Background The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 600,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis. Methods We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO 2 , PM 2.5 and O 3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, population density, sociodemographics, socioeconomic status, race and ethnicity, behavioral risk factors, and meteorology. Results 3,659,828 COVID-19 cases and 138,552 deaths were reported in 3,076 US counties from January 22, 2020 to July 17, 2020, with an overall observed case-fatality rate of 3.8%. County-level average NO 2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models. When adjusted for co-pollutants, per inter-quartile range (IQR) increase in NO 2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 11.3% (95% CI 4.9% to 18.2%) and 16.2% (95% CI 8.7% to 24.0%), respectively. We did not observe significant associations between COVID-19 case-fatality rate and long-term exposure to PM 2.5 or O 3 , although per IQR increase in PM 2.5 (2.6 ug/m 3 ) was marginally associated with 14.9% (95% CI: 0.0% to 31.9%) increase in COVID-19 mortality rate when adjusted for co-pollutants. Discussion Long-term exposure to NO 2 , which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM 2.5 and O 3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO 2 levels. Continuation of current efforts to lower traffic emissions and ambient air pollution may be an important component of reducing population-level risk of COVID-19 case-fatality and mortality.

These results demonstrate the usefulness of separating total personal particle exposures into their ambient and nonambient components. The results support previous epidemiologic findings using ambient concentrations by demonstrating an association between health outcomes and ambient (outdoor origin) particle exposures but not with nonambient (indoor origin) particle exposures.

Most time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. IMPLICATIONSAs epidemiological studies aim to attribute observed health effects to outdoor air pollution, the contribution of outdoor air pollutants to population exposure must be assessed. To support time-series epidemiological studies that evaluate the health impacts of short-term changes in air pollution, an exposure metric is required for which the day-to-day variability in personal exposures reflects the variability of ambient concentrations being measured. We found that personal exposures to particulate sulfate in a group of subjects at risk for adverse health effects of particulate air pollution were highly correlated, over time, with ambient particle concentrations. Personal exposures to sulfate were highly correlated with ambient levels across all individuals and all levels of exposure, whereas correlations between personal exposures to PM 2.5 and ambient particle concentrations were lower and more variable. Overall, we have shown that a personal measure of exposure to outdoor source PM is highly related to variation in ambient levels of PM, lending support to time-series epidemiological studies.Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM 2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM 10 and PM 2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO 4 2-, which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM 2.5 samples as an indicator of accumulation mode particulate matter of ambient origin.The mean personal and ambient PM 2.5 concentrations were 18 µg/m 3 and 11 µg/m 3 , respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM 2.5 or SO 4 2-. All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO 4 2-was more highly correlated with all ambient measures than PM 2.5 ....

Background: Animal models suggest that the cardiovascular effects of air pollution result in part from inflammation caused by proinflammatory mediators originating in the lung. In a human study of the cardiovascular effects of air pollution, we aimed to evaluate the potential association between air pollution levels and the fraction of exhaled nitric oxide (FE NO ), a non-invasive measure of airway inflammation. Methods: Breath samples were collected weekly between September and December 2000 in a community based group of elderly subjects (median age 70.7 years) in Steubenville, Ohio. The samples were analysed for NO. Air pollution levels were measured concurrently at a central site monitor. Results: An increase in the 24 hour average PM 2.5 concentration of 17.7 mg/m 3 was associated with an increase in FE NO of 1.45 ppb (95% CI 0.33 to 2.57) in models adjusted for subject, week of study, day of the week, hour of the day, ambient barometric pressure, temperature, and relative humidity. This represents a change of approximately 15% compared with the mean FE NO in the cohort (9.9 ppb). A significant association was also observed for a 24 hour moving average of ambient NO (0.83 ppb increase, 95% CI 0.26 to 1.40). In two-pollutant models, the magnitude and precision of the PM 2.5 effect was not reduced and the ambient NO effect was no longer significant. The associations between FE NO and PM 2.5 were significantly higher in subjects with a doctor's diagnosis of COPD (p value for interaction = 0.03). Conclusions: Ambient pollution may lead to airway inflammation as measured by FE NO . These subclinical inflammatory changes may be an important step in the pathogenesis of the cardiopulmonary effects induced by exposure to air pollution.

Background:The novel human coronavirus disease 2019 pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis. Methods:We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO 2 , PM 2.5 and O 3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors.Results: 1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO 2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO 2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM 2.5 or O 3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM 2.5 (3.4 ug/m 3 ) was marginally associated with 10.8% (95% CI: -1.1% to 24.1%) increase in COVID-19 mortality rate. Discussions and Conclusions:Long-term exposure to NO 2 , which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of longterm PM 2.5 and O 3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO 2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.