the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Feb 2025
Urban Ozone Trends in Europe and the USA (2000–2021)
Abstract. Trends in urban O3 and NO2 across Europe and the United States of America were explored between 2000–2021. Using surface monitoring site data from the TOAR-II and European Environment Agency databases, piecewise quantile regression (PQR) analysis was performed on 228 O3 time series (144 European, 84 USA) and 322 NO2 times series (245 European, 77 USA). The PQR analysis permitted 2 break points over the 23 year period to balance the intent to describe changes over a large time period, while still capturing the abrupt changes that can occur in urban atmospheres. Regressions were performed over quantiles ranging from 0.05 to 0.95 and indications of a slowing in the increase of high European O3 levels was observed. In Europe, more trends were found to having an increasing O3 trend between 2015–2021 compared with 2000–2004. The reverse was true in the USA, with a reduction in the number of sites with increasing O3 trends when the same periods were compared. An analysis of the change points revealed a large proportion of sites in Europe, were the second change point in NO2 switched from a positive to negative trend, occurred in 2020 (41/43 second change points in this year). This was attributed a reduction in NO2 due to the COVID-19 pandemic, however, in some cases these increasing trends have sustained beyond the recovery from restrictions.
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RC1: 'Comment on egusphere-2024-3743', Anonymous Referee #1, 02 Mar 2025
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This manuscript describes a trend analysis of urban ozone in Europe and USA over 2000-2021. I believe the authors have great ambition and spent a great deal of time putting the analysis together. Unfortunately, their approach and discussion appear to be premature and unskilled for ACP. In general, I will expect a vast and extensive rewritten if this manuscript is not rejected. Some major issues are pointed out as follows:
- Methodology: Although using nonlinear methods such as Loess can visually identify the change points, are the authors really inspecting all the ozone and no2 time series (>500) and recording the change points for each individual location?
- Methodology: AIC is most useful to avoid overfitting, so it can be used to determine if a model with change points (more parameters) is actually better than a model without change points (fewer parameters). But AIC does not tell us the optimal changepoint location, the authors should discuss how they select the change point locations. More importantly, how to select change points objectively (eg, Muggeo 2003; Chen et al., 2011), given that some change points may be hindered by data variability and not visually detectable. The authors should also properly define what they mean regarding change points. To me, the authors merely compare the trends between different periods, and see which locations have large trend differences. This does not really change point analysis in statistics.
Chen, C. W., Chan, J. S., Gerlach, R., & Hsieh, W. Y. (2011). A comparison of estimators for regression models with change points. Statistics and Computing, 21, 395-414.
Muggeo, V. M. (2003). Estimating regression models with unknown break‐points. Statistics in medicine, 22(19), 3055-3071.
- Majority of US ozone studies show the ozone reductions since 2000 in response to emissions controls, but this study shows contradicted results. The fundamental problem of this study is that they use daily median ozone to conduct trend analysis, which is neither relevant to human health nor generally interesting. Medians can occur either daytime in one day or nighttime in another, mixing two makes the trends really ambiguous and difficult to interpret. I don't understand why the authors do not use MDA8 or daytime/nighttime observations, especially since this study is focused on urban ozone.
- Scientific interpretations are essential for ACP. Most discussions have only scratched the surface and not provided sufficient interpretations. For example, NOx is not the only proxy for ozone production, disproportionate seasonal trends (winter increases and summer decreases), wildfires, and weather (2003 heat wave in Europe and 2012 heatwave in the eastern US) also play important roles (Cooper et al. 2012; Simon et al., 2015; Seltzer et al., 2020; Wells et al., 2021; Chang et al., 2023), but none of these factors are discussed.
Chang, K. L., Cooper, O. R., Rodriguez, G., Iraci, L. T., Yates, E. L., Johnson, M. S., ... & Tarasick, D. W. (2023). Diverging ozone trends above western North America: Boundary layer decreases versus free tropospheric increases. Journal of Geophysical Research: Atmospheres, 128(8), e2022JD038090.
Cooper, O. R., Gao, R. S., Tarasick, D., Leblanc, T., & Sweeney, C. (2012). Long‐term ozone trends at rural ozone monitoring sites across the United States, 1990–2010. Journal of Geophysical Research: Atmospheres, 117(D22).
Seltzer, K. M., Shindell, D. T., Kasibhatla, P., & Malley, C. S. (2020). Magnitude, trends, and impacts of ambient long-term ozone exposure in the United States from 2000 to 2015. Atmospheric Chemistry and Physics, 20(3), 1757-1775.
Simon, H., Reff, A., Wells, B., Xing, J., & Frank, N. (2015). Ozone trends across the United States over a period of decreasing NOx and VOC emissions. Environmental science & technology, 49(1), 186-195.
Wells, B, Dolwick, P, Eder, B, Evangelista, M, Foley, K, Mannshardt, E, Misenis, C, Weishampel, A. 2021. Improved estimation of trends in US ozone concentrations adjusted for interannual variability in meteorological conditions. Atmospheric Environment 248: 118234. http://dx.doi.org/10.1016/j.atmosenv.2021.118234.
- If the authors aim to study extreme ozone events (Section 3.2), they should know the difference between the 95th percentile of daily medians and the 95th percentile of daily MDA8 or hourly observations, these are completely different concepts. Using daily medians to study extremes is completely misleading and unreasonable.
- All the figures with maps (eg Figs 3, 4, 9-12) have low quality.
l22 which WHO standards?
l49 please clarify which analysis will end in 2021 or 2023.
l63 medians are not calculated through averaging.
l64 please provide justifications. A visual inspection may be subjective.
l66 deseasonalized
l217 should the units of slope be ppb/decade or ppb/year?
Citation: https://doi.org/10.5194/egusphere-2024-3743-RC1
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