Ultrafine Particles Near a Roadway Intersection: Origin and Apportionment of Fast Changes in Concentration

Abstract

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.

A work group report on ultrafine particles (American Academy of Allergy, Asthma & Immunology): Why ambient ultrafine and engineered nanoparticles should receive special attention for possible adverse health outcomes in human subjects

“…Background UFP concentrations in cities and upwind of roadways are summarized in Table 4, 33, 34, 36, 43–48 Higher concentrations were associated with lower humidity, 43, 49 greater proportion of diesel vehicles, 36, 44, 46, 49–51 winter months, 44, 47 and when traffic accelerates after stopping. 44, 51 Not surprisingly, UFP concentrations decline with distance from the highway. 39, 46 …”

Adaptive Decomposition of Highly Resolved Time Series into Local and Non-Local Components

“…A similar method has been explored by Klems et al (2010) using one-second particle number concentrations (using a condensation particle counter) collected near a busy intersection to study its origins and to apportion the collected data to appropriate sources. In that study, the authors used wavelet transforms to parse out the high frequency portion of the data.…”

“…While CADETS allows the user to choose the cut-off frequency and apply a lowpass filter on the data using the chosen frequency, the method proposed by Klems et al (2010) suggests that data be repeatedly filtered until the resulting output reaches the point of minimal improvement. The latter approach is practical in separating the signal into two parts, but does not provide any information about the separated components.…”

Nanoparticle chemical composition and diurnal dependence at the CalNex Los Angeles ground site

“…For example, within the first 100 m of a freeway, the particle number concentration has been found to decrease almost exponentially with increasing distance downwind of the freeway [ Sioutas et al , 2005]. Adjacent to an intersection, intense spikes in number concentration occur at regular time intervals that are related to the stoplight cycle governing traffic flow through the intersection [ Klems et al , 2010]. As one moves away from the roadway microenvironment, these variations decrease and eventually blend into the ambient background, which is influenced by longer time frame processes such as diurnal dependencies of human activity (e.g., rush hour patterns of motor vehicle emissions) [ Zhang et al , 2004] and meteorology (e.g., photochemical particle formation) [ Kulmala et al , 2004].…”