1. Introduction
Electronic cigarettes (“e-cigarettes” or “e-cigs”) have been rapidly growing in popularity in recent years, which has raised a great deal of concern about the health risks associated with vaping [
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13]. A considerable amount of studies have reported carcinogenic compounds, and trace metals in e-cigarette aerosols [
7,
8,
9,
12,
14,
15,
16,
17,
18,
19,
20,
21,
22]. In some cases, the concentrations of these harmful contents are even higher in e-cigarette aerosols than in traditional cigarette smoke [
7,
14,
15,
18,
19]. Inhalation of these chemicals has been associated with the development of multiple negative health conditions, including but not limited to heart disease, lung cancer, stenosis, asthma, and hypertension [
7,
8,
9,
20]. The health risks of vaping have been reported to be even more prevalent among youth and children [
3,
5,
7,
9,
20,
23,
24].
In e-cigarette aerosol, the actual amounts of various chemicals and the particle size distributions of airborne particles, known as particulate matter (PM), are determined by two main aspects: the e-cigarette device, including hardware and e-liquid, and the user’s vaping habits. The aerosols generated depend on the type of e-cigarette device (such as disposable, rechargeable, cartridge, pod, mod, etc.), e-liquid compositions (including propylene glycol, vegetable glycerin, flavoring agents, and nicotine), and the e-cigarette brand/manufacturer [
5,
8,
9,
16,
17,
25,
26,
27,
28]. E-cigarettes are often believed to be less lethal than combustible tobacco and are considered beneficial for cessation of traditional smoking. One study showed that the levels of certain carcinogens and toxicants in e-cigarette aerosols can be one to two orders of magnitude lower than those in traditional cigarette smoke [
15]. However, due to the diversity and variety of e-cigarette products and the lack of manufacturing standards and quality controls, the actual e-cigarette aerosols can vary widely [
5]. Poorly manufactured e-cigarettes and e-liquids can generate even more harmful constituents than traditional cigarettes [
1]. The regulation of e-cigarette products is currently seen as a significant challenge by government agencies, such as the U.S. Food and Drug Administration (FDA) [
29].
Given a specific e-cigarette device and e-liquid, the e-cigarette aerosol properties and nicotine yields are further decided by the user’s personalized vaping habits, known as puff topography [
18,
25,
30,
31,
32,
33,
34,
35,
36]. In general, a user’s e-cigarette puff topography can be quantified by parameters, such as puff numbers, puff frequencies, inter-puff intervals, puff durations, puff flow rates, and puff volumes [
25,
30,
31,
36]. Several studies have investigated the puff topography and nicotine intake of different e-cigarette user groups [
30,
31]. Korzun et al. studied the effects of flow rates on toxicants in e-cigarette aerosols and e-liquid consumption [
37]. Floyd et al. also reported the effects of flow rates on e-cigarette outputs [
35,
36].
From a broader perspective, puff topography should further include the user’s preferred device operational conditions [
36]. Atomizer coil power, coil resistance, and coil temperature are known to strongly influence the e-cigarette aerosol outputs [
25,
32,
36,
38,
39,
40]. Zhao et al. studied the variations in e-cigarette aerosols under different coil temperatures [
32]. Farsalinos et al. reported changes in users’ puff topography due to different power settings [
34]. Floyd et al. revealed the effects of atomizer coil power on particle size distribution and the ratio between finer and bigger particles [
38]. Pourchez et al. studied the effects of atomizer coil power and e-liquid compositions on aerosol output [
41]. Mulder et al. demonstrated that e-cigarette aerosol particle size distributions and nicotine yields are strongly dependent on both battery voltage and coil resistance [
39]. Lechasseur et al. investigated the effects of coil temperature, coil power, and e-liquid types on particle size distribution and lung deposition from e-cigarette aerosols [
40].
To better understand the long-term adverse health consequences of vaping, it is essential to measure and track the personalized puff topography for all e-cigarette users. The puff topographies of many e-cigarette users represent potentially harmful vaping behaviors. For example, certain e-cigarette users have strong nicotine cravings and tend to overheat the e-liquids, which can cause the users to inhale very harmful carcinogenic constituents produced from the thermal decomposition of e-liquids at temperatures that are too high [
6]. If puff topography can be monitored closely, puff by puff, users can be warned about such device misuse, potentially leading to modifications in their vaping behaviors towards healthier habits. To mitigate the health risks of vaping, there is a high demand for topography sensors built inside e-cigarettes that can monitor the user’s daily puff topography. Such topography sensors must be compact, low-cost, and compatible with mainstream e-cigarettes. In existing e-cigarette devices, the puff number, puff frequency, inter-puff interval, and puff duration can all be attained by monitoring the activation of the atomizer. Some e-cigarette brands can also automatically measure the coil resistance and record the power setting of the coil. Built-in airflow and pressure sensors, which are quite common in many e-cigarettes, activate the atomizer when the user inhales [
2,
5]. Such sensors can be used to monitor the puff flow rate and puff volume [
36].
In existing studies on e-cigarettes, the properties of generated e-cigarette aerosols have been treated as a consequence resulting from the user’s puff topography [
18,
25,
30,
31,
32,
33,
34,
35,
36]. Due to the aforementioned diversity of e-cigarette products and variations in vaping habits, direct measurements on the properties of e-cigarette output can potentially provide more valuable and reliable information than other parameters. Existing research methods typically implemented professional aerosol instruments or specially engineered topography devices to measure e-cigarette aerosols. Fast mobility particle sizer (FMPS), scanning mobility particle sizer (SMPS), and multi-stage micro-orifice uniform deposit impactor (MOUDI) were often implemented to measure the particle size distribution in e-cigarette aerosols [
18,
26,
32,
38,
39,
40,
42]. Liquid chromatography/mass spectrometry (LC/MS), gas chromatography/mass spectrometry (GC/MS), and high-performance liquid chromatography (HPLC) were popularly used for chemical analysis of e-cigarette aerosols [
23,
25,
30,
39]. There are also established protocols for studying e-cigarette aerosols, developed by the Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) [
43]. All these mentioned research methods require sophisticated, expensive, and bulky analytical instruments, and they are limited to studying e-cigarette aerosols in laboratories only. Several portable topography devices have been demonstrated, which allow in situ investigation of puff topography and aerosol properties [
31,
36,
44]. Dunkhorst et al. implemented laser light polarization ratio method to measure the mass median diameter (MMD) of e-cigarette aerosols [
44]. Floyd et al. developed a topography device based on Bernoulli flow cell to measure puff flow rate from differential pressure [
36]. Although these topography devices opened up new possibilities to study puff topography in situ, they are not yet suitable to be integrated inside e-cigarettes for tracking users’ daily puff topography.
Due to the significance of e-cigarette aerosol properties, we propose further broadening the concept of puff topography to include quantification parameters on aerosol properties, if such parameters can be directly measured from the e-cigarette device itself. Considering its implications on the health risks of vaping, it is potentially more crucial than all other existing puff topography parameters. Previously, our group introduced the concept of “smart e-cigarettes” with built-in aerosol sensors [
45]. Using a sensor assembly composed of a multi-wavelength photometric sensor and a gas sensor, the relevant aerosol properties, including the ratio between finer and bigger particles, the aerosol temperature, and the electrical resistance in response to volatile organic compounds (VOCs), were measured and tracked for every puff to analyze the user’s puff topography [
45]. In this article, we introduce a new functionality of this topography sensor, which can measure the aerosol output—defined as the mass of total particulate matter (TPM) in each puff—and estimate the nicotine yield puff by puff. This “mass of TPM” is similar to the “mass of vaporized e-liquid (MVE)” or “mass loss per puff” found in the literature [
35,
46], and the differences will be discussed in later sections. In this article, we demonstrate the concept of our e-cig topography sensor, the construction of the prototype, the calibration and validation of the sensor’s responses, and the experimental results on various e-cigarette device settings and tracking one user’s puff topography.
The mass of TPM has been widely studied in association with puff topography. The majority of existing studies have implemented gravimetric approaches to measure e-liquid consumption by weighing the relevant e-cigarette components, such as the entire device, the cartomizer/clearomizer, and the filter pad for aerosol sample collections, before and after the puffs [
6,
18,
25,
30,
34,
35,
37,
38,
39,
46,
47,
48]. Several studies have directly measured the mass of TPM in the generated aerosols using analytical aerosol instruments [
39,
41,
49]. Furthermore, external devices and experimental platforms have also been demonstrated. Wasisto et al. developed a piezoresistive cantilever sensor capable of measuring the mass of e-cigarette aerosols [
50]. Dunkhorst et al. demonstrated the real-time monitoring of the PM mass concentration of e-cigarette aerosols using wavelength-dependent mid-infrared light extinction [
51], and the polarization ratio method [
44]. Wu et al. implemented photometric detections to measure e-cigarette aerosol concentrations using a laser beam in a scaled-model experiment [
48]. These aforementioned examples are, by far, limited to in situ measurements of e-cigarette aerosols. It should be noted that none of the existing methodologies have enabled compact topography sensors to be built inside e-cigarettes.
2. E-Cig Topography Sensor Working Principle
Figure 1 shows the working principle of our e-cig topography sensor, which is integrated inside a smart e-cigarette device. A photometric sensor and a pressure sensor are both installed inside the aerosol delivery passage of the e-cigarette device to directly probe the aerosols from within the device. The purpose of the photometric sensor is to measure the real-time aerosol mass concentration,
. The function of the pressure sensor is to monitor the real-time volumetric aerosol flow rate,
.
The mass of TPM in a puff, defined as
, is given by:
where the integral is carried over the entire duration of the puff.
Photometric measurements for aerosols typically detect the intensity of light scattered from—or transmitting through—the aerosols, and the optical signal is then converted into a reading of the mass concentration of the PM according to a known calibration curve [
44,
48,
51,
52,
53]. In this work, the photometric sensor, as schematically shown in
Figure 1d, is comprised of multiple LEDs and a photodiode. We detect the aerosol concentration
through the optical signal
of the near-infrared light (wavelength centered at 880 nm) scattered from the high-concentration airborne particles in e-cigarette aerosols. The optical signal
is proportional to the optical power transmitted through the active area of the photodiode. Since the size of the active area is a constant value, the optical signal is proportional to the intensity of the scattered light.
Figure 1b shows an optical signal acquired from one puff. Consider the simplest scenario of the photometric measurement,
is approximately proportional to
, i.e.,
The pressure sensor measures the real-time absolute air pressure, given as
, inside the aerosol delivery passage from a location between the atomizer and the mouthpiece. When a user draws a puff at the mouthpiece of the e-cigarette, a differential pressure,
, referred to as “inhalation pressure” in this article, is applied between the air inlet and the mouthpiece to drive the flow of aerosol across the atomizer. Consider the pressure at the air inlet being equal to the ambient air pressure
, the inhalation pressure
.
Figure 1c shows the inhalation pressure acquired from the same puff associated with the optical signal in
Figure 1b. An e-cigarette aerosol is a pressure-driven turbulent flow and the flow rate is approximately proportional to the square root of the pressure drop [
36,
54]. For simplicity, if we ignore the effects of other factors, such as aerosol temperature, humidity, and concentration, the relationship between volumetric flow rate and inhalation pressure can be given as
Based on the relations given in Equations (
2) and (
3), the mass of TPM in the puff (
) in Equation (
1) can be given by
where
is a coefficient to be determined by calibrating the sensor according to known references. Based on
, the nicotine yield in the puff is estimated based on the weight concentration of nicotine in the e-liquid. For example, the sensor signals shown in
Figure 1b,c have measured a mass of 3.38 mg of TPM and estimated a nicotine yield of 35.5
g in the puff.
4. Discussion
Our e-cig topography sensor allows quantitative measurements of e-cigarette aerosols within the smart e-cigarette device, and such measurements have so far only been carried out in well-equipped laboratories or by using bulky topography devices. The results measured from our e-cig topography sensor matched well with the trends reported in existing studies, and the relative error is mostly lower than 9% for most of the trials. When examining all experimental results listed in
Table A3,
Table A4 and
Table A5, the summation of the mass of TPM measured by the e-cig topography sensor from all puffs is 296.87 mg, while the reference measurement result is 314.48 mg, which suggests an overall relative error of about 5.60%. Considering the compactness and simplicity of the sensor, the achieved accuracy is remarkable. Based on the experimental results, our e-cig topography sensor has promptly, conveniently, and accurately monitored the mass of TPM, puff by puff, over a wide range of settings, including atomizer power, puff duration, and inhalation pressure; this has never been demonstrated from sensors integrated inside e-cigarettes before. The success of our topography sensor stems from the strategy of combining multi-parameter sensors for concurrent pressure and optical measurements, similar to the strategies demonstrated for other health-related sensor applications [
57,
58].
The capability of our e-cig topography sensor can open up new avenues to monitor all e-cigarette users’ daily puff topography and mitigate the health risks of vaping. With our e-cig topography sensor, the mass of TPM and nicotine yield in every puff can be closely tracked, regardless of the setting of the device, the condition of the atomizer, and the user’s inhalation fashion. In particular, on certain types of e-cigarette devices, atomizer power control does not exist, making it impossible to quantify how much particulate matter and nicotine can be inhaled by the user. Since our sensor directly measures the aerosols of the e-cigarette output, it can directly function with such e-cigarette devices to make quantitative measurements. From the perspective of regulation, our e-cig topography sensor can be used for the quality control of e-cigarette products by comparing the measured mass of TPM with the predetermined ideal values for a given setting. When significant differences are detected, the user should be warned about the potentially malfunctioned device. For example, when the e-liquid is nearly empty in the tank and the atomizer is relatively dry, the mass of TPM in the generated e-cigarette aerosols will be different from normal. With our sensor, such a condition can be detected and the user will be notified. In addition, our e-cig topography sensor can also allow the nicotine dose to be tracked for every puff. Such a feature can be very useful for special e-cigarette devices designed for the cessation of smoking traditional tobacco.
In our work, the photometric measurement of the aerosol concentration is based on light scattering, and the mass concentration of aerosol is proportional to the intensity of scattered light, as illustrated in
Figure 1. Alternatively, the aerosol concentration can also be measured using a light transmission configuration, in which the concentration is proportional to the absorbance based on Beer–Lambert’s Law. The transmission scheme will be investigated in future work.
The “mass of TPM” measured from our topography sensor is similar to the “mass of vaporized e-liquid (MVE)” or “mass loss per puff” in literature [
35,
46], but there are also inherent differences. The vaporized e-liquid in each puff will form into PM and gas-phase components in the generated e-cigarette aerosol. Since our sensor is based on light scattering of near-infrared wavelength, only the PM significantly contributes to the optical signals and, thus, the reading of our sensor. The scattering from gas-phase components is negligible when compared to that from PM. The gas-phase components are important as they may contain VOC and other harmful gas-phase chemicals; however, they cannot be captured by our sensor reported in this article. Such gas-phase components can potentially be measured using specialized gas sensors. Ideally, the e-cig topography sensor should include both PM sensing and gas sensing functionalities, which will be studied in future work.
The optical signal and inhalation pressure shown in
Figure 1b,c, and
Figure 9c were acquired from the human subject, who drew the puff from the device. The optical signal is determined by the concentration of the generated aerosol, which is further controlled by the activation of the atomizer coil. At the end of activation, the current is turned off and the atomizer coil cools down quickly. As a result, the aerosol output decreases sharply and gives a steep falling edge in the optical signal. The inhalation pressure reflects the human subject’s inhalation pattern, which varies among different users. At the end of the inhalation, the human subject tends to relax, resulting in a gentle decreasing slope in the inhalation pressure.
One concern about our sensor’s performance is the adsorption of vaporized e-liquid on the surface of the optical sensor. From our experiments, we observed that the e-cigarette aerosol adsorbed on the optical sensor surface formed into a diffusing layer, which reduced the optical power transmitted to the photodiode. After running the e-cigarette for a few puffs, this layer of e-liquid reached a steady state, which gave a stable optical loss. Since our sensor was calibrated in this steady state, the effects of optical loss through this diffusing layer were compensated. Another concern is the limit of detection of the sensor for measuring the mass of TPM. We carried out experiments to estimate the limit of detection. We decreased the atomizer power to generate an aerosol with a smaller and smaller mass of TPM to find out the minimal mass that could be detected by the sensor. Based on these experiments, the limit of detection of our sensor is about 0.2 mg, which was attained using 8.5 W atomizer power, 2 s button-pusher duration, and 54 s box pressurization time. The relative error between our sensor and the reference measurement is about 7.71%. It should be noted that e-cigarette aerosols generated from mod-type devices usually have a mass of TPM that is much higher than this limit.
There are limitations in the prototype of the e-cig topography sensor presented in this work. Firstly, as observed from the results in
Figure 5,
Figure 6 and
Figure 7 and
Table A3,
Table A4 and
Table A5, the relative errors of the sensor’s readings, when compared with the reference measurements, grew to over 10% when either the optical signal or the inhalation pressure was too high. In this work, we implemented the simplistic mathematical model of the aerosol mass concentration versus optical signal and the flow rate versus inhalation pressure, given in Equations (
2) and (
3), respectively. The calibration coefficient was treated as a constant, which was attained using single-point calibration procedures. When the optical signal is too high, the aerosol concentration becomes excessive, and multiple scattering can lead to the saturation of the optical signal. When the inhalation pressure is too high, the flow rate requires additional corrections. These challenges can be solved by using more accurate mathematical models and advanced calibration procedures. In addition, the air temperature and the humidity can also affect the sensor’s reading. As previously mentioned, the air temperature can cause the optical sensor’s response to drift slightly. The humidity can affect the aerosol’s physical properties, which can also affect the reading. These parameters can potentially be monitored using BME680’s built-in temperature and humidity sensing functionalities to enable compensations for the effects of temperature and humidity. Secondly, the e-cig topography sensor’s calibration coefficient depends on the airflow resistance, as explained in
Section 3.4. In this work, the sensor has to be calibrated again after the removal and re-installation of the sensor components, which altered the airflow resistance slightly. This problem can be solved by accurately controlling the airflow resistance using specially designed orifices. Thirdly, since the breakout boards of sensors used in this prototype are on the centimeter scale, the constructed smart e-cigarette is larger than regular e-cigarette devices, as shown in
Figure 2d,e. The core components of the sensors are actually on the millimeter scale, as shown in
Figure 2c. Given a miniaturized circuit board optimally designed for the core sensor components, the size of the topography sensor can be scaled down to a few millimeters to directly fit into all mainstream e-cigarette devices or components, including compact vaping pods, cartomizers/clearomizers, and mouthpieces. Lastly, the e-cigarette aerosols can be further analyzed in parallel using analytical chemistry instruments to further study how different parameters affect the generated e-cigarette aerosols. These aforementioned potential approaches for enhancing our e-cig topography sensor will be explored in our future work.
Different compositions of e-liquids, such as varying ratios of PG to VG, and different flavoring agents, can influence the particle size distribution and the concentrations of the generated e-cigarette aerosols. In our experiments, we compared two different e-liquids, BB VAPES BRVND ENVY and BB VAPES BRVND KSPR, which have different flavors. After calibrating the sensor for the specific e-liquid, the sensor can deliver very consistent readings for that e-liquid. The calibration coefficients for these two e-liquids differ by about 8%. It should be noted that this variation in calibration coefficient is comparable with the level of uncertainty in the sensor’s response versus reference measurements. Further experiments are needed to investigate the effects of different e-liquids, which will be part of our future work.