Meteorologically adjusted trends in UK daily maximum surface ozone concentrations

Abstract Different cumulus schemes cause significant discrepancies in simulated precipitation, cloud cover, and temperature, which in turn lead to remarkable differences in simulated biogenic volatile organic compound (BVOC) emissions and surface ozone concentrations. As part of an effort to investigate the impact (and its uncertainty) of climate changes on U.S. air quality, this study evaluates the sensitivity of BVOC emissions and surface ozone concentrations to the Grell (GR) and Kain–Fritsch (KF) cumulus parameterizations. Overall, using the KF scheme yields less cloud cover, larger incident solar radiation, warmer surface temperature, and higher boundary layer height and hence generates more BVOC emissions than those using the GR scheme. As a result, the KF (versus GR) scheme produces more than 10 ppb of summer mean daily maximum 8-h ozone concentration over broad regions, resulting in a doubling of the number of high-ozone occurrences. The contributions of meteorological conditions versus BVOC emissions on regional ozone sensitivities to the choice of the cumulus scheme largely offset each other in the California and Texas regions, but the contrast in BVOC emissions dominates over that in the meteorological conditions for ozone differences in the Midwest and Northeast regions. The result demonstrates the necessity of considering the uncertainty of future ozone projections that are identified with alternative model physics configurations.

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Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

Atmospheric Chemistry and Physics ◽

10.5194/acp-5-1187-2005 ◽

2005 ◽

Vol 5 (5) ◽

pp. 1187-1203 ◽

Cited By ~ 123

Author(s):

C. Ordóñez ◽

H. Mathis ◽

M. Furger ◽

S. Henne ◽

C. Hüglin ◽

...

Keyword(s):

Statistical Model ◽

Surface Ozone ◽

Global Radiation ◽

Vertical Mixing ◽

Analysis Of Covariance ◽

Daily Maximum ◽

Ozone Concentrations ◽

Four Seasons ◽

Lower Effect ◽

The Impact

Abstract. An Analysis of Covariance (ANCOVA) was used to derive the influence of the meteorological variability on the daily maximum ozone concentrations at 12 low-elevation sites north of the Alps in Switzerland during the four seasons in the 1992–2002 period. The afternoon temperature and the morning global radiation were the variables that accounted for most of the meteorological variability in summer and spring, while other variables that can be related to vertical mixing and dilution of primary pollutants (afternoon global radiation, wind speed, stability or day of the week) were more significant in winter. In addition, the number of days after a frontal passage was important to account for ozone build-up in summer and ozone destruction in winter. The statistical model proved to be a robust tool for reducing the impact of the meteorological variability on the ozone concentrations. The explained variance of the model, averaged over all stations, ranged from 60.2% in winter to 71.9% in autumn. The year-to-year variability of the seasonal medians of daily ozone maxima was reduced by 85% in winter, 60% in summer, and 50% in autumn and spring after the meteorological adjustment. For most stations, no significantly negative trends (at the 95% confidence level) of the summer medians of daily O3 or Ox (O3+NO2) maxima were found despite the significant reduction in the precursor emissions in Central Europe. However, significant downward trends in the summer 90th percentiles of daily Ox maxima were observed at 6 sites in the region around Zürich (on average −0.73 ppb yr-1 for those sites). The lower effect of the titration by NO as a consequence of the reduced emissions could partially explain the significantly positive O3 trends in the cold seasons (on average 0.69 ppb yr-1 in winter and 0.58 ppb yr-1 in autumn). The increase of Ox found for most stations in autumn (on average 0.23 ppb yr-1) and winter (on average 0.39 ppb yr-1) could be due to increasing European background ozone levels, in agreement with other studies. The statistical model was also able to explain the very high ozone concentrations in summer 2003, the warmest summer in Switzerland for at least ~150 years. On average, the measured daily ozone maximum was 15 ppb (nearly 29%) higher than in the reference period summer 1992–2002, corresponding to an excess of 5 standard deviations of the summer means of daily ozone maxima in that period.

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Can a global model reproduce observed trends in summertime surface ozone levels?

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-6983-2012 ◽

2012 ◽

Vol 12 (15) ◽

pp. 6983-6998 ◽

Cited By ~ 17

Author(s):

S. Koumoutsaris ◽

I. Bey

Keyword(s):

Transport Model ◽

Control Strategies ◽

Surface Ozone ◽

The United States ◽

Daily Maximum ◽

Chemical Transport Model ◽

Ozone Concentrations ◽

Western Us ◽

Ozone Trends ◽

Rural Sites

Abstract. Quantifying trends in surface ozone concentrations is critical for assessing pollution control strategies. Here we use observations and results from a global chemical transport model to examine the trends (1991–2005) in daily maximum 8-h average concentrations in summertime surface ozone at rural sites in Europe and the United States (US). We find a decrease in observed ozone concentrations at the high end of the probability distribution at many of the sites in both regions. The model attributes these trends to a decrease in local anthropogenic ozone precursors, although simulated decreasing trends are overestimated in comparison with observed ones. The low end of observed distribution show small upward trends over Europe and the western US and downward trends in Eastern US. The model cannot reproduce these observed trends, especially over Europe and the western US. In particular, simulated changes between the low and high end of the distributions in these two regions are not significant. Sensitivity simulations indicate that emissions from far away source regions do not affect significantly summer ozone trends at both ends of the distribution in both Europe and US. Possible reasons for discrepancies between observed and simulated trends are discussed.

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Dynamic Adjustment of Climatological Ozone Boundary Conditions for Air-Quality Forecasts

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-13643-2010 ◽

2010 ◽

Vol 10 (6) ◽

pp. 13643-13688 ◽

Cited By ~ 4

Author(s):

P. A. Makar ◽

W. Gong ◽

C. Mooney ◽

J. Zhang ◽

D. Davignon ◽

...

Keyword(s):

Air Quality ◽

High Resolution ◽

Boundary Conditions ◽

Surface Ozone ◽

Daily Maximum ◽

Tropopause Height ◽

Dynamic Adjustment ◽

Air Quality Model ◽

Maximum Surface ◽

Ozone Profile

Abstract. Ten different approaches for applying lateral and top climatological boundary conditions for ozone have been evaluated using the off-line regional air-quality model AURAMS. All ten approaches employ the same climatological ozone profiles, but differ in the manner in which they are applied, via the inclusion or exclusion of (i) a dynamic adjustment of the climatological ozone profile in response to the model-predicted tropopause height, (ii) a sponge zone for ozone on the model top, (iii) upward extrapolation of the climatological ozone profile, and (iv) different mass consistency corrections. The model performance for each approach was evaluated against North American surface ozone and ozonesonde observations from the BAQS-Met field study period in the summer of 2007. The original daily one-hour maximum surface ozone biases of about +15 ppbv were greatly reduced (halved) in some simulations using alternative methodologies. However, comparisons to ozonesonde observations showed that the reduction in surface ozone bias sometimes came at the cost of significant positive biases in ozone concentrations in the free troposphere and upper troposphere. The best overall performance throughout the troposphere was achieved using a methodology that included dynamic tropopause height adjustment, no sponge zone at the model top, extrapolation of ozone when required above the limit of the climatology, and no mass consistency corrections (global mass conservation was still enforced). The simulation using this model version had a one-hour daily maximum surface ozone bias of +8.6 ppbv, with small reductions in model correlation, and the best comparison to ozonesonde profiles. This recommended and original methodologies were compared for two further case studies: a high-resolution simulation of the BAQS-Met measurement intensive, and a study of the downwind region of the Canadian Rockies. Significant improvements were noted for the high resolution simulations during the BAQS-Met measurement intensive period, both in formal statistical comparisons and time series comparisons of events at surface stations. The tests for the downwind-Rockies region showed that the coupling between vertical transport associated with troposphere/stratosphere exchange, and that associated with boundary layer turbulent mixing, may contribute to ozone positive biases.

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IntelliO3-ts v1.0: A neural network approach to predict near-surface ozone concentrations in Germany

10.5194/gmd-2020-169 ◽

2020 ◽

Author(s):

Felix Kleinert ◽

Lukas H. Leufen ◽

Martin G. Schultz

Keyword(s):

Time Series ◽

Surface Ozone ◽

Training Data ◽

Horizontal Wind ◽

Daily Maximum ◽

High Exposure ◽

Near Surface ◽

Reference Models ◽

Ozone Concentrations ◽

Single Station

Abstract. The prediction of near-surface ozone concentrations is important to support regulatory procedures for the protection of humans from high exposure to air pollution. In this study, we introduce a data-driven forecasting model named IntelliO3-ts, which consists of multiple convolutional neural layers (CNN), grouped together as inception blocks. The model is trained with measured multi-year ozone and nitrogen oxides concentrations of more than 300 German measurement stations in rural environments, and six meteorological variables from the meteorological COSMO reanalysis. This is by far the most extensive dataset used for time series predictions based on neural networks so far. IntelliO3-ts allows predicting daily maximum 8-hour average (dma8eu) ozone concentrations for a lead time of up to four days, and we show that the model outperforms standard reference models like persistence. Moreover, we demonstrate that IntelliO3-ts outperforms climatological reference models for the first two days, while it does not add any genuine value for longer lead times. We attribute this to the limited deterministic information that is contained in the single station time series training data. We applied a bootstrapping technique to analyse the influence of different input variables and found, that the previous day ozone concentrations are of major importance, followed by 2 m temperature. As we did not use any geographic information to train IntelliO3-ts in its current version and included no relation between stations, the influence of the horizontal wind components on the model performance is minimal. We expect that the inclusion of advection-diffusion terms in the model could improve results in future versions of our model.

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Significant increase of surface ozone at a regional background station in the eastern China

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-31951-2015 ◽

2015 ◽

Vol 15 (21) ◽

pp. 31951-31972 ◽

Cited By ~ 3

Author(s):

Z. Q. Ma ◽

J. Xu ◽

W. J. Quan ◽

Z. Y. Zhang ◽

W. L. Lin

Keyword(s):

Control Strategies ◽

Surface Ozone ◽

Eastern China ◽

Filter Method ◽

Daily Maximum ◽

Ozone Pollution ◽

Short Term ◽

Ozone Concentrations ◽

Long Term Trend

Abstract. Ozone pollution has become one of the top environmental concerns in eastern China. Quantifying temporal trend of surface ozone concentrations is very meaningful to assess the impacts of the anthropogenic precursor reductions and the effects of emission control strategies. The level of surface ozone is impacted by both emissions of precursors and meteorological conditions. In order to examine the variation trend of ozone from 2003 to 2015 in Shangdianzi regional atmosphere background station, the modified KZ filter method was performed in this study to remove the influence of meteorological fluctuations on ozone concentrations. Results reveal that the short-term component, seasonal component and long-term component of ozone account for 36.4, 57.6 and 2.2 % of the total variance, respectively. The long-term trend shows that the surface daily maximum 8-h O3 has undergone a significant increase during 2003–2015, with a rate of 1.1 ppb yr−1. We find that the increase was completely resulted from the change of the emissions when the influence of the meteorological factors was eliminated. Furthermore, the variation of NO2 indicated that VOCs seemed to play more important role in the increase trend of the surface ozone.

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Can a global model reproduce observed trends in summertime surface ozone levels?

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-2025-2012 ◽

2012 ◽

Vol 12 (1) ◽

pp. 2025-2056 ◽

Cited By ~ 1

Author(s):

S. Koumoutsaris ◽

I. Bey

Keyword(s):

Transport Model ◽

Control Strategies ◽

Surface Ozone ◽

The United States ◽

Daily Maximum ◽

Chemical Transport Model ◽

Ozone Precursors ◽

Ozone Concentrations ◽

Western Us ◽

Ozone Trends

Abstract. Quantifying trends in surface ozone concentrations are critical for assessing pollution control strategies. Here we use observations and results from a global chemical transport model to examine the trends (1991–2005) in daily maximum 8-hour average concentrations in summertime surface ozone at rural sites in Europe and the United States. We find a decrease in observed ozone concentrations at the high end of the probability distribution at many of the sites in both regions. The model attributes these trends to a decrease in local anthropogenic ozone precursors, although simulated decreasing trends are overestimated in comparison with observed ones. The low end of observed distribution show small upward trends over Europe and the western US and downward trends in Eastern US. The model cannot reproduce these observed trends, especially over Europe and the western US. In particular, simulated changes between the low and high end of the distributions in these two regions are not significant. Sensitivity simulations indicate that emissions from far away source regions do not affect significantly ozone trends at both ends of the distribution. This is in contrast with previously available results, which indicated that increasing ozone trends at the low percentiles may reflect an increase in ozone background associated with increasing remote sources of ozone precursors. Possible reasons for discrepancies between observed and simulated trends are discussed.

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