A High Resolution Multipollutant Assessment of Health Damages Due to the Onroad Sector in Boston, Massachusetts

Onroad vehicular emissions can adversely affect the health of people both near-road and regionally through exposure to O, NO and PM. While multiple studies have characterized the overall air quality and health benefits of emissions from the transportation sector, fewer studies have modeled the benefits of transportation policies at higher geographic resolution relevant to communities. We used the United States Environmental Protection Agency (U.S. EPA)'s Community Multiscale Air Quality (CMAQ) Version 5.2.1 coupled with the decoupled direct method (DDM) within a nested grid with maximum resolution of 1.33 km × 1.33 km. We predicted O, NO and PM sensitivities to a large matrix of input parameters concerning five different vehicle classes, five precursors, and six subregions within the Boston metropolitan area (Massachusetts, U.S.). We used the Environmental Benefits Mapping and Analysis Program in R (BenMAPR) to estimate health impacts given concentration-response functions from epidemiological studies, focusing on premature mortalities as well as asthma exacerbations. Based upon the sensitivity matrix, for NO and PM, NO and directly emitted PM (PPM) have the maximum sensitivity, respectively. O is found to be more sensitive to VOC emissions than NO emissions. We also found that NH and SO emissions are the next most significant contributors to PM concentrations after PPM. Our overall findings suggest that approximately 342 premature deaths (95 % CI: 200-465) occur annually in the region due to on-road emissions, with 87 % of these linked to elevated NO concentrations. For PM from PPM, the most densely populated subregion had damages per ton 1.2 to 1.8 times higher than for the other inner core regions and three times higher than suburban regions. Substantial variation in health damages per ton of emissions was observed across precursor pollutants, source regions, and vehicle classes, underscoring the need for targeted emission reduction strategies. This study highlights the importance of high-resolution air quality modeling to accurately capture intra-urban health impacts and inform effective policymaking.