Selective detection and characterization of nanoparticles from motor vehicles.

Selective detection and characterization of nanoparticles from motor vehicles. Johnston, M., Klems, J., Zordan, C., Pennington, M., Smith, J., & HEI Health Review Committee 2013.
abstract bibtex

Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 3% to 35% of the daily ambient number concentration, with spike contributions sometimes greater than 50% of hourly number concentrations. When the data were weighted by particle volume, this portion of the signal contributed an average of 10% to 20% to the daily concentration of particulate matter (PM) < or = 0.1 microm in aerodynamic diameter (PM0.1). The preferred locations for observing particle concentration spikes were those surrounding the measurement site at which motor vehicles accelerated after a red traffic light turned green. As the distance or transit time from emission to sampling increased, the size distribution shifted to a larger particle size, which confirmed the source assignments. To determine the distribution of emissions from individual vehicles, we correlated camera images with the spike contribution to particle number concentration at each time point. A small percentage of motor vehicles were found to emit a disproportionally large concentration of nanoparticles, and these high emitters included both spark-ignition (SI) and heavy-duty diesel (HDD) vehicles. In addition to characterizing the contribution of the spikes (local sources) to the ambient number concentration, we developed a method to determine the net contribution of motor vehicles (all sources) to the total mass concentration of ambient nanoparticles. To do this, we correlated the concentration of spikes with measurements of fast changes in the chemical composition of nanoparticles measured with the nano aerosol mass spectrometer (NAMS; built by the Johnston group). The NAMS irradiates individual, size-selected nanoparticles with a high-energy laser pulse to generate a mass spectrum consisting of multiply charged atomic ions.

@misc{
 title = {Selective detection and characterization of nanoparticles from motor vehicles.},
 type = {misc},
 year = {2013},
 source = {Research report (Health Effects Institute)},
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 issue = {173},
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 created = {2019-07-11T17:26:48.239Z},
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 last_modified = {2019-07-11T17:26:48.239Z},
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 abstract = {Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 3% to 35% of the daily ambient number concentration, with spike contributions sometimes greater than 50% of hourly number concentrations. When the data were weighted by particle volume, this portion of the signal contributed an average of 10% to 20% to the daily concentration of particulate matter (PM) < or = 0.1 microm in aerodynamic diameter (PM0.1). The preferred locations for observing particle concentration spikes were those surrounding the measurement site at which motor vehicles accelerated after a red traffic light turned green. As the distance or transit time from emission to sampling increased, the size distribution shifted to a larger particle size, which confirmed the source assignments. To determine the distribution of emissions from individual vehicles, we correlated camera images with the spike contribution to particle number concentration at each time point. A small percentage of motor vehicles were found to emit a disproportionally large concentration of nanoparticles, and these high emitters included both spark-ignition (SI) and heavy-duty diesel (HDD) vehicles. In addition to characterizing the contribution of the spikes (local sources) to the ambient number concentration, we developed a method to determine the net contribution of motor vehicles (all sources) to the total mass concentration of ambient nanoparticles. To do this, we correlated the concentration of spikes with measurements of fast changes in the chemical composition of nanoparticles measured with the nano aerosol mass spectrometer (NAMS; built by the Johnston group). The NAMS irradiates individual, size-selected nanoparticles with a high-energy laser pulse to generate a mass spectrum consisting of multiply charged atomic ions.},
 bibtype = {misc},
 author = {Johnston, M.V. and Klems, J.P. and Zordan, C.A. and Pennington, M.R. and Smith, J.N. and HEI Health Review Committee, undefined}
}

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