Characterizing Urban Particulate Matter Vehicle Emission Spatial Distributions with On-Road Black Carbon and Particle Number Observations

Distributed urban emissions contribute to spatially variable air pollutant exposures from neighborhood block to city-wide scales. It is challenging to attribute fine particulate matter (PM-2.5) exposure patterns associated with important public health impacts to specific sources. Tracking primary traffic PM emissions is essential due to diesel emission control policies with uncertain impacts as control technologies age across the vehicle fleet. We investigate spatiotemporal variations in on-road vehicle black carbon (BC), particle number (PN), nitrogen oxide (NO and NO2) emission factors to fingerprint the influence of heavy diesel vehicle emissions. Two Google Street-View vehicle platforms performed simultaneous daily mobile measurements in Houston, Texas across 38 census tract communities with a range of socioeconomic status and emission sources. These observations have unprecedented spatiotemporal coverage (~160 km per day from July 2017 to March 2018) and 1-5s time resolution, enabling characterization of exposures and vehicle emission factors aggregated across road segments (30-120m), hours and days of the week. We derive vehicle plume enhancements above background (~10s timescales) and fuel-based emission factors with enhancements relative to carbon dioxide (CO2). First, we quantify BC emission factors and their contributions to PM-2.5 enhancements to fingerprint diesel source plumes. Second, we assess the influence of diesel vehicles equipped with particulate filters that exhibit both higher NO oxidation to NO2 and ultrafine mode particle numbers via NO2 and PN emission factor distributions respectively. Our approach demonstrates the value of mobile monitoring to characterize vehicle PM source patterns and to evaluate their contributions relative to stationary sources (e.g. cement batch plants) in Houston. These insights are valuable to attribute spatial exposure patterns to specific sources and inform health impact studies and emission mitigation strategies.