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Abstract. High-quality long-term observational records are essential to ensure appropriate and reliable trend detection of tropospheric ozone. However, the necessity of maintaining high sampling frequency, in addition to continuity, is often under-appreciated. A common assumption is that, so long as long-term records (e.g., a span of a few decades) are available, (1) the estimated trends are accurate and precise, and (2) the impact of small-scale variability (e.g., weather) can be eliminated. In this study, we show that the undercoverage bias (e.g., a type of sampling error resulting from statistical inference based on sparse or insufficient samples, such as once-per-week sampling frequency) can persistently reduce the trend accuracy of free tropospheric ozone, even if multi-decadal time series are considered. We use over 40 years of nighttime ozone observations measured at Mauna Loa, Hawaii (representative of the lower free troposphere), to make this demonstration and quantify the bias in monthly means and trends under different sampling strategies. We also show that short-term meteorological variability remains a cause of an inflated long-term trend uncertainty. To improve the trend precision and accuracy due to sampling bias, two remedies are proposed: (1) a data variability attribution of colocated meteorological influence can efficiently reduce estimation uncertainty and moderately reduce the impact of sparse sampling, and (2) an adaptive sampling strategy based on anomaly detection enables us to greatly reduce the sampling bias and produce more accurate trends using fewer samples compared to an intense regular sampling strategy. 

Ground-level ozone (O3) is a key atmospheric gas that controls the oxidizing capacity of the atmosphere and has significant health and environmental implications. Due to ongoing reductions in the concentrations of O3 precursors, it is important to assess the variables influencing baseline O3 to inform pollution control strategies. This study uses a statistical model to characterize daily peak 8 h O3 concentrations at the Mount Bachelor Observatory (MBO), a rural mountaintop research station in central Oregon, from 2006–2020. The model was constrained by seven predictive variables: year, day-of-year, relative humidity (RH), aerosol scattering, carbon monoxide (CO), water vapor (WV) mixing ratio, and tropopause pressure. RH, aerosol scattering, CO, and WV mixing ratio were measured at MBO, and tropopause pressure was measured via satellite. For the full 15-year period, the model represents 61% of the variance in daily peak 8 h O3, and all predictive variables have a statistically significant (p < 0.05) impact on daily peak 8 h O3 concentrations. Our results show that daily peak 8 h O3 concentrations at MBO are well-predicted by the model, thereby providing insight into what affects baseline O3 levels at a rural site on the west coast of North America. 

Abstract. Long et al. (2021) conducted a detailed study of possible interferences inmeasurements of surface O3 by UV spectroscopy, which measures the UV transmission in ambient and O3-scrubbed air. While we appreciate the careful work done in this analysis, there were several omissions, and in one case, the type of scrubber used was misidentified as manganese dioxide (MnO2) when in fact it was manganese chloride (MnCl2). This misidentification led to the erroneous conclusion that all UV-based O3 instruments employing solid-phase catalytic scrubbers exhibit significant positive artifacts, whereas previous research found this not to be the case when employing MnO2 scrubber types. While the Long et al. (2021) study, and our results, confirm the substantial bias in instruments employing an MnCl2 scrubber, a replication of the earlier work with an MnO2 scrubber type and no humidity correction is needed. 

Abstract. With a few exceptions, most studies on tropospheric ozone (O3) variability during and following the COrona VIrus Disease (COVID-19) economic downturn focused on high-emission regions or urban environments. In this work, we investigated the impact of the societal restriction measures during the COVID-19 pandemic on surface O3 at several high-elevation sites across North America and western Europe. Monthly O3 anomalies were calculated for 2020 and 2021, with respect to the baseline period 2000–2019, to explore the impact of the economic downturn initiated in 2020 and its recovery in 2021. In total, 41 high-elevation sites were analyzed: 5 rural or mountaintop stations in western Europe, 19 rural sites in the western US, 4 sites in the western US downwind of highly polluted source regions, and 4 rural sites in the eastern US, plus 9 mountaintop or high-elevation sites outside Europe and the United States to provide a “global” reference. In 2020, the European high-elevation sites showed persistent negative surface O3 anomalies during spring (March–May, i.e., MAM) and summer (June–August, i.e., JJA), except for April. The pattern was similar in 2021, except for June. The rural sites in the western US showed similar behavior, with negative anomalies in MAM and JJA 2020 (except for August) and MAM 2021. The JJA 2021 seasonal mean was influenced by strong positive anomalies in July due to large and widespread wildfires across the western US. The polluted sites in the western US showed negative O3 anomalies during MAM 2020 and a slight recovery in 2021, resulting in a positive mean anomaly for MAM 2021 and a pronounced month-to-month variability in JJA 2021 anomalies. The eastern US sites were also characterized by below-mean O3 for both MAM and JJA 2020, while in 2021 the negative values exhibited an opposite structure compared to the western US sites, which were influenced by wildfires. Concerning the rest of the world, a global picture could not be drawn, as the sites, spanning a range of different environments, did not show consistent anomalies, with a few sites not experiencing any notable variation. Moreover, we also compared our surface anomalies to the variability of mid-tropospheric O3 detected by the IASI (Infrared Atmospheric Sounding Interferometer) satellite instrument. Negative anomalies were observed by IASI, consistent with published satellite and modeling studies, suggesting that the anomalies can be largely attributed to the reduction of O3 precursor emissions in 2020.