A statistical model for FEV1 response to arbitrary dynamic ozone exposure conditions

Lung function response to inhaled ozone at ambient air pollution levels is known to be a function of ozone concentration, exposure duration, and minute ventilation. Most data-driven exposure-response models address exposures under static condition (i.e., with a constant ozone concentration and exercise pattern). Such models are simplifications, as both ambient ozone concentrations and normal human activity patterns change with time. The purpose of this study was to develop a dynamic model of response with the advantages of a statistical model (a relatively simple structure with few parameters). A previously proposed mechanistic model for changes in specific airways resistance was adapted to describe the percent change in forced expiratory volume in one second (FEV1). This model was then reduced using the fit to three existing exposure-response data sets as criterion. The resulting model consists of a single linear differential equation together with an algebraic logistic equation. Under restricted static conditions the model reduces to a logistic model presented earlier by the authors.     

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.     

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton,Alberta, Canada

Abstract

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.     

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.     

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).     

Effects of air pollution on lung function and symptoms of asthma, rhinitis and eczema in primary school children

Health effects of ambient air pollution were studied in three groups of schoolchildren living in areas (suburban, urban and urban-traffic) with different air pollution levels in Eski?ehir, Turkey. This study involved 1,880 students aged between 9 and 13 years from 16 public primary schools. This two-season study was conducted from January 2008 through March 2009. Symptoms of asthma, rhinitis and eczema were determined by the International Study of Asthma and Allergies in Childhood questionnaire in 2008. Two lung function tests were performed by each child for summer and winter seasons with simultaneous ambient air measurements of ozone (O₃), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) by passive sampling. Effects of air pollution on impaired lung function and symptoms in schoolchildren were estimated by multivariate logistic regression analyses. Girls with impaired lung function (only for the summer season evaluation) were more observed in suburban and urban areas when compared to urban-traffic area ([odds ratio (OR)?=?1.49; 95 % confidence interval (CI) 1.04–2.14] and [OR?=?1.69 (95 % CI 1.06–2.71)] for suburban vs. urban-traffic and urban vs. urban-traffic, respectively). Significant association between ambient ozone concentrations and impaired lung function (for an increase of 10 μg m^?3) was found only for girls for the summer season evaluation [OR?=?1.11 (95 % CI 1.03–1.19)]. No association was found for boys and for the winter season evaluation. No association was found between any of the measured air pollutants and symptoms of current wheeze, current rhinoconjunctivitis and current itchy rash. The results of this study showed that increasing ozone concentrations may cause a sub-acute impairment in lung function of school aged children.     

The relation between ozone,NOx and hydrocarbons in urban and polluted rural environments

Research over the past ten years has created a more detailed and coherent view of the relation between O₃ and its major anthropogenic precursors, volatile organic compounds (VOC) and oxides of nitrogen (NO_x). This article presents a review of insights derived from photochemical models and field measurements. The ozone–precursor relationship can be understood in terms of a fundamental split into a NO_x-senstive and VOC-sensitive (or NO_x-saturated) chemical regimes. These regimes are associated with the chemistry of odd hydrogen radicals and appear in different forms in studies of urbanized regions, power plant plumes and the remote troposphere. Factors that affect the split into NO_x-sensitive and VOC-sensitive chemistry include: VOC/NO_x ratios, VOC reactivity, biogenic hydrocarbons, photochemical aging, and rates of meteorological dispersion. Analyses of ozone–NO_x–VOC sensitivity from 3D photochemical models show a consistent pattern, but predictions for the impact of reduced NO_x and VOC in indivdual locations are often very uncertain. This uncertainty can be identified by comparing predictions from different model scenarios that reflect uncertainties in meteorology, anthropogenic and biogenic emissions. Several observation-based approaches have been proposed that seek to evaluate ozone–NO_x–VOC sensitivity directly from ambient measurements (including ambient VOC, reactive nitrogen, and peroxides). Observation-based approaches have also been used to evaluate emission rates, ozone production efficiency, and removal rates of chemically active species. Use of these methods in combination with models can significantly reduce the uncertainty associated with model predictions.     

Weekday vs. Weekend Ambient Ozone Concentrations: Discussion and Hypotheses with Focus on Northern California

Abstract

Since the early 1970s, researchers and data analysts have reported differences between weekday and weekend ozone concentrations, with higher ozone concentrations occurring on Sundays in some locations. At that time, the phenomenon was referred to as the “Sunday effect.” In the late 1980s, additional papers focused on weekday/weekend differences in air quality in the South Coast (Los Angeles) Air Basin.

Analyses of ozone concentrations measured at a number of locations in northern California reveal that average ozone concentrations are frequently higher on weekends than on weekdays. Violations of the California 0.09 ppm 1-hour air quality standard for ozone also occur in disproportionately greater frequency on weekends. We hypothesize that this phenomenon is based largely on the differences between weekday and weekend emission patterns. We believe that the observed differences may provide information regarding which pollutant reduction strategy, NO_x or ROG control, may be more effective in reducing ambient ozone concentrations. For the northern California region, the presence of higher weekend ozone concentrations suggests the need for ROG control is greater than for NO_x control. If both NO_x and ROG are to be controlled, it is important to understand the interdependence of the two pollutants in forming ozone. With the current uncertainty and debate regarding official vehicular emission inventories, this phenomenon emphasizes the importance of using observation-based data to examine ambient pollution and emission relationships. This natural experiment of varying emissions provides an interesting test case for sophisticated air pollution model performance and evaluation.

Using a Bay Area emission inventory and an estimate of its change from weekday to weekend, combined with a generic Empirical Kinetic Modeling Approach (EKMA) diagram, we demonstrate the weekend effect. In addition, changes in the Bay Area emission inventory from 1980 to 1990, when combined with the EKMA diagram, also show why the weekend effect is more evident in the 1990s.

It is our hypothesis that the presence of the weekend effect, positive or negative, combined with changes in emission changes, provides a simple clue to whether an area is NO_xor ROG limited with respect to ozone formation.     

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NO_x) emissions and the larger resulting from controlling of the less certain mobile NO_x emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.     

Comparison of a diurnal vs steady-state ozone exposure profile on growth and yield of oilseed rape (Brassica napus L.) in open-top chambers in the Yangtze Delta, China

Most available exposure-response relationships for assessing crop loss due to elevated ozone (O₃) have been established using data from chamber and open-top chamber experiments, using a simulated constant O₃ concentration exposure (square wave), which is not consistent with the diurnal variation of O₃ concentration that occurs in nature. We investigated the response of oilseed rape (Brassica napus L.) to O₃ as affected by two exposure regimes: one with a diurnal variation (CF100D) and another with a constant concentration (CF100). Although the two exposure regimes have the same mean O₃ concentration and accumulated O₃ concentration above 40 ppb (AOT40), our results show that O₃ at CF100D reduced biomass and number of pods/plant more than O₃ at CF100. Both O₃ exposures resulted in larger seed weights/100 pods compared to CF. Numbers of seeds/100 pods were reduced by CF100, while numbers of seeds/100 pods in the CF100D chambers were comparable to those in CF. Our results suggest that chamber experiments that use a constant O₃ exposure may underestimate O₃ effects on biomass and yields.     

The impact of an 8 h ozone air quality standard on ROG and NOx controls in Southern California

The new National Ambient Air Quality Standard for ozone in the US uses 8 h averaging for the concentration. Based on the 1993 ambient data for Southern California, 8 h averaging has a moderate tendency to move the location of the peak ozone concentration east of the location of the peak 1 h ozone concentration. Reducing the area-wide peak 8 h ozone concentration to 80 ppb would require an effective reduction of the area-wide peak 1 h ozone concentration to around 90 ppb. The Urban Airshed Model with improved numerical solvers, meteorological input based on a mesoscale model and an adjusted emissions inventory was used to study the effect of reactive organic gases (ROG) and NO_x controls on daily-maximum and peak 8 h ozone concentrations under the 26–28 August 1987 ozone episodic conditions in Southern California. The NO_x disbenefit remains prominent for the case of 8 h ozone concentration but is somewhat less prominent, especially when areal ozone exposure is considered, than the case for 1 h ozone concentration. The role of two indicators – O₃/NO_y and H₂O₂/HNO₃ – for NO_x- and ROG-sensitivity for 1 and 8 h ozone concentrations were also studied. In general, the indicator trends are consistent with model predictions, but the discriminating power of the indicators is rather limited.     

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

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

A comparison of indices that describe the relationship between exposure to ozone and reduction in the yield of agricultural crops

The objective of this study is to compare the use of several indices of exposure in describing the relationship between O₃ and reduction in agricultural crop yield. No attempt has been made to determine which exposure-response models best fit the data sets examined. Hourly mean O₃ concentration data, based on two-three measurements per hour, were used to develop indices of exposure from soybean and winter wheat experiments conducted in open-top chambers at the Boyce Thompson Institute, Ithaca, New York NCLAN field site. The comparative efficacy of cumulative indices (i.e. number of occurrences equal to or above specific hourly mean concentrations, sum of all hourly mean concentrations equal to or above a selected level, and the weighted sum of all hourly mean concentrations) and means calculated over an experimental period to describe the relationship between exposure to O₃ and reductions in the yield of agricultural crops was evaluated. None of the exposure indices consistently provided a best fit with the Weibull and linear models tested. The selection of the model appears to be important in determining the indices that best describe the relationship between exposure and response. The focus of selecting a model should be on fitting the data points as well as on adequately describing biological responses. The investigator should be careful to couple the model with data points derived from indices relevant to the length of exposure. While we have used a small number of data sets, our analysis indicates that exposure indices that weight peak concentrations differently than lower concentrations of an exposure regime can be used in the development of exposure-response functions. Because such indices may have merit from a regulatory perspective, we recommend that additional data sets be used in further analyses to explore the biological rationale for various indices of exposure and their use in exposure-response functions.     

Temporal and Spatial Distributions of Ozone in Atlanta: Regulatory and Epidemiologic Implications

ABSTRACT

Relationships between ambient levels of selected air pollutants and pediatric asthma exacerbation in Atlanta were studied retrospectively. As a part of this study, temporal and spatial distributions of ambient ozone concentrations in the 20-county Atlanta metropolitan area during the summers of 1993, 1994, and 1995 were assessed. A universal kriging procedure was used for spatial interpolation of aerometric monitoring station data. In this paper, the temporal and spatial distributions of ozone are described, and regulatory and epidemiologic implications are discussed. For the study period, the Atlanta ozone nonattainment area based on the 1-h, exceedance-based standard of 0.12 ppm is estimated to expand—from 56% of the Atlanta MSA by area and 71% by population to 88% by area and 96% by population—under the new 8-h, concentration-based standard of 0.08 ppm. Regarding asthma exacerbation, a 4% increase in pediatric asthma rate per 20-ppb increase in ambient ozone concentration was observed (p-value = 0.001), with ambient ozone level representing a general indicator of air quality due to its correlations with other pollutants. The use of spatial ozone estimates in the epidemiologic analysis demonstrates the need for control of demographic covariates in spatiotem poral assessments of associations of ambient air pollutant concentrations with health outcome.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Short-Term Effects of Gaseous Pollutants on Cause-Specific Mortality in Wuhan,China

Abstract

In Asia, limited studies have been published on the association between daily mortality and gaseous pollutants of nitrogen dioxide (NO₂), ozone (O₃), and sulfur dioxide (SO₂). Our previous studies in Wuhan, China, demonstrated long-term air pollution effects. However, no study has been conducted to determine mortality effects of air pollution in this region. This study was to determine the acute mortality effects of the gaseous pollutants in Wuhan, a city with 7.5 million permanent residents during the period from 2000 to 2004. There are approximately 4.5 million residents in Wuhan who live in the city’s core area of 201 km², where air pollution levels are highest, and pollution ranges are wider than the majority of the cities in the published literature. We used the generalized additive model to analyze pollution, mortality, and covariate data. We found consistent NO₂effects on mortality with the strongest effects on the same day. Every 10-μg/m³increase in NO₂daily concentration on the same day was associated with an increase in nonaccidental (1.43%; 95% confidence interval [CI]: 0.87–1.99%), cardiovascular (1.65%; 95% CI: 0.87–2.45%), stroke (1.49%; 95% CI: 0.56–2.43%), cardiac (1.77%; 95% CI: 0.44–3.12%), respiratory (2.23%; 95% CI: 0.52–3.96%), and cardiopulmonary mortality (1.60%; 95% CI: 0.85– 2.35%). These effects were stronger among the elderly than among the young. Formal examination of exposure-response curves suggests no-threshold linear relationships between daily mortality and NO₂, where the NO₂concentrations ranged from 19.2 to 127.4 μg/m³. SO₂and O₃were not associated with daily mortality. The exposure-response relationships demonstrated heterogeneity, with some curves showing nonlinear relationships for SO₂and O₃. We conclude that there is consistent evidence of acute effects of NO₂on mortality and suggest that a no-threshold linear relationship exists between NO₂and mortality.     

Predicting ozone levels

This paper presents a statistical model that is capable of predicting ozone levels from precursor concentrations and meteorological conditions during daylight hours in the Shuaiba Industrial Area (SIA) of Kuwait. The model has been developed from ambient air quality data that was recorded for one year starting from December 1994 using an air pollution mobile monitoring station. The functional relationship between ozone level and the various independent variables has been determined by using a stepwise multiple regression modelling procedure. The model contains two terms that describe the dependence of ozone on nitrogen oxides (NOx) and nonmethane hydrocarbon precursor concentrations, and other terms that relate to wind direction, wind speed, sulphur dioxide (SO₂) and solar energy. In the model, the levels of the precursors are inversely related to ozone concentration, whereas SO₂ concentration, wind speed and solar radiation are positively correlated. Typically, 63 % of the variation in ozone levels can be explained by the levels of NOx. The model is shown to be statistically significant and model predictions and experimental observations are shown to be consistent. A detailed analysis of the ozone-temperature relationship is also presented; at temperatures less than 27 °C there is a positive correlation between temperature and ozone concentration whereas at temperatures greater than 27 °C a negative correlation is seen. This is the first time a non-monotonic relationship between ozone levels and temperature has been reported and discussed.     

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.