Assessing Dynamic Exposure to Air Pollution - Space-Time Integration in Geography and GIScience - page 282

Dispersion models, however, have several drawbacks. Multiple parameters must
be entered for each individual source and hence a substantial amount of time is
needed for data preparation. Gaussian assumptions about dispersion patterns may
be unrealistic (Jerrett et al. 2005 ). Estimation error may be present when there are
temporal mismatches between emissions and meteorological data. For instance, this
can happen when meteorological data are collected by the hour while emissions data
are provided as an annual rate. As a result, exposure estimations have the potential
to contain substantial error.

16.2.2 Assessing Population or Individual Exposure

to Pollution

Another important component of exposure assessment is to determine which portion
of the population is exposed to elevated levels of air pollution. Here, pollution
exposure can be analyzed in terms of distinct population groups or at the individual
level. For an aggregate assessment, the total number of people living in each
square kilometer can be examined in relation to varying hourly concentrations for
a well-defined area in the study area (e.g., Slørdal 1998 ). On the other hand, point
estimations can be made for all homes and buildings within a given area (Clench-
Aas et al. 1999a ). For individual assessment, long and short term exposure can be
determined using different approaches. When concerned with long term exposure,
dispersion models can be used to estimate concentrations surrounding the home,
work place, or school for a specific individual based on yearly, monthly, or seasonal
averages (e.g., Bartonova et al. 1999 ). Conversely, short term exposure can be
analyzed using a diary method (Duan 1982 ; Gulliver and Briggs 2005 ). Diary entries
provide information regarding location and time of targeted individuals, which in
turn can be related to the spatial and temporal variations of estimated air pollutants
(Bartonova et al. 1999 ; Clench-Aas et al. 1999b ).
A traffic exposure study in Oslo, Norway provides an example of individual
assessment that used the diary method (Bartonova et al. 1999 ). In this research,
dispersal patterns of particulate matter and nitrogen oxides related to traffic and
spatial heating sources were estimated using a dispersion model. Estimations were
provided for a 1-km resolution grid on an hourly basis which reflected air pollution
patterns for an urban region. A subgroup of the participants provided activity diaries
that contained a detailed description of their daily movement. Participant activities
were recorded by the hour for a 2-3 week period (Bartonova et al. 1999 ). For
the study area, concentration estimations for each receptor location were provided
for each hour during a 3 month period. These calculations were used to represent
annual average concentrations for a 3-year time frame. On the other hand, individual
exposure levels were provided for each location that was visited on an hourly basis.
Here, receptor values at each location were assigned to the individual when they
were situated within the study area while grid values were assigned outside of the