Study of atmospheric ozone formation by means of a neural network-based model

The occurrence of high ozone levels in the atmosphere of urban areas has become a serious pollution problem in a number of large cities in the world. Although mathematical models have been proposed for predicting ozone concentrations as a function of a number of gas components, sometimes there are uncertainties due to lack of the combined effects of meteorological factors and the complex chemical reaction system involved. The application of neural network models, based on measured values of air pollutants and meteorological factors at different locations within the S?o Paulo Metropolitan Area, combine chemical and meteorological information. This has shown to be a promising tool for predicting ozone concentration. Simulations carried out with the model indicate the sensitivity of ozone in relation to different air pollution and weather conditions. Predictions using this model have shown good agreement with measured values of ozone concentrations.     

Summer Ozone Concentrations in Southern Ontario in Relation to Photochemical Aspects and Vegetation Damage

In the summers of 1960 and 1961, groups from the Canada Department of Agriculture, the Meteorological Service of Canada, and the Canada Department of National Health and Welfare conducted a joint study in a tobacco-growing area along the north shore of Lake Erie. The purpose of the study was to determine the causal agent for weather fleck damage to tobacco crops. A number of air pollutants were monitored and the results correlated with extensive observations of meteorological phenomena and effects on rate of growth and fleck damage to leaves of tobacco plants in experimental plots. Ozone concentrations followed a diurnal cycle, rising a few hours after sunrise, peaking in early afternoon at about 5 pphm, and dropping to a minimum of less than 1 pphm during the night. Other measurements indicated the presence of NO₂ in the order of 1 pphm, aldehydes about 0.2 pphm or lower, and negligible concentrations of SO₂. Cracking of stretched rubber strips followed the ozone values although, in general, the cracking index was greater than could be attributed to ozone (by oxidized KI) alone. The maximum ozone value recorded during the two growing seasons was IS pphm. A dosage of 20 pphm-hr was found sufficient to cause weather fleck or ozone damage to susceptible tobacco leaves. In addition meteorological data could be used to predict weather fleck attacks one to four days in advance.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.     

Effects of the density of meteorological observations on the diagnostic wind fields and the performance of photochemical modeling in the greater Seoul area

The high ozone episode in the greater Seoul area (GSA) for the period of 27 July–1 August 1997 was modeled by the California Institute of Technology (CIT) three-dimensional photochemical model. During the period, ozone concentrations around 140 ppb were observed for 2 days. Two sets of diagnostic wind fields were constructed by using observations from the weather stations operated by the Korea Meteorological Administration. One set of wind fields utilized only observations from the surface weather stations (SWS) and the other set also utilized observations from the automatic weather stations (AWS) that were more densely distributed than the SWS. The results showed that utilizing observations from the AWS could represent fine variations in the wind field such as those caused by topography. A better wind field gave a more reasonable spatial distribution of ozone concentrations. The model performance of ozone prediction was also improved to some extent, but only marginally acceptable owing to large day-to-day variations. Overshoots of primary pollutants particularly for NO₂ were observed as pollutants were accumulated where low wind speeds were maintained. More precise information on diurnal and daily variations in emissions was warranted in order to better model the photochemical phenomena over the GSA.     

Trends in near-surface ozone concentrations in Switzerland: the 1990s

A time series analysis of ozone monitoring data from several locations in Switzerland from 1991 to 1999 is presented. Different methods are used to address changes in the ozone level during these years and to account for the influence of changing meteorological conditions. The results show a slight decrease of the peaks but a highly significant increase of the mean value of around 0.5–0.9 ppb yr⁻¹. The frequency distribution has changed in the sense that very low values have become less frequent and that there is a strong increase in frequency of occurrence of half-hourly mean values between about 45 and 55 ppb. A selection procedure reveals slight tendencies towards different trends of afternoon ozone peaks in summer depending on weather and pollution situations. Ozone peaks tend to decrease on fair weather days at rural sites (but increase at urban sites) and show a small increase on cloudy and windy days. A non-linear regression model is used to estimate trends of summertime afternoon ozone peaks in the presence of meteorological variability. In the model, the long-term signal is additively split into a linear part and a part which is modulated by global radiation. The coefficients for both terms are statistically significant at many sites, with an increasing linear trend at the sites north of the Alps of around 1 ppb yr⁻¹ and a decrease of ozone peaks under fair weather conditions relative to cloudy conditions. When additionally considering the effect of precursor concentrations in the regression models, both trends are weakened, which means that they can partly be explained by changes in local to regional emissions. However, at the sites north of the Alps remains a tendency towards a positive linear “base trend” of around 0.4 ppb yr⁻¹. This could possibly be due to increasing background ozone concentrations.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Increase in summer European ozone amounts due to climate change

The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.     

An Assessment of the Economic Effects of Ozone on U.S. Agriculture

Past attempts to measure the economic consequences of ozone on agriculture have been based on limited plant science information. This paper reports on an economic assessment of ozone on U.S. agriculture using recent crop response data from the National Crop Loss Assessment Network (NCLAN). The results are derived from a U.S. agricultural sector model that includes major crop and livestock production as well as domestic consumption, livestock feeding and export uses. The economic effects of four hypothetical ambient ozone levels are investigated. The analysis Indicates that the benefits to society of moderate (25%) ozone reductions are approximately $1.7 billion. A 25% Increase in ozone pollution results in costs (negative benefits) of $2.1 billion. These estimates do not reflect compliance costs of achieving the ozone changes and hence are not net benefits.     

Daily surface UV exposure and its relationship to surface pollutant measurements

For the past 30 years, the stratospheric ozone layer has decreased in the Northern Hemisphere. The main effect of this ozone decrease was an expected increase in the UV radiation at the Earth's surface, but there has been no clear evidence of an increasing urban trend in surface UV. This study shows that specific air pollutants can reduce the increased surface levels of UV radiation and offers an explanation for why the expected surface UV increases have not been observed, especially in urban regions. A U.S. Environmental Protection Agency (EPA) UV monitoring site at the University of California at Riverside combined with air pollution data from a site operated by the California Air Resources Board in Rubidoux, CA, provided the basis of this study. The 1997 South Coast Ozone Study (SCOS-97) provided three key ingredients: black carbon, PM10 concentrations, and collocated radiometric measurements. The Total Ozone Mapping Spectrometer (TOMS) satellite data were used to provide the stratospheric ozone levels that were included in the statistical model. All of these input parameters would be used to test this study's hypothesis: the expected increase of surface UV radiation, caused by decreases in stratospheric ozone, can be masked by increases in anthropogenic emissions. The values for the pollutants were 7:00 a.m.-5:00 p.m. averages of the instrument's values taken during summer 1997. A statistical linear regression model was employed using the stratospheric ozone, black carbon, PM10, and surface ozone concentrations, and the sin (theta) and cos (theta). The angle theta is defined by theta = 2pi (Julian date/365). This model obtained a coefficient of determination of 0.94 with an uncertainty level (p value) of less than 0.3% for all of the variables in the model except ground-level ozone. The final model, regressed against a data set from a remote, western North Carolina site, resulted in a coefficient of determination of 0.92. The model shows that black carbon can reduce the Diffey-weighted UV levels that reach the surface by as much as 35%, depending on the season.     

Projected ozone trends and changes in the ozone-precursor relationship in the South Coast Air Basin in response to varying reductions of precursor emissions

This study examined the effects of varying future reductions in emissions of oxides of nitrogen (NO_x) and volatile organic compounds (VOC) on the location and magnitude of peak ozone levels within California’s South Coast Air Basin (SoCAB or Basin). As ozone formation is currently VOC-limited in the Basin, model simulations with 2030 baseline emissions (?61% for NO_x and ?32% for VOC from 2008) predict 10–20% higher peak ozone levels (i.e., NO_x disbenefit) in the western and central SoCAB compared with the 2008 base simulation. With additional NO_x reductions of 50% beyond the 2030 baseline emissions (?81% from 2008), the predicted ozone levels are reduced by about 15% in the eastern SoCAB but remain comparable to 2008 levels in the western and central Basin. The Basin maximum ozone site shifts westward to more populated areas of the Basin and will result potentially in greater population-weighted exposure to ozone with even a relatively small shortfall in the required NO_x reductions unless accompanied by additional VOC reductions beyond 2030 baseline levels. Once committed to a NO_x-focused control strategy, NO_x reductions exceeding 90% from 2008 levels will be necessary to attain the ozone National Ambient Air Quality Standards (NAAQS). The findings from this study and other recent work that the current VOC emission estimates are underestimated by about 50% suggest that greater future VOC reductions will be necessary to reach the projected 2030 baseline emissions. Increasing the base year VOC emissions by a factor of 1.5 result in higher 2008 baseline ozone predictions, lower relative response factors, and about 20% lower projected design values. If correct, these findings have important implications for the total and optimum mix of VOC and NO_x emission reductions that will be required to attain the ozone NAAQS in the SoCAB.

Implications: Results of this study indicate that ozone levels in the western and central SoCAB would remain the same or increase with even a relatively small shortfall in the projected NO_x reductions under planned NO_x-focused controls. This possibility, therefore, warrants a rigorous analysis of the costs and effects of varying reductions of VOC and NO_x on the formation and combined health impacts of ozone and secondary particles. Given the nonlinearity of ozone formation, such analyses should include the implications of gradually increasing global background ozone concentrations and the Basin’s topography and meteorology on the practical limits of alternative emission control strategies.     

Neural network-based study for predicting ground-level ozone concentration in large urban areas, applied to the Sao Paulo metropolitan area

Events of high concentration of ground-level ozone constitute a matter of major concern in large urban areas in terms of air quality, and public health. In the Sao Paulo Metropolitan Area (SPMA), air quality data generated by a network of air quality measuring stations have been used in a number of studies correlating ozone formation with different variables. A study was carried out on the application of neural network models in the identification of typical sceneries leading to high ground-level ozone concentrations in the SPMA. The results were then applied in the selection of variables, and in the definition of neural network-based models for estimating ozone levels from meteorological variables. When combined with existing weather prediction tools, the models can be applied in the prediction of ozone levels in the SPMA     

Design of Afterburners for Varnish Cookers

Currently, outdoor ozone levels in many U.S. cities exceed the primary health-based national ambient air quality standard. While outdoor ozone levels are an important measure of the severity of those exceedances, people typically spend more than 80 percent of their time Indoors, where ozone levels are lower. Indoor ozone levels range from 10 to 80 percent of outdoor levels, with many people receiving a substantial portion of their ozone exposure while indoors. This paper uses an Indoor air quality model (IAQM) to estimate indoor ozone levels by mlcroenvlronment type (home, office, and vehicle) and configuration (windows open, windows closed, older construction, weatherized, and air conditioned). The formulation of IAQM is discussed, along with specification of model parameters for ozone. The multicompartment version of IAQM is described, with a single-compartment version used for the analyses. IAQM-calculated ozone indoor-outdoor ratios compare well with research-reported values. Results indicate that ozone peak-concentration indoor-outdoor ratios range as follows: home—0.65 (windows open), 0.36 (air conditioned), 0.23 (typical construction, windows closed), and 0.05 (energy-efficient construction, windows closed); office—0.82 (heat-Ing, ventilation and air conditioning systems supplying 100 percent outdoor air), 0.60 (typical HVAC), and 0.32 (energy-efficient HVAC); and vehicle—0.41 (85 mph), 0.33 (55 mph), and 0.21 (10 mph). Analysis results are presented to characterize IAQM’s sensitivity to assumed model parameters.     

Use of an indoor air quality model (IAQM) to estimate indoor ozone levels

Currently, outdoor ozone levels in many U.S. cities exceed the primary health-based national ambient air quality standard. While outdoor ozone levels are an important measure of the severity of those exceedances, people typically spend more than 80 percent of their time indoors, where ozone levels are lower. Indoor ozone levels range from 10 to 80 percent of outdoor levels, with many people receiving a substantial portion of their ozone exposure while indoors. This paper uses an indoor air quality model (IAQM) to estimate indoor ozone levels by microenvironment type (home, office, and vehicle) and configuration (windows open, windows closed, older construction, weatherized, and air conditioned). The formulation of IAQM is discussed, along with specification of model parameters for ozone. The multicompartment version of IAQM is described, with a single-compartment version used for the analyses. IAQM-calculated ozone indoor-outdoor ratios compare well with research-reported values. Results indicate that ozone peak-concentration indoor-outdoor ratios range as follows: home--0.65 (windows open), 0.36 (air conditioned), 0.23 (typical construction, windows closed), and 0.05 (energy-efficient construction, windows closed); office--0.82 (heating, ventilation and air conditioning systems supplying 100 percent outdoor air), 0.60 (typical HVAC), and 0.32 (energy-efficient HVAC); and vehicle--0.41 (85 mph), 0.33 (55 mph), and 0.21 (10 mph). Analysis results are presented to characterize IAQM's sensitivity to assumed model parameters.     

Statistical estimation of ozone exposure metrics

Data from recent experiments at North Carolina State University and other locations provide a unique opportunity to study the effect of ambient ozone on the growth of clover. The data consist of hourly ozone measurements over a 140 day growing season at eight sites in the US, coupled with clover growth response data measured every 28 days. The objective is to model an indicator of clover growth as a function of ozone exposure. A common strategy for dealing with the numerous hourly ozone measurements is to reduce these to a single summary measurement, a so-called exposure metric, for the growth period of interest. However, the mean ozone value is not necessarily the best summarization, as it is widely believed that low levels of ozone have a negligible effect on growth, whereas peak ozone values are deleterious to plant growth. There are also suspected interactions with available sunlight, temperature and humidity. A number of exposure metrics have been proposed that reflect these beliefs by assigning different weights to ozone values according to magnitude, time of day, temperature and humidity. These weighting schemes generally depend on parameters that have, to date, been subjectively determined. We propose a statistical approach based on profile likelihoods to estimate the parameters in these exposure metrics.     

Ozone Regimes in or near Forests of the Western United States: Part 2. Factors Influencing Regional Patterns

Abstract

Ozone levels in or near forests of the western United States resulted from transport of ozone from urban areas, photochemical formation of ozone in nonurban areas from either natural or manmade precursors, and downward mixing of ozone from the tropospheric reservoir. Similarities in ozone exposure regimes were clearly associated with ozone characteristics, such as the shape of the diurnal curve in hourly ozone concentrations and the magnitudes of ozone levels. No single site characteristic dominated across the region. Eight classes of ozone regimes were identified: largeurban, medium-urban, small-urban, urban downwind-urban, urban-transport, rural, rural-remote, and remote. Sites in the western United States can be classified according to these classes. Of the sites included in the analysis, Olympic National Park, Colorado National Monument, Redwood National Park, Grand Canyon, and Crook County in Oregon showed the lowest impact from urban-generated ozone. The greatest impact of manmade ozone was found in forests of southern and central California, and to some extent in Rocky Mountain National Park and along the western slopes of the Cascades in Washington.

The eight groups of sites showing similar ozone exposure regimes as identified by Böhm et al.¹ corresponded closely with the eight classes of ozone regimes, indicating that regional similarities in ozone exposure regimes can be linked to ozone formation and transport processes despite a lack of geographic cohesion. Sixty-four percent of variance in ozone exposure regimes can be expressed in a twodimensional space called diurnal-curve space. Group membership is more cohesive in diurnal-curve than geographic space. Applications of diurnal-curve space include (1) a sensitive regional analysis of the nature and magnitudes of ozone exposure regimes in or near western forests; (2) a pro-active means for identifying sites with changing ozone exposure regimes; and (3) guidelines from which biologists can develop realistic experimental fumigation protocols. It is suggested that univariate statistics, such as 7-hour mean, 24-hour mean, SUM06, and SUM08, cannot identify up to 39% of the variance in ozone exposure regimes among sites in or near forests of the western United States.     

Estimated tropospheric ozone levels on the southeast Spanish Mediterranean coast

The objective of this study is to estimate the spatial variability of tropospheric ozone in an area using a simple model. The area in this case was applied in the western Mediterranean basin. The study period was from May to September in 2003 and 2004.A multiple linear regression between ozone concentrations, altitude and distance to the precursor sources in a fluvial basin can be used to estimate ozone values at other sites during the warmer seasons. The correlation coefficients obtained with 2-week ozone values measured at five points with a passive sampling technique were high enough to apply the model (0.77<r<0.99).To verify the model, ozone concentrations were measured with passive samplers and continuous analyzers at some selected sites, and the values were compared with the estimated concentration. The results of the validations were satisfactory, in 80% of the measurements the estimated levels differ from measured less than 20%, which is included in the bound error for the type of sampler used in this study.     

Estimating long-term population exposure to ozone in urban areas of Europe

Tropospheric ozone concentrations regarded as harmful for human health are frequently encountered in Central Europe in summertime. Although ozone formation generally results from precursors transported over long distances, in urban areas local effects, such as reactions due to nearby emission sources, play a major role in determining ozone concentrations. Europe-wide mapping and modeling of population exposure to high ozone concentrations is subject to many uncertainties, because small-scale phenomena in urban areas can significantly change ozone levels from those of the surroundings. Currently the integrated assessment modeling of European ozone control strategies is done utilizing the results of large-scale models intended for estimating the rural background ozone levels. This paper presents an initial study on how much local nitrogen oxide (NOx) concentrations can explain variations between large-scale ozone model results and urban ozone measurements, on one hand, and between urban and nearby rural measurements, on the other. The impact of urban NOx concentrations on ozone levels was derived from chemical equations describing the ozone balance. The study investigated the applicability of the method for improving the accuracy of modeled population exposure, which is needed for efficient control strategy development. The method was tested with NOx and ozone measurements from both urban and rural areas in Switzerland and with the ozone predictions of the large-scale photochemical model currently used in designing Europe-wide control strategies for ground-level ozone. The results suggest that urban NOx levels are a significant explanatory factor in differences between urban and nearby rural ozone concentrations and that the phenomenon could be satisfactorily represented with this kind of method. Further research efforts should comprise testing of the method in more locations and analyzing the performance of more widely applicable ways of deriving the initial parameters.     

Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.     

Evaluation of near surface ozone in air quality simulations forced by a regional climate model over Europe for the period 1991–2000

This study aims to evaluate near surface ozone simulated with the modelling system RegCM3/CAMx against ozone measurements from the EMEP database for the recent decade 1991–2000. The RegCM3/CAMx simulations were performed on a 50 km × 50 km grid over Europe driven either by ERA-40 reanalysis (hereafter referred as ERA simulation) or the global circulation model (GCM) ECHAM5 (hereafter referred as ECHAM simulation). A set of statistical metrics is used for the model evaluation, including temporal correlation coefficient, the ratio of the standard deviations and the bias of simulated versus observed values. Overall, a good agreement is found for both ERA and ECHAM simulations at the majority of the selected EMEP stations in all metrics throughout the year based either on monthly or daily ozone values. Based on these results, it is assessed that the modelling system RegCM3/CAMx is suitable to be used for present and future regional climate-air quality simulations with emphasis on near surface ozone. The ERA simulations reproduce more accurately the observed ozone values in comparison to ECHAM simulations because the meteorology of the ERA experiment is closer to real atmospheric conditions than the GCM based experiment. On a seasonal basis, both ERA and ECHAM simulations exhibit a seasonally dependent bias, with winter and spring ozone values being generally under-estimated by the model and summer and autumn values being slightly overestimated. This seasonally dependent bias is also evident from median and peak midday ozone values. However, the highest observed midday ozone peaks in summer, with values higher than 80 ppbv, could not be captured either by ERA or ECHAM simulations. An analysis of day-time and night-time ERA and ECHAM modelled ozone values shows that CAMx performs better during the day-time.