Bayesian Methods for Modeling Time Series of Ultrafine Particle Distributions

• Activity Number: 137
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Heidi Fischer*+ and Robert E Weiss
• Companies: University of California at Los Angeles and University of California at Los Angeles Fielding School of Public Health
• Keywords: Bayesian Methods ; MCMC ; Ultrafine Particles ; Time Series ; Functional Analysis

Abstract

The intrusion of tailpipe emissions into school bus cabins increases school children's exposure to diesel emissions when commuting in school buses. The factors determining the penetration of tailpipe-emitted ultrafine particles (UFPs, diameter < 100 nm) into bus cabins remain unclear. Particle concentrations were measured in 102 size bins ranging from 7-280 nm, in multiple scenarios simulated to represent common exposure conditions when school buses were idling to pick up or drop off school children. We use Bayesian functional models to study UFP behavior over time across a range of particle sizes.