Abstract
Long-term ozone (O3) exposure estimates from chemical transport models are frequently paired with exposure-response relationships from epidemiological studies to estimate associated health burdens. Impact estimates using such methods can include biases from model-derived exposure estimates. We use data solely from dense ground-based monitoring networks in the United States, Europe, and China for 2015 to estimate long-term O3 exposure and calculate premature respiratory mortality using exposure-response relationships derived from two separate analyses of the American Cancer Society Cancer Prevention Study-II (ACS CPS-II) cohort. Using results from the larger, extended ACS CPS-II study, 34 000 (95% CI: 24, 44 thousand), 32 000 (95% CI: 22, 41 thousand), and 200 000 (95% CI: 140, 253 thousand) premature respiratory mortalities are attributable to long-term O3 exposure in the USA, Europe and China, respectively, in 2015. Results are approximately 32%–50% lower when using an older analysis of the ACS CPS-II cohort. Both sets of results are lower (∼20%–60%) on a region-by-region basis than analogous prior studies based solely on modeled O3, due in large part to the fact that the latter tends to be high biased in estimating exposure. This study highlights the utility of dense observation networks in estimating exposure to long-term O3 exposure and provides an observational constraint on subsequent health burdens for three regions of the world. In addition, these results demonstrate how small biases in modeled results of long-term O3 exposure can amplify estimated health impacts due to nonlinear exposure-response curves.
Highlights
There is strong epidemiological and toxicological evidence linking exposure to ambient ozone (O3) with adverse health impacts (US EPA 2013)
Long-term ozone (O3) exposure estimates from chemical transport models are frequently paired with exposure-response relationships from epidemiological studies to estimate associated health burdens
Due to spatial and temporal limitations of groundbased monitors, as well as difficulty in relating the vertical column density of O3 observed by satellites to surface values (Duncan et al 2014), global estimates of long-term O3 exposure are generally estimated using output from state-of-the-art chemical transport models (CTMs); (e.g. Anenberg et al 2010, Silva et al 2013, Brauer et al 2015, Lelieveld et al 2015, Malley et al 2017, Shindell et al 2018)
Summary
There is strong epidemiological and toxicological evidence linking exposure to ambient ozone (O3) with adverse health impacts (US EPA 2013). While historical research has largely focused on impacts attributable to short-term O3 exposure, there is a growing body of literature suggesting a significant association between long-term ambient O3 exposure and increased premature mortality, in particular from respiratory diseases (Jerrett et al 2009, Lipsett et al 2011, Zanobetti and Schwartz 2011, REVIHAAP 2013, Turner et al 2016). Some studies even report significant associations with increased premature cardiovascular mortality (Lipsett et al 2011, Jerrett et al 2013, Crouse et al 2015, Cakmak et al 2016, Turner et al 2016, Day et al 2017) When incorporating these epidemiological updates, the estimated health burden attributable to long-term O3 exposure increases (Malley et al 2017, Shindell et al 2018), indicating that efforts to reduce long-term O3 exposure could be more effective in reducing total air pollution-attributable premature mortalities than previously identified (Schwartz 2016)
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