Biomass burning emits large amounts of aerosol particles globally, influencing human health and climate, but the number and size of the particles is highly variable depending on fuel type, burning and meteorological conditions, and secondary reactions in the atmosphere. Ambient measurements of aerosol during wildfire events can therefore improve our understanding of particulate matter produced from biomass burning. In this study, time-resolved sub-micrometer ambient aerosol size and mass distributions of freshly emitted aerosol were measured for three biomass burning wildfire events near Northridge, California, located in the highly populated San Fernando Valley area of Los Angeles. One fire (Marek) was observed during the dry Santa Ana conditions that are typically present during large Southern California wildfires, but two smaller fires (Getty and Camarillo) were observed during the more predominant non-Santa Ana weather conditions. Although the fires were generally small and extinguished quickly, they produced particle number concentrations as high as 50,000 cm-3 and mass concentrations as large as 150 µg cm-3, well above background measurements and among the highest values observed for fires in Southern California. Therefore, small wildfires can have a large impact on air quality if they occur near urban areas. Particle number distributions were lognormal, with peak diameters in the accumulation mode at approximately 100 nm. However, significant Aitken mode and nucleation mode particles were observed in bimodal distributions for one fire. Significant variations in the median diameter were observed over time, as particles generally became smaller as the fires were contained. The results indicate that it is likely that performing mass measurements alone could systematically miss detection of the smaller particles and size measurements may be better suited for studies of ambient biomass burning events. Parameters of representative unimodal and bimodal lognormal fits to the distributions are provided for reproduction of distributions in aerosol and climate models. © 2014 Elsevier Ltd. All rights reserved.