scholarly journals Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea

2021 ◽  
Vol 13 (10) ◽  
pp. 1877
Author(s):  
Ukkyo Jeong ◽  
Hyunkee Hong
Keyword(s):  
South Korea ◽  
Spatial Resolution ◽  
Atmospheric Composition ◽  
Mixing Ratio ◽  
Mean Values ◽  
Mixing Ratios ◽  
Tropospheric No2 ◽  
Korean Ministry ◽  
Surface Mixing ◽  
Rural Sites

Since April 2018, the TROPOspheric Monitoring Instrument (TROPOMI) has provided data on tropospheric NO2 column concentrations (CTROPOMI) with unprecedented spatial resolution. This study aims to assess the capability of TROPOMI to acquire high spatial resolution data regarding surface NO2 mixing ratios. In general, the instrument effectively detected major and moderate sources of NO2 over South Korea with a clear weekday–weekend distinction. We compared the CTROPOMI with surface NO2 mixing ratio measurements from an extensive ground-based network over South Korea operated by the Korean Ministry of Environment (SKME; more than 570 sites), for 2019. Spatiotemporally collocated CTROPOMI and SKME showed a moderate correlation (correlation coefficient, r = 0.67), whereas their annual mean values at each site showed a higher correlation (r = 0.84). The CTROPOMI and SKME were well correlated around the Seoul metropolitan area, where significant amounts of NO2 prevailed throughout the year, whereas they showed lower correlation at rural sites. We converted the tropospheric NO2 from TROPOMI to the surface mixing ratio (STROPOMI) using the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) profile shape, for quantitative comparison with the SKME. The estimated STROPOMI generally underestimated the in-situ value obtained, SKME (slope = 0.64), as reported in previous studies.

scholarly journals One-Year Characterization and Reactivity of Isoprene and Its Impact on Surface Ozone Formation at A Suburban Site in Guangzhou, China

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 201 ◽  
Author(s):  
Yu Zou ◽  
Xue Jiao Deng ◽  
Tao Deng ◽  
Chang Qin Yin ◽  
Fei Li
Keyword(s):  
Surface Ozone ◽  
Atmospheric Composition ◽  
Anthropogenic Factors ◽  
Mixing Ratio ◽  
Night Time ◽  
Subtropical Zone ◽  
Guangzhou City ◽  
Mixing Ratios ◽  
One Year ◽  
Suburban Site

Isoprene has a potentially large effect on ozone (O3) formation in the subtropical, highly polluted city of Guangzhou. Online measurements of isoprene in Guangzhou city are scarce; thus, isoprene levels were monitored for one year at the Guangzhou Panyu Atmospheric Composition Station (GPACS), a suburban site in Guangzhou, using an online gas chromatography-flame ionization detector (GC–FID) system to investigate the characterization and reactivity of isoprene and its effect on the O3 peak profile in different seasons. The results showed that the daily average mixing ratios of isoprene at GPACS were 0.40, 2.20, 1.40, and 0.13 mixing ratio by volume (ppbv) in spring, summer, autumn, and winter, respectively. These values were considerably higher than the mixing ratios of isoprene in the numerous other subtropical and temperate cities around the world. Furthermore, isoprene ranked first with regard to O3 formation potential (OFP) and propylene-equivalent mixing ratio among 56 measured non–methane hydrocarbons (NMHCs). The ratios of isoprene to cis-2-butene, an exhaust tracer, were determined to estimate the fractions of biogenic and anthropogenic emissions. The results revealed a much greater contribution from biogenic than anthropogenic factors during the daytime in all four seasons. In addition, night-time isoprene emissions were mostly associated with vehicles in winter, and the residual isoprene that remained after photochemical loss during the daytime also persisted into the night. The high levels of isoprene in summer and autumn may cause the strong and broad peaks of the O3 profile because of its association with the most favorable meteorological conditions (e.g., high temperature and intense solar radiation) and the highest OH mixing ratio, which could affect human health by exposing people to a high O3 mixing ratio for prolonged periods. The lower mixing ratios of isoprene resulted in a weak and sharp peak in the O3 profile in both spring and winter. The high level of isoprene in the subtropical zone could accentuate its large impact on atmospheric oxidant capacity and air quality in Guangzhou city.

Incorporation and evaluation of the CRI v2.2 chemical mechanism in UKESM1: An alternative mechanism with updated isoprene chemistry for investigating the influence of BVOCs on atmospheric composition and climate. 

2021 ◽  
Author(s):  
James Weber ◽  
Scott Archer-Nicholls ◽  
N. Luke Abraham ◽  
Youngsub M. Shin ◽  
Thomas Bannan ◽  
...  
Keyword(s):  
Peroxy Radical ◽  
Tropospheric Chemistry ◽  
Chemical Mechanism ◽  
Atmospheric Composition ◽  
Radiation Budget ◽  
Alternative Mechanism ◽  
Mixing Ratios ◽  
The United Kingdom ◽  
Surface Mixing ◽  
Phase Chemistry

<p>We present the first incorporation and evaluation of the Common Representative Intermediates version 2.2 chemistry mechanism, CRI v2.2, for use in the United Kingdom Earth System Model (UKESM1). Tuned against the MCM v3.3.1, the CRI v2.2 mechanism builds on the previous CRI version, CRI v2.1, in UKESM1 (Archer-Nicholls et al., 2020) by updating isoprene chemistry and offers a more comprehensive description of tropospheric chemistry than the standard chemistry mechanism STRAT-TROP (ST).</p><p><span>CRI v2.2 adds state-of-the-art isoprene chemistry with the introduction of HO</span><sub><span>x</span></sub><span>-recycling via the isoprene peroxy radical isomerisation pathway, </span><span>making UKESM1 one of the first CMIP6 models to include this important chemistry. </span><span>HO</span><sub><span>x</span></sub><span>-recycling has noticeable effects on oxidants in regions with large emissions of biogenic volatile organic compounds (BVOCs). Low altitude OH in tropical forested regions increases by 75-150% relative to ST, reducing the existing model low bias compared to observations. Consequently, isoprene surface mixing ratios decrease considerably (25-40%), significantly improving the model high bias relative to ST. Methane lifetime decreases by 2% and tropospheric ozone burden increases by 4%. </span></p><p>Aerosol processes also differ between CRI v2.2 and ST, resulting in changes to the size and number distributions. Relative to ST, CRI v2.2 simulates an 8% decrease in the sulphate aerosol burden with 20% decreases in the nucleation and Aitken modes. By contrast, the secondary organic aerosol (SOA) nucleation mode burden increases by 11%. Globally, the average nucleation and Aitken mode aerosol number concentrations decrease by 20%.</p><p>The differences in aerosol and gas phase chemistry between CRI v2.2 and ST are likely to have impacts on the radiation budget. We plan to use CRI v2.2 and ST to investigate the influence that the chemical mechanism has on the simulated chemistry-climate feedbacks from BVOCs. In addition, CRI v2.2 will serve as the basis for the addition of a scheme describing the formation of highly oxygenated organic molecules (HOMs) from BVOCs, facilitating a semi-explicit mechanism for new particle formation from organic species.</p>

scholarly journals Cluster analysis of European surface ozone observations for evaluation of MACC reanalysis data

2016 ◽  
Vol 16 (11) ◽  
pp. 6863-6881 ◽  
Author(s):  
Olga Lyapina ◽  
Martin G. Schultz ◽  
Andreas Hense
Keyword(s):  
Cluster Analysis ◽  
Statistical Tests ◽  
Surface Ozone ◽  
Atmospheric Composition ◽  
Regional Differentiation ◽  
Mixing Ratio ◽  
Data Set ◽  
Diurnal Cycles ◽  
Mixing Ratios ◽  
Weekly Cycles

Abstract. The high density of European surface ozone monitoring sites provides unique opportunities for the investigation of regional ozone representativeness and for the evaluation of chemistry climate models. The regional representativeness of European ozone measurements is examined through a cluster analysis (CA) of 4 years of 3-hourly ozone data from 1492 European surface monitoring stations in the Airbase database; the time resolution corresponds to the output frequency of the model that is compared to the data in this study. K-means clustering is implemented for seasonal–diurnal variations (i) in absolute mixing ratio units and (ii) normalized by the overall mean ozone mixing ratio at each site. Statistical tests suggest that each CA can distinguish between four and five different ozone pollution regimes. The individual clusters reveal differences in seasonal–diurnal cycles, showing typical patterns of the ozone behavior for more polluted stations or more rural background. The robustness of the clustering was tested with a series of k-means runs decreasing randomly the size of the initial data set or lengths of the time series. Except for the Po Valley, the clustering does not provide a regional differentiation, as the member stations within each cluster are generally distributed all over Europe. The typical seasonal, diurnal, and weekly cycles of each cluster are compared to the output of the multi-year global reanalysis produced within the Monitoring of Atmospheric Composition and Climate (MACC) project. While the MACC reanalysis generally captures the shape of the diurnal cycles and the diurnal amplitudes, it is not able to reproduce the seasonal cycles very well and it exhibits a high bias up to 12 nmol mol−1. The bias decreases from more polluted clusters to cleaner ones. Also, the seasonal and weekly cycles and frequency distributions of ozone mixing ratios are better described for clusters with relatively clean signatures. Due to relative sparsity of CO and NOx measurements these were not included in the CA. However, simulated CO and NOx mixing ratios are consistent with the general classification into more polluted and more background sites. Mean CO mixing ratios are within 140–145 nmol mol−1 (CL1–CL3) and 130–135 nmol mol−1 (CL4 and CL5), and NOx mixing ratios are within 4–6 nmol mol−1 and 2–3 nmol mol−1, respectively. These results confirm that relatively coarse-scale global models are more suitable for simulation of regional background concentrations, which are less variable in space and time. We conclude that CA of surface ozone observations provides a powerful and robust way to stratify sets of stations, being thus more suitable for model evaluation.

scholarly journals Effect of different emission inventories on modeled ozone and carbon monoxide in Southeast Asia

2014 ◽  
Vol 14 (23) ◽  
pp. 12983-13012 ◽  
Author(s):  
T. Amnuaylojaroen ◽  
M. C. Barth ◽  
L. K. Emmons ◽  
G. R. Carmichael ◽  
J. Kreasuwun ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Atmospheric Composition ◽  
Anthropogenic Emissions ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Regional Study ◽  
Mixing Ratios ◽  
Surface Mixing

Abstract. In order to improve our understanding of air quality in Southeast Asia, the anthropogenic emissions inventory must be well represented. In this work, we apply different anthropogenic emission inventories in the Weather Research and Forecasting Model with Chemistry (WRF-Chem) version 3.3 using Model for Ozone and Related Chemical Tracers (MOZART) gas-phase chemistry and Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosols to examine the differences in predicted carbon monoxide (CO) and ozone (O3) surface mixing ratios for Southeast Asia in March and December 2008. The anthropogenic emission inventories include the Reanalysis of the TROpospheric chemical composition (RETRO), the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), the MACCity emissions (adapted from the Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment projects), the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS) emissions, and a combination of MACCity and SEAC4RS emissions. Biomass-burning emissions are from the Fire Inventory from the National Center for Atmospheric Research (NCAR) (FINNv1) model. WRF-Chem reasonably predicts the 2 m temperature, 10 m wind, and precipitation. In general, surface CO is underpredicted by WRF-Chem while surface O3 is overpredicted. The NO2 tropospheric column predicted by WRF-Chem has the same magnitude as observations, but tends to underpredict the NO2 column over the equatorial ocean and near Indonesia. Simulations using different anthropogenic emissions produce only a slight variability of O3 and CO mixing ratios, while biomass-burning emissions add more variability. The different anthropogenic emissions differ by up to 30% in CO emissions, but O3 and CO mixing ratios averaged over the land areas of the model domain differ by ~4.5% and ~8%, respectively, among the simulations. Biomass-burning emissions create a substantial increase for both O3 and CO by ~29% and ~16%, respectively, when comparing the March biomass-burning period to the December period with low biomass-burning emissions. The simulations show that none of the anthropogenic emission inventories are better than the others for predicting O3 surface mixing ratios. However, the simulations with different anthropogenic emission inventories do differ in their predictions of CO surface mixing ratios producing variations of ~30% for March and 10–20% for December at Thai surface monitoring sites.

scholarly journals Measurement report: Exploring NH<sub>3</sub> behavior in urban and suburban Beijing: comparison and implications

2021 ◽  
Vol 21 (6) ◽  
pp. 4561-4573
Author(s):  
Ziru Lan ◽  
Weili Lin ◽  
Weiwei Pu ◽  
Zhiqiang Ma
Keyword(s):  
Relative Humidity ◽  
Rural Areas ◽  
Urban Site ◽  
Mixing Ratio ◽  
Mixing Ratios ◽  
Different Seasons ◽  
Rural Sites ◽  
Highly Correlated ◽  
Urban And Rural Areas ◽  
Suburban Site

Abstract. Ammonia (NH3) plays an important role in particulate matter formation; hence, its atmospheric level is relevant to human health and climate change. Due to different relative distributions of NH3 sources, concentrations of atmospheric NH3 may behave differently in urban and rural areas. However, few parallel long-term observations of NH3 exist to reveal the different behaviors of NH3 concentrations at urban and rural sites in a same region. In this study, online ammonia analyzers were used to continuously observe atmospheric NH3 concentrations at an urban site and a suburban site in Beijing from 13 January 2018 to 13 January 2019. The observed mixing ratio of NH3 averaged 21±14 ppb (range of 1.6–133 ppb) at the urban site and 22±15 ppb (range of 0.8–199 ppb) at the suburban site. The NH3 mixing ratios at the urban and suburban sites exhibited similar seasonal variations, with high values in summer and spring and low values in autumn and winter. The hourly mean NH3 mixing ratios at the urban site were highly correlated (R=0.849, P<0.01) with those at the suburban site; however, the average diurnal variations in the NH3 mixing ratios at the urban and suburban sites differed significantly, which implies different contributions from NH3 sources and sinks at the urban and suburban sites. In addition to the emission sources, meteorological factors were closely related to the changes in the NH3 concentrations. For the same temperature (relative humidity) at the urban and suburban sites, the NH3 mixing ratios increased with relative humidity (temperature). Relative humidity was the factor with the strongest influence on the NH3 mixing ratio in different seasons at the two sites. The relationships between the NH3 concentrations and temperature (relative humidity) varied from season to season and showed differences between the urban and suburban sites. The reasons for the different relationships need to be investigated in future studies. Higher wind speed mainly from the northwest sector lowered the NH3 mixing ratios at both sites. Similarly to other primary pollutants in Beijing, the NH3 mixing ratios were high when impacted by air masses from the southern sector.

scholarly journals Measurements of CFC-11, CFC-12, and HCFC-22 total columns in the atmosphere at the St. Petersburg site in 2009–2019

2021 ◽  
Vol 14 (8) ◽  
pp. 5349-5368
Author(s):  
Alexander Polyakov ◽  
Anatoly Poberovsky ◽  
Maria Makarova ◽  
Yana Virolainen ◽  
Yuri Timofeyev ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Scale ◽  
Atmospheric Composition ◽  
Independent Data ◽  
Mean Values ◽  
Mixing Ratios ◽  
Radiation Spectra ◽  
Observational Site ◽  
Ozone Depleting Substances ◽  
Atmospheric Concentrations

Abstract. Monitoring atmospheric anthropogenic halocarbons plays an important role in tracking their atmospheric concentrations in accordance with international agreements on emissions of ozone-depleting substances and, thus, in estimating the ozone layer recovery. Within the Network for the Detection of Atmospheric Composition Change (NDACC), regular Fourier transform infrared (FTIR) measurements can provide information on the abundancies of halocarbons on a global scale. We improved retrieval strategies for deriving the CFC-11 (CCl3F), CFC-12 (CCl2F2), and HCFC-22 (CHClF2) atmospheric columns from IR solar radiation spectra measured by the Bruker IFS125HR spectrometer at the St. Petersburg site (Russia). We used the Tikhonov–Phillips regularization approach for solving the inverse problem with optimized values of regularization parameters. We tested the strategies developed by comparison of the FTIR measurements with independent data. The analysis of the time series of column-averaged dry air mole fractions (Xgas) measured in 2009–2019 gives mean values of 225 pptv (parts per trillion by volume; CFC-11), 493 pptv (CFC-12), and 238 pptv (HCFC-22). Trend values total −0.40 % yr−1 (CFC-11), −0.49 % yr−1 (CFC-12), and 2.12 % yr−1 (HCFC-22). We compared the means, trends, and seasonal variability in XCFC-11, XCFC-12, and XHCFC-22 to that of (1) near-ground volume mixing ratios (VMRs), measured at the observational site Mace Head, Ireland (GVMR), (2) the mean in the 8–12 km layer VMRs, measured by ACE-FTS and averaged over 55–65∘ N latitudes (SVMR), and (3) Xgas values of the Whole Atmosphere Community Climate Model (WACCM) for the St. Petersburg site (WXgas). In general, the comparison of Xgas with the independent data showed a good agreement of their means within the systematic errors of the measurements considered. The trends observed over the St. Petersburg site demonstrate the smaller decrease rates for XCFC-11 and XCFC-12 than that of the independent data and the same increase rate for XHCFC-22. As a whole, Xgas, SVMR, and WXgas showed qualitatively similar seasonal variations, while the GVMR variability is significantly less, and only the WXHCFC-22 variations are essentially smaller than that of XHCFC-22 and SVMRHCFC-22.

Corrigendum to: Atmospheric variation of nitrous acid at different sites in Europe

2007 ◽  
Vol 4 (5) ◽  
pp. 364 ◽  
Author(s):  
Karin Acker ◽  
Detlev Möller
Keyword(s):  
Hydroxyl Radical ◽  
Nitrous Acid ◽  
Field Experiments ◽  
Early Morning ◽  
Mixing Ratio ◽  
Gas Phase Reactions ◽  
Sources And Sinks ◽  
Mixing Ratios ◽  
Secondary Pollutants ◽  
Rural Sites

Environmental context. Nitrous acid (HNO2) is an important source of the hydroxyl radical (OH.), the most important daytime oxidising species that contributes to the formation of ozone as well as of other secondary pollutants in the troposphere. Understanding the sources and sinks of HNO2 is of crucial interest for accurately modelling the chemical composition of the troposphere and predicting future trace gas concentrations. Abstract. Nitrous acid and several other atmospheric components and variables were continuously measured during complex field experiments at seven different suburban and rural sites in Europe. HNO2 is mainly formed by heterogeneous processes and is often accumulated in the nighttime boundary layer. Our results confirm that the photolysis of HNO2 is an important source of the hydroxyl radical, not only in the early morning hours but also throughout the entire day, and is often comparable with the contribution of ozone and formaldehyde photolysis. At all research sites unexpectedly high HNO2 mixing ratios were observed during the daytime (up to several hundred ppt, or pmol mol-1). Moreover, surprisingly, the HNO2 mixing ratio at the three mountain sites often showed a broad maximum or several distinct peaks at midday and lower mixing ratios during the night. Assuming a quickly established photo-equilibrium between the known significant gas phase reactions, only a few ppt HNO2 should be present around noon. The ratio of known sources to sinks indicates a missing daytime HNO2 source of 160-2600 ppt h-1 to make up the balance. Based on these values and on production mechanisms proposed in the literature we hypothesise that the daytime mixing ratio levels may only be explained by a fast electron transfer onto adsorbed NO2.

scholarly journals Ground-based stratospheric O<sub>3</sub> and HNO<sub>3</sub> measurements at Thule, Greenland: an intercomparison with Aura MLS observations

2013 ◽  
Vol 6 (9) ◽  
pp. 2441-2453 ◽  
Author(s):  
I. Fiorucci ◽  
G. Muscari ◽  
L. Froidevaux ◽  
M. L. Santee
Keyword(s):  
Optimal Estimation ◽  
Atmospheric Composition ◽  
Vertical Profiles ◽  
Good Sensitivity ◽  
Mixing Ratio ◽  
Composition Change ◽  
Mixing Ratios ◽  
Vertical Range ◽  
Atmospheric Variations ◽  
Wave Spectrometer

Abstract. In response to the need for improving our understanding of the evolution and the interannual variability of the winter Arctic stratosphere, in January 2009 a Ground-Based Millimeter-wave Spectrometer (GBMS) was installed at the Network for the Detection of Atmospheric Composition Change (NDACC) site in Thule (76.5° N, 68.8° W), Greenland. In this work, stratospheric GBMS O3 and HNO3 vertical profiles obtained from Thule during the winters 2010 (HNO3 only), 2011 and 2012 are characterized and intercompared with co-located measurements of the Aura Microwave Limb Sounder (MLS) experiment. Using a recently developed algorithm based on Optimal Estimation, we find that the GBMS O3 retrievals show good sensitivity (> 80%) to atmospheric variations between ~ 17 and ~ 50 km, where their 1σ uncertainty is estimated to be the larger of ~ 11% or 0.2 ppmv. Similarly, HNO3 profiles can be considered for scientific use between ~ 17 and ~ 45 km altitude, with a 1σ uncertainty that amounts to the larger of 15% or 0.2 ppbv. Comparisons with Aura MLS version 3.3 observations show that, on average, GBMS O3 mixing ratios are biased negatively with respect to MLS throughout the stratosphere, with differences ranging between ~ 0.3 ppmv (8%) and 0.9 ppmv (18%) in the 17–50 km vertical range. GBMS HNO3 values display instead a positive bias with respect to MLS up to 26 km, reaching a maximum of ~ 1 ppbv (10%) near the mixing ratio profile peak. O3 and HNO3 values from the two datasets prove to be well correlated at all altitudes, although their correlations worsen at the lower end of the altitude ranges considered. Column contents of GBMS and MLS O3 (from 20 km upwards) and HNO3 (from 17 km upwards) correlate very well and indicate that GBMS measurements can provide valuable estimates of column interannual and seasonal variations for these compounds.

Atmospheric variation of nitrous acid at different sites in Europe

2007 ◽  
Vol 4 (4) ◽  
pp. 242 ◽  
Author(s):  
Karin Acker ◽  
Detlev Möller
Keyword(s):  
Hydroxyl Radical ◽  
Nitrous Acid ◽  
Field Experiments ◽  
Early Morning ◽  
Mixing Ratio ◽  
Gas Phase Reactions ◽  
Sources And Sinks ◽  
Mixing Ratios ◽  
Secondary Pollutants ◽  
Rural Sites

Environmental context. Nitrous acid (HNO2) is an important source of the hydroxyl radical (OH•), the most important daytime oxidising species that contributes to the formation of ozone as well as of other secondary pollutants in the troposphere. Understanding the sources and sinks of HNO2 is of crucial interest for accurately modelling the chemical composition of the troposphere and predicting future trace gas concentrations. Abstract. Nitrous acid and several other atmospheric components and variables were continuously measured during complex field experiments at seven different suburban and rural sites in Europe. HNO2 is mainly formed by heterogeneous processes and is often accumulated in the nighttime boundary layer. Our results confirm that the photolysis of HNO2 is an important source of the hydroxyl radical, not only in the early morning hours but also throughout the entire day, and is often comparable with the contribution of ozone and formaldehyde photolysis. At all research sites unexpectedly high HNO2 mixing ratios were observed during the daytime (up to several hundred ppt, or pmol mol–1). Moreover, surprisingly, the HNO2 mixing ratio at the three mountain sites often showed a broad maximum or several distinct peaks at midday and lower mixing ratios during the night. Assuming a quickly established photo-equilibrium between the known significant gas phase reactions, only a few ppt HNO2 should be present around noon. The ratio of known sources to sinks indicates a missing daytime HNO2 source of 160–2600 ppt h–1 to make up the balance. Based on these values and on production mechanisms proposed in the literature we hypothesise that the daytime mixing ratio levels may only be explained by a fast electron transfer onto adsorbed NO2.

scholarly journals Cluster analysis of European surface ozone observations for evaluation of MACC reanalysis data

2016 ◽  
Author(s):  
Olga Lyapina ◽  
Martin G. Schultz ◽  
Andreas Hense
Keyword(s):  
Cluster Analysis ◽  
Statistical Tests ◽  
Surface Ozone ◽  
Atmospheric Composition ◽  
Regional Differentiation ◽  
Mixing Ratio ◽  
Data Set ◽  
Diurnal Cycles ◽  
Mixing Ratios ◽  
Weekly Cycles

Abstract. The high density of European surface ozone monitoring sites provides unique opportunities for the investigation of regional ozone representativeness and for the evaluation of chemistry climate models. The regional representativeness of European ozone measurements is investigated through a cluster analysis (CA) of 4 years of three-hourly ozone data from 1492 European surface monitoring stations in the Airbase database; the time resolution corresponds to the output frequency of the model that is compared to the data in this study. K-means clustering is implemented for seasonal-diurnal variations (i) in absolute mixing ratio units, and (ii) normalized by the overall mean ozone mixing ratio at each site. Statistical tests suggest that each CA can distinguish between 4 and 5 different ozone pollution regimes. The individual clusters reveal differences in seasonal-diurnal cycles, showing typical patterns of the ozone behavior for more polluted stations or more rural background. The robustness of the clustering was tested with a series of k-means runs decreasing randomly the size of the initial data set or lengths of the timeseries. Except for the Po Valley, the clustering does not provide a regional differentiation, as the member stations within each cluster are generally distributed all over Europe. The typical seasonal, diurnal, and weekly cycles of each cluster are compared to the output of the multi-year global reanalysis produced within the Monitoring of Atmospheric Composition and Climate (MACC) project. While the MACC reanalysis generally captures the shape of the diurnal cycles and the diurnal amplitudes it is not able to reproduce the seasonal cycles very well and it exhibits a high bias up to 12 nmol/mol. The bias decreases from more polluted clusters to cleaner ones. Also, the seasonal and weekly cycles and frequency distributions of ozone mixing ratios are better described for clusters with relatively clean signatures. Due to relative sparsity of CO and NOx measurements these were not included in the cluster analysis. However, simulated CO and NOx mixing ratios are consistent with the general classification into more polluted and more background sites. Mean CO mixing ratios are ≈ 140–145 nmol/mol (CL1 – CL3) and ≈ 130–135 nmol/mol (CL4 and CL5), and NOx mixing ratios are ≈ 4–6 nmol/mol and ≈ 2–3 nmol/mol, respectively. These results confirm that relatively coarse scale global models are more suitable for simulation of regional background concentrations, which are less variable in space and time. We conclude that cluster analysis of surface ozone observations provides a powerful and robust way to stratify sets of stations being thus more suitable for model evaluation.

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