Aerosol Chemistry and Physics - Aerosols: Measurement, Dosimetry, and Health Effects - page 150

PMF has been applied worldwide to apportion indoor PM to likely sources (e.g., Kocaeli City,
Turkey, Pekey et al., 2010; Seoul, Korea, Lim et al., 2011). Work continues on modeling indoor expo-
sure to PM for epidemiology. For example, using simple measurements of carbonaceous particles
and elemental analysis of PM in Boston, Massachusetts, Clougherty et al. (2011) recently showed
how factor analysis can be enhanced for indoor source apportionment by incorporating some fea-
tures of land use regression modeling, along with the effects of ventilation on indoor/outdoor ratios
of pollutants. Their work identiied three indoor factors, combustion, cleaning, and resuspension,
and three outdoor factors, long-range transport, fuel oil/diesel, and road dust/resuspension.
6.3 PHYSICAL PROPERTIES OF INDOOR AEROSOLS
This section presents a brief overview of a few key aspects of aerosol physics that inluence the
indoor behavior and fate of airborne particles. Hinds presents a clear and thorough discussion
of aerosol physical properties in his classic text (Hinds, 1999). Seinfeld and Pandis (2006) and
Friedlander (2000) also introduce aerosol physics with many examples from ambient air.
6.3.1 s ize d istributions
Particle size and mass are key physical parameters that inluence aerosol behavior, for example, the
penetration of aerosols through building envelopes (Thatcher et al., 2003), deposition of particles in
the human respiratory system (Chapter 1 of Hinds, 1999), and low through sampling instruments
(Chapter 10 of Hinds, 1999). Many studies indicate that ine particles (<2.5 μm diameter) appear
to be more toxic to cells per unit mass than coarse particles with diameters between 2.5 and 10 μm.
Because many sources contribute to airborne particles in an urban area, and particle sizes vary in
time and space, size distribution functions are very useful tools to describe the size dependence of
particle number, surface area, and volume (or mass) concentrations.
Aerosol instrumentation design depends on understanding the size dependence of aerosol behav-
ior, particularly aerosol low dynamics. Number size distributions are measured with particle coun-
ters that depend on aerosol electrical mobility and optical properties. The size dependence of light
scattering by airborne particles is used in optical particle counters, for example.
Nucleation, accumulation, and coarse size modes : Particles that arise from nucleation are small
(∼5-50 nm), and large numbers of UFP (<0.1 μm; nucleation mode: 2-70 nm) are typically found
near combustion sources. Atmospheric lifetimes of nucleation mode particles are minutes or less.
After formation they coagulate when they collide with each other and with larger particles, and reach
the accumulation mode between about 0.1 and 1 μm. Airborne particles between about 2 and 10 μm
are part of the coarse mode. Resuspended soil particles, sea spray, plant debris, pollen, and spores
contribute to the coarse mode. Outdoor lifetimes of accumulation and coarse mode particles are
days to weeks and minutes to days, respectively (Seinfeld and Pandis, 2006).
6.3.1.1 Number
The top part of Figure 6.8 shows a typical urban aerosol number size distribution , as illustrated by
Seinfeld and Pandis (1998, p. 431). In this example, the number size distribution peaks in the nucle-
ation mode, even for this somewhat aged, rather than fresh, aerosol.
Normal or bell-shaped distributions of particle size are symmetrical about the average particle
diameter. The standard deviation describes the spread of particle diameter around the mean. Since
most airborne aerosols are not normally distributed in size, but tail off with increasing size, log
normal distributions are more appropriate descriptors. The logarithms of particle diameters, rather
than the particle diameters, are normally distributed, and the geometric standard deviation describes
the spread of the log of particle diameters about the median. Many ambient aerosol number size
distributions can be described as the sum of modes that are each log-normally distributed (Hinds,
1999; Seinfeld and Pandis, 2006).