Iman Goldasteh

PM2.5 and ultrafine particles emitted during heating of commercial cooking oils.

UNLABELLED Seven commercial cooking oils were investigated to determine the PM(2.5) mass and ultrafine particle (UFP) emission rates and emission fluxes (rates per area). The results of this study showed that at 197°C soybean, safflower, canola, and peanut oils produced lower PM(2.5) emission fluxes (6.1 × 10(5), 3.0 × 10(5), 5.4 × 10(5), and 3.9 × 10(5) μg/min/m(2), respectively) than corn, coconut, and olive oils (2.7 × 10(6), 2.9 × 10(6), and 5.7 × 10(6) μg/min/m(2), respectively). Similarly, the total particle number flux at 197°C was lower for soybean, safflower, and canola oils (3.5 × 10(13), 8.6 × 10(13), and 1.0 × 10(14) #/min/m(2), respectively) than the corn, coconut, olive, and peanut oils (2.4 × 10(14), 1.4 × 10(14), 1.7 × 10(14), and 3.8 × 10(14) #/min/m(2), respectively). In general, oils with a higher smoke temperature resulted in lower particle concentrations over the measured temperature range (131-197°C). The percentage of UFP (particle diameter D(p) 10-100 nm) to total particles (D(p) 10-500 nm) ranged from 76 to 99% for this temperature range. Particles below 10 nm in diameter were not measured. The particle number size distribution showed a polydisperse behavior with major mode sizes ranging from 25 nm (for peanut oil) to 82 nm (for soybean oil) at an oil temperature of 197°C. PRACTICAL IMPLICATIONS The study presents particle number and mass concentrations, size distributions, emission rates, and emission fluxes from heating common cooking oils. The emission rates and emission fluxes can be used as inputs to models for indirect exposure analysis studies. The study may also be used to provide guidance on choosing oils that result in lower emission rates when heated.

Wind tunnel study and numerical simulation of dust particle resuspension from indoor surfaces in turbulent flows

Particle resuspension from flooring is an important source of air pollution in the indoor environment. In this work, resuspension of monolayer, polydisperse, irregularly shaped dust particles from various types of floorings was studied via a series of wind tunnel experiments. The range of free-stream velocity needed for resuspension of dust particles was evaluated as a function of particle size and material of particles and surfaces. In addition, a Monte Carlo simulation for predicting the resuspension of dust particles was developed. The resuspension model took into account the effects of particle irregularity, particle surface roughness, and flow characteristics. The dust particle resuspension from different floorings for several particle sizes was evaluated. The model predictions for resuspension fractions were compared with the experimental data and good agreement was observed. The study provided information on the role of airflow velocity on irregular dust particle resuspension from common floorings.

A Model for Removal of Compact, Rough, Irregularly Shaped Particles from Surfaces in Turbulent Flows

A model for removal of compact, rough, irregularly shaped particles from surfaces in turbulent flow was developed. Following the approach of our previous bumpy particle model, irregularly shaped particles were modeled as spherical particles with a number of bumps on them. To improve the model, the effect of surface roughness was added to the bumps. Each bump was modeled with large number of asperities and the Johnson-Kendall-Roberts (JKR) adhesion theory was used to model the adhesion and detachment of each bump and asperity in contact with the surface. The total adhesion force for each bump was obtained as the summation of each asperity force in contact with the substrate. To account for the variability observed in the removal of particles, the number of bumps and roughness values of particles are assumed to be random, respectively, with Poisson and log-normal distributions. For particle separation from the surface, the theory of critical moment was used, and the orientation of bumps on the surface was considered when determining the range of shear velocity needed for removal of the irregularly, shaped particles. The effects of particle size, turbulent flow, particle irregularity, and particle surface roughness on detachment and resuspension were studied for different particles and surfaces. Model prediction for removal of rough, irregularly shaped graphite particles from steel substrate was compared with the available experimental data and earlier numerical models, and good agreement was obtained. This study may find application in adhesion and detachment of irregular particles from flooring in indoor and outdoor environments.

Effect of Air Flow on Dust Particles Resuspension From Common Flooring

Particle resuspension from flooring in connection with increased indoor air pollution was studied. Earlier efforts hypothesized that during the gait cycle, high speed airflow is generated at the floor level that would lead to particle resuspension. The details of the mechanism of the particle resuspension, however, are not well understood. Earlier models were mainly developed for spherical particle detachment from smooth surfaces, but in reality, dust particles are irregular in shape and have a wide size distribution. The resuspension of dust particles thus depends on their shape and size and the nature of their contact with the surface. In this work, a wind tunnel study of dust particle resuspension from common flooring was performed and the critical air velocities for particle detachment were measured. The main goal of the present experimental work is to understand the main mechanism of dust particle resuspension under real conditions by systematically investigating a range of airflow speeds. The other goal of the study is to provide information on the role of the airflow on dust particle detachment from common floorings.Copyright

Particle Detachment from Rough Surfaces in Turbulent Flows: An Analytical Expression for Resuspension Fraction

The critical shear velocity for resuspension of micrometer size particles from rough surfaces was studied. The random variation of surface roughness was accounted for. The recently developed Monte Carlo simulations accounted for the statistical variations of physical parameters that control the particle resuspension process. A sensitivity analysis showed that the surface roughness and its random variation was the key factor affecting the particle resuspension from rough surfaces. The theory of probabilistic transformation was used and an analytical expression for evaluating the resuspension fraction of particles of different sizes from rough surfaces versus the shear velocity was developed. The resuspension fractions as predicted by the analytical model were evaluated for several particles sizes for a range of turbulent flow shear velocities. The resulting resuspension fractions were compared with those obtained from the Monte Carlo simulations as well as the available experimental data. It was found that the predictions of the new analytical equation were in good agreement with the Monte Carlo simulation results and the experimental data, especially for smaller size particles. This new analytical expression could be used as a simple empirical equation for estimating flow-induced resuspension of particles from rough surfaces.

CFD Simulation of Particle Transport and Dispersion in Indoor Environment by Human Walking

Particle resuspension is an important source of particulate matter in indoor environments that significantly affects the indoor air quality and could potentially have adverse effect on human health. Earlier efforts to investigate indoor particle resuspension hypothesized that high speed airflow generated at the floor level during the gate cycle is the main cause of particle resuspension. The resuspended particles are then assumed to be dispersed by the airflow in the room, which is impacted by both the ventilation and the occupant movement, leading to increased PM concentration.In this study, a three dimensional model of a room was developed using FLUENT™ CFD package. A RANS approach with the RNG k-e turbulence model was used for simulating the airflow field in the room for different ventilation conditions. The trajectories of resuspended particulate matter were computed with a Lagrangian method by solving the equations of particle motion. The effect of turbulent dispersion was included with the use of the eddy lifetime model. The resuspension of particles due to gait cycle was estimated and included in the computational model. The dispersion and transport of particles resuspended from flooring as well as particle re-deposition on flooring and walls were simulated. Particle concentrations in the room generated by the resuspension process were evaluated and the results were compared with experimental chamber study data as well as simplified model predictions, and good agreement was found.Copyright

Monte Carlo Simulations of Micro-Particle Detachment and Resuspension From Surfaces in Turbulent Flows

Micro-particle adhesion, detachment and resuspension from surfaces have attracted considerable attention due to their numerous applications in semiconductor, xerographic, and pharmaceutical industries, and, more recently, in understanding indoor air quality. However, most earlier studies have focused on idealized spherical particles and smooth surfaces, and the effects of particle irregularities and surface roughness on the rate of particle removal and resuspension are not well understood. In this work, a Monte Carlo simulation of particle resuspension from a surface under turbulent flow conditions was developed and resuspension of nearly spherical and irregular shaped particles with rough surfaces from substrates under turbulent flow condition was studied. Following our earlier approach, compact irregular shaped particles were modeled as spherical particles with a number of hemispherical bumps. It was assumed that the bump surfaces also have fine roughness. The extended Johnson-Kendall-Roberts (JKR) adhesion theory for rough surfaces was used to model the particle adhesion and detachment.A number of assumptions were made to apply the model. It was assumed that the particles have a Gaussian size distribution. The number of bumps of the irregular particles and surface roughness values of particle are assumed to be random, respectively, with Poisson and log-normal distributions. For particle detachment from the surface, the theory of critical moment was used. The effects of particle size, turbulent flow, particle irregularity and surface roughness on particle detachment and resuspension were studied for different cases. The Monte Carlo model predictions show probabilistic distributions of the particle resuspension. The simulation results are compared with the available experimental data and good agreement was found. The study provided information on the random nature of particle resuspension due to the randomness in the airflow, particle size distribution and surface roughness.Copyright