Analyses of ozone in urban and rural sites in Málaga (Spain)

Ozone concentrations were measured at two (urban and a rural) sites near the city of Málaga (Spain). The aim of this study was to determine the daily, monthly and seasonal variation patterns of ozone concentrations at both sites and to study the possible regional influences. The daily variations mostly have the usual features with the afternoon maximum and the night minimum being more pronounced in the urban area. The average monthly concentrations throughout the year start to increase in March reaching their maximum values in July for the urban site. However, in the rural area, the monthly variations are smaller reaching their maximum value in June. The hourly evolution of the ozone concentrations in both sampling sites is well defined in spring and summer and not so well defined in autumn and winter. Taking into account the four seasons, the rural concentrations are higher than the urban ones. Summer is the season when there are similar concentrations at both sampling sites. Average hourly summer afternoon ozone for the hours 12:00-20:00 LST exceeded the 110 microg m(-3) European Union guidelines for human health for 8 h ozone exposure at the urban and rural sites.     

An examination of the 6:00 a.m.-9:00 a.m. measurements of ozone precursors in the New York City metropolitan area

In recent years, ambient measurements of hourly ozone precursor concentrations, namely speciated and total nonmethane organic compounds (NMOCs), have become available through the Photochemical Assessment Monitoring Stations (PAMS) program. Prior to this, NMOCs were measured in the central business district using a canister to obtain the 3-hr integrated sample for the 6:00 a.m.-9:00 a.m. period. Such sampling had been carried out annually for nearly a decade at three locations in the New York City metropolitan area. The intent of these measurements, along with measurements of the other ozone precursor, NO(x), was to provide an understanding of ozone formation and the emissions loading and mix in the urban area. The analysis of NMOC and NO(x) measurements shows a downward trend in the case of NMOC. In addition, we compared the canister-based NMOC concentrations with data obtained from the PAMS program for the 6:00 a.m.-9:00 a.m. period. Analysis of the NMOC concentrations reveals poor spatial correlation between the various monitors, reflecting the effect of localized emissions. This suggests that NMOC measurements made at a single location cannot be viewed as representative of the entire region. On the other hand, correlations were found to be higher among the NO(x) monitors, indicating the commonality of emission     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.     

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

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.     

Long-term variation in surface ozone and its precursors in Athens,Greece

INTENTION, GOAL, SCOPE, BACKGROUND: Photochemical pollution is a very complex process involving meteorological, topographic, emission and chemical parameters. The most important chemical mechanisms involved in the atmospheric process have already been identified and studied. However, many unknown parameters still exist because of the large number of participating chemical reactions. OBJECTIVE: The present study investigates the processes involved in the photochemical pollution effect of an urban station located in the greater area of the Athens basin and gives a plausible explanation for the different seasonal ozone development between that station and another rural one. Furthermore, the distribution of the mean monthly surface ozone observed at the urban station during 1987-2001 is examined in order to create a relevant forecasting tool. METHODS: Averaged hourly data of O3 and NOx observations monitored at the above mentioned stations, during 1987-2001, have been used in order to derive the daytime (7:00-15:00) values. Trajectories calculated by using a 2D-trajectory code and meteorological data, during the period 1988-1996, have also been used. RESULTS AND DISCUSSION: At the urban station, the percentage negative trend of NO and NOx data in winter and summer is higher than that in spring and autumn, while the percentage ozone trend is maximum in the summer. On the contrary, the negative surface ozone trend at the rural station exhibits a minimum in summer and a maximum in autumn and winter. The mean seasonal wind-rose for the selected months shows that the northward wind flow dominates during June, the month of the lowest negative ozone trend in the rural station. Finally, the development of the forecasting tool shows that the mean monthly surface ozone data during the period (1987-2001) demonstrates a semi-log distribution. CONCLUSIONS: Air transport effect on the air pollution of the rural station (not blocked by mountains) is deduced as a possible reason for the different seasonal ozone development observed between the rural and the urban station. Finally, the discrepancies between the theoretical probabilities deduced by the model and the empirical ones appear to be very small, and the corresponding correlation coefficient is 0.99. RECOMMENDATION AND OUTLOOK: However, to interpret the aforementioned statistical results about the negative trends in ozone and its precursors, additional parameters can be taken into account. Changes in NOx concentrations, for instance, can result not only from changes in emissions or meteorological conditions. There might also be a contribution through changes in the atmospheric composition. A study of the contribution of changes in atmospheric composition to trends of observed NOx concentrations requires that a series of steps be taken (removal of meteorological influence in the time series, calculation of trends in OH concentrations, etc.).     

Predictive mapping of air pollution involving sparse spatial observations

A limited number of sample points greatly reduces the availability of appropriate spatial interpolation methods. This is a common problem when one attempts to accurately predict air pollution levels across a metropolitan area. Using ground-level ozone concentrations in the Tucson, Arizona, region as an example, this paper discusses the above problem and its solution, which involves the use of linear regression. A large range of temporal variability is used to compensate for sparse spatial observations (i.e. few ozone monitors). Gridded estimates of emissions of ozone precursor chemicals, which are developed, stored, and manipulated within a geographic information system, are the core predictor variables in multiple linear regression models. Cross-validation of the pooled models reveals an overall R2 of 0.90 and approximately 7% error. Composite ozone maps predict that the highest ozone concentrations occur in a monitor-less area on the eastern edge of Tucson. The maps also reveal the need for ozone monitors in industrialized areas and in rural, forested areas.     

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.     

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.     

The Characterization of Ozone and Sulfur Dioxide Air Quality Data for Assessing Possible Vegetation Effects

Since the 1960s, much effort has been devoted to collecting and formatting air quality data. This paper discusses 1) the availability of air quality data for assessing potential biological impacts associated with ozone and sulfur dioxide ambient exposures, 2) examples of how air quality data can be characterized for assessing vegetation effects, and 3) the limitations associated with some exposure parameters used for developing relevant vegetation doseresponse yield reduction models. Data are presented showing that some ozone monitoring sites not continuously affected by local urban sources experience consecutive hourly ozone exposures ≥0.10 ppm in the late evening and early morning hours. These sites experience their maximum ozone concentrations either in the spring or summer months. Sites influenced by local rural sources experience their maximum ozone concentrations during the summer months. It is suggested that further research be performed to identify whether the sensitivity of a target organism at the time of exposure, as well as the pollutant concentration and chemical form that enters into the target organism, is as important in defining effects as air pollutant exposure alone.     

The Characterization of Ozone,Sulfur Dioxide,and Nitrogen Dioxide for Selected Monitoring Sites in the Federal Republic of Germany

Ambient ozone, sulfur dioxide, and nitrogen dioxide data collected at 11 rural gaseous air pollution monitoring stations located throughout the Federal Republic of Germany (FRG) were characterized to provide a basis for investigating the effect these air pollutants may have on forest decline. For any given year, with the exception of the Waldhof site, the ozone monitoring sites did not experience more than 50 occurrences of hourly mean concentrations equal to or above 0.10 ppm. In most cases, the number of occurrences equal to or above 0.10 ppm at the FRG ozone monitoring sites was below the number experienced at a rural forested site located at Whiteface Mountain, New York. Several of the FRG monitoring sites experienced a large number of occurrences of hourly mean ozone concentrations between 0.08 and 0.10 ppm. Hof, Selb, Arzberg, and Waldhof experienced several occurrences of elevated levels of sulfur dioxide concentrations. The nitrogen dioxide 24-h mean concentrations were low for all sites. Because the 24-h mean data may mask the occurrence of a few high concentration events, it is not known if any of the sites that monitored nitrogen dioxide experienced short-term elevated concentrations. To gain further insight into the possible effect of pollutant mixtures on vegetation, future efforts should involve characterizing the timing of multi-pollutant exposures.     

Modeling the influence of biogenic volatile organic compound emissions on ozone concentration during summer season in the Kinki region of Japan

Tropospheric ozone adversely affects human health and vegetation, and biogenic volatile organic compound (BVOC) emission has potential to influence ozone concentration in summer season. In this research, the standard emissions of isoprene and monoterpene from the vegetation of the Kinki region of Japan, estimated from growth chamber experiments, were converted into hourly emissions for July 2002 using the temperature and light intensity data obtained from results of MM5 meteorological model. To investigate the effect of BVOC emissions on ozone production, two ozone simulations for one-month period of July 2002 were carried out. In one simulation, hourly BVOC emissions were included (BIO), while in the other one, BVOC emissions were not considered (NOBIO). The quantitative analyses of the ozone results clearly indicate that the use of spatio-temporally varying BVOC emission improves the prediction of ozone concentration. The hourly differences of monthly-averaged ozone concentrations between BIO and NOBIO had the maximum value of 6 ppb at 1400 JST. The explicit difference appeared in urban area, though the place where the maximum difference occurred changed with time. Overall, BVOC emissions from the forest vegetation strongly affected the ozone generation in the urban area.     

Estimating long-term population exposure to ozone in urban areas of Europe

Tropospheric ozone concentrations regarded as harmful for human health are frequently encountered in Central Europe in summertime. Although ozone formation generally results from precursors transported over long distances, in urban areas local effects, such as reactions due to nearby emission sources, play a major role in determining ozone concentrations. Europe-wide mapping and modeling of population exposure to high ozone concentrations is subject to many uncertainties, because small-scale phenomena in urban areas can significantly change ozone levels from those of the surroundings. Currently the integrated assessment modeling of European ozone control strategies is done utilizing the results of large-scale models intended for estimating the rural background ozone levels. This paper presents an initial study on how much local nitrogen oxide (NOx) concentrations can explain variations between large-scale ozone model results and urban ozone measurements, on one hand, and between urban and nearby rural measurements, on the other. The impact of urban NOx concentrations on ozone levels was derived from chemical equations describing the ozone balance. The study investigated the applicability of the method for improving the accuracy of modeled population exposure, which is needed for efficient control strategy development. The method was tested with NOx and ozone measurements from both urban and rural areas in Switzerland and with the ozone predictions of the large-scale photochemical model currently used in designing Europe-wide control strategies for ground-level ozone. The results suggest that urban NOx levels are a significant explanatory factor in differences between urban and nearby rural ozone concentrations and that the phenomenon could be satisfactorily represented with this kind of method. Further research efforts should comprise testing of the method in more locations and analyzing the performance of more widely applicable ways of deriving the initial parameters.     

An observation-based model for analyzing ozone precursor relationships in the urban atmosphere

An Observation-Based Model (OBM) is described, which uses in-situ atmospheric observations to determine the sensitivity of ozone concentrations in an urban atmosphere to changes in the emissions of ozone precursors (i.e., volatile organic compounds and nitrogen oxides). The model is formulated following the concept of Relative Incremental Reactivity (RIR) developed by Carter and Atkinson. In the OBM, however, observed concentrations rather than emission inventories are used to drive the photochemical simulations and thereby ensure that the calculations are carried out for the proper mix of nitrogen oxides and volatile organic compounds. From these calculations, a series of sensitivity factors, or RIRs, are inferred that can be used to (1) determine whether reducing emissions of nitrogen oxide or emissions of hydrocarbons would be most effective in abating ozone in a given urban area, and (2) identify the most critical subset of hydrocarbons present in an urban atmosphere causing ozone exceedances. Because the OBM is relatively easy and inexpensive to operate and makes use of data that are increasingly available, it can be used to analyze a wide array of ozone episodes and, thus, could prove to be a relatively cost-effective tool for the analysis of ozone precursor relationships in an urban atmosphere. On the other hand, because the OBM is diagnostic rather than prognostic, it cannot be used in a predictive mode to estimate exactly how much emission reduction is needed to reduce ozone concentrations. For this reason, the OBM should be viewed as a complement to, rather than a substitute for, more sophisticated gridded, emission-based models. To illustrate the characteristics of the OBM and to demonstrate its applicability, we first compare the results of the OBM to those obtained from a series of simulations of the Atlanta metropolitan area using the Urban Airshed Model (UAM), a three-dimensional Eulerian grid model. The OBM is then used to analyze a dataset obtained from the 1990 Atlanta Ozone Study, an EPA field sampling program conducted during the summer of 1990. Because of limitations and potential flaws in the 1990 Atlanta dataset, the results of this OBM analysis are largely illustrative rather than definitive. Nevertheless, a few important issues are elucidated by the analysis. These include (1) the importance of accounting for biogenic hydrocarbons produced from urban vegetation; (2) the potential flaw in using early-morning VOC-to-NOx ratios to infer whether ozone production is limited by VOC or NOx; (3) the critical need for high-sensitivity nitrogen oxide measurements to quantify the sub-ppbv concentrations of NO during the afternoon hours; and (4) the need to consider a number of individual ozone episodes in studying an urban atmosphere because of the possibility that the degree of VOC- and NOx-limitation may vary from one episode to another.     

Issues with ozone attainment methodology for Houston, TX

To comply with the federal 8-hr ozone standard, the state of Texas is creating a plan for Houston that strictly follows the U.S. Environmental Protection Agency's (EPA) guidance for demonstrating attainment. EPA's attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houston's ozone violations at monitoring sites are realized as gradual hour-to-hour increases in ozone concentrations, or by large hourly ozone increases that exceed up to 100 parts per billion/hr. Given the time profiles at the violating monitors and those of nearby monitors, these large increases appear to be associated with small parcels of spatially limited plumes of high ozone in a lower background of urban ozone. Some of these high ozone parcels and plumes have been linked to a combination of unique wind conditions and episodic hydrocarbon emission events from the Houston Ship Channel. However, the regulatory air quality model (AQM) does not predict these sharp ozone gradients. Instead, the AQM predicts gradual hourly increases with broad regions of high ozone covering the entire Houston urban core. The AQM model performance can be partly attributed to EPA attainment guidance that prescribes the removal in the baseline model simulation of any episodic hydrocarbon emissions, thereby potentially removing any nontypical causes of ozone exceedances. This paper shows that attainment of all monitors is achieved when days with observed large hourly variability in ozone concentrations are filtered from attainment metrics. Thus, the modeling and observational data support a second unique cause for how ozone is formed in Houston, and the current EPA methodology addresses only one of these two causes.     

Comparison of atmospheric concentrations of currently used pesticides between urban and rural areas during intensive application period in Alsace (France) by using XAD-2® based passive samplers

XAD-2® passive samplers (PAS) have been exposed simultaneously for 14 days on two sites, one rural and one urban, situated in Alsace (East of France) during intensive pesticides application in agriculture (between March and September). PAS have been extracted and analyzed for current-used pesticides and lindane with an analytical method coupling accelerated solvent extraction (ASE), solid-phase microextraction (SPME) and GC/MS/MS. Results show the detection of pesticides is linked to the period of application and spatial and temporal variabilities can be observed with these PAS during the selected sampling period. The spatial and temporal variability is comparable to the one previously observed by comparing data obtained with PAS with data from Hi.-Vol. samplers in an urban area. Sampling rates were calculated for some pesticides and values are comparable to the data already available in the literature. From these sampling rates, concentrations in ng m^?3 of pesticides in PAS have been calculated and are in the same order of magnitude as those obtained with Hi.Vol. sampling during the same period of time.     

GARCH modelling in association with FFT–ARIMA to forecast ozone episodes

In operational forecasting of the surface O₃ by statistical modelling, it is customary to assume the O₃ time series to be generated through a homoskedastic process. In the present work, we’ve taken heteroskedasticity of the O₃ time series explicitly into account and have shown how it resulted in O₃ forecasts with improved forecast confidence intervals. Moreover, it also enabled us to make more accurate probability forecasts of ozone episodes in the urban areas. The study has been conducted on daily maximum O₃ time series for four urban sites of two major European cities, Brussels and London. The sites are: Brussels (Molenbeek) (B1), Brussels (PARL.EUROPE) (B2), London (Brent) (L1) and London (Bloomsbury) (L2). Fast Fourier Transform (FFT) has been used to model the periodicities (annual periodicity is especially distinct) exhibited by the time series. The residuals of “actual data subtracted with their corresponding FFT component” exhibited stationarity and have been modelled using ARIMA (Autoregressive Integrated Moving Average) process. The MAPEs (Mean absolute percentage errors) using FFT–ARIMA for one day ahead 100 out of sample forecasts, were obtained as follows: 20%, 17.8%, 19.7% and 23.6% at the sites B1, B2, L1 and L2. The residuals obtained through FFT–ARIMA have been modelled using GARCH (Generalized Autoregressive Conditional Heteroskedastic) process. The conditional standard deviations obtained using GARCH have been used to estimate the improved forecast confidence intervals and to make probability forecasts of ozone episodes. At the sites B1, B2, L1 and L2, 91.3%, 90%, 70.6% and 53.8% of the times probability forecasts of ozone episodes (for one day ahead 30 out of sample) have correctly been made using GARCH as against 82.6%, 80%, 58.8% and 38.4% without GARCH. The incorporation of GARCH also significantly reduced the no. of false alarms raised by the models.     

Modelling the photochemical pollution over the metropolitan area of Porto Alegre,Brazil

The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models – CAMx and CALGRID – were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.     

Effects of Nighttime Chemistry upon the Transport of Ozone and Ozone Precursors

It has been recognized for several years that ozone in rural areas can exceed the National Ambient Air Quality Standard (NAAQS) for photochemical oxidant whirh was 0.08 ppm for one hour, not to be exceeded more than once per year. During the summer of 1973, the NAAQS was exceeded from 15 to 37% of the time at four rural monitoring sites in Maryland, Pennsylvania, Ohio, and West Virginia.¹ This is a greater violation rate than is found in many urban areas. Dimitriades and Altshuller² have enumerated four possible sources for this rural ozone: (a) transport from urban areas, (b) local photochemical generation from urban ozone precursors, (c) local photochemical generation from precursors of rural origin which may be man-made or natural, and (d) injection of stratospheric ozone into the rural area. This paper considers the chemistry pertinent to the first two of these possible sources of rural ozone, namely the long distance (overnight) transport of ozone and ozone precursors.     

Rural and Urban Ozone Relationships In New York State

High ozone concentrations, often in excess of the national ambient air quality standard for photochemical oxidants, have been measured simultaneously in urban and rural areas of New York State. Average daily rural ozone concentrations were found to correlate well with daily maximum urban ozone concentrations suggesting a common source. Estimations of the quantity of ozone advectively transported into New York State are more than an order of magnitude greater than estimations of the potential photochemical generation of ozone from hydrocarbon emissions within New York State. It is suggested thai the high rural ozone levels are not primarily due to the transport of ozone and ozone precursors from olher urban areas, but are rather due to natural phenomena such as photochemical generation from naturally occurring precursors or transport of ozone from the stratosphere to the troposphere. The effectiveness of a hydrocarbon control strategy for New York State to meet the ambient air quality standard for photochemical oxidants when background levels themselves may be above the standard is questioned.     

The sensitivity of modeled ozone to the temporal distribution of point, area, and mobile source emissions in the eastern United States

Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields used in air quality models (AQMs) generally show less temporal variability than corresponding measurements from continuous emissions monitors (CEM) and field campaigns would imply. If emissions control scenarios to reduce emissions at peak ozone forming hours are to be assessed with AQMs, the effect of emissions' daily variability on modeled ozone must be understood. We analyzed the effects of altering all anthropogenic emissions' temporal distributions by source group on 2002 summer-long simulations of ozone using the Community Multiscale Air Quality Model (CMAQ) v4.5 and the Carbon Bond IV (CBIV) chemical mechanism with 12 km resolution. We find that when mobile source emissions were made constant over the course of a day, 8-h maximum ozone predictions changed by ±7 parts per billion by volume (ppbv) in many urban areas on days when ozone concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation of point sources resulted in ozone changes of +6 and −6 ppbv, but only for small areas near sources. Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone, especially in urban areas at night; results suggest that shifting the emissions of NO_x from day to night, for example in electric powered vehicles recharged at night, could have beneficial impacts on air quality.