Systematic development of an artificial neural network model for real-time prediction of ground-level ozone in Edmonton, Alberta, Canada

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O3) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O3 events. The models are used to determine the meteorological conditions and precursors that most affect O3 concentrations. O3 time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O3 prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.     

Parameter Evaluation and Model Validation of Ozone Exposure Assessment Using Harvard Southern California Chronic Ozone Exposure Study Data

Abstract

To examine factors influencing long‐term ozone (O₃) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O₃ concentrations, as well as related housing and other questionnaire information collected in the one‐year‐long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O₃ concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance‐covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best‐linear unbiased prediction technique.The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O₃ concentration, central ambient O₃ concentration, outdoor O₃ concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O₃ concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O₃ concentrations plus questionnaire variables, central and indoor O₃ concentrations plus questionnaire variables, indoor O₃ concentrations plus questionnaire variables, central O₃ concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O₃ for children and offer insights into how to reliably and cost‐effectively predict personal O₃ exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost‐effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.     

Meteorological Factors of Ozone Predictability at Houston,Texas

ABSTRACT

Several ozone modeling approaches were investigated to determine if uncertainties in the meteorological data would be sufficiently large to limit the application of physically realistic ozone (O₃) forecast models. Three diagnostic schemes were evaluated for the period of May through September 1997 for Houston, TX. Correlations between measured daily maximum and model calculated O₃ air concentrations were found to be 0.70 using a linear regression model, 0.65 using a non-advective box model, and 0.49 using a three-dimensional (3-D) transport and dispersion model. Although the regression model had the highest correlation, it showed substantial underestimates of the highest concentrations. The box model results were the most similar to the regression model and did not show as much underestimation. The more complex 3-D modeling approach yielded the worst results, likely resulting from O₃ maxima that were driven by local factors rather than by the transport of pollutants from outside of the Houston domain. The highest O₃ concentrations at Houston were associated with light winds and meandering trajectories. A comparison of the gridded meteorological data used by the 3-D model to the observations showed that the wind direction and speed values at Houston differed most on those days on which the O₃ underestima-tions were the greatest. These periods also tended to correspond with poor precipitation and temperature estimates. It is concluded that better results are not just obtained through additional modeling complexity, but there needs to be a comparable increase in the accuracy of the meteorological data.     

Long term changes in nitrogen oxides and volatile organic compounds in Toronto and the challenges facing local ozone control

Ground level ozone represents a significant air quality concern in Toronto, Canada, where the national 65 ppb 8-h standard is repeatedly exceeded during the summer. Here we present an analysis of nitrogen dioxide (NO₂), ozone (O₃), and volatile organic compound (VOC) data from federal and provincial governmental monitoring sites from 2000 to 2007. We show that summertime VOC reactivity and ambient concentrations of NO₂ have decreased over this period of time by up to 40% across Toronto and the surrounding region. This has not resulted in significant summertime ozone reductions, and in some urban areas, it appears to be increasing. We discuss the competing effects of decreased ozone titration leading to an increase in O₃, and decreased local ozone production, both caused by significant decreases in NO_x concentrations. In addition, by using local meteorological data, we show that annual variability in summer ozone correlates strongly with maximum daily temperatures, and we explore the effect of atmospheric transport from the southwest which has a significant influence on early morning levels before local production begins. A mathematical model of instantaneous ozone production is presented which suggests that, given the observed decreases in NO_x and VOC reactivity, we would not expect a significant change in local ozone production under photochemically relevant conditions. These results are discussed in the context of Toronto's recent commitment to cutting local smog-causing pollutants by 20% by 2012.     

Prediction of the Vertical Profile of Ozone Based on Ground-Level Ozone Observations and Cloud Cover

Abstract

A number of statistical techniques have been used to develop models to predict high-elevation ozone (O₃) concentrations for each discrete hour of day as a function of elevation based on ground-level O₃ observations. The analyses evaluated the effect of exclusion/inclusion of cloud cover as a variable. It was found that a simple model, using the current maximum ground-level O₃ concentration and no effect of cloud cover provided a reasonable prediction of the vertical profile of O₃, based on data analyzed from O₃ sites located in North Carolina and Tennessee. The simple model provided an approach that estimates the concentration of O₃ as a function of elevation (up to 1800 m) based on the statistical results with a ±13.5 ppb prediction error, an R² of 0.56, and an index of agreement, d ₁, of 0.66. The inclusion of cloud cover resulted in a slight improvement in the model over the simple regression model. The developed models, which consist of two matrices of 24 equations (one for each hour of day for clear to partly cloudy conditions and one for cloudy conditions), can be used to estimate the vertical O₃ profile based on the inputs of the current day’s 1-hr maximum ground-level O₃ concentration and the level of cloud cover.     

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

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

Filtration of Radioactive Aerosols By Glass Fibers

Abstract

An ozone (O₃) exposure assessment study was conducted in Toronto, Ontario, Canada during the winter and summer of 1992. A new passive O₃ sampler developed by Harvard was used to measure indoor, outdoor, and personal O₃ concentrations. Measurements were taken weekly and daily during the winter and summer, respectively. Indoor samples were collected at a total of 50 homes and workplaces of study participants. Outdoor O₃ concentrations were measured both at home sites using the passive sampler and at 20 ambient monitoring sites with continuous monitors. Personal O₃ measurements were collected from 123 participants, who also completed detailed time-activity diaries. A total of 2,274 O₃ samples were collected. In addition, weekly air exchange rates of homes were measured.

This study demonstrates the performance of our O₃ sampler for exposure assessment. The data obtained are further used to examine the relationships between personal, indoor (home and workplace), and outdoor O₃ concentrations, and to investigate outdoor and indoor spatial variations in O₃ concentrations. Based on home outdoor and indoor, workplace, and ambient O₃ concentrations measured at the Ontario Ministry of the Environment (MOE) sites, the traditional microenvironmental model predicts 72% of the variability in measured personal exposures. An alternative personal O₃ exposure model based on outdoor measurements and time-activity information is able to predict the mean personal exposures in a large population, with the highest R² value of 0.41.     

Differences between Weekday and Weekend Air Pollutant Levels in Atlanta; Baltimore; Chicago; Dallas–Fort Worth; Denver; Houston; New York; Phoenix; Washington,DC; and Surrounding Areas

Abstract

We evaluated day-of-week differences in mean concentrations of ozone (O₃) precursors (nitric oxide [NO], nitrogen oxides [NO_x], carbon moNO_xide [CO], and volatile organic compounds [VOCs]) at monitoring sites in 23 states comprising seven geographic focus areas over the period 1998– 2003. Data for VOC measurements were available for six metropolitan areas in five regions. We used Wednesdays to represent weekdays and Sundays to represent weekends; we also analyzed Saturdays. At many sites, NO, NO_x, and CO mean concentrations decreased at all individual hours from 6:00 a.m. to 3:00 p.m. on Sundays compared with corresponding Wednesday means. Statistically significant (p < 0.01) weekend decreases in ambient concentrations were observed for 92% of NO_x sites, 89% of CO sites, and 23% of VOC sites. Nine-hour (6:00 a.m. to 3:00 p.m.) mean concentrations of NO, NO_x, CO, and VOCs declined by 65, 49, 28, and 19%, respectively, from Wednesdays to Sundays (median site responses). Despite the large reductions in ambient NO_x and moderate reductions in ambient CO and VOC concentrations on weekends, ozone and particulate matter (PM) nitrate did not exhibit large changes from week-days to weekends. The median differences between Wednesday and Sunday mean ozone concentrations at all monitoring sites ranged from 3% higher on Sundays for peak 8-hr concentrations determined from all monitoring days to 3.8% lower on Sundays for peak 1-hr concentrations on extreme-ozone days. Eighty-three percent of the sites did not show statistically significant differences between Wednesday and weekend mean concentrations of peak ozone. Statistically significant weekend ozone decreases occurred at 6% of the sites and significant increases occurred at 11% of the sites. Average PM nitrate concentrations were 2.6% lower on Sundays than on Wednesdays. Statistically significant Sunday PM nitrate decreases occurred at one site and significant increases occurred at seven sites.     

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting

Introduction

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O₃) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons.

Methods

Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O₃ concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO₂), and O₃ (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004.

Results and discussion

Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O₃ regimes were temperature, CO and NO₂ concentrations, due to their importance in O₃ chemistry in an urban atmosphere.

Conclusion

In the prediction of O₃ concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.     

Potential Interference Bias in Ozone Standard Compliance Monitoring

Abstract

The U.S. Environmental Protection Agency has established a federal reference method (FRM) for ozone (O₃) and allowed for designation of federal equivalent methods (FEMs). However, the ethylene‐chemiluminescence FRM for O₃ has been replaced by the UV photometric FEM by most state and local monitoring agencies because of its relative ease of operation. Accumulating evidence indicates that the FEM is prone to bias under the hot, humid, and stagnant conditions conducive to high O₃ formation. This bias may lead to overreporting hourly O₃ concentrations by as much as 20–40 ppb. Measurement bias is caused by contamination of the O₃ scrubber, a problem that is not detected by dry air calibration. An adequate wet test has not been codified, although a procedure has been proposed for agency consideration. This paper includes documentation of laboratory tests quantifying specific interferant responses, collocated ambient FRM/FEM monitoring results, and smog chamber comparisons of the FRM and FEMs with alternative scrubber designs. As the numbers of reports on monitor interferences have grown, interested parties have called for agency recognition and correction of these biases.     

Ground level ozone concentrations and its association with NOx and meteorological parameters in Kathmandu valley, Nepal

This paper summarizes the results of a yearlong continuous measurements of gaseous pollutants, NO, NO₂, NO_x and O₃ in the ambient air at Kathmandu valley. Measured concentration of the pollutants in study area is a function of time. NO, NO₂ and O₃ peak occurred in succession in presence of sunlight. At the time of maximum O₃ concentration most of the NO_x are utilized. The diurnal cycle of ground level ozone concentrations, revealed mid-day peak with lower nocturnal concentrations and inverse relationship exists between O₃ and NO_x, which are evidences of photochemical O₃ formation. The observed ground level ozone during monsoon is slight lower than the pre-monsoon value. Further, lack of rainfall and higher temperature, solar radiation in the pre-monsoon have given rise to the gradual build up of ozone and it is lowest during winter. Ground level ozone concentrations measured during bandha (general strike) and weekend are 19% and 13% higher than those measured during weekdays. The most effective ozone abatement strategy for Kathmandu Valley may be control of NO_x emissions.     

DNA damage in Populus tremuloides clones exposed to elevated O3

The effects of elevated concentrations of atmospheric tropospheric ozone (O₃) on DNA damage in five trembling aspen (Populus tremuloides Michx.) clones growing in a free-air enrichment experiment in the presence and absence of elevated concentrations of carbon dioxide (CO₂) were examined. Growing season mean hourly O₃ concentrations were 36.3 and 47.3 ppb for ambient and elevated O₃ plots, respectively. The 4th highest daily maximum 8-h ambient and elevated O₃ concentrations were 79 and 89 ppb, respectively. Elevated CO₂ averaged 524 ppm (+150 ppm) over the growing season. Exposure to O₃ and CO₂ in combination with O₃ increased DNA damage levels above background as measured by the comet assay. Ozone-tolerant clones 271 and 8L showed the highest levels of DNA damage under elevated O₃ compared with ambient air; whereas less tolerant clone 216 and sensitive clones 42E and 259 had comparably lower levels of DNA damage with no significant differences between elevated O₃ and ambient air. Clone 8L was demonstrated to have the highest level of excision DNA repair. In addition, clone 271 had the highest level of oxidative damage as measured by lipid peroxidation. The results suggest that variation in cellular responses to DNA damage between aspen clones may contribute to O₃ tolerance or sensitivity.     

Application of Artificial Neural Networks to Modeling and Prediction of Ambient Ozone Concentrations

ABSTRACT

The deterministic modeling of ambient O₃ concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O₃ concentrations based on a limited number of measured hydrocarbon species, NO_x compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O₃, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O₃ concentrations from measured VOC and NO concentrations. To predict the future concentrations of O₃, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species.

The steady-state model produced an approximation of O₃ data and demonstrated the functional relationship between O₃ and VOC-NO_x concentrations. The dynamic models were able to the adequately predict the O₃ concentration and behavior of VOC-NO_x-O₃ system a number of hourly intervals into the future. For 3 hr into the future, O₃ concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.     

Development of a Speciated,Hourly, and Gridded Air Pollutants Emission Modeling System—A Case Study on the Precursors of Photochemical Smog in the Seoul Metropolitan Area,Korea

ABSTRACT

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO₂) and ozone (O₃) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas.

The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO₂, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO₂ and O₃ concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

Measurement of Ozone Concentrations in Ambient Air Using a Badge-Type Passive Monitor

Abstract

A badge-type passive monitor was used to evaluate the effectiveness of four ozone trapping reagents for measuring O₃ concentrations in the air. These were sodium nitrite (NaNO₂), 3-methyl-2-benzothiazolinone acetone azine (MBTH), p-acetamidophenol (p-ATP), and indigo carmine. Experiments in an exposure chamber showed that only NaNO₂ and MBTH monitors gave sensitive and linear responses over realistic ranges of O₃ concentrations. When tested in ambient air, NaNO₂ and MBTH monitors with a single-layer diffusion barrier overestimated O₃ concentrations by a significant amount. This was largely canceled out in the NaNO₂ monitor by using a multi-layered diffusion barrier to combat wind turbulence effects. However it had almost no effect on the MBTH monitor, and it was found that NO₂ was a source of serious interference. We concluded that using the NaNO₂ monitor with an effective diffusion barrier can measure O₃ in ambient air with an accuracy of ±16%.     

Ambient Ozone Concentration Patterns among Eastern U.S. Urban Areas Using Factor Analysis

Data on dally maximum ozone concentrations measured at ambient air monitoring stations operated by state and local air pollution control agencies in the Eastern United States were analyzed using principal factor analysis. Four orthogonal factors representing O₃ formation potentials were derived using the statistical package SPSS; these factors accounted for over two-thirds of the variations in 1978 summer O₃ levels at 21 urban-oriented stations. The analysis confirmed that O₃ variations are similar among stations within defined geographical areas; this confirmation supports the widely held theory that ambient O₃ formations are reglonwlde. The analysis suggested that trends analysis for determining general progress in improving O₃ air quality should be based on aggregate statistics from clusters of monitors rather than from a single monitoring station within areas associated with the derived factors.     

Field evaluations of newly available “interference-free” monitors for nitrogen dioxide and ozone at near-road and conventional National Ambient Air Quality Standards compliance sites

Long-standing measurement techniques for determining ground-level ozone (O₃) and nitrogen dioxide (NO₂) are known to be biased by interfering compounds that result in overestimates of high O₃ and NO₂ ambient concentrations under conducive conditions. An increasing near-ground O₃ gradient (NGOG) with increasing height above ground level is also known to exist. Both the interference bias and NGOG were investigated by comparing data from a conventional Federal Equivalent Method (FEM) O₃ photometer and an identical monitor upgraded with an “interference-free” nitric oxide O₃ scrubber that alternatively sampled at 2 m and 6.2 m inlet heights above ground level (AGL). Intercomparison was also made between a conventional nitrogen oxide (NO_x) chemiluminescence Federal Reference Method (FRM) monitor and a new “direct-measure” NO₂ NO_x 405 nm photometer at a near-road air quality measurement site. Results indicate that the O₃ monitor with the upgraded scrubber recorded lower regulatory-oriented concentrations than the deployed conventional metal oxide–scrubbed monitor and that O₃ concentrations 6.2 m AGL were higher than concentrations 2.0 m AGL, the nominal nose height of outdoor populations. Also, a new direct-measure NO₂ photometer recorded generally lower NO₂ regulatory-oriented concentrations than the conventional FRM chemiluminescence monitor, reporting lower daily maximum hourly average concentrations than the conventional monitor about 3 of every 5 days.

Implications: Employing bias-prone instruments for measurement of ambient ozone or nitrogen dioxide from inlets at inappropriate heights above ground level may result in collection of positively biased data. This paper discusses tests of new regulatory instruments, recent developments in bias-free ozone and nitrogen dioxide measurement technology, and the presence/extent of a near-ground O₃ gradient (NGOG). Collection of unbiased monitor inlet height–appropriate data is crucial for determining accurate design values and meeting National Ambient Air Quality Standards.     

Growth of soybean at future tropospheric ozone concentrations decreases canopy evapotranspiration and soil water depletion

Tropospheric ozone is increasing in many agricultural regions resulting in decreased stomatal conductance and overall biomass of sensitive crop species. These physiological effects of ozone forecast changes in evapotranspiration and thus in the terrestrial hydrological cycle, particularly in intercontinental interiors. Soybean plots were fumigated with ozone to achieve concentrations above ambient levels over five growing seasons in open-air field conditions. Mean season increases in ozone concentrations ([O₃]) varied between growing seasons from 22 to 37% above background concentrations. The objective of this experiment was to examine the effects of future [O₃] on crop ecosystem energy fluxes and water use. Elevated [O₃] caused decreases in canopy evapotranspiration resulting in decreased water use by as much as 15% in high ozone years and decreased soil water removal. In addition, ozone treatment resulted in increased sensible heat flux in all years indicative of day-time increase in canopy temperature of up to 0.7 °C.     

Contribution of ambient ozone to Scots pine defoliation and reduced growth in the Central European forests: a Lithuanian case study

The study aimed to explore if changes in crown defoliation and stem growth of Scots pines (Pinus sylvestris L.) could be related to changes in ambient ozone (O₃) concentration in central Europe. To meet this objective the study was performed in 3 Lithuanian national parks, close to the ICP integrated monitoring stations from which data on meteorology and pollution were provided. Contribution of peak O₃ concentrations to the integrated impact of acidifying compounds and meteorological parameters on pine stem growth was found to be more significant than its contribution to the integrated impact of acidifying compounds and meteorological parameters on pine defoliation. Findings of the study provide statistical evidence that peak concentrations of ambient O₃ can have a negative impact on pine tree crown defoliation and stem growth reduction under field conditions in central and northeastern Europe where the AOT40 values for forests are commonly below their phytotoxic levels.