Is ozone less deadly than we thought?

28 Jan 2019

(Image courtesy: Shutterstock/Johnny-ka)

Global premature mortality due to respiratory problems from ozone exposure is up to 60% lower than previously thought, researchers in the US and the UK have found.

The result comes from an analysis of ground-based data, rather than exposure estimates from computer models.

“I would certainly classify [the result] as good news,” says Karl Seltzer of Duke University, US. “The estimated health burden is still high, but not as high.”

There is much evidence linking both short-term and long-term ozone exposure to health problems such as respiratory diseases.

In the past, however, it has proven difficult to assess the size of these health impacts. A shortage of ground-based ozone-monitoring stations has left researchers with little option but to estimate global exposure values from chemical transport models. When the outputs of such models were compared with the data that did exist, it became clear that the models tend to overestimate ozone exposure.

In recent years, more ground-based data have become available, particularly for countries such as China. These have opened up the possibility of a truly global health-impact analysis without resorting to modelled ozone. “More people are becoming aware of the importance in collecting such data,” says Seltzer.

Seltzer and colleagues collected hourly ozone data for 2015 from monitoring networks in the US, Europe and China, and translated them into values on a grid. For each of the grid squares, they then found values for population numbers and mortality rates. Using “exposure–response” relationships from epidemiological studies, the researchers estimated the premature mortalities attributable to long-term ozone exposure.

The resulting map showed that Europe had 32,000 such mortalities whilst the US had 34,000 and China had 200,000. The values were between about 20% and 60% lower than those generated by chemical transport models – in large part, the researchers say, because those models are biased towards greater ozone exposure.

“These results demonstrate how small biases in [the] modelled results of long-term ozone exposure can amplify estimated health impacts,” the team concludes.

Seltzer hopes that the study will create a clearer picture of regional health challenges for policy makers, so that they can make better-informed decisions about how to tackle global health.

That said, the picture is not yet complete. In a few places in the health-impact map, there still weren’t enough observations for Seltzer and colleagues to make long-term exposure estimates. As a result, Seltzer is trying to use machine-learning tools to fill in the gaps.

The team reported the findings in Environmental Research Letters (ERL).

28/01/2019 FROM PHYSICSWORLD.COM