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. Author manuscript; available in PMC: 2023 Mar 18.
Published in final edited form as: Aerosol Sci Technol. 2022 Mar 18;56(6):517–529. doi: 10.1080/02786826.2022.2047152

Laboratory Determination of Gravimetric Correction Factors for Real-time Area Measurements of Electronic Cigarette Aerosols

Sinan Sousan a,b, Jack Pender c, Dillon Streuber d, Meaghan Haley d, Will Shingleton d, Eric Soule d
PMCID: PMC9071016  NIHMSID: NIHMS1798416  PMID: 35527743

Abstract

Research on secondhand electronic cigarette (ECIG) aerosol exposure using aerosol monitors has demonstrated that ECIG use can generate high concentrations of particulate matter (PM) and impact indoor air quality. However, quantifying indoor air PM concentrations using real-time optical monitors with on-site calibration specifically for different PM exposures has not been established. Therefore, the ECIG aerosol filter correction factors were calculated for different PM sizes (PM1, PM2.5, and PM10) and different aerosol optical monitors, the MiniWRAS, pDR, and SidePak. ECIG aerosol generation was achieved using five ECIGs representing three ECIG types, disposable, pod-mod, and box mod. The aerosol size distribution by mass was measured for the five ECIGs during PM generation. Compared to the discrete filter measurements, the MiniWRAS performed the best when the concentrations were low, followed by the pDR and SidePak. The average PM concentrations and correction factor ranges for the different ECIGs were 323-1,775 μg/m3 and 0.64-6.01 for the MiniWRAS, 1,388-13,365 μg/m3 and 0.41-0.80 for the pDR, and 4,632-55,339 μg/m3 and 0.13-0.20 for the SidePak, respectively. The mass median diameter ranged from 0.41 and 0.62 μm, and most particles generated from the ECIGs were smaller than 1 μm. This study demonstrates that aerosol size distribution varies between ECIGs. Likewise, the correction factors developed for the real-time aerosol monitors are specific to the ECIG used. Thus, these data can help improve ECIG aerosol exposure measurement accuracy.

Graphical Abstract

graphic file with name nihms-1798416-f0001.jpg

Introduction

Electronic cigarettes (ECIGs) are devices that use an electric heater to aerosolize a liquid often containing propylene glycol (PG), vegetable glycerol (VG), nicotine, and chemical flavorants (Breland et al. 2017). While ECIGs do not produce smoke through combustion, as in cigarettes or other combustible tobacco products, laboratory research demonstrates that ECIGs generate aerosols that include suspended droplets (i.e., particulate matter or PM) and volatile organic compound vapors. The droplets mainly contain PG, VG, nicotine, water, and flavorings (Czogala et al. 2014; Hutzler et al. 2014; Kosmider et al. 2014; Logue et al. 2017; Schripp et al. 2013; Sleiman et al. 2016; Williams et al. 2017; Williams et al. 2013). Additionally, chemical reactions during ECIG use can generate other toxicants known to be associated with negative health effects, including formaldehyde, acetaldehyde, acrolein, furans, chloropropanols, and tobacco-specific nitrosamines (El-Hage et al. 2019; Flora et al. 2016; Goniewicz et al. 2014; Jensen et al. 2015). Research in exposure chambers (Czogala et al. 2014; Protano et al. 2017; Schober et al. 2014) and real-world settings (Ballbè et al. 2014; Chen et al. 2018; Fernández et al. 2015; Soule et al. 2017; Volesky et al. 2018) have demonstrated that indoor ECIG use can generate high concentrations of PM and greatly impacts indoor air quality. Studies have focused on measuring primary ECIG emissions as well as secondhand and thirdhand ECIG exposure inside laboratory and field settings (Czogala et al. 2014; Goniewicz and Lee 2014; Hiler et al. 2020). These studies measure ECIG aerosol area exposure inside a controlled laboratory chamber.

Recent data suggest exposure to secondhand ECIG aerosol (i.e., bystanders’ exposure to ECIG-generated aerosol) may be associated with negative health effects. Visser et al. (2019) reported that secondhand ECIG aerosol contains toxicants including nicotine, PG, copper, and tobacco-specific nitrosamines. In-vitro data show that primary emissions and secondhand aerosols can impact cell metabolism and oxidative stress in epithelial cells (Jarrell et al. 2021). Carwile et al. (2019) reported that prevalence of asthma among children was higher in houses where adults reported indoor ECIG use based on data from a study conducted between 2016 and 2017 in the United States. In addition, Gentzke et al. (2019) reported that more than 50% of adolescents in the United States are exposed to secondhand cigarette aerosol and ECIGs aerosol regularly. ECIGs exposure and their related health effects are new, and unfortunately, the long-term health effects of firsthand and secondhand exposures will not be known for a long period. Exposure to ECIG aerosol is particularly of concern due to the size of particles that are inhaled and could have detrimental health effects.

ECIGs generate PM2.5 (PM 2.5 μm and smaller in diameter) and are particularly dangerous because they penetrate and deposit deeper into the lungs and could reach the alveoli, where air exchanges occur with the blood and translocate to other organs of the body (Choi et al. 2010; Hinds 1999). The Environmental Protection Agency (EPA) and World Health Organization (WHO) list PM2.5 and PM10 (PM 10 μm and smaller in diameter) as environmental hazards, and PM2.5 as an indoor hazard (EPA 1990; 2021; WHO 2010; 2018). EPA and WHO have no indoor regulations for PM2.5 and PM10. However, the WHO has concluded that there is no difference in the hazardous nature of PM2.5 and PM10 between indoor and outdoor settings (WHO 2018). In addition, there is an increasing interest in PM1 (particles 1μm and smaller in size) particles due to their short-term effects, increased morbidity and mortality, and cardiopulmonary effects (Bari et al. 2015; Chen et al. 2017; Wang et al. 2021a; Wang et al. 2021b). Environmental effects are based on indirect PM sources and inhaling PM directly can have a more severe effect. In addition, bystanders of ECIG user may be exposed to the compounds common to ECIG aerosols that are known to cause negative impacts on health through secondhand exposure (David et al. 2020; Logue et al. 2017; McGrath-Morrow et al. 2020). Due to the potential for negative health effects from exposure to secondhand ECIG aerosol, ECIG-generated PM concentrations are often measured using discrete and real-time monitors.

PM measurements are obtained using gravimetric analysis, which is considered the gold standard for air quality monitoring (Sousan, Regmi and Park 2021). The method uses filter samples to calculate time-weighted average (TWA) PM mass concentration by weighing the mass difference of PM accumulated on the filter at a specific flow rate and sampling time (Olegario, Regmi and Sousan 2021). However, gravimetric analysis is time-consuming and requires specialized laboratories to control the temperature within ±1°C and relative humidity between 30–50% with ± 5% variability (Hinds 1999). In addition, gravimetric analysis provides an average concentration value over the sampling time with no temporal information. On the other hand, light scattering monitors provide real-time PM mass concentration and are inexpensive to operate (Sousan et al. 2016b). Optical particle counters (OPCs) use the magnitude of light scattered from particles to count the number of particles per size (e.g., PM2.5) and calculate the mass concentration at different PM sizes. Photometers use light scattering from an assembly of particles passing at a specific angle to estimate mass concentration at a specific PM size based on a linear regression model. However, these devices require on-site filter correction as recommended by the manufacturer (GRIMM 2010; Sousan et al. 2016a; ThermoFisherScientific 2010). Multiple field and laboratory studies have measured ECIG PM2.5 concentrations in ECIGs discussed in the next paragraph.

Field studies have measured PM2.5 concentrations in indoor settings with active ECIG users using different aerosol monitors without filter correction. Schober et al. (2019) measured PM2.5 inside vehicles using the Grimm 1.108 OPC and a Grimm NanoCheck 1.320 to cover the entire particle size range and reported real-time concentrations up to ~6,000 μg/m3, Melstrom et al. (2017) measured PM2.5 inside a 52.6 m3 room using a SidePak photometer and a TSI P-Trak to examine the entire particle size range and reported concentrations up to ~19,000 μg/m3. Volesky et al. (2018) measured PM2.5 inside a 38 m3 office using a TSI DustTrak photometer at 0.5 and 1 m away from the participant and reported 289.5 and 246.9 μg/m3 mass concentrations, respectively. In contrast, Czogala et al. (2014) measured PM2.5 concentrations from machine-generated ECIG aerosol inside a 39 m3 chamber in laboratory settings using a SidePak and a filter calibration factor of 0.32 that has been used previously to examine cigarette smoke PM concentrations. This study reported PM2.5 concentrations up to ~1,000 μg/m3. However, cigarette smoke and ECIG aerosol have different aerosol size distributions, due to different aerosol mechanisms of generations, differences in refractive index between solid and liquid aerosols, and particle shape. Therefore, there is a need to identify new correction factors for ECIG aerosol.

The objective of this study was to calculate filter correction factor values for different ECIG devices and different PM optical monitors. In addition, this study will provide considerations for researchers looking to measure aerosol concentrations for future studies using different real-time aerosol monitors. First, the filter correction factors were calculated for different particle sizes of three real-time monitors for five different ECIGs: one box mod (VooPoo Drag 2), two pod mods (JUUL, 5% nicotine concentration label and NJOY Ace), and two disposable ECIG devices (NJOY Daily and Hyde). Then, the aerosol size distributions of the five different ECIGs were measured.

Material and Methods

Five ECIGs were used to generate PM inside an airborne-controlled laboratory chamber to measure PM1, PM2.5, and PM10. Measurements were performed with discrete gravimetric analysis to measure the reference and real-time optical monitors to capture temporal variability. Finally, the equipment used in this section to achieve the required measurements will be described.

Real-time Reference Monitors

MiniWRAS Real-time Monitor

The specifications of the real-time equipment used in the study are listed in Table S1 in Supplemental Information. The GRIMM Mini Wide-Range Aerosol Spectrometer (MiniWRAS 1371, Grimm Aerosol Technik, Ainring, Germany) is a high-cost (>$30,000) real-time monitor that measures PM in a wide particle size range between 0.01 μm and 35 μm in 41 number count bin sizes. The device was chosen because it can measure the entire size range of PM and calculate PM1, PM2.5, and PM10, which was required for this study. The device uses two technologies to examine this size range: an optical monitor for particles larger than 0.25 μm and a corona charger to measure particles 0.25 μm and smaller. The MiniWRAS uses different laser powers to detect particles smaller than 2.5 μm, compared to larger particles, to achieve reliable estimates for these smaller sizes (Sousan, Regmi and Park 2021). The device samples air at a flow rate of 1.2 L/min and measures PM mass concentration between 0-100,000 μg/m3. The MiniWRAS is an evolved Grimm 1.108 OPC modified to measure particles smaller than 0.25 μm that cannot be detected with optical science. The MiniWRAS was set to record data with a 1-minute frequency.

pDR 1500 Real-time Monitor

The personal DataRAM (pDR 1500, Thermo Scientific, Franklin, MA, USA) is a medium-cost (~$7,000) real-time photometer that measures PM at a specific size using a cyclone operated at a specific flow rate. The device was chosen because it is equipped with a built-in 37 mm filter holder that can be used to collect PM for gravimetric analysis. The device measures PM mass concentration between 0-400,000 μg/m3. Two pDRs were used for this study to measure PM2.5 and PM10, equipped with 2.5 and 10 μm (50% cut-point) cyclones and flow rates of 1.52 and 1.19 L/min, respectively. The pDRs were set to record data with a 1-second frequency.

SidePak Real-time Monitor

The SidePak Personal aerosol monitor (AM520, TSI Inc., Shoreview, MN, USA) is a medium-cost (~$5,000) real-time photometer that measures PM at a specific size using an impactor. The device was chosen due to its relatively lower cost and greater usage among the ECIG and cigarette researcher community (Czogala et al. 2014; Jiang et al. 2011; Klepeis, Ott and Switzer 2007; Melstrom et al. 2017). The device samples air at a flow rate of 1.8 L/min and measures PM mass concentration between 0-100,000 μg/m3. The SidePak was used to measure PM2.5 equipped with a 2.5 μm (50% cut-point) impactor. The SidePak was set to record data with a 1-second frequency.

Discrete PM Measurement

An SCC 0.695 cyclone (BGI, INC, Waltham, MA, USA) was used to measure PM1. The SCC 0.695 cyclone was operated with an SKC AirChek TOUCH (SKC Inc., Cat. No. 220-5000TC, Eighty Four, PA, USA) air sampling pump at a flow rate of 1.8 L/m. The cyclone and pump were calibrated daily using a calibration shroud (BGI, Item number: 188303, Waltham, MA, USA) and chek-mate calibrator (SKC Inc., Cat. No. 375-0550N, Eighty Four, PA, USA).

Gravimetric Analysis

The pDRs and the discrete PM method were equipped with a 37 mm fiberglass filter (Whatman, CAT Non.1827-037, Maidstone, United Kingdom) to collect mass for gravimetric analysis. The filters were pre- and post-weighed using a Mettler Toledo microbalance (Model: XPR6UD5, Columbus, Ohio, USA) and an anti-static kit with a large U-electrode (Model: 63052302, Mettler Toledo, Columbus, Ohio, USA). The filter mass concentration was calculated by dividing the difference between the filter mass pre- and post-weight with the flow rate and sampling time. In addition, the filters were equilibrated for temperature and relative humidity inside the balance room at 22±1 °C and between 45±5%, respectively (Hinds 1999).

Experimental Setup

Chamber Description

Experiments were conducted inside the Research Aerosol Laboratory located at East Carolina University. The laboratory contains an airtight 0.5 m3 exposure chamber used for controlled aerosol generation and assessment, as shown in Figure 1. The chamber was split in half, where the first half represented the mixing zone (0.25 m3 in size) and the other half the sampling zone (0.25 m3 in size). Particle-free air was supplied at a flowrate of 1.00 m3/min to the mixing zone using two (HEPA) filters with 99.99% efficiency. The chamber was flushed with particle-free air between experiments (Sousan, Regmi and Park 2021). Air was removed from the chamber using a vacuum that included two HEPA filters for aerosol removal and a carbon filter for gas removal. During the experiments, the inlet dilution air to the chamber and vacuum was turned off to increase the mass concentration inside the sampling zone. This was done as dilution air prevented the filters from achieving the limit of detection. A honeycomb flow straightening section separated the two zones (AS100, Ruskin, Grandview, MO, USA) used to create an even distribution in the sampling zone by mixing the air with two fans, operated at a flow rate of 0.20 m3/min in the mixing zone. The fans were operated during the experiment and when the chamber was flushed with dilution air in between experiments. The aerosol homogeneity of the sampling zone was tested before the experiment by placing four real-time optical aerosol monitors in the middle and sides of the zone while measuring salt aerosol concentration, and the average differences were ~9% for both positions. The pDR, SidePak, and SCC 0.695 cyclone were positioned in the sampling zone of the chamber. The MiniWRAS was positioned outside the chamber and sampled air directly from the sampling zone using an isokinetic tube. The AirChek TOUCH pump was positioned outside the chamber and was attached to the cyclone with a tube. Temperature and relative humidity inside the chamber were maintained at 22±2 °C and 45±5%, respectively.

Figure 1:

Figure 1:

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Experimental setup used to measure E-CIG exposure of Different Vaping Devices

Aerosol Generation

The ECIGs used in the current study are shown in Table S2 in the Supplemental Information. Five ECIGs readily available in the market were used in this study that included a “box mod” device (VOOPOO DRAG 2; (VAPING 2021)), two “pod mod devices” (JUUL (JUUL 2021)); NJOY Ace (NJOY 2021), and two disposable ECIG devices (NJOY Daily (NJOY 2021); Hyde Original (Hyde 2021)). The VooPoo Drag 2 has a refillable tank loaded with Hawaiian POG flavored liquid (30/70 propylene glycol/vegetable glycerin ratio, 3 mg/ml nicotine concentration) liquid (PerfectVap 2021). During the experiments, a UFLORCE U4 (0.23 Ω) coil was used and the device was set to operate at a default wattage of 70 W. The JUUL and NJOY Ace have replaceable pods, and the Hyde and NJOY Daily are disposable products. Aerosols were generated using a diaphragm pump (Thomas 1420-0504, Gardner Denver, Davidson, NC, USA), and a clock generator (TFIS 12-240VUC 1CO CG, Weidmüller Interface GmbH & Co. K.G., Detmold, Germany). The clock generator was used to control the ECIG puffing time. The pump generated 4 seconds puffs with an interpuff interval of 30 seconds, similar to puffing data reported from ECIG users (Hiler et al. (2020). The diaphragm pump flow rate differed between the ECIGs with 1-1.5 L/m for the pod mods and disposable devices (Vargas-Rivera et al. 2021) and 8.5 L/m for the VooPoo Drag 2 (Hiler et al. 2020). The experiments were repeated three times with each ECIGs.

Data Analysis

Real-Time Mass Concentrations

PM concentrations measured from the pDRs and the SidePak were averaged over 1 minute and paired with the MiniWRAS, which was collected for 1 minute. Box and Whisker plots of each sensor, MiniWRAS, pDR, and SidePak were plotted for PM1, PM2.5, and PM10. PM concentrations measured by particle size were PM1, PM2.5 and PM10 from the MiniWRAS, PM1 and PM2.5 from the pDR, and PM2.5 from the SidePak.

Filter Correction Factors

Filter correction factors were calculated for each PM monitor, particle size, and ECIG device by dividing the discrete filter mass concentration by the average real-time mass concentration measured by the PM monitors.

Aerosol Size Distribution

The aerosol size distribution by mass was captured with multiple devices in separate experiments listed in the previous sections. The first device was the MiniWRAS that captures the distribution in 41 bins. To compare the MiniWRAS measurements, a high-cost reference instrument, the Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, ~$91,000, TSI, Shoreview, Minnesota, USA) coupled with the Optical Particle Sizer (OPS 3330, ~$16,000, TSI, Shoreview, Minnesota, USA) were used. The SMPS has 191 bins measuring particle size using electrical mobility, compared to the MiniWRAS, which has 41 bins, 10 electrical and 31 optical. The optical science measures the remaining bin sizes. The SMPS system includes a 3082 electrostatic classifier, 3081A Long Differential Mobility Analyzer, 3756 Ultrafine Condensation Particle Counter, and an advanced aerosol soft Xray neutralizer. The SMPS was operated at an aerosol and sheath flows of 0.3 L/min and 2 L/min, respectively. The SMPS uses electric mobility to measure submicron particles between 0.001 and 1.0 μm. The SMPS was operated with a 0.0508 cm impactor and a 50% cut-point of 0.72 μm. Therefore, the OPS that incorporates optical science to capture the number size distribution between 0.3 and 10 μm in up to 16 channels was used. The OPS operates at an aerosol and sheath flow of 1.0 L/min each. The SMPS and OPS were positioned outside the chamber while sampling air directly from the sampling zone in Figure 1. The SMPS and OPS were set to record data with a 1-minute frequency. The SMPS and OPS were used once with the MiniWRAS for each ECIG generation method, except for the NJOY Ace, where only the SMPS and MiniWRAS were available at the time of the experiment. Therefore, the SMPS+OPS data for the NJOY Ace measurements were not provided.

TSI provides the Multi-Instrument Manager (MIM) software (version 3.0) to perform the SMPS and OPS data curve fitting using a lognormal distribution function. The default automated curve fitting options were used for these calculations. The mass median diameter (MMD) and geometric standard deviation (GSD) were tabulated for the MiniWRAS, SMPS, OPS, and the curve fitted data. The aerosol size distribution for MiniWRAS and the SMPS+OPS fitted data were plotted for each ECIG generation method. Particle size was converted to volumetric particle diameter for all monitors. PG and VG, once aerosolized, generate liquid particles, and those aerosol particles are spherical in shape. Therefore, this study assumed the shape factor as 1 for all aerosol generated from different ECIG types (Hinds 1999). The density was assumed as 1.16 g/ml, based on a one-to-one ratio of P.G. (1.04 g/ml) and V.G. (1.27 g/ml) (Sleiman et al. 2016)

Results and discussion

The diaphragm pump flow rates, the clock generator vaping time for the ECIGs, and experiment times for this study are listed in Table 1. The disposables and the pods were set to operate at 1 L/m, however, measurable PM with the JUUL and two of the Hyde experiments at that desired flow could not be achieved, so the flow rate was increased to 1.5 L/m. As a result, the generation time for each ECIG was 15 minutes for VooPoo Drag 2 and 30 minutes for NJOY Ace, NJOY Daily, and Hyde. The JUUL experiments deviated from the other ECIG generation methods, where the puffing time of 5 seconds and generation of 60 minutes was chosen because the filter limit of detection at 4-second puffs and 30-minute generation time was not achieved. In addition, all the JUUL pods were used for 30 minutes before the experiments, where new pods did not generate sufficient mass on the filters to exceed the limit of detection. In contrast, 15 minutes and 4 puffs were sufficient for the VooPoo Drag 2 to exceed the filter limit of detection.

Table 1.

Settings for Different E-CIG Devices

Flow
(L/min)		 Puffs
(ON/OFF
)
[seconds]		 Experim
ent Runtime
[minutes]		 Liquid
Ratio of
ECIG
(P.G./V.G.)		 Po
wer
(W)		 Heate
r
Resistanc
e (Ω)		 Vol
tage
(V)
VooPoo Drag 2 8.5 4/30 15 35/65 701 0.23 7.51
JUUL 1.5 5/30 60 27/732 0.62-4.082 1.832 1.13-2.722
NJOY Ace 1.0 4/30 30 NA3 NA3 NA3 NA3
NJOY Daily 1.0 4/30 30 NA3 NA3 NA3 NA3
Hyde 1.0-1.5 4/30 30 19/814 8.284 1.754 3.814
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1)

Displayed on the device (not measured)

3)

NA: Not Available in the literature or the manufacturer’s website.

Real-Time Mass Concentrations

The non-filter-corrected raw real-time data for the MiniWRAS, pDR, and SidePak with their respective particle sizes measured during the experiments are shown in Figure 2. The PM monitors reported different concentrations between devices and for each ECIG generation method. The average PM2.5 concentrations as measured by the MiniWRAS were as follows: VooPoo Drag 2 (1,775 μg/m3) , JUUL (323 μg/m3), NJOY Ace (1,389 μg/m3), NJOY Daily (806 μg/m3) and Hyde (1,309 μg/m3); as measured by the pDR were as follows: VooPoo Drag 2 (13,365 μg/m3), JUUL (1,388 μg/m3), NJOY Ace (5,966 μg/m3), NJOY Daily (3,157 μg/m3), and Hyde (4,086 μg/m3); and as measured by the SidePak were as follows: VooPoo Drag 2 (55,339 μg/m3), JUUL (4,632 μg/m3), NJOY Ace (20,254 μg/m3), NJOY Daily (12,028 μg/m3) and Hyde (8,846 μg/m3). The lowest measurements for the ECIGs were for the PM1 JUUL concentrations as follows: MiniWRAS (148 μg/m3), pDR (289 μg/m3), and SidePak (340 μg/m3), and the highest measurements were for the PM10 VooPoo Drag 2 concentrations as follows: (2,446 μg/m3), (21,213 μg/m3), (79,310 μg/m3).

Figure 2:

Figure 2:

Figure 2:

Figure 2:

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Size-selective Box-Whisker plots for A) MiniWRAS, B) pDR, and C) SidePak. The MiniWRAS measures PM1, PM2.5, and PM10, whereas two pDRs were used, one for PM2.5 and the other for PM10 measurements, and the SidePak only measured PM2.5. The measurements represent non-filter-corrected raw data.

The VooPoo Drag 2 ECIG generated the highest PM concentrations in all sizes and the JUUL generated the lowest concentrations. The SidePak monitor reported the highest average PM2.5 concentrations with values 31 and 4 times higher than the MiniWRAS and pDR, respectively, when compared using the VooPoo Drag 2. The average PM2.5 and PM10 measurements within the same monitor were comparable for the MiniWRAS and pDR measurements for all ECIG generation methods. For the MiniWRAS PM1 average measurements, the values were similar to the PM2.5 and PM10, except for differences for the Hyde generation of 126 μg/m3. The PM2.5 average concentrations for the pDR indicated that values were mostly smaller than 2.5 μm for all ECIGs. In contrast, the MiniWRAS PM1 concentrations indicated that values were mostly below 1 μm for all ECIGs, especially for Hyde, indicating PM1 and PM2.5 concentrations were not the same. The high concentrations exhibited by the VooPoo Drag 2 were most likely due to the high wattage utilized by the device which resulted in more ECIG liquid being aerosolized. In contrast, the wattages of the disposables or the JUUL were not measured, but the JUUL (Talih et al. 2020), and other disposable vapes (Talih et al. 2021) operate at lower wattage. Previous research has shown that high device wattage is associated with greater particulate matter production (Talih et al. 2017).

Aerosol light scattering instruments are valuable tools used to estimate real-time mass concentration (Hinds 1999). However, light scattering is sensitive to different parameters such as refractive index, scattering angle, particle size and particle shape. In addition, these monitors are usually manufactured with default parameters representing ideal laboratory conditions. Therefore, aerosol monitor manufacturers recommend creating an onsite filter calibration factor using gravimetric analysis to correct the real-time measurements (GRIMM 2010; ThermoFisherScientific 2010). Studies have also used refractive index correction to the intensity of light measured using these real-time monitors (Ingebrethsen, Cole and Alderman 2012; Liu and Daum 2000; Rosenberg et al. 2012). The current work uses gravimetric analysis to correct light scattering disadvantages as recommended by instrument manufacturers and adopted by different studies (Burkart et al. 2010; Czogala et al. 2014; Sousan, Regmi and Park 2021; Wang et al. 2016). The data presented in Figure 2 represent the raw real-time mass concentrations biased due to differences in light scattering parameters. However, the data can be corrected using the filter correction factors developed in the next section. Therefore, the next paragraph compares raw data from this work with raw real-time data from previous studies.

While other studies focus on PM2.5, the current study also examined PM1 and PM10. Schober et al. (2019) examined secondhand ECIG exposure inside vehicles and measured PM2.5 using the Grimm 1.108 OPC. Participants in this study used an ECIG inside of a vehicle taking 4-second puffs. The researchers reported an average PM2.5 range of 8-490 μg/m3 between vehicles. In comparison, in this study, the average PM2.5 concentration measured by the MiniWRAS for the NJOY and JUUL experiments were 804 and 321 μg/m3, respectively, with higher values for the VooPoo Drag 2 and Hyde. Melstrom et al. (2017) performed secondhand ECIG exposure inside a ~53 m3 room and measured PM2.5 using a SidePak. The participants used a disposable and tank-style ECIG, and the study reported PM2.5 concentrations up to 19,961 and 19,972 μg/m3, respectively, for both devices. Similarly, the SidePak in the current study reported up to 21,800 μg/m3 PM2.5 concentration. However, this study did not use participants to generate ECIG secondhand aerosol. Rather a diaphragm pump was used to simulate aerosol vaping at the same flow rates provided from the literature. Therefore, these results might differ if participants are recruited to vape inside the chamber.

Filter Correction Factors

The filter correction factors and standard deviation of the MiniWRAS, pDR, and SidePak for each particle size and ECIG are shown in Table 2. The correction factors were different between devices. A correction factor of 1.0 indicates that the average real-time concentration of the optical monitor is equal to the discrete filter measurement. A correction factor above unity or below unity indicates that the monitor underestimates or overestimates the discrete filter measurement, respectively. The correction factor range between ECIGs and particles sizes was 0.64-6.01 for the MiniWRAS, 0.41-0.80 for the pDR, and 0.13-0.20 for the SidePak. In general, the MiniWRAS underestimated the true mass (filter) concentration for all particle sizes and ECIGs, except for the Hyde PM1 concentrations. The lowest underestimation was with the Hyde ECIGs, where values were within ±40% around unity, and the highest underestimation was with VooPoo Drag 2 with values up to 500% above unity (1.0). The pDR and SidePak both overestimated all particle sizes, but the SidePak exceeded the pDR values. The pDR overestimation was variable with 20% and 60% below unity for the VooPoo Drag 2 and Hyde, respectively. The SidePak underestimation was consistent with an ≥80% value below unity. In comparison between particle sizes for the same monitor, the MiniWRAS and pDR have similar correction factors for PM2.5 and PM10, but the MiniWRAS PM1 values were lower than PM2.5 and PM10 for all ECIG generation methods. The MiniWRAS high underestimation values for the VooPoo Drag 2 are because the device does not handle high concentrations for particles 0.25 μm and smaller. Instead, the manufacturer recommends an aerosol diluter that could cost up to $5,000 if purchased from Grimm. The pDR performed better than the SidePak because the manufacturer calibrates the former to operate with four times higher mass concentrations than the SidePak.

Table 2.

Correction factors for instruments of each particle size and ECIG device. The average and standard deviation were computed based on three experiments.

PM Sensor-Size Average Standard Deviation
 A) VooPoo Drag 2
 MiniWRAS PM1 3.99 2.05
 MiniWRAS PM2.5 6.01 0.27
 MiniWRAS PM10 5.48 0.32
 pDR PM2.5 0.80 0.08
 pDR PM10 0.69 0.04
 SidePak PM2.5 0.18 0.01
 B) JUUL
 MiniWRAS PM1 1.72 0.11
 MiniWRAS PM2.5 1.90 0.46
 MiniWRAS PM10 2.05 0.60
 pDR PM2.5 0.59 0.10
 pDR PM10 0.59 0.14
 SidePak PM2.5 0.13 0.02
 C) NJOY Ace
 MiniWRAS CF PM1 2.15 0.53
 MiniWRAS CF PM2.5 2.66 0.36
 MiniWRAS CF PM10 2.56 0.26
 pDR CF PM2.5 0.67 0.08
 pDR CF PM10 0.62 0.10
 SidePak CF PM2.5 0.19 0.02
 D) NJOY Daily
 MiniWRAS PM1 1.42 0.46
 MiniWRAS PM2.5 2.52 0.78
 MiniWRAS PM10 2.28 0.63
 pDR PM2.5 0.68 0.07
 pDR PM10 0.58 0.07
 SidePak PM2.5 0.18 0.01
 E) Hyde
 MiniWRAS PM1 0.64 0.11
 MiniWRAS PM2.5 1.38 0.24
 MiniWRAS PM10 1.30 0.14
 pDR PM2.5 0.45 0.09
 pDR PM10 0.41 0.03
 SidePak PM2.5 0.20 0.06
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In comparison with this study, Czogala et al. (2014) performed ECIG aerosol exposure inside a 39 m3 chamber and measured PM2.5 using the SidePak AM510 while applying a correction factor of 0.32. The correction factor used in the study was based on previous studies investigating regular cigarettes with the SidePak. ECIG exposure was generated using a vaping machine with a duration of 1.8 seconds ON and 10 seconds OFF for 1 hour using three ECIG popular brands sold in Poland. The researchers reported PM2.5 concentrations up to 1,000 μg/m3. The correction factors calculated for this study for the SidePak were between 0.13 and 0.2 for different ECIGs, and the maximum concentration reached by the filter corrected JUUL PM2.5 concentration was 1,074 μg/m3. The slight difference between the correction factors could be attributed to the type of exposure, ECIG compared to regular cigarettes and the SidePak models, where the SidePak AM520 model was used in this study. Therefore, SidePak has a higher correction for ECIGs compared to regular cigarettes, and all monitors have different correction factors depending on the ECIG used.

Aerosol Size Distribution

The MMD, volumetric diameter, and GSD values for the SMPS, OPS, SMPS+OPS fitted data, and MiniWRAS are shown in Table 3. In addition, the aerosol size distribution by mass for the SMPS+OPS fitted data and MiniWRAS are shown in Figure 3. The MMD range between ECIGs was 0.22-0.28 μm for the SMPS, 0.41-0.62 μm for the SMPS+OPS, and 0.37-0.5 μm for the MiniWRAS. The SMPS captured MMD values with an average of 0.24±0.03 μm for all ECIG generation types. However, the SMPS was only set to measure particles smaller than 0.72 μm. Therefore, the SMPS+OPS fitted data was a better comparison with the MiniWRAS. The MMD values for the SMPS+OPS fitted data and the MiniWRAS were similar for the VooPoo Drag 2, JUUL, and NJOY Daily, with differences between 0.03 and 0.07 μm. In contrast, for the Hyde ECIG generation, the SMPS+OPS fitted data MMD value was slightly higher at 0.62 μm, compared to 0.5 μm for the MiniWRAS. In addition, the SMPS+OPS aerosol size distribution for VooPoo Drag 2, NJOY, and JUUL shows the particles are smaller than 1 μm for both datasets. In contrast, Hyde's SMPS+OPS aerosol size distribution shows that some particles are larger than 1 μm but smaller than 2.5 μm. These results align well with Figure 2-A, MiniWRAS results, where PM2.5 and PM10 concentrations are higher than PM1 for Hyde ECIG generation, but PM1, PM2.5, and PM10 concentrations are similar for VooPoo Drag 2, NJOY, and JUUL. The slight difference between the SMPS+OPS fitted data and the MiniWRAS for the Hyde aerosol size distribution and MMD could be attributed to the automated settings for the MIM software that can be changed. Finally, it is important to mention that the aerosol size distribution data provided in Table 3 and Figure 3 does not take into account the refractive index differences between ECIG types for the OPS and the larger bins (≥0.25 μm) of the MiniWRAS (Ingebrethsen, Cole and Alderman 2012). In addition, studies have shown that the dilution factor used in electrical mobility monitors to estimate particle size cause P.G. and V.G. evaporation and shifts the aerosol size distribution to smaller particle sizes for the SMPS and smaller bins (<0.25 μm) of the MiniWRAS (Kane and Li 2021).

Table 3.

The MMD and GSD for each E-CIG device based on the SMPS, OPS, and SMPS+OPS fitted data. The average and standard deviation (between brackets) were computed based on three measurements.

SMPS OPS SMPS+OPS
(Fitted Data)		 MiniWRAS
Device MMD
(μm)		 G
SD		 MMD
(μm)		 GS
D		 MMD
(μm)		 G
SD		 MMD
(μm)		 G
SD
VooPoo Drag 2 0.22(0.01) 2.5 0.40(0.01) 1.5 0.43(0.01) 1.2 0.40(0.02) 1.4
JUUL 0.25(0.01) 2.0 0.37(0.01) 1.5 0.41(0.01) 1.2 0.37(0.01) 2.2
NJOY Ace 0.22(0.02) 2.1 - - - - 0.47(0.01) 1.5
NJOY Daily 0.23(0.01) 2.2 0.42(0.01) 1.5 0.46(0.01) 1.4 0.39(0.01) 1.8
Hyde 0.28(0.01) 2.0 0.50(0.01) 1.5 0.62(0.01) 1.6 0.50(0.02) 1.9
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Figure 3:

Figure 3:

Figure 3:

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Aerosol size distribution by mass for the A) SMPS+OPS fitted data and B) MiniWRAS for the different ECIG devices. The x-axis represents the volumetric particle diameter. Each curve's average and standard deviation were computed based on three measurements. The y-axis represents the standard deviation of the three measurements.

In comparison with this study, Sundahl, Berg and Svensson (2017) measured MMD, aerodynamic diameter, using a Next Generation Pharmaceutical Impactor (NGI) and a custom-made aerosol generation for 13 popular ECIG brands sold in the United Kingdom. The NGI reported different MMD values between 0.53 and 0.96 μm. The MMD values measured for this study were lower between 0.41 and 0.62. However, the volumetric diameter was reported compared to the aerodynamic diameter presented by Sundahl, Berg and Svensson (2017). When converted from the volumetric diameter, the aerodynamic diameter has a higher value (Peters et al. 1993). Therefore, MMD values for both studies are comparable.

Filter correction factors are crucial for real-time PM monitors, where aerosol manufacturers recommend on-site calibration with gravimetric analysis to increase the accuracy of the measurements (Sousan et al. 2018). This study calculated filter correction factors for ECIG aerosol exposure of three PM monitors, the MiniWRAS, pDR, and SidePak, for five mainstream ECIGs and different particle sizes. The correction factors were measured in an exposure chamber using a diaphragm pump. Real-life scenarios with participants vaping could yield different results. Therefore, researchers should use the filter correction factors calculated from this study with caution in real-life scenarios. Future work should be performed to compare these results with real-life scenarios.

Conclusion

This study shows that correction factors must be developed for different ECIGs and different optical monitors. In addition, this study shows that the ECIG particles were smaller than 1 μm for most PM generated from the ECIGs examined. Previous studies have focused on PM2.5; however, due to the rising interest in PM1 and its health effects, attention should be brought to this particle fraction (Bari et al. 2015; Wang et al. 2021a). Further research and focus on exposure to PM1 generated from ECIGs is needed to take into account the refractive index differences of ECIGs for optical monitors and dilution factors that cause particle size misclassification for electrical mobility monitors. In addition, the study illustrates that the pDR, with the built-in filter that can be used for gravimetric analysis, has better performance and is a better solution for ECIG exposure monitoring than the SidePak. However, the pDR can only measure one particle size during operation, compared to the MiniWRAS that can measure different particle sizes and provide number concentration and aerosol size distribution. Therefore, given the price differences, the pDR is a better solution as a photometer, but the MiniWRAS is a comprehensive mobile solution given the price range is not an obstacle, and the aerosol concentrations are not considerably higher. The SidePak performs well and maybe a more cost-effective for researchers looking to monitor secondhand ECIG exposures in real-world settings.

Supplementary Material

Supp 1

Acknowledgments

The authors would like to thank Dr. Timothy Wright, formerly of North Carolina State University, for his help during this study

Funding

This research is supported by grant number R15ES032138 from the National Institute on Environmental Health Sciences of the National Institutes of Health. Part of E.S.’s efforts is also supported by grant numbers U54DA036105 from the National Institute on Drug Abuse and R21CA239188 from the National Cancer Institute of the National Institutes of Health and the Center for Tobacco Products (CTP) of the U.S. Food and Drug Administration. The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH or the FDA.

Footnotes

Conflict of Interest: Eric Soule is named on a patent for a device that determines electronic cigarette device and liquid characteristics.

Data Availability Statement:

The datasets generated from the current study are available from the corresponding author on reasonable request.

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Associated Data

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Supplementary Materials

Supp 1
NIHMS1798416-supplement-Supp_1.docx (17.2KB, docx)

Data Availability Statement

The datasets generated from the current study are available from the corresponding author on reasonable request.

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