Traffic Impacts on Fine Particulate Matter Air Pollution at the Urban Project Scale: A Quantitative Assessment

Abstract

Formal health impact assessment (HIA),currently underused in the United States, is a relatively new process for assistingdecision-makers in non-health sectors by estimating the expected public healthimpacts of policy and planning decisions. In this paper we quantify theexpected air quality impacts of increased traffic due to a proposed newuniversity campus extension in Chapel Hill, North Carolina. In so doing, webuild the evidence base for quantitative HIA in the United States and developan improved approach for forecasting traffic effects on exposure to ambient fineparticulate matter (PM2.5) in air. Very few previous US HIAs have quantifiedhealth impacts and instead have relied on stakeholder intuition to decidewhether effects will be positive, negative, or neutral. Our method uses an airdispersion model known as CAL3QHCR to predict changes in exposure to airborne,traffic-related PM2.5 that could occur due to the proposed new campusdevelopment. We employ CAL3QHCR in a new way to better represent variability inroad grade, vehicle driving patterns (speed, acceleration, deceleration, andidling), and meteorology. In a comparison of model predictions to measuredPM2.5 concentrations, we found that the model estimated PM2.5 dispersion towithin a factor of two for 75% of data points, which is within the typical benchmarkused for model performance evaluation. Applying the model to present-dayconditions in the study area,we found that current traffic contributes a relatively small amount to ambientPM2.5 concentrations: about 0.14 μg/m3 in the most exposed neighborhood—relativelylow in comparison to the current US National Ambient Air Quality Standard of 12μg/m3. Notably, even though the new campus is expected to bring anadditional 40,000 daily trips to the study community by the year 2025,vehicle-related PM2.5 emissions are expected to decrease compared to currentconditions due to anticipated improvements in vehicle technologies and cleanerfuels.