Exposure to diesel-related air pollution, which includes black carbon (BC) as a major component of the particulate matter emitted in engine exhaust, is a known human health hazard. The resulting health burden falls heavily on vulnerable communities located close to major sources including highways, rail yards, and ports. Determination of source contributions to the overall pollution burden is challenging due to collinearity in the exhaust composition profiles for relevant sources including heavy-duty diesel trucks, railroad locomotives, cargo-handling equipment, and marine engines. Additionally, the impact of each source depends not just on the magnitude of emissions but on its location relative to receptors as well as on meteorology. We modeled source-resolved BC concentrations in West Oakland, California, at a high (150 m) spatial resolution using the Weather Research and Forecasting model. The ability of the model to predict hourly and 24 h average BC concentrations is evaluated for a 100-day period in summer 2017 when BC was measured at 100 sites within the community. We find that a community monitoring site is representative of population-weighted average BC exposure in the community. Major contributing sources to BC in West Oakland include on-road diesel trucks (44 ± 5%) and three off-road diesel sources: ocean-going vessels (19 ± 1%), railroad locomotives (16 ± 2%), and harbor craft such as tugboats and ferries (11 ± 1%).
Keywords: air quality modeling; black carbon; diesel exhaust; high spatial resolution; large eddy simulation; source apportionment.