Secondary indoor air pollution and passive smoking associated with cannabis smoking using electric cigarette device-demonstrative in silico study

A revision of the multiple-path particle dosimetry model focusing on tobacco product aerosol dynamics

To assess the health impact of inhaled aerosols, it is necessary to understand aerosol dynamics and the associated dosimetry in the human respiratory tract. Although several studies have measured or simulated the dosimetry of aerosol constituents, the respiratory tract focus areas have been limited. In particular, the aerosols generated from tobacco products are complex composites and simulating their dynamics in the respiratory tract is challenging. To assess the dosimetry of the aerosol constituents of tobacco products, we developed a revised version of the Multiple-Path Particle Dosimetry (MPPD) model, which employs (1) new geometry based on CT-scanned human respiratory tract data, (2) convective mixing in the oral cavity and deep lung, and (3) constituent partitioning between the tissue and air, and clearance. The sensitivity analysis was conducted using aerosols composed of four major constituents of electronic cigarette (EC) aerosols to investigate the parameters that have a significant impact on the results. In addition, the revised model was run with 4 and 10 constituents in ECs and conventional cigarettes (CCs), respectively. Sensitivity analysis revealed that the new modeling and the physicochemical properties of constituents had a considerable impact on the simulated aerosol concentration and dosimetry. The simulations could be carried out within 3 min even when 10 constituents of CC aerosols were analyzed simultaneously. The revised model based on MPPD is an efficient and easy-to-use tool for understanding the aerosol dynamics of CC and EC constituents and their effect on the human body.

The legalization of cannabis may result in increased indoor exposure to Δ9-tetrahydrocannabinol

Cannabis is a genus of plants in the Cannabaceae family that contains tetrahydrocannabinolic acid. When heated or burned, the acid decarboxylates to form tetrahydrocannabinol (THC). Its (-)-trans-Δ9-THC isomer is a psychoactive substance that has been used as a drug for centuries. In most countries, both the private sale of cannabis products and their use for non-medical purposes are still prohibited by law. However, for some time now there has been societal and political pressure to at least partially legalize cannabis products. It can be expected that such a measure will lead to a significant increase in the consumption of cannabis. However, this also increases the possibility of involuntary passive exposure to THC and contamination of the indoor environment. In indoor sciences, THC is still a largely unknown or underrepresented substance. In this perspective paper, THC will therefore first be presented on the basis of its physical properties. Then, the distribution of THC in different indoor compartments and potential routes of passive exposure are discussed. Finally, an assessment of the future importance of THC for indoor use is made. Previous experience has shown that early monitoring is always advantageous so that preventive and protective measures can be taken quickly if necessary.

Effect of transient breathing cycle on the deposition of micro and nanoparticles on respiratory walls

BACKGROUND AND OBJECTIVE

From various perspectives (e.g. inhalation exposure and drug delivery), it is important to provide insights into the behavior of inhaled particles in the human respiratory system. Although most of the experimental and numerical studies have relied on an assumption of steady inhalation, the transient breathing profile is a key factor in particle deposition in the respiratory tract. In this study, particle transportation and deposition were predicted in a realistic human airway model during a breathing cycle and the effects of steady-state and transient flows on the deposition fraction were observed using computational fluid dynamics.

METHODS

Two transient breathing cycles with different respiratory durations were considered to evaluate the effects of respiration duration on particle transport and deposition characteristics. Two types of steady breathing conditions with corresponding steady-state respiratory volumes were reproduced. The Lagrangian discrete phase model approach was used to investigate particle transportation and deposition under transient breathing conditions. Additionally, the Eulerian approach was used to analyze the transport of nanoparticles in the gas phase. A total of >50,000 monodispersed particles with aerodynamic diameters ranging between 2 nm and 10 μm were selected for comprehensive deposition predictions for particle sizes ranging from the nano- to microscale.

RESULTS

The predicted results were compared with the experimental data. The particle deposition fraction in the nasal cavity and tracheal regions showed differences between the steady and transient simulations. In addition, particle analysis under steady inhalation conditions cannot accurately predict particle transportation and deposition in the lower airway. Furthermore, the breathing cycle had a significant effect on the deposition fraction of the particles and the behavior of the inhaled particles.

CONCLUSIONS

Transient simulation mimicking the breathing cycle was observed to be an important factor in accurately predicting the transportation and deposition of particles in the respiratory tract.

Prediction of exhaled carbon dioxide concentration using a computer-simulated person that included alveolar gas exchange

Accurate prediction of inhaled CO₂ concentration and alveolar gas exchange efficiency would improve the prediction of CO₂ concentrations around the human body, which is essential for advanced ventilation design in buildings. We therefore, developed a computer-simulated person (CSP) that included a computational fluid dynamics approach. The CSP simulates metabolic heat production at the skin surface and carbon dioxide (CO₂ ) gas exchange at the alveoli during the transient breathing cycle. This makes it possible to predict the CO₂ distribution around the human body. The numerical model of the CO₂ gas exchange mechanism includes both the upper and lower airways and makes it possible to calculate the alveolar CO₂ partial pressure; this improves the prediction accuracy. We used the CSP to predict emission rates of metabolically generated CO₂ exhaled by a person and assumed that the tidal volume will be unconsciously reduced as a result of exposure to poor indoor air quality. A reduction in tidal volume resulted in a decrease in CO₂ emission rates of the same magnitude as was observed in our published experimental data. We also observed that the predicted inhaled CO₂ concentration depended on the flow pattern around the human body, as would be expected.

Breathing zone and exhaled air re-inhalation rate under transient conditions assessed with a computer-simulated person

The breathing zone of an individual indoors is usually defined as a finite region steadily formed in front of a face. Assuming the steady formation of the breathing zone, we propose a procedure for quantitatively identifying a breathing zone formed in front of a human face in the transient condition. This assumption is reasonable considering that the ventilation time scale of human respiration is sufficiently short compared to the ventilation time scale of a room. We used steady-state computational fluid dynamics (CFD) and a computationally simulated person (CSP). We present the probabilistic size of the breathing zone for various postures and breathing conditions. By analyzing unsteady inhalation and exhalation airflow characteristics via a CSP with a respiratory system, we also estimated the direct re-inhalation rate of the exhaled air. The results can be used for developing methods to control the long-term and low-contaminant concentration exposures.