Chemistry Reference
In-Depth Information
exp
i
ΒΌ
C
i
t
i
;
(1)
where exp
i
is the total exposure for the person
i
over the specified period of time,
C
i
is the pollutant concentration in a given location, and
t
i
is the time spent by the
person
i
in that specific location. As a result, the exposure value is expressed in
concentration
time (e.g.
m
gm
3
h), and thus can be interpreted as the mean
pollutant concentration value to which the individual has been exposed during
a given period of time (e.g. 1 h).
For exposure assessment, a combination of the spatial distribution of air
quality, namely PM levels, and an individual location on time (for personal
exposure) and population activity data and density (for population exposure) is
required. In what concerns time-activity data strategies are different when defin-
ing personal or population exposure. For personal exposure, what is needed is an
individual time-activity pattern. This can be obtained, for example, by personal
interview or using GPS tracking, since the exact place of the individual at each
moment is needed. For population exposure the used information is usually
aggregated by population class, and is focused on mobility of the population,
work/school-home displacements, presented, for example, as origin-destination
matrixes (number of people and time spent in displacement by means of trans-
port). Those matrices allow the calculation of the number of people that enters
and leaves the modelling domain. Numerical models are needed for the PM
mapping along the time, once the monitoring networks are able to assess the air
quality in the single stations of the monitoring network, and not the whole area of
interest.
According to IPCS [
18
] an exposure model is a conceptual or mathematical
representation of the exposure process, designed to reflect real-world human expo-
sure scenarios and processes. There are many different ways to classify exposure
models. A consensus appears to be developing around the following classification
scheme proposed by the World Health Organization [
19
], which has been adopted
in this chapter: (a) mechanistic or empirical and (b) deterministic or stochastic
(probabilistic). Table
1
lists these model categories. However, alternative
classifications may be considered as well.
Kousa et al. [
20
] classified exposure models as statistical, mathematical
and mathematical-stochastic models. Statistical models are based on the historical
data and capture the past statistical trend of pollutants [
21
]. The mathematical
modelling, also called deterministic modelling, involves application of emission
inventories, combined with air quality and population activity modelling. The
stochastic approach attempts to include a treatment of the inherent uncertainties
of the model [
22
].
Mathematical exposure models applied to urban areas have been presented by
Jensen [
23
], Kousa et al. [
20
] and Wu et al. [
24
]. The model presented by Jensen
[
23
] is based on the use of traffic flow computations and the operational street
pollution model (OSPM) for evaluating outdoor air pollutants concentrations in
urban areas. The activity patterns of the population have been evaluated using
