Journal of Aerosol Science最新文献

Aerosol dosimetry in respiratory airways is relevant for pulmonary drug delivery and inhalation toxicology. Consequently, computational fluid-particle dynamics (CF-PD) modelling of pulmonary aerosol delivery is an active research field. Additionally, mice are the most commonly used animals in medical research. Technological advances have provided information on whole mice lung morphologies with unprecedented high resolution. Therefore, in this study, we used high-resolution light sheet fluorescent microscopy (LSFM) images of a healthy C57BL/6 mouse lung with a constant air flow rate of 72 ml/min, to extract an anatomical 3-dimensional (3D) geometry of the entire airway tree of the left lung from the primary bronchi to the most distal bronchioles excluding the trachea. The airways were segmented based on an order- and generation-based method. Also, to compare the morphological data and regional deposition, a generation-based investigation including 25 generations was employed in the present model. One-way coupling of CF-PD modeling was applied to model an intubated and mechanically-ventilated mouse. Maximum values of the velocity and vorticity magnitude of 3.2 m/s and 200,000 1/s were reached in the second order, respectively, and maximum pressure and wall shear stress levels were 30 Pa and 3.5 Pa, respectively. Finally, order- and generation-based particle deposition efficiency and dose per lung area were obtained for the particle size range of 1 μm ≤ d_p ≤ 10 μm yielding pronounced hotspot deposition patterns mainly near the proximal bifurcations. The results showed a positive correlation between deposition efficiency and particle size due to a size-dependent increase in inertial and gravitational effects. Maximum regional deposition and normalized dose was seen for 10 μm particles in the 1st order of the murine left lung. Smaller peak sizes of deposition efficiency were seen in the third and fourth orders of the mouse left lung due to almost complete loss of the largest particles in lower order airways. It also justifies the close to zero deposition efficiency in the highest orders (fifth to sixth). Both lung morphology as well as total and regional aerosol deposition showed reasonably good agreement with empirical data from the literature. The present CF-PD model with accurate realistic lung morphology, improves our knowledge of airway aerosol deposition hotspots. The obtained modeling method and the qualitative results can be implemented on human airways.

This study investigates the role of particle shape on the aerodynamic resuspension process of irregular flat micro-particles on a substrate. We propose that these particles resuspend at higher velocities than spherical ones of the same size under the same aerodynamic forces. Two sets of data are analyzed to test the argument, the first from experiments we conducted using crushed glass particles (ranging from 80 μm to 300 μm) and the second from published data on RDX explosive residue particles (sized between 10 μm and 25 μm) published previously.

We particularly analyze the shape factors of the particles used in the experiments and introduce them into a Monte Carlo (MC) simulation model. The probabilities for the time evolution of the resuspension process are calculated through a Markov chain of states. The transition probabilities entail the balance between the forces and moments involved in the mechanisms for particle detachment from the surface.

The particle resuspension rate as a function of the fluid velocity is evaluated both experimental and numerically. Additionally, we assess the removal efficiency for different particle size ranges whenever possible.

Both experimental and numerical results demonstrate that the resuspension fraction of irregular flat particles is significantly lower than for equally sized glass microspheres under the same conditions. Simulations corroborate previous experimental findings, indicating that smaller irregular particles exhibit higher removal efficiency. According to the MC model results, irregular particles detach by sliding rather than rolling.

As an increasingly important solution for the energy industry, batteries are widely used in electric vehicles and energy storage systems. However, thermal runaway of batteries is a serious safety hazard. In this process, the materials in the battery undergo thermal decomposition and combustion, resulting in the formation of soot and other harmful byproducts and posing a significant threat to the environment and human health. In this work, LiFePO₄ and ternary lithium batteries are selected as experimental subjects to comprehensively evaluate the soot hazard in the thermal runaway process. The LiFePO₄ and ternary lithium battery soot samples exhibited a typical "core-shell" structure, with lattice spacings ranging between 0.36-0.46 and 0.35–0.46 nm, respectively. The surfaces of these materials are covered with functional groups, including C–C, C–O, and O–H bonds. Soot samples taken from the thermal runaway of ternary lithium batteries also contain O–CO and π bonds, consistent with the functional groups in wood soot. Through EDS and XPS characterization, it is evident that the LiFePO₄ battery soot contains C, O, Li, F, P, and Fe, while the ternary lithium battery soot, in addition to these elements, also contains Ni, Co, and Mn. The battery soot samples exhibited significant cytotoxicity to human cells, such as lung cells (MRC-5) and neural cells (SH-SY5Y). With high concentrations of soot, the survival rate of lung cells and nerve cells is low. Compared to wood soot, battery soot causes greater damage to human lungs and neural cells. The research in this work contributes to a better understanding of the hazardous characteristics of soot in battery thermal runaway and its potential threats to human health, offering a crucial reference for enhancing battery safety and emergency responses.

Taking advantage of continuous, atmospheric, dry, and high-purity aerosol processes, we have developed the three-dimensional (3D) aerosol nanoprinting technique. Precise manipulation of charged aerosol trajectories was realized by controlling the electric field near the substrate with nanoscale resolution to position aerosols in the exact three-dimensional space for finally manufacturing 3D nanostructures in an array form under atmospheric conditions. In our aerosol printing technique, the charged aerosol is a fundamental building block and the electric field line is a drawing tool to print the aerosol. Here, we review how our 3D aerosol nanoprinting technology has been developed and show the importance of aerosol science in controlling the generation of charged aerosols, surface charging, particle motion under Brownian random force, electrical force, inertial force, drag force, and also particle agglomeration for ensuring small and non-agglomerated nanoscale building blocks. We also present possible applications utilizing 3D nanostructures fabricated by our 3D aerosol nanoprinting technique.

Traditional agrichemical formulations are often composed of synthetic ingredients that may exhibit adverse environmental and health effects. Losses from spray drift mean that these potentially toxic ingredients can contaminate the environment and pose significant risks to human health. There is therefore a need for natural ingredients to formulate agrichemical sprays that are non-toxic to humans and less harmful to the environment to ensure greater safety and sustainability. Essential oils are promising candidates as natural biopesticides, but their application is limited due to their phytotoxicity at biocidal-effective dosages. A novel alternative approach utilizes essential oils as dilute oil-in-water emulsion spray adjuvants. This strategy can potentially reduce the usage of conventional pesticide ingredients by synergistically enhancing their effectiveness and reducing losses from spray drift. In this study, we evaluated the anti-drift potential of using plant-derived essential oils and quillaja saponin (a natural surfactant) to prepare dilute oil-in-water emulsions for use as safe and sustainable agrichemical adjuvants. In this study, we evaluated the potential of plant-derived essential oils and quillaja saponin, a natural surfactant, to create dilute oil-in-water emulsions as safe and sustainable agrichemical adjuvants. We found that emulsions made with methylated seed oil (MSO) and quillaja saponin showed similar drift reduction performance to those made with MSO and Tween 80, a synthetic non-ionic surfactant. Carvacrol (oregano and thyme essential oil) in water emulsion was found to increase the spray droplet size, thereby making it a promising ingredient for drift reduction. However, we found that limonene (citrus fruits essential oil) in water emulsion had no drift reduction abilities at the same specifications. The different performances of the two essential oils likely arise from differences in their physicochemical properties, which influence the spray atomization mechanism, specifically the ability of the oil droplets entering and spreading on the water–air interface to form perforations.

Industrial processes generate chemicals that have the potential to be aerosolized and inhaled by workers, thereby posing health risks. Traditional toxicology methods employing animal models cannot keep up with the pace of emerging hazards. Nascent in vitro practices face challenges regarding translatability to the real world. To address this critical gap, this study demonstrated a workflow utilizing aerosol characterization in a more realistic exposure scenario: dry powder aerosolization onto the air-liquid interface of lung cells. This study delves into biophysical aspects of lung function by examining lung surfactant inhibition. A set of particulates, including aluminum, aluminum oxide, carbon nanotubes, diesel particulate matter, and colloidal silica, was selected for investigation. Particles were in the respirable regime, with mean aerodynamic diameters ranging from 111 to 162 nm by number and 369–2884 nm by mass. Carbon nanotubes and colloidal silica were identified as surfactant inhibitors. Aerosol doses reduced cell viability, up to 38%, with the most pronounced effects observed in response to exposure to aluminum and diesel particulate matter. Dry particle exposure at the air-liquid interface shows promise even at low doses, compared with nebulization or inoculation to submerged cultures. Our findings underscore the potential of this innovative approach for assessing the hazards of aerosolized particulates and emerging contaminants, offering a more accurate representation of real-world exposure scenarios.

The characterization of workers’ exposure to airborne metallic ultrafine particles (UFP) has been an increasing issue because of their effects on health, and as many activities are potentially concerned such as welding, oxy-cutting or 3D printing. Determining the particle size distribution of such an aerosol provides a real contribution to the understanding of UFP exposures and associated health effects, as it is directly related to their penetration in the respiratory tract. In this context, it is proposed to optimize the preparation of collection substrates of cascade impactors of airborne metallic UFP. The experimental results confirm that the collection substrates have to be prepared beforehand by coating them with a high-vacuum-resistant silicone grease. The results highlight that this grease has to be preliminarily dissolved in a heptane-based solution with a mass ratio grease-solvent of 7.5%, and then deposited on the substrate with a target height of 9 $\mu m$. Applying this protocol ensures a reproducible and representative determination of the particle size distribution, allowing the phenomena of particle bouncing and reentrainment to be significantly reduced. It is also shown that coated collection substrates remain stable for several months in terms of mass, and that the samples collected remain stable during transport thanks to the improvement of particle cohesion on the coated membrane.

The toxicity of particulate matter (PM) is dependent on particle physical and chemical properties and is commonly studied using in vivo and in vitro approaches. PM to be used for in vivo and in vitro studies is often collected on filters and then extracted from the filter surface using a solvent. During extraction and further PM sample handling, particle properties change, but this is often neglected in toxicology studies, with possible implications for health effect assessment. To address the current lack of knowledge and investigate changes in particle properties further, ambient PM with diameter less than 2.5 μm (PM_2.5) was collected on filters at an urban site and extracted using a standard methanol protocol. After extraction, the PM was dried, dispersed in water and subsequently nebulized. The resulting aerosol properties were then compared to those of the ambient PM_2.5. The number size distribution for the nebulized aerosol resembled the ambient in terms of the main mode diameter, and >90 % of particle mass in the nebulized size distribution was still in the PM_2.5 range. Black carbon made up a similar fraction of PM mass in nebulized as in ambient aerosol. The sulfate content in the nebulized aerosol seemed depleted and the chemical composition of the organic fraction was altered, but it remains unclear to what extent other non-refractory components were affected by the extraction process. Trace elements were not distributed equally across size fractions, neither in ambient nor nebulized PM. Change in chemical form was studied for zinc, copper and iron. The form did not appear to be different between the ambient and nebulized PM for iron and copper, but seemed altered for zinc. Although many of the studied properties were reasonably well preserved, it is clear that the PM_2.5 collection and re-aerosolization process affects particles, and thus potentially also their health effects. Because of this, the effect of the particle collection and extraction process must be considered when evaluating cellular and physiological outcomes upon PM_2.5 exposure.

Accurate predictions of nucleation and atomic-level estimates of cluster properties in gas-phase chemical physics have proven challenging. These challenges arise from two primary sources: finite-size effects associated with nanoscopic particles and the emergence of non-standard thermodynamics, particularly at elevated temperatures. This study reexamines the formation of argon clusters using established methodologies such as atomistic simulations, configurational sampling, and statistical thermochemistry. To enhance the representation of condensed-phase argon, we employ an ab initio-based two-body potential, complemented by a three-body Axilrod–Teller potential. Additionally, we address the impact of anharmonicities on cluster stabilities using a recently developed extension to the standard statistical cluster model. The employed anharmonic model is rigorously benchmarked against molecular dynamics simulations. The subsequent analysis demonstrates a robust and consistent agreement between our model and experimental data. Our analysis covers nearly every experimental data point collected between 1971 and 2010, offering valuable insights into the predictive capabilities of the model. Moreover, in contrast to previous studies, our findings indicate that individual measurements are consistently in alignment with each other.

Aerosol effects on clouds and radiation are a large source of uncertainty in our understanding of human impacts on the climate system. Uncertainty in aerosol effects results from uncertainty in parameter values, known as parametric uncertainty, and from uncertainty from the model’s structure, known as structural uncertainty. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions and their dynamics have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging. These findings indicate that structural error in modeled aerosol properties is a key factor contributing to uncertainty in aerosol forcing.