With concerns about environmental issues, transportation studies have
extensively evaluated emissions impacts associated with traffic
operational strategies and transportation policies. However, the impact
studies mainly relied on emissions impacts with a demand forecasting
model. The planning model cannot capture individual vehicles’
interactions (i.e., lane changes or stop-and-go situation) or detailed
traffic operations such as traffic signals. These limitations lead to
under- or over-estimated emissions while evaluating several policies.
Even though many studies utilized microscopic traffic models to better
estimate emissions, the studies have not considered further steps such
as air quality estimation and health impact studies.
This research develops an integrated framework for evaluating air
quality and health impacts of transportation corridors using microscopic
traffic model, micro-scale emissions model, non-steady state dispersion
model, and health impact model. The main advantage of this approach is
to better estimate air quality and health impacts from vehicle
interactions and detailed traffic management strategies.
As a case study, we evaluate air quality and health impacts of several
scenarios associated with major transportation corridors accessing the
San Pedro Bay Ports (SPBP) complex, California. The corridors consist of
20 miles-long major freight freeways and arterials, as well as line-haul
rail along the Alameda corridor and several rail yards associated with
the SPBP complex. For the scenarios, we consider a clean truck program,
cleaner locomotives, and modal shifts compared to the 2005 baseline. All
scenarios performed with the integrated framework have provided larger
improvements of air quality and health impacts associated with
transportation corridors than conventional frameworks using
transportation planning models. However, the difference in air quality
and health impacts from modal shift scenarios between clean trucks and
locomotives are minor.
As explanatory research, pollution response surface models are
developed. The main feature of the pollution response surface model is
to avoid the high computational cost of the microscopic traffic model,
which makes it difficult to estimate traffic for multiple days needed
for evaluating emissions and health impacts. A conceptual framework for
estimating pollution response surface models is proposed. Using a toy
network, response surfaces of NOX and PM are estimated.
