Variation of surface ozone in Campo Grande,Brazil: meteorological effect analysis and prediction

The effect of meteorological variables on surface ozone (O₃) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O₃ concentration, relative humidity and solar radiation. The threshold model that considers two O₃ regimes was the one that correctly describes the effect of important meteorological variables in O₃ behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O₃ regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O₃ concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O₃ behaviour, being useful to define policy strategies for human health protection regarding air pollution.     

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.     

Factors Influencing the Variability of SO2 Concentrations in Istanbul

ABSTRACT

The correlation between sulfur dioxide (SO₂) concentrations measured at the European and Asian sides of Istanbul and meteorological parameters is investigated using principal component analysis (PCA) and multiple regression analysis techniques. Several meteorological parameters are selected to represent the atmospheric conditions during two winter periods: 1993–1994 and 1994–1995. Six principal components are found to explain the majority of the observed meteorological variability. Surface pressure, 850-mb temperature, and surface zonal (east-west) and meridional (north-south) winds show high loadings on separate factors identified by PCA. We seek dominant meteorological parameters that control the SO₂ levels at each monitoring station. Several multiple regression analysis models are fitted to the data from each monitoring station using six principal components and previous day SO₂ concentrations as independent variables.

Results suggest that the most important parameters, highly correlated with SO₂ concentrations in the Istanbul metropolitan area, are atmospheric pressure and surface zonal and meridional winds. These components have more influence on the determination of the air pollution levels at the Asian side than at the European side.     

Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain

The photochemical grid model, UAM-V, has been used by regulatory agencies to make decisions concerning emissions controls, based on studies of the July 1995 ozone episode in the eastern US. The current research concerns the effect of the uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on the uncertainties in UAM-V ozone predictions. Uncertainties of 128 input variables have been estimated and most range from about 20% to a factor of two. 100 Monte Carlo runs, each with new resampled values of each of the 128 input variables, have been made for given sets of median emissions assumptions. Emphasis is on the maximum hourly-averaged ozone concentration during the 12–14 July 1995 period. The distribution function of the 100 Monte Carlo predicted domain-wide maximum ozone concentrations is consistently close to log-normal with a 95% uncertainty range extending over plus and minus a factor of about 1.6 from the median. Uncertainties in ozone predictions are found to be most strongly correlated with uncertainties in the NO₂ photolysis rate. Also important are wind speed and direction, relative humidity, cloud cover, and biogenic VOC emissions. Differences in median predicted maximum ozone concentrations for three alternate emissions control assumptions were investigated, with the result that (1) the suggested year-2007 emissions changes would likely be effective in reducing concentrations from those for the year-1995 actual emissions, that (2) an additional 50% NO_x emissions reductions would likely be effective in further reducing concentrations, and that (3) an additional 50% VOC emission reductions may not be effective in further reducing concentrations.     

Variations of surface O3 in August at a rural site near Shanghai: influences from the West Pacific subtropical high and anthropogenic emissions

Large day-to-day variability in O₃ and CO was observed at Chongming, a remote rural site east of Shanghai, in August 2010. High ozone periods (HOPs) that typically lasted for 3?C5?days with daily maximum ozone exceeding 102?ppb were intermittent with low ozone periods (LOPs) with daily maximum ozone less than 20?ppb. The correlation analysis of ozone with meteorological factors suggests that the large variations of surface ozone are driven by meteorological conditions correlated with the changes in the location and intensity of the west Pacific subtropical high (WPSH) associated with the East Asian summer monsoon (EASM). When the center of WPSH with weaker intensity is to the southeast of Chongming site, the mixing ratios and variability of surface ozone are higher. When the center of WPSH with stronger intensity is to the northeast of Chongming site, the mixing ratios and variability of surface ozone are lower. Sensitivity simulations using the GEOS-Chem chemical transport model indicate that meteorological condition associated with WPSH is the primary factor controlling surface ozone at Chongming in August, while local anthropogenic emissions make significant contributions to surface ozone concentrations only during HOP.     

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.     

An ozone climatology: relationship between meteorology and ozone in the Southeast USA

A statistical analysis of ozone (O₃) concentrations and meteorological parameters was performed to determine the relationship between meteorological changes and ambient O₃ concentrations in the Southeast United States. The correlation between average daily maximum O₃ concentration and various meteorological variables was analysed on a monthly basis from April through October during 1980-1994. The correlations were strongest during the summer months, particularly June, July, and August. Analysis of long term O₃ concentration trends indicates increasing trends during the 1980s and decreasing trends during the early 1990s.     

Long-term trends of primary and secondary pollutant concentrations in Switzerland and their response to emission controls and economic changes

A detrending technique is developed for short-term and yearly variations in order to identify long-term trends in primary and secondary pollutants. In this approach, seasonal and weekly variations are removed by using a mean year; the residual meteorological short-term variation is removed by using a multiple linear regression model. This methodology is employed to detrend ozone (O₃), NO_x, VOC and CO concentrations in Switzerland. We show that primary pollutants (NO_x,VOC and CO) at urban and sub-urban stations show a downward trend over the last decade which correlates well with the reductions in the estimated Swiss emissions. In spite of these large decreases achieved in precursor emissions, summer peak ozone concentrations do not show any statistically significant trend over the last decade. Application of this method to ozone concentrations measured at the Jungfraujoch (3580 m a.s.l.) also shows no trend over the last 10 years. Detrended summer ozone correlates well with European Union gross national product and industrial production growth rates. These results suggest that if substantial reductions in summer peak ozone in Switzerland are desired, emissions reduction strategies must be part of control program involving a much larger region.     

Artificial Neural Network-Derived Trends in Daily Maximum Surface Ozone Concentrations

ABSTRACT

Interannual variability in meteorological conditions can confound attempts to identify changes in ozone concentrations driven by reduced precursor emissions. In this paper, a technique is described that attempts to maximize the removal of meteorological variability from a daily maximum ozone time series, thereby revealing longer term changes in ozone concentrations with increased confidence. The technique employs artificial neural network [multilayer perceptron (MLP)] models, and is shown to remove more of the meteorological variability from U.S. ozone data than does a Kolmogorov-Zurbenko (KZ) filter and conventional regression-based technique.     

Long-term meteorologically independent trend analysis of ozone air quality at an urban site in the greater Houston area

The Houston-Galveston-Brazoria (HGB) area of Texas has a history of ozone exceedances and is currently classified under moderate nonattainment status for the 2008 8-hr ozone standard of 75 ppb. The HGB area is characterized by intense solar radiation, high temperature, and high humidity, which influence day-to-day variations in ozone concentrations. Long-term air quality trends independent of meteorological influence need to be constructed for ascertaining the effectiveness of air quality management in this area. The Kolmogorov-Zurbenko (KZ) filter technique, used to separate different scales of motion in a time series, is applied in the current study for maximum daily 8-hr (MDA8) ozone concentrations at an urban site (U.S. Environmental Protection Agency [EPA] Air Quality System [AQS] Site ID: 48-201-0024, Aldine) in the HGB area. This site, located within 10 miles of downtown Houston and the George Bush Intercontinental Airport, was selected for developing long-term meteorologically independent MDA8 ozone trends for the years 1990–2016. Results from this study indicate a consistent decrease in meteorologically independent MDA8 ozone between 2000 and 2016. This pattern could be partially attributed to a reduction in underlying nitrogen oxide (NO_x) emissions, particularly lowering nitrogen dioxide (NO₂) levels, and a decrease in the release of highly reactive volatile organic compounds (HRVOCs). Results also suggest solar radiation to be most strongly correlated to ozone, with temperature being the secondary meteorological control variable. Relative humidity and wind speed have tertiary influence at this site. This study observed that meteorological variability accounts for a high of 61% variability in baseline ozone (low-frequency component, sum of long-term and seasonal components), whereas 64% of the change in long-term MDA8 ozone post 2000 could be attributed to NO_x emission reduction. Long-term MDA8 ozone trend component was estimated to be decreasing at a linear rate of 0.412 ± 0.007 ppb/yr for the years 2000–2016 and 0.155 ± 0.005 ppb/yr for the overall period of 1990–2016.

Implications: The effectiveness of air emission controls can be evaluated by developing long-term air quality trends independent of meteorological influences. The KZ filter technique is a well-established method to separate an air quality time series into short-term, seasonal, and long-term components. This paper applies the KZ filter technique to MDA8 ozone data between 1990 and 2016 at an urban site in the greater Houston area and estimates the variance accounted for by the primary meteorological control variables. Estimates for linear trends of MDA8 ozone are calculated and underlying causes are investigated to provide a guidance for further investigation into air quality management of the greater Houston area.     

Variability of ozone concentration in a montane environment,northern Italy

To evaluate the spatial variability of ozone concentrations, two studies were undertaken in the montane environment of Trentino region, northern Italy, in 2007. In the first study, a 225 km² area was considered. Here, a randomized design was used to evaluate the variability of ozone concentration at 1 and 225 km² scale. Measurements were carried out by passive samplers between May and June 2007. In a second study, the whole 6207 km² area of Trentino was considered. The area is covered by five grid cells of the European Monitoring and Evaluation Programme (EMEP). A systematic 15 × 15 km grid was used to allocate 15 passive samplers over the entire province, resulting into 1–4 samplers for each of the 5 EMEP grid cells (2500 km² each) overlapping the study area. Measurements were carried out between June and September 2007. Accuracy of passive samplers was checked by direct comparison with conventional ozone analysers. Significant differences (P = 0.034) were found in ozone concentration among 1 × 1 km quadrates within the 225 km² study area, while variability within the 1 × 1 km grid cells (coefficient of variation, CV′ = 0.12) slightly exceed the measurement error (CV′ = 0.08). At larger scales (225, 2500 and 6207 km²), ozone concentration shows much higher variability (CV′ from 0.18 to 0.28, with peak values at 0.40). Reported differences lead to very different AOT40 estimates even within the same EMEP grid cell. These findings suggest that 1 × 1 km resolution seems appropriate for ozone concentration modelling. On the other hand, significant sub-grid variation may exist at the resolution adopted by the EMEP model. Coupled with the likely variability of other important meteorological, soil and vegetation variables, our findings suggest that ozone risk assessment for vegetation based on large-scale modelled AOT40 and flux needs to be considered with great caution. The evidence reported in this paper asks for more detailed national-scale modelling, and the development of methods to incorporate local scale variations into large-scale models.     

Increasing interannual and altitudinal ozone mixing ratios in the Catalan Pyrenees

Interannual, seasonal, daily and altitudinal patterns of tropospheric ozone mixing ratios, as well as ozone phytotoxicity and the relationship with NO_x precursors and meteorological variables were monitored in the Central Catalan Pyrenees (Meranges valley and Forest of Guils) over a period of 5 years (2004–2008). Biweekly measurements using Radiello passive samplers were taken along two altitudinal transects comprised of thirteen stations ranging from 1040 to 2300 m a.s.l. Visual symptoms of ozone damage in Bel-W3 tobacco cultivars were evaluated biweekly for the first three years (2004–2006). High ozone mixing ratios, always above forest and vegetation protection AOT40 thresholds, were monitored every year. In the last 14 years, the AOT40 (Apr–Sept.) has increased significantly by 1047 μg m^?3 h per year. Annual means of ozone mixing ratios ranged between 38 and 67 ppb_v (38 and 74 ppb_v during the warm period) at the highest site (2300 m) and increased at a rate of 5.1 ppb_v year^?1. The ozone mixing ratios were also on average 35–38% greater during the warm period and had a characteristic daily pattern with minimum values in the early morning, a rise during the morning and a decline overnight, that was less marked the higher the altitude. Whereas ozone mixing ratios increased significantly with altitude from 35 ppb_v at 1040 m–56 ppb_v at 2300 m (on average for 2004–2007 period), NO₂ mixing ratios decreased with altitude from 5.5 ppb_v at 1040 m–1 ppb_v at 2300 m. The analysis of meteorological variables and NO_x values suggests that the ozone mainly originated from urban areas and was transported to high-mountain sites, remaining aloft in absence of NO. Ozone damage rates increased with altitude in response to increasing O₃ mixing ratios and a possible increase in O₃ uptake due to more favorable microclimatic conditions found at higher altitude, which confirms Bel-W3 as a suitable biomonitor for ozone concentrations during summer time. Compared to the valley-bottom site the annual means of ozone mixing ratios are 37% larger in the higher sites. Thus the AOT40 for the forest and vegetation protection threshold is greatly exceeded at higher sites. This could have substantial effects on plant life at high altitudes in the Pyrenees.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), onemixed (alternating winds) and one onlyanticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

An assessment of the impact of climate change on air quality at two UK sites

Possible effects of climate change on air quality are studied for two urban sites in the UK, London and Glasgow. Hourly meteorological data were obtained from climate simulations for two periods representing the current climate and a plausible late 21st century climate. Of the meteorological quantities relevant to air quality, significant changes were found in temperature, specific humidity, wind speed, wind direction, cloud cover, solar radiation, surface sensible heat flux and precipitation. Using these data, dispersion estimates were made for a variety of single sources and some significant changes in environmental impact were found in the future climate. In addition, estimates for future background concentrations of NO_x, NO₂, ozone and PM₁₀ upwind of London and Glasgow were made using the meteorological data in a statistical model. These showed falls in NO_x and increases in ozone for London, while a fall in NO₂ was the largest percentage change for Glasgow. Other changes were small. With these background estimates, annual-average concentrations of NO_x, NO₂, ozone and PM₁₀ were estimated within the two urban areas. For London, results averaged over a number of sites showed a fall in NO_x and a rise in ozone, but only small changes in NO₂ and PM₁₀. For Glasgow, the changes in all four chemical species were small. Large-scale background ozone values from a global chemical transport model are also presented. These show a decrease in background ozone due to climate change. To assess the net impact of both large scale and local processes will require models which treat all relevant scales.     

The effect of variability in industrial emissions on ozone formation in Houston, Texas

Ambient observations have indicated that high concentrations of ozone observed in the Houston/Galveston area are associated with plumes of highly reactive hydrocarbons, mixed with NO_x, from industrial facilities. Ambient observations and industrial process data, such as mass flow rates for industrial flares, indicate that the VOCs associated with these industrial emissions can have significant temporal variability. To characterize the effect of this variability in emissions on ozone formation in Houston, data were collected on the temporal variability of industrial emissions or emission surrogates (e.g., mass flow rates to flares). The observed emissions variability was then used to construct regionwide emission inventories with variable industrial emissions, and the impacts of the variability on ozone formation were examined for two types of meteorological conditions, both of which lead to high ozone concentrations in Houston. The air quality simulations indicate that variability in industrial emissions has the potential to cause increases and decreases of 10–52 ppb (13–316%), or more, in ozone concentration. The largest of these differences are restricted to regions of 10–20 km², but the variability also has the potential to increase regionwide maxima in ozone concentrations by up to 12 ppb.     

Air mass characteristics in the vicinity oF Barrow,Alaska, 9–19 March 1983

The synoptic conditions over the Alaskan Arctic during the Arctic Gas and Aerosol Sampling Program (AGASP) of March 1983 are described. Air mass characteristics are pictured in terms of meteorological parameters, condensation nuclei, ozone and CO₂ concentrations, aerosol size and number distributions, and aerosol scattering coefficients, as measured at the Barrow Geophysical Monitoring for Climatic Change (GMCC) baseline station and by aircraft Latitude-altitude cross sections of meteorological and aerosol parameters indicated both strong vertical and horizontal variability within the Arctic air mass. Aerosol concentrations aloft were usually higher than those measured at the ground and peak-to-peak variations are greater aloft than at the surface, showing that the stable Arctic boundary layer reduces mixing from aloft to the surface. Thus, surface measurements cannot be extrapolated to higher levels in a straightforward manner. Horizontal variability in the haze, as determined by the aircraft, was found to be abrupt and was not generally due to the presence of strong meteorological fronts. During 9–19 March 1983, at least four different air mass types were present in the Barrow region, each of which was characterized by distinct meteorological, aerosol and trace gas characteristics.     

Long-range potential source contributions of episodic aerosol events to PM10 profile of a megacity

This paper evaluates possible long-range source contributions to the PM₁₀ profile of Istanbul, Turkey. A novel method for classifying PM₁₀ episodic events resulting from long-range transport, as opposed to local ones, was implemented. Hourly PM₁₀ mass concentrations from ten stations distributed throughout Istanbul during the year 2008 were used for this purpose. Hourly backward trajectories for the arrival of air masses to the center of Istanbul for the year 2008 were calculated using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model. Significant episodes from these backward trajectories were selected and employed in Potential Source Contribution Function (PSCF) analysis to estimate the possible contribution of long-range PM₁₀ transport (LRPMT) to observed PM₁₀ concentrations. The PSCF results showed significant seasonal variations. Based on the results obtained, PM₁₀ concentrations observed in Istanbul during summer and autumn are not heavily affected by LRPMT. Mediterranean countries, especially those of the central part of northern Africa (northern Algeria and Libya) are the most significant potential PM₁₀ contributors to Istanbul's atmosphere during springtime. During winter, Balkan countries, including the Aegean part of Turkey, Greece, Bulgaria, Serbia, and Croatia, as well as northern Italy, eastern France, southern Germany, Austria and the eastern part of Russia, were the most important LRPMT source regions for high PSCF values.     

Meteorologically adjusted trends of daily maximum ozone concentrations in Taipei,Taiwan

The meteorological conditions exert large impacts on ozone concentrations, and may mask the long-term trends in ozone concentrations resulting from precursor emissions. Estimation of long-term trends of ozone concentrations due to the changes in precursor emissions is important for corresponding control strategy. Multiple linear regression (method I), multilayer perceptron (MLP) neural network (method II) and Komogorov-Zurbenko (KZ) filter method plus MLP methodology (method III), are used to estimate the meteorologically adjusted long-term trends of daily maximum ozone concentrations by removing the masking effects of meteorological conditions in this study. The daily maximum ozone concentrations and relative meteorological variables were extracted from six air-monitoring stations in Taipei area from 1994 to 2001. The data collected during 1994–2000 period were used as modeling set and utilized to estimate the meteorologically adjusted trends, and the data of 2001 were used as the validation data. The meteorologically adjusted trends of ozone for these three methods were calculated and compared. The results show that both MLP and KZ filter +MLP models are more suitable than multiple linear regression for estimating the long-term trends of ozone in Taipei, Taiwan. The long-term linear trends of meteorologically adjusted ozone concentrations due to the precursor emissions show an increase trend at all stations, and the percent changes per year range from 1.0% to 2.25% during the modeling period in Taipei area.     

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.     

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.