Uncertainties in tropospheric ozone changes due to natural precursor emissions

Accurate modelling of tropospheric ozone is crucial for understanding its climate and health effect, yet the uncertainty associated with natural ozone precursor emissions such as lightning and soil NO_x is often overlooked. Here we apply a global chemical transport model, GEOS-Chem High Performance, to explore this uncertainty.

The modelled present-day tropospheric ozone burden, under low to high natural NO_x emissions levels (set to align with the current literature’s range), varies from 285 to 373 Tg; primarily attributed to lightning NO_x uncertainty. Such a range far exceeds the ozone difference driven by anthropogenic emissions between the two most disparate SSP scenarios in 2050 (33 Tg). Ozone’s sensitivity to natural emissions is the highest around the tropical upper troposphere where ozone’s climate effect is also large, and would be even higher if anthropogenic emissions were reduced along the SSP1-2.6 pathway. At the surface, global mean warm-season ozone ranges from 32.4 to 38.8 ppbv, mainly due to soil NO_x. This especially introduces large ozone uncertainties in southern hemisphere regions such as the Amazon and Australia.

We also examine ΔO₃-anthro, the ozone change driven by anthropogenic emissions changes up-to 2050. We found that with respect to tropospheric ozone burden, ΔO₃-anthro shows limited differences between high and low natural emission levels (~13%), implying that the estimate of future changes in ozone radiative forcing is subject to less uncertainty from uncertain natural emissions than the present-day ozone radiative forcing itself. However, ΔO₃-anthro related to the surface ozone exposure metric shows significant contrasts with different natural NO_x emissions. The largest difference exceeds 5 ppbv (~50%) in regions such as Europe, North America, eastern China, and India. We hence stress that extra care needs to be taken when using individual models to assess ozone health risks in these densely populated regions as highly uncertain natural emissions will produce a presently unconstrained error.