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Determination of the Contributions of Light Duty and Heavy Duty Vehicle Emissions to Ambient Particles in California.
| 题名： | Determination of the Contributions of Light Duty and Heavy Duty Vehicle Emissions to Ambient Particles in California. |
| 作者： | PRATHER, K. A.; REBOTIER, T. P.; SHIELDS, L. G.; SODEMAN, D. A.; SPENCER, M. T.; TONER, S. M. |
| 关键词： | AMBIENT PARTICLES; PARTICULATE MATTER; VEHICLE AIR POLLUTION |
| 摘要： | A new approach for particulate matter (PM) source apportionment has been developed and successfully tested, using meteorological, gas phase, and single particle source signatures to identify and apportion ambient particles in California. A central component of these studies involves using aerosol time-of-flight mass spectrometry (ATOFMS), a technique which analyzes the size and chemical composition of single particles in real-time, to determine the size-resolved mass spectral source signatures of the particulate exhaust emissions from heavy duty diesel vehicles (HDDV) and gasoline powered light duty vehicles (LDV) that can be used for ambient source apportionment. The source signatures were measured by directly sampling PM emissions from multiple vehicles operating on different driving cycles while on a chassis dynamometer. Differences between HDDV and LDV source seeds are discussed. The second and final phase of this project involved sampling ambient particles inside a tunnel and alongside a major freeway. In the freeway study, a high fraction (70-85%) of ambient particles were shown to match the dynamometer source seeds, showing the dynamometer seeds are indeed representative of real-world emissions. The different signatures from LDV and HDDV allow for differentiation of ambient particles from multiple sources including vehicles, biomass, and meat cooking. The established ATOFMS signature libraries for HDDV and LDV exhaust particles will be used in future ATOFMS apportionment studies which will detail the fraction of vehicle emissions in particulate matter in ambient air throughout California. |
| 报告类型： | 科技报告 |
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