The contribution of motor vehicle emissions to ambient fine particulate matter public health impacts in New York City: a health burden assessment

Background: On-road vehicles are an important source of fine particulate matter (PM2.5) in cities, but spatially varying traffic emissions and vulnerable populations make it difficult to assess impacts to inform policy and the public. Methods: We estimated PM2.5-attributable mortality and morbidity from on-road vehicle generated air pollution in the New York City (NYC) region using high-spatial-resolution emissions estimates, air quality modeling, and local health incidence data to evaluate variations in impacts by vehicle class, neighborhood, and area socioeconomic status. We developed multiple 'zero-out' emission scenarios focused on regional and local cars, trucks, and buses in the NYC region. We simulated PM2.5 concentrations using the Community Multi-scale Air Quality Model at a 1-km spatial resolution over NYC and combined modeled estimates with monitored data from 2010 to 2012. We applied health impact functions and local health data to quantify the PM2.5- attributable health burden on NYC residents within 42 city neighborhoods. Results: We estimate that all on-road mobile sources in the NYC region contribute to 320 (95 % Confidence Interval (CI): 220-420) deaths and 870 (95 % CI: 440-1280) hospitalizations and emergency department visits annually within NYC due to PM2.5 exposures, accounting for 5850 (95 % CI: 4020-7620) years of life lost. Trucks and buses within NYC accounted for the largest share of on-road mobile-attributable ambient PM2.5, contributing up to 14.9 % of annual average levels across 1-km grid cells, and were associated with 170 (95 % CI: 110-220) PM2.5-attributable deaths each year. These contributions were not evenly distributed, with high poverty neighborhoods experiencing a larger share of the exposure and health burden than low poverty neighborhoods. Conclusion: Reducing motor vehicle emissions, especially from trucks and buses, could produce significant health benefits and reduce disparities in impacts. Our high-spatial-resolution modeling approach could improve assessment of on-road vehicle health impacts in other cities.