Vertical Ozone Profile in the Lower Troposphere over Chicago

ABSTRACT

A 15-year (1981-95) climatology for the diurnal maximum ozone concentration (DMOC) was developed using 1-hr average ozone concentrations in the Baltimore-Washington area, which was made up of four regions: Baltimore, Washington, non-urban Maryland, and non-urban northern Virginia. The DMOC time series for each of these regions were divided into four terms representing different behavioral time scales: the long-term mean; the mean in-tra-annual perturbation; the interannual perturbation; and the synoptic perturbation. The urban regions had smaller values of the long-term mean ozone, but the annual range was larger. The values of the interannual perturbation were largest in the summer, when ozone production is significant, and smallest in the late winter and early spring. The interannual perturbation in the summer in the four regions consistently had positive departures in 1983, 1988, and 1991, and it had negative departures in 1981, 1984, 1985, 1989, 1990, and 1992. Summers with large positive interannual departures experienced a large number of ozone exceedances (i.e., relative to the 1-hr National Ambient Air Quality Standard of 125 parts per billion [ppb]), and summers with large negative departures experienced few or no exceedances. About 50% of the exceedances had concentrations ranging in value from 125-135 ppb, and about 75% had concentrations from 125-145 ppb.     

An enhanced ozone forecasting model using air mass trajectory analysis

An enhanced ozone forecasting model using nonlinear regression and an air mass trajectory parameter has been developed and field tested. The model performed significantly better in predicting daily maximum 1-h ozone concentrations during a five-year model calibration period (1993–1997) than did a previously reported regression model. This was particularly true on the 28 “high ozone” days ([O₃]>120 ppb) during the period, for which the mean absolute error (MAE) improved from 21.7 to 12.1 ppb. On the 77 days meteorologically conducive to high ozone, the MAE improved from 12.2 to 9.1 ppb, and for all 580 calibration days the MAE improved from 9.5 to 8.35 ppb. The model was field-tested during the 1998 ozone season, and performed about as expected. Using actual meteorological data as input for the ozone predictions, the MAE for the season was 11.0 ppb. For the daily ozone forecasts, which used meteorological forecast data as input, the MAE was 13.4 ppb. The high ozone days were all anticipated by the ozone forecasters when the model was used for next day forecasts.     

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.     

Ozone measurements in South Carolina using passive samplers

Passive samplers with two different collection substrates were used to obtain an average ozone concentration for 1 month during the summer of 2002 for each South Carolina county. One sampler contained a filter coated with indigo carmine, whose color fades when exposed to ozone. The fading was measured by reflectance spectroscopy. The other sampler contained filters that were coated with nitrite, which is oxidized to nitrate when exposed to ozone. The nitrate was measured by ion chromatography. Calibration curves were developed for the two methods by comparing color fading from indigo carmine and nitrate ion concentration from the nitrite filter with ambient ozone concentration measured by a co-located reference continuous UV ozone analyzer. These curves were used to calculate integrated ozone concentrations for samplers distributed across South Carolina. Using the indigo carmine method, the average ozone concentrations ranged from 21 to 64 ppb (average = 46 +/- 7.9 ppb, n = 58) across the 46 counties in the state during one summer month of 2002. Concentrations for the same time period from the nitrite-coated filters ranged from 23 to 62 ppb (average = 41 +/- 8.1 ppb, n = 58). Also for the same time period, the 23 continuous UV photometric ozone monitors operated by the South Carolina Department of Health and Environmental Control at sites within 10 miles of some of the passive monitors showed ozone concentrations ranging from 28 to 50 ppb (average = 39 +/- 6.3 ppb, n = 22).     

Fuzzy system models combined with nonlinear regression for daily ground-level ozone predictions

This study focuses on applying a Takagi–Sugeno fuzzy system and a nonlinear regression (NLR) model for ozone predictions in six Kentucky metropolitan areas. The fuzzy “c-means” clustering technique coupled with an optimal output predefuzzification approach (least square method) was used to train the Takagi–Sugeno fuzzy system. The fuzzy system was tuned by specifying the number of rules and the fuzziness factor. The NLR models were based in part on a previously reported, trajectory-based hybrid NLR model that has been used for years for forecasting ground-level ozone in Louisville, KY. The NLR models were each composed of an interactive nonlinear term and several linear terms. Using a common meteorological parameter set as input variables, the NLR models and the Takagi–Sugeno fuzzy systems model exhibited equivalent forecasting performance on test data from 2004. For all 2004 ozone season forecasts for the six metropolitan areas, the mean absolute error was 8.1 ppb for the NLR model and 8.0 ppb for the Takagi–Sugeno fuzzy model. When a nonlinear term (which was part of the NLR model) was included in the fuzzy model, the combined NLR–fuzzy model had slightly better performance than the original NLR model. For all 2004 metropolitan area forecasts, the mean absolute error of the NLR–fuzzy model forecasts was 7.7 ppb. These small differences may be statistically significant, but for practical purposes the performance of the fuzzy models was equivalent to that of the NLR models.     

Air Pollution Control and Waste Management in a New World

Abstract

A research site for atmospheric chemistry and air pollution measurements was established at Pinnacle State Park in Addison, NY, in 1995. This paper presents an overview of the site characteristics and measurement program, as well as monthly average concentrations for many of the trace gas and aerosol pollutants over the full measurement period. Monthly averaged ozone concentrations range from values as low as 15 parts per billion (ppb) during cold-season months, to values approaching 50 ppb during some spring and summer months. Sulfur dioxide (SO₂), oxides of nitrogen (NO_x), and reactive odd nitrogen (NO_y) all show distinct seasonal variation, with summertime monthly averages as low as 1–3 ppb, and wintertime monthly averages from 6–12 ppb. The variation in carbon monoxide (CO) is much smaller, with minimums of approximately 150 ppb and maximums only rarely exceeding 250 ppb. Data for three hydrocarbon species propane, benzene, and isoprene—are presented. Propane and benzene show higher monthly averaged concentrations in the winter and lower values in the summer, with values ranging over a factor of 4–5. Isoprene, on the other hand has much higher values during the summer season, sometimes a factor of 10 or more greater than concentrations measured in the winter. Monthly averaged plots for fine particulate matter (PM_2.5) beginning in 1999 show a robust summer maximum and winter minimum, and roughly a factor of two difference between the two. An empirical measure of ozone production using the correlation of hour-averaged ozone and NO_y data illustrates relatively robust ozone production during some, but not all, summertime months over the time period. Also, an analysis of the frequency distribution of the hours of maximum ozone concentration shows a strong mid-afternoon peak, as expected, but also a prominent secondary maximum centered around midnight. The secondary peak is interpreted as ozone transported from ozone-producing areas to the west, including Buffalo, Cleveland, Pittsburgh, and the Ohio Valley. Finally, SO₂ concentrations as a function of wind direction clearly indicate maximum impacts when the winds are out of the south (Pittsburgh and Philadelphia), with a secondary peak when the winds are from the north-northeast, consistent with the locations of major SO₂ emission sources in the region.     

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.     

Preliminary assessment of risk of ozone impacts to maize (Zea mays) in southern Africa

Surface ozone concentrations in southern Africa exceed air quality guidelines set to protect agricultural crops. This paper addresses a knowledge gap by performing a preliminary assessment of potential ozone impacts on vegetation in southern African. Maize (Zea mays L.) is the receptor of interest in the main maize producing countries, i.e. South Africa, Zambia and Zimbabwe. Surface ozone concentrations are estimated for the growing season (October to April) using photochemical modelling. Hourly mean modelled ozone concentrations ranged between 19.7 and 31.2 ppb, while maximums range between 28.9 and 61.9 ppb, and are near 30 ppb over South Africa and Zambia, while in Zimbabwe, they exceed 40 ppb and translate into monthly AOT40 values of over 3,000 ppb h in five of the seven months of the growing season. This study suggests that surface ozone may pose a threat to agricultural production in southern African, particularly in Zimbabwe.     

Ozone Measurements in South Carolina Using Passive Samplers

Abstract

Passive samplers with two different collection substrates were used to obtain an average ozone concentration for 1 month during the summer of 2002 for each South Carolina county. One sampler contained a filter coated with indigo carmine, whose color fades when exposed to ozone. The fading was measured by reflectance spectroscopy. The other sampler contained filters that were coated with nitrite, which is oxidized to nitrate when exposed to ozone. The nitrate was measured by ion chromatography.

Calibration curves were developed for the two methods by comparing color fading from indigo carmine and nitrate ion concentration from the nitrite filter with ambient ozone concentration measured by a co-located reference continuous UV ozone analyzer. These curves were used to calculate integrated ozone concentrations for samplers distributed across South Carolina.

Using the indigo carmine method, the average ozone concentrations ranged from 21 to 64 ppb (average = 46 ± 7.9 ppb, n = 58) across the 46 counties in the state during one summer month of 2002. Concentrations for the same time period from the nitrite-coated filters ranged from 23 to 62 ppb (average = 41 ± 8.1 ppb, n = 58). Also for the same time period, the 23 continuous UV photometric ozone monitors operated by the South Carolina Department of Health and Environmental Control at sites within 10 miles of some of the passive monitors showed ozone concentrations ranging from 28 to 50 ppb (average = 39 ± 6.3 ppb, n = 22).     

Peroxyacetyl nitrate and peroxypropionyl nitrate in Porto Alegre,Brazil

For 41 days between 25 May 1996 and 27 March 1997, peroxyacetyl nitrate (PAN) and peroxypropionyl nitrate (PPN) have been measured by electron capture gas chromatography at Santa Rita near Porto Alegre, RS, Brazil, where light-duty vehicles used either ethanol or a gasoline–MTBE blend. Daily maximum concentrations ranged from 0.19 to 6.67 ppb for PAN and 0.06 to 0.72 ppb for PPN. Linear regression of maximum PPN vs. maximum PAN yielded a slope of 0.105±0.004 (R²=0.974). Diurnal variations of ambient PAN often followed those of ozone with respect to time of day but not with respect to amplitude. This was reflected in the large relative standard deviations associated with the study-averaged PAN/ozone concentration ratio, 0.037±0.105 (ppb/ppb, n=789) and the maximum PAN/maximum ozone concentration ratio, 0.028±0.015 (ppb/ppb, range 0.005–0.078, n=41). On several days PAN accounted for large fractions of the total ambient NO_x in the late morning and afternoon hours, e.g., PAN/NO_x⩽0.58 and PAN/(NO_x–NO) ⩽0.76 on 27 March 1997. The amount of PAN lost by thermal decomposition (TPAN) was comparable in magnitude to that present in ambient air. The ratios TPAN/(PAN+TPAN) were up to 0.53, 0.67 and 0.64 during the warm afternoons of 25, 26 and 27 March 1997, respectively. The highest calculated value of TPAN was 5.6 ppb on 27 March 1997. On that day the 24 h-averaged value of TPAN (1.01 ppb) was nearly the same as that of PAN (1.09 ppb). Using computer kinetic modeling (SAPRC 97 chemical mechanism) and sensitivity analysis of VOC incremental reactivity, we ranked VOC present in Porto Alegre ambient air for their importance as precursors to PAN and to PPN. Using as input data the averages of VOC concentrations measured in downtown Porto Alegre during the ca. 1 yr period March 1996–April 1997, we calculated that the most important precursors to PAN and PPN were the SAPRC 97 model species ARO2 (which includes the aromatics xylenes, trimethylbenzenes, ethyltoluenes, etc.), which accounted for ca. 17% of the total PAN and total PPN formation potentials. Overall, the results indicate a major role for aromatics and alkenes and a minor role for acetaldehyde and ethanol as precursors to peroxyacyl nitrates in the Porto Alegre urban area.     

Impact of downward-mixing ozone on surface ozone accumulation in southern Taiwan

The ozone that initially presents in the previous day's afternoon mixing layer can remain in the nighttime atmosphere and then be carried over to the next morning. Finally, this ozone can be brought to the ground by downward mixing as mixing depth increases during the daytime, thereby increasing surface ozone concentrations. Variation of ozone concentration during each of these periods is investigated in this work. First, ozone concentrations existing in the daily early morning atmosphere at the altitude range of the daily maximum mixing depth (residual ozone concentrations) were measured using tethered ozonesondes on 52 experimental days during 2004-2005 in southern Taiwan. Daily downward-mixing ozone concentrations were calculated by a box model coupling the measured daily residual ozone concentrations and daily mixing depth variations. The ozone concentrations upwind in the previous day's afternoon mixing layer were estimated by the combination of back air trajectory analysis and known previous day's surface ozone distributions. Additionally, the relationship between daily downward-mixing ozone concentration and daily photochemically produced ozone concentration was examined. The latter was calculated by removing the former from daily surface maximum ozone concentration. The measured daily residual ozone concentrations distributed at 12-74 parts per billion (ppb) with an average of 42 +/- 17 ppb are well correlated with the previous upwind ozone concentration (R2 = 0.54-0.65). Approximately 60% of the previous upwind ozone was estimated to be carried over to the next morning and became the observed residual ozone. The daily downward-mixing ozone contributes 48 +/- 18% of the daily surface maximum ozone concentration, indicating that the downward-mixing ozone is as important as daily photochemically produced ozone to daily surface maximum ozone accumulation. The daily downward-mixing ozone is poorly correlated with the daily photochemically produced ozone and contributes significantly to the daily variation of surface maximum ozone concentrations (R2 = 0.19). However, the contribution of downward-mixing ozone to daily ozone variation is not included in most existing statistical models developed for predicting daily ozone variation. Finally, daily surface maximum ozone concentration is positively correlated with daily afternoon mixing depth, attributable to the downward-mixing ozone.     

Determination of ozone in outdoor and indoor environments using nitrite-impregnated passive samplers followed by ion chromatography

An improved ion chromatographic (IC) method has been developed for the separation of nitrate in filter extracts in the presence of high concentrations of nitrite. This analytical method was successfully used for an indirect measurement of ozone (O3) in outdoor and indoor air, following its collection using a nitrite-impregnated passive sampler. The limit of detection and the limit of quantification, using the modified IC method, were 6 microg l(-1) (3sigma) and 20 microg l(-1) (10sigma), respectively. Improved detection limits and low baseline noise were obtained with the use of eluent generator and high-capacity ion exchange column. The optimized method was used for assessing O3 concentration in both indoor and outdoor environments of 28 child care centers (CCCs) located in different parts of Singapore. The O3 concentrations ranged from 0.1 to 11.95 parts per billion (ppb) in indoor and from 3.2 to 21.7 ppb in outdoor environments during the study period. It was found that, among the CCCs investigated in this study, air-conditioned CCCs and those located in close proximity to traffic emissions had significantly lower O3 concentrations indoors.     

Sampled Monte Carlo uncertainty analysis for photochemical grid models

This study reports on the development and testing of a method of quantifying the uncertainties in concentration predictions by a complex photochemical grid model (PGM), using a modification of the basic Monte Carlo method (MCM). The computationally intensive aspects of applying a full MCM to hundreds of PGM inputs and model parameters is replaced by a highly restricted sampling approach that exploits the spatial persistence found in predicted concentration fields. The sampling approach to the MCM is being explored as an efficient approach to assess the uncertainty in the differences in predicted maximum ozone concentration between base case and control scenarios. The MCM is applied to several dozen surface cells, with the goal of sampling the spatial pattern of uncertainty in the PGM-predicted differences in surface ozone concentration fields between a pair of base and control scenarios. The uncertainty in model inputs and parameters is simulated using several types of stochastic models. These stochastic models are driven using Latin hypercube sampling (LHS) to generate a non-redundant ensemble of alternative model inputs. Preliminary testing of the sampled MCM approach was conducted using the UAM-IV PGM on the New York ozone attainment modeling domain for the 6–8 July 1988 ozone episode. One hundred alternative concentration estimates were generated for a base scenario and for control scenarios representing 50%, 10% and 5% reduction of NO_x emissions. The upper and lower bounds of the concentration difference ensemble that define a 95% confidence range were spatially interpolated from 27 monitoring sites to the full (surface) modeling domain, using the field of zero uncertainty (ZU) concentration differences. For the 50% NO_x control scenario, predicted increases in peak ozone concentration smaller than 20 ppb were generally not significant from zero. By contrast, predicted decreases in peak ozone greater than 10 ppb were usually significant. For a control scenario with a small 5% NO_x reduction, predicted concentration differences and confidence intervals were much smaller, but predicted changes in peak ozone were significant at a number of sample cells.     

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.     

Measurements of peroxyacyl nitrates (PANS) in Mexico City: implications for megacity air quality impacts on regional scales

Peroxyacyl nitrates (PANs) were measured using gas chromatography with electron capture detection (GC/ECD) in north central Mexico City during February–March of 1997. Peroxyacetyl nitrate (PAN) was observed to exceed 30 ppb during five days of the study, with peroxypropionyl nitrate (PPN) and peroxybutryl nitrate (PBN) reaching 6 and 1 ppb maximum, respectively. Levels of total PANs typically exceeded 10 ppb during the period of measurement and showed a very strong diurnal variation with PANs maximum during the early afternoon and falling to less than 0.1 ppb during the evening hours. These levels of PANs are the highest reported values in North America (and the world) for an urban center, since levels of approximately 30 ppb were reported during the late 1970s in the Los Angeles area (South Coast Air Basin, Tuazon et al., 1978). Hydrocarbon measurements indicate that the levels of olefins, specifically butenes are significant in Mexico City. A time series taken of source indicator hydrocarbons taken before and during a Mexican National Holiday with reduced automobile traffic clearly show that mobile sources of butenes are as important as liquefied petroleum gas. Observations of 10–40 ppb C methyl-t-butyl ether (MTBE) are consistent with MTBE/gasoline fuel usage as a source of isobutene and formaldehyde. Both these reactive species can lead to increased oxidant and PAN formation. The strong diurnal profiles of PANs are consistent with regional clearing of the Mexico City air basin on a daily basis. Estimates are given using a simple box model calculation for a number of key primary and secondary pollutant emissions from this megacity on an annual basis. These calculations indicate that megacities can be important sources of both primary and secondary pollutants, and that PANs produced in megacity environments are likely to contribute strongly to regional scale ozone and aerosol productions during long range transport.     

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 %.     

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), one mixed (alternating winds) and one only anticyclonic (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 %.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Modelling critical levels of ozone for the forested area of austria modifications of the aot40 concept

GOAL, SCOPE AND BACKGROUND: Ozone is the most important air pollutant in Europe for forest ecosystems and the increase in the last decades is significant. The ozone impact on forests can be calculated and mapped based on the provisional European Critical Level (AOT40 = accumulated exposure over a threshold of 40 ppb, 10,000 ppb x h for 6 months of one growing season calculated for 24 h day(-1)). For Norway spruce, the Austrian main tree species, the ozone risk was assessed in a basis approach and because the calculations do not reflect the health status of forests in Austria, the AOT40 concept was developed. METHODS: Three approaches were outlined and maps were generated for Norway spruce forests covering the entire area of Austria. The 1st approach modifies the AOT40 due to the assumption that forests have adapted to the pre-industrial levels of ozone, which increase with altitude (AOTalt). The 2nd approach modifies the AOT40 according to the ozone concentration in the sub-stomata cavity. This approach is based on such factors as light intensity and water vapour saturation deficit, which affect stomatal uptake (AOTsto). The 3rd approach combines both approaches and includes the hemeroby. The pre-industrial ozone level approach was applied for autochthonous ('natural') forest areas, the ozone-uptake approach for non-autochthonous ('altered') forest areas. RESULTS AND DISCUSSION: The provisional Critical Level (AOT40) was established to allow a uniform assessment of the ozone risk for forested areas in Europe. In Austria, where ozone risk is assessed with utmost accuracy due to the dense grid of monitoring plots of the Forest Inventory and because the continuously collected data from more than 100 air quality measuring stations, an exceedance up to the five fold of the Critical Level was found. The result could lead to a yield loss of up to 30-40% and to a severe deterioration in the forest health status. However, the data of the Austrian Forest Inventory and the Austrian Forest Damage Monitoring System do not reflect such an ozone impact. Therefore, various approaches were outlined including the tolerance and avoidance mechanisms of Norway spruce against ozone impact. Taking into consideration the adaptation of forests to the pre-industrial background level of ozone, the AOT40 exceedances are markedly reduced (1st approach). Taking into account the stomatal uptake of ozone, unrealistic high amounts of exceedances up to 10,000 ppb x h were found. The modelled risk does not correspond with the health status and the wood increment of the Austrian forests (2nd approach). Consolidating the forgoing two approaches, a final map including the hemeroby was generated. It became clear that the less natural ('altered') forested regions are highly polluted. This means, that more than half of the spruce forests are endangered by ozone impact and AOT40 values of up to 30,000 ppb x h occur (3rd approach). CONCLUSIONS: The approaches revealed that a plausible result concerning the ozone impact on spruce forests in Austria could only be reached by combining pre-industrial ozone levels, ozone flux into the spruce needles and the hemeroby of forests.