Predictive mapping of air pollution involving sparse spatial observations

A limited number of sample points greatly reduces the availability of appropriate spatial interpolation methods. This is a common problem when one attempts to accurately predict air pollution levels across a metropolitan area. Using ground-level ozone concentrations in the Tucson, Arizona, region as an example, this paper discusses the above problem and its solution, which involves the use of linear regression. A large range of temporal variability is used to compensate for sparse spatial observations (i.e. few ozone monitors). Gridded estimates of emissions of ozone precursor chemicals, which are developed, stored, and manipulated within a geographic information system, are the core predictor variables in multiple linear regression models. Cross-validation of the pooled models reveals an overall R2 of 0.90 and approximately 7% error. Composite ozone maps predict that the highest ozone concentrations occur in a monitor-less area on the eastern edge of Tucson. The maps also reveal the need for ozone monitors in industrialized areas and in rural, forested areas.     

Ground-based remote sensing measurements of aerosol and ozone in an urban area: A case study of mixing height evolution and its effect on ground-level ozone concentrations

We have estimated the mixing height (MH) and investigated the relationship between vertical mixing and ground-level ozone concentrations in Seoul, Korea, by using three ground-based active remote sensing instruments operating side by side: micro-pulse lidar (MPL), differential absorption lidar (DIAL), and differential optical absorption spectroscopy (DOAS). The MH is estimated from MPL measurements of aerosol extinction profiles by the gradient method under convective conditions. Comparisons of the MHs estimated from MPL and radiosonde measurements show a good agreement (r²=0.99). Continuous MPL measurements with high temporal and vertical resolution reveal the diurnal variations of the MH under convective conditions and the presence of a residual layer during the nighttime. Comprehensive measurements of ozone and aerosol by MPL, DIAL and DOAS during an high ozone episode (24–26 May 2000) in Seoul, Korea, reveal that (1) photochemical ozone production and advection from upwind regions (the western part of Seoul) contribute two peaks of ozone concentrations at the ground around 14:00 and 18:00 local time on 25 May 2000, respectively, and (2) the entrainment and the fumigation processes of ozone aloft in the nighttime residual layer into the ground is a major contributor of high concentrations of ground-level ozone observed on the following day (26 May 2000).     

A simple semi-empirical photochemical model for the simulation of ozone concentration in the Seoul metropolitan area in Korea

O₃ concentrations were simulated over the Seoul metropolitan area in Korea using a simple semi-empirical reaction (SEGRS) model which consists of generic reaction set (GRS), photochemical reaction set, and the diagnostic wind field generation model. The aggregated VOC emission strength was empirically scaled by the comparison of the simulated slope of (O₃–2NO–NO₂) concentration as a function of cumulative actinic light flux against measurements on high surface ozone concentration days with the relatively weak easterly geostrophic winds at the 850 hPa level in summer when the effect of horizontal advection was fairly small. The results indicated that the spatial distribution patterns and temporal variations of spatially averaged ground-level ozone concentrations were quite well simulated compared with those of observations with the modified volatile organic compound (VOC) emission strength. The diurnal trend of the surface ozone concentration and the maximum concentration compared observations were also quite reasonably simulated. However, the maximum ozone concentration occurring time at Seoul lagged about 2 h and the ozone concentration in the suburban area was slightly overestimated in the afternoon due to the influx of high ozone concentration from the urban area. It was found that the SEGRS model could be effectively used to simulate or predict the ground-level ozone concentration reasonably well without heavy computational cost provided the emission of ozone precursors are given.     

Ground-level ozone in the Pearl River Delta region: Analysis of data from a recently established regional air quality monitoring network

The ambient air quality monitoring data of 2006 and 2007 from a recently established Pearl River Delta (PRD) regional air quality monitoring network are analyzed to investigate the characteristics of ground-level ozone in the region. Four sites covering urban, suburban, rural and coastal areas are selected as representatives for detailed analysis in this paper. The results show that there are distinct seasonal and diurnal cycles in ground-level ozone across the PRD region. Low ozone concentrations are generally observed in summer, while high O₃ levels are typically found in autumn. The O₃ diurnal variations in the urban areas are larger than those at the rural sites. The O₃ concentrations showed no statistically significant difference between weekend and weekdays in contrast to the findings in many other urban areas in the world. The average ozone concentrations are lower in urban areas compared to the sites outside urban centers. Back trajectories are used to show the major air-mass transport patterns and to examine the changes in ozone from the respective upwind sites to a site in the center of the PRD (Wanqingsha). The results show higher average ozone concentrations at the upwind sites in the continental and coastal air masses, but higher 1 h-max O₃ concentrations (by 8–16 ppbv) at the center PRD site under each of air-mass category, suggesting that the ozone pollution in the PRD region exhibits both regional and super-regional characteristics.     

Meteorologically adjusted long-term trend of ground-level ozone concentrations in Kaohsiung County,southern Taiwan

Since meteorological changes strongly affect ambient ozone concentrations, trends in concentrations of ozone upon the adjustment of meteorological variations are important of evaluating emission reduction efforts. The goal of this work is to study meteorological effects on the long-term trends of ozone concentration using a multi-variable additive model. Data on the hourly concentrations of ozone were collected from four air-quality stations from 1997 to 2006 in Kaohsiung County to determine the monthly, seasonal and annual average concentrations of ozone. The model incorporates seven meteorological parameters – pressure, temperature, relative humidity, wind speed, wind direction, duration of sunshine and cloud cover. The simulated results show that the long-term ozone concentration increases at 13.84% (or 13.06%) monthly (or annually) after meteorological adjustments, less than at 26.10% (or 23.80%) without meteorological adjustments. Wind speed, duration of sunshine and pressure are the three dominant factors that influence the ground-level ozone levels.     

Space-time analysis of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 1 air quality simulations

This study presents an evaluation of summertime ozone concentrations over North America (NA) and Europe (EU) using the database generated from Phase 1 of the Air Quality Model Evaluation International Initiative (AQMEII). The analysis focuses on identifying temporal and spatial features that can be used to stratify operational model evaluation metrics and to test the extent to which the various modeling systems can replicate the features seen in the observations. Using a synoptic map typing approach, it is demonstrated that model performance varies with meteorological conditions associated with specific synoptic-scale flow patterns over both eastern NA and EU. For example, the root mean square error of simulated daily maximum 8-hr ozone was twice as high when cloud fractions were high compared with when cloud fractions were low over eastern NA. Furthermore, results show that over both NA and EU the regional models participating in AQMEII were able to better reproduce the observed variance in ambient ozone levels than the global model used to specify chemical boundary conditions, although the variance simulated by almost all regional models is still less that the observed variance on all spatiotemporal scales. In addition, all modeling systems showed poor correlations with observed fluctuations on the intraday time scale over both NA and EU. Furthermore, a methodology is introduced to distinguish between locally influenced and regionally representative sites for the purpose of model evaluation. Results reveal that all models have worse model performance at locally influenced sites. Overall, the analyses presented in this paper show how observed temporal and spatial information can be used to stratify operational model performance statistics and to test the modeling systems’ ability to replicate observed temporal and spatial features, especially at scales the modeling systems are designed to capture.

Implications: The analyses presented in this paper demonstrate how observed temporal and spatial information can be used to stratify operational model performance and to test the modeling systems’ ability to replicate observed temporal and spatial features. Decisions for the improvement of regional air quality models should be based on the information derived from only regionally representative sites.     

An information theoretic perspective on mesoscale seasonal variations in ground-level ozone

Relatively little prior use has been made of information theory in air quality analysis. This paper explores whether basic, but formal, quantitative measures of information content might yield fresh perspectives on seasonal variations in the ground-level ozone concentration field across the lower Fraser Valley (LFV), British Columbia, Canada. I calculate Shannon entropy in daily maximum ozone concentration on a month-by-month, station-by-station basis, using 1 year of hourly measurements from 18 air quality monitoring stations. The values are then qualitatively compared with an eye to identifying spatial and seasonal patterns. The results further demonstrate the potential utility of information theoretic concepts for assessing air quality variability; yield some new insight into tropospheric ozone dynamics across the LFV; and may provide some guidance to the refinement of monitoring network configuration. Of particular note is that, although entropy and mean concentration exhibit some similarities in their respective seasonal patterns, maximum uncertainty and information content appears to occur at times and locations somewhat different from those at which highest concentrations are experienced.     

Surface ozone exposures measured at clean locations around the world

For assessing the effects of air pollution on vegetation, some researchers have used control chambers as the basis of comparison between crops and trees grown in contemporary polluted rural locations and those grown in a clean environment. There has been some concern whether the arbitrary ozone level of 0.025 ppm and below, often used in charcoal-filtration chambers to simulate the natural background concentration of ozone, is appropriate. Because of the many complex and man-made factors that influence ozone levels, it is difficult to determine natural background. To identify a range of ozone exposures that occur at 'clean' sites, we have calculated ozone exposures observed at a number of 'clean' monitoring sites located in the United States and Canada. We do not claim that these sites are totally free from human influence, but rather than the ozone concentrations observed at these 'clean' sites may be appropriate for use by vegetation researchers in control chambers as pragmatic and defensible surrogates for natural background. For comparison, we have also calculated ozone exposures observed at four 'clean' remote sites in the Northern and Southern Hemispheres and at two remote sites (Whiteface Mountain, NY and Hohenpeissenberg, FRG) that are considered to be more polluted. Exposure indices relevant for describing the relationship between ozone and vegetation effects were applied. For studying the effects of ozone on vegetation, the higher concentrations are of interest. The sigmoidally-weighted index appeared to best separate those sites that experienced frequent high concentration exposures from those that experienced few high concentrations. Although there was a consistent seasonal pattern for the National Oceanic and Atmospheric Administration (NOAA) Geophysical Monitoring for Climate Change (GMCC) sites indicating a winter/spring maximum, this was not the case for the other remote sites. Some sites in the continental United States and southern Canada experienced ozone exposures in the range between those values experienced at the South Pole and Mauna Loa NOAA GMCC sites. The 7-month average of the daily 7 h average ozone concentration at 'clean' sites located in the continental United States and southern Canada ranged from 0.028 to 0.050 ppm. Our analysis indicates that seasonal 7 h average values of 0.025 ppm and below, used by some vegetation researchers as a reference point, may be too low and that estimates of crop losses and tree damage in many locations may have been too high. Our analysis indicates that a more appropriate reference point in North America might be between 0.030 and 0.045 ppm. We have observed that the subtle effects of changing distribution patterns of hourly average ozone concentrations may be obscured with the use of exposure indices such as the monthly average. Future assessments of the effects associated with ground-level ozone should involve the use of exposure indices sensitive to changes in the distribution patterns of hourly average ozone concentrations.     

Atmospheric characteristics conducive to high-ozone days in the Atlanta metropolitan area

The purpose of this paper is to identify the atmospheric conditions associated with elevated ground-level ozone concentrations during June–August of 2000–2007 at 11 ozone-monitoring stations in the Atlanta, GA, USA metropolitan statistical area (MSA). Analyses were confined to high-ozone days (HODs), which had a daily maximum 8-h average ozone concentration in the 95th percentile of all June–August values. Therefore, each station had 36 HODs. The southeastern and far northern portions of the MSA had HODs with the highest and lowest ozone concentrations, respectively. HODs at nearly all Atlanta MSA ozone-monitoring stations were enabled by migratory anticyclones. HODs for most stations were hot, dry, and calm with low morning mixing heights and high afternoon mixing heights. All sets of HODs had daily mean relative humidities and afternoon mixing heights that, respectively, were significantly less than and significantly greater than mean values for the remaining days. Urbanized Atlanta typically was upwind of an ozone-monitoring station on its HODs; therefore, wind direction on HODs varied considerably among the stations. HODs may have been caused partially by NO_x emissions from electric-utility power plants: HODs in the southern portion of the MSA were linked to air-parcel trajectories intersecting a power plant slightly northwest of Atlanta and plants in the Ohio River Valley, while HODs in the northern portion of the MSA were linked to air-parcel trajectories intersecting two large power plants slightly southeast of the Atlanta MSA. Results from this study suggest that future research in the Atlanta MSA should focus on power-plant contributions to ground-level ozone concentrations as well as the identification of non-monitored locations with potentially high ozone concentrations.     

Stochastic model to forecast ground-level ozone concentration at urban and rural areas

Stochastic models that estimate the ground-level ozone concentrations in air at an urban and rural sampling points in South-eastern Spain have been developed. Studies of temporal series of data, spectral analyses of temporal series and ARIMA models have been used. The ARIMA model (1,0,0) x (1,0,1)24 satisfactorily predicts hourly ozone concentrations in the urban area. The ARIMA (2,1,1) x (0,1,1)24 has been developed for the rural area. In both sampling points, predictions of hourly ozone concentrations agree reasonably well with measured values. However, the prediction of hourly ozone concentrations in the rural point appears to be better than that of the urban point. The performance of ARIMA models suggests that this kind of modelling can be suitable for ozone concentrations forecasting.     

Application of the Urban Airshed Model to forecasting next-day peak ozone concentrations in Atlanta, Georgia

Twenty-four to forty-eight-hour ozone air quality forecasts are increasingly being used in metropolitan areas to inform the public about potentially harmful air quality conditions. The forecasts are also behind "ozone action day" programs in which the public and private sectors are encouraged or mandated to alter activities that contribute to the formation of ground-level ozone. Presented here is a low-cost application of the Urban Airshed Model (UAM), an Eulerian 3-dimensional photochemical-transport grid model for generating next-day peak ozone concentration forecasts. During the summer of 1997, next-day peak ozone concentrations in Atlanta, GA, were predicted both by a team of eight forecasters and by the Urban Airshed Model in Forecast Mode (UAM-FM). Results are presented that compare the accuracy of the team and the UAM-FM. The results for the summer of 1997 indicate that the UAM-FM may be a better predictor of peak ozone concentrations when concentrations are high (> 0.095 ppmv), and the team may be a better predictor of ozone concentrations when concentrations are low (< or = 0.095 ppmv). The UAM-FM is also discussed in the context of other forecasting tools, primarily linear regression models and a no-skill, persistence-based technique.     

Ground-Level Ozone in Eastern Canada: Seasonal Variations,Trends, and Occurrences of High Concentrations

Over the past few years, concern has increased in Canada over the health and environmental impacts of elevated concentrations of ground-level ozone. During the summer the most populated regions of Canada frequently record ozone concentrations that exceed the one-hour average maximum acceptable air quality objective of 32 parts per billion (ppb). In 1988 the Canadian Council of Ministers of the Environment agreed to develop a federal/provincial management plan to control nitrogen oxide and volatile organic compound emissions to reduce ozone concentrations in all affected regions of the country. In addition to the proposed interim control measures, the plan recommended that studies be undertaken to acquire the information necessary to develop sound control strategies. This report represents one of those studies and provides a summary of ground-level ozone measurements for eastern Canada for the 1980 to 1991 period with an emphasis on seasonal variations, trends, and occurrences of high concentrations.

Southwestern Ontario experiences the highest maximum hourly ozone concentrations and the greatest frequency of hours greater than the 82 ppb acceptable objective. Urban sites have the highest frequencies of ozone concentration measurements in the < 10 ppb range, while rural and remote sites show peaks in frequency distribution in the 20 to 30 ppb range. Trend analysis of summertime (May to September) average daily maximum ozone concentration showed no consistent pattern for eastern Canadian sites during 1980 to 1991. Sites in Montreal showed statistically insignificant downward trends while sites in Toronto showed small but statistically significant upward trends. These ozone-increasing trends are associated with reductions in nitric oxide concentrations. At all sites there was large year-to-year variability in peak ozone levels and in the frequency of hours with ozone concentrations above the maximum acceptable objective.     

Application of the Urban Airshed Model to Forecasting Next-Day Peak Ozone Concentrations in Atlanta,Georgia

ABSTRACT

Twenty-four to forty-eight-hour ozone air quality forecasts are increasingly being used in metropolitan areas to inform the public about potentially harmful air quality conditions. The forecasts are also behind “ozone action day” programs in which the public and private sectors are encouraged or mandated to alter activities that contribute to the formation of ground-level ozone. Presented here is a low-cost application of the Urban Airshed Model (UAM), an Eulerian 3-dimensional photochemical-transport grid model for generating next-day peak ozone concentration forecasts. During the summer of 1997, next-day peak ozone concentrations in Atlanta, GA, were predicted both by a team of eight forecasters and by the Urban Airshed Model in Forecast Mode (UAM-FM). Results are presented that compare the accuracy of the team and the UAM-FM. The results for the summer of 1997 indicate that the UAM-FM may be a better predictor of peak ozone concentrations when concentrations are high (> 0.095 ppmv), and the team may be a better predictor of ozone concentrations when concentrations are low (< 0.095 ppmv). The UAM-FM is also discussed in the context of other forecasting tools, primarily linear regression models and a no-skill, persistence-based technique.     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.     

The influence of tropospheric ozone on the air temperature of the city of Toronto,Ontario, Canada

Weekday/weekend variations in tropospheric ozone concentrations were examined to determine whether ground-level greenhouse gases have a significant impact on local climate. The city of Toronto, Canada, was chosen due to a high volume of commuter traffic and frequent exposure to high ozone episodes. Due to day-of-the-week variations in commuter traffic, ozone concentrations were shown to vary significantly between weekdays and weekends. During high ozone episodes weekend air temperatures were significantly higher than those observed on weekdays. As no meteorological phenomenon is known to occur over a 7 day cycle the observed temperature variations were attributed to anthropogenic activity.     

Site Redundancy in Urban Ozone Monitoring

This article describes two statistical methods that enable air pollution control agencies to assess the effectiveness of the spatial distribution of current stationary ozone monitoring networks by providing measures of site redundancy. These methods analyze site redundancy by determining the degree to which ozone measurements at one site can be successfully predicted from data collected at other monitoring sites. The first method, the similarity (SIM) measure, calculates redundancy based on the percentage of common operational days during which two monitoring stations report similar daily maximum ozone concentrations. The second method, a modeling technique, relates site redundancy in ozone measurement to an R-squared statistic from an autoregressive model. The model uses meteorological components recorded at a central location and ozone concentrations reported by the network’s other monitoring stations. Both techniques can assist in effective allocation of limited monitoring resources and offer a statistical approach to ambient air monitoring network design. The techniques are applied to data collected at six ozone monitoring stations in Harris County, Texas, during an eight-year period in the 1980s. The methods identified two sites in the six-site network that exhibit a high degree of redundancy.     

Assessment of nitrogen oxides and ground-level ozone behavior in a dense air quality station network: Case study in the Lesser Antilles Arc

ABSTRACT

This paper presents a study on ground-level ozone (O₃), nitrogen oxides (NO_x = NO + NO₂) concentrations, and their variabilities in the ambient air of three sites of a tropical archipelago that is moderately urbanized. Statistical analysis was performed on a quite complete (>80%) set of 5 years of measurements (2008–2012). There are few studies on those pollutants and their seasonal behavior in the Caribbean area, where pollution level and cities configuration are different from megacities. Analyses are focused on pollutant variations at the scale of the day, the week, and the seasons, using hourly data. The observations show that NO_x concentrations are more elevated during the wet season, whereas O₃ concentrations are higher in the dry season. Amplitudes of ozone cycles are strongly influenced by meteorological conditions (temperature, global radiation, and wind speed) and prevailing levels of NO_x. An ozone weekend effect is detected with the highest amplitude in the city, where anthropogenic activity is the lowest during the weekend. Due to the nature and the origin of pollutants, NO_x shows higher variability than O₃ in the time series. Our results evince the need for continuous measurements of volatile organic compounds (VOCs) in order to better quantify their contribution in O₃ formation in an insular context where numerous natural sources have been identified.

Implications: Statistical analyses of observed NO_x and O₃ concentrations for 5 years for a typical low industrialized site of the Caribbean area have been done. Air quality for those components is correct based on the standards of the World Health Orgaization, pollutant source spatial distributions, and level of industrialization. Observations show the same patterns as in megacities but also a strong impact of weather conditions and road traffic. Behaviors of O₃ cannot be fully explained without VOCs monitoring. Localization and type of AQS should be reconsidered to improve the accuracy of concentrations of the pollutant and better understand their behaviors.     

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.     

A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

Comparison of modelled and measured ozone concentrations and meteorology for a site in south-west Sweden: implications for ozone uptake calculations

Measurements of ground-level ozone concentrations and meteorology (temperature, vapour pressure deficit (VPD), solar radiation) at the monitoring site Ostad (south-west Sweden) were compared to data from the corresponding grid in the EMEP photo-oxidant model for 1997, 1999 and 2000. The influence of synoptic weather on the agreement between model and measurements was studied. Implications of differences between modelled and observed inputs for ozone flux calculations for wheat and potato were investigated. The EMEP model output of ozone, temperature and VPD correlated well with measurements during daytime. Deviations were larger during the night, especially in calm conditions, attributed to local climatological conditions at the monitoring site deviating from average conditions of the grid. These differences did not lead to significant differences in calculated ozone uptake, which was reproduced remarkably well. The uptake calculations were sensitive to errors in the ozone and temperature input data, especially when including a flux threshold.