Jj. Colls et A. Micallef, Measured and modelled concentrations and vertical profiles of airborne particulate matter within the boundary layer of a street canyon, SCI TOTAL E, 235(1-3), 1999, pp. 221-233
Concentrations and vertical profiles of various fractions of airborne parti
culate matter (suspended particulate matter (SPM), PM10 and PM2.5) have bee
n measured over the first three metres from ground in a street canyon. Meas
urements were carried out using automated near rear-time apparatus called t
he Kinetic Sequential Sampling (KSS) system. KSS system is essentially an e
lectronically-controlled lift carrying a real-time particle monitor for sam
pling air sequentially, at different heights within the breathing zone, whi
ch includes all heights within the surface layer of a street canyon at whic
h people may breathe. Data is automatically logged at the different recepto
r levels, for the determination of the average vertical concentration profi
le of airborne particulate matter. For measuring the airborne particle conc
entration, a Grimm Dust Monitor 1.104/5 was used. The recorded data also al
lows for time series analysis of airborne particulate matter concentration
at different heights. Time series data and hourly-average vertical concentr
ation profiles in the boundary layer of the confines of a street are though
t to be mainly determined by traffic emissions and traffic associated proce
sses. Hence the measured data were compared with results of a street canyon
emission-dispersion model in time and space. This Street Level Air Quality
(SLAQ) model employs the plume-box technique and includes modules for simu
lating vehicle-generated effects such as thermally- and mechanically-genera
ted turbulence and resuspension of road dust. Environmental processes, such
as turbulence resulting from surface sensible heat and the formation of su
lphate aerosol from sulphur dioxide exhaust emissions, are taken into accou
nt. The paper presents an outline description of the measuring technique an
d model used, and a comparison of the measured and modelled data. (C) 1999
Elsevier Science B.V. All rights reserved.