We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to
varying key input parameters and assumptions including: 1) the spatial scale at
which impacts are estimated, 2) using either a single concentration-response
function (CRF) or using racial/ethnic group specific CRFs from the same
epidemiologic study, 3) assigning exposure to residents based on home, instead
of home and work locations. This analysis was carried out for the state of
Colorado. We found that the spatial scale of the analysis influences the
magnitude of NO2, but not PM2.5, attributable deaths. Using county-level
predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of
mortality attributable to NO2 by ~ 50% for all of Colorado for each year
between 2000-2020. Using an all-population CRF instead of racial/ethnic group
specific CRFs results in a higher estimate of annual mortality attributable to
PM2.5 by a factor 1.3 for the white population and a lower estimate of
mortality attributable to PM2.5 by factors of 0.4 and 0.8 for Black and
Hispanic residents, respectively. Using racial/ethnic group specific CRFs did
not result in a different estimation of NO2 attributable mortality for white
residents, but led to lower estimates of mortality by a factor of ~ 0.5 for
Black residents, and by a factor of 2.9 for to Hispanic residents. Using NO2
based on home instead of home and workplace locations results in a smaller
estimate of annual mortality attributable to NO2 for all of Colorado by ~0.980
each year and 0.997 for PM2.5.Comment: 24 pages, 6 figures, 2 table