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Public Health Consequences of E-Cigarettes (2018)

Chapter: 3 E-Cigarette Devices, Uses, and Exposures

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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
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Suggested Citation:"3 E-Cigarette Devices, Uses, and Exposures." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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3 E-Cigarette Devices, Uses, and Exposures CHARACTERISTICS OF E-CIGARETTE DEVICES Electronic cigarettes are a diverse group of products that produce a heated aerosol, typically containing nicotine, which users inhale via a mouthpiece. E-cigarettes range widely in design, appearance, and complexity, but generally contain similar components and operate in a similar manner (Brown and Cheng, 2014). Common components of e-cigarettes include a battery, heating coil, atomizer that transforms the e-liquid to an aerosol, cartridge that contains the e-liquid, and mouthpiece. Each component has the potential to affect health outcomes independently. They may also interact to create an influence different from the sum of their individual parts, posing a challenge for research in this field. The basic operation of e-cigarettes generally follows several steps and includes drawing on the e-cigarette, activation of a heating element, which aerosolizes the contained liquid, and inhalation of the liquid aerosol. Currently a diverse and non-standardized terminology is used to refer to e-cigarette devices, their components, and their use. Terms used differ in non-systematic ways, often simply due to user preference. This non-standard nomenclature presents a key challenge for e-cigarette product surveillance and examining patterns of use (Alexander et al., 2016). Appendix C lists some commonly used terms related to e-cigarette devices and their use, along with their definitions. The e-liquids typically contain nicotine, flavorings, and a humectant. The health effects of nicotine are well documented, although much remains unknown about the specific health effects of nicotine when delivered as an aerosol as compared with a constituent in combusted smoke. Many of the flavoring constituents have been thoroughly evaluated for safety when included in food, but their effects when they enter the bloodstream through the lungs are less well known. Similarly, much remains unknown about the effects of inhaling aerosolized humectants such as propylene glycol and glycerol. Chapter 5 presents a comprehensive discussion on the toxicology of e-liquid constituents and other contaminants found in e-cigarette aerosols. The battery design and type may put the device at risk for a fire or in rare cases for an explosion, and in combination with the heating coils, the battery also influences the aerosol properties (discussed in more detail in the following paragraph). The majority of e-cigarette devices are powered by a rechargeable battery (a manufacturer-supplied unit), a non- 3-1 PREPUBLICATION COPY: UNCORRECTED PROOFS

3-2 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES rechargeable battery, or a user-replaceable battery (rechargeable or non-rechargeable). Portable chargeable carrying cases are available for remote e-cigarette charging for some brands. Nickel- cadmium (NiCad), nickel metal-hydride (NiMh), lithium ion (Li-ion), alkaline and lithium polymer (Li-poly), and lithium manganese (LiMn) batteries may be used to power e-cigarettes (Brown and Cheng, 2014). Many e-cigarettes use lithium batteries because they can store a large amount of energy in a compact space. However, the inherent characteristics of lithium batteries can pose a risk of fire and explosion. Poor design, use of low-quality materials, manufacturing flaws and defects, and improper use and handling can all contribute to a condition known as “thermal runaway,” whereby the internal battery temperature can increase to the point of causing a battery fire or even an explosion. The use of overcharging protection circuits, thermal power cut-offs, and internal overpressure relief mechanisms can help prevent and mitigate thermal runaway. The heating coils and atomizer influence the aerosol properties, and therefore potential health effects. When aerosolization settings are not optimal (e.g., when the heating power is too high), it creates a negative sensation called a “dry hit” in users. This unpleasant sensation may be related to the formation of thermal decomposition by-products of propylene glycol and glycerol, including toxic carbonyl compounds (Farsalinos et al., 2015b; Geiss et al., 2016). Of note, nicotine undergoes pyrolytic degradation at temperatures above 600ºC (Schmeltz et al., 1979), which no studies on e-cigarettes have reported reaching, so the potential pyrolytic degradation of nicotine is very unlikely in e-cigarettes. The amount of power applied to the atomizer also affects the mass of aerosol produced from the e-cigarette device, with more power typically creating denser aerosol per puff (Gillman et al., 2016). The characteristics of the heating coils and atomizer can be customized by users. They may add more coils and/or lower the standard resistance of the heating coils to generate more heat and create denser aerosols. In some devices it is possible for e-liquids to come into direct contact with the heating coils in a process known as “dripping,” which may introduce metals and other constituents into the aerosol that users inhale. Classification of E-Cigarettes For the purpose of this report, e-cigarette devices are classified as first, second, and third generation based on their product characteristics and operational features. Figure 3-1 shows typical first, second, and third generation e-cigarette devices. First generation devices refer to e-cigarettes devices designed to mimic the smoking experience as close as possible. These products served as stand-ins for cigarettes among users who wished to quit smoking or sought out an alternative product to a cigarette. First generation e-cigarettes are often designed to look like a combustible tobacco cigarette, but some are designed to simulate a cigar or pipe. They are also called cigalikes (cig-a-likes) or “vape sticks.” Other cigalikes are slightly longer or narrower than a combustible tobacco cigarette (so called “pen style”). Second generation e-cigarettes are characterized by a clearomizer—a transparent cartridge that holds e-liquid and an atomizer—and a thin battery. Second-generation devices include products that are shaped like pens, are comparatively larger and cylindrical, and are often referred to as “tank systems” in reference to the transparent reservoir that holds larger amounts of e-liquid than previous cartridge-containing models. PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGAR RETTE DEV VICES, USES AND EXP S, POSURES 3-3 FIGURE 3-1 First, sec cond, and thir generation e-cigarette de rd evices. Third generat T tion devices represent a diverse set o products a represen the greates d of and nt st departure from comb e bustible toba acco cigarette Often the devices a advertise as “vaping es. ese are ed g” products and the asso ociated mark keting makes no referenc to cigarett (Zhu et a 2014). s ce tes al., Aestheticcally they be little rese ear emblance to cigarettes, a many are s as square or recctangular and feature cu ustomizable and rebuild dable atomize and batte ers eries. In addiition, since t beginning of the the availa ability of e-c cigarettes an their comp nd ponent parts , users have been modifyfying the devvices or buildin their own devices, wh are ofte referred to as “mods.” The differe ng n hich en o ” ences in desi ign and enginneering of th products are key facto in the siz distributio and amount of aerosol he a ors ze, on, particles. The variabi . ility in levels of chemica and nicot present i the e-liqu als tine in uid/aerosol determin the compo ne osition of the aerosol delivered to the user (Brow and Chen 2014). e e wn ng, ARETTE U E-CIGA USE The basic ope T eration of e-c cigarettes geenerally follo several steps. First, the user dra ows aws upon the e-cigarette. Then, a user either manually presse s a switch bu r utton to activate a heatin ng element, or draws up the e-cig pon garette and an airflow sen n nsor automaatically activa it. In ates automatically activat devices, the airflow sensor detect pressure c ted t s ts changes and prompts the e flow of power to a he p eating eleme and (optionally) an L ent LED. The e-l liquid contaiined in the d device saturates a wick via capillary acti which th heating e lement then aerosolizes. This proces is c ion, he . ss commonly called “va aporization.” Aerosolize droplets o f liquid subs ” ed sequently flo into the u ow user’s mouth an are inhale into the lu nd ed ungs. Althou e-cigaret use is com ugh tte mmonly refe erred to as vaping, technically th device em and the user inhales an aerosol, composed o a suspension of he mits u of a mixture of gases, vapors, and aqueous parti e a icles, and no a vapor, w ot which is a sub bstance in gaas phase. Th exposure of a user to potentially hazardous ch he h hemicals deppends on how the user w inhales th aerosol, th physical characteristi of that ae he he c ics erosol, where the aerosol ends up in the e l respirator tract, and the concent ry d tration of tox xicants in the aerosol at d e different loccations in the e respirator tract. The following sections review informat ry e s tion about ho to assess those expos ow s sures PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

3-4 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES and illustrative results from the literature. The pharmacology and toxicology of those exposures is discussed in Chapters 4 and 5. Puff Topography For combustible tobacco cigarettes, smoking is understood to be a complex process that allows smokers to titrate their desired dose of nicotine and nicotine brain level on a puff-by-puff basis. The intake of nicotine during smoking depends on what are referred to as topography variables, such as puff volume, the depth of inhalation, the rate of puffing, and the intensity of puffing, as well as the extent of smoke dilution with room air (Hukkanen et al., 2005). Puffing patterns influence nicotine intake and exposure to hazardous substances in tobacco smoke. Similarly, puffing behavior or topography may also be an important determinant of nicotine intake and exposure to potentially toxic substances in e-cigarette aerosol, with implications for disease risks. (An examination of the relationship between puff topography and nicotine exposure in e-cigarette users is presented in Chapter 4.). Furthermore, understanding user puff topography is also useful to inform animal, in vitro, and machine-based studies of e-cigarette aerosol exposures that are relevant to human exposures. Fourteen studies were identified that which described e-cigarette puffing topography. A summary of the studies is presented in Table 3-1, including the e-cigarette(s) used, nicotine concentration of the e-liquids consumed, study population (whether experienced e-cigarette users or e-cigarette–naïve smokers), the study conditions and vaping protocol, and averages of vaping topography variables. The methods or instruments used to measure e-cigarette puffing topography varied across studies. Four of the studies used a modified Clinical Research Support System (CReSS Pocket, Borgwaldt Ltd., Germany) (Behar et al., 2015; Goniewicz et al., 2013; Lee et al., 2015; Norton et al., 2014). Three studies from one research group used a device developed and manufactured by collaborators at the American University of Beirut (Lopez et al., 2016; Spindle et al., 2015, 2017). Two other studies, led by the same author, used a wireless Personal Use Monitor (wPUM) designed by researchers at Rochester Institute of Technology (Robinson et al., 2015, 2016). Other studies used video recordings (St.Helen et al., 2016a), an e-cigarette that tracks puff number and puff duration (eVic) (Dawkins et al., 2016; Farsalinos et al., 2015a), or a modified SA7 (British American Tobacco [Investments]) (Cunningham et al., 2016). Differences in instruments/methods of measurement likely introduce variability among study findings. One question of interest is whether e-cigarette puffing topography is comparable to that of combustible tobacco cigarette use. Three studies examined this question. Norton and colleagues (2014) conducted a pilot study to examine initial reactions to e-cigarette use and puffing behaviors among combustible tobacco cigarette smokers. Puffing topography was measured on day 1 while participants smoked a combustible tobacco cigarette and about 24 hours later during ad libitum (ad lib) use of a first generation e-cigarette. Participants had been asked to use the e-cigarette exclusively over the previous 24 hours. The study found that e- cigarette–naïve smokers (n = 18) took more puffs when smoking a combustible tobacco cigarette, but per-puff volume, flow rate, and peak flow rate were significantly higher with e- cigarettes; puff duration was not significantly different. The relatively short period of e-cigarette use (~24 hours) before the lab session was likely inadequate to stabilize e-cigarette puffing behavior; the findings may not be generalizable to experienced e-cigarette users. Spindle and colleagues measured puffing topography of 13 experienced second generation e-cigarette users during a 10-puff session in which puffing characteristics such as duration were not standardized PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-5 (Spindle et al., 2015). The authors compared the findings with a previously published study on combustible tobacco cigarette smokers (Kleykamp et al., 2008). By comparison, experienced e- cigarette users took larger volumes per puff and longer puffs, but flow rate with e-cigarettes was lower. Given that these comparisons are not within subject, the findings should be treated cautiously. In another study, Strasser and colleagues measured puff topography of combustible tobacco cigarette smokers who switch to first generation e-cigarettes (Strasser et al., 2016). Puff topography when smoking one combustible tobacco cigarette was measured on the first day and e-cigarette puff topography was measured on days 5 and 10 during a 10-minute ad lib session. The number of puffs taken did not differ when smoking the combustible cigarette compared with using the e-cigarettes. However, puff duration increased with e-cigarette use while interpuff interval decreased. Because the study used video analysis, other variables such as puff volume and flow rate were not reported. Based on these three studies, it appears that puff duration is longer and puff volume larger with e-cigarette use compared with combustible tobacco cigarette use. The findings on flow rate were less consistent. Another question is whether e-cigarette puffing topography of experienced users differs from that of e-cigarette–naïve users. In other words, does puffing topography change as e- cigarette–naïve users gain experience with e-cigarettes? Four of the studies enrolled e-cigarette– naïve combustible tobacco cigarette smokers, nine studies enrolled experienced e-cigarette users, and one enrolled both groups. Farsalinos and colleagues compared the number of puffs taken and puff duration between 24 experienced e-cigarette users and 23 e-cigarette–naïve users (Farsalinos et al., 2015a). Participants were given a second generation e-cigarette (eVic by Joyetech) and were asked to take 10 puffs in 5 minutes followed by 60 minutes of ad lib use. The number of puffs and puff duration were recorded by the e-cigarette (eVic by Joyetech). The study found that while the number of puffs taken during the 65-minute period did not differ between the two groups, experienced e-cigarette users took significantly longer puffs than the e- cigarette–naïve users. Two studies examined changes in puffing topography in e-cigarette–naïve combustible tobacco smokers over time. Lee and colleagues (2015) found that puff duration increased and puff flow rate decreased significantly after e-cigarette–naïve smokers (n = 20) used a first generation e-cigarette for one week compared with baseline (first use of the e- cigarette); these differences were sustained after 2 weeks of e-cigarette use (Lee et al., 2015). Strasser and colleagues (2016) reported similar average number of puffs, puff duration, and interpuff interval during a 10-minute ad lib session 5 and 10 days after switching from combustible tobacco cigarettes to e-cigarettes. Based on Table 3-2, in general, puff duration appears to be longer among experienced e-cigarette users (range of means: 1.8 to 5.29 seconds) compared with e-cigarette–naïve users (range of means: 1.64 to 3.0 seconds). Puff volume also appears to be larger with experienced e-cigarette users (range of means: 51.0 to 148.5 ml) compared with e-cigarette–naïve users (range of means: 63.0 to 118.2 ml). A third question is whether e-cigarette device characteristics influence puffing topography. Device characteristics include the type of e-cigarette (first generation versus advanced models), voltage or power, and nicotine strength of e-liquids. In one study, Cunningham and colleagues (2016) assigned experienced e-cigarette users to either a first generation device (Vype Reload, Classic Flavour Bold containing 4.5 percent nicotine by volume) (n = 32) or to a button-activated, variable voltage e-cigarette that uses pre-filled cartridges containing e-liquid (Vype ePen with 3.0 percent nicotine by volume) (n = 28). Vaping topography was measured during ad lib sessions of self-determined durations during two lab visits. Participants used the same devices during each visit, but those with the variable-voltage PREPUBLICATION COPY: UNCORRECTED PROOFS

3-6 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Vype ePen alternated between a low or high voltage during each visit. No significant differences in puff topography were reported between different days of use of the first generation e-cigarette or voltage of the advanced-model e-cigarette. However, compared with the first generation e- cigarette (Vype Reload), average number of puffs taken was fewer, average puff volume was larger, mean interpuff interval was longer, and mean peak flow rate was higher with the advanced-model e-cigarette. These findings suggest that e-cigarette puffing topography is different among types of e-cigarettes. One likely explanation is the difference in power between types of devices, as more advanced e-cigarettes are operated at higher power (voltage) than first generation e-cigarettes. However, this study found no differences in topography variables when the same participants switched between low and high voltage (the exact voltages were not stated), implying that, while plausible, power did not influence vaping topography in this study. Another plausible explanation for differences in puffing topography among types of devices is the nicotine concentration of the e-liquid. The first generation had higher nicotine concentration compared with the second generation e-cigarette. Lopez and colleagues (2016) examined the effect of e-liquid nicotine concentration on puffing topography. Sixteen e-cigarette–naïve smokers crossed over among second generation e- cigarettes with 0, 8, 18, and 36 mg/ml nicotine over 4 days. Participants engaged in two 10-puff sessions in which puff parameters were not standardized. Puff volume and puff duration tended to decrease with increasing nicotine concentration, while there was no clear trend with flow rate. In a similar study, Dawkins et al. (2016) found that experienced e-cigarette users took fewer and shorter puffs at high nicotine concentration (24 mg/ml) compared with low nicotine concentration (6 mg/ml) over a 60-minute period of ad lib access to a second generation e- cigarette. Based on these studies, it appears that nicotine concentration of the e-liquid used is a major determinant of e-cigarette puffing topography (Cunningham et al., 2016; Dawkins et al., 2016; Lopez et al., 2016). Most of the studies (12 of 14) measured puffing topography in controlled environments, where puffing behavior may or may not represent e-cigarette use behavior in the “real world.” Two observational studies characterized puffing topography of experienced e-cigarette users of first generation devices in their naturalistic environments. In the first study, Robinson and colleagues (2015) described puffing topography of e-cigarette users over a 24-hour period. Participants (n = 21) were given a day’s supply of blu rechargeable e-cigarettes (a first generation device), which was used in conjunction with a wPUM (Robinson et al., 2015). Average puff duration, flow rate, and puff volume were within the range of reported values from studies of experienced e-cigarette users in controlled environments (see Table 3-1). In addition, the researchers identified what they characterized as three representative puff topographies: “many short” puffs (1.4 second puff duration); “typical” puffs (3.7 second puff duration); and “fewer long” puffs (6.9 second puff duration). The average number of puffs taken was 225 (SD, 272). Given that the study enrolled only users of first generation e-cigarettes, the findings may not be generalizable to users of more advanced models. Robinson and colleagues (2016) conducted a second observational study of experienced first generation e-cigarette users in their naturalistic environment, but over a 7-day period. Participants (n = 20) used their usual e-cigarettes in conjunction with the topography device (wPUM). Average puff duration was at the lower end of the range of values observed among experienced e-cigarette users in controlled settings and also lower than the first study by Robinson and colleagues (2015). Three groups of puffs based on duration were identified: “short” puff duration (1.8 seconds); “moderate” puff duration (2 seconds); and “long” puff PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-7 duration (2.5 s). These groups were different from the three representative topographies identified in the first study. In addition, the study found that participants engaged in an average of 6 distinct vaping sessions (activation of a wireless personal use monitor, taking puffs, and turning the device off) per day, and took an average of 78 puffs per day. The average number of puffs taken per day was drastically lower than the average number of puffs taken per day in the first study. The lower number of puffs per day in the 7-day study compared with the 1-day study likely reflects variability in use patterns among days within subjects. In addition, it was uncertain to what extent participants complied with the study protocol by using the wPUM for every puff taken. Although studies of e-cigarette users in their naturalistic environments may offer realistic information on user behaviors, compliance with study protocol cannot be guaranteed, thus limiting the reliability of study findings. In summary, puffing topography seems to differ between users of e-cigarettes and combustible tobacco cigarettes. E-cigarette users tend to take puffs of longer duration and large volume. Furthermore, puffing topography changes as e-cigarette–naïve users become more experienced. Puff duration and puff volume increase with experience. Also, device characteristics such as type of device (first generation versus advanced models) and nicotine strength of e-liquids influence puffing topography. Number of puffs taken and puff duration tend to decrease as nicotine strength of the e-liquid increases. Finally, puffing topography of experienced e-cigarette users measured in their naturalistic environment were in the range of values measured in experienced users in controlled settings. EXPOSURE TO AEROSOLS AND PARTICULATES E-cigarette aerosol is best described as a mist, which is an aerosol formed by the condensation of spherical liquid droplets in the submicrometer to 200 m size range. Methods for particle measurement have included spectral transmission using an electrical mobility analyzer. Pratte and colleagues (2016) used a light scattering methodology for droplet sizing of e-cigarette aerosols. Yet others have used the cascade impactors to determine the mass of various particle sizes. Ingebrethsen and colleagues (2012) demonstrated particle size distribution of aerosols produced by electronic cigarettes in an undiluted state using a spectral transmission procedure after high dilution with an electrical mobility analyzer. They found particle diameters of average mass in the 250-450 nm size range with particle number concentrations of 109 particles/cm3. These measurements are comparable to those observed for combustible tobacco cigarette smoke in prior studies and also measured in the current study with the spectral transmission method and with the electrical mobility procedure. Total particulate mass for the e-cigarettes calculated from the size distribution parameters measured by spectral transmission were in good agreement with replicate determinations of total particulate mass by gravimetric filter collection. By contrast, average particle diameters determined for e-cigarettes by the electrical mobility method were in the 50 nm range, and total particulate masses calculated based on the suggested diameters are orders of magnitude smaller than those determined gravimetrically. These small particle diameters observed are thought to arise from e-cigarette aerosol particle evaporation at the dilution levels and conditions of the electrical mobility analysis. By contrast, a smaller degree, approximately 20 percent by mass, of particle evaporation has been observed for combustible tobacco cigarette smoke. PREPUBLICATION COPY: UNCORRECTED PROOFS

3-8 PUBLI HEALTH CONSEQU IC H UENCES OF E-CIGARET TTES Alderman and colleagues (2014) did follow-up st A d s tudies using a cascade im mpactor to determin particle siz distributio by collect ne ze on ting eight pu total (four per e-ciga uffs arette) with a 30- second innterpuff inter rval. Three e-cigarette brands were e e b evaluated. E E-cig 1 and EE-cig 2 were both rechargea models, with cartom able mizer type caartridges, wh the E-cig 3 was a disposable mo hile odel. All compponents were connected by conductiv silicone r e ve rubber tubing to minimiz particle lo g ze oss during sa ampling. Fig gure 3-2 pressents the repr resentative iimpactor-col llected data, namely a mmass frequency distributio curve and correspondi lognorm fit to the d y on ing mal data, as well as the l corresponnding cumul lative mass distribution. The data pr d rovided in Fiigure 3-2 are for E-cig 1 and e are generrally representative of ea e-cigaret brand sam ach tte mpled. Figur 3-2 indica that re ates essentiall all (95 per ly rcent) aeroso mass is co ol onfined to th particle siz range of 2 he ze 280-1,420 nm m. Further analysis of th particle si distributi from the cascade imp a he ize ion pactor analy is shown in ysis n Table 3-1 Further an 1. nalysis demo onstrated the particle size distribution represente by the mass e e n ed median aerodynamic diameter an count mea diameter, although he a c nd an , eterogeneous in size, are all e highly re espirable throoughout the respiratory tract. t FIGURE 3-2 Mass fre equency and cumulative mass distributio derived fr c m ons from impactor particle size r e distributio measureme of e-cigar on ent rette 1. NOTE:Th data shown here are repr he n resentative of each e-cigar f rette brand ev valuated. SOURCE Alderman et al., 2014 E: e . TABLE 3-1 Particle Size Distributi Parameter Determined from Casca Impactor A 3 ion rs d ade Analysis E-cig MMAD (nm) D CMD (nm m) GSD Pu mass (mg/p uff puff) 1 631 319 1.50 2.1 16 2 487 262 1.52 3.0 07 3 534 261 1.52 1.9 95 NOTE: CMD = count mean diamete GSD = geometric stand m er; dard deviation MMAD = m mean n; mass aerodynam diameter. mic . SOURCE Alderman et al., 2014. E: e PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-9 Table 3-1 is a particle size summary for all products evaluated in the Alderman and colleagues (2014) study. The particle size distribution parameters in Table 3-1 are derived by fitting the mass frequency data to a lognormal function. In addition, the puff mass in Table 3-1 is based on the cumulative mass of particulate matter collected on the various impactor stages. Both curves from Figure 3-2 indicate that essentially all (95 percent) aerosol mass is confined to the particle size range of 280-1,420 nm, or in other words highly respiratory within the respiratory tract. Fuoco and colleagues (2014) found similar findings with different types of e-cigarettes, while also showing the total particle number concentration peak (using a 2-second puff), averaged across the different electronic cigarette types and liquids, at 4.4 ± 0.4 × 109 particles/cm3, compared with the combustible tobacco cigarette 3.1 ± 0.6 × 109 particles/cm3. Puffing times and nicotine contents were found to influence the particle concentration, whereas no significant differences were recognized in terms of flavors and types of combustible tobacco cigarettes used. Particle number distribution modes of the electronic cigarette-generated aerosol were in the 120-165 nm range. Marini and colleagues (2014) further confirmed similar particle concentrations. This striking contrast in particle size between Alderman and Fuoco might suggest the generation of different particle sizes due to the wattage and temperature used to generate the e-cigarette aerosol, as well as possible differences in e-cigarette composition. Ji and colleagues (2016) generated and characterized e-cigarette aerosols using advanced technologies. In the gas phase, the particle number concentration (PNC) of e-cigarette aerosols was found to be positively correlated with puff duration, whereas the PNC and size distribution may vary with different flavors and nicotine concentration. In the liquid phase (water or cell culture media), the size of e-cigarette aerosol particles appeared to be significantly larger than those in the gas phase, which might be due to aggregation of aerosol particles in the liquid phase. While the particle count in e-cigarette aerosols may not be substantially different than main stream combustible tobacco smoke, the nature of the particles is substantially different. E- cigarette aerosol particulate consist largely of aqueous droplets and vapors of humectants, either propylene glycol or glycerol, whereas particulate matter in combustible tobacco smoke are complex, largely organic constituents that contain polyaromatic hydrocarbons and a variety of other known or suspected carcinogens. Thus, it would be incorrect to assume that the long term health risks of the two aerosols were similar just because particle count was similar. Particle Deposition Deposition by e-cigarette vaping within the human respiratory tract is essential to better understand the biological dosing of gases, aerosols, and aqueous particles generated during e- cigarette use. To address particle dosing, Pichelstorfer and colleagues (2016) implemented the Aerosol Dynamics in Containments (ADiC) model to describe the dynamic changes of both inhaled combustible tobacco cigarette smoke as well as aerosols generated by e-cigarette vaping. The model involved particles present during puf ng, mouth-hold, inspiration, and expiration. The authors included consideration of coagulation, phase transition, conductive heat and diffusive/convective vapor transport, as well as dilution/mixing into a single-path representation of the stochastic lung dosimetry model IDEAL (Inhalation, Deposition and Exhalation of Aerosols in the Lungs) to compute particulate phase deposition as well as vapor phase deposition in the airway generations of the human lung. The ADiC model applied to the inhalation of combustible and electronic cigarette aerosols is a means to understand those aerosol dynamics processes that influence the physical PREPUBLICATION COPY: UNCORRECTED PROOFS

3-10 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES properties of the particle and vapor phases in the human respiratory tract with the following observations: (1) reduced inhaled aerosol particle number is caused primarily by coagulation and less by deposition for both types of aerosols; (2) hygroscopic growth rates are higher for e- cigarettes than for combustible tobacco cigarettes; (3) the effect of particle growth on deposition leads to a lower total deposition in the case of combustible tobacco cigarette smoke particles and a higher total deposition in the case of e-cigarette droplets relative to their initial size distributions; and (4) most of the nicotine is deposited by the vapor phase for both aerosols (Pichelstorfer et al., 2016). Because of the complexity of the model and the resulting extensive computational time, Pichelstorfer and colleages used a single-path version of the IDEAL airway geometry. Average airway dimensions for each airway generation were derived for the particle and vapor transport in the lungs, while average deposition fractions for each airway generation were based on the full stochastic deposition model. Figure 3-3 illustrates the number/size distribution of inhaled particles of combustible tobacco cigarette smoke (panel A) and e-cigarette droplets (panel B) across time. These time points include after puffing, mouth-hold, inhalation, and exhalation phases. The figure shows most particles in both aerosols are removed after the puffing and mouth-hold stages, eliminating initial size distribution disparities between the two aerosols (Fuoco et al., 2014). This can largely be attributed to coagulation, which decreases particle concentration and increases particle diameter. For example, nicotine is almost eliminated in the alveolar region (as seen in that peak’s split in panel B). Evaporation of water and glycerol in smaller e-cigarette particles also occurs in the mouth during the puffing and mouth-hold periods (as shown in the peak of particles near 40 nm in panel B). Size-selective deposition by Brownian motion in the lungs and hygroscopic growth, which becomes greater as particle size increases (Winkler-Heil et al., 2014), remove additional particles in the respiratory tract. These three processes (coagulation, size-selective deposition, and hygroscopic growth) result in particles with larger diameters by the expiration phase. Indeed, e-cigarette droplets’ higher hygroscopic growth rates make this change to larger diameters by the end stage more distinct than alterations to combustible tobacco cigarette smoke particle diameters. Furthermore, unlike combustible tobacco cigarettes, e-cigarette particles will not reach equilibrium with their surroundings because they have more volatile substances; combustible tobacco cigarettes’ tar content helps stabilize the particles. Therefore, smaller particles are removed by processes such as coagulation, resulting in a larger median particle diameter. E-cigarette aerosols’ higher growth rates increase total deposition in the lung. This deposition is powered mainly by inertia in bronchial airways and via gravity in alveolar spaces. Finally, puff topography (Evans and Hoffman, 2014; Norton et al., 2014), on average, will not alter these results; the effects of longer puff duration with e-cigarettes on deposition fractions will be offset in general by their higher puff volume (Evans and Hoffman, 2014; Fuoco et al., 2014; Norton et al., 2014; Winkler-Heil et al., 2014). Measurements of Constituents Found in E-Cigarettes E-liquids generally contain four main components: nicotine, flavors, water, and carrier liquids (humectants). The carrier liquid dissolves flavors and nicotine and aerosolizes at a certain temperature on the atomizer of the e-cigarette. Propylene glycol and glycerol, the principal carriers used in e-liquids, undergo partial decomposition in contact with the atomizer heating- coil forming volatile carbonyls. Some of these, such as formaldehyde, acetaldehyde, and PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGAR RETTE DEV VICES, USES AND EXP S, POSURES 3-11 FIGURE 3-3 Tempora evolution of the number al o r/size distribut ution of inhale combustibl tobacco ed le cigarette smoke particl (panel A) and e-cigarett droplets (p s les te panel B) durin puf ng, mo ng outh-hold (M MH), inhalation and exhalati based on the same init size distrib n ion, tial bution. SOURCE Pichelstorfe et al., 2016. E: er acrolein, are of conce due to th adverse impact on hu ern heir i uman health when inhaled at sufficient h concentraations. Physical, chemical, and toxic cological chaaracteristics of e-cigarett liquids an te nd aerosols are discussed in Chapter 5. r Analytical me A ethodology for qualitativ and/or qu f ve uantitative deetermination of a constit n tuent in e-cigarrette aerosol generally en l ncompasses two areas o effort: sam preparat of mple tion and instrumen analysis Sample preparation inv ntal s. volves aeros generatio sample ex sol on, xtraction, an nd sample collection. Innstrumental analysis invo a olves analyzi the samp to identif and quant ing ple fy tify analytes of interest. The instrume is commo T ent only selected based on t chemical characterist d the l tics of the tar analyte, the applicab features of the instrum rget ble o ment, and th instrumen accessibili he nt ity (Cheng, 2014). 2 Currently, the is no stan C ere ndardized method for ge enerating and collecting aerosol from e- d m cigarettes for analytic purposes and laborat s cal s tory studies. Factors inflluencing e-ciigarette aeroosol generatio include th e-cigarette device and set-up, puff on he e d fing topograaphy, machin aerosol ne generatio parameter and aeros generatio techniques As describ in the be on rs, sol on s. bed eginning of t this chapter, the design an composit t nd tion of e-ciga arette device (including e-liquid co es g omposition, device baattery power and activati voltage, coil resistan r ion nce) vary con nsiderably, a these and variation influence the e-cigaret aerosol pr ns t tte roduced. Thu it is cruc to unders us, cial stand each PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

3-12 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES unique set-up and test article prior to chemical analysis and in vitro biological exposure. Human puffing topography, described in detail above, is important in determining true levels of human exposure to constituents in e-cigarettes. Smoking machine parameters for laboratory studies are important in understanding the way that constituent yields delivered by a product can change over a range of different smoking conditions. With respect to aerosol generation techniques, current machine-based aerosol generation techniques pose several challenges for assessing different product aerosols because many smoking machines and exposure systems were originally designed for use with combustible tobacco cigarettes and do not easily translate to the standard production of e-cigarette aerosols. For example, e-cigarettes require a higher airflow rate and longer puff durations to produce aerosols than combustible tobacco cigarettes require to produce smoke. Furthermore, pressure drop (mmH2O across e-cigarettes during each puff) varies greatly, including across cartridges used in the same models, across brands, and even within brands (Goniewicz et al., 2013, 2014; Trehy et al., 2011; Trtchounian et al., 2010; Williams and Talbot, 2011). Other important differences between e-cigarette aerosols and combustible tobacco cigarette smoke in such systems include aerosols condensing in transit tubing (possibly restricting aerosol flow and impeding syringe function) and some concerns with device button activation synchrony (either manually, or automated with a separate robot) with the syringe puffing to ensure the entire puff is activated and delivered (Goniewicz et al., 2014; Havel et al., 2016). These important methodological issues with generating e-cigarette aerosol for analytical and toxicological testing have important implications for analyzed dose and biological effects. A standardized protocol for evaluating emissions (particulate and gas phase) of e-cigarettes would facilitate interpretation of study results reported in literature. Novel devices may help overcome the challenges of using smoking machines. For example, Herrington and Myers (2015) developed a simple sampling device to draw e-cigarette aerosol into a multisorbent thermal desorption tube, which was then thermally extracted and analyzed via gas chromatography (GC) mass spectrometry (MS) methodology. The investigators found that this novel device was effective at providing detectable levels of numerous compounds from e-cigarette aerosol, including many not listed by the manufacturers and those not present in the e-liquid. After producing aerosols, most studies conduct a multistep chemical analysis of emissions in e-cigarette aerosols. High performance liquid chromatography and GC-MS are analytical techniques commonly used for separation, identification, and measurement of chemicals in e-liquids. Aerosols also commonly require sample pretreatment such as extraction and/or derivatization (Geiss et al., 2015; Goniewicz et al., 2014; Ohta et al., 2011; Papousek et al., 2014; Schripp et al., 2013; Uchiyama et al., 2010). The instrument is typically selected based on the chemical characteristics of the target analyte, the applicable features of the instrument, and the instrument accessibility. For the identification of the major ingredients (glycols and glycerol) and their relative concentrations, gas chromatography with flame ionization detector or with MS is usually used. For the identification and quantitative analysis of nicotine, gas chromatography with nitrogen-selective detector or with MS are typically used. Flavorings are commonly identified using gas chromatography with headspace sample delivery interface and tandem mass spectrometry (GC-MS/MS) or time-of-flight mass spectrometer. Chromatography methods provide adequate sensitivity, but a main challenge includes a significant matrix effect, which results in peak suppression of analytes (Geiss et al., 2016; Herrington and Myers, 2015). PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGAR RETTE DEV VICES, USES AND EXP S, POSURES 3-13 SECO ONDHAND EXPOSUR TO E-CI D RE IGARETTE AEROSO E OL In 2006, the Report of the Surgeon General on th health con n R e G he nsequences o involuntar of ry exposure to tobacco smoke concl e luded there is no risk-fre level of ex i ee xposure to secondhand tobacco smoke (Moritsugu, 2007 Consisten s 7). ntly, the guid delines for th implemen he ntation of Arrticle 8 of the World Health Organizati (WHO) Framework Convention on Tobacco Control (FC W h ion F o CTC) indicated there is no safe level of exposure to secondhand smoke, an the only effective mea d f o nd asure to preven exposure is the total el nt i limination of smoking in indoor env n vironments (W WHO, 2003 3). Followin those evid ng dence-based conclusions, many cities and states in the United States and s d countries around the world have enacted com s mprehensive smoke-free legislation b banning smo oking in all ind door public places. Many of those law also inclu outside a p y ws ude areas near th entrances to he indoor ar reas. The spr reading of th smoke-fre movement and the ban he ee nt nning of smo oking indoor is rs probably one of the biggest achie y b evements in public healt in the first decade of t 21st cent th t the tury, protectin hundreds of millions of people fro involunta exposure to secondha smoke ng o o om ary e and around th world. Ma people remain exposed, in venu that have been exclud from he any r ues ded legislatio (e.g., cas ons sinos), in stat and coun tes ntries that ha not enact legislatio and ave ted on, especially in private settings. Wh intervent y hile tions rely m mostly on edu ucational and voluntary d measures to eliminate secondhan tobacco sm s nd moke exposu in privat spaces, leg ure te gislation ban nning smoking in private pl laces, such as in motor vehicles whe children a present a in public a v en are and c housing, is increasing For examp in 2016, the U.S. De g. ple, , epartment of Housing an Urban f nd Developm issued a mandate requiring hou ment using author rities to adop smoke-free policies, pt affecting 1.2 million households nationwide (PIH, 2016) g ). E-cigarettes were initially advertised as a form of tobacco tha could circu E w y f at umvent exis sting smoke-fr legislatio (Paradise, 2014). Thei increasing popularity brought initi confusion as ree on , ir g ial n to whethe existing smoke-free le er egislations also apply to e-cigarettes (Stillman et al., 2015). a s Increasinngly, smoke- -free legislattions banning combustib tobacco c g ble cigarette smooking in indooor public places have be amended to expand their coverag to e-cigar een d t ge rettes (Parad dise, 2014). Many exceptions exi For instan vaping is allowed in e-cigarette shops and a in venue ist. nce, n e also es that hold vaping conv d ventions (ev if the use of e-cigaret is banne in those v ven e ttes ed venues during g other eve ents) (Jarmul et al., 2017 (see Figure 3-4). Over l 7) rall, relativel few studie have ly es FIGURE 3-4 Photogra taken dur aph ring a cloud competition at about 2 pm a a vaping co t at onvention, Ap pril 2016, Maryland SOURCE Chen et al., 2017. E: PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

3-14 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES investigated the characteristics and health effects of secondhand exposure to e-cigarette aerosol. In this section, the committee reviews the evidence available on secondhand e-cigarette aerosol, its characteristics, and its possible health effects, compared with ambient air. Comparisons between secondhand exposure from e-cigarettes and combustible tobacco cigarettes are discussed in Chapter 18 on harm reduction. Characteristics and Chemical Composition of Secondhand E-Cigarette Aerosol For combustible tobacco cigarettes, secondhand smoke is defined as the combination of mainstream (exhaled by the smoker) and sidestream (emitted from the burning cigarette) smoke, with sidestream smoke representing more than 80 percent of the total amount of secondhand tobacco smoke. Secondhand aerosol from e-cigarettes is very different from secondhand combustible tobacco smoke. First, e-cigarette aerosol is composed in large part by small liquid droplets while tobacco smoke contains mostly solid and semi-solid materials, resulting in different half-lifes and deposition behavior in the environment. Second, the e-cigarette aerosol is directly inhaled by the user from the battery-powered device without generation of sidestream smoke. The secondhand aerosol from the e-cigarette thus originates from the aerosol that is exhaled by the vaper and is almost 100 percent mainstream. Multiple studies have characterized the inhaled secondhand smoke using smoking machines or other systems to generate the e- cigarette aerosol, and described it as an aerosol formed by the condensation or atomization of spherical liquid droplets in the submicrometer to 200 m. Those studies are not directly relevant for understanding the characteristics and health risks of secondhand aerosol from e-cigarettes as it has not been exhaled by a vaper. In this part of the report the committee only reviews studies in which the aerosol under study has been originated by a person vaping an e-cigarette, and thus reflects the exposure to bystanders. The number of such studies is relatively small, despite its potential impact in indoor air quality and as the involuntary nature of exposure. Those studies have been conducted in exposure chambers or rooms that tried to recreate a room where vaping is occurring (Czogala et al., 2014; Liu et al., 2017; Melstrom et al., 2017; Protano et al., 2017; Schober et al., 2014), in a real-life setting in the homes of e-cigarette users (Ballbe et al., 2014; Fernández et al., 2015), and during vaping conventions (Chen et al., 2017; Soule et al., 2016). In a study conducted in an exposure chamber with five dual users who used their personal e-cigarette devices (no details provided regarding type of device) ad lib twice for 5 minutes with a 30-min interval, mean (SD) 1-hour air nicotine concentration measured using active sampling was 3.32 (2.49) g/m3 compared with undetectable for 1-h measure collected at baseline (p-value less than 0.05) (Czogala et al., 2014). Real-time PM2.5 concentrations increased shortly after the beginning of vaping. The mean (SD) PM2.5 concentration was also higher following vaping (152 (86.8) g/m3) compared with baseline (32.4 g/m3) (p-value less than 0.05). No differences were observed for CO (1.40 (0.55) versus 1.40 (0.55). For VOCs, toluene was the only one detected in the exposure chamber and the levels remained similar after vaping (3.79 (2.16) versus 4.09 (2.21), p = 0.85) (Czogala et al., 2014). Another chamber study with four volunteers vaping e- cigarettes for 12 puffs with Smooke E-SMART device confirmed that particles increased in real time, although the concentrations were lower compared with secondhand tobacco smoke (Protano et al., 2017). In a chamber study with 37 volunteers using cigalikes and tank-style devices under controlled conditions and 4-hour ad lib use, nicotine, PG, and glycerol increased, but were several-fold below the time-weighted average limits used in workplace settings (Liu et al., 2017). The tank device produced the highest difference from baseline in the level of PG and glycerol. For nicotine the air levels ranged from 0.38 to 2.83 g/m3. Of the 15 carbonyls PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGAR RETTE DEV VICES, USES AND EXP S, POSURES 3-15 measured only hexal d, ldehyde and acetaldehyd were sign d de nificantly hig gher with eitther cigalikes or s tank-style devices, reespectively. Of the 12 VO measur benzene isoprene, a toluene O OCs red, e, and increased with the us of cigalike or tank-sty devices. This study d not meas d se es yle did sure particullate matter. In a study of nine volunte using e-cigarettes (w a refilla tank) for 2 hours in n n eers with able r groups of three trying to recreate a real-life scenario (caf f g e s fé-like setting) and using different e- g - liquids with and with w hout nicotine the mean airborne con e, a ncentration o PM2.5 duri the vapin of ing ng sessions was 197 g/ 3 versus 6 g/m3 for th control pe /m he eriods (Scho ober et al., 20014). PM10 3 (mean 22 versus 47 g/m ), par 29 rticle number concentrati r ions (61,682 versus 4,46 N/cm3), 2 66 nicotine (2.2 versus less than 0.04 g/m3), to PAHs (5 15 versus 35 g/m3), a aluminum ( l otal 50 and m 3 (483 vers 203 ng/m ) also incre sus m eased during the vaping sessions. g In real-life settings, studie in homes found small real-time in n es l ncreases in PPM2.5 concentra ations in the home of an e-cigarette user that coi u incided with vaping use during a 60- h - minute sa ampling, althhough the median conce m entration (9.8 g/m3) w similar (8 88 was 8.32 g/m3) to the levels found in th home of th non-vape (Fernández et al., 2015 In anothe study in ho s he he er z 5). er omes by the sa research team, median air nicotin (0.11 ver ame h ne rsus 0.01 g/ 3, p-value 0.007), salivary /m e cotinine (0.24 versus 0.05 ng/ml, p-value 0.0 ( s , 003), and urinnary cotinin (2.64 versu 0.72 ng/m p- ne us ml, value 0.0008) concent trations were higher in homes of part e h ticipants wh lived with somebody w ho h who vaped mo than 2 ho ore ours/day verrsus control homes (Ballb et al., 2014). h lbe Two studies measured ind T m door air qual in e-ciga lity arette conven ntion events (Chen et al. s ., 2017; So et al., 20 oule 016). Those events are often attended by tens to hundreds of e-cigarette users e d f who often vape at the same time. In both stud levels o particulate matter (PM10 in one stu e . dies of e M udy, PM2.5 in the other stuudy) were markedly elev vated, reachin levels tha are typical of bars and ng at d hookah venues. One of the studie measured PM2.5 the da before, du v es ay uring the event, and the day after (see Figure 3-5) showing th even on the day after PM2.5 conc e ), hat t r, centrations w still were markedly higher com y mpared with the day befo the event (Soule et al 2016). t ore t l., FIGURE 3-5 Event ro oom PM2.5 con ncentrations before, during and after an e-cigarette c b g, n convention. SOURCE Soule et al., 2016. E: , PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

3-16 PUBLI HEALTH CONSEQU IC H UENCES OF E-CIGARET TTES In the other st n tudy in a vapping conven ntion, in addi ition to real-ttime PM10, r time CO2 (a real O marker of how many people were in the room and TVO were me o y e m) OCs easured, as w as a 7-ho well our nicotine concentratio (Chen et al., 2017). Th estimated 24-hour tim weighted average PM10 c on a he d me d M was 1,800 g/m3, 12 times highe than the En er nvironmenta Protection Agency 24-hour regula al n ation (150 g/m3). Median indoor TVO concent m n OCs tration was 00.13 (0.04, 0 ppm. TV 0.3) VOC and PM10 M were high correlate with CO2, indicating the high num hly ed t mber of peop using e-c ple cigarettes and d exposed to poor air quality. The concentratio of TVOC also increa q c ons C ased markedl during a c ly cloud competition (for PM10 the monito stopped sh or hortly after t beginnin of the com the ng mpetition and the d comparis is limited (see Figur 3-6). The picture show in Figure 3-6 shows a high moment son d) re wn e during th cloud com he oncentration was 125 g 3, similar to mpetition. Air nicotine co g/m r concentra ations measuured in bars and nightclu ubs. The findings from these two studies indicate that e-cigarette a T t i aerosol in vaaping conventio that congregate man e-cigarette users is a m ons ny e major source of particula matter, ai e ate ir nicotine, and VOCs, impairing ai quality. Th ir hese exposu can also be a concern for e-cigar ures n rette vendors and other ve a enue workers who spend many hours in those pla s s aces (Chen e al., 2017). et In addition to these studie based prim n o es marily on ex xposure asses ssment and e environment tal sampling two studies have devel g, loped model to evaluate the second ls e dhand aeroso generated by e- ol cigarettes under diffe s erent conditions (Logue et al., 2017; Rostami et al., 2016). F instance, one For model as ssessed real-l settings, such as a re life esidential settting where a non-user li ives with a u user and a bar that allows vaping indo (Logue et al., 2017) The contrib r oors ). bution of seccondhand e- - cigarette aerosol exposure to air pollutant con p ncentrations in the home did not exc s e ceed the Californi OEHHA 8-hour refere ia 8 ence exposur levels (RE re ELs), except when a high t h-emitting device was used (4.8 V). In that extreme scen w e nario, the coontributions f from vaping amounted t as g to 3 3 much as 12 g m fo ormaldehyde and 2.6 g m acrolein In the bar scenario, th contributions e n. r he from vapping to indoo air levels were marked higher th those in t home scenario. or w dly han the NOTE: 1 = outside the venue; 2 = in e nside the venu 3 = trick c ue; competition; 4 = vaping co ompetition. FIGURE 3-6 Real-tim changes of PM10, CO2, and TVOC c me f concentrations during a vap s ping conventi in ion Maryland During the vaping compe d. v etition (sectio 4 of the gra on aph), TVOCs and PM10 inc s creased, altho ough for PM10 the monitor st t topped before the end of th competitio e he on. SOURCE Chen et al., 2017. E: PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-17 Formaldehyde (mean 135 g m 3) and acrolein (28 g m 3) exceeded the acute 1-hour exposure REL for the highest emitting vaporizer/voltage combination. Predictions for these compounds also exceeded the 8-hour REL in several bars when less intense vaping conditions were considered. Benzene concentrations in a few bars approached the 8-hour REL, and diacetyl levels were near the lower limit for occupational exposures. These findings support the evidence that e-cigarettes can contribute to substantial air pollution, especially in places with a large number of vapers. The committee did not identify any studies evaluating health effects or early biomarkers of disease resulting from secondhand exposure to e-cigarette aerosols per se. One study conducted a health impact assessment based on computing disability-adjusted life years (DALYs) lost due to exposure to secondhand e-cigarette aerosol (Logue et al., 2017). DALYs were estimated for residential and hospitality industry scenarios based on the recent incorporation of DALYs into health impact assessments of exposures to indoor pollutants, including tobacco smoke and particles, and estimating, on a compound-by-compound basis, the population-averaged health damage per year of exposure. The toxicants included were formaldehyde, acetaldehyde, benzene, acrolein, and glycidol. Formaldehyde, acetaldehyde and benzene are established carcinogens and glycidol is a probable carcinogen according to the IARC. Acrolein is not yet classified as a carcinogen but it was the dominant contributor to the aggregate harm (see Figure 3-7). DALYs for different combinations of device/voltage characteristics were lower, but in some instances comparable to those estimated for exposure to secondhand tobacco smoke. Synthesis Several studies have measured airborne concentrations of particulate matter, nicotine, and other constituents in indoor environments, either in exposure chambers, rooms trying to recreate real-life settings, and real-life settings such as homes and conventions where vaping takes place. All studies measuring particulate matter and nicotine (for experiments with nicotine e-liquids) found statistically significant increases of those chemicals as compared with background. The levels of both particulate matter and nicotine were higher in experiments with more than one vaper, and they were extremely high in studies of vaping conventions, where levels of particulate matter and nicotine concentrations were comparable to those founds in bars and nightclubs. Among the other constituents, two studies have detected airborne toluene and other VOCs in the air following vaping experiments. Total VOCs were markedly high and increased with increasing levels of vaping, during a vaping cloud competition, supporting that VOCs are released from the e-cigarettes into the environment during the exhalation of the e-cigarette aerosol. Overall, these exposure studies indicate that e-cigarette vaping contributes to some level of indoor air pollution, which, although lower than what has been observed from secondhand combustible tobacco cigarettes, is above the smoke-free level recommended by the U.S. Surgeon General and the WHO FCTC. As with secondhand smoke, children, pregnant women, the elderly, and patients with cardiorespiratory diseases may be at special risk. The e-cigarette convention studies also suggest that e-cigarette aerosol exposure could be substantial for workers in these venues, especially those who are exposed during multiple events. No available studies have evaluated health effects (either clinical effects or early biomarkers of disease) of secondhand e-cigarette exposure. Conclusion 3-1. There is conclusive evidence that e-cigarette use increases airborne concentrations of particulate matter and nicotine in indoor environments compared with background levels. PREPUBLICATION COPY: UNCORRECTED PROOFS

3-18 PUBLI HEALTH CONSEQU IC H UENCES OF E-CIGARET TTES This conclusi is suppor by cham T ion rted mber experimments, real-se etting experi iments, and observatiional studies in homes an conventio centers. I experimen with one single e- s nd on In nts cigarette user, levels are markedl lower than for second ly n dhand tobacc smoke. Le co evels increas se markedly with the increase in the number of vapers, in p articular at v y e vaping conve entions. Conclusion 3-2. There is limited evid C dence that e- cigarette use increases l e levels of nicotine and other e-cigarette constit o tuents on a v variety of ind door surface es co ompared wit backgroun levels. th nd NOTES: The boxes show the media and 95th pe T an ercentile rang of predicte health dam ge ed mage. A = toxi icant- specific im mpact estimat for the res ted sidential scen nario in which the vaper co h onsumes CT e e-liquid using the g EGO devi at 3.8 V; B = aggregate damage for six scenario of home an bar exposu using thre ice ed r os nd ures ee device/voltage combin nations. In all cases, emission rates corre espond to typ essions of 25 puffs pical vaping se each. The figure includ the estima damage due to second and thirdha smoke fro combustib e des ated d d- and om ble tobacco ciigarettes as ca alculated in a previous stud from St.H dy Helen et al. (20 016b). The DA ALYS are presented for full smok and for the VOCs alone (excluding P 2.5). ke e PM FIGURE 3-7 Estimate disability-a ed adjusted life years (DALY lost due to exposure to secondhand e y YS) o e- cigarette aerosol. a Source: Logue et al., 2017. L PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-19 TABLE 3-2 Summary of 14 E-Cigarette Puffing Topography Studies Study Study Product Nicotine Sample Study Method Puff Count Puff Interpuff Flow Rate Puff Content Size Conditions Duration (s) Interval (s) (ml/s) Volume (ml) Norton et al., Smoke 51 11 mg/ml 18 Lab; ad lib CReSS 8.7 (1.6) 3.0 (0.8) 29.6 (11.7) 52.0 (4.7) 118.2 (13.3) 2014a TRIO (1st gen) (SEM) usual n/a Lab; 1 cigarette 13.2 (1.1) 3.0 (1.0) 21.3 (6.2) 36.1 (1.8) 67.5 (6.3) combustible tobacco cigarette Farsalinos et eVic by 18 mg/ml 23 Lab; 10 puffs in 5 eVic n/a 2.3 (0.2) n/a n/a n/a al., 2015b Joyetech (2nd min followed by gen) ad lib use in 60 min Lee et al., M201 (1st gen) 18 mg (11.0 20 Lab: baseline, ad CReSS 19.3 (2.5) 2.2 (0.1) 19.2 (2.7) 30.6 (2.3) 64.0 (4.8) 2015c ± 1.5 mg lib (SEM) measued) Lab: week 2, ad 21.3 (2.4) 2.9 (0.2) 22.1 (4.9) 24.8 (1.9) 63.3 (5.2) lib Lopez et al., eGO 3.3 V 0 mg/ml 16 Lab; two 10-puff in-house n/a 3.00 (1.38) n/a 30.0 (25.7) 83.2 (62.6) 2016d battery with standardized device (SD) 1.5-Ohm 8 mg/ml sessions, 30-s n/a) 2.80 (1.41) n/a 30.9 (20.1) 80.3 (53.8) Smoktech interval, sessions (SD) cartomizer 18 mg/ml were 1 hour apart n/a 2.85 (1.49) n/a 27.1 (13.1) 70.2 (28.8) (SD) 36 mg/ml n/a 2.27 (0.99) n/a 31.8 (33.1) 66.7 (55.9) (SD) Strasser et al., five brands: NJOY: 18 28 Lab; ad lib over videotape 16.1 (11.9) 1.99 (0.7) 11.2 (5.2) n/a n/a 2016e NJOY, V2, mg; V2: 18 10 min (day 5) (SD) Green Smoke, mg; Green Lab; ad lib over 13.2 (9.4) 2.06 (0.7) 11.2 (5.2) Blu, White Smoke: 10 min (day 10) (SD) Cloud 18.9-20.7 mg; Blu: 20- 24 mg; White Cloud: 23- 24 mg usual n/a Lab; 1 cigarette 13.6 (4.0) 1.64 (0.3) 25.3 (13.3) combustible (day 1) (SD) (SD) tobacco cigarette PREPUBLICATION COPY: UNCORRECTED PROOFS

3-20 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Study Study Product Nicotine Sample Study Method Puff Count Puff Interpuff Flow Rate Puff Content Size Conditions Duration (s) Interval (s) (ml/s) Volume (ml) Goniewicz et usual e- n/a 10 Lab; ad lib CReSS 15 (6) (SD) 1.8 (0.9) 10 (13) n/a 70 (68) al., 2013f cigarette brands Behar et al., Blu and V2 (1st Blu: 16 20 Lab; ad lib use CReSS 32 (8) (SD) 2.65 (0.98) 17.9 (7.5) 20 (6) 51 (21) 2015g gen) mg/ml; V2: for 10 min 18 mg/ml Farsalinos et eVic by 18 mg/ml 24 Lab; 10 puffs in 5 eVic n/a 3.5 (0.2) n/a n/a n/a al., 2015h Joyetech (2nd min followed by (mean, SEM) gen) ad lib use in 60 min Robinson et blu (1st gen) 16 mg 22 Naturalistic wPUM 24-h: 225 3.5 (1.8) n/a 37 (16) 133 (90) al., 2015i environment, ad (272) (SD); lib, 1 day per session: 15 (25) Spindle et al., Usual battery Usual e- 13 Lab; 10-puff in-house n/a 4.16 (1.06) n/a 24.17 101.37 2015j with 1.5 Ohm liquid: 21.7 standardized device (SD) (10.66) (50.01) SmokTech (3.9) mg/ml session, 30 s cartomizer (mean, SD); between puffs range: 12-24 mg/ml Cunningham Vype Reload 4.5% 32 Lab; ad lib over modifed 21.1 (14.9) 2.0 (0.7) 23.2 (10.6) 39.0 (10.3) 52.2 (21.6) et al., 2016k (1st gen) nicotine (45 self-determined SA7 (SD) peak mg/ml) length; mean: 6:54 (3:43) min (SD) Vype ePen (2nd 3.0% 28 Lab; ad lib over 16.1 (8.0) 2.2 (0.9) 29.3 (19.2) 60.6 (19.8) 83.0 (44.3) gen) nicotine (30 self-determined (SD) peak mg/ml) length; mean: 7:41 (6:17) min (SD) Dawkins et eVic by 6 mg/ml 11 Lab; ad lib over eVic 70.73 (34.45) 5.20 (1.39) n/a n/a n/a al., 2016l Joyetech (2nd 60 min (SD) gen) 24 mg/ml 48.36 (22.86) 3.84 (1.02) Robinson et usual device usual 20 Naturalistic wPUM 78 (81) (SD) 2.0 (0.6) n/a 30.4 (9.2) 65.4 (24.8) al., 2016m (1st gen) nicotine environment, ad level lib, 1 day PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-21 Study Study Product Nicotine Sample Study Method Puff Count Puff Interpuff Flow Rate Puff Content Size Conditions Duration (s) Interval (s) (ml/s) Volume (ml) St.Helen et usual brands usual 13 Lab; ad lib over videotape 64 (38) (SD) 3.5 (1.4) 118 (141) n/a n/a al., 2016n e-liquid: 9.4 90 min 12.5 (4.1) mg/ml (mean, SD); range: 5.0- 15.3 mg/ml Spindle et al., Usual battery usual e- 29 Lab; 10-puff in-house 9.97 (0.12) 4.51 (1.55) 25.19 27.78 124.56 2017o with 1.5 Ohm liquid: 18.9 session (30-s device (SD) (1.55) (19.48) (89.13) SmokTech (5.9) mg/ml interpuff interval) cartomizer (mean, SD) lab; ad lib over 90 62.55 (32.34) 5.29 (2.08) 102.77 27.47 148.52 min (SD) (63.07) (22.63) (119.6) NOTE: SD = standard deviation; SEM = standard error of mean. a Norton et al., 2014. b Farsalinos et al., 2015a. c Lee et al., 2015. d Lopez et al., 2016. e Strasser et al., 2016. f Goniewicz et al., 2013. g Behar et al., 2015. h Farsalinos et al., 2015a. i Robinson et al., 2015. j Spindle et al., 2015. k Cunningham et al., 2016. l Dawkins et al., 2016. m Robinson et al., 2016. n St.Helen et al., 2016a. o Spindle et al., 2017. PREPUBLICATION COPY: UNCORRECTED PROOFS

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E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-23 Geiss, O., I. Bianchi, F. Barahona, and J. Barrero-Moreno. 2015. Characterisation of mainstream and passive vapours emitted by selected electronic cigarettes. International Journal of Hygiene and Environmental Health 218(1):169-180. Geiss, O., I. Bianchi, and J. Barrero-Moreno. 2016. Correlation of volatile carbonyl yields emitted by e-cigarettes with the temperature of the heating coil and the perceived sensorial quality of the generated vapours. International Journal of Hygiene and Environmental Health 219(3):268-277. Gillman, I. G., K. A. Kistler, E. W. Stewart, and A. R. Paolantonio. 2016. Effect of variable power levels on the yield of total aerosol mass and formation of aldehydes in e-cigarette aerosols. Regulatory Toxicology and Pharmacology 75:58-65. Goniewicz, M. L., T. Kuma, M. Gawron, J. Knysak, and L. Kosmider. 2013. Nicotine levels in electronic cigarettes. Nicotine & Tobacco Research 15(1):158-166. Goniewicz, M. L., J. Knysak, M. Gawron, L. Kosmider, A. Sobczak, J. Kurek, A. Prokopowicz, M. Jablonska-Czapla, C. Rosik-Dulewska, C. Havel, I. P. Jacob, and N. Benowitz. 2014. Levels of selected carcinogens and toxicants in vapour from electronic cigarettes. Tobacco Control 23(2):133-139. Havel, C. M., N. L. Benowitz, P. Jacob, 3rd, and G. St.Helen. 2016. An electronic cigarette vaping machine for the characterization of aerosol delivery and composition. Nicotine & Tobacco Research [e-pub ahead of print]. Herrington, J. S., and C. Myers. 2015. Electronic cigarette solutions and resultant aerosol profiles. Journal of Chromatography A 1418:192-199. Hukkanen, J., P. Jacob, 3rd, and N. L. Benowitz. 2005. Metabolism and disposition kinetics of nicotine. Pharmacological Reviews 57(1):79-115. Ingebrethsen, B. J., S. K. Cole, and S. L. Alderman. 2012. Electronic cigarette aerosol particle size distribution measurements. Inhalation Toxicology 24(14):976-984. Jarmul, S., A. Aherrera, A. M. Rule, P. Olmedo, R. Chen, and A. Navas-Acien. 2017. Lost in e- cigarette clouds: A culture on the rise. American Journal of Public Health 107(2):265- 266. Ji, E. H., B. B. Sun, T. K. Zhao, S. Shu, C. H. Chang, D. Messadi, T. Xia, Y. F. Zhu, and S. Hu. 2016. Characterization of electronic cigarette aerosol and its induction of oxidative stress response in oral keratinocytes. PLoS ONE 11(5): 1-13. Kleykamp, B. A., J. M. Jennings, C. Sams, M. F. Weaver, and T. Eissenberg. 2008. The influence of transdermal nicotine on tobacco/nicotine abstinence and the effects of a concurrently administered cigarette in women and men. Experimental and Clinical Psychopharmacology 16(2):99-112. Lee, Y. H., M. Gawron, and M. L. Goniewicz. 2015. Changes in puffing behavior among smokers who switched from tobacco to electronic cigarettes. Addictive Behaviors 48:1-4. Liu, J., Q. Liang, M. J. Oldham, A. A. Rostami, K. A. Wagner, I. G. Gillman, P. Patel, R. Savioz, and M. Sarkar. 2017. Determination of selected chemical levels in room air and on surfaces after the use of cartridge- and tank-based e-vapor products or conventional cigarettes. International Journal of Environmental Research & Public Health 14(9): 1- 21. Logue, J. M., M. Sleiman, V. N. Montesinos, M. L. Russell, M. I. Litter, N. L. Benowitz, L. A. Gundel, and H. Destaillats. 2017. Emissions from electronic cigarettes: Assessing vapers’ intake of toxic compounds, secondhand exposures, and the associated health impacts. Environmental Science & Technology 51(16):9271-9279. PREPUBLICATION COPY: UNCORRECTED PROOFS

3-24 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Lopez, A. A., M. M. Hiler, E. K. Soule, C. P. Ramoa, N. V. Karaoghlanian, T. Lipato, A. B. Breland, A. L. Shihadeh, and T. Eissenberg. 2016. Effects of electronic cigarette liquid nicotine concentration on plasma nicotine and puff topography in tobacco cigarette smokers: A preliminary report. Nicotine & Tobacco Research 18(5):720-723. Marini, S., G. Buonanno, L. Stabile, and G. Ficco. 2014. Short-term effects of electronic and tobacco cigarettes on exhaled nitric oxide. Toxicology and Applied Pharmacology 278(1):9-15. Melstrom, P., B. Koszowski, M. H. Thanner, E. Hoh, B. King, R. Bunnell, and T. McAfee. 2017. Measuring pm2.5, ultrafine particles, air nicotine and wipe samples following the use of electronic cigarettes. Nicotine & Tobacco Research 19(9):1055-1061. Moritsugu, K. P. 2007. The 2006 report of the surgeon general: The health consequences of involuntary exposure to tobacco smoke. American Journal of Preventive Medicine 32(6):542-543. Norton, K. J., K. M. June, and R. J. O’Connor. 2014. Initial puffing behaviors and subjective responses differ between an electronic nicotine delivery system and traditional cigarettes. Tobacco Induced Diseases 12 (1):1-8. Ohta, K., S. Uchiyama, Y. Inaba, H. Nakagome, and N. Kunugita. 2011. Determination of carbonyl compounds generated from the electronic cigarette using coupled silica cartridges impregnated with hydroquinone and 2,4-dinitrophenylhydrazine. Bunseki Kagaku 60(10):791-797. Papousek, R., Z. Pataj, P. Novakova, K. Lemr, and P. Bartak. 2014. Determination of acrylamide and acrolein in smoke from tobacco and e-cigarettes. Chromatographia 77(17-18):1145- 1151. Paradise, J. 2014. Electronic cigarettes: Smoke-free laws, sale restrictions, and the public health. American Journal of Public Health 104(6):e17-e18. Pichelstorfer, L., W. Hofmann, R. Winkler-Heil, C. U. Yurteri, and J. McAughey. 2016. Simulation of aerosol dynamics and deposition of combustible and electronic cigarette aerosols in the human respiratory tract. Journal of Aerosol Science 99:125-132. PIH (Office of the Assistant Secretary for Public and Indian Housing). 2016. Instituting smoke- free public housing. Federal Register 81(233):87430-87444. Pratte, P., S. Cosandey, and C. Goujon-Ginglinger. 2016. A scattering methodology for droplet sizing of e-cigarette aerosols. Inhalation Toxicology 28(12):537-545. Protano, C., M. Manigrasso, P. Avino, and M. Vitali. 2017. Second-hand smoke generated by combustion and electronic smoking devices used in real scenarios: Ultrafine particle pollution and age-related dose assessment. Environment International 107:190-195. Robinson, R. J., E. C. Hensel, P. N. Morabito, and K. A. Roundtree. 2015. Electronic cigarette topography in the natural environment. PLoS ONE 10(6):e0129296. Robinson, R. J., E. C. Hensel, K. A. Roundtree, A. G. Difrancesco, J. M. Nonnemaker, and Y. O. Lee. 2016. Week long topography study of young adults using electronic cigarettes in their natural environment. PLoS ONE 11(10):e0164038. Rostami, A. A., Y. B. Pithawalla, J. M. Liu, M. J. Oldham, K. A. Wagner, K. Frost-Pineda, and M. A. Sarkar. 2016. A well-mixed computational model for estimating room air levels of selected constituents from e-vapor product use. International Journal of Environmental Research and Public Health 13(8): 1-15. PREPUBLICATION COPY: UNCORRECTED PROOFS

E-CIGARETTE DEVICES, USES, AND EXPOSURES 3-25 Schmeltz, I., A. Wenger, D. Hoffmann, and T. C. Tso. 1979. Chemical studies on tobacco smoke. 63. The fate of nicotine during pyrolysis and in a burning cigaret. Journal of Agricultural and Food Chemistry 27(3):602-608. Schober, W., K. Szendrei, W. Matzen, H. Osiander-Fuchs, D. Heitmann, T. Schettgen, R. A. Jorres, and H. Fromme. 2014. Use of electronic cigarettes (e-cigarettes) impairs indoor air quality and increases FeNO levels of e-cigarette consumers. International Journal of Hygiene and Environmental Health 217(6):628-637. Schripp, T., D. Markewitz, E. Uhde, and T. Salthammer. 2013. Does e-cigarette consumption cause passive vaping? Indoor Air 23(1):25-31. Soule, E. K., S. F. Maloney, T. R. Spindle, A. K. Rudy, M. M. Hiler, and C. O. Cobb. 2016. Electronic cigarette use and indoor air quality in a natural setting. Tobacco Control 26(1):109. Spindle, T. R., A. B. Breland, N. V. Karaoghlanian, A. L. Shihadeh, and T. Eissenberg. 2015. Preliminary results of an examination of electronic cigarette user puff topography: The effect of a mouthpiece-based topography measurement device on plasma nicotine and subjective effects. Nicotine & Tobacco Research 17(2):142-149. Spindle, T. R., M. M. Hiler, A. B. Breland, N. V. Karaoghlanian, A. L. Shihadeh, and T. Eissenberg. 2017. The influence of a mouthpiece-based topography measurement device on electronic cigarette user's plasma nicotine concentration, heart rate, and subjective effects under directed and ad libitum use conditions. Nicotine & Tobacco Research 19(4):469-476. St.Helen, G., K. C. Ross, D. A. Dempsey, C. M. Havel, P. Jacob, 3rd, and N. L. Benowitz. 2016a. Nicotine delivery and vaping behavior during ad libitum e-cigarette access. Tobacco Regulatory Science 2(4):363-376. St.Helen, G.; C. Havel; D. Dempsey; P. Jacob, 3rd; and N.L. Benowitz. 2016b. Nicotine delivery, retention and pharmacokinetics from various electronic cigarettes. Addiction (111)3:535 544. Stillman, F. A., A. Soong, L. Y. Zheng, and A. Navas-Acien. 2015. E-cigarette use in air transit: Self-reported data from us flight attendants. Tobacco Control 24(4):417-418. Strasser, A. A., V. Souprountchouk, A. Kaufmann, S. Blazekovic, F. Leone, N. L. Benowitz, and R. A. Schnoll. 2016. Nicotine replacement, topography, and smoking phenotypes of e- cigarettes. Tobacco Regulatory Science 2(4):352-362. Trehy, M. L., W. Ye, M. E. Hadwiger, T. W. Moore, J. F. Allgire, J. T. Woodruff, S. S. Ahadi, J. C. Black, and B. J. Westenberger. 2011. Analysis of electronic cigarette cartridges, refill solutions, and smoke for nicotine and nicotine related impurities. Journal of Liquid Chromatography and Related Technologies 34(14):1442-1458. Trtchounian, A., M. Williams, and P. Talbot. 2010. Conventional and electronic cigarettes (e- cigarettes) have different smoking characteristics. Nicotine & Tobacco Research 12(9):905-912. Uchiyama, S., Y. Inaba, and N. Kunugita. 2010. Determination of acrolein and other carbonyls in cigarette smoke using coupled silica cartridges impregnated with hydroquinone and 2,4- dinitrophenylhydrazine. Journal of Chromatography A 1217(26):4383-4388. WHO (World Health Organization). 2003. WHO framework convention on tobacco control. Geneva, Switzerland: World Health Organization. Williams, M., and P. Talbot. 2011. Variability among electronic cigarettes in the pressure drop, airflow rate, and aerosol production. Nicotine & Tobacco Research 13(12):1276-1283. PREPUBLICATION COPY: UNCORRECTED PROOFS

3-26 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Winkler-Heil, R., G. Ferron, and W. Hofmann. 2014. Calculation of hygroscopic particle deposition in the human lung. Inhalation Toxicology 26(3):193-206. Zhu, S. H., J. Y. Sun, E. Bonnevie, S. E. Cummins, A. Gamst, L. Yin, and M. Lee. 2014. Four hundred and sixty brands of e-cigarettes and counting: Implications for product regulation. Tobacco Control 23(Suppl 3):iii3-iii9. PREPUBLICATION COPY: UNCORRECTED PROOFS

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Millions of Americans use e-cigarettes. Despite their popularity, little is known about their health effects. Some suggest that e-cigarettes likely confer lower risk compared to combustible tobacco cigarettes, because they do not expose users to toxicants produced through combustion. Proponents of e-cigarette use also tout the potential benefits of e-cigarettes as devices that could help combustible tobacco cigarette smokers to quit and thereby reduce tobacco-related health risks. Others are concerned about the exposure to potentially toxic substances contained in e-cigarette emissions, especially in individuals who have never used tobacco products such as youth and young adults. Given their relatively recent introduction, there has been little time for a scientific body of evidence to develop on the health effects of e-cigarettes.

Public Health Consequences of E-Cigarettes reviews and critically assesses the state of the emerging evidence about e-cigarettes and health. This report makes recommendations for the improvement of this research and highlights gaps that are a priority for future research.

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