A 10-day winter sampling campaign was conducted in downtown Toronto for particulate matter (PM) air pollution in the fine (<2.5 microm) size range. An aerosol laser ablation mass spectrometer (LAMS), a tapered-element oscillating microbalance (TEOM), and an aerodynamic particle sizer (APS) were operated in parallel to characterize the PM on-line. In this study, the LAMS observed differences in the chemical composition between three separate episodes with higher PM2.5 mass and APS counts. LAMS results showed that in one instance of elevated PM, organic amines were present in the particulates. Temporal analyses of this episode revealed chemical transformations as the amines, characterized by m/z peaks 58(C3HeN)+, 86(C5H2N)+, and nitrates, increased in number concentration while Ca and hydrocarbon particle classes concurrently decreased. On another day, sulfates were found to have increased significantly. The third event was only 4 h in duration and exhibited an increase in the number of submicron-sized K/hydrocarbons and sulfate-containing particles. In this last event, the hydrocarbons and a K to Fe ratio enrichment indicated there was likely a contribution from a combustion source. This work offers some of the first insights into single particle size and chemistry in a cold winter climate.
Urban Toronto fine particulate matter (PM2.5) was physically and chemically characterized by online aerosol laser ablation mass spectrometry (LAMS) between January 2002 and February 2003. The mass spectra from the analysis of individual aerosol particles were classified according to chemical composition by a neural network approach called adaptive resonance theory (ART-2a). Temporal trends of the hourly analysis rate of over 120 different particles types were constructed and subjected to positive matrix factorization (PMF). This receptor modeling technique enabled the identification of nine distinct emission sources responsible for these particle types: biogenic, mixed crustal, organic nitrate, construction dust, Toronto soil/road salt, secondary salt, wood burning, intercontinental dust, and an unknown source of aluminum fluoride dust. Episodic events occurred with the wood burning, intercontinental dust, and unknown dust sources. This is the first paper reporting the application of PMF to single-particle spectral data.
Particle concentrators allow exposure to controlled levels of concentrated ambient particulate matter (PM) over a broad range of concentrations. The performance of these systems can be influenced by the physicochemical characteristics of PM and so it is vital to characterize the concentrators at a given site. The quasiultrafine PM (<0.2 µm), fine PM (0.15-2.5 µm), and coarse PM (2.5-10 µm) concentrators at the Southern Ontario Center for Atmospheric Aerosol Research (SOCAAR), University of Toronto, were characterized as a part of the "Health Effects of Aerosols in Toronto (HEAT)" campaign held during February-March, 2010. The full size distributions of ambient and concentrated particles were simultaneously measured in terms of number, surface area, and volume using high time-resolution instruments. Examination of the complete size distribution, including the unconcentrated particles beyond the cutpoints of the concentrator systems, revealed that particles in the unconcentrated size ranges made significant contributions to the particle number and surface area present in the concentrated airstreams of fine and coarse concentrators. Further transients in the ambient ultrafine particle concentrations were evident as dampened signals in these concentrated airstreams. The ultrafine concentrator exhibited a significant size shift when the ambient particle size distribution had a mode ≤30 nm. OverReceived 22 July 2011; accepted 29 March 2012. Funding for SOCAAR was provided by the Canadian Foundation for Innovation, the Ontario Innovation Trust, and the Ontario Research Fund. Operational funding for this study was provided by NSERC (Natural Sciences and Engineering Research Council of Canada) and CIHR (Canadian Institutes of Health Research). We also thank Gang Lu for his help in setting up the GRIMM dust monitor.Address correspondence to Neeraj Rastogi, Physical Research Laboratory, Navrangpura, Ahmedabad 380 009, India. E-mail: neeraj6676@gmail.com all the fine and coarse concentrators provided a reasonable concentrated reproduction of the ambient PM mass while questions remain regarding the representativeness of the ultrafine concentrator.
Primary sources of particulate matter (PM) were analyzed by suspending powdered samples into an aerosol laser ablation mass spectrometer (LAMS). PM sources studied included vehicle exhaust particulates, dust from a nonferrous smelter, cement powder, incinerator fly ash, two coal fly ash samples, and two soils. Marker peaks signified certain PM source sectors: construction particles could be distinguished by abundant Ca and Ca compounds, fuel combustion was marked by elemental carbon clusters, and nonferrous industrial particles showed inorganic As, Cu, Pb, Zn, and SO x . In addition to the distinction between particles from these different source sectors, mass spectral results also showed that for a single source, different particle types existed, and among different sources within a sector, similar spectra were present. The aerosol LAMS results show the difficulty in differentiating among separate fly ash sources as well as among different soil samples. A particle class balance receptor model that measures the amount of specific particle types rather than the amount of a chemical component is suggested as a means of source apportionment when particle spectra with overlapping source possibilities occur. The assumptions and limitations of receptor modeling aerosol LAMS data are also described. In particular, methods need to be developed to account for the contribution of secondary sources. INTRODUCTIONIn Ontario, Canada, ~1900 premature deaths, 9800 hospitalizations, and many more minor illnesses each year are attributed to air pollution.1 The Ontario Medical Association estimates that these burdens combine to cost, conservatively, more than $10 billion every year, both in direct (e.g., increased hospitalizations and employee absenteeism) and indirect (e.g., premature deaths and mental suffering) costs.1 A better characterization of air pollution, which includes a significant particulate matter (PM) component of acid aerosols, SO 4 2-particles, and PM from primary emission sources, would improve the understanding of its adverse health effects.2 Also, apportionment of the PM among its identified sources would help in determining targeted regulatory paths to remediate the PM component of air pollution problems.Single particle laser mass spectrometry is an advanced technique recently applied to the characterization of ambient PM.3 Aerosol laser ablation or laser desorption/ ionization mass spectrometers typically sample PM directly from the environment into the vacuum source region of a time-of-flight mass spectrometer. Individual particles are then ablated allowing particle-to-particle chemistries to be monitored online. In contrast to conventional bulk filter collection of PM that requires subsequent offline sample preparation and analysis, aerosol laser ablation mass spectrometry (LAMS) provides rapid, real-time information on separate particles. A recent literature review of the technique was conducted by Suess and Prather.
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