A wavelet-based algorithm was implemented to separate the high frequency portion of ambient nanoparticle measurements taken during the summer and winter of 2009 in Wilmington, Delaware. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC) and a fast mobility particle sizer (FMPS). The high frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 6-35% of the daily ambient number concentration with hourly contributions sometimes greater than 50%. When the data were weighted by particle volume, this portion of the signal contributed an average of 20% to the daily PM(0.1) concentration. Particle concentration spikes were preferentially observed from locations surrounding the measurement site where motor vehicles accelerate after a red traffic light turns green. As the distance or transit time from emission to sampling increased, the size distribution shifted to larger particle diameters.