摘要：Formal health impact assessment (HIA),
currently underused in the United States, is a relatively new process for assisting
decision-makers in non-health sectors by estimating the expected public health
impacts of policy and planning decisions. In this paper we quantify the
expected air quality impacts of increased traffic due to a proposed new
university campus extension in Chapel Hill, North Carolina. In so doing, we
build the evidence base for quantitative HIA in the United States and develop
an improved approach for forecasting traffic effects on exposure to ambient fine
particulate matter (PM2.5) in air. Very few previous US HIAs have quantified
health impacts and instead have relied on stakeholder intuition to decide
whether effects will be positive, negative, or neutral. Our method uses an air
dispersion model known as CAL3QHCR to predict changes in exposure to airborne,
traffic-related PM2.5 that could occur due to the proposed new campus
development. We employ CAL3QHCR in a new way to better represent variability in
road grade, vehicle driving patterns (speed, acceleration, deceleration, and
idling), and meteorology. In a comparison of model predictions to measured
PM2.5 concentrations, we found that the model estimated PM2.5 dispersion to
within a factor of two for 75% of data points, which is within the typical benchmark
used for model performance evaluation. Applying the model to present-day
conditions in the study area,
we found that current traffic contributes a relatively small amount to ambient
PM2.5 concentrations: about 0.14 μg/m3 in the most exposed neighborhood—relatively
low in comparison to the current US National Ambient Air Quality Standard of 12
μg/m3. Notably, even though the new campus is expected to bring an
additional 40,000 daily trips to the study community by the year 2025,
vehicle-related PM2.5 emissions are expected to decrease compared to current
conditions due to anticipated improvements in vehicle technologies and cleaner
fuels.
