Daily Maximum Ozone Concentrations Research Articles

Long-term changes of ozone and traffic in Bilbao

It is well known that ozone levels are the result of the interaction among emissions of VOC's and NO x , on the one hand, and meteorological effects on the other hand. In this work, using the low-pass KZ filter developed by Kolmogorov and Zurbenko, the original time series consisting of the logarithm of daily maximum ozone concentrations measured at three locations in the Bilbao area, are splitted into long-term, seasonal and short-term effects. Next, meteorological effects are moderated or removed from filtered ozone series using multiple linear regression. The long-term evolution of ozone forming capability due to changes in precursor emissions can be obtained applying the KZ filter to the residuals of this regression. The present work is an application of the widely used and well known KZ filter technique and focuses on analyzing the joint evolution of the long-term components of ozone time series on the one hand, and mean traffic in the Bilbao area (Spain) on the other hand during years 1993, 1994, 1995 and 1996. To that end, regression analysis between the long-term fractions of ozone and traffic has been performed. The results show that long-term changes of the mean traffic flow are responsible for the long-term changes in ozone forming capability due to changes in precursor emissions of the area. Long-term trend of daily mean traffic can explain between 81% and 99.6% of the total variance of long-term ozone changes at the three locations of Bilbao studied.

Evaluating the performance of regional-scale photochemical modeling systems: Part II—ozone predictions

In this paper, the concept of scale analysis is applied to evaluate ozone predictions from two regional-scale air quality models. To this end, seasonal time series of observations and predictions from the RAMS3b/UAM-V and MM5/MAQSIP (SMRAQ) modeling systems for ozone were spectrally decomposed into fluctuations operating on the intra-day, diurnal, synoptic and longer-term time scales. Traditional model evaluation statistics are also presented to illustrate how the scale analysis approach can help improve our understanding of the models’ performance. The results indicate that UAM-V underestimates the total variance (energy) of the ozone time series when compared with observations, but shows a higher mean value than the observations. On the other hand, MAQSIP is able to better reproduce the average energy and mean concentration of the observations. However, both modeling systems do not capture the amount of variability present on the intra-day time scale primarily due to the grid resolution used in the models. For both modeling systems, the correlations between the predictions and observations are insignificant for the intra-day component, high for the diurnal component because of the inherent diurnal cycle but low for the amplitude of the diurnal component, and highest for the synoptic and baseline components. This better model performance on longer time scales suggests that current regional-scale models are most skillful in characterizing average patterns over extended periods, rather than in predicting concentrations at specific locations, during 1–2 day episodic events. In addition, we discuss the implications of these results to using the model-predicted daily maximum ozone concentrations in the regulatory framework in light of the uncertainties introduced by the models’ poor performance on the intra-day and diurnal time scales.

Association between ozone and hospitalization for acute respiratory diseases in children less than 2 years of age.

To clarify the health effects of ozone exposure in young children, the authors studied the association between air pollution and hospital admissions for acute respiratory problems in children less than 2 years of age during the 15-year period from 1980 to 1994 in Toronto, Canada. The daily time series of admissions was adjusted for the influences of day of the week, season, and weather. A 35% (95% confidence interval: 19%, 52%) increase in the daily hospitalization rate for respiratory problems was associated with a 5-day moving average of the daily 1-hour maximum ozone concentration of 45 parts per billion, the May-August average value. The ozone effect persisted after adjustment for other ambient air pollutants or weather variables. Ozone was not associated with hospital admissions during the September-April period. Ambient ozone levels in the summertime should be considered a risk factor for respiratory problems in children less than 2 years of age.

Eastern North American transport climatology during high- and low-ozone days

A synoptic scale transport climatology during days with high and low ozone concentrations was established for five summers from 1991 to 1995 over eastern North America. The airmass transport patterns were estimated from source impact regions derived from forward airmass histories. Daily maximum ozone concentrations were used to define locally and regionally high- (90th percentile) and low- (10th percentile) ozone days. Examination of transport during locally high-ozone days revealed that there is poor transport in the central part of the domain, i.e. from Tennessee to northern Indiana, and in the South from Texas to South Carolina due to stagnating or recirculating air masses. However, high ozone concentrations over the western and northern sections of the domain occurred during strong and persistent southerly and westerly winds, respectively. In addition, on average, high ozone concentration surrounding the central part of the domain were associated with transport from this region. These results support the notion that ozone exceedances in the central and Southeastern US are predominately “homegrown” while the western and northern section of the domain are also influenced by regional transport. In contrast, on low-ozone days, the transport was predominantly from outside (e.g., Canada and the Gulf of Mexico) into the Eastern US. The transport conditions during regionally high-ozone days were characterized by slow meandering transport over Kentucky, Tennessee, and West Virginia, with a strong clockwise transport around this region of stagnation.

On performing long-term predictions of ozone using the SOMS model

This study examined the potential of using the Simplified Ozone Modeling System (SOMS) (Venkatram et al., 1994. Atmospheric Environment 28, 3665–3678) to generate long-term ozone predictions that may be used to complement the results from more complex air quality models for creating control strategies and establishing long-term trends. A sensitivity study was performed using SOMS to study the application of a model, which is an exponential function of temperature, to estimate the intra-annual biogenic VOC concentration at the receptor in a 1-year run (i.e. 1988). The predictions were made for a core urban site in Baltimore, Maryland. After the sensitivity analyses was completed, the daily maximum ozone concentration (DMOC) was predicted for a 3-year (1987–1989) period for the Baltimore site. The results of the 3-year model prediction were compared with observations.

Acute effects of low levels of ambient ozone on peak expiratory flow rate in a cohort of Australian children

We enrolled a cohort of primary schoolchildren with a history of wheeze (n = 148) in an 11-month longitudinal study to examine the relationship between ambient ozone concentrations and peak expiratory flow rate.Enrolled children recorded peak expiratory flow rates (PEFR) twice daily. We obtained air pollution, meteorological and pollen data. In all, 125 children remained in the final analysis.We found a significant negative association between daily mean deviation in PEFR and same-day mean daytime ozone concentration (beta-coefficient = 0.88; P = 0.04) after adjusting for co-pollutants, time trend, meteorological variables, pollen count and ALTERNARIA: count. The association was stronger in a subgroup of children with bronchial hyperreactivity and a doctor diagnosis of asthma (beta-coefficient = -2.61; P = 0.001). There was no significant association between PEFR and same-day daily daytime maximum ozone concentration. We also demonstrated a dose-response relationship with mean daytime ozone concentration.Moderate levels of ambient ozone have an adverse health effect on children with a history of wheezing, and this effect is larger in children with bronchial hyperreactivity and a doctor diagnosis of asthma.

Acute effects of low levels of ambient ozone on peak expiratory flow rate in a cohort of Australian children

We enrolled a cohort of primary schoolchildren with a history of wheeze (n = 148) in an 11-month longitudinal study to examine the relationship between ambient ozone concentrations and peak expiratory flow rate. Enrolled children recorded peak expiratory flow rates (PEFR) twice daily. We obtained air pollution, meteorological and pollen data. In all, 125 children remained in the final analysis. We found a significant negative association between daily mean deviation in PEFR and same-day mean daytime ozone concentration (beta-coefficient = 0.88; P = 0.04) after adjusting for co-pollutants, time trend, meteorological variables, pollen count and ALTERNARIA: count. The association was stronger in a subgroup of children with bronchial hyperreactivity and a doctor diagnosis of asthma (beta-coefficient = -2.61; P = 0.001). There was no significant association between PEFR and same-day daily daytime maximum ozone concentration. We also demonstrated a dose-response relationship with mean daytime ozone concentration. Moderate levels of ambient ozone have an adverse health effect on children with a history of wheezing, and this effect is larger in children with bronchial hyperreactivity and a doctor diagnosis of asthma.

Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations

In an effort to forecast daily maximum ozone concentrations, many researchers have developed daily ozone forecasting models. However, this continuing worldwide environmental problem suggests the need for more accurate models. Development of these models is difficult because the meteorological variables and photochemical reactions involved in ozone formation are complex. In this study, a neural network model for forecasting daily maximum ozone levels is developed and compared with two conventional statistical models, regression and Box–Jenkins ARIMA. The results show that the neural network model is superior to the regression and Box–Jenkins ARIMA models we tested.

Measuring regional trends in ozone

We model maximum daily ozone concentration at a number of sites in Ontario in terms of weather classes, temperature, season and a moving average error term. In an effort to detect a regional trend in the remaining residuals, we develop a method related to principal components which obtains the linear combination of sites with greatest autocorrelation. We apply this method to data from sites in Southern Ontario and conclude that there was a regional trend in ozone during the period 1980–1992. A similar treatment does not find a general trend in temperature data but does reveal a widening gap in temperature between northern and southern sites.

SMOGSTOP: a model for forecasting maximum daily ozone concentration in Belgium

Every summer, ground level ozone concentrations rise in Belgium and cause episodes of photochemical summer smog. This phenomenon is the cause of well recognised public health distress, especially for people suffering from respiratory diseases. To warn groups of sensitive people against forthcoming smog episodes, VITO (the Flemish Institute for Technological Research) and VMM (the Flemish Environmental Agency) have joined forces to create an ozone pollution forecasting model, called SMOGSTOP (Statistical Model Of Groundlevel Short Term Ozone Pollution). SMOGSTOP is used by Belgian government agencies to issue ozone reports and warnings in the media (TV, radio, internet, etc.). Ozone pollution levels, as well as concentrations of other air pollutants, are monitored in Belgium by the telemetric air quality measuring networks of the three Belgian regions: Flanders, Wallonia and Brussels. The major meteorological variables, such as the windvector, temperature, pressure, humidity and precipitation, are also monitored by the same networks. The historical time series of those variables, generated by the networks, are the source of input data for SMOGSTOP. Photochemical ozone pollution is the result of complex non-linear interactions between atmospheric pollutants and meteorology. As a consequence, it is extremely difficult to determine relationships between source emissions (ozone precursors) and ambient pollutant concentrations (ozone). To deal with this complexity, SMOGSTOP was constructed as an empirical model, applying a VITO tailor-made methodology called stratified pattern matching, to link meteorological and precursor information into ozone forecasts. In this paper, an overview of the process of ozone formation in Belgium is given, followed by the definition of the explanatory variables which will be used in the model. Then the methodology behind the model is reported and finally the results of the forecasting efforts in the period of 1.5.1995 till 31.8.1995 are presented.

Meteorologically adjusted trends in UK daily maximum surface ozone concentrations

A methodology to meteorologically adjust daily UK surface ozone data is presented which reveals the impact of longer-term variations in precursor emissions more clearly. Based on this approach a general site-dependant decline in meteorologically adjusted summer daily maximum ozone concentrations has occurred between 1994 and 1998 and is between 0.7 and 2.3 ppb yr −1.

Forecasting Daily Maximum Ozone Concentrations in the Athens Basin

In the work ozone data from the Liossion monitoring station of the Athens/PERPA network are analysed. Data cover the months May to September for the period 1987–93. Four statistical models, three multiple regression and one ARIMA (0,1,2), for the prediction of the daily maximum 1-hour ozone concentrations are developed. All models together, with a persistence forecast, are evaluated and compared with the 1993's data, not used in the models development. Validation statistics were used to assess the relative accuracy of models. Analysis, concerning the models' ability to forecast real ozone episodes, was also carried out. Two of the three regression models provide the most accurate forecasts. The ARIMA model had the worst performance, even lower than the persistence one. The forecast skill of a bivariate wind speed and persistence based regression model for ozone episode days was found to be quite satisfactory, with a detection rate of 73% and 60% for O3 >180 μg m-3 and O3 >200 μg m-3, respectively.

Effect of ambient ozone exposure on lung function in farm workers.

Effects of ozone exposure on outdoor farm workers in the Fraser Valley of British Columbia, Canada, were investigated. Fifty-eight workers underwent spirometry daily before and after each 8- to 14-h workday from June 23 to August 26, 1993. The mean daily maximum (1 h) ambient ozone concentration was 40 ppb (range: 13 to 84 ppb). Concentrations of acid aerosols and fine particulates, potential confounders of ozone effects, were very low. In individual regressions of evening FEV1 and FVC on maximum daily ozone concentration, 47 of 53 workers with valid data (46 of 53 for FVC) had negative slopes. The average slopes (weighted by the inverse SE of the regression coefficients) were -3.3 and -4.7 ml for FEV1 and FVC, respectively, for each ppb increase in ozone (p < 0.001). Following correction for an individual's mean lung function level, date, and temperature, regression of either the afternoon or the daily change (afternoon-morning) corrected for the morning measurement of FEV1 and FVC on ozone showed similar magnitudes of effect. These associations were still apparent on the following morning, suggesting a persistent ozone effect. These results indicate that exposure of a population of outdoor workers to ambient ozone concentrations below 85 ppb is associated with decreased lung function over the day, which persists to the following day.

Boundary layer structure and photochemical pollution in the Harz Mountains—An observational study

Results from a field campaign that has been performed in summer 1993 to study photochemical pollution in the Harz Mountains, Germany, are presented. During a five-day, fair-weather period, a steady increase of the daily maximum ozone concentration up to values around 100 ppb was observed in the Harz region. The results of ozone measurements at two surface stations (404 m a.s.l. and 1142 m a.s.l., respectively) are discussed with respect to both the transport and dispersion conditions during the period and the local structure of the atmospheric boundary layer. Remarkable similarities in the time series of the ozone mixing ratio at the two places have been found which indicate some kind of quasi-homogeneity even over complex terrain. The trace gas concentrations at the top of Mt. Brocken, the highest summit of the Harz Mountains, are shown to be strongly influenced by vertical transports due to convection (at daytime) and subsidence of inversion layers (at nighttime).

A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area

Prediction of ambient ozone concentrations in urban areas would allow evaluation of such factors as compliance and noncompliance with EPA requirements. Though ozone prediction models exist, there is still a need for more accurate models. Development of these models is difficult because the meteorological variables and photochemical reactions involved in ozone formation are complex. In this study, we developed a neural network model for forecasting daily maximum ozone levels. We then compared the neural network's performance with those of two traditional statistical models, regression, and Box-Jenkins ARIMA. The neural network model for forecasting daily maximum ozone levels is different from the two statistical models because it employs a pattern recognition approach. Such an approach does not require specification of the structural form of the model. The results show that the neural network model is superior to the regression and Box-Jenkins ARIMA models we tested.

Issues Regarding the Ozone Air Quality Standard and the Design Value

Abstract Two problems exist in the form and the compliance test of the present National Ambient Air Quality Standard (NAAQS) for ozone. One is the use of the number of exceedances in the form of the standard, which generates confusion and unnecessary complexity when the form is translated to the design value. The other is the requirement of a zero percent chance of violation in the compliance test, which makes the NAAQS considerably more stringent than generally assumed. There are also two sample-size problems in the estimation procedure for the design value. One is the upward creeping of the (n+l)th highest value in n years as n increases from one in the table look-up approach. The other is the infinite-sample-size assumption instead of the number of high-ozone season days per year for the daily maximum ozone concentrations in the distribution fitting approach. Both problems lead to an exaggeration of the design value. The above problems can be removed in a revised NAAQS by (1) using a statistic that is identical to the design value itself in the form of the standard, (2) defining the design value as an n-year mean of, say, the annual mth highest values rather than the xth highest value in n years, and (3) using a simple compliance test like the t test that compares the design value with the level of the standard, taking into account the year-to-year fluctuation of the annual mth highest values. When the design value of an area is close to the level of the standard, the test provides a natural “too close to call” interval, which adjusts itself with the fluctuation of the annual mth highest values, so that as the fluctuation increases, the ability to assign the compliance status of the area decreases. The inclusion of a “too close to call” interval or category in the standard is critical to reduce the tendency toward ozone attainment flip-flops in areas approaching attainment and to assure that the ozone NAAQS is not more or less stringent than it appears.

Synoptic-Scale Meteorological Variability and Surface Ozone Concentrations in Vancouver, British Columbia

The Lower Fraser Valley of British Columbia is currently experiencing rapid population growth and episodically suffers elevated oxidant concentrations, the frequency of which is linked to meteorological conditions on the synoptic scale. This study is a first step toward developing and validating a methodology for “declimatizing” air quality data so that postulated effects of changing emissions patterns can be addressed. Principal component analysis of gridded fields at three atmospheric levels (sea level–reduced surface pressure, 850-mb height, and 500-mb height) yields four principal components (or modes of the atmospheric circulation) that account for over 83% of geophysical dataset variance. Daily component scores from these components are used as independent parameters in a region equation of the daily maximum ozone concentrations at a site (Rocky Point Park) in Vancouver over five summers (1984–88, inclusive). The coefficients in this equation are used to construct another algorithm that is used to predict maximum daily ozone concentrations at this site during the summers of 1989–92 on the basis of synoptic-scale meteorology. The algorithm correctly predicts the low frequency of ozone episodes in the July 1989–July 1992 period but cannot account for the reduction in daily maximum ozone concentrations on nonexceedance days at Rocky Point Park over this period. The implications of these findings are that during the summers of 1989–92 meteorological conditions on the synoptic scale were not conducive to the occurrence of ozone exceedances but that the reduction in average daily maximum ozone concentrations cannot be accounted for on the basis of synoptic-scale meteorological variability as parameterized by the component scores.

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 statist...

Ozone in the urban southeastern United States

Ozone measurements (daily maximum values) from the Aerometric Information Retrieval System database are analyzed for selected sites, during 1980 to 1988, in southeastern USA. Frequency distributions, for most sites during most years, show a typical bell-shaped curve with the higher frequency around the yearly daily maximum ozone mean of about 100 to about 110 μg m −3 (50–55 ppbv). Abnormal years in ozone concentration may skew the distribution as the mean shifts. A correlation of daily maximum ozone concentrations above 140 μg m −3 (70 ppbv) between sites shows a division between the sites in the northern protion of the region and those in the southern portion of the region. Variations in ozone levels are well correlated over distances of several hundred kilometers, suggesting that high values are associated with synoptic scale episodes. An ozone exposure analysis also shows higher ozone exposures (250–300 ppm days) in the northerly sites as compared to the southerly sites (150–170 ppm days).

AN ENHANCED SYNOPTIC CLIMATOLOGY OF OZONE USING A SEQUENCING TECHNIQUE

A synoptic classification scheme is derived to examine basic associations between surface ozone pollution and the atmospheric circulation. Nine weather types are related to the daily maximum ozone concentration in Pittsburgh, Pennsylvania, for the years 1978–1987. A sequencing technique is developed to extract the maximum utility from the classification scheme. An analysis of the sequences of synoptic weather types highlights additional spatial and temporal information, such as air mass origins, system speed, and seasonal variations. Low concentrations of ozone are experienced in winter during lake-effect and cyclonic storms, which move in rapidly from the north-west, bringing cold, cloudy, windy conditions with precipitation. High concentrations occur during summer in slow-moving anticyclones, with southwesterly transport and warm, sunny conditions that are favorable for photochemical formation of ozone. The study demonstrates that the use of a sequencing technique in conjunction with a synoptic classifi...