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J. L. Moutinho et al.
55.1 Introduction
On-road mobile emissions lead to elevated air pollutant concentrations in near-road
environments and steep concentration gradients exist with distance from major roads.
Exposure to traffic related air pollutants (TRAP), including carbon monoxide (CO),
nitrogen oxides (NOx), and fine particulate matter (PM 2.5 ), has been linked to many
adverse health effects [2]. While vehicles are a significant source of pollutants in
the near-road environment, improved vehicle engine technology, emissions control
systems, and fuel regulations have reduced emissions leading to a decrease in traffic related air pollutants (TRAP) near heavily trafficked roads [2]. Quantifying the
pollutant concentration attributed to traffic pollution from regional pollution through
measurement becomes more difficult as vehicle emissions decrease. In addition, nearroad measurements are often limited within a city leading to a limited understand
of the spatial gradients. Dispersion modeling can provide spatially and temporally
resolved concentration fields of TRAPs for assessing exposure.
55.2 Methods
Hourly-modeled primary traffic-related CO, NOx, and PM 2.5 concentrations at a 25
× 25 m grid resolution were generated using RLINE (Research Line Source Model),
a steady-state, Gaussian plume dispersion model [3]. The Atlanta Regional Commission (ARC) provided link-based, on-road mobile source emissions for the 20country region surrounding metro Atlanta using a traffic demand and mobile source
emissions model. ARC estimated 2010 CO, NOx, and PM2.5 emissions for 43,712
links based on modeled traffic volume, vehicle speed, and fleet demographics. The
surface meteorological data was from the National Weather Service at the HartsfieldJackson Atlanta International Airport (ATL) and preprocessed using AERMINUTE.
The upper air data was from the Peachtree City Falcon Field Airport (FFC).
Initial RLINE results were corrected by applying ARC monthly and hourly diurnal
emissions variability, and hours with wind speeds less than 1 ms
−1 were replaced.
The 2010 ARC link-based emissions were scaled to 2014 emissions levels using the
mobile emissions ratio from the Motor Vehicle Emissions Simulator [4]. Corrected
RLINE results were calibrated to the hourly surface concentrations measurements
collected as part of the Dorm Room Inhalation to Vehicle Emissions (DRIVE) study.
A linear regression between the hourly-corrected RLINE concentrations and the
hourly measurements at the six monitoring locations scaled the corrected results and
the intercept was removed to exclude the local background. In a second process,
the hourly-corrected RLINE results were calibrated to the hourly DRIVE surface
measurements using 24 linear regressions to account for differences in the diurnal
profile. A third process averaged three hourly RLINE concentrations at each grid
with wind direction varying five degrees in either direction to help reduce bias when
the wind aligns with the road links.
J. L. Moutinho et al.
55.1 Introduction
On-road mobile emissions lead to elevated air pollutant concentrations in near-road
environments and steep concentration gradients exist with distance from major roads.
Exposure to traffic related air pollutants (TRAP), including carbon monoxide (CO),
nitrogen oxides (NOx), and fine particulate matter (PM 2.5 ), has been linked to many
adverse health effects [2]. While vehicles are a significant source of pollutants in
the near-road environment, improved vehicle engine technology, emissions control
systems, and fuel regulations have reduced emissions leading to a decrease in traffic related air pollutants (TRAP) near heavily trafficked roads [2]. Quantifying the
pollutant concentration attributed to traffic pollution from regional pollution through
measurement becomes more difficult as vehicle emissions decrease. In addition, nearroad measurements are often limited within a city leading to a limited understand
of the spatial gradients. Dispersion modeling can provide spatially and temporally
resolved concentration fields of TRAPs for assessing exposure.
55.2 Methods
Hourly-modeled primary traffic-related CO, NOx, and PM 2.5 concentrations at a 25
× 25 m grid resolution were generated using RLINE (Research Line Source Model),
a steady-state, Gaussian plume dispersion model [3]. The Atlanta Regional Commission (ARC) provided link-based, on-road mobile source emissions for the 20country region surrounding metro Atlanta using a traffic demand and mobile source
emissions model. ARC estimated 2010 CO, NOx, and PM2.5 emissions for 43,712
links based on modeled traffic volume, vehicle speed, and fleet demographics. The
surface meteorological data was from the National Weather Service at the HartsfieldJackson Atlanta International Airport (ATL) and preprocessed using AERMINUTE.
The upper air data was from the Peachtree City Falcon Field Airport (FFC).
Initial RLINE results were corrected by applying ARC monthly and hourly diurnal
emissions variability, and hours with wind speeds less than 1 ms
−1 were replaced.
The 2010 ARC link-based emissions were scaled to 2014 emissions levels using the
mobile emissions ratio from the Motor Vehicle Emissions Simulator [4]. Corrected
RLINE results were calibrated to the hourly surface concentrations measurements
collected as part of the Dorm Room Inhalation to Vehicle Emissions (DRIVE) study.
A linear regression between the hourly-corrected RLINE concentrations and the
hourly measurements at the six monitoring locations scaled the corrected results and
the intercept was removed to exclude the local background. In a second process,
the hourly-corrected RLINE results were calibrated to the hourly DRIVE surface
measurements using 24 linear regressions to account for differences in the diurnal
profile. A third process averaged three hourly RLINE concentrations at each grid
with wind direction varying five degrees in either direction to help reduce bias when
the wind aligns with the road links.