Greg J. Evans

Comparative cardiopulmonary effects of size-fractionated airborne particulate matter

Context: Strong epidemiological evidence exists linking particulate matter (PM) exposures with hospital admissions of individuals for cardiopulmonary symptoms. The PM size is important in influencing the extent of infiltration into the respiratory tract and systemic circulation and directs the differential physiological impacts. Objective: To investigate the differential effects of the quasi-ultrafine (PM0.2), fine (PM0.15-2.5), and coarse PM (PM2.5-10) size fractions on pulmonary and cardiac function. Methods: Female BALB/c mice were exposed to HEPA-filtered laboratory air or concentrated coarse, fine, or quasi-ultrafine PM using Harvard Ambient Particle Concentrators in conjunction with our nose-only exposure system. These exposures were conducted as part of the “Health Effects of Aerosols in Toronto (HEAT)” campaign. Following a 4 h exposure, mice underwent assessment of respiratory function and recording of electrocardiograms using the flexiVent® system. Results: Exposure to coarse and fine PM resulted in a significant reduction in quasistatic compliance of the lung. Baseline total respiratory resistance and maximum responsiveness to methacholine were augmented after coarse PM exposures but were not affected by quasi-ultrafine PM exposures. In contrast, quasi-ultrafine PM alone had a significant effect on heart rate and in reducing heart rate variability. Conclusion: These findings indicate that coarse and fine PM influence lung function and airways responsiveness, while ultrafine PM can perturb cardiac function. This study supports the hypothesis that coarse and fine PM exerts its predominant physiologic effects at the site of deposition in the airways, whereas ultrafine PM likely crosses the alveolar epithelial barrier into the systemic circulation to affect cardiovascular function.

Rapid physical and chemical transformation of traffic-related atmospheric particles near a highway

The health of a substantial portion of urban populations is potentially being impacted by exposure to traffic–related atmospheric pollutants. To better understand the rapid physical and chemical transformation of these pollutants, the number size distributions of non–volatile traffic–related particles were investigated at different distances from a major highway. Particle volatility measurements were performed upwind and downwind of the highway using a fast mobility particle sizing spectrometer with a thermodenuder on a mobile laboratory. The number concentration of non–denuded ultrafine particles decreased exponentially with distance from the highway, whereas a more gradual gradient was observed for non–volatile particles. The non–volatile number concentration at 27 m was higher than that at 280 m by a factor of approximately 3, and the concentration at 280 m was still higher than that upwind of the highway. The proportion of non–volatile particles increased away from the highway, representing 36% of the total particle number at 27 m, 62% at 280 m, and 81% at the upwind site. A slight decrease in the geometric mean diameter of the non–volatile particle size distributions from approximately 35 nm to 30 nm was found between 27 m and 280 m, in contrast to the growth of non–denuded particles with increasing distance from the highway. Single particle analysis results show that the contribution of elemental carbon (EC)–rich particle types at 27 m was higher than the contribution at 280 m by a factor of approximately 2. The findings suggest that people living or spending time near major roadways could be exposed to elevated number concentrations of nucleation–mode volatile particles ( 100 nm). The impact of the highway emissions on air quality was observable up to 300 m.

Strategies to Enhance the Interpretation of Single-Particle Ambient Aerosol Data

New instruments are beginning to reveal the chemical complexity of atmospheric aerosol particles. Exploitation of the plethora of information being made accessible through aerosol particle spectrometry and other techniques requires new strategies for data interpretation. This paper demonstrates and evaluates several analysis methods used to exploit this single-particle high-time-resolution data. In the first part of this study, Standard Reference Material (SRM) particulate matter samples were analyzed by an Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) in order to evaluate the use of a modified, logarithm based, method of clustering mass spectra using the Adaptive Resonance Theory (ART-2a) algorithm. In the second part of this study, data obtained from the ATOFMS during the four seasons of 2007 were interpreted using a variety of approaches so as to elucidate the nature and sources of particles influencing the great lakes region of North America. This dataset is believed to represent the longest time-span of single-particle data ever analyzed in a study of this nature. These mass spectra were clustered into 21 different particle types using the supervised log-transformed ART-2a algorithm. Both long-term seasonal trends and high-time-resolution temporal patterns of particle type concentrations were examined. Source identification was supported by comparison with known source samples. Potential source contribution functions were used to identify source regions. This paper describes and evaluates these approaches to data interpretation using examples from the ambient air study to illustrate the methodology and highlight the findings. Furthermore, these ambient examples demonstrate how the application of these strategies enhances the interpretation of single-particle ambient aerosol data. Copyright 2012 American Association for Aerosol Research

Perceptions of Undergraduate Engineering Students about Learning Objectives of Undergraduate Laboratories

The paper presents student perceptions about learning objectives of laboratories. Three focus group sessions were conducted with chemical engineering undergraduate students at UofT as part of a larger project to enhance the learning outcomes of laboratories. In this study, thirteen laboratory learning objectives developed at the ABET colloquy in 2002, were used as a framework to determine the strengths and limitations of the laboratories. These learning objectives cover cognition, psychomotor and affective domains of knowledge. The results indicate that improvements are needed with respect to providing opportunities for students to be creative, devise their own procedures, repeat experiments and improve communication skills. In addition, ethics in the lab and safety need more emphasis.