Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter*

From hourly ozone observations obtained from three regions Houston, Dallas, and West Texas we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutional neural network and Shapely additive explanation (SHAP) to examine the complex underlying nonlinearity between variations of surface ozone and meteorological factors. Results of the models showed that between 2000 and 2019, specific humidity (38% and 27%) and temperature (28% and 37%) contributed the most to ozone formation over the Houston and Dallas metropolitan areas, respectively. On the other hand, the results show that solar radiation (50%) strongly impacted ozone variation over West Texas during this time. Using a combination of the Kolmogorov-Zurbenko (KZ) filter and multiple linear regression, we also evaluated the influence of meteorology on ozone and quantified the contributions of meteorological parameters to trends in surface ozone formation. Our findings showed that in Houston and Dallas, meteorology influenced ozone variations to a large extent. The impacts of meteorology on West Texas, however, showed meteorological factors had fewer influences on ozone variabilities from 2000 to 2019. This study showed that SHAP analysis and the KZ approach can investigate the contributions of the meteorological factors on ozone concentrations and help policymakers enact effective ozone mitigation policies.

Automated summary

In this study, the contributions of meteorology to changes in surface ozone were investigated using hourly ozone observations from Houston, Dallas, and West Texas. A deep convolutional neural network and Shapely additive explanation (SHAP) were applied to examine the relationship between surface ozone and meteorological factors. The results showed that specific humidity and temperature had the greatest contribution to ozone formation in the Houston and Dallas metropolitan areas, while solar radiation strongly impacted ozone variation over West Texas. Additionally, the study quantified the influence of meteorology on ozone using the Kolmogorov-Zurbenko (KZ) filter and multiple linear regression, and found that meteorology had a significant impact on ozone variations in Houston and Dallas, but a smaller influence in West Texas. This research highlights the importance of SHAP analysis and the KZ approach in understanding the contributions of meteorological factors to ozone concentrations and informing effective ozone mitigation policies.