1 research outputs found
Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffic-Related Ultrafine Particles
Comparative
evaluations are needed to assess the suitability of
near-road air pollution models for traffic-related ultrafine particle
number concentration (PNC). Our goal was to evaluate the ability of
dispersion (CALINE4, AERMOD, R-LINE, and QUIC) and regression models
to predict PNC in a residential neighborhood (Somerville) and an urban
center (Chinatown) near highways in and near Boston, Massachusetts.
PNC was measured in each area, and models were compared to each other
and measurements for hot (>18 °C) and cold (<10 °C)
hours
with wind directions parallel to and perpendicular downwind from highways.
In Somerville, correlation and error statistics were typically acceptable,
and all models predicted concentration gradients extending ∼100
m from the highway. In contrast, in Chinatown, PNC trends differed
among models, and predictions were poorly correlated with measurements
likely due to effects of street canyons and nonhighway particle sources.
Our results demonstrate the importance of selecting PNC models that
align with study area characteristics (e.g., dominant sources and
building geometry). We applied widely available models to typical
urban study areas; therefore, our results should be generalizable
to models of hourly averaged PNC in similar urban areas