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Anthropogenic particulate source characterization and source apportionment using aerosol time-of-flight mass spectrometry


Methods of measuring the chemical and physical properties of aerosols as well as proper source apportionment of ambient particles are necessary to provide insight as to the roles they play in the environment and their impact on human health. In addition, the ability to apportion ambient particles quickly and accurately will be very helpful for environmental and health agencies and for monitoring and enforcing emission standards by allowing such agencies to determine the primary source of aerosols in their monitoring areas. The goal of this dissertation is to provide a new approach for aerosol source apportionment using aerosol time-of-flight mass spectrometry (ATOFMS) single particle data. This goal was accomplished by determining unique mass spectral signatures for specific aerosol sources and by developing these signatures into a source signature library in which ambient ATOFMS data can be matched and apportioned. The creation of the source signature library (SSL) began with the characterization of specific sources themselves. Heavy duty diesel vehicle (HDDV) emissions were characterized using ATOFMS from a dynamometer study. The particle types detected for HDDVs were compared to those from a previous dynamometer study of gasoline powered light duty vehicles (LDV) to see if HDDV and LDV particles can be distinguished. A SSL was then created for the HDDV and LDV emissions to test the ability to properly apportion between the two sources on ambient ATOFMS data collected next to a major freeway using a SSL matching technique. This work demonstrated that the two sources are readily distinguishable in a fresh emission environment, and that the matching method is a valid means for apportioning ATOFMS data. The SSL was then extended for multiple specific sources as well as for non-source specific particles and was used to apportion the same freeway study particles; showing that the source matching method is able to accurately distinguish different particle sources and that there can be a large contribution from sources other than vehicles near a major freeway. Lastly, the SSL matching method was used to apportion ambient aerosols for two major non-US cities to show that the SSL matching technique is applicable to worldwide ambient ATOFMS data

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