- 2018/10/12 11:30
- Duke/York study finds long-term exposure to ozone has significant impacts on human health, but lower than prior modeling results
A team from Duke University in the US and University of York in the UK have utilized a novel method to estimate long-term ozone exposure and previously reported epidemiological results to quantify the health burden from long-term ozone exposure in three major regions of the world. The team’s observationally-derived data shows smaller human-health impacts when compared to prior modeling results.
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.
—Seltzer et al.
The researchers used 2015 data from ground-based monitoring networks in the US, Europe and China to estimate long-term O3 exposure. They then calculated premature mortalities using exposure-response relationships from two American Cancer Society (ACS) cancer prevention studies.
Global estimates of O3 exposure are often made using chemical transport models (CTMs). However, the Duke/York team based the study on observed air quality data, because it has several advantages over CTM modelling approaches, Seltzer said.
This difference is due to small biases in modeled results. These small biases are subsequently amplified by non-linear exposure-response curves. This highlights the importance of accurately estimating long-term O3 exposure in health impact assessments. The overall findings from this study have important implications for policy makers and the public, for several reasons.
First, health impacts attributable to long-term O3 exposure are higher when using the newest ACS CPS-II cohort analysis. Plus, the impacts are expanded further if the association between long-term O3 exposure and cardiovascular mortality is indeed shown to be causal and included in the total health burden estimates.
Second, results from the newest ACS CPS-II cohort analysis suggest that O3 exposure should be considered year-round. This is particularly relevant for the three regions included in this analysis, where the seasonal cycle and regional distributions of O3 have shifted over the last few decades.
Finally, these results also highlight the importance of accurately estimating O3 exposure and the consequences of high exposure bias in estimating impacts for health assessments.
Karl M Seltzer et al. (2018) “Measurement-based assessment of health burdens from long-term ozone exposure in the United States, Europe, and China” Environ. Res. Lett. 13 doi: 10.1088/1748-9326/aae29d