Assessing Dynamic Exposure to Air Pollution - Space-Time Integration in Geography and GIScience - page 283

study area (Bartonova et al. 1999 ). If multiple locations were visited during a 1 h
time frame, an average was taken of the outdoor concentrations at each stop.
While air pollution exposure is determined by the interaction of air pollution
concentrations and people's activity-travel patterns, few past studies have taken
into account the fact that people are at different locations at different times of the
day (Kwan 2013 ; Richardson et al. 2013 ). To evaluate people's exposures to air
pollution more accurately, it is important to also consider their daily movement
(Kwan 2012a , b ). To address this issue, we present in what follows a method for
integrating the spatial-temporal dynamics of pollution concentrations and people's
space-time activity patterns. We develop and explore two notions of exposure: (a)
static exposure that evaluates exposure based on an individual's residential location;
and (b) dynamic exposure that assesses exposure based on various locations that an
individual travels to throughout the day, including the routes taken to travel between
these locations.

16.3 Study Area and Data

The study area for this research is Franklin County located at the heart of the
Columbus Metropolitan Area in Ohio, USA. It is a mid-sized metropolitan area
with a dispersed urban structure and a population of about 1.8 million in 2010.
Suburbanization in the past three decades has led to the spatial expansion of its
urban area, a hollowing out of the inner city, and strong auto dependence.
To evaluate individual exposure to air pollution, two main types of data were
used in this study: estimates of 24-h PM 10 concentrations and activity-travel diary
data for Franklin County residents. The 24-h particulate matter concentrations were
estimated with an air dispersion model that utilizes three types of data: emission
data, meteorological data, and topographic data. Characteristics of these data are
described as follows, while the estimation procedures are provided in the next
section.
First, emission data of the 119 major point sources of industrial pollutants in
the study area were obtained from the Ohio Environmental Protection Agency's
1999 emissions inventory (Fig. 16.1 ). Variables from these data include latitude,
longitude, base elevation, stack height, stack temperature, exit flow rate, and
the total amount of pollution emitted (tons per year) of each source. Second,
meteorological data of both surface and upper air used to determine the dispersal
patterns of pollutants were obtained from the Columbus International Airport and
the Dayton Wright Patterson Air Force Base. From both datasets, variables such as
wind direction, wind speed, and temperature were used to determine atmospheric
turbulence characteristics, which in turn influence the overall dispersal patterns of
the emitted pollutants. Finally, data about the topographic features in the study area
were drawn from USGS 7.5 min digital elevation model (DEM) quads of the study
area. Typically, the elevation of the study area will have a stronger influence on