Local and regional components of aerosol in a heavily trafficked street canyon in central London derived from PMF and cluster analysis of single-particle ATOFMS spectra.

Positive matrix factorization (PMF) has been applied to single particle ATOFMS spectra collected on a six lane heavily trafficked road in central London (Marylebone Road), which well represents an urban street canyon. PMF analysis successfully extracted 11 factors from mass spectra of about 700,000 particles as a complement to information on particle types (from K-means cluster analysis). The factors were associated with specific sources and represent the contribution of different traffic related components (i.e., lubricating oils, fresh elemental carbon, organonitrogen and aromatic compounds), secondary aerosol locally produced (i.e., nitrate, oxidized organic aerosol and oxidized organonitrogen compounds), urban background together with regional transport (aged elemental carbon and ammonium) and fresh sea spray. An important result from this study is the evidence that rapid chemical processes occur in the street canyon with production of secondary particles from road traffic emissions. These locally generated particles, together with aging processes, dramatically affected aerosol composition producing internally mixed particles. These processes may become important with stagnant air conditions and in countries where gasoline vehicles are predominant and need to be considered when quantifying the impact of traffic emissions.

In vitro toxicology of ambient particulate matter: correlation of cellular effects with particle size and components.

High concentrations of airborne particulate matter (PM) have been associated with increased rates of morbidity and mortality among exposed populations. Although certain components of PM were suggested to influence these effects, no clear-cut correlation was determined thus far. One of the possible modes of action is the induction of oxidative stress by inhaled PM triggering inflammatory responses. Therefore, the in vitro formation of reactive oxygen species (ROS) in three cell lines in the presence of five subfractions of PM(10), collected in Münster, Germany was investigated. The PM components chloride, nitrate, ammonium, sulfate, 68 chemical elements, and endotoxin were quantified. The highest concentration of endotoxin was found in particles of 0.42-1.2 µm aerodynamic diameters, and therefore probably subject to long-range transport. Intracellular ROS formation in three well established mammalian cell lines (CaCo2, human; MDCK, canine; RAW264.7, mouse) only correlated positively with particle size. The two smallest PM size fractions provoked the highest rise in ROS. However, the latter did not correlate with the concentration of any PM components investigated. The smallest PM size fractions significantly dominated the number of particles. Therefore, the particle number may be most effective in inducing oxidative stress in vitro.

Analysis of traffic and meteorology on airborne particulate matter in Münster, northwest Germany.

The importance of street traffic and meteorological conditions on the concentrations of particulate matter (PM) with an aerodynamic diameter smaller than 10 microm (PM10) was studied in the city of Münster in northwest Germany. The database consisted of meteorological data, data of PM10 mass concentrations and fine particle number (6-225 nm diameter) concentrations, and traffic intensity data as counted with tally hand counters at a four- to six-lane road. On working days, a significant correlation could be found between the diurnal mean PM10 mass concentration and vehicle number. The lower number of heavy-duty vehicles compared with passenger cars contributed more to the particle number concentration on working days than on weekend days. On weekends, when the vehicle number was very low, the correlation between PM10 mass concentration and vehicle number changed completely. Other sources of PM and the meteorology dominated the PM concentration. Independent of the weekday, by decreasing the traffic by approximately 99% during late-night hours, the PM10 concentration was reduced by 12% of the daily mean value. A correlation between PM10 and the particle number concentration was found for each weekday. In this study, meteorological parameters, including the atmospheric stability of the boundary layer, were also accounted for. The authors deployed artificial neural networks to achieve more information on the influence of various meteorological parameters, traffic, and the day of the week. A multilayer perceptron network showed the best results for predicting the PM10 concentration, with the correlation coefficient being 0.72. The influence of relative humidity, temperature, and wind was strong, whereas the influence of atmospheric stability and the traffic parameters was weak. Although traffic contributes a constant amount of particles in a daily and weekly cycle, it is the meteorology that drives most of the variability.