Chemistry Reference
In-Depth Information
Table 1 Model categories [
19
]
Mechanistic
Empirical
Deterministic Mathematical constructs of physical/
chemical processes that predict fixed
outputs for a fixed set of inputs
Statistical models based on measured
input and output values (e.g.
regression models that relate air
concentrations and blood levels of a
chemical or ambient pollutant
concentration with personal
exposures)
Stochastic
Mathematical construction of physical/
chemical processes that predict the
range and probability density
distribution of an exposure model
outcome (e.g. predicted distribution
of personal exposures within a study
population)
Regression-based models, where model
variables and coefficients are
represented by probability
distributions, representing
variability and/or uncertainty in the
model inputs and parameters
various administrative databases and standardised time-activity profiles. The
modelling system uses a GIS in combining and processing the concentration and
population data activity. The model was applied to evaluate population exposure in
one specific municipality in Denmark.
An individual exposure model (IEM) was developed by Wu et al. [
24
]to
retrospectively estimate the long-term average exposure of individual children
from Southern California to several pollutants, including PM
10
and PM
2.5
. In the
IEM model, pollutant concentration due to both local mobile source emissions
and meteorologically transported pollutants were taken into account by combining
a Gaussian line source model (CALINE4) with a regional air quality model
(SMOG). Information from the Southern California Children's Health Study
(CHS) survey was used to group each child into a specific time-activity category,
for which corresponding time-activity profiles were sampled.
Once the outdoor concentration has been calculated by air quality models, the
indoor pollutant concentration can also be modelled based on an understanding of
the ways in which indoor air becomes exchanged with outdoor air, together with
the deposition or decay dynamics of the pollutants, and with indoor emission
source rates characteristics. Several methodologies exist to estimate indoor air
pollution concentrations from outdoor modelled concentrations. These include a
variety of empirical approaches based on: statistical evaluation of test data and a
least-square regression analysis; deterministic models based on a pollutant mass
balance around a particular indoor air volume; or a combination of both
approaches. Most of the current available studies (e.g. [
24
-
29
]) are based on
experimental data, resulting from measurements of outdoor and indoor
concentrations for different microenvironments in order to establish a relation
between indoor and outdoor (I/O) PM concentrations. Morawska and Congrong
[
30
] presented a review of studies conducted in different countries concluding
that in the absence of known indoor sources the I/O ratios range from 0.50 to
0.98. These values show that firstly the contribution of outdoor air as a source of
