime (HCIm) may be employed tomake closer comparison with the HCI smoking regime withcombustible cigarettes (as seen in previous studies5,6,8).

Study 2: interlaboratory comparisons

The second part of the study was the interlaboratory com-parison of nicotine quantification results from a referencecigarette (product A) and a single e-cigarette (product B)on the VC 10 in two laboratories (Lab A and Lab D)(Fig. 3). These laboratories were part of a previous interla-boratory dosimetry study11 and hence retained their code let-ters. This previous study demonstrated that in terms oftobacco smoke particle gravimetric deposition, determinedby QCMs, there was strong agreement between six indepen-dent VC 10 smoking machines: gauge R&r (a statistical mea-sure of the error between VC 10s in different laboratories andthe error within the same VC 10 in a single laboratory) was7.7%, less than 10% overall being considered statistically fitfor purpose.11

Therefore, before even commencing this latest investiga-tion with e-cigarette nicotine concentration at source, wehad confidence that the systems were performing equiva-lently, and perhaps any differences seen would be methodor operator derived. Two different nicotine quantificationmethods were employed, each laboratory using their pre-ferred/approved approach. Lab A utilized UPLC-MS/MSand Lab D utilized GC-MS; all other experimental variableswere the same between laboratories unless described inTable 2.

The interlaboratory results from the cigarette showed theexpected trend in both sets of results, where nicotine deliv-ery increased per puff, and where following HCI deliveredmore than following ISO (Fig. 5). There was variabilityeven within runs, demonstrated by some large standard devi-ations; this was likely due to the puff-by-puff methodemployed, which is a more challenging test to run, hence in-troducing a larger variability than just smoking the wholecigarette and reporting data on a per stick basis. The cigaretteresults between laboratories were different and showed thatLab D was consistently 21% lower than Lab A for themean mg/puff values when following the ISO and HCI re-gimes. However, the overall trend between laboratorieswas the same. The laboratories’ differing nicotine quantifica-tion methods may also be a contributing factor to the ob-served bias; the CFP extraction in 10 mL instead of 20 mLcould have contributed to the different values obtained. Aninterlaboratory cross-check on the same samples (sample ex-change) would help to identify such causes and is the subjectof a future study.

Likely, there are numerous contributing factors (time, op-erator, product, method) and an additional level of variabilityin results would be expected in an interlaboratory study, es-pecially when diverse methods are employed. That said, thedata ranges overlap for both laboratories at both regimes forthe cigarette (Fig. 7).

10 ADAMSON ET AL.

For the e-cigarette (product B), the inverse relationship be-tween laboratories was observed: Lab A was 7% lower thanLab D (Fig. 6), but as discussed before, there was a repeat-able puff profile between runs in the same laboratory and be-tween the laboratories. One noteworthy observation was therepeatedly lower delivery from puff one in Lab D (Fig. 6).This is likely due to some unknown factors that affectedthe performance of the e-liquid cartridge (often referred toas the cartomizer) (Fig. 1).

To deliver efficiently on activation, the device must havewicked sufficient e-liquid and the cartomizer must increasefrom room temperature up to atomization temperature (coilheater temperatures reported as ranging 40–180�C under cor-rect operation24). Wicking will also be dependent on liquidviscosity: viscosity will be lower and therefore wicking slowerat room temperature versus mid run when the cartomizer is upto temperature because the e-liquid will be more viscous andthus wicking will be quicker. These combined factors likelyresulted in the relatively lower concentration of aerosol atfirst puff, but during subsequent puffs, the heating temperatureof the device would be sustained as the interval of 30 secondswould not be enough for cooling back to room temperature.

This observation would be especially prominent when thedevice was allowed to cool between subsequent runs of 10puffs (as was the case in Lab D, but not Lab A). On thisnote, some studies may define a priming of the electronic de-vice, where the first few puffs are wasted to warm the deviceup and allow appropriate wicking. However, if the product isbeing assessed/evaluated in vitro, it might be argued thatthe test article be generated in the same way a consumerwould interact with the product—without priming and in-cluding the first puff. On the other hand, slightly lower de-livery on the first puff for a biological exposure is likelyinsignificant for the in vitro model to discriminate. Compar-ing just the e-cigarette results from both laboratories, statis-tically they were deemed different to each other, and this ispartially due to such tight standard deviations observed ineach laboratory.

When the laboratories were compared on a single product/regime, statistical differences were highlighted (all £0.05).However, when the three test observations were combinedfrom Study 2 (Fig. 7), laboratory differences and the interac-tion of laboratory * puff number were not significant ( p = 0.067and 0.960, respectively).Thus, we concluded that these datashow positive agreement despite geographical, operator, andmethod differences. The main purpose here was to comparedifferent methods employed at the two laboratories, and con-sidering the differences mentioned (Table 2), we believe thedisparity seen between the laboratories is reasonable for afirst comparison of this nature and points out useful areasfor further improvements.

There are associated logistical challenges with interlabor-atory studies, especially with great distance between the two,and thinking about these challenges can help for future stud-ies. Study 2 was designed such that each laboratory wouldanalyze their own generated samples with their own nicotinequantification method; and in future studies such as this, wewould propose a double crossover whereby each laboratorywould analyze and cross-check the other’s samples. In thisway, it would become easier to identify if the observed dif-ferences between laboratories were due to product and prod-uct operation variability (same values obtained from the

same sample analyzed between laboratories) or originatedin method differences (different values obtained in each lab-oratory from the same sample).

This was the main purpose of the shelf life investigation:to provide data to support a future investigation where transittimes between laboratories may take up to one month (Fig. 8).As mentioned earlier, product selection for this study was lim-ited by the availability of the e-cigarette to both laboratorieswithin the time frame of the study. Considering the logisticalchallenges with multisite studies, the e-cigarette shelf life datawill support and help the planning of future studies such asthese. With the learning identified, the authors recommend sam-ple exchange and cross-check studies in the future, along withtesting of different NGPs.

The NGP spectrum will continue to evolve and so weshould not always assume that what is known about a previ-ously tested product will apply to the next category; mostlikely, as demonstrated herein, their aerosols will be formeddifferently and will be compositionally/chemically different(even if only slightly) depending on device power and deliv-ery, e-liquid formulation and nicotine content, and how theproduct is consumed (its puffing regime). Exposure systemsare complex and thorough characterization of new systemscan take some time. More rapid dosimetric assessment ofthe test article composition at generation and then onceagain at the cellular interface once diluted and delivered tothe exposure chamber (planned for future studies) can giveconfidence in a later observed biological response.

For those new to the environment or daunted by systemcharacterization, these small investigations may enable theusers to largely bypass the complexities between generationand exposure (associated with dilution mechanisms, transit,and aerosol loss, for example).

Ultimately, the most important aspects are (in rankingorder) to show what the in vitro culture actually received dur-ing exposure (in terms of a measured marker); demonstratethe test article was generated in a consistent manner at source(as shown in this study); determine what mix of chemicals isbeing generated at source (nicotine and others); demonstratethat the analytical methods used for chemical characteriza-tion are fit for purpose; and then establish a quantitative mea-surement of the most critical markers (e.g., nicotine andother chemical substances at the ALI, depending on theknown toxicological properties of the components). This lat-est interlaboratory study, along with the previously publishedwork investigating dosimetry and characterizing exposuresystems,11,19–22 will add another level of knowledge, reliabil-ity, and assurance in this area.

Conclusions

The in vitro dosimetry results obtained from this studydemonstrated the following:

� Reference 3R4F cigarette delivers different nicotine con-centrations across the two regulatory standard smokingregimes and across puff numbers in accordance withknown smoke formation and delivery mechanisms.

� Nicotine assessment across the tested e-cigarette cate-gories showed consistent delivery of nicotine per puffwithin products and that the method was sensitiveenough to detect different levels of nicotine acrossproducts.

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 11

� Puffing regime affects e-cigarette nicotine delivery par-ticularly puff duration and puff flow profile.� Interlaboratory assessment of nicotine generated at

source from an e-cigarette and a cigarette in two loca-tions with different analytical quantification methodsshowed the following mean values were obtained:

B Cigarette at ISO = 0.080 – 0.026 (Lab A) and 0.064 –0.031 mg/puff (Lab D).

B Cigarette at HCI = 0.193 – 0.055 (Lab A) and 0.149 –0.054 mg/puff (Lab D).

B E-cigarette at CRM No81 = 0.112 – 0.004 (Lab A)and 0.121 – 0.010 mg/puff (Lab D).

� Good overlap in nicotine results obtained in two labora-tories utilizing different methods for nicotine quantifica-tion when all interlaboratory variables were combined ina GLM, and the laboratory differences and the interactionof laboratory * puff number were not statistically signif-icant ( p = 0.067 and 0.960, respectively).� Nicotine extracted in methanol solvent (from the

e-cigarette used in this study) was stable at room tem-perature up to 54 days; but after 76 days, measuredconcentrations were *40% lower than the originalvalue. This will aid experimental design for future inter-laboratory studies.

Acknowledgments

The authors would like to acknowledge and thank OscarCamacho, Graham Errington, Chuan Liu, Jessica Mushonga-nono, Andrew Baxter, Carl Vas, and Martin Mullin for theircontributions at BAT; and M&J for procuring a U.S. marketplace e-cigarette for testing in Southampton, United Kingdom.

Author Contributions

J.A., D.T., and X.L. conceived the study. J.A. performedthe experimental work at BAT, analyzed all of the data,and drafted the manuscript; X.L. and H.C. conducted the ex-perimental work at ZTRI. F.X. and M.G. reviewed the col-lected data, the data analysis, and the drafted manuscript.All authors read and approved the final manuscript.

Author Disclosure Statement

The authors declare that there are no conflicts of interest.All of the authors are full-time employees of British Ameri-can Tobacco or the Zhengzhou Tobacco Research Institute ofCNTC.

References

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12 ADAMSON ET AL.

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Address correspondence to:Jason Adamson, BSc

British American TobaccoR&D

Southampton SO15 8TLUnited Kingdom

E-mail: jason_adamson@bat.com

(Appendix follows /)

E-CIGARETTE NICOTINE QUANTIFICATION IN VITRO 13

Appen

dix

Ta

ble

1.

Pu

ff-by

-P

uff

So

urce

Nico

tin

eD

ata

fro

mA

ll

Pro

du

cts

in

Bo

th

La

bo

ra

to

ries

Puff

Pro

duct

A(I

SO

)P

roduct

A(H

CI)

Pro

duct

BP

roduct

CP

roduct

D(2

s)P

roduct

D(3

s)P

roduct

E

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Nic

oti

ne

(mg/p

uff

)SD

Lab

A 10.0

58

0.0

06

0.0

97

0.0

13

0.1

12

0.0

06

0.0

50.0

03

0.0

55

0.0

06

0.0

57

0.0

09

0.1

21

0.0

06

20.0

32

0.0

05

0.1

35

0.0

21

0.1

13

0.0

03

0.0

49

0.0

01

0.0

56

0.0

19

0.0

69

0.0

06

0.0

95

0.0

04

30.0

73

0.0

19

0.1

56

0.0

17

0.1

12

0.0

05

0.0

48

0.0

02

0.0

52

0.0

12

0.0

71

0.0

08

0.1

08

0.0

13

40.0

82

0.0

06

0.1

62

0.0

17

0.1

14

0.0

04

0.0

46

0.0

02

0.0

48

0.0

13

0.0

71

0.0

02

0.0

88

0.0

19

50.0

94

0.0

12

0.1

93

0.0

18

0.1

15

0.0

04

0.0

46

0.0

02

0.0

54

0.0

17

0.0

69

0.0

04

0.0

93

0.0

08

60.0

95

0.0

09

0.2

15

0.0

08

0.1

11

0.0

02

0.0

47

0.0

04

0.0

54

0.0

17

0.0

69

0.0

02

0.0

92

0.0

21

70.0

98

0.0

06

0.2

27

0.0

03

0.1

09

0.0

07

0.0

47

0.0

02

0.0

53

0.0

15

0.0

70.0

07

0.0

96

0.0

16

80.1

09

0.0

14

0.2

49

0.0

30.1

12

0.0

03

0.0

50.0

03

0.0

56

0.0

14

0.0

68

0.0

07

0.0

94

0.0

08

9—

—0.2

37

0.0

23

0.1

08

0.0

02

0.0

49

0.0

05

0.0

56

0.0

13

0.0

73

0.0

03

0.0

99

0.0

06

10

——

0.2

59

0.0

34

0.1

12

0.0

06

0.0

45

0.0

02

0.0

48

0.0

14

0.0

71

0.0

06

0.0

83

0.0

1M

ean

0.0

80.0

26

0.1

93

0.0

55

0.1

12

0.0

04

0.0

48

0.0

03

0.0

53

0.0

12

0.0

69

0.0

06

0.0

97

0.0

15

Lab

D 10.0

14

0.0

01

0.0

45

0.0

05

0.0

99

0.0

06

20.0

30.0

06

0.1

01

0.0

09

0.1

23

0.0

06

30.0

64

0.0

03

0.1

13

0.0

14

0.1

21

0.0

09

40.0

59

0.0

06

0.1

46

0.0

16

0.1

25

0.0

05

50.0

71

0.0

06

0.1

32

0.0

10.1

25

0.0

09

60.0

71

0.0

03

0.1

81

0.0

17

0.1

26

0.0

04

70.0

87

0.0

17

0.1

73

0.0

17

0.1

24

0.0

08

80.1

14

0.0

09

0.2

25

0.0

31

0.1

24

0.0

04

9—

—0.1

62

0.0

36

0.1

21

0.0

11

10

——

0.2

10.0

16

0.1

21

0.0

13

Mea

n0.0

64

0.0

31

0.1

49

0.0

54

0.1

21

0.0

1

14