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.

翻译：本文评估了PM2.5和NO2健康影响估计对关键输入参数及假设变化的敏感性，具体包括：1）影响评估的空间尺度；2）采用单一浓度-响应函数（CRF）或同一流行病学研究中种族/民族特异性CRF；3）基于居住地而非居住地与工作地双重位置分配暴露水平。该分析以科罗拉多州为研究区域。研究发现，分析空间尺度影响NO2而非PM2.5所致的死亡人数估值。采用县级层面而非1 km²空间分辨率的NO2预测值时，2000-2020年间科罗拉多州每年由NO2所致死亡率降低约50%。采用全人群CRF替代种族/民族特异性CRF后，白人群体PM2.5所致年死亡率估值升高1.3倍，而黑人和西班牙裔居民PM2.5所致死亡率估值分别降低0.4倍和0.8倍。种族/民族特异性CRF未改变白人居民NO2所致死亡率估值，但导致黑人居民死亡率估值降低约0.5倍，西班牙裔居民升高2.9倍。基于居住地而非居住地与工作地双重位置的NO2排放分配，使得科罗拉多州每年NO2所致死亡率估值降低约0.980，PM2.5所致死亡率降低0.997。